Mussels: Anatomy, Habitat and Environmental Impact (Fish, Fishing and Fisheries)

FISH, FISHING AND FISHERIES

MUSSELS: ANATOMY, HABITAT AND ENVIRONMENTAL IMPACT No part of this digital document may be reproduced, stored in a retrieval system or transmitted in any form or by any means. The publisher has taken reasonable care in the preparation of this digital document, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained herein. This digital document is sold with the clear understanding that the publisher is not engaged in rendering legal, medical or any other professional services.

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FISH, FISHING AND FISHERIES

MUSSELS: ANATOMY, HABITAT AND ENVIRONMENTAL IMPACT

LAUREN E. MCGEVIN EDITOR

Nova Science Publishers, Inc. New York

Copyright ©2011 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers‘ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Additional color graphics may be available in the e-book version of this book. LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA Mussels : anatomy, habitat and environmental impact / editor, Lauren E. McGevin. p. cm. Includes index. ISBN 978-1-61122-149-7 (eBook) 1. Mussels. 2. Mussels--Effect of water pollution on. 3. Indicators (Biology) I. McGevin, Lauren E. QL430.6.M876 2010 594'.4--dc22 2010036147

Published by Nova Science Publishers, Inc.  New York

CONTENTS Preface Chapter 1

Chapter 2

Chapter 3

Chapter 4

Chapter 5

ix Inter-Site Differences and Seasonal Patterns of Fatty Acid Profiles in Green-Lipped Mussels Perna Viridis in A Subtropical Eutrophic Harbour and Its Vicinity S. G. Cheung and P. K. S. Shin Environmental Impact of Anthropogenic Activities: The Use of Mussels as a Reliable Tool for Monitoring Marine Pollution Stefanos Dailianis The Experience of the Mussel Sector in Galicia: The Natural, Institutional and Economic Environment Gonzalo Caballero-Miguez, Manuel Varela-Lafuente and Marcos Pérez-Pérez Translational Control of Gene Expression in the Mussel Mytilus Galloprovincialis: The Impact of Cellular Stress on Protein Synthesis, the Ribosomal Stalk and the Protein Kinase CK2 Activity S. Kouyanou-Koutsoukou, D. L. Kalpaxis, S. Pytharopoulou, R. M. Kolaiti, A. Baier and R. Szyszka MAP Kinase Signaling Pathway: A Potential Biomarker of Environmental Pollution in the Mussel Mytilus Galloprovincialis A. Châtel and B. Hamer

Chapter 6

Mussel Glue and Its Prospects in Biotechnology Veronika Hahn and Annett Mikolasch

Chapter 7

Molecular Determinants in Mussels as Biomarkers for Environmental Stress Sutin Kingtong and Tavan Janvilisri

1

43

73

97

129 145

173

vi

Contents

Chapter 8

Integrated Impact Assessment of Mussels Health Jocelyne Hellou and François Gagné

Chapter 9

Ecotoxicological Genetic Studies on the GreenLipped Mussel Perna Viridis in Malaysia C. K. Yap and S.G. Tan

Chapter 10

Environmental Impact to Mussels‘ Metabolism Jordan T. Nechev

Chapter 11

Combining Stable Isotopes and Biochemical Markers to Assess Organic Contamination in Transplanted Mussels Mytilus Galloprovincialis S. Deudero, A. Box, A. Sureda, J. Tintoré and S. Tejada

Chapter 12

Environmental Impact Assessment of Mussels Caught in Mediterranean Sea, Italy Monia Perugini and Pierina Visciano

Chapter 13

Competition for Space and Food Among Blue Mussels Daisuke Kitazawa

Chapter 14

Production and Shelf Life of Mussel Meat Powder Flavor Vanessa Martins da Silva, Kil Jin Park and Míriam Dupas Hubinger

197

221 245

263

285 303

337

Chapter 15

Life Cycle Assessment of Mussel Culture Diego Iribarren María Teresa Moreira and Gumersindo Feijoo

Chapter 16

Mussels as a Tool in Metal Pollution Biomonitoring – Current Status and Perspectives Joanna Przytarska and Adam Sokołowski

379

Sclerochronology – Mussels as Bookkeepers of Aquatic Environment Samuli Helama

395

Chapter 17

Chapter 18

Chapter 19

Marine Biotoxins and Blue Mussel: One of the Most Troublesome Species During Harmful Algal Blooms Paulo Vale Immunotoxicity of Environmental Chemicals in the Pearl Forming Mussel of India- A Review Sajal Ray, Mitali Ray, Sudipta Chakraborty and Suman Mukherjee

357

413

429

Contents Chapter 20

Chapter 21

Anticoagulant and Carbohydrate Induced Interference of Aggregation of Mussel Haemocyte Under Azadirachtin Exposure Suman Mukherjee, Mitali Ray and Sajal Ray The Origin of Populations of Dreissena Polymorpha Near the North-Eastern Boundary of Its Distribution Area I. S. Voroshilova, V. S. Artamonova and V. N. Yakovlev

vii

441

453

Chapter 22

Unionidae Freshwater Mussel Anatomy Diana Badiu, Rafael Luque and Ovidiu Teren

469

Chapter 23

The Cytogenetics of Mytilus Mussels Andrés Martínez-Lage and Ana M. González-Tizón

485

Chapter 24

A New Approach in Biomonitoring Freshwater Ecosystems Based on the Genetic Status of the Bioindicator Dreissena Polymorpha Godila Thomas, Göran I. V. Klobučar, Alfred Seitz and Eva Maria Griebeler

Chapter 25 Index

Mussels: Their Common Enemies and Adaptive Defenses Devapriya Chattopadhyay

495

503 521

PREFACE The common name mussel is used for members of several families of clams or bivalvia mollusca, from saltwater and freshwater habitats. These groups have in common a shell whose outline is elongated and asymmetrical compared with other edible clams, which are often more or less rounded or oval. This book presents current research in the study of mussels and their anatomy, habitat and their environmental impact. Some of the topics discussed herein include the use of mussels as a reliable tool for monitoring marine pollution; mussel glue and its use in biotechnology; environmental impact to mussels' metabolism; the competition for space and food among Blue Mussels; the life cycle assessment of mussel culture; Unionidae freshwater mussel anatomy; and the cytogenics of Mytilus mussels. Chapter 1 - Fatty acid profiles of total particulate matters (TPMs) in water and greenlipped mussels Perna viridis were studied for one year in the eutrophic Victoria Harbour, Hong Kong and its vicinity. Bimonthly sampling of TPMs and P. viridis were conducted at four sites inside the harbour, namely Tsim Sha Tsui (TST), North Point (NP), Kwun Tong (KT) and Central (C) and two references sites outside of the harbour, namely Peng Chau (PC) and Tung Lung Chau (TLC). Levels of saturated fatty acids (SFAs) 16:0 and 18:0 in TPMs, signatures of marine detritus, bacteria and nano-zooplankton, were higher at reference sites than at harbour sites. In contrast, levels of monounsaturated fatty acids (MUFAs) 18:1n9 and 18:1n7 and polyunsaturated fatty acid (PUFA) 18:2n6 were higher in Victoria Harbour than at reference sites. These suggested that the waters in Victoria Harbour contained relatively high amounts of marine fungi and bacteria, reflecting the poor water quality within the harbour proper. The gonad and soma of mussels from the six sites exhibited similar inter-site differences and seasonal changes in fatty acid profiles. The fatty acid profiles of mussels were affected by their diets, which, in turn, depended on the composition of TPMs in the water column. For inter-site differences, levels of SFAs 16:0 and 18:0, which are indicative of presence of marine detritus, were significantly higher at TLC and PC than C, TST and NP, whereas amounts of MUFAs 18:1n9, 20:1n9 and PUFA 18:2n6, which are indicative of presence of zooplankton and marine fungi, were higher at the harbour sites than the reference sites. For seasonal changes, levels of SFAs 14:0, 16:0 and 18:0 were generally higher in summer than winter whereas levels of MUFA 18:1n9 and PUFA 18:2n6 were higher in winter than summer. The fatty acid profiles of TPMs in the water samples were positively correlated with those of gonad and soma of mussels. This further reflected that the fatty acid profiles of mussels were affected by their food sources. Temperature and chlorophyll a in the water

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samples were positively correlated with the fatty acid profiles of TPMs. Levels of PUFAs 20:5n3 and 20:6n3 in TPMs, which are important for reproduction of mussels, were not correlated with those in the gonad and soma. The present findings suggested that these fatty acids tended to be affected by the reproductive period of the mussels rather than by their diets. Chapter 2 - The current chapter is focused on a) the general anatomy and morphological characteristics of mussels (fresh water and saltwater species), b) the effect of both abiotic (temperature, salinity, congestion, pollution, air-exposure, food availability, etc.) and biotic (age, soft-body weight, reproductive cycle, predators, etc.) environmental factors on mussel behavior and physiology, c) the role of filter-feeding mussels as sensitive marker for assessing human-derived environmental impacts and d) the important ecological and environmental role of mussels, with emphasis to saltwater mussels, as reliable tool for monitoring the aquatic environment health status. Specifically, the role of mussels for monitoring aquatic environment is of great interest, since the presence of human-derived inorganic and organic pollutants into the water could affect environmental health status. The good knowledge of their physiology and behavior, as well as their study in cellular, genetic and biochemical level, are important parameters which reinforces the role of mussels as Bioindicators of the marine environment. Moreover, Biomarkers (general- and specific stress as well as genotoxicity), which represent biochemical, cellular,, genotoxical, physiological or behavioral variation that can be measured in mussels, providing evidence of exposure to and/or effects of, one or more chemical pollutants being present into the water, were briefly mentioned, in order to emphasize the use of mussels as bioindicators in a lot well-documented monitoring studies, as a result of the continuously anthropogenic-induced impacts on the environmental health status. Chapter 3 - The Galician coast is the natural environment in which more than 95% of Spanish mussel production occurs. Galicia is a Spanish region located in the far NorthWestern corner of the Iberian Peninsula and its coastline is 1200 km long. In this coastline there are a series of estuaries or bays (also referred to as ―rías‖) that are actually ancient drowned river valleys that were taken over by the sea. Mussels are farmed in the coastal inlets of Galicia by means of a floating raft culture. The Galician mussel sector is based on nearly 3300 installed floating rafts in the five "rías" (Vigo, Pontevedra, Arousa, Muros, Ares). These ría waters are blessed with an extraordinary quality for the farming of mussels due to their warmth and the high amount of nutrients which they contain. Moreover, the rías are ocean areas that are protected from severe weather conditions, which is why the mussel farms are resistant to the changing maritime weather. The Galician mussel production has surpassed 200,000 tonnes annually. Consequently, we are talking about one of the largest mussel producers in the world, and the sector directly generates more than 8000 jobs and incorporates 1000 aquaculture support vessels. This chapter studies the conditions, environment and characteristics of mussel production in the Galician Floating raft culture. This is an updated analysis of the physical, institutional and economic elements of the Galician mussel sector. Chapter 4 - The mussels of the genus Mytilus live in eutrophic seas. Due to their ability to absorb food by filtration and to concentrate both organic and inorganic pollutants, mussels have been extensively used as bioindicators. The exposure to heavy metals often causes sublethal changes, such as abnormalities in DNA replication and transcription, alterations in the pattern of protein expression, changes in other biochemical pathways, and subcellular

Preface

xi

injuries. Cellular stress caused by environmental contamination has been shown to cause spatial and seasonal variability in global protein synthesis in M. galloprovincialis. Most regulation of protein synthesis occurs at the initiation phase of translation. Nevertheless, it was found that the variation of ribosome efficiency at initiating protein synthesis under stress is not proportional to the polysome content, a fact suggesting that additional regulation may occur at other phases of peptide chain elongation. For instance, the ribosomal stalk, composed of a pentameric complex P0(P1/P2)2, is an important structural element of the large subunit which is involved in the ribosome-mediated stimulation of translation factor-dependent GTP hydrolysis. The phosphorylation of P1, and P2 proteins and changes of their content in the stalk may control protein synthesis by influencing initiation and elongation factors, and thereby may affect the translation of individual mRNAs. Protein kinase CK2, a Ser/Thr kinase composed of α and/or α΄ catalytic subunits and a dimer of regulatory  subunit, is involved in cell differentiation, proliferation and tumorgenesis of higher eukaryotes Experimental evidence suggests that CK2 is responsible for modification of the ribosomal stalk proteins and other components of the translational machinery in mussels. Therefore, relationships between protein synthesis alterations, ribosomal stalk function and protein kinase CK2 expression and activity in response to environmental stress is a promising field for exploration in marine invertebrates. Chapter 5 - In the present study, the effects of environmental pollutants have been investigated in the Mediterranean mussel Mytilus galloprovincialis as sentinel species. For the purpose of detecting water contamination in the early stages, biomarkers of effect and exposure must be studied. Most specifically, proteins of intracellular signaling pathways appear to be very interesting targets as their conservation through evolution is maintained and since their modulation via environmental relevant levels of chemical contaminants is an indicating sign of stress for bivalves. Genes encoding the Mitogen-Activated Protein Kinases (MAPKs) in M. galloprovicialis confirmed high homology with those of other vertebrates and invertebrates. Further, mussels were exposed to various model agents: tributyltin, hydrogen peroxide and water soluble fraction of diesel fuel and the activation/phosphorylation of the MAPKs p38, JNK and ERK were evaluated by a new developed ELISA assay. The authors results clearly indicated that pollutants generated different MAPK phosphorylation induction patterns. All the results converge towards the fact that proteins of intracellular signaling pathway could be very promising biomarkers of marine pollution within the mussel M. galloprovincialis. Chapter 6 - The glue of mussels is a remarkable material which has the ability to fix the animals onto organic and inorganic surfaces in aqueous environments. This material consists largely of mussel adhesive proteins (MAPs). The structure of MAPs from a number of different marine invertebrates including mussels has been investigated over the course of the last decades. One common feature of many MAPs studied is the high content of the amino acid 3,4-dihydroxy-L-phenylalanine (DOPA). The DOPA residues are thought to play a key role in the chemisorption of the polymers to substrates underwater and to the formation of covalent cross-links within the adhesive. However, though studies on the adherence of MAPs have described adhesions, oxidations and cross-linking reaction pathways for peptidyl DOPA and DOPA ortho-quinone (oxidation product of DOPA) there remain considerable uncertainties concerning the ways in which different marine mussel species carry out the curing process, and all of the mechanisms described to date are largely hypothetical. To gain a more comprehensive insight of these processes, synthetic DOPA-containing polypeptides

xi Lauren E. McGevin i have been used to experimentally identify the functions and reactions of the amino acids which are active in the chemistry of the MAPs. These studies demonstrate that the adhesion and cross-linking capabilities of mussel adhesive proteins can be successfully reproduced using synthetic materials. The possible applications of these findings in biotechnology are virtually unlimited. Thus synthetic MAPs may be used for medical adhesives in surgery, ophthalmology or dentistry, as well as for enzyme, cell, and tissue immobilization, and as anticorrosives, and metal scavengers. For the design of potential biomaterials it is necessary to understand (i) the reaction of MAPs especially DOPA with organic or inorganic substances; (ii) the chemical structure of the reaction products and (iii) the role of possible catalysts such as, for example, oxidizing enzymes which may support the cross-linking and curing processes. These crucial factors for the synthesis of biomedical or industrial biomaterials will be highlighted in this chapter. Chapter 7 - Mussels comprise members of several families including clams and bivalvia mollusca from both marine and freshwater habitats. They are distributed worldwide and are implicated as bio-indicators for environmental stress. These animals are exposed to a variety of pollutants of industrial, agricultural and urban origin. The accumulation of several anthropogenic agents in their tissues suggests that they possess mechanisms that allow them to cope with the toxic effects of these contaminants. Besides pollutant uptake, this paper presents an overview of the significance of the use of molecular biomarkers in mussels as diagnostic and prognostic tools for marine and freshwater pollution monitoring. Biomarkers complement the information of the direct chemical characterization of different types of contaminants. This review focuses on several types of biomarkers classified according to their functional roles in normal tissues, their respective expression following the exposure to harmful contaminants and their relevant physiological aspects in term of response to environmental stress. Evidence from both experimental laboratory conditions as well as field studies will be taken into account in a perspective of a multi-biomarker approach to assess environmental changes. Chapter 8 - This chapter describes how the ―Mussel Watch‖ concept proposed by Goldberg in 1975 to assess and monitor the state of the water column has evolved over the past few decades. Definitions with specific examples are provided to illustrate the range of chemicals analysed in international programs interested in the presence of persistent organic pollutants, priority pollutants and emerging contaminants. Although the latter organic molecules are generally analyzed in the inflow and outflow of sewage treatment plants, they are also actively researched for potential risk needing attention in aquatic organisms. The measurement of effects going from the biochemical to the population level affecting reproduction is discussed in detail. Examples of studies measuring the depletion or enhancement of enzymatic activities are provided along with explanations on the type of stress linked to the toxic effects. The latest publications dealing with impact assessment encompassing chemical and environmental stresses highlight the complexity of the variables integrated by bivalves in response to changes in their habitat. The future of these investigations is in combining knowledge generated from ―curiosity based‖ and ―solution oriented‖ research that uses chemical and biomarker measurements to determine the sustainability of aquatic ecosystems. Chapter 9 - The present paper reviews all the studies done on genetics and heavy metal ecotoxicology focussing on the green-lipped mussel Perna viridis from Malaysia. Based on the findings reported in 10 publications on the above topics, the genetic differentiation in P.

xii i viridis populations could be explained as being due to geographical factors, physical barriers and heavy metal contamination. All the studies were done using allozymes and DNA microsatellite markers. The results based on both the biochemical and the molecular markers were comparable and almost similar in their genetic distances and FST values. The genetic distances indicate that the mussel populations from Peninsular Malaysia are conspecific populations while the FST values show a moderate genetic differentiation based on Wright's (1978) F-statistics. All the genetic variation parameters strongly support the use of P. viridis as a good biomonitor in the coastal waters of Peninsular Malaysia since the various geographical populations in the region belong to the same species. Without knowledge of the genetic structure of the mussel populations, the biomonitor species is chosen solely based on its morphological characters which could be confusing. Therefore, biochemical and molecular studies are needed to validate the genetic similarity of the chosen biomonitor. From another point of view, based on hierarchical F-statistics and cluster analysis, the physical barrier that blocked the gene flow (through the pelagic larvae swimmers) of P. viridis, and a distinct heavy metal contamination in a polluted population were identified as being the two main causal agents for the genetic differentiation of P. viridis populations, indicating that environmentally induced selection had occurred. All these conclusions could only be drawn when both the genetic and the ecotoxicological information were put together. If the aim of ecotoxicological genetics research on marine invertebrates is to determine whether anthropogenic chemicals are able to damage the DNA sufficiently to alter the population dynamics in ecosystems (Depledge, 1998), then the biomonitoring and monitoring work should be regarded as being as equally important as the biochemical and molecular level study on the biomonitor species itself. It was only together with the availability of information on the anthropogenic chemical levels in the biomonitor and its environmental habitat that the deviation from the Hardy Weinberg Equilibrium observed in the polluted mussel population could be meaningfully interpreted. By taking the biomonitor P. viridis as a model, ecotoxicological genetics should be a focal research area in order to protect the valuable living natural resources in the coastal waters of Malaysia. Chapter 10 - Mussels' attract scientific attention due to two main reasons – they are excellent seafood being source of n-3 polyunsaturated fatty acids, and they are sensitive bioindicators for the environmental conditions. Metabolic changes in mussels are due to their developmental phase, environmental conditions and pollution stress. They could be result of stress induced degradation processes as well as to changes leading to a better adaptation towards the harmful environment. The lipid cell membranes are important for this adaptation, since one of the effects of the stress impact is to perturb the physical properties of the cell membranes by changing their chemical composition and biophysical organization. In such a case the adequate response of the cells would be a series of biochemical modifications and rearrangements of lipophilic compounds (phospholipids, sterols) in the cell membranes, in order to recover their initial organization. Chemical composition and enzymatic activities of mussels from different areas are discussed. Impact of temperature, food availability, salinity, pollution (including metals and persistent organic pollutants) to the mussels‘ biochemistry, also resulted in significant changes in metabolites. Oxidative stress could also take place in marine bivalves under a series of environmental adverse conditions. Chapter 11 - Marine pollution and water quality are evaluated on direct measurements of the abiotic variables and also on bioaccumulation measurements of chemical contaminants in marine organisms. Measuring the same biomarkers in different localities simultaneously gives Preface

xi Lauren E. McGevin v information about the pollution states and provides a better comprehension of the mechanistic model of action of environmental pollutants on the organisms. The use of biomarkers to evaluate stressful situations is widely extended in bivalves. In the current work, organic compound concentrations (dichlorodiphenyltrichloroethane isomers, dioxins, PCBs and PAHs), antioxidant biomarkers (malondialdehyde, catalase, glutathione peroxidase, superoxide dismutase and glutathione reductase) and isotopic composition (15N and 13C) were measured in the digestive gland and gill tissues of the mussel Mytilus galloprovincialis in coastal waters of the Balearic Islands (Western Mediterranean) in order to assess pollution levels in these waters. The highest concentrations of PAHs corresponded to naphthalene, acenaphthylene, fluorene and phenanthrene, with the harbours of Santa Eulàlia and Eïvissa having the highest levels of PAHs. Oxidative stress and biomarkers are used as indicators of pollution exposure, showing that pollution can not evidence exposure effects, while the antioxidant responses can change with time. In the current work, the existence of pollution was indicated by the positive correlation between the concentrations of the lighter PCBs in the digestive gland of the mussels and catalase and glutathione reductase enzyme activities. Gills showed a correlation between the lighter PCBs and superoxide dismutase activity, indicating the bioaccumulation of these organic compounds. Carbon and nitrogen isotopic signatures showed a clear trend for differences in tissue distribution among the studied localities, with the digestive gland being more enriched in carbon and nitrogen than the gills. PCA for biomarkers also showed that tissues responded differently at sampling stations. The presence of pollutants could be the responsible for the changes described in the isotopic composition and in the antioxidant defences of the mussel M. galloprovincialis in waters of the Balearic Islands. The correlations between organic pollutants and the isotopic composition and biomarkers in M. galloprovincialis suggest that these measures could represent a good proxy for evaluation of contamination, additional to the chemical characterisation. Chapter 12 - Human activities and atmospheric pollution impact coastal ecosystems at different rate in the world. The oceans contain a wide range of animal species that are harvested for human consumption. It is estimated that more than 2 billion people world-wide depend on protein from seas and coastal habitats, yet it is into this environment that anthropogenic pollutants often accumulate. Contamination of seafood is inevitable. The word ―mussel‖ is frequently used to name the edible bivalves of the marine family Mytilidae, most of which live on exposed shores in the intertidal zone, attached by means of their strong byssal threads to a firm substrate. Mussels are stationary filter feeders that filter large quantities of seawater, keeping in this way large amounts of pollutants, and constitute a source of contaminants for marine organisms that feed on them. As they accumulate pollutants (polycyclic aromatic hydrocarbons, PAHs, polychlorobiphenyls, PCBs, organochlorine compounds, OCs) efficiently, they can be used in water monitoring programs. Similarly to other invertebrates mussels show a slow metabolic rate and consequently a slow xenobiotic biotransformation. Mussels filter suspended matter from the water column and deposit it as feces and pseudofeces. The food of mussels consists of particulate organic matter and other microscopic sea creatures which are free-floating in seawater. Organic matter is produced in the water column (phytoplankton) and the waves are very important for the availability of this food because they cause turbulence and keep organic matter in suspension. Mussels serve as an important food source for a wide range of organisms (e.g., starfish, eider ducks, some predatory marine gastropods and oystercatchers) and are also eaten by humans. As a matter of fact they contribute to the PCBs, PAHs and OCs intake in human being.

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The species Mytilus galloprovincialis is a very abundant organism in the Mediterranean Sea. This is a mostly enclosed sea that has limited exchange of deep water with outer oceans and where the water circulation is dominated by salinity and temperature differences rather than winds. It covers an approximate area of 2.5 million km2 but its connection to the Atlantic Ocean is only 14 km wide. In The authors studies toxic pollutants were detected at different rates in mussels caught from Adriatic and Tyrrhenian Sea in the last years and compared with the levels found in other seas as reported in literature. Chapter 13 - A multi-layer structure of blue mussels, Mytilus galloprovincialis, was analyzed by in situ investigation and numerical modeling. Blue mussels usually colonize the surfaces of coastal rocks, artificial structures, and the ropes for aquaculture. They filter the ambient waters to ingest particulate organic matter and to obtain oxygen. Their feeding and respiratory activities cause changes in material cycle. However, the effects of blue mussels on material cycle cannot be easily predicted. Blue mussels colonize several layers of the substrate and subsequently compete for space and food among them. Some of the mussels are pushed to the inner layer of a mussel bed and undergo starvation due to their unfavorable position. They do not contribute to the food-ingestion and oxygen-consumption rates of the mussel bed. In this chapter, a multi-layer structure of blue mussels was analyzed by measuring the oxygen-consumption rates of the mussel bed and by investigating the relationship between the growth of an individual mussel and its position in the mussel bed. Then, an individual-based model was developed to describe the dynamics of blue mussels under competition for space and food. The model consists of a physiological growth submodel and a competition submodel. This model was applied to blue mussels adhering to artificial structures in Tokyo Bay in Japan. The authors observed that the individual-based model could reproduce the in situ observations and elucidate the multi-layer structure of blue mussels. Chapter 14 - Aquaculture has consistently increased and it is expected to overtake capture production of food fish supply in the near future (~2020 or 2030). Bivalves usually refer to groups of species like oysters, clams, cockles, mussels and scallops that have been contributing to this growth. Flavor is considered as a high value product and, specifically, good quality seafood flavors are in high demand. As a common industrial practice, the natural seafood flavors are reformulated by adding other ingredients and artificial flavors for specific desired characteristics. Such flavors are being used in seafood sauces, chowders, soups, bisques, instant noodles, snacks and surimi seafoods. The present chapter focuses on the seafood flavor production by some methods, especially, enzymatic hydrolysis due to some advantages such as high yield, good quality with less off-flavor production and control of flavor characteristics through variation of enzyme reactions. Mussel meat was chosen due to this unique taste, high quality of raw material, which ensures good quality flavor, and also the low fatty content that avoids the susceptibility to lipid oxidation. Flavors are preferably used in the powder form, both for processing convenience as well as end use, and this allows the reduction of shipping costs and increases their stability. Microencapsulation is a useful tool in protection of the integrity of food ingredients used as flavors, from oxygen, water or light. Spray drying is the most commonly used technique for the production of dry flavorings and this process converts a liquid flavor into a free flowing powder which is stabler, easier to handle and incorporate into a dry food system. The addition of carrier agents has been used to reduce stickiness, increase stability during storage and trap volatile flavor constituents inside the droplets. Therefore, the production of mussel meat flavor powder by enzymatic hydrolysis

x Lauren E. McGevin vi and spray drying, using gum Arabic, and the determination of its shelf life in terms of sorption isotherms, glass transition temperature, morphology and volatile losses are described and discussed in this chapter. Chapter 15 - The application of Life Cycle Assessment (LCA) for the environmental analysis of mussel culture was considered through the study of the main production areas in Galicia (NW Spain). Inventory data came from interviews and surveys from a set of vessels accounting for the production of more than 7,000 tonnes of mussels cultured in rafts. In addition, physico-chemical characterization of wastewater from the vessels was performed. Abiotic resources depletion, global warming, ecotoxicity, human toxicity, acidification, ozone layer depletion, photochemical oxidant formation, and eutrophication were the impact categories included. Characterization results for each of the categories revealed the importance of taking into account not only the operational issues, but also the capital goods. The consumption of diesel for the vessel arose as the main contributor to potential environmental impacts, along with energy demand and iron production linked to capital goods. Furthermore, an analysis with four different scenarios was carried out, highlighting the importance of studying capital goods in greater detail. Additionally, a toxicity/ecotoxicity analysis was performed, proving a lack of consensus when characterizing toxicity and ecotoxicity potentials. Finally, mussel aquaculture was compared to mussel capture, finding that mussel aquaculture may present a higher potential environmental impact for farmed mussels due to the involvement of a number of operational inputs and outputs without correspondence in current data for mussel capture. Chapter 16 - The dynamics and range of environmental changes that have been observed recently in many coastal and estuarine regions highlight the importance of monitoring for the understanding of these alterations to ecosystems. Of particular relevance are issues which concern the loss of biodiversity, pollution, water quality, sustainable development, and climate change and their potential impact on marine biota. High quality, long-term monitoring programmes have been developed in recent decades to determine current contamination status against which future changes can be assessed (Oldfield and Dearing, 2003; Simcik, 2005; Batzias et al., 2006). In practice, monitoring pollutants is a very complex task, and it comprises an important element of the global observation system. The Mussel Watch Program was created with the aim of determining current metal status in coastal environments as an efficient tool to monitor environmental trace metal levels. The Mussel Watch Program has been implemented in many countries worldwide including the United States, the United Kingdom, France, Hong Kong, and Australia. Pollutant contamination and that of trace metals in particular, has been an environmental issue in many countries for decades, and there is still a need to assess the bioavailability and toxicity of metals in many water basins. This aspect is extremely important not only for estimating the environmental risk of metal contamination to marine fauna and flora, but also the potential effect of metals on humans. Despite trace metals being natural elements in the marine environment, they pose very serious concerns for seafood safety and various aspects of the tourism industry (Wang and Rainbow; 2008). The contamination of the coastal and estuarine areas can be assessed using biological monitors (biomonitors) which accumulate organic and non-organic compounds in their tissues at concentrations which are proportional to the ambient bioavailability (Philips and Rainbow, 1994; e Silva et al., 2006). Therefore, a single biomonitor provides information on the availability and accumulation of a particular compound, and it can be used to assess the

xvi i environmental status of this compound on a local scale (e Silva et al., 2006). The choice of a biological monitor depends on the characteristics of the study area and the objectives of the monitoring program (Resh, 2008). Mussels or other bivalves are commonly exploited for biomonitoring aquatic metal pollution because of their specific biological features relative to other organisms. Bivalves, including oysters, mussels and clams, have been used as biomonitors for evaluating metal pollution in marine water basins for nearly seventy years (Zhou et al., 2008). Bivalves have played an essential role in developing observational methods to detect the potential impact of contaminants on ecosystems over long periods of time, and the importance of biomonitoring programs is now unquestionable. Chapter 17 - Growth of several aquatic organisms is recorded in their hard parts. The skeleton of mussels (akin to clams, corals and brachiopods) is known to portray an array of shell growth increments. Investigations delving into the anatomy of these annuli have proven that the most discernible of them are often exhibiting annual periodicity. In other words, an increment is layered once a year. Rigorous examination of these increments is most commonly called as sclerochronology. Essentially, the sclerochronological approaches all benefit from the meticulous comparison and matching of shell growth increment records between several individuals. This procedure, called as sclerochronological crossdating, relies on growth increment widths and ensures that no increment is falsely added or missing in the resulting chronology. Apart from crossdating, the sclerochronological studies may benefit from the procedures of detrending and pre-whitening. Many environmental factors significantly influence the thickness variability of the increments. Both detrending and prewhitening enable capturing the internally driven growth variability and to isolate the growth variations caused by external factors. Correlation analysis can be used to find out those environmental variables potentially influencing the shell growth variability. Mussels are thus keeping the book of environmental history. Sclerochronologists with skill of crossdating and other methods of time-series analysis are benefitted by increased ability to read these books. Chapter 18 - Marine biotoxins are produced by a few species of microalgae, mostly dinoflagellates. These biotoxins are produced in abnormal quantities during blooms of these microalgae and are accumulated mainly in filter-feeding organisms, such as bivalves. Bivalves are the major vectors of human poisonings in temperate waters. In tropical waters more complex food web interactions lead to the accumulation and bioamplification along the food chain of reef fishes of the toxins causing ciguatera fish poisoning (CFP). Marine biotoxins cause gastrointestinal and/or neurological symptoms. In some of these syndromes the symptoms are short lived, while for instance in CFP symptoms may persist for months. In rare cases, severe intoxications might prove fatal, such as extreme cases of paralytic shellfish poisoning (PSP). In order to prevent human intoxications with contaminated bivalves, phytoplankton and flesh testing analysis are carried out routinely in producing areas. These monitoring programmes follow established food safety laws that allow the interdiction of harvesting activity in the bivalve producing areas. These banning periods impose a socio-economical burden in all those directly or indirectly involved in bivalve trading (Franco, 2005). The periods may last from days to months. In some cases, depending on the bivalve species, particular retention of the toxins might occur year-round. For just a few of these extreme cases some strategies have been found, namely industrial processing might allow continuous bivalve harvest. In Europe, two Preface

x Lauren E. McGevin vi ii exceptions allowing harvest when toxin levels are above the regulatory levels in force are permitted under the current legislation (European Commission, 1996; 2002). Heat treatment followed by evisceration and canning is used today in Spain to deal with the persistent contamination with PSP toxins of the giant cockle Acanthocardia tuberculata (Berenguer et al., 1993), while fresh scallop‘s, Pecten maximus or Pecten jacobaeus, evisceration deals with the persistence of amnesic shellfish poisoning (ASP) toxins in the digestive glands (Salgado et al., 2003). However, evisceration is amenable only to large sized and hard body species, such as these two. Various in vivo methods for accelerating the detoxification process have been tried in the past, particularly for PSP toxins. They include thermal and osmotic stress, electric shocks, decrease in pH, and chlorination (Shumway et al., 1995). None of these methods, however, has proved effective. A review of recent EU projects on detoxification shows either with added algal food or not, depuration takes too many days to be of any use to the bivalve industry (Lassus et al., 2007). The aquaculture sector relies then mainly in natural decontamination processes, taking place in estuarine and lagunar areas after the toxin-producing microalge bloom decays. The decay is species-dependent. In the case of the widely cultivated species in Europe, the blue mussel, scientific data points that it is amongst the most toxic species and presents the longest harvest restriction periods, although some exceptions are known, as those mentioned above. Data accumulated after several years studying Portuguese bivalves will be reviewed to illustrate this point. Following recommendations of a working group organised by the Community Reference Laboratory for Marine Biotoxins on sampling plans (EU-CRL, 2001), the Portuguese programme for biotoxins was refined in 2002 to better incorporate the concept of indicator species – the species that has the highest rate of toxin accumulation. For lagunar and estuarine areas both blue mussels (Mytilus galloprovincialis) and common cockles (Cerastoderma edule) were chosen as weekly indicators. Not a single species, but two were chosen. This outcomes of previous experience showing mussels could reach higher toxin levels than cockle, clams or oysters, and also took longer time to return to safe levels in order to reopen producing areas. If a regulatory decision had to be made based solely on toxin levels in mussel, exploitation of other commercial species would suffer unnecessary closures (Figure 1). As mussels retain toxins longer than other species, when new blooms of toxic microalgae take place, they tend to surpass first the regulatory levels, as toxins ingested add up to the toxin burden already present in the tissues. When the bloom ends, in comparison for example with cockles, toxin levels in mussels might remain above the regulatory levels for several weeks (Figure 1). Detailed data on the main occurring toxins will be next reviewed, and mechanisms underlying the physiological responses will be discussed. Chapter 19 - Mollusca comprises of a wide ranging invertebrate Phylum with nearly 100,000 number of living species. Mussels are aquatic bivalves distributed in diverse types of waterbodies of India. Internal visceral organs of mussels are located between the muscular foot and calcareous hard shell. Pair of valves enclose the soft body parts and are attached with adductor muscle. The space between the membranous mantle and soft visceral mass constitutes mantle cavity harbouring the gill. Gill is the chief respiratory organ of mussel which actively participates in the process of filter feeding. During filtration of the water column, the freshwater mussels are capable of filtering a large volume of water. While

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filtering the water for the purpose of food procurement, mussels create characteristic regional current in its aquatic environment. This movement of water mass in the form of current interferes with the important process of distribution of dissolved particulates and gases. Many of these particulates are of nutritional, metabolic and toxicological importance and the dissolved gases include oxygen, carbon dioxide etc. Filter feeding activity of mussel thus influences various physiological activities of the other inhabitants of water by influencing their nutritional, immunological and toxicological status. Coexistence and perpetuation of aquatic flora and fauna of the freshwater environment is a result of successful evolutionary process where the mussels play a key role. Successful perpetuation and reproductive activity of mussel depend on biosafe propagation of the species in its toxin-free habitat. Physiological defence of mussel mostly depends on its highly evolved immunological system. Molluscan immunity is chiefly dependent on the activity of the circulating haemocytes or blood cells. In Lamellidens marginalis, the information on blood cell is limited with reference to the toxicity of common environmental contaminants. Gradual shrinkage and contamination of habitat by environmental contaminants appear to be a serious threat to the freshwater mussel. Various agrotoxins and metalloid toxin like arsenic are reported as major toxins which affect the immunological status of L. marginalis. Chapter 20 - Lamellidens marginalis (Mollusca; Bivalvia; Eulamellibranchiata) is a freshwater edible mussel distributed in the wetland of different districts of WestBengal, India. Natural habitat of the species is under risk of contamination by multineeem, a newly introduced azadirachtin (limonoid) based pesticide.Blood or haemolymph of L. marginalis contains haemocytes, capable of performing diverse physiological functions. Haemocytes, the circulating blood cells are considered as immunoreactive agent capable of performing phagocytosis, nonself adhesion and aggregation. Magnitude of haemocyte aggregation was studied in depth under the exposure of 0.006, 0.03, 0.06 and 0.03 ppm of azadirachtin for varied span of exposure. Azadirachtin exposure yields decrease of haemocyte aggregation against a control level of aggregation of 34.21%. In the dynamic ecosystem of freshwater, the inhabitants participate in the struggle of niche occupation for survival and existence. Situation often leads to a state of acute predation and fight among animals. As a result, the animals experience physical wounding and loss of body fluid. Aggregation of haemocyte at wound site prevents the loss of blood and entry of microorganism and considered as an immunological response. Magnitude of hemocyte aggregation of mussel was screened under the experimental exposure of EDTA and mannose at different concentrations. Study was aimed to screen the effect of chelating agent and sugars on aggregation. For all the chemicals screened, a drastic increase in the occurrence of free cells were reported which is suggestive to role of these agents in the physiological process of haemocyte aggregation. Moreover, exposure to azadirachtin may lead to gradual loss of blood cell homeostasis of freshwater mussel distributed in its natural habitat. Continuous exposure to toxic azadirachtin may lead to a population decline of freshwater mussel and loss of biodiversity in the freshwater ecosystem of India. Chapter 21 - The expansion of the zebra mussel, Dreissena polymorpha, is observing during at least two hundred years. It has increased the speed at the end of the twentieth century. Adaptation of these species to new natural conditions beyond bounds of ecological optimum is interesting in evolutionary aspect. However, populations of the northern boundaries of the present range, which are the most essential in this respect, practically are not studied until now.

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For studies of microevolution processes the phylogeographic methods with application of mitochondrial DNA analysis are widely used. Haplotype diversity of the mtDNA locus, encoding cytochrome c oxidase subunit I for D. polymorpha is learned across the large part of its distribution area, however the previous investigations have no included the boundary populations of the north-eastern regions. Samples of the zebra mussels located at 580 – 640 N were studied in The authors investigation. Two of Caspian haplotypes have been found here, that supported the assumption about the spread of the zebra mussel into the northern area from Caspian Sea. The results of The authors work supply the general pattern of gene geography of D. polymorpha, and suggested to possible existence of secondary sources of the zebra mussel spread beyond the bounds of Ponto-Caspian region. Chapter 22 - Freshwater mussels of the family Unionidae, also known as naiads, have inhabited fresh waters around the world for the past 400 million years. The presence of these unique mussels ensures our water quality and helps support the worldwide pearl industry. Yet their continued survival is by no means certain, due to overharvesting, environmental degradation and the rapid spread of exotic mussel species. Most research related to mussels has dwelt on different topics as fine-scale, intradrainage distribution patterns and life history traits relevant to applied conservation and propagation issues but there are only a few reports on anatomy studies. This chapter provides baseline reference material regarding the anatomy of Unionidae freshwater mussels, focusing in particular on the subfamily Unioninae with the aim to improve the knowledge in mussels of professional biologists and amateur naturalists as well as their preservation. Chapter 23 - Mussels within the genus Mytilus are one of the most thoroughly studied marine molluscs at both the ecological and physiological levels. A great number of studies on morphology, morphometry, proteins and DNA markers have been performed, but origin and taxonomy of this genus still remains unclear. Based on these studies, different authors recognised the existence of different species, semi-species or subspecies within this genus. For example, according to McDonald et al. (1991) these are five taxa: M. edulis, M. galloprovincialis, M. trossulus, M. californianus and M. coruscus, and Gosling (1992) includes M. (edulis) desolationis as a subspecies of M. edulis. Data from different mitochondrial and nuclear DNA markers have revealed strong biogeographic and phylogenetic relationships among M. edulis, M. galloprovincialis and M. trossulus -these three forming the M. edulis complex- (Varvio et al. 1988; Koehn 1991; McDonald et al. 1991; Rawson and Hilbish, 1998; Quesada et al. 1998; Martinez-Lage et al. 2002; Riginos and McDonald 2003; Riginos and Cunningham 2005; Pereira Silva and Skibinski 2009). According to Blot et al. (1988) and Gérard et al. (2008) M. desolationis seems to be a ―semispecies in the super-species Mytilus edulis complex‖, whereas M. californianus and M. coruscus constitute two separate species as shown by the results obtained from the 18S ribosomal DNA (Kenchington et al. 1995), mitochondrial DNA (Hilbish et al. 2000), and satellite DNA Apa I (Martínez-Lage et al. 2002, 2005) analyses. Chapter 24 - Evolutionary toxicology investigates population genetic effects caused by environmental contamination. Toxicant inputs of increasing industry, agriculture and fast growing cities have severely modified freshwater ecosystems. These anthropogenic stressors are expected to influence population genetic patterns by causing mortalities, so that, e.g., a recent reduction in genetic diversity would be indicative of deteriorating environmental

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conditions. The amount of genetic diversity can therefore be applied as a biomarker for the condition of freshwater ecosystems in a biomonitoring system. The zebra mussel is a common bioindicator for passive as well as active biomonitoring of freshwater ecosystems. Here, the authors suggest a novel approach to establish the genetic status of zebra mussel populations as an independent indicator of environmental condition. In this strategy, the well-established techniques of comet assay, micronucleus test and microsatellite analysis are combined to assess the health of freshwater habitats. Chapter 25 - are bivalves that are variously adapted for relatively immobile nature. They are characterized by the presence of short byssal threads attached close to exposed surface of hard substrates. Majority of them occur in intertidal areas, although some of them have occasionally been reported from deep water. Because of their relatively immobile nature and ubiquitous presence in the littoral and shallow sublittoral waters, they have been commonly targeted by their natural enemies. The natural enemies of mussels can be categorized in four main groups. The first group consists of predators like fish, crabs, birds, starfish and snails. Fish, crabs and birds just peel or crush the hard shell. Starfish uses whole body consumption. Predatory snails drill holes in the hard shell and consume the soft tissue; this kind of predation can be identified postmortem. Predation could be responsible for up to 50% of the mortality of a mussel population. The severity of predation generally is size and locality selective. Often the smaller size class of mussels takes the heaviest hit. The second groups of natural enemies are the competitors, fighting for similar food and space such as barnacles, crepidula, tunicates. These competitions could be severe enough to drive entire mussel population to the brink of extinction. However, these competitors are often serving as prey items for the same predators that prey upon mussels. In those scenarios, these competitors often render a positive feedback on the mussels by sharing the predation stress. The third group is the shell destroyers such as demosponges, polychaete. They are known to damage the calcitic shells of mussels by boring them. These boreholes are different from predatory drillholes as they are generally non-lethal. However, those boreholes damage the structural integrity of the shell and eventually lead them to disintegration by wave action. The fourth group of natural enemies are the parasites such as mytilicola, pinnotheres. These parasites often cause significant damage to the vital organs affecting respiration, filtration, ventilation and digestion. Although primarily these natural enemies render negative effect on mussel population, the overall interaction is very complicated and often produces positive effects locally.

In: Mussels: Anatomy, Habitat and Environmental Impact ISBN 978-1-61761-763-8 Editor: Lauren E. McGevin ©2011 Nova Science Publishers, Inc.

Chapter 1

INTER-SITE DIFFERENCES AND SEASONAL PATTERNS OF FATTY ACID PROFILES IN GREEN-LIPPED MUSSELS PERNA VIRIDIS IN A SUBTROPICAL EUTROPHIC HARBOUR AND ITS VICINITY S. G. Cheung1,2 and P. K. S. Shin1,2 1

Department of Biology and Chemistry, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong 2 State Key Laboratory in Marine Pollution, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong

ABSTRACT Fatty acid profiles of total particulate matters (TPMs) in water and green-lipped mussels Perna viridis were studied for one year in the eutrophic Victoria Harbour, Hong Kong and its vicinity. Bimonthly sampling of TPMs and P. viridis were conducted at four sites inside the harbour, namely Tsim Sha Tsui (TST), North Point (NP), Kwun Tong (KT) and Central (C) and two references sites outside of the harbour, namely Peng Chau (PC) and Tung Lung Chau (TLC). Levels of saturated fatty acids (SFAs) 16:0 and 18:0 in TPMs, signatures of marine detritus, bacteria and nano-zooplankton, were higher at reference sites than at harbour sites. In contrast, levels of monounsaturated fatty acids (MUFAs) 18:1n9 and 18:1n7 and polyunsaturated fatty acid (PUFA) 18:2n6 were higher in Victoria Harbour than at reference sites. These suggested that the waters in Victoria Harbour contained relatively high amounts of marine fungi and bacteria, reflecting the poor water quality within the harbour proper. The gonad and soma of mussels from the six sites exhibited similar intersite differences and seasonal changes in fatty acid profiles. The fatty acid profiles of mussels were affected by their diets, which, in turn, depended on the composition of TPMs in the water column. For inter-site differences, levels of SFAs 16:0 and 18:0, 

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S. G. Cheung and P. K. S. Shin which are indicative of presence of marine detritus, were significantly higher at TLC and PC than C, TST and NP, whereas amounts of MUFAs 18:1n9, 20:1n9 and PUFA 18:2n6, which are indicative of presence of zooplankton and marine fungi, were higher at the harbour sites than the reference sites. For seasonal changes, levels of SFAs 14:0, 16:0 and 18:0 were generally higher in summer than winter whereas levels of MUFA 18:1n9 and PUFA 18:2n6 were higher in winter than summer. The fatty acid profiles of TPMs in the water samples were positively correlated with those of gonad and soma of mussels. This further reflected that the fatty acid profiles of mussels were affected by their food sources. Temperature and chlorophyll a in the water samples were positively correlated with the fatty acid profiles of TPMs. Levels of PUFAs 20:5n3 and 20:6n3 in TPMs, which are important for reproduction of mussels, were not correlated with those in the gonad and soma. The present findings suggested that these fatty acids tended to be affected by the reproductive period of the mussels rather than by their diets.

INTRODUCTION Lipids are important to the marine environment because of their significant constitution to the total carbon flux through the trophic levels (Lee et al. 1971, Sargent et al. 1977, Reuss and Poulsen 2002). They are a compact and concentrated form of energy storage for plants and animals and constitute a source of essential nutrients, vitamins and chemical messengers (Napolitano et al. 1997). Fatty acids constitute the main part of the lipids in marine organisms. Many biologically important fatty acids, such as some polyunsaturated fatty acids (PUFAs), particularly eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), are only synthesized de novo by phytoplankton (Pohl and Zurheide 1979, Sargent and Whittle 1981, Desvilettes et al. 1997, Napolitano et al. 1997, Reuss and Poulsen 2002). They are synthesized at the lower trophic levels and remain unchanged, or stay in a recognizable form, when transferred to higher trophic levels (Napolitano et al. 1997, Reuss and Poulsen 2002). Thus, fatty acids can be useful markers to indicate the trophic relationship among marine organisms and trace the food source through multiple food web linkages. On the other hand, fatty acid markers are able to compensate the shortcomings of traditional stomach analyses. Since the food items in the gut are usually difficult to identify and quantitatively biased due to differential digestion rates of soft and hard parts, fatty acid markers can provide supplementary information to indicate whether the food is assimilated into the tissue of the organisms (Dalsgaard et al. 2003). Fatty acid markers can also be used to determine the dominance of particular groups of organisms, as well as the interaction among trophic groups (Dalsgaard et al. 2003). In most studies, data showed that the saturated fatty acids (SFA) 14:0 and 16:0 constitute the major components of the fatty acid pool of most algal classes (Reuss and Poulsen 2002). High concentrations of saturated fatty acid (SFA) 14:0, monounsaturated fatty acid (MUFA) 16:1n7, 16 carbon-chain PUFAs and 20:5n3 are characteristically measured in diatom-dominated communities. High levels of 18 carbon-chain and 22:6n3 are consistent within dinoflagellate-dominated communities. Calanoid copepods have considerable amounts of MUFA and monounsaturated fatty alcohols with 20 and 22 carbon atoms. In addition to indicating trophic relationships, fatty acids can be markers to reflect the quality of lipid materials in the environment (Brazão et al. 2003). Fatty acid compositions in the water column are shown to vary under a succession of species within a natural plankton community (Dalsgaard et al. 2003). For instance, when there is a shift in a plankton

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community from the dominance of diatoms to flagellates, 16:1/16:0 ratio in the water column tends to decrease and 18:4/18:1 ratio increase. Thus, fatty acids can be used to indicate the seasonal patterns of plankton communities in the marine environment (Dalsgaard et al. 2003). Green-lipped mussel Perna viridis is a tropical and subtropical species distributed widely in the Indo-Pacific (Siddall 1980, Wong and Cheung 2003a). They usually form dense populations (35,000 individuals m-2) on a variety of structures including vessels, fish rafts, buoys and any hard substrates (NIMPIS 2002). In Hong Kong, Perna viridis is commonly found from oceanic to estuarine waters (Wong and Cheung 2003b). They are dominant in the subtidal region with high densities recorded from Victoria Harbour (246 individuals m-2) and Tolo Harbour (> 1,000 individuals m-2) (Huang et al. 1985, Wong and Cheung 2003b). P. viridis is an efficient filter feeder, feeding on phytoplankton, small zooplankton and other organic materials. They can usually be found in a habitat with salinity in the range of 18–33‰ and temperature in a range of 11–32ºC. P. viridis generally spawns twice a year, between early spring and late autumn. Fertilized eggs develop into larvae and remain in the water column for two weeks before settling as juveniles. Sexual maturity usually occurs while the shell length is about 15–30 mm, corresponding to two to three months of age. The life of P. viridis is about two to three years. Their growth rates are influenced by environmental factors such as temperature, food availability and water movement. First year growth rates vary between locations. In Hong Kong, the first year growth rate is 47 mm year-1. Mussels can be a bioindicator because they are sedentary and can accumulate, tolerate and concentrate contaminants from the environment. They always occur in wide and stable populations and hence can be sampled repeatedly in different seasons. Moreover, responses such as growth, reproduction and energetics in green-lipped mussels have been reported to be largely controlled by environmental factors (Lee 1986, Cheung 1991). Thus, mussels can be a good indicator of changes in the environment. P. viridis has been used as a bioindicator to detect the level of trace metals and organochlorines (Phillips and Yim 1981; Phillips 1985; Phillips and Rainbow 1988, Bayen et al. 2004), PAHs (Xu et al. 1999) and the effect of hypoxia in the marine environment (Wu and Lam 1997). Victoria Harbour lies between the most heavily urbanized area of the Kowloon Peninsula and the northern shore of Hong Kong Island (Yung et al. 1999). It is a major tidal channel with strong current flushings and has long been utilized for disposal of sewage effluent. In the past, wastewater was discharged into the harbour only after a simple screening process. It resulted in poor water quality with high nutrients and sewage bacteria (HKEPD 2004). Before 1997, there were 12 outfalls from 11 sewage screening plants, which discharge about 1.5 million M3 of screened effluent into Victoria Harbour per day (HKEPD 1997). In 2001, the Harbour Area Treatment Scheme (HATS) was fully implemented to treat sewage and improve the water quality in Victoria Harbour. In the first stage of HATS, the sewage from Kowloon and north eastern parts of Hong Kong Island was transferred to a central sewage treatment works for chemical treatment before being discharged into the western approaches of Victoria Harbour. The water quality in eastern Victoria Harbour sharply improved in 2004 (HKEPD 2004). In 2004, the dissolved oxygen increased (5.3–6.0 mg l-1) and could meet the standard (4 mg l-1). The level of E. coli was lower (480–630 cfu ml-1), compared to the previous year, and almost met the standard for secondary contact in recreational areas (600 cfu ml-1). The levels of nitrate, phosphate and ammonia were also markedly reduced. The aims of the present study were to investigate the inter-site difference and seasonal change of the fatty acid profiles of total particulate matters (TPMs) in the waters and in the

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gonad and soma of green-lipped mussels in Victoria Harbour and reference sites. Since TPMs in the water are a food source for the mussels, the impact of the TPMs to the fatty acid profiles of the gonad and soma of green-lipped mussels was assessed.

MATERIALS AND METHODS Sample Collection During each campling, twenty individuals of the green-lipped mussel Perna viridis with shell length of 65–85 mm were collected from four locations at Tsim Sha Tsui (TST), North Point (NP), Kwun Tong (KT), Central (C) in Victoria Harbour and two reference sites outside the harbour at Peng Chau (PC) and Tung Lung Chau (TLC) (Figure 1). At the same time, 20 litres of seawater were also collected from each site. The sampling occurred from September 2004 to July 2005 and was conducted every two months. After collection, the feeding and digestive system of Perna viridis were cleared in filtered seawater until no faeces was produced. The mussels were then put into a freezer at -20ºC, to await further analysis.

Figure 1. The six sampling locations in Victoria Harbour.

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5

Measurement of Physical and Chemical Factors of Water Samples At each site, temperature, dissolve oxygen, pH and salinity of the water were measured during each visit. One litre of water was collected at sub-surface (0.5 m below surface) for determination of chlorophyll a concentration, according to the method from Eaton et al. (1995). Three 60 ml bottles of water were also sampled to determine the level of ammonia, nitrate (NO3-) and phosphate (PO43-) concentrations, according to the method from Eaton et al. (1995).

Fatty Acid Analysis Preparation of Water Samples Fifteen litres of water were collected at each sampling location and divided into three aliquots so that five litres of water formed one replicate sample. The water was filtered through ashed glass fibre filter paper, with 0.6 µm pore size and 90 mm diameter. The suspended particulate matters in the water were collected on the filter paper. The remains on the filter paper were used for lipid extraction after filtration. Preparation of Mussel Samples The shells of Perna viridis were removed and all soft tissue was rinsed with water to remove byssal threads and salts. Twenty mussels were pooled together. The tissues of 20 mussels were separated into gonad and somatic tissues (remaining tissues). The tissues were dried in an oven at 45ºC for 72 hours. The gonado-somatic index (GSI) was calculated according to the following equation: GSI = (dried weight of gonad / dried weight of whole tissue) x 100% All the dried tissues were ground into fine particles and used for fatty acid analysis.

Lipid Extraction and Quantification For total lipid extraction, around 200 mg of dry tissue of each tissue part were used following a slightly modified method according to Bligh and Dyer (Bligh and Dyer 1959). Lipid was extracted by 5 ml 2:1 chloroform-methanol solvent mixture (v/v) overnight. The mixed crude extract was then washed with 0.04% CaCl2 solution (0.2 of the crude extract‘s volume) so that a top aqueous and a bottom organic layer were formed. These two layers were separated by centrifugation. The upper aqueous layer was removed. Five ml of petroleum ether was added and dried with a stream of nitrogen and the extract was further dried overnight in a vacuum desiccator for the determination of total lipids. Fatty acid Analysis and Quantification Fatty acid methyl esters (FAMEs) of total lipids were also determined following a modified method of Bligh and Dyer (1959). 2.5 ml of 2% sulphuric acid (H2SO4) in methanol was added to the lipid extract and the solution was incubated in an oven at 80ºC for two hours. After cooling, 1 ml distilled water and 2 ml petroleum ether were added to the tube and

6

S. G. Cheung and P. K. S. Shin

mixed with a vortex. The upper organic layer was transferred to a vial and dried using a nitrogen stream with a very slow flow rate to keep from blowing the FAMEs away. Then FAMEs were analyzed using an Agilent 5890 series GC-FID with an autosampler and DB225-MS capillary column (30 m, 0.25 mm internal diameter, 0.20 m film thickness). Authentic methylated fatty acid standards were purchased from Sigma and Supelco. Methyl nonadecanoate (19:0) was used as an internal standard. Standard FAMEs (Supelco) solution (20–240 ppm) was also prepared and 15 ppm internal standard was added. Therefore, for each standard FAME, a calibration curve between the peak area of this specific FAME and the peak area of the internal standard was established in order to calculate the concentration of the FAMEs in the lipid extract. The operating conditions for the GC-FID were as follows: split-injection mode was used with injector being held at 230ºC. Initial temperature was 50ºC for two minutes, then from 50ºC to 210ºC at 4ºC min-1, where the temperature was held at 210ºC for an additional 50 minutes. The detector was held at 230ºC and helium was used as the carrier gas with a flow rate of 1 ml min-1. A sample of 2 l was injected into the GC-FID for each analysis.

Statistical Analyses Data on the fatty acid profiles of TPMs in the waters, as well as the gonads and somatic tissue of green-lipped mussels were used to calculate the mean percentage of Bray-Curtis similarity among different samplings from the various sites (Bray and Curtis 1957). Significant differences among sites, or seasonal variations, were also tested by analysis of similarity (ANOSIM) from the software PRIMER (Clarke and Warwick 2001). Based on the similarity values, hierarchical cluster analyses using the group-average sorting method were performed to show inter-site differences and seasonal changes in fatty acid profiles of TPMs and the gonad and soma of mussels in Victoria Harbour and the reference sites. Repeatedmeasures Multivariate Analysis of Variance (MANOVA) with Tukey test for multiple comparisons were used to compare the differences in the percentages of individual fatty acids of TPMs in waters and the gonad and soma of mussels collected from Victoria Harbour and reference sites. Data were arcsin square root transformed prior to analysis to conform to data normality (Zar 1996). Correlations between fatty acid profiles in TPMs and mussels, as well as the physico-chemical parameters, were tested by Pearson correlation analysis. All statistical analyses were performed with the software SPSS 12.0 for Windows (SPSS Inc. 2002) and PRIMER 5.0 (Clarke and Warwick 2001).

RESULTS Physico-Chemical Parameters of Waters in Victoria Harbour and Reference Sites Figure 2 shows temporal variations in water temperature at the six sampling sites. The trend was similar among all the sites, with temperatures decreasing gradually from September 2004 to their lowest values in March 2005. After March 2005, temperatures increased to a

Inter-Site Differences and Seasonal Patterns…

7

maximum in July. Lower dissolved oxygen levels were obtained at NP and KT, while higher levels were obtained at the reference sites, PC and TLC (Figure 3) where the temporal variation of dissolved oxygen levels was the smallest (6.6–7.6 mg l-1). For pH, no temporal variation was observed with higher values being obtained at the reference sites (8.1–8.6) than sites in Victoria Harbour (7.6–8.4). For salinity, lower values were obtained in the summer, from May through July (21–35 ‰), as compared with other seasons (30–37 ‰) (Figure 4).

Figure 2. Temperature (ºC) of waters collected from reference sites (PC and TLC) and Victoria Harbour. PC: Peng Chau, C: Central, TST: Tsim Sha Tsui, KT: Kwun Tong, TLC: Tung Lung Chau.

Figure 3. Concentration of dissolved oxygen (mg l-1) in waters collected from reference sites (PC and TLC) and Victoria Harbour. PC: Peng Chau, C: Central, TST: Tsim Sha Tsui, KT: Kwun Tong, TLC: Tung Lung Chau.

S. G. Cheung and P. K. S. Shin

8

Figure 4. Salinity (‰) of waters collected from reference sites (PC and TLC) and Victoria Harbour. PC: Peng Chau, C: Central, TST: Tsim Sha Tsui, KT: Kwun Tong, TLC: Tung Lung Chau.

Table 1. Multiple comparisons of repeated-measures MANOVA for physico-chemical parameters of waters from Victoria Harbour and references sites. Letter „a‟ represents the highest concentration of each fatty acid. The same letter means that no significant difference existed between the sites (p > 0.05). PC: Peng Chau, TLC: Tung Lung Chau, C: Central, TST: Tsim Sha Tsim, NP: North Point, KT: Kwun Tong; mm/yy represents month/year (e.g., 09/04 = September 2004) Wilk‘s λ

p-value

Multiple comparison

Chlorophyll a

0.00

< 0.001

KTa PCb TLCc TSTd NPe Cf

Ammonia

0.01

< 0.001

KTa Cb NPbc TSTc PCd TLCe

Nitrate

0.06

< 0.001

KTa PCb TSTb Cb NPb TLCb

Phosphate

0.03

< 0.001

KTa TSTb Cb NPb PCbc TLCc

Chlorophyll a

0.00

< 0.001

07/05a 09/04b 11/04c 01/05d 05/05d 03/05d

Ammonia

0.00

< 0.001

07/05a 09/04b 11/04c 01/05d 05/05d 03/05d

Nitrate

0.02

< 0.001

05/05a 07/05a 03/05b 01/05b 11/04b 09/04b

Phosphate

0.01

< 0.001

01/05a 11/04a 05/05ab 07/05ab 09/04b 03/05b

Physico-chemical parameters Inter-site difference

Seasonal change

Inter-Site Differences and Seasonal Patterns…

9

Figure 5 shows the chlorophyll concentration and Figure 6 the nutrient contents at the study sites. Inter-site differences in chlorophyll a and nutrient contents were observed, with highest values being obtained from KT and the lowest from TLC, except for chlorophyll a (Table 1). For seasonal differences, the concentrations of chlorophyll a and ammonia were the highest in July but the lowest in January, March and May. The concentration of nitrate was the highest in the summer (May through July), whereas the concentration of phosphate was the highest in the winter (January and November).

Figure 5. Concentration of chlorophyll a (mg m-3) in waters collected from reference sites (PC and TLC) and Victoria Harbour (Mean ± 1SD, n = 3). PC: Peng Chau, C: Central, TST: Tsim Sha Tsui, KT: Kwun Tong, TLC: Tung Lung Chau.

Fatty Acid Profiles of Total Particulate Matters in Waters from Victoria Harbour and Reference Sites Tables 2–7 show the fatty acid profiles of TPMs in waters collected from the reference sites and Victoria Harbour from September 2004 to July 2005. In general, the fatty acid profile of TPMs in waters from Victoria Harbour and reference sites during the sampling period was mainly composed of SFA (23–75 % for C, TST, NP and KT; 27–88% for PC and TLC). The main SFAs in waters were 16:0 and 18:0. PUFAs were present in moderate level (9– 56% for C, TST, NP and KT; 5–64% for PC and TLC). The main PUFAs were 18:2n6, 18:3n3, 20:5n3 and 22:6n3. MUFAs (9–43% for C, TST, NP and KT; 2–28% for PC and TLC) were present at minimum levels and mainly dominated by 16:1n7 and 18:1n9.

10

S. G. Cheung and P. K. S. Shin

Figure 6. Concentration of ammonia, nitrate and phosphate (ppm) in waters collected from reference sites (PC and TLC) and Victoria Harbour (Mean ± 1SD, n = 3). PC: Peng Chau, C: Central, TST: Tsim Sha Tsui, KT: Kwun Tong, TLC: Tung Lung Chau.

Inter-Site Differences and Seasonal Patterns…

11

Table 2. Fatty acid profiles (%) of total particulate matters in waters from Peng Chau (Mean ± 1SD; n = 3). SFA: saturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid; ND: not detected Fatty acids

09/04

11/04

01/05

03/05

05/05

07/05

14:0

2.63 ± 0.42

1.06 ± 0.92

ND

ND

ND

ND

15:0

ND

ND

ND

3.25 ± 0.32

ND

ND

16:0

29.64 ± 1.83

27.64 ± 1.83

18.92 ± 0.64

23.95 ± 4.03

14.98 ± 0.88

39.31 ± 2.03

17:0

1.03 ± 0.13

2.41 ± 0.28

ND

1.30 ± 0.05

2.99 ± 0.37

ND

18:0

51.07 ± 2.60

31.26 ± 0.55

7.64 ± 3.26

31.28 ± 2.09

16.99 ± 1.61

17.52 ± 4.78

20:0

3.33 ± 0.31

ND

ND

ND

13.78 ± 0.29

ND

SFA

87.7 ± 1.23

62.37 ± 2.51

26.56 ± 2.70

58.49 ± 5.90

48.75 ± 2.75

56.83 ± 5.96

15:1

ND

ND

ND

ND

ND

ND

16:1n7

1.70 ± 0.48

0.73 ± 0.38

2.42 ± 1.05

0.00

4.05 ± 0.07

14.66 ± 2.48

18:1n9

4.59 ± 0.76

3.14 ± 0.59

5.30 ± 0.42

2.32 ± 0.50

3.67 ± 0.03

10.17 ± 2.04

18:1n7

0.86 ± 0.26

ND

1.93 ± 0.08

ND

ND

3.43 ± 0.26

20:1n9

ND

ND

ND

4.03 ± 1.62

ND

ND

MUFA

7.15 ± 1.43

3.88 ± 0.53

9.65 ± 1.50

6.36 ± 2.01

7.72 ± 0.10

28.27 ± 4.71

18:2n6

1.90 ± 0.76

10.60 ± 0.51

11.50 ± 1.33

8.05 ± 1.22

0.00

3.98 ± 1.52

18:3n3

1.34 ± 0.22

16.67 ± 2.48

13.88 ± 2.75

15.59 ± 1.53

10.95 ± 1.46

10.91 ± 0.27

20:2

ND

ND

ND

ND

ND

ND

20:3n3

ND

ND

ND

ND

ND

ND

20:3n6

ND

ND

ND

ND

14.40 ± 0.52

ND

20:5n3

1.90 ± 0.19

6.47 ± 0.75

26.26 ± 0.65

10.21 ± 1.26

18.18 ± 0.91

ND

22:6n3

ND

ND

12.15 ± 1.70

ND

ND

ND

PUFA

5.15 ± 0.62

33.75 ± 2.99

63.79 ± 1.87

33.85 ± 3.96

43.53 ± 2.84

14.90 ± 1.30

S. G. Cheung and P. K. S. Shin

12

Table 3. Fatty acid profiles (%) of total particulate matters in waters from Tung Lung Chau (Mean ± 1SD; n = 3). SFA: saturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid; ND: not detected Fatty acids

09/04

11/04

01/05

03/05

05/05

07/05

14:0

1.22 ± 0.50

3.52 ± 0.38

ND

ND

1.08 ± 0.89

3.40 ± 2.48

15:0

ND

ND

ND

1.44 ± 0.99

ND

ND

16:0

31.16 ± 0.98

31.98 ± 1.48

26.57 ± 3.47

26.91 ± 0.78

17.87 ± 1.36

21.11 ± 1.41

17:0

0.66 ± 0.14

0.10 ± 0.12

ND

2.14 ± 0.23

0.99 ± 1.71

ND

18:0

37.89 ± 4.33

55.74 ± 4.02

21.61 ± 2.72

34.87 ± 2.03

19.09 ± 0.89

8.13 ± 1.42

20:0

4.09 ± 0.56

ND

ND

ND

ND

12.09 ± 0.75

SFA

75.01 ± 3.23

92.24 ± 2.26

48.18 ± 5.18

65.36 ± 2.97

39.02 ± 4.00

44.73 ± 1.29

15:1

ND

ND

ND

ND

ND

ND

16:1n7

0.19 ± 0.18

0.25 ± 0.29

ND

ND

7.03 ± 0.88

13.52 ± 1.99

18:1n9

4.34 ± 0.44

1.51 ± 0.16

9.75 ± 1.28

4.07 ± 0.20

1.99 ± 0.56

3.41 ± 0.80

18:1n7

0.84 ± 0.11

ND

ND

1.04 ± 0.11

1.19 ± 0.23

2.06 ± 0.17

20:1n9

ND

ND

ND

ND

ND

ND

MUFA

5.37 ± 0.69

1.76 ± 0.31

9.75 ± 1.28

5.11 ± 0.09

10.21 ± 1.50

18.99 ± 1.67

18:2n6

2.59 ± 0.42

2.26 ± 1.07

21.19 ± 3.50

11.56 ± 1.92

0.00

0.39 ± 0.06

18:3n3

2.02 ± 0.24

3.75 ± 1.16

20.87 ± 0.78

17.98 ± 2.14

9.11 ± 3.54

3.65 ± 0.42

20:2

ND

ND

ND

ND

ND

ND

20:3n3

ND

ND

ND

ND

ND

ND

20:3n6

ND

ND

ND

ND

16.43 ± 2.78

0.00

20:5n3

2.38 ± 0.49

ND

ND

ND

25.22 ± 3.08

32.25 ± 0.63

22:6n3

12.64 ± 3.10

ND

ND

ND

ND

ND

PUFA

19.63 ± 2.55

6.01 ± 2.16

42.07 ± 3.90

29.54 ± 2.98

50.76 ± 5.50

36.28 ± 0.42

Inter-Site Differences and Seasonal Patterns…

13

Table 4. Fatty acid profiles (%) of total particulate matters in waters from Central (Mean ± 1SD; n = 3). SFA: saturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid; ND: not detected Fatty acids

09/04

11/04

01/05

03/05

05/05

07/05

14:0

1.40 ± 1.03

1.21 ± 0.52

ND

ND

ND

ND

15:0

ND

ND

ND

ND

ND

ND

16:0

28.38 ± 1.17

20.69 ± 0.58

16.18 ± 0.93

25.61 ± 2.63

19.17 ± 1.29

29.25 ± 0.95

17:0

1.06 ± 0.27

2.42 ± 1.10

ND

ND

2.01 ± 0.19

ND

18:0

41.07 ± 3.41

23.65 ± 2.17

9.66 ± 1.35

30.91 ± 1.56

21.57 ± 1.32

18.17 ± 1.37

20:0

3.25 ± 0.49

ND

ND

ND

12.63 ± 0.83

ND

SFA

75.16 ± 2.50

47.97 ± 1.29

25.84 ± 2.16

56.52 ± 4.19

55.38 ± 1.63

47.42 ± 1.83

15:1

ND

ND

ND

1.51 ± 1.12

ND

ND

16:1n7

1.85 ± 0.38

1.72 ± 0.12

ND

0.30 ± 0.29

ND

9.65 ± 0.73

18:1n9

8.76 ± 1.85

10.43 ± 0.72

16.96 ± 0.55

11.12 ± 0.21

5.96 ± 0.86

10.66 ± 2.33

18:1n7

1.60 ± 0.34

0.92 ± 0.11

2.11 ± 0.18

1.66 ± 0.29

1.38 ± 0.07

1.94 ± 0.26

20:1n9

ND

2.33 ± 0.15

ND

ND

ND

ND

MUFA

12.21 ± 2.40

15.40 ± 0.81

19.06 ± 0.37

13.08 ± 0.03

8.84 ± 1.72

22.25 ± 1.78

18:2n6

5.32 ± 0.94

15.51 ± 3.60

17.34 ± 0.83

14.66 ± 1.75

5.06 ± 0.84

4.97 ± 2.46

18:3n3

1.16 ± 0.55

12.25 ± 0.61

6.46 ± 0.47

13.10 ± 1.23

11.45 ± 1.23

6.53 ± 0.66

20:2

ND

ND

ND

ND

ND

ND

20:3n3

ND

ND

ND

ND

ND

ND

20:3n6

ND

ND

ND

ND

19.27 ± 3.03

18.83 ± 3.70

20:5n3

2.20 ± 0.48

4.04 ± 0.34

18.79 ± 2.13

2.64 ± 4.57

ND

ND

22:6n3

3.96 ± 1.02

4.83 ± 0.70

12.51 ± 0.72

ND

ND

ND

PUFA

12.63 ± 2.68

36.63 ± 2.10

55.10 ± 2.53

30.40 ± 4.17

35.78 ± 2.19

30.33 ± 3.23

S. G. Cheung and P. K. S. Shin

14

Table 5. Fatty acid profiles (%) of total particulate matters in waters from Tsim Sha Tsui (Mean ± 1SD; n = 3). SFA: saturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid; ND: not detected Fatty acids

09/04

11/04

01/05

03/05

05/05

07/05

14:0

1.20 ± 0.96

0.73 ± 0.12

ND

ND

ND

1.14 ± 1.97

15:0

ND

ND

ND

1.95 ± 1.41

ND

ND

16:0

29.38 ± 2.68

12.66 ± 0.10

13.75 ± 2.23

22.41 ± 0.96

18.24 ± 0.98

20.50 ± 1.85

17:0

0.88 ± 0.14

0.00

0.67 ± 0.11

1.42 ± 0.68

2.42 ± 1.49

0.00

18:0

41.88 ± 1.94

7.75 ± 0.26

4.97 ± 1.03

22.71 ± 2.56

20.58 ± 0.80

8.91 ± 2.13

20:0

3.71 ± 0.78

3.87 ± 0.52

7.62 ± 0.55

ND

13.02 ± 1.60

ND

SFA

73.34 ± 2.62

25.01 ± 0.58

27.00 ± 2.77

48.50 ± 2.79

54.27 ± 1.03

30.55 ± 2.01

15:1

ND

ND

ND

ND

ND

ND

16:1n7

1.46 ± 0.43

1.71 ± 0.12

ND

ND

3.91 ± 0.38

16.00 ± 3.19

18:1n9

10.63 ± 0.94

38.04 ± 0.46

30.78 ± 0.89

18.38 ± 1.57

7.25 ± 1.79

5.03 ± 2.00

18:1n7

1.46 ± 0.42

1.17 ± 0.02

ND

1.13 ± 0.06

1.58 ± 0.10

1.98 ± 0.25

20:1n9

ND

2.08 ± 0.42

2.81 ± 0.63

ND

ND

ND

MUFA

13.55 ± 1.33

43.01 ± 0.23

33.59 ± 1.49

19.51 ± 1.63

12.74 ± 1.77

23.01 ± 3.37

18:2n6

5.18 ± 1.65

24.48 ± 0.43

25.47 ± 0.38

16.12 ± 1.06

4.19 ± 0.87

1.32 ± 0.71

18:3n3

0.92 ± 0.20

6.60 ± 0.29

5.67 ± 0.28

8.93 ± 0.27

13.60 ± 2.10

4.85 ± 0.98

20:2

ND

ND

ND

ND

ND

ND

20:3n3

ND

ND

ND

ND

ND

ND

20:3n6

ND

ND

ND

ND

15.19 ± 1.82

ND

20:5n3

1.84 ± 0.40

ND

8.27 ± 0.72

6.95 ± 0.59

ND

40.27 ± 0.96

22:6n3

1.45 ± 0.34

ND

ND

ND

ND

ND

PUFA

9.40 ± 2.15

31.08 ± 0.72

39.41 ± 1.28

31.99 ± 1.43

32.97 ± 1.07

46.44 ± 1.88

Inter-Site Differences and Seasonal Patterns…

15

Table 6. Fatty acid profiles (%) of total particulate matters in waters from North Point (Mean ± 1SD; n = 3). SFA: saturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid; ND: not detected Fatty acids

09/04

11/04

01/05

03/05

05/05

07/05

14:0

0.31 ± 0.29

0.60 ± 0.50

ND

0.02 ± 0.02

ND

0.73 ± 0.97

15:0

ND

ND

ND

ND

ND

ND

16:0

26.03 ± 0.45

23.62 ± 0.28

17.87 ± 1.63

20.73 ± 1.90

15.08 ± 0.24

21.31 ± 0.50

17:0

0.60 ± 0.06

ND

0.42 ± 0.73

ND

2.83 ± 2.28

ND

18:0

31.42 ± 1.65

23.07 ± 1.51

10.64 ± 1.82

21.79 ± 2.26

17.34 ± 1.71

10.38 ± 1.20

20:0

3.47 ± 0.49

5.24 ± 0.67

ND

ND

10.12 ± 2.84

ND

SFA

61.83 ± 1.24

52.53 ± 1.70

28.93 ± 0.21

42.54 ± 4.14

45.37 ± 0.94

32.42 ± 1.42

15:1

ND

ND

ND

ND

1.71 ± 0.28

ND

16:1n7

1.34 ± 0.17

2.90 ± 0.21

0.71 ± 0.64

0.85 ± 0.37

3.24 ± 0.42

13.48 ± 1.50

18:1n9

18.56 ± 0.95

15.07 ± 1.79

25.32 ± 2.82

18.63 ± 1.78

16.53 ± 2.90

6.42 ± 1.00

18:1n7

1.59 ± 0.06

2.18 ± 0.45

2.07 ± 0.13

1.31 ± 0.11

1.39 ± 0.06

3.17 ± 0.33

20:1n9

ND

ND

3.13 ± 0.81

2.52 ± 1.00

ND

ND

MUFA

21.49 ± 0.85

20.15 ± 1.60

31.23 ± 2.50

23.30 ± 0.97

22.87 ± 3.35

23.07 ± 2.53

18:2n6

11.33 ± 0.40

12.92 ± 0.53

23.72 ± 1.03

17.07 ± 1.57

9.26 ± 0.51

2.86 ± 0.88

18:3n3

1.45 ± 0.19

6.13 ± 0.21

5.69 ± 1.31

8.26 ± 0.30

8.73 ± 2.75

0.00

20:2

ND

ND

ND

ND

ND

ND

20:3n3

ND

ND

ND

ND

ND

ND

0:3n6

ND

ND

ND

ND

13.77 ± 0.40

ND

20:5n3

1.74 ± 0.28

4.28 ± 0.46

10.42 ± 2.11

5.68 ± 1.03

ND

41.65 ± 1.18

22:6n3

2.15 ± 0.46

3.99 ± 0.34

ND

3.15 ± 1.71

ND

ND

PUFA

14.53 ± 0.62

27.31 ± 0.21

39.83 ± 2.53

34.16 ± 3.41

31.76 ± 3.17

44.51 ± 2.01

S. G. Cheung and P. K. S. Shin

16

Table 7. Fatty acid profiles (%) of total particulate matters in waters from Kwun Tong (Mean ± 1SD; n = 3). SFA: saturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid; ND: not detected Fatty acids

09/04

11/04

01/05

03/05

05/05

07/05

14:0

8.42 ± 0.14

1.99 ± 0.02

0.01 ± 0.01

ND

ND

5.43 ± 0.23

15:0

ND

ND

ND

ND

ND

ND

16:0

30.84 ± 0.26

19.87 ± 0.39

17.46 ± 0.40

25.68 ± 3.22

16.70 ± 1.21

13.78 ± 1.73

17:0

0.50 ± 0.06

0.55 ± 0.13

0.35 ± 0.50

1.66 ± 1.13

5.32 ± 0.81

0.00

18:0

23.46 ± 4.46

10.65 ± 1.90

5.29 ± 1.25

28.25 ± 1.54

19.90 ± 1.38

3.00 ± 0.61

20:0

4.07 ± 0.54

1.62 ± 0.11

ND

ND

10.13 ± 0.67

1.42 ± 2.46

SFA

67.30 ± 4.37

34.13 ± 2.19

23.11 ± 1.72

55.59 ± 1.27

52.05 ± 1.37

23.64 ± 3.94

15:1

ND

ND

ND

ND

3.16 ± 1.01

ND

16:1n7

12.02 ± 1.19

5.88 ± 0.26

7.64 ± 0.75

1.38 ± 1.28

3.30 ± 0.68

16.49 ± 1.37

18:1n9

5.37 ± 0.89

29.48 ± 2.00

27.37 ± 1.92

6.79 ± 1.67

7.49 ± 0.73

3.13 ± 0.82

18:1n7

1.40 ± 0.22

2.75 ± 0.20

3.29 ± 0.05

1.76 ± 0.66

1.74 ± 0.13

1.11 ± 0.05

20:1n9

ND

1.27 ± 0.08

2.02 ± 0.54

ND

ND

ND

MUFA

18.79 ± 2.20

39.38 ± 2.48

40.32 ± 1.91

9.93 ± 1.93

15.68 ± 0.76

20.72 ± 2.17

18:2n6

2.65 ± 0.25

17.37 ± 0.72

19.55 ± 1.25

11.62 ± 1.60

7.34 ± 1.80

0.86 ± 0.05

18:3n3

0.76 ± 0.14

2.89 ± 0.33

3.51 ± 0.84

13.29 ± 0.53

11.14 ± 0.85

1.43 ± 0.23

20:2

ND

ND

ND

ND

ND

ND

20:3n3

ND

ND

ND

ND

ND

ND

20:3n6

ND

ND

ND

ND

12.61 ± 0.86

ND

20:5n3

7.57 ± 1.71

2.26 ± 0.22

6.25 ± 0.19

9.56 ± 1.82

ND

24.92 ± 5.39

22:6n3

2.93 ± 0.54

3.42 ± 0.82

5.50 ± 1.75

ND

ND

28.43 ± 0.65

PUFA

13.90 ± 2.22

25.94 ± 0.35

34.81 ± 1.06

34.48 ± 2.80

31.08 ± 1.58

55.64 ± 5.10

Inter-Site Differences and Seasonal Patterns…

17

Inter-Site Difference and Seasonal Changes in Fatty Acid Profiles of Total Particulate Matters in Waters from Victoria Harbour and Reference Sites The results of analysis of similarity (ANOSIM) showed that there were significant intersite differences in the fatty acid profiles of TPMs in waters from the six sampling sites in Victoria Harbour and reference sites (Global test of ANOSIM, R = 0.972, p = 0.001). Similarly, the fatty acid profiles of TPMs in waters were also significantly different from each other (Global test of ANOSIM, R = 0.998, p = 0.001) among the six sampling months.

Figure 7. Similarity (%) of the fatty acid profiles of total particulate matters (TPM) in waters from Victoria Harbour and reference sites collected from September 2004 to July 2005. PC: Peng Chau, NP: North Point, KT: Kwun Tong, TST: Tsim Sha Tsui, C: Central, TLC: Tung Lung Chau; 09: Sept. 04, 11: Nov. 04, 01: Jan. 05, 03: Mar. 05, 05: May 05, 07: Jul. 05; W: TPMs in waters.

Hierarchical cluster analysis of the fatty acid profiles of TPMs in waters from Victoria Harbour and reference sites mainly separated the sampling period (September 2004 to July 2005) into four temporal groups at a similarity level of 60% (Figure 7). Group 1 comprised the fatty acid profiles of TPMs collected from PC, NP, TST and TLC in September 2004 and November 2004, and all sites in March 2005. Group 2 mainly contained all sites for May 2005 samplings. Group 3 mainly consisted of NP, KT, TST and C samples in January 2005. Group 4 largely comprised KT, TST, C and TLC samples in July 2005. Repeated-measures MANOVA were performed to find the overall inter-site and seasonal differences in each chosen fatty acid in TPMs from waters. For inter-site difference, the percentages of SFAs 15:0, 16:0 and 18:0, and PUFA 18:3n3 collected from reference sites (PC and TLC) were significantly higher than those from Victoria Harbour (C, TST, NP and KT) except 15:0 at TST, 16:0 at C and 18:3n3 at KT. The percentage of SFA 14:0 was significantly higher for KT and TLC. For SFA 20:0 and MUFA 20:1n9, the percentages were higher in Victoria Harbour than at the reference sites, except KT. For MUFAs 18:1n9 and 18:1n7 and PUFA 18:2n6, their percentages from the sites in Victoria Harbour were significantly higher than from the two reference sites. For MUFA 18:1n9 and PUFA 18:2n6, the percentages were significantly higher for TST and NP than C and KT. For MUFA 18:1n7, the percentages were significantly higher for NP and KT than C and TST. In KT, the percentages of MUFA 16:1n7 and PUFAs 20:5n3 and 22:6n3 were the highest among all the sampling sites. For seasonal difference, the percentages of SFAs 14:0, 16:0 and 18:0 were the highest in September 2004. For SFA 14:0, the percentage was the lowest in January, March and May

18

S. G. Cheung and P. K. S. Shin

2005. For SFA 16:0, the percentage was the lowest in January and May 2005. For SFA 18:0, the percentage was the lowest in January and July 2005. For SFA 17:0, the percentages were the highest in May 2005. For MUFA 16:1n7, the percentage was significantly higher in the summer period (May 2005 and July 2005) than in the winter months (November 2004, January 2005 and March 2005). In contrast, the percentages of MUFAs 18:1n9 and 20:1n9 and PUFA 18:2n6 were significantly higher in the winter months than in summer. For MUFA 18:1n7 and PUFAs 20:5n3 and 22:6n3, the percentages were significantly higher in January 2005 and July 2005 than in the other months. For PUFAs 20:2, 20:3n3 and 20:4n6, they were not detected in TPMs in waters from all sites.

Fatty Acid Profiles in Gonad of Green Mussels from Victoria Harbour and Reference Sites Tables 8–13 show the fatty acid profiles of the gonad and soma of mussels collected from Victoria Harbour and reference sites from September 2004 to July 2005. For reference sites PC (Table 8) and TLC (Table 9), the fatty acid profile of the gonads of the mussels was composed mainly of SFAs (30–49%) and PUFAs (32–54%). MUFAs were present at a lower level (14–19%) compared with SFAs and PUFAs. For Victoria Harbour (NP, KT, TST, C) (Tables 10-13), the fatty acid profile of the gonad was mainly comprised of PUFAs (39– 55%), followed by SFAs (22–41%) and MUFAs (18–29%). The main SFAs present were 14:0, 16:0 and 18:0, the major MUFAs were 16:1n7, 18:1n9 and 20:1n9, and the dominant PUFAs were 18:2n6, 20:4n6, 20:5n3 and 22:6n3.

Inter-Site Difference and Seasonal Changes in Fatty Acid Profiles in Gonad of Green Mussels from Victoria Harbour and Reference Sites Analysis of similarity (ANOSIM) was carried out to show the seasonal changes and intersite differences in the fatty profiles in gonad of green mussels in Victoria Harbour and reference sites. The results showed that there were significant inter-site differences in the fatty acid profiles in the gonad of green mussels from the six sampling sites in Victoria Harbour and reference sites (Global test of ANOSIM, R = 0.941, p = 0.001). The fatty acid profiles in gonad of mussels were also significantly different from each other (Global test of ANOSIM, R = 0.931, p = 0.001), among the six sampling months. Hierarchical cluster analysis of the fatty acid profiles of the gonads of the mussels separated the data into two groups and one standalone sample (January 2005 sample from North Point) at a similarity level of 79% (Figure 8). Group 1 comprised the fatty acid profiles of the gonad collected mostly from the reference sites (PC and TLC), together with KT and two TST samples in Victoria Harbour. Group 2 comprised mainly mussels collected from NP, TST and C in Victoria Harbour, together with one sample from KT (May 2005) and TLC (March 2005), respectively.

Table 8. Fatty acid profiles (%) of gonad and soma of mussels from Peng Chau (Mean ± 1SD; n = 3). SFA: saturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid; ND: not detected

30.43 ± 0.40 1.39 ± 0.07 9.24 ± 0.32 ND

11/04 6.15 ± 0.53 0.20 ± 0.18 22.56 ± 2.39 1.06 ± 0.21 3.98 ± 1.47 ND

01/05 6.42 ± 0.63 0.13 ± 0.12 24.65 ± 1.16 1.34 ± 0.16 5.37 ± 0.10 ND

03/05 3.25 ± 0.35 0.09 ± 0.08 19.62 ± 0.88 1.35 ± 0.11 6.57 ± 0.48 ND

05/05 4.06 ± 0.31 0.20 ± 0.04 20.77 ± 1.00 1.24 ± 0.06 7.49 ± 0.71 ND

07/05 4.53 ± 0.29 0.33 ± 0.04 24.49 ± 0.45 1.33 ± 0.02 6.34 ± 0.16 ND

Soma 09/04 9.57 ± 0.50 0.25 ± 0.09 30.25 ± 0.96 1.52 ± 0.13 8.51 ± 0.65 ND

11/04 6.29 ± 1.05 0.25 ± 0.15 23.18 ± 3.39 1.26 ± 0.30 5.21 ± 0.78 ND

01/05 6.45 ± 0.40 0.02 ± 0.02 24.83 ± 0.26 1.53 ± 0.04 6.53 ± 0.29 ND

03/05 2.73 ± 0.45 0.15 ± 0.26 18.72 ± 0.95 1.59 ± 0.23 6.96 ± 0.72 ND

05/05 2.57 ± 0.34 0.03 ± 0.03 18.11 ± 1.13 1.54 ± 0.18 8.59 ± 1.03 ND

07/05 4.36 ± 0.70 0.09 ± 0.16 20.90 ± 1.13 1.34 ± 0.21 7.26 ± 0.73 ND

SFA

49.38 ± 0.93

33.95 ± 4.49

37.92 ± 2.07

30.89 ± 1.82

33.76 ± 1.40

37.02 ± 0.90

50.11 ± 0.66

36.19 ± 5.60

39.35 ± 0.57

30.16 ± 1.32

30.84 ± 1.91

33.95 ± 1.53

15:1

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

16:1n7

13.97 ± 0.60 0.77 ± 0.10 2.04 ± 0.08 1.98 ± 0.12 18.76 ± 0.85

12.97 ± 1.12 0.67 ± 0.13 2.04 ± 0.15 2.35 ± 0.25 18.04 ± 0.93

11.58 ± 0.38 0.96 ± 0.04 1.89 ± 0.03 2.78 ± 0.31 17.20 ± 0.14

8.09 ± 0.43 1.17 ± 0.03 1.87 ± 0.01 4.47 ± 0.02 15.61 ± 0.42

8.26 ± 0.13 1.08 ± 0.10 1.83 ± 0.04 5.36 ± 0.19 16.53 ± 0.29

10.46 ± 0.19 1.19 ± 0.03 1.87 ± 0.05 4.24 ± 0.05 17.77 ± 0.12

16.44 ± 1.47 0.92 ± 0.04 2.04 ± 0.05 2.04 ± 0.26 21.43 ± 1.44

11.88 ± 1.54 0.90 ± 0.15 1.79 ± 0.21 2.43 ± 0.17 17.00 ± 2.04

12.00 ± 0.21 1.10 ± 0.08 1.85 ± 0.04 3.72 ± 0.59 18.68 ± 0.39

6.64 ± 0.93 1.37 ± 0.20 1.59 ± 0.17 5.26 ± 0.35 14.87 ± 0.50

6.90 ± 0.38 1.27 ± 0.13 1.63 ± 0.13 6.05 ± 0.38 15.85 ± 0.47

9.96 ± 0.53 1.35 ± 0.15 1.90 ± 0.14 4.86 ± 0.27 18.07 ± 0.43

Fatty acids 14:0 15:0 16:0 17:0 18:0 20:0

18:1n9 18:1n7 20:1n9 MUFA

Gonad 09/04 8.32 ± 0.46 ND

Table 8. (Continued)

20:2

Gonad 09/04 1.22 ± 0.28 0.65 ± 0.07 ND

20:3n3

ND

20:3n6

ND

1.39 ± 0.18 ND

20:4n6

3.33 ± 0.27 16.75 ± 0.74 9.91 ± 1.01 31.85 ± 1.15

4.71 ± 0.63 23.47 ± 1.90 14.98 ± 1.43 48.01 ± 4.06

Fatty acids 18:2n6 18:3n3

20:5n3 22:6n3 PUFA

11/04 1.71 ± 0.11 1.76 ± 0.17 ND

01/05 1.72 ± 0.11 1.49 ± 0.26 ND

05/05 1.96 ± 0.15 1.64 ± 0.37 ND

ND

03/05 1.70 ± 0.04 1.93 ± 0.28 1.48 ± 0.11 ND

ND

ND

ND

07/05 1.81 ± 0.08 1.93 ± 0.02 1.16 ± 0.10 1.40 ± 0.23 ND

3.64 ± 0.18 22.32 ± 1.02 15.70 ± 1.06 44.83 ± 2.58

3.76 ± 0.04 26.64 ± 1.17 18.00 ± 0.86 53.51 ± 2.23

3.20 ± 0.49 22.64 ± 0.42 20.27 ± 1.50 49.71 ± 1.35

3.83 ± 0.17 16.79 ± 0.45 18.30 ± 0.59 44.05 ± 1.12

ND

Soma 09/04 1.49 ± 0.08 0.61 ± 0.45 ND

11/04 1.82 ± 0.21 1.53 ± 0.14 ND

01/05 2.08 ± 0.13 1.64 ± 0.26 ND

ND

ND

ND 3.49 ± 0.11 14.53 ± 1.08 8.33 ± 1.38 28.46 ± 2.09

05/05 2.27 ± 0.13 1.57 ± 0.42 ND

ND

03/05 1.74 ± 0.08 1.92 ± 0.38 0.48 ± 0.84 ND

ND

ND

ND

ND

07/05 2.08 ± 0.40 1.79 ± 0.24 1.18 ± 0.22 0.39 ± 0.67 ND

4.54 ± 0.46 18.71 ± 1.86 13.84 ± 1.05 40.43 ± 3.55

3.70 ± 0.14 18.65 ± 0.53 15.90 ± 0.23 41.97 ± 0.45

4.33 ± 0.35 24.34 ± 0.54 22.16 ± 0.95 53.06 ± 1.21

5.29 ± 0.51 20.12 ± 0.76 24.07 ± 1.61 53.31 ± 2.38

5.16 ± 0.23 15.27 ± 0.70 22.11 ± 2.38 47.98 ± 1.96

ND

Table 9. Fatty acid profiles (%) of gonad and soma of mussels from Tung Lung Chau (Mean ± 1SD; n = 3). SFA: saturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid; ND: not detected Gonad 09/04 4.87 ± 0.17 ND

11/04 3.05 ± 0.09 ND 21.08 ± 1.13 1.32 ± 0.13 5.04 ± 0.69 ND

01/05 4.36 ± 0.48 0.16 ± 0.14 23.72 ± 1.12 1.63 ± 0.04 5.47 ± 0.16 ND

03/05 1.93 ± 0.19 0.22 ± 0.06 22.18 ± 0.96 2.01 ± 0.16 7.36 ± 0.67 ND

05/05 3.82 ± 0.96 0.49 ± 0.32 19.61 ± 0.91 1.55 ± 0.15 6.58 ± 0.52 ND

07/05 4.81 ± 0.24 0.16 ± 0.14 19.21 ± 0.57 1.12 ± 0.01 7.81 ± 0.16 ND

Soma 09/04 4.73 ± 0.88 0.04 ± 0.06 26.39 ± 3.30 1.44 ± 0.19 7.98 ± 1.04 ND

29.46 ± 0.51 1.64 ± 0.20 9.09 ± 1.56 ND

SFA

45.08 ± 2.01

30.48 ± 1.99

35.35 ± 1.90

33.69 ± 1.98

32.04 ± 1.65

33.11 ± 0.91

15:1

ND

ND

ND

ND

ND

16:1n7

7.22 ± 0.55 1.41 ± 0.09 1.80 ± 0.12 3.98 ± 0.32 14.41 ± 0.47

7.78 ± 0.27 1.95 ± 0.07 1.82 ± 0.06 4.29 ± 0.17 15.84 ± 0.38

8.98 ± 0.31 1.99 ± 0.04 1.59 ± 0.04 3.92 ± 0.25 16.48 ± 0.07

5.16 ± 0.25 5.00 ± 0.05 1.51 ± 0.04 5.88 ± 0.11 17.55 ± 0.36

6.70 ± 0.68 1.77 ± 0.09 1.40 ± 0.07 5.80 ± 0.69 15.67 ± 0.37

Fatty acids 14:0 15:0 16:0 17:0 18:0 20:0

18:1n9 18:1n7 20:1n9 MUFA

11/04 2.18 ± 0.51 ND

01/05 2.30 ± 1.39 ND

03/05 ND ND

05/05 4.13 ± 1.43 ND

20.64 ± 0.79 1.86 ± 0.14 6.55 ± 0.68 ND

19.35 ± 0.05 1.84 ± 0.09 6.18 ± 0.25 ND

13.77 ± 1.90 2.12 ± 0.53 6.37 ± 0.84 ND

21.18 ± 3.98 1.87 ± 0.14 7.91 ± 0.33 ND

07/05 7.54 ± 0.97 0.25 ± 0.16 21.55 ± 1.13 1.41 ± 0.11 7.92 ± 0.33 ND

40.57 ± 5.30

31.23 ± 0.84

29.67 ± 1.07

22.26 ± 3.24

35.08 ± 5.07

38.66 ± 1.28

ND

ND

ND

ND

ND

ND

ND

9.36 ± 0.38 1.13 ± 0.03 2.25 ± 0.02 4.22 ± 0.18 16.96 ± 0.32

7.37 ± 0.81 1.68 ± 0.15 1.90 ± 0.17 4.04 ± 0.42 15.00 ± 1.44

6.39 ± 0.29 3.03 ± 0.17 1.47 ± 0.10 5.34 ± 0.28 16.23 ± 0.32

5.91 ± 0.04 2.80 ± 0.25 1.31 ± 0.04 5.14 ± 0.24 15.15 ± 0.32

1.58 ± 0.47 3.25 ± 0.42 0.89 ± 0.12 7.59 ± 0.39 13.32 ± 0.95

7.28 ± 1.97 2.09 ± 0.04 1.25 ± 0.01 5.67 ± 1.13 16.29 ± 0.89

13.61 ± 0.56 1.29 ± 0.13 2.21 ± 0.11 3.06 ± 0.09 20.17 ± 0.87

Table 9. (Continued) Gonad

Soma

Fatty acids

09/04

11/04

01/05

03/05

05/05

07/05

09/04

11/04

01/05

03/05

05/05

07/05

18:2n6

1.83 ± 0.17

2.57 ± 0.03

2.58 ± 0.13

4.06 ± 0.14

2.37 ± 0.04

1.64 ± 0.03

2.20 ± 0.16

3.70 ± 0.18

3.70 ± 0.20

4.11 ± 0.14

3.43 ± 0.15

1.99 ± 0.23

18:3n3

1.20 ± 0.38 ND

1.46 ± 0.06 ND

1.26 ± 0.05 ND

1.17 ± 0.18 ND

0.46 ± 0.01 ND

0.77 ± 0.16 ND

1.59 ± 0.33 ND

1.83 ± 0.28 ND

1.87 ± 0.25 ND

0.19 ± 0.32 ND

20:3n3

1.15 ± 0.06 1.56 ± 0.16 ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

20:3n6

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

0.55 ± 0.13 0.98 ± 0.07 1.48 ± 0.11 ND

20:4n6

3.81 ± 0.03 13.82 ± 1.04 18.34 ± 1.31 40.51 ± 2.17

6.28 ± 0.44 19.19 ± 0.11 24.44 ± 1.91 53.68 ± 2.25

5.31 ± 0.37 19.47 ± 0.89 19.35 ± 0.50 48.18 ± 1.90

4.86 ± 0.08 16.08 ± 0.75 22.50 ± 1.08 48.76 ± 1.96

4.28 ± 0.62 18.80 ± 0.80 25.66 ± 0.82 52 29 ± 1.55

5.60 ± 0.08 26.36 ± 0.61 15.86 ± 0.61 54.15 ± 1.24

4.98 ± 0.54 17.40 ± 0.97 24.26 ± 0.89 49.62 ± 2.43

7.67 ± 0.46 15.38 ± 0.12 24.20 ± 0.37 52.54 ± 0.88

7.78 ± 0.27 15.89 ± 0.05 25.98 ± 0.35 55.17 ± 0.98

8.87 ± 0.38 14.60 ± 0.61 34.96 ± 2.76 64.42 ± 3.36

5.74 ± 0.97 14.47 ± 1.45 24.80 ± 3.88 48.63 ± 5.90

5.23 ± 0.23 18.69 ± 1.12 12.25 ± 1.18 41.17 ± 2.05

20:2

20:5n3 22:6n3 PUFA

Table 10. Fatty acid profiles (%) of gonad and soma of mussels from North Point (Mean ± 1SD; n = 3). SFA: saturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid Gonad

Soma

Fatty acids

09/04

11/04

01/05

03/05

05/05

07/05

09/04

11/04

01/05

03/05

05/05

07/05

14:0

2.94 ± 0.47 ND

0.21 ± 0.13 0.02 ± 0.02 16.49 ± 0.48 1.01 ± 0.07 4.88 ± 0.24 ND 22.61 ± 0.81

1.99 ± 0.77 0.27 ± 0.43 17.33 ± 2.43 1.25 ± 0.08 6.10 ± 0.35 ND 26.93 ± 3.19

1.23 ± 1.00 0.18 ± 0.23 16.23 ± 3.03 1.25 ± 0.09 5.59 ± 0.61 ND 24.48 ± 3.98

3.06 ± 0.28 0.14 ± 0.09 16.21 ± 0.51 1.22 ± 0.13 5.57 ± 0.06 ND 26.20 ± 0.62

ND

0.01 ± 0.01 ND

0.56 ± 0.16 ND

ND

ND

0.04 ± 0.07 ND

3.37 ± 0.95 ND

23.92 ± 1.07 0.91 ± 0.12 4.03 ± 0.37 ND 31.80 ± 1.50

1.07 ± 0.59 0.02 ± 0.02 18.50 ± 0.18 0.85 ± 0.08 4.72 ± 0.42 ND 25.16 ± 0.11

17.62 ± 0.25 0.72 ± 0.17 2.23 ± 0.82 ND 20.58 ± 1.13

13.69 ± 1.87 0.59 ± 0.05 2.49 ± 0.78 ND 16.82 ± 2.74

13.84 ± 0.45 0.85 ± 0.08 3.94 ± 0.50 ND 18.65 ± 0.97

13.21 ± 1.09 1.81 ± 0.36 5.66 ± 0.22 ND 21.24 ± 1.22

12.05 ± 0.67 1.30 ± 0.12 5.79 ± 0.07 ND 19.15 ± 0.77

15.44 ± 1.33 ND

ND 5.88 ± 0.51 8.96 ± 0.36 1.60 ± 0.08 5.46 ± 0.50 21.90 ± 0.75

ND 3.81 ± 0.57 16.15 ± 0.12 1.36 ± 0.02 3.57 ± 0.33 24.88 ± 0.31

ND 2.34 ± 0.16 21.83 ± 0.19 1.29 ± 0.05 3.51 ± 0.17 28.97 ± 0.24

ND 4.11 ± 0.72 11.97 ± 0.31 1.41 ± 0.04 5.02 ± 0.74 22.51 ± 0.62

ND 2.58 ± 0.79 13.08 ± 0.44 1.22 ± 0.05 8.61 ± 0.87 25.50 ± 0.79

ND 5.74 ± 0.41 6.58 ± 0.18 1.58 ± 0.03 8.05 ± 0.32 21.95 ± 0.74

ND 2.46 ± 0.38 10.86 ± 0.07 1.69 ± 0.17 6.29 ± 0.82 21.30 ± 0.66

ND 2.49 ± 0.21 21.98 ± 0.59 1.20 ± 0.02 3.85 ± 0.49 29.52 ± 0.26

ND 1.95 ± 0.05 29.09 ± 0.27 1.24 ± 0.01 3.49 ± 0.11 35.77 ± 0.30

ND 2.29 ± 0.24 18.72 ± 2.11 1.28 ± 0.12 6.68 ± 0.78 28.97 ± 2.62

ND 1.46 ± 0.27 15.26 ± 0.66 1.24 ± 0.23 9.68 ± 1.02 27.64 ± 0.44

ND 5.97 ± 0.66 8.43 ± 0.25 1.23 ± 0.27 7.63 ± 0.84 23.25 ± 0.24

18:2n6

11.12 ± 0.38

18.05 ± 0.06

24.80 ± 0.42

13.39 ± 0.27

14.59 ± 0.47

9.43 ± 0.21

13.76 ± 0.42

24.46 ± 0.72

28.11 ± 0.87

16.54 ± 0.84

16.23 ± 1.07

12.27 ± 0.63

18:3n3

0.77 ± 0.05

1.11 ± 0.15

1.18 ± 0.13

0.22 ± 0.37

0.52 ± 0.13

0.71 ± 0.21

ND

2.26 ± 0.34

1.39 ± 0.10

0.96 ± 0.21

1.02 ± 0.24

0.78 ± 0.22

15:0 16:0 17:0 18:0 20:0 SFA

15:1 16:1n7 18:1n9 18:1n7 20:1n9 MUFA

ND

6.28 ± 0.18 ND 25.09 ± 2.26

Table 10. (Continued) Gonad

Soma

Fatty acids

09/04

11/04

01/05

03/05

05/05

07/05

09/04

11/04

01/05

03/05

05/05

07/05

20:2

1.56 ± 0.04 ND

ND

ND

ND

ND

ND

ND

2.06 ± 0.73 ND

ND

ND

1.81 ± 0.48 ND

ND

20:3n3

2.41 ± 0.15 ND

ND

ND

ND

ND

ND

1.85 ± 0.09 ND

20:3n6

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

20:4n6

2.73 ± 0.19 14.79 ± 0.46 14.47 ± 1.81 46.30 ± 1.85

3.28 ± 0.19 11.91 ± 0.05 14.06 ± 0.34 49.96 ± 0.37

2.99 ± 0.06 8.60 ± 0.38 10.84 ± 0.74 48.41 ± 0.95

3.33 ± 0.28 16.04 ± 1.51 17.59 ± 1.40 50.57 ± 2.87

2.84 ± 0.61 11.50 ± 1.12 18.72 ± 5.77 50.03 ± 4.11

4.64 ± 0.96 17.56 ± 0.18 17.44 ± 0.76 51.85 ± 1.31

5.00 ± 0.19 13.25 ± 0.33 26.11 ± 0.97 58.13 ± 1.31

3.64 ± 0.64 8.92 ± 0.38 14.39 ± 0.81 53.67 ± 2.53

2.65 ± 0.11 4.81 ± 0.25 8.62 ± 0.04 44.19 ± 1.19

4.54 ± 0.97 11.05 ± 0.99 16.71 ± 1.77 49.79 ± 3.22

5.48 ± 0.20 9.82 ± 0.30 20.65 ± 1.24 53.22 ± 0.87

5.62 ± 0.59 14.13 ± 1.16 16.99 ± 1.18 51.65 ± 2.11

20:5n3 22:6n3 PUFA

Table 11. Fatty acid profiles (%) of gonad and soma of mussels from Kwun Tong (Mean ± 1SD; n = 3). SFA: saturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid Gonad 09/04 5.58 ± 0.33 0.20 ± 0.12 28.23 ± 0.67 1.61 ± 0.28 5.53 ± 0.43 ND

11/04 4.80 ± 0.42 0.21 ± 0.18 23.30 ± 1.56 1.06 ± 0.08 4.08 ± 0.32 ND

01/05 4.51 ± 0.26 0.04 ± 0.05 21.37 ± 0.37 1.24 ± 0.08 4.43 ± 0.36 ND

03/05 4.21 ± 0.32 ND

SFA

41.16 ± 1.43

33.44 ± 2.48

15:1

ND

16:1n7

11.40 ± 0.08 2.03 ± 0.03 2.51 ± 0.07 3.92 ± 0.25 19.85 ± 0.19

Fatty acids 14:0 15:0 16:0 17:0 18:0 20:0

18:1n9 18:1n7 20:1n9 MUFA

11/04 3.05 ± 0.63 0.03 ± 0.05 21.51 ± 1.23 1.37 ± 0.14 4.69 ± 0.84 ND

01/05 4.09 ± 0.45 0.27 ± 0.15 22.83 ± 1.20 1.68 ± 0.10 6.04 ± 0.51 ND

03/05 0.98 ± 0.33 ND

21.12 ± 0.56 1.42 ± 0.13 5.81 ± 0.21 ND

Soma 09/04 5.36 ± 0.22 0.23 ± 0.03 28.89 ± 1.44 1.77 ± 0.11 6.65 ± 0.50 ND

24.56 ± 4.30

32.34 ± 0.78

42.89 ± 2.18

30.65 ± 2.82

ND

ND

ND

ND

10.01 ± 0.99 3.27 ± 0.08 2.34 ± 0.23 5.48 ± 0.05 21.11 ± 1.11

4.75 ± 2.84 4.36 ± 0.65 1.96 ± 0.38 9.48 ± 1.94 20.55 ±1.55

8.75 ± 0.40 2.49 ± 0.26 2.20 ± 0.04 4.87 ± 0.23 18.31 ± 0.63

11.44 ± 0.42 2.39 ± 0.11 2.41 ± 0.07 3.85 ± 0.22 20.09 ± 0.46

07/05 3.99 ± 0.46 ND

20.29 ± 2.43 1.93 ± 0.67 4.80 ± 0.24 ND

05/05 0.59 ± 1.02 0.07 ± 0.11 15.95 ± 3.25 1.58 ± 0.23 6.37 ± 1.05 ND

31.59 ± 0.65

31.23 ± 3.34

ND

ND

10.94 ± 0.35 1.93 ± 0.25 2.41 ± 0.06 3.87 ± 0.17 19.16 ± 0.44

11.28 ± 0.25 2.89 ± 0.05 2.50 ± 0.06 4.00 ± 0.35 20.68 ± 0.21

07/05 5.10 ± 0.14 ND

17.49 ± 0.56 1.77 ± 0.06 6.95 ± 0.51 ND

05/05 0.74 ± 1.12 0.10 ± 0.16 14.49 ± 2.91 0.37 ± 0.64 5.72 ± 1.11 ND

34.91 ± 2.15

27.18 ± 0.54

21.41 ± 4.07

33.98 ± 0.82

ND

ND

ND

ND

ND

9.45 ± 0.60 2.72 ± 0.14 2.35 ± 0.11 4.57 ± 0.25 19.09 ± 0.94

10.99 ± 0.39 3.71 ± 0.29 2.55 ± 0.12 5.30 ± 0.36 22.55 ± 0.53

6.42 ± 0.42 4.24 ± 0.11 2.48 ± 0.05 7.53 ± 0.45 20.67 ± 0.25

4.77 ± 3.63 5.55 ± 1.85 1.99 ± 0.56 8.94 ± 1.04 21.25 ± 1.65

10.44 ± 0.30 2.28 ± 0.93 1.90 ± 0.15 5.84 ± 1.04 20.46 ± 2.33

22.06 ± 1.54 0.43 ± 0.74 6.40 ± 0.02 ND

Table 11. (Continued)

20:3n3

Gonad 09/04 3.36 ± 0.09 1.00 ± 0.30 1.31 ± 0.05 ND

20:3n6

ND

11/04 3.75 ± 0.10 1.70 ± 0.10 1.84 ± 0.06 1.92 ± 0.10 ND

20:4n6

2.27 ± 0.31 17.66 ± 0.58 13.38 ± 1.63 38.99 ± 1.48

3.15 ± 0.40 19.97 ± 1.02 15.08 ± 1.16 47.40 ± 2.63

Fatty acids 18:2n6 18:3n3 20:2

20:5n3 22:6n3 PUFA

07/05 4.19 ± 0.13 0.97 ± 0.25 0.00

ND

05/05 6.32 ± 0.67 0.86 ± 0.19 1.74 ± 0.21 ND

ND

ND

ND

ND

Soma 09/04 3.93 ± 0.10 1.00 ± 0.01 1.32 ± 0.04 1.35 ± 0.06 ND

2.63 ± 0.14 23.53 ± 0.30 15.20 ± 0.57 47.73 ± 0.70

ND

5.48 ± 1.35 17.31 ± 4.05 23.18 ± 4.47 54.88 ± 5.66

3.76 ± 0.85 21.00 ± 1.19 19.42 ± 0.76 49.34 ± 1.15

2.67 ± 0.26 15.31 ± 0.96 11.45 ± 1.06 36.02 ± 2.32

01/05 4.96 ± 0.06 1.40 ± 0.30 ND

03/05 5.15 ± 0.34 0.62 ± 1.07 ND

ND

22.74 ± 1.22 19.15 ± 3.04 47.66 ± 4.45

ND

11/04 5.08 ± 0.33 2.07 ± 0.50 ND

01/05 5.52 ± 0.13 1.20 ± 0.28 ND

03/05 6.10 ± 0.12 0.00

ND

05/05 7.15 ± 1.81 1.20 ± 0.74 1.69 ± 0.21 ND

07/05 4.34 ± 2.36 1.35 ± 0.20 0.33 ± 0.56 ND

ND

ND

ND 5.12 ± 0.69 19.36 ± 1.10 18.63 ± 0.98 50.26 ± 2.55

ND

ND

ND

ND

3.15 ± 0.19 18.86 ± 1.07 13.81 ± 1.16 42.53 ± 2.40

4.62 ± 0.30 20.63 ± 0.41 20.80 ± 0.18 52.15 ± 0.51

4.98 ± 1.29 20.19 ± 1.82 22.13 ± 3.41 55.65 ± 5.56

4.07 ± 1.06 16.08 ± 1.26 19.39 ± 4.30 45.56 ± 3.08

ND

Table 12. Fatty acid profiles (%) of gonad and soma of mussels from Tsim Sha Tsui (Mean ± 1SD; n = 3). SFA: saturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid Gonad

Soma

Fatty acids

09/04

11/04

01/05

03/05

05/05

07/05

09/04

11/04

01/05

03/05

05/05

07/05

14:0

5.56 ± 0.41 0.30 ± 0.04 28.05 ± 2.88 1.37 ± 0.13 6.17 ± 0.32 ND

4.43 ± 1.21 0.05 ± 0.05 22.10 ± 1.94 1.19 ± 0.18 4.32 ± 0.08 ND

2.84 ± 0.40 ND

0.93 ± 0.09 ND

4.91 ± 1.49 ND

1.04 ± 0.16 ND

0.26 ± 0.23 ND

20.22 ± 2.45 0.34 ± 0.58 6.10 ± 0.25 ND

20.91 ± 1.09 1.81 ± 0.90 4.73 ± 0.06 ND

15.96 ± 0.33 1.01 ± 0.08 4.15 ± 0.32 ND

11.17 ± 1.07 ND 4.49 ± 0.42 ND

1.44 ± 0.83 0.06 ± 0.09 16.40 ± 2.19 2.02 ± 0.38 6.97 ± 0.63 ND

3.64 ± 0.52 ND

14.28 ± 0.54 0.99 ± 0.77 5.31 ± 0.23 ND

9.27 ± 0.58 0.29 ± 0.01 32.14 ± 1.18 1.60 ± 0.10 8.42 ± 0.77 ND

3.04 ± 0.75 ND

19.31 ± 0.46 1.05 ± 0.12 4.52 ± 0.29 ND

1.79 ± 0.37 0.15 ± 0.02 15.31 ± 0.44 1.23 ± 0.03 5.77 ± 0.52 ND

SFA

41.44 ± 3.28

32.10 ± 3.12

27.73 ± 0.81

21.51 ± 0.87

24.24 ± 0.64

31.23 ± 3.76

51.72 ± 2.50

30.49 ± 2.62

22.15 ± 0.64

15.92 ± 1.31

26.88 ± 2.99

27.52 ± 2.76

15:1

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

ND

16:1n7

7.84 ± 0.84 5.20 ± 0.22 1.55 ± 0.05 4.26 ± 0.54 18.85 ± 0.65

6.98 ± 0.69 5.83 ± 0.34 1.59 ± 0.15 4.58 ± 0.52 18.98 ± 0.61

5.13 ± 0.30 12.86 ± 0.26 1.47 ± 0.07 4.57 ± 0.05 24.04 ± 0.36

3.12 ± 0.15 13.46 ± 0.44 1.38 ± 0.02 6.19 ± 0.24 24.16 ± 0.35

3.27 ± 0.15 9.94 ± 0.32 1.28 ± 0.08 8.06 ± 0.27 22.56 ± 0.26

8.10 ± 1.72 3.89 ± 0.17 1.61 ± 0.08 7.08 ± 0.72 20.68 ± 1.44

16.43 ± 0.49 0.90 ± 0.08 2.02 ± 0.09 1.95 ± 0.34 21.30 ± 0.23

5.59 ± 0.56 7.49 ± 0.54 1.43 ± 0.10 5.80 ± 0.42 20.31 ± 0.58

3.15 ± 0.18 24.38 ± 1.67 1.35 ± 0.02 4.60 ± 0.25 33.48 ± 1.28

1.59 ± 0.38 22.90 ± 1.04 1.17 ± 0.17 6.83 ± 0.22 32.49 ± 1.41

2.71 ± 0.55 11.64 ± 0.31 1.19 ± 0.07 8.67 ± 0.60 24.20 ± 0.42

7.57 ± 1.22 5.31 ± 0.26 1.59 ± 0.08 7.64 ± 0.42 22.10 ± 0.71

15:0 16:0 17:0 18:0 20:0

18:1n9 18:1n7 20:1n9 MUFA

16.47 ± 2.17 1.28 ± 0.25 6.13 ± 0.62 ND

Table 12. (Continued)

20:3n3

Gonad 09/04 7.32 ± 0.37 0.90 ± 0.07 1.31 ± 0.07 ND

20:3n6

ND

ND

ND

ND

ND

ND

1.33 ± 0.29 ND

20:4n6

2.52 ± 0.25 13.33 ± 0.84 14.35 ± 3.00 39.72 ± 3.77

3.48 ± 0.47 17.68 ± 1.31 18.72 ± 1.33 48.93 ± 3.01

3.56 ± 0.11 14.02 ± 0.38 15.80 ± 0.24 48.23 ± 0.56

4.01 ± 0.38 15.99 ± 0.26 18.54 ± 0.50 54.34 ± 0.79

4.08 ± 0.30 14.73 ± 0.07 22.03 ± 0.76 52.42 ± 0.70

4.40 ± 0.58 18.90 ± 1.68 15.78 ± 2.57 47.75 ± 4.65

3.30 ± 0.24 13.00 ± 1.33 6.96 ± 0.78 26.98 ± 2.63

Fatty acids 18:2n6 18:3n3 20:2

20:5n3 22:6n3 PUFA

11/04 7.78 ± 0.37 1.27 ± 0.20 ND

01/05 13.59 ± 0.36 1.26 ± 0.07 ND ND

03/05 13.45 ± 0.33 0.85 ± 0.05 1.49 ± 0.13 ND

05/05 9.87 ± 0.45 0.78 ± 0.21 1.72 ± 0.26 ND

07/05 5.56 ± 0.34 0.39 ± 0.34 2.72 ± 0.41 ND

ND

Soma 09/04 1.42 ± 0.04 0.97 ± 0.03 ND

11/04 9.71 ± 0.46 1.03 ± 0.20 ND

01/05 19.12 ± 0.40 1.45 ± 0.23 ND

03/05 18.97 ± 0.57 1.49 ± 0.57 ND

ND

ND

ND 4.85 ± 1.13 13.89 ± 0.93 19.73 ± 1.10 49.20 ± 2.20

05/05 12.04 ± 0.24 0.00

ND

1.43 ± 0.07 ND

07/05 7.86 ± 0.49 1.22 ± 0.36 1.83 ± 0.33 ND

ND

ND

ND

ND

3.38 ± 0.13 8.25 ± 0.79 12.16 ± 1.21 44.36 ± 1.88

4.84 ± 0.58 8.62 ± 0.72 17.68 ± 2.64 51.59 ± 2.72

4.81 ± 1.28 10.54 ± 1.40 20.09 ± 0.50 48.91 ± 2.60

5.82 ± 0.78 16.19 ± 1.17 17.45 ± 2.00 50.38 ± 3.28

Table 13. Fatty acid profiles (%) of gonad and soma of mussels from Central (Mean ± 1SD; n = 3). SFA: saturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid

Fatty acids 14:0 15:0 16:0 17:0 18:0 20:0 SFA 15:1 16:1n7 18:1n9 18:1n7 20:1n9 MUFA

Gonad 09/04 2.11 ± 0.09 ND 20.93 ± 1.78 1.22 ± 0.18 4.77 ± 0.77 ND

11/04 2.73 ± 0.21 0.08 ± 0.14 19.65 ± 0.89 1.07 ± 0.17 4.63 ± 0.57 ND

01/05 2.02 ± 0.04 0.20 ± 0.05 18.49 ± 0.42 1.19 ± 0.09 4.80 ± 0.39 ND

03/05 1.59 ± 0.93 0.46 ± 0.57 16.03 ± 3.20 1.20 ± 0.15 4.28 ± 1.82 ND

29.03 ± 2.80 ND

28.16 ± 1.89 ND

26.71 ± 0.95 ND

4.72 ± 0.19 7.14 ± 0.27 1.65 ± 0.08 6.58 ± 0.08 20.09 ± 0.52

5.67 ± 0.23 7.33 ± 0.17 1.49 ± 0.03 4.83 ± 0.48 19.32 ± 0.10

4.24 ± 0.05 14.04 ± 0.42 1.53 ± 0.04 4.52 ± 0.15 24.33 ± 0.31

Soma 09/04 0.47 ± 0.05 ND

11/04 1.60 ± 0.53 ND

01/05 0.42 ± 0.11 ND

17.88 ± 0.61 1.42 ± 0.03 5.31 ± 0.50 ND

19.57 ± 1.12 1.51 ± 0.03 5.23 ± 0.331 ND

9.97 ± 0.13 1.38 ± 0.18 3.94 ± 0.23 ND

25.31 ± 0.68 ND

25.08 ± 1.07 ND

27.91 ± 1.88 ND

5.86 ± 0.16 7.28 ± 0.22 1.57 ± 0.08 8.04 ± 0.28 22.75 ± 0.41

2.94 ± 0.08 8.15 ± 0.36 1.49 ± 0.06 7.26 ± 0.73 19.83 ± 1.11

4.47 ± 0.54 11.70 ± 0.08 1.51 ± 0.02 5.85 ± 0.45 23.53 ± 0.16

07/05 2.52 ± 0.15 0.14 ± 0.21 16.16 ± 0.58 1.15 ± 0.07 5.34 ± 0.08 ND

23.57 ± 3.07 ND

05/05 0.73 ± 0.05 0.11 ± 0.07 13.84 ± 0.39 1.31 ± 0.07 5.69 ± 0.17 2.08 ± 0.18 23.76 ± 0.62 ND

2.83 ± 0.42 12.51 ± 0.41 1.17 ± 0.15 5.38 ± 0.02 21.90 ± 0.09

2.32 ± 0.02 12.27 ± 0.33 1.26 ± 0.05 7.97 ± 0.11 23.81 ± 0.31

03/05 0.14 ± 0.08 0.09 ± 0.06 14.37 ± 1.06 1.58 ± 0.17 5.91 ± 0.23 ND

05/05 0.73 ± 0.59 ND 15.70 ± 2.22 1.54 ± 0.15 6.82 ± 0.23 ND

07/05 2.18 ± 0.12 0.29 ± 0.03 18.62 ± 0.05 1.61 ± 0.05 6.90 ± 0.15 ND

15.71 ± 0.39

22.10 ± 1.25 ND

24.80 ± 2.43 ND

29.60 ± 0.31 ND

2.81 ± 0.12 23.63 ± 0.57 1.69 ± 0.08 6.45 ± 0.02 34.58 ± 0.54

1.97 ± 0.25 22.06 ± 0.68 1.53 ± 0.04 6.45 ± 0.04 32.00 ± 0.91

1.93 ± 0.56 14.23 ± 0.65 1.15 ± 0.03 8.00 ± 0.83 25.32 ± 0.84

5.32 ± 0.21 9.10 ± 0.08 1.39 ± 0.02 7.44 ± 0.09 23.24 ± 0.04

Table 13. (Continued)

11/04 9.35 ± 0.39 1.14 ± 0.21 2.46 ± 0.32 ND

01/05 15.58 ± 0.33 1.33 ± 0.10 ND

03/05 13.51 ± 0.49 0.97 ± 0.18 ND

20:3n3

Gonad 09/04 9.88 ± 0.30 1.17 ± 0.11 2.27 ± 0.28 ND

ND

20:3n6

ND

ND

20:4n6

3.46 ± 0.19 14.64 ± 0.83 19.45 ± 0.98 48.61 ± 2.23

3.70 ± 0.17 17.00 ± 0.73 18.87 ± 0.82 52.52 ± 1.88

Fatty acids 18:2n6 18:3n3 20:2

20:5n3 22:6n3 PUFA

ND

05/05 13.37 ± 0.33 0.75 ± 0.13 1.60 ± 0.10 ND

07/05 9.91 ± 0.23 0.96 ± 0.20 2.08 ± 0.35 ND

Soma 09/04 11.20 ± 0.23 1.03 ± 0.51 2.35 ± 0.20 ND

ND

ND

ND

ND

ND

3.55 ± 0.09 13.45 ± 0.50 15.05 ± 0.92 48.96 ± 1.26

4.70 ± 1.23 15.69 ± 0.80 19.66 ± 1.73 54.54 ± 3.14

4.01 ± 0.12 12.41 ± 0.19 20.29 ± 0.06 50.83 ± 0.33

4.31 ± 0.38 14.62 ± 0.42 20.07 ± 0.44 51.95 ± 0.70

4.93 ± 0.08 12.19 ± 0.60 23.39 ± 0.61 55.09 ± 1.25

11/04 12.51 ± 0.24 1.11 ± 0.15 1.89 ± 0.16 ND

01/05 12.16 ± 0.33 ND

05/05 15.01 ± 0.28 ND

ND

03/05 19.69 ± 0.37 0.79 ± 0.35 ND

ND

ND

ND

ND

ND

ND

ND

07/05 11.49 ± 0.19 0.75 ± 0.09 1.65 ± 0.02 0.24 ± 0.42 ND

4.47 ± 0.24 11.81 ± 0.16 16.77 ± 1.75 48.57 ± 2.02

6.74 ± 0.34 10.38 ± 0.28 20.42 ± 1.46 49.71 ± 0.93

3.40 ± 0.55 8.41 ± 0.52 13.60 ± 1.54 45.90 ± 2.13

4.58± 1.13 9.85 ± 0.58 20.44 ± 1.56 49.88 ± 2.46

5.05 ± 0.10 12.20 ± 0.05 15.79 ± 0.65 47.16 ± 0.27

ND

Inter-Site Differences and Seasonal Patterns…

31

Figure 8. Similarity (%) of the fatty acid profiles of gonad of mussels from Victoria Harbour and reference sites collected from September 2004 to July 2005. PC: Peng Chau, NP: North Point, KT: Kwun Tong, TST: Tsim Sha Tsui, C: Central, TLC: Tung Lung Chau; 09: Sept. 04, 11: Nov. 04, 01: Jan. 05, 03: Mar. 05, 05: May 05, 07: Jul. 05; G: gonad.

Repeated-measures MANOVA were performed to find the overall inter-site and seasonal differences in each fatty acid in the gonads of the mussels. For inter-site differences, the percentages of SFAs 14:0 and 16:0 were the highest at PC and the lowest at NP and C. For SFA 18:0, the percentages at the reference sites (PC and TLC) were significantly higher than those at the other sites. For MUFAs 16:1n7 and 18:1n7 and PUFAs 18:3n3 and 20:5n3, the percentages at the reference sites were significantly higher than that in Victoria Harbour except for KT. For MUFAs 18:1n9 and 20:1n9 and PUFAs 18:2n6 and 20:2, the percentages in Victoria Harbour were significantly higher than those at the reference sites. For SFA 17:0 and PUFA 22:6n3, the percentage was the highest at TLC. SFA 20:0 was only present at C and PUFA 20:3n3 was present at PC and KT. PUFA 20:3n6 was absent in the gonads of mussels from all sites. For seasonal changes, the percentages of SFAs 14:0, 16:0 and 18:0 and MUFA 18:1n7 were the highest in September 2004 and they were relatively lower in March 2005 and May 2005. In contrast, the percentages of PUFA 22:6n3 were higher in March 2005 and May 2005 than in September 2004. For MUFA 18:1n9 and PUFA 18:2n6, the percentages in January 2005, March 2005 and May 2005 were higher than in September 2004, November 2004 and July 2005.

Fatty Acid Profiles in Soma of Green Mussels from Victoria Harbour and Reference Sites For PC (Table 8), the percentage of SFAs (36–50%) in soma was generally similar to or greater than that of PUFAs (28–42%) in September 2004, November 2004 and January 2005.

32

S. G. Cheung and P. K. S. Shin

In March, May and July 2005, the percentage of PUFAs (48–53%) was greater than that of SFAs (30–34%). The percentage of MUFA (15–21%) was the lowest among SFAs, MUFAs and PUFAs during the whole sampling time. For TLC (Table 9), the percentage of PUFAs (41–64%) was also greater than that of SFA (22–41%) and the percentage of MUFAs was the lowest among these fatty acids. For the sampling sites in Victoria Harbour (Tables 10-13), the percentage of PUFAs was higher (27–58%) than SFAs and MUFAs.

Inter-Site Difference and Seasonal Changes in the Fatty Acid Profiles in Soma of Green Mussels from Victoria Harbour and Reference Sites Analysis of similarity (ANOSIM) was carried out to show the seasonal changes and intersite differences in the fatty profiles in soma of green mussels in Victoria Harbour and reference sites. The results showed that there were significant inter-site differences in the fatty acid profiles from the six sampling sites in Victoria Harbour and reference sites (Global test of ANOSIM, R = 0.941, p = 0.001). On the other hand, the fatty acid levels were also significantly different from each other (Global test of ANOSIM, R = 0.915, p = 0.001) among the six sampling months. Hierarchical cluster analysis of the fatty acid profiles of soma showed similar separation to those of the gonads of the mussels. Two groups were separated (Figure 9). Group 1 comprised the fatty acid profiles of soma of mussels collected from the reference sites (PC and TLC) and KT in Victoria Harbour at a similarity level of 73%, together with one sample (September 2004) from TST. Group 2 contained samples from NP, TST and C in Victoria Harbour. Repeated-measures MANOVA were performed to find overall inter-site and seasonal differences in each fatty acid in the soma of the mussels. For inter-site difference, the percentages of SFAs 14:0 and 16:0, MUFA 16:1n7 and PUFA 20:5n3 at the reference sites (PC and TLC) were higher than those at the sites in Victoria Harbour (C, TST and NP), except the fatty acids for KT mussels and 14:0 at TST mussels. For SFA 18:0, the percentages at the reference sites (PC and TLC) were significantly higher than those at the other sites. For MUFA 18:1n7, the percentage was the highest at KT. For MUFA 18:1n9 and PUFA 18:2n6, the percentages in Victoria Harbour (C, TST, NP, KT) were significantly higher than at the reference sites. For PUFA 22:6n3, the percentage was the highest in TLC. For seasonal changes, the percentages of SFAs 14:0 and 16:0 and MUFAs 16:1n7 and 18:1n7 were the lowest in March 2005 and May 2005. For SFA 14:0 and MUFAs 16:1n7 and 18:1n7, the percentages were the highest in September 2004 and July 2005. In contrast, the percentages of PUFA 22:6n3 were the highest in March 2005 and May 2005 and significantly higher than those in September 2004 and July 2005. For MUFA 18:1n9 and PUFA 18:2n6, the percentages in the winter period (January 2005 through March 2005) were higher than those in the summer period (September 2004 through July 2005).

Inter-Site Differences and Seasonal Patterns…

33

Figure 9. Similarity (%) of the fatty acid profiles of somatic tissue of mussels from Victoria Harbour and reference sites collected from September 2004 to July 2005. PC: Peng Chau, NP: North Point, KT: Kwun Tong, TST: Tsim Sha Tsui, C: Central, TLC: Tung Lung Chau; 09: Sept. 04, 11: Nov. 04, 01: Jan. 05, 03: Mar. 05, 05: May 05, 07: Jul. 05; ST: somatic tissue.

Correlations between Fatty Acids Profiles of Total Particulate Matters in Waters and Fatty Acid Profiles of Mussels and Physico-chemical Parameters of Waters The fatty acid profiles of the gonads and somas of the mussels were significantly affected by their diets (Table 14). The level of SFAs 14:0 and 16:0, MUFAs 16:1n7 and 18:1n9 and PUFA 18:2n6 of TPMs in waters were positively correlated with those in both the gonads and the somas of the mussels. For SFA 18:0 and PUFA 20:5n3 of TPMs in waters, they were only positively correlated with those in the gonad. For MUFA 18:1n7, it was only positively correlated with those in the soma. The fatty acid profiles of TPMs in waters were also correlated with the physico-chemical parameters of the water column. SFA 14:0, MUFA 16:1n7 and PUFAs 20:5n3 and 22:6n3 in TPMs showed positive correlation with chlorophyll a, whereas SFA 18:0, MUFA 18:1n9 and PUFAs 18:2n6 and 18:3n3 showed negative correlation. SFA 14:0 and MUFA 16:1n7 were also positively correlated with temperature; however, a negative correlation was found with MUFA 20:1n9 and PUFAs 18:2n6 and 18:3n3. PUFA 20:5n3 was positively correlated with dissolved oxygen, whereas a negative correlation with MUFA 18:1n9 was found. PUFA 18:2n6 was positively correlated with salinity but a negative correlation was found with MUFA 16:1n7. MUFA 16:1n7 and PUFA 20:5n3 were also positively correlated with pH data, whereas a negative correlation was found with MUFA 18:1n9 and PUFA 18:2n6. MUFA 18:1n9 and PUFA 18:2n6 were positively correlated with ammonia. However, SFAs 16:0 and 18:0 were negatively correlated with nitrate. For phosphate, a positive correlation was found with MUFA 18:1n9, whereas a negative correlation was noted for SFA 18:0.

Table 14. Pearson correlation between individual fatty acids of total particulate matters in waters, and that of gonad and soma of mussels and physico-chemical parameters of waters collected from Victoria Harbour and reference sites. Only significant correlation with p-value is shown Fatty acid of TPMs SFA 14:0

Fatty acid of gonad

Fatty acid of soma

Temperatur e

Dissolved oxygen

Salinity

pH

Ammonia

Nitrate

Phosphate

Chlorophyll a

0.44 (99%) after one week, following an Scrobicularia 70% exponential decay curvecockle (Figure 4b). 80 60% As DTX2 is less converted to esters, and in turn the free form is eliminated slowly than 50% esters, there is a gradual increase in the percentage of 60 total DTX2 found in routine mussel 40% is clearly illustrated in Figure 5a, where the percentage of DTX2 was low in samples. This 30% due to contamination being derived solely early summer, 40 from eating D. acuminata cells, which do 20% not produce DTX2. The percentage of DTX2 increases during the D. acuta season. The ratio 10% between OA and DTX2 in plankton is around2060:40 %, and in cockle DTX2 also fluctuates around 40% during the end of summer and autumn. However, in mussels DTX2 0% 0 in mid autumn. Sudden drops in percentage surpasses steadily the 40% ratio and reaches 80% 0 2 4 6 8 10 12 14 16 18 this ratio, were coincident with blooms of D. acuta, representing ingestion of fresh toxins in a Days in tank ratio 60:40 % (Vale, 2004, 2006a). AsFigure esters determination was indirect, to chemical (over alkaline hydrolysis of theDTX2 fatty 5. a) Comparison of totalresorting DTX2 percentage total OA+ total acid moiety, at this stage of the research it was hypothesized the esters were attributed sum) between plankton, mussel and cockle from Aveiro lagoon, 2003 (LC-MS exclusively the transformation of OA and were DTX2presented into 7-O-acyl derivatives in mussels data). toDetails of free and ester forms in Figure 3. Arrows point (Quilliam et al., 2003). Another research carried out in summer 2005 confirmed the D. acuta maximals in plankton. b) Detoxification experiments with 7-O-acyl bivalves derivatives explained the majority the toxins esters (pre-column found in a variety of species, comprising naturally contaminated withofPSP HPLC-FLD data). mussels, cockles, clams and razor clams (Vale, 2006b). A strange finding was found related to the presence of odd fatty acids (FA): C15:0, C17:0, C17:1, and a probably branched FA isomer of C16:0 (br-C16:0). The esters with this br-C16:0 where found in high percentages particularly in two species of estuarine clams (Ruditapes decussatus, Venerupis senegalensis), where they represented 13-34% of total esters found. This percentage was smaller in cockles (6-9%) and in mussels (below 2.5%). In razor clams the percentage of br-C16:0 was low, but in contrast these presented a high percentage of odd fatty acids.

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Figure 5. a) Comparison of total DTX2 percentage (over total OA+ total DTX2 sum) between plankton, mussel and cockle from Aveiro lagoon, 2003 (LC-MS data). Details of free and ester forms were presented in Figure 3. Arrows point D. acuta maximals in plankton. b) Detoxification experiments with bivalves naturally contaminated with PSP toxins (pre-column HPLC-FLD data).

These odd and branched FA are not produced by eukariontes but are commonly seen as bacterial markers (Harvey and Macko, 1997; Ivanova et al., 2000). Another study carried out in 2009 in a smaller lagoon – Albufeira lagoon – showed again a high percentage of br-C16:0 in cockle but not in mussel (Vale, 2010b). Due to the difficulty in identifying its structure, its tentative identification was done by comparing relative retention times of free FA with FA esterified into OA. It was putatively identified as a multimethyl-branched isomer abundant in marine matrices: the isoprenoid 4,8,12-trimethyltridecanoic acid (TMTD). However, such a high percentage of TMTD is not found amongst the FA composing the digestive glands of cockles. But in contrast, TMTD is relatively more abundant in mussel‘s digestive glands, but not so abundant amongst its OA esters (Vale, 2010b). As TMTD is a product of phytol degradation (the isoprenoid moiety of chlorophyll) by certain bacteria, this led to a hypothesis pointing that part of the OA ester pool actually may be located in the gut flora of bivalves and not intracellularly in the digestive gland. This might explain its quick turnover, as bacteria multiply and are gradually eliminated in faeces. On the other hand, free toxins might be tied to bonding proteins in the digestive gland, making its elimination slower. In a research by Rossignoli and Blanco (2010) the subcellular distribution of OA in mussels was found to be in the in the cytosol, by means of centrifugation and ultrafiltration. Notwithstanding only a small proportion of the total toxin was found to be in free form, being most of it bound to a soluble cellular compound with a molecular mass which ranged from 30 to 300 kDa. A series of fractionations of samples digested with a protease, a lipase, and amylase suggested that the component to which okadaic acid is bound is a high density lipoprotein. Unfortunately, these authors did not look into the distribution of OA esters. Another study by Guéguen et al. (2009) found OA esters precipitated quickly while free OA remained in the supernantant. These authors attributed the localization of OA esters to the lysosome fraction and free OA to the cytosol. This hypothesis is not in contradiction with the hypothesis by Vale (2010b), as both bacteria and lysosomes are large in size and will precipitate faster than other soluble components of the cells.

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Recent research by Vale also showed that either in mussels or cockles after a simple centrifugation free OA and free DTX1 are mostly located in the supernatant (about 80%). On the other side, 7-O-acyl esters of OA and DTX1 will rapidly precipitate and about 80% in mussel and 90% in cockle are found in the supernatant.

PARALYTIC SHELLFISH POISONING TOXINS In the marine environment paralytic shellfish poisoning toxins (PSP) are produced by dinoflagellates belonging to some members of Alexandrium genus, Pyrodinium bahamense and Gymnodinium catenatum (Hallegraeff, 1993). High concentrations of these toxins in bivalve molluscs, or in other vectors such as crabs, might induce neurological disturbances in the human consumer, known as the PSP syndrome (Shumway, 1995). The severity of this seafood poisoning might be fatal in some instances due to the progressive respiratory paralysis. At the western Iberian coast Gymnodinium catenatum is the major PSP producer, followed by sporadic contamination episodes caused by Alexandrium minutum. G. catenatum produces a wide range of toxins, mostly belonging to the N-sulfocarbamoyl group, followed by the decarbamoyl group (Ordás et al., 2004). Another group that is exclusively produced by G. catenatum are the benzoate analogues (Negri et al., 2003; Vale, 2008b). In shellfish these are present at trace levels, and mostly are converted to the decarbamoyl group (Vale, 2008a). In addition to Acanthocardia tuberculata, an open sea species, at the Iberian coast the estuarine clam Scrobicularia plana presents long retention of PSP toxins. This bivalve has been studied in detail and compared with mussels and cockles (Artigas et al., 2006). In vivo depuration experiments were carried out in tanks confirming elimination of PSP toxins was very slow in tank when compared to mussels and cockles (Figure 5b). It had been previously hypothesized this clam could feed on G. catenatum cysts that deposit in the sediment (Vale and Sampayo, 2001), but this experiment pointed in the opposite direction: a strong retention mechanism. After a week in tank, mussels retained 27% of the original toxin, while cockles retained only 16% (Artigas et al., 2006). In vivo experiments confirmed the observations in the natural medium that differences among species are due to different elimination rates (Figure 1b). Pronounced differences of toxin‘s profile during elimination were not observed (Figure 6a and 6b). On the other way, rapid differences are observed mainly during toxification in species that present strong carbamoylase activity, such as Scrobicularia plana (Figure 6c) and Spisula solida (Artigas et al., 2007). These species transform rapidly the N-sulfocarbamoyl toxins into decarbamoyl analogues, which present much higher specific toxicity. Bivalves might present another biotransformation route poorly studied at the moment. Some toxins such as saxitoxin (STX) and N21-sulfocarbamoyl-saxitoxin (B1) might be single and double hydroxylated at C11 position, originating the M-toxins (Dell‘Aversano et al., 2008). However, unlike the classic PSP toxins which upon oxidation render strongly fluorescent products, these metabolites present very low fluorescence, and can only be detected with a mass spectrometer. When studying the contribution of M1 to the toxin profile of some Portuguese bivalve species, a comparison was made with its precursor B1: M1 accounted for 70% of total peak area of B1+M1 in Mytilus galloprovinciallis, 45% in

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Cerastoderma edule and 20% in Ruditapes decussatus (Vale, 2010a). Curiously M1 was more abundant in the species that usually retain longer PSP toxins, in the following order: mussels > cockles > clams (Artigas et al., 2006). Thus the longer toxin‘s retention, the more extensively these are converted into metabolites.

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Figure 6. Evolution profiles of N1-H during containing during artificial Figure 6. Evolution of profilesofof N artificialtoxins detoxification of naturally 1-H containing toxins contaminated: a) mussel; b) cockle contaminated: (see also Fig. 5b); a) andmussel; c) during b) artificial toxification of Fig. 5b); detoxification of naturally cockle (see also Scrobicularia planaartificial with a G. catenatum culture. data obtained by HPLC-FLD and c) during toxification of All Scrobicularia plana with aafter G.peroxide catenatum oxidation of digestive glands, showing only N1-H containing toxins.

digestive gland mass (g)

YTXs (µg/g)

Cells / Liter

with variation in their sensitivity to the toxins, as determined by the in vitro response of isolated, unsheated nerves to STX and tetrodotoxin (reviewed in Bricelj and Shumway, 1998). According to these studies, the most insensitive are Mytilus edulis, Mytilus californianus and the scallop Placopecten magellanicus. Oysters are the most sensitive, and a) b) clams intermediate (these studies did not provide any information on cockles, chosen here to compare with the blue mussel). Thus, the less sensitive will accumulate more. But this does 0.70 in some species. 0.40 1.6explain mussel 1400 not the tailing observed during the decontamination phase YTX equiv. cockle Other mechanisms clearly apply to bivalves that present long retention. It is long known 1.4 DG 0.60 Protoceratium spp. 1200 the North American butter clam Saxidomus giganteus accumulates PSP toxins particularly in Gonyaulax spinifera 0.30 1.2 siphons for months (Bricelj and Shumway, 1998). In 0.50 the Mediterranean waters, the giant 1000 cockle Acanthocardia tuberculatum retains toxins in the foot. A group tried to partially purify 1.0 0.40 800 a poison-binding protein from A. tuberculatum, and found it possessed a molecular weigh of 0.20 0.8 181 kDa (Takati et al., 2007). Unfortunately, 600 for the moment,0.30 protein binding of PSP toxins is a 0.6 field still little explored, but might provide a key to explain the differential retention of 0.20 400 toxins 0.10 0.4 between Mytilidae and other groups.

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culture. All data obtained by HPLC-FLD after peroxide oxidation of digestive glands, showing only N1-H containing toxins. Differences in accumulation of PSP toxins among bivalve species have been correlated

0.00 0

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Figure 7. a) Temporal variability of YTXs in mussel and cockle and the occurrence of several toxic microalgae in Aveiro Lagoon during summer/autumn 2005; b) detoxification of mussels naturally contaminated from Lisbon Bay from yessotoxins (DG = digestive glands; YTX equiv. = yessotoxin equivalents as determined by ELISA assay)

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OTHER OBSERVATIONS IN MUSSELS Although PSP and DSP family of toxins are the most serious problems faced by the shellfish industries both in Portugal and Spain, there are other regulated marine compounds occurring in bivalves. To date amnesic shellfish poisoning (ASP) toxins were never linked to severe human poisonings in Europe. These toxins tend to accumulate and disappear quickly from shellfish and no relevant data to compare species in detail as above is available. Diatom blooms causing this contamination are short lived and closure periods rarely surpass one week (Vale et al. 2008). Unlike dinoflagellates that present strong motility, diatoms tend to sink much quicker. In Portugal suspended mussel cultures are scarce, and samples analysed in the monitoring programme are intertidal mussels, that are only exposed to the topmost surface of the water column, while cockles are exposed to lower sections of the water column during high tide. This has been the explanation attributed so far as to why mussels present usually lower levels of this toxin than cockles for example (Vale and Sampayo, 2001). Although yessotoxins (YTXs) are still regulated in European legislation, there has been much controversy over its importance to human health because of its low oral activity (Tubaro et al., 2004). The characterization of a natural compound as a marine biotoxin, has been mostly based in the outcome of the toxicity observed after intraperitonial injection in mice, which is an artificial feeding route. Nevertheless, these compounds present an interesting example of the differential behaviour observed in mussels and other bivalves. At Aveiro lagoon mussels presented higher levels of YTXs than cockles (Gomes et al., 2008b). In either species, the decrease of toxins was not as quick as usually observed with other toxins following the decay of the microalgae bloom (Figure 7a). Prolonged retention in mussels was later observed in Cascais bay mussels (Gomes et al., 2008a). In vivo experiments showed over a period of 10 days no decrease in toxin concentration. An increase was even observed, but this was attributable to loss of tissue mass (Figure 7b). Another curious observation was found during the assessment of a prototype for a commercial rapid diagnostic kit based in lateral flow immunochromatographie (LFIC) (Laycock et al., 2006). The kit presented a severe drawback, which was a high percentage of false positives as determined by another technique: liquid chromatography coupled to mass spectrometry (LC-MS) (Vale et al., 2009). From these, 37% in the range below 50 µg OA equiv./kg, i.e., the cut-off programmed in the method, and 79% in the range of 50-160 ug/kg, i.e., the current regulatory limit. The detection of too many false positives is cumbersome; particularly when low levels of toxins occur. This will require food business operators relying in this test to unnecessarily further test by a confirmatory method in a centralised laboratory a high percentage of the samples. Extracts from clams (Tapes decussatus, Venerupis senegalensis) and oyster (Crassostrea spp.) gave few false positives (Table 1). Cockle (Cerastoderma edule) and the clam Scrobicularia plana gave low percentages of false positives in the south and SW coasts, but these were higher at the NW coast. Mussel (Mytilus spp.) had the highest percentage of false positives, which also seemed dependent on geographic location. The highest percentage of false positives was observed at the northwest coast, where usually the highest DSP levels are recorded year after year (Vale et al., 2008). Comparison between mussels and cockles from Aveiro lagoon, showed false positives might appear from autumn through spring, a period of usually low toxic microalgae countings (Vale et al., 2009).

and c) during artificial toxification of Scrobicularia plana with a G. catenatum culture. All data obtained by HPLC-FLD after peroxide oxidation of digestive glands, showing only N1-H containing toxins. Paulo Vale

a) mussel cockle Protoceratium spp. Gonyaulax spinifera

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Figure 7. a) variability of YTXs mussel cockleand andcockle the occurrence several toxicof Figure 7. Temporal a) Temporal variability of in YTXs inand mussel and theofoccurrence microalgae Aveiro Lagoon during 2005;during b) detoxification of mussels naturally several in toxic microalgae in summer/autumn Aveiro Lagoon summer/autumn 2005; b) contaminated from Lisbon Bay from yessotoxins (DG = digestive glands; YTX equiv. = yessotoxin detoxification of mussels naturally contaminated from Lisbon Bay from yessotoxins equivalents as determined by ELISA assay).

(DG = digestive glands; YTX equiv. = yessotoxin equivalents as determined by ELISA assay)

Table 1. Distribution by geographic area and species of false positives recorded in a prototype of LFIC assays for okadaites by comparison with data obtained simultaneously by LC-MS. NW = northwest, SW = southwest Portuguese Coastline

Bivalve species

False Positives (%)

Mytilus

Nº of samples tested 81

NW

Cerastoderma+Scrobicularia

85

37.6

Mytilus

20

35.0

SW+south

Cerastoderma+Scrobicularia

50

14.0

NW+SW+south

Ruditapes+Venerupis+Crassostrea 41

NW SW+south

72.8

5.0

Can these false responses still represent degradation products of the okadaites, that the test kit can detect, but not the LC-MS, which scans only the intact molecule? Or can these represent an unspecific binding of the antibody to a wide range of other natural or anthropogenic compounds? When antibody assays are developed, the cross reactivity is tested among other marine biotoxins of the same family, in this case DTX1 and DTX2 (Laycock et al., 2006), but nothing is known towards the wide array of other structures naturally present or of anthropogenic origin. Curiously, about the double of false positives were found in mussel when compared with cockles. Similar ratios were found when comparing the average annual DSP levels in mussels and cockles in selected production areas in several consecutive years (summarised in Table 3 by Vale et al., 2008).

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CONCLUSION Blue mussels are widely used in aquaculture, having the ability to colonise substrates in a dense packed vertical habitat, unlike other bottom dweller bivalves. However, for aquaculturists the blue mussel physiology poses more problems than other benthic bivalves when comes to the speed of accumulation and elimination of marine biotoxins. There is still much to understand regarding the biotransformation of marine biotoxins in bivalves. The recent hypothesis that gut bacteria might play a major role in biotransformation in some benthic bivalves but less in mussels is still a puzzle. All are herbivorous and relay strongly in phytoplankton. All degrade chlorophyll and TMTD, one of its intermediate degradation products, is very abundant in mussels. Why bacteria do not play such an important role in mussel? Among other physiological differences, mussels possess byssal formation for attachment in contrast to benthic bivalves living free in the sediment. Byssal formation can be inhibited by bacteria (Ayala et al., 2006; Dobrestov et al., 2006). Bacteria can also degrade byssal protein (Venkateswaran and Dohmoto, 2000). In this biochemical warfare of biofouling organisms, could the specific bacteria involved in OA esterification be largely inhibited in mussels, and in this case little TMTD was incorporated in OA esters? A comparison between Mytilus edulis, Cerastoderma edule and Ensis siliqua showed that immune cells and functions differed extensively in these three closely related species, with M. edulis showing a much higher level of immunological vigour that may be linked to its considerable resilience to adverse environmental conditions (Wootton et al., 2003). If OA is not rapidly transformed into esters, its binding to lipoproteins might diminish its interference with the mussel metabolism. OA is a potent inhibitor of protein phosphatases in eukariotic cells. The stereochemistry modification imposed by esterification also renders OA inactive against protein phosphatases (Takai et al., 1992). In turn this binding maintains a residual level of toxins above the regulatory limit, prohibiting the harvesting and selling of mussels. Mussels have been extensively used in the past as a biological indicator of pollution in monitoring programs. The reason for this choice is that the mussel is a sessile, filter-feeding organism, able to accumulate within its tissues many of the contaminants (pesticides, hydrocarbons, metals, etc.) present in seawater (Viarengo and Canesi, 1991). However, depending on the compound of study, mussels might present a binding capacity quite different from other commercial bivalves, and might supply overestimated accumulation data in relation to the accumulation by other aquatic species.

ACKNOWLEDGMENTS The programmes FCT/PRAXIS 2/2.1/MAR/1718/95 from FCT, ―Sanidade e Salubridade de Moluscos Bivalves‖ - ―POPESCA 1995/1999‖ (QCAII/med.3), ―Segurança, Vigilância e Qualidade de Moluscos Bivalves‖ - MARE 2000/2006 (QCAIII/med.4) and ―BENPER‖ MARE 2006/2008 (QCAIII/med.4) supported this research.

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REFERENCES Artigas, M.L., Amorim, A., Vale, P., Gomes, S.S., Botelho, M.J., Rodrigues, S.M., 2006. Prolonged toxicity of Scrobicularia plana after PSP events and its relation to Gymnodinium catenatum cyst consumption and toxin depuration. In: Moestrup, Ø. et al. (Eds.), Proceedings of 12th International Conference on Harmful Algae, ISSHA and IOC of UNESCO, Copenhagen, Netherlands, pp. 273-275. Artigas, M.L., Vale, P., Gomes, S.S., Botelho, M.J., Rodrigues, S.M., Amorim, A., 2007. Profiles of PSP toxins in shellfish from Portugal explained by carbamoylase activity. Journal of Chromatography A., 1160 (1-2), 99-105. Ayala, C., Clarke, M., Riquelme, C., 2006. Inhibition of byssal formation in Semimytilus algosus (Gould, 1850) by a film-forming bacterium isolated from biofouled substrata in northern Chile. Biofouling, 22(1), 61- 68. Berenguer, J.A., Gonzalez, L., Jimenez, I., Legarda, T.M., Olmedo, J.B., Burdaspal, P.A., 1993. The effect of commercial processing on the paralytic shellfish poison (PSP) content of naturally-contaminated Acanthocardia tuberculatum L. Food Addit. Contam., 10 (2), 217 230. Bricelj, V.M., Shumway, E., 1998. Paralytic shellfish toxins in bivalve molluscs: occurrence, transfer kinetics, and biotransformation. Rev. Fish. Sci., 6, 315-383. Dell‘Aversano, C., Walter, J.A., Burton, I.W., Stirling, D.J., Fattorusso, E., Quilliam, M.A., 2008. Isolation and structure elucidation of new and unusual saxitoxin analogues from mussels. J. Nat. Prod., 71 (9), 1518-1523. Dobretsov, S., Dahms, H.-U., Qian, P.-Y., 2006. Inhibition of biofouling by marine microorganisms and their metabolites. Biofouling, 22 (1), 43-54. Escalera, L., Reguera, B., Moita, T., Pazos, Y., Cerejo, M., Cabanas, J.M., Ruiz-Villarreal, M., 2010. Bloom dynamics of Dinophysis acuta in an upwelling system: In situ growth versus transport. Harmful Algae, 9 (3), 312-322. EU-CRL, 2001. Report of the working group on sampling plans. Brussels, 3-4/Oct/2001. European Commission, 1996. Commission Decision 96/77/EC establishing the conditions for the harvesting and processing of certain bivalve molluscs coming from areas where the paralytic shellfish poison level exceeds the limit laid down by Council Directive 91/492/EEC. Official Journal, L 015, 46-47. European Commission, 2002. Commission Decision 2002/226/EC establishing special health checks for the harvesting and processing of certain bivalve molluscs with a level of amnesic shellfish poison (ASP) exceeding the limit laid down by Council Directive 91/492/EEC. Official Journal, L 075, 65-66. FAO, 2004. Marine Biotoxins, FAO Food and Nutrition Paper, 80. Food and Agriculture Organization of the United Nations, Rome. 278 pp. Franco, M., 2005. Social and economic effects of biotoxins: the case of mussels farming in Galicia region. In: AOAC First Joint Toxin Symposium and Task Force Meeting, Baiona, Spain, 11-14 April 2005. Abstract book, pp. 63. Gomes, S.S., Palma, A.S., Botelho, M.J., Moita, T., Vale, P., 2008a. Monitorização de iessotoxinas em mexilhão na baía de Lisboa. In: Avances y tendencias en Fitoplancton Tóxico y Biotoxinas, Gilabert, J. (Ed.), Univ. Politécnica de Cartagena, Espanha, pp. 223-229.

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Gomes, S.S., Vale, P., Botelho, M.J., Rodrigues, S.M., Cerejo, M., Vilarinho, M.G., 2008b. ELISA Screening for yessotoxins in Portuguese shellfish. In: Moestrup, Ø. et al. (Eds.), Proceedings of 12th International Conference on Harmful Algae, ISSHA and IOC of UNESCO, Copenhagen, Netherlands, pp. 290-292. Guéguen, M., Duinker, A., Marcaillou, C., Aasen, J., Barillé, L., 2009. First approach to localizing lipophilic biotoxins in the mussel digestive glands. In: 7th International Conference on Molluscan Shellfish Safety, Nantes, France, 15-19/June/2009. Abstract book pp 64. Hallegraeff, G.M. 1993. A review of harmful algal blooms and their apparent global increase. Phycologia, 32, 79-99. Harvey, H.R. Macko, S.A., 1997. Catalysts or contributors? Tracking bacterial mediation of early diagenesis in the marine water column. Org. Geochem., 26, 531-544. Hu, T., Marr, J., deFreitas, A.S.W., Quilliam, M.A., Walter, J.A., Wright, J.L.C., Pleasance, S., 1992. New diol esters isolated from cultures of the dinoflagellates Prorocentrum lima and Prorocentrum concavum. J. Nat. Products, 55 (11), 1631-1637. Ivanova, E.P., Zhukova, N.V., Svetashev, V.I., Gorshkova, N.M., Kurilenko, V.V., Frolova, G.M., Mikhailov, V.V., 2000. Evaluation of phospholipid and fatty acid compositions as chemotaxonomic markers of alteromonas-like proteobacteria. Current Microbiology, 41, 341-345. James, K.J., Bishop, A.G., Gillman, M., Gillman, M., Kelly, S.S., Roden, C., Draisci, R., Lucentini, L., Giannetti, L., Boria, P., 1997. Liquid chromatography with fluorimetric, masss spectrometric and tandem mass spectrometric detection for the investigation of the seafood-toxin producing phytoplankton, Dinophysis acuta. J. Chromatogr. A, 777, 213221. Lassus, P., Gowland, D., McKenzie, D., Kelly, M. Braaten, B., Marcaillou-Martin, C., Blanco, J., 2007. Industrial scale detoxification of phycotoxin-contaminated shellfish: myth or reality? In: Busby, P. (Ed.). Proceedings of the 6th International Conference on Molluscan Shellfish Safety, Miscellaneous Series 71, The Royal Society of New Zealand, Wellington, NZ, pp. 289-297. Laycock MV, Jellett JF, Easy DJ, Donovan MA. 2006. First report of a new rapid assay for diarrhetic shellfish poisoning toxins. Harmful Algae 5: 74-78. Lee, J.S., Igarashi, T., Fraga, S., Dahl, E., Hovgaard, P., Yasumoto, T., 1989. Determination of diarrhetic shellfish toxins in various dinoflagellate species. J. Appl. Phycol., 1: 147152. Negri, A., Stirling, D., Quilliam, M., Blackburn, S., Bolch, C., Burton, I., Eaglesham, G., Thomas, K., Walter, J., Willis, R., 2003. Three novel hydroxybenzoate saxitoxin analogues isolated from the dinoflagellate Gymnodinium catenatum. Chem. Res. Toxicol., 16(8), 1029-1033. Ordás, M.C., Fraga, S., Franco, J.M., Ordás, A., Figueras, A. 2004. Toxin and molecular analysis of Gymnodinium catenatum (Dinophyceae) strains from Galicia (NW Spain) and Andalucia (S Spain). J. Plankt. Res., 26, 341-349. Quilliam, M.A., Vale, P., Sampayo, M.A.M., 2003. Direct detection of acyl esters of OA and DTX2 in Portuguese shellfish by LC-MS. In: Molluscan Shellfish Safety, Villalba, A., Reguera, B., Romalde, J.R., Beiras, R. (Eds.), Consellería de Pesca e Asuntos Marítimos da Xunta de Galicia and IOC of UNESCO, Santiago de Compostela, Spain, pp. 67-73.

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Rossignoli, A.E., Blanco, J., 2010. Subcellular distribution of okadaic acid in the digestive gland of Mytilus galloprovincialis: First evidences of lipoprotein binding to okadaic acid. Toxicon, 55 (2-3), 221-226. Salgado, C., Maneiro, J., Correa, J., Pérez, J.L., Arévalo, F., 2003. ASP biotoxins in scallops: the pratical application in Galicia of Commission Decision 2002/226/CE. In: Molluscan Shellfish Safety, Villalba, A., Reguera, B., Romalde, J.R., Beiras, R. (Eds.), Consellería de Pesca e Asuntos Marítimos da Xunta de Galicia and IOC of UNESCO, pp. 169-177. Shumway, S.E., 1995. Phycotoxin-related shellfish poisoning: bivalve molluscs are not the only vectors. Rev. Fish. Sci., 3, 1-31. Shumway, SE, van Egmond, H, Hurt, JW, Bean, LL. 1995. Management of shellfish resources. In: Hallegraeff, GM, Anderson, M, Cembella, AD (eds.) Manual on harmful marine microalgae. IOC Manuals and Guides, UNESCO, 33, 436-463. Takai, A., Murata, M., Torigoe, K., Isobe, M., Mieskes, G., Yasumoto, T., 1992. Inhibitory effect of okadaic acid derivatives on protein phosphatases. Biochem. J., 284, 539-544. Takati, N. Mountassif, D. Taleb, H. Lee K., Blaghen M., 2007. Purification and partial characterization of paralytic shellfish poison-binding protein from Acanthocardia tuberculatum. Toxicon, 50 (3), 311-321. Tubaro, A., Sosa, S., Altinier, G., Soranzo, M.R., Satake, M., Della Loggia, R., Yasumoto T., 2004. Short-term oral toxicity of homoyessotoxins, yessotoxin and okadaic acid in mice. Toxicon, 43 (4), 439-445. Vale, P., 2004. Differential dynamics of dinophysistoxins and pectenotoxins between blue mussel and common cockle: a phenomenon originating from the complex toxin profile of Dinophysis acuta. Toxicon, 44 (2), 123-134. Vale, P., 2006a. Differential dynamics of dinophysistoxins and pectenotoxins, part II: offshore bivalve species. Toxicon, 47 (2), 163-173. Vale, P., 2006b. Detailed profiles of 7-O-acyl esters in plankton and shellfish from the Portuguese coast. Journal of Chromatography A, 1128, 181-188. Vale, P., 2008a. Fate of benzoate paralytic shellfish poisoning toxins from Gymnodinium catenatum in shellfish and fish detected by pre-column oxidation and liquid chromatography with fluorescence detection. Journal of Chromatography A, 1190 (1-2), 191-197. Vale, P., 2008b. Complex profile of hydrophobic paralytic shellfish poisoning compounds in Gymnodinium catenatum detected by liquid chromatography with fluorescence and mass spectrometry detection. Journal of Chromatography A, 1195, 85-93. Vale, P., 2010a. Metabolites of saxitoxin analogues in bivalves contaminated by Gymnodinium catenatum. Toxicon, 55 (1), 162-165. Vale, P., 2010b. Profiles of fatty acids and 7-O-acyl okadaic acid esters in bivalves: Can bacteria be involved in acyl esterification of okadaic acid? Comparative Biochemistry and Physiology, Part C, 151, 18–24. Vale, P., Botelho, M.J., Rodrigues, S.M., Gomes, S.S., Sampayo, M.A.M., 2008. Two decades of marine biotoxin monitoring in bivalves from Portugal (1986-2006): a review of exposure assessment. Harmful Algae, 7 (1), 11-25. Vale, P., Gomes, S.S., Lameiras, J., Rodrigues, S.M., Botelho, M.J., Laycock, M.V., 2009. Assessment of a new LFIC assay for the okadaic acid group of toxins using naturally contaminated bivalve shellfish from the Portuguese coast. Food Additives and Contaminants, 26 (2), 229-235.

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Vale, P., Sampayo, M.A.M., 2000. Dinophysistoxin-2: a rare diarrhetic toxin associated with Dinophysis acuta. Toxicon, 38 (11), 1599-1606. Vale, P., Sampayo, M.A.M., 2001. Domoic acid in Portuguese shellfish and fish. Toxicon, 39 (6), 893-904. Vale, P., Sampayo, M.A.M., 2002. Esterification of DSP toxins by Portuguese bivalves from the Northwest coast determined by LC-MS  a widespread phenomenon. Toxicon, 40 (1), 33-42. Viarengo, A., Canesi, L., 1991. Mussels as biological indicators of pollution. Aquaculture, 94 (2-3), 225-243. Venkateswaran, K., Dohmoto, N., 2000. Pseudoalteromonas peptidolytica sp. nov., a novel marine mussel-thread-degrading bacterium isolated from the Sea of Japan. International Journal of Systematic and Evolutionary Microbiology, 50, 565–574. Wootton, E.C., Dyrynda, E.A., Ratcliffe, N.A., 2003. Bivalve immunity: comparisons between the marine mussel (Mytilus edulis), the edible cockle (Cerastoderma edule) and the razor-shell (Ensis siliqua). Fish and Shellfish Immunology, 15, 195-210.

In: Mussels: Anatomy, Habitat and Environmental Impact ISBN: 978-1-61761-763-8 Editors: Lauren E. McGevin ©2011 Nova Science Publishers, Inc.

Chapter 19

IMMUNOTOXICITY OF ENVIRONMENTAL CHEMICALS IN THE PEARL FORMING MUSSEL OF INDIA- A REVIEW Sajal Ray*1, Mitali Ray1, Sudipta Chakraborty2 and Suman Mukherjee3 1

Aquatic Toxicology Laboratory, Department of Zoology, University of Calcutta, West Bengal, India 2 Parasitology and Immunology Laboratory, Department of Zoology, Maulana Azad College, West Bengal, India 3 Immunobiology Laboratory, Department of Zoology, A.B.N. Seal College, West Bengal India.

INTRODUCTION Mollusca comprises of a wide ranging invertebrate Phylum with nearly 100,000 number of living species. Mussels are aquatic bivalves distributed in diverse types of waterbodies of India. Internal visceral organs of mussels are located between the muscular foot and calcareous hard shell. Pair of valves enclose the soft body parts and are attached with adductor muscle. The space between the membranous mantle and soft visceral mass constitutes mantle cavity harbouring the gill. Gill is the chief respiratory organ of mussel which actively participates in the process of filter feeding. During filtration of the water column, the freshwater mussels are capable of filtering a large volume of water. While filtering the water for the purpose of food procurement, mussels create characteristic regional current in its aquatic environment. This movement of water mass in the form of current interferes with the important process of distribution of dissolved particulates and gases. Many of these particulates are of nutritional, metabolic and toxicological importance and the dissolved gases include oxygen, carbon dioxide etc. Filter feeding activity of mussel thus * Corresponding author: [email protected], Aquatic Toxicology Laboratory, Department of Zoology, University of Calcutta, 35, Ballygunge Circular Road, Kolkata-700019, West Bengal, India.

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influences various physiological activities of the other inhabitants of water by influencing their nutritional, immunological and toxicological status. Coexistence and perpetuation of aquatic flora and fauna of the freshwater environment is a result of successful evolutionary process where the mussels play a key role. Successful perpetuation and reproductive activity of mussel depend on biosafe propagation of the species in its toxin-free habitat. Physiological defence of mussel mostly depends on its highly evolved immunological system. Molluscan immunity is chiefly dependent on the activity of the circulating haemocytes or blood cells. In Lamellidens marginalis, the information on blood cell is limited with reference to the toxicity of common environmental contaminants. Gradual shrinkage and contamination of habitat by environmental contaminants appear to be a serious threat to the freshwater mussel. Various agrotoxins and metalloid toxin like arsenic are reported as major toxins which affect the immunological status of L. marginalis.

ECONOMIC IMPORTANCE OF INDIAN FRESHWATER MUSSEL Apart from its ecological significance, L. marginalis is a traditional item of diet for human and poultry. Both rural and selected population of urban India prefers L. marginalis as an item of daily food. However, the species is more popular among the under-privileged rural population including the tribes as food. The species is often being sold in open market for human consumption. L. marginalis is eaten in both cooked and semi-cooked form. The species is available in both shelled and deshelled form in selected daily market. The flesh of L. marginalis is used as an important component of artificial poultry feed. Following a definite ratio, the dried and processed meat of mussel is mixed with other edible components to prepare a balanced diet for poultry. Moreover, ornamental pearls can be grown in L. marginalis. Pearl is a traditional component of ornament and is highly expensive for its jewellery value. Most of the commercial pearls are usually grown in the marine oyster belonging to the genus Pinctada. In India, L. marginalis is one of the few species of freshwater origin where pearl is generated. Formation of pearl involves secretion of nacre layer which is known as ‗mother of pearl‘. The nacre is secreted around a foreign particle giving birth to a developing pearl of different size, lusture and colouration. Formation of pearl is an immunological response involving recognition of non-self and encapsulation reaction. By secreting the nacreous content, a mussel successfully encapsulates the invading particulate matter and dissociates the foreign substance from self tissue. Successful formation of pearl involves effective immune response and allied physiological processes and activities. Encapsulation reaction is an established immune function of mussel by which the animal effectively gets rid of physiological adversities elicited by foreign pathogen and parasites. Environmental chemicals impart toxicological effect on the immunological profile of the bivalves affecting possible formation of ornamental pearl. The shell of bivalve and gastropod mollusc is a rich source of calcium. Calcium is a clinically important element needed for the growth of bone and tooth. Moreover, calcium is often used by the pharmacological industry for the preparation of selected medicine. Commercial, biological and nutritional importance of Indian mussel including L. marginalis is well established and hence the species demands special attention for its biological propagation in its natural habitat.

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IMMUNITY OF MUSSEL AND ENVIRONMENTAL TOXINS Mussels rely mostly on innate immunity to combat against foreign pathogen and parasites. The natural habitat of freshwater mussels of India often remains infested with diverse forms of pathogens. Various species of microorganisms, bacteria, parasites and viruses are abundantly present in the waterbodies. The disease producing organisms continuously impart a physiological challenge on the mussels. Such situation leads to elicitation of immune reaction in the host for its successful survival. Haemocytes, the circulating blood cells of the haemolymph play a pivotal role in the freshwater mussel. Mussels rely mostly on the innate immunity to combat the environmental toxins and invading pathogens. Hard calcareous shell or valves provide the first line of defence against pathogens and toxins. Under the exposure of the pathogens, parasites and environmental toxins, the two valves are kept closed tightly to restrict the entry of unacceptable agents. In this context, highly developed adductor muscles play a significant role. Adductor muscle is capable of contraction resulting formation of a water-tight enclosure restricting the entry of pathogens and toxins. Mussels developed a highly evolved sensory system to recognise and identify the presence of toxic elements and specific environmental cues in the event of immunological challenge. Despite evolution of a highly evolved system of immuno-recognition and musculature, opportunistic entry of toxic pathogens is not uncommon. Additionally, the secretory mucous of the internal viscera provides another line of defence against the entry of pathogens and toxins. Calcareous shells and mucous are considered as external physicochemical barriers which provide an effective line of immunological defence of first order. Under poor nutritional and immunological status, their first line of defence is often breached yielding physiological exposure to toxins and pathogens. Toxins and external pathogens often escape the first line of biological defence and interact with the internal environment of the organism (Figure 1). Mussel exhibits open circulatory system with the haemocoel containing haemolymph as blood. Blood of mussel is composed of fluid and cellular component. Plasma, a serum part of the blood, contains numerous components including lectins, minerals, sugars and interleukin like molecules. Physiological and immunological activities of these components is less characterised with limited available information. Haemocytes on the other hand is a relatively better studied component of mussel immune system. Haemocytes are generated in specific haematopoietic organs under discrete cellular communication process. In molluscs, the haematopoietic organs are distributed in the body system as diffused tissues. However, occurrence of diverse population is a characteristic feature of the mussel haemocyte. Various workers have classified haemocytes on the basis of morphology and functional attributes. On having enormous diversity in body planning, habitat preference, ethology and physiological characters, classification schemes of blood cells of mussels appear to be varying. Such a situation created debate and confusion among the workers of this field. However, the immune profile of the mussel appears to be extremely different from that of the mammals. Mussel lacks antibody and complement like molecules in the blood and mostly depends on the innate immunity. Inspite of these limitations, mussels have evolved a specialised system of immunorecognition and discriminative ability of self from nonself. In this respect, the haemocytes, the chief immunoeffector cells of the mussels are reported to perform various functions like phagocytosis, nonself recognition, nutrient carriage, encapsulation, aggregation and adhesion [1].

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Aquatic Immunotoxins

Mussel

External Barrier

Haemolymph

Haemocyte

Nonself recognition

Wound healing

Phagocytosis

Cytotoxicity Immunoadhesion

Aggregation/ encapsulation

Figure 1. Immunotoxicological attribute of mussel haemocyte

Figurean 1: Immunotoxicological of mussel haemocyte Mussels contribute important member of attribute the freshwater ecosystem of India. Freshwater environment includes ponds, lakes, irrigation canals and artificial embankments. These water bodies are either of perennial or non-perennial type with different sizes and shapes. Freshwater ecosystem of India harbours an enormous biodiversity including plants and animals with multiple taxonomic identities. Uniqueness of functional interrelationship is a result of evolutionary success which permits the inhabitants of freshwater habitat to reproduce and perpetuate to ensure a balanced ecosystem. L. marginalis, the common freshwater mussel represent the Phylum Mollusca. Mollusca exhibit an enormous diversity in anatomy, physiology, habitat preference, behaviour and immunological profile. Aquatic molluscs largely rely on innate immunity to combat the pathogen and toxic exposure. In this context, the mussels largely depend on diverse immunocytes distributed in blood and elsewhere for elicitation of immune response. Report of adaptive immunity is very limited in invertebrate series. In Arthropoda, a few insect species had evolved inducible humoral factors which appeared in their blood following a brief experimental exposure of pathogen. These inducible factors like hemolin are soluble proteins with multiple isomers. Mussels are shelled bivalves and their hard shell is composed mainly of calcium carbonate. Calcified shells provide the mussels the first line of immunological barrier against environmental toxins and pathogen. Air and water tightness of internal body cavity is result of evolution of strong pair of lateral muscles known as adductor muscles. These specialised musculature and hard external shell contribute the effectiveness of immunological defence in mussel. Continuous interaction with the adverse chemical environment often leads to degeneration or loss of

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external layer of shell. Calcareous shell has the unique ability of regeneration following the principle of dynamic equilibrium of calcium uptake from external medium. Chronic exposure to immunotoxins like mineral acid and alkali interferes with the replenishment of calcium layer affecting the mussels adversely. Domestic and industrial use of mineral acid and alkali render the mussel vulnerable to tissue damage and immunoalteration. Shell, the effective external physiochemical barrier of mussel is often subjected to risk of irreversible damage caused by potential immunotoxins like sulphuric acid, hydrochloric acid, nitric acid, bleaching agents like bleaching powder and alkali like sodium hydroxide and potassium hydroxide. Once the first line of external barrier is breached off, the environmental toxins and pathogens initiate functional interaction with the cellular components of the immunological system of the mussel. The cellular array of molluscan immunity involves progenitor cells, haemostatic cells or granular cells, phagocytic cells, macrophages, nutritive cells and pigmented cells etc. Scientists classified the immunocytes of molluscs on the basis of morphology and functional attributes. For many of these classification schemes, there arose contradiction and debate and the issue remained alive till date. However, the progenitor cells are probable stem cells which are transformable to other cell types through differentiation and maturation. Phagocytes are immunocompetent cells of mussel which are involved in the process of immunorecognition and engulfment of the nonself particulates. In elicitation of immunological response, the phagocytic cells play an important role under the exposure of environmental chemicals. A discrete population of circulating blood cells or haemocytes acts as phagocytes in mussels. Haemostatic cells are involved in the process of aggregation, agglutination and lysozyme production during immunological stimulation. Nutritive cells are distinct in immunoencapsulation and wound healing process in invertebrates and may be involved in transport of various nutritive elements. Moreover, there are specific cell types of sessile behaviour which may be actively associated with immunofunctions. These nonmobile cells include pore cells distributed in the pericardium. Apart from the cellular participation, the haematopoietic organs are often involved in the process of phagocytosis [2].

IMMONOTOXIC CHEMICALS OF THE AQUATIC ENVIRONMENT Immunology deals with the physiological defence of an organism under the challenge of pathogen, parasite and toxins. Immunity of an animal exhibits two functionally operating systems i.e., cell mediated immunity and humoral immunity. Immunity in general, follow specific attributes namely innate and adaptive responses. Invertebrates like mussel depend mostly on innate immunological response and lack antibody molecules. In spite of the absence antibody molecule, invertebrates evolved an effective mechanism of discriminating the self from nonself, the essential prerequisite of immunorecognition. Successful elicitation of immune response of mussel enabled them to perpetuate in the environment as a ‗positive variant‘. In many of the biological and environmental situations, the aquatic habitat of mussel is contaminated by chemical substances of unknown or less known toxicity. Immunotoxicity involves an initiation of physiological adversity in functioning of immunological system. Immunotoxins are the chemical compounds which bear potentiality to affect immunotoxicity

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in a defined organism under specific ecophysiological condition. Nature and magnitude of immunotoxicity depend on multiple factors i.e. concentration of toxins, exposure type and span, routes of entry and nutritional state of the animal. Toxin induced shift in the immunological status of the animal may lead to aggravation of infective and disease process. Studies on human indicate that various chemicals of industrial and environmental origin are capable of producing deleterious effect on immune system. Immunotoxicity is defined as adverse effects on the functioning of immune system that results from exposure to chemical substances. Altered immune function may lead to increased incidence or severity of infectious diseases. Identification of immunotoxicants is difficult because the chemicals can cause a wide variety of complicated effects on the immune function. Observations on human and rodents have clearly demonstrated that a number of environmental and industrial chemicals adversely affect the immune system. Exposure to asbestos, benzene, polychlorinated biphenyls, polybrominated biphenyls, dioxine can lead to immunosuppression in human. Toxic agents can also cause autoimmune disorders in which healthy tissues are affected by the immune system that fails to differentiate self antigens from foreign antigens. Dieldrine induces autoimmune responses against blood cell resulting in haemolytic anaemia. Allergens are immunotoxicant compounds that stimulate the immune system and cause allergy or hypersensitivity. Many allergens can cause a variety of clinical manifestations such as asthma, rhinitis and anaphylaxis. The industrial chemicals like toluene diisocyanate and metals like nickel, beryllium are allergic agents. Freshwater ecosystem of India is often contaminated with diverse forms of environmental chemicals. The chemicals include pesticides, toxic metals, metalloids, detergents etc. Arsenic, a toxic metalloid has drawn attention to the toxicologists due to its precarious presence in the aquatic ecosystem. Extraction of the contaminated groundwater for the purpose of irrigation often contaminates the natural habitat of pearl forming mussel of India. Reports on immunotoxicity of arsenic residues in mussels are available in literature of recent past. Another group of biopesticide containing toxic azadirachtin has been posing a serious threat to the immune status of the mussels. These pesticides are used to protect plants fro pest attack. But during rainy season, residues of azadirachtin based pesticides contaminate the natural habitat of mussel affecting the normal functioning of their immune system.

MAJOR IMMUNOTOXICOLOGICAL ATTRIBUTE OF MUSSEL Mussels rely on the functional attributes of the haemocytes to combat the environmental toxins. Being the principal immunoeffector cells, haemocytes are capable of eliciting effective immunological response under the exposure of common environmental chemicals. Apart from the haemocytes, the secondary parameters of immunological functionary include shell, mucous, humoral component, gills, digestive tract and gland. Haemocytes are the cellular components of the blood of the mussels performing diverse physiological functions. They actively participate in the process of nutrient carriage, wound healing, phagocytosis, aggregation, encapsulation, cytotoxicity and nonself recognition. Functional homeostasis of the blood of the mussel is under the influence of density and physiological status of the haemocytes. Total and differential density of the haemocytes is under the influence of

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exposure of the mussels to various xenobiotics and pathogens. However, no uniform scheme of classification of haemocytes is available in the mollusc and this situation raised enough contradiction, debate and confusion among the scientists working in this field. Extensive study was done by [3] on the morphological variety of the haemocytes of L. marginalis and effect of sodium arsenite on the haemocyte density of the same species. They reported salient variations as blast like cells, agranulocytes, granulocytes, hyalinocytes and asterocytes (Figure 2 a-e). Blast-like cells were abundant and were identified by their high nuclear to cytoplasmic ratio. Their nuclei remain extended up to the peripheral region of the cell membrane. Agranulocytes exhibited large number of eosinophilic granules. Hyalinocytes were spindle shaped cells with centrally located condensed nuclei. Asterocytes are star shaped spreading cells with sharp filopodial extensions. Multiple of radiating projections of cytoplasm is characteristic to asterocytes.

(a)

(b)

(c)

(d)

(e)

(f)

Figure 2. Light microscopic images of the haemocyte subpopulation of L. marginalis stained with Giemsa‘s stain (a) blast like cell (b) agranulocyte (c) hyalinocytes (d) granulocyte (e) asterocyte or spreading haemocyte (f) a haemocyte with engulfed yeast particles (on arrow heads). (Magnification: 100x; Scale = 10µm)

In this important study, the workers examined the alteration of haemocyte density by sodium arsenite, a major, natural environmental contaminant of the mussel habitat. Mussels were experimentally exposed to sublethal concentrations of 1, 2, 3, 4 and 5 ppm of sodium arsenite for 24, 48, 72, 96 hours in static water environment. Arsenic exposure resulted a steady fall in the total count of the haemocytes along with the blast like cells. Granulocyte density was increased significantly under the exposure of sodium arsenite. Density of the asterocytes was elevated under the high concentrations of sodium arsenite. Arsenic treated mussels were examined for possible recovery of haemocyte density by exposing them in arsenic free water up to a period of 30 days. Result indicated a state of irreversible inhibition

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of cell density by sodium arsenite. A major population of haemocytes is functionally associated with innate immune response of mussel. Thus, the observation was indicative to appearance of immunotoxicity in mussel distributed in the arsenic contaminated habitat in India. Study of total count and differential count of haemocyte of the mussel under the exposure of azadirachtin based pesticide is in report [4, 5]. Azadirachtin is a highly toxic neem based limonoid and a principal component of biopesticide. This pesticide is a recent introduction in the agricultural practice of India. This less studied environmental toxin was tested on the haemocyte density of L. marginalis. Mussels were experimentally exposed to 0.03, 0.06 and 0.09 ppm of azadirachtin for 24, 48, 72, 96 hours in static water environment. Relative exposure of higher concentrations of azadirachtin yielded a significant rise in total haemocyte count. Study indicates a possible state of immunotoxicity resulted from the exposure of the mussel to azadirachtin. Both arsenic and azadirachtin appear to initiate a state of immunotoxicity by altering the total count and differential count of the circulating blood cells or immunocytes.

NONSELF SURFACE ADHESION AND PHAGOCYTOSIS Exposure to azadirachtin results a shift in the nonself surface adhesion and phagocytic response of haemocyte of freshwater pearl forming mussel of India [6]. Discriminative ability of the immunocytes to recognise self and nonself provides the premises for effective immunoelecitation. Organisms, by various physiological means, discriminate the nonself toxic particulates during their invasion into the body. This is an important immunological phenomenon evolved in the phylogeny. Molluscs developed this unique ability of differentiation as prime attribute of haemocyte functions. Discrete subpopulation of haemocyte is capable to perform immunorecognition under the challenge of parasite and pathogen. Screening of nonself surface recognition efficacy was carried out by exposing the haemocytes of azadirachtin treated mussel to glass surface. Azadirachtin exposure yielded a significant shift in the surface adhesion of selected population of haemocytes. Azadirachtin induced shift in nonself surface adhesion is suggestive to alteration in immunological status of the mussel. Phagocytosis on the other hand plays a key role in combating the invading microorganism. Phagocytosis is a widely recorded immunological phenomenon reported in almost all animal groups. Phagocytosis involves recognition, chemotaxis, attachment, engulfment, killing and digestion of nonself particulates (Figure 3). Exposure to 0.03, 0.06 and 0.09 ppm of azadirachtin upto seven days of span inhibited the phagocytic response of mussel haemocytes. In this experiment, haemocytes were challenged with cultured yeast particles and phagocytic index was determined (Figure 2f). Azadirachtin induced inhibition in phagocytosis suggested a state of immunotoxicity in the mussel. It is assumed that the mussel distributed in its natural habitat might also experience similar degree of immunotoxicity under the exposure of azadirachtin, a common environmental toxin. Arsenic is another major aquatic contaminant affected the phagocytic efficacy of freshwater mussel [7]. Phagocytic index of the haemocyte was determined in mussels exposed to 1, 2, 3, 4 and 5 ppm of sodium

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Figure 3. Immunological attributes of the haemocytes of L. marginalis involving phagocytosis and generation of cytotoxic molecule - nitric oxide. Phagocytosis is associated with (1) endocytosis of nonself particle (NP) (2) fusion of the phagosome (P) with lysosomal vesicle (LV) secreting hydrolytic enzymes (3) degradation of the NP in the phagolysosomal vesicle (PLV) (4) exocytosis of degraded undigestable residues from the haemocyte. Cytoxic molecule nitric oxide (NO) is generated during conversion of L-arginine to L-citrulline by nitric oxide synthase (NOS); nitric oxide reacts with superoxide anion (O2 ) generated by mitochondrial NADPH oxidase to form potent antipathogenic molecule – peroxynitrite (ONOO ).

arsenite for 24, 48, 72, 96 hours and 30 days.Most of the experimental exposure of sodium arsenite resulted in significant inhibition of phagocytosis of yeast by the mussel haemocytes. Asterocytes were recorded as principal cell type performing engulfment. Inhibition in phagocytosis under similar experimental condition was also noted for the haemocytes of arsenic haemocytes of L. marginalis when challenged with human red blood corpuscles (HRBC) [8]. Such impairment in the phagocytic potency of the haemocytes of arsenic exposed mussels possibly indicates a compromise in the immunological status of the animals distributed in contaminated habitats (Figure 4). Generation of nitric oxide in the haemocytes of the mussel was estimated under the experimental exposure of 1, 2, 3, 4 and 5 ppm of sodium arsenite for 24, 48, 72, 96 hours and 30 days [7]. Haemocytes are reported to have the ability to generate multiple cytotoxic agents including nitric oxide. Exposure to sodium arsenite resulted in inhibition in nitric oxide generation in the haemocytes of the mussel. Mussel haemocytes often kill intrahaemocytic pathogens with the help of nitric oxide. Nitric oxide mediated pathogen destruction is an established strategy of host‘s defence [9]. Additionally, nitric oxide chemically produces toxic residues of peroxynitrite – another potential pathogen killing agent of molluscan haemocytes (Figure 3). Inhibition of the nitric oxide generation in the haemocytes of the mussel exposed to sodium arsenite indicates impairment of this effective strategy of defence in host. This depletion in generation of nitric oxide by the sodium arsenite exposed mussels was concurred with inhibition in the phagocytic potency by the same cells. Impairment of

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phagocytosis and generation of nitric oxide renders a state of immunoincompetence in the freshwater mussel under the exposure of sodium arsenite (Figure 4). Exposure of Immunotoxin

FP

O2 NADPH oxidase

L-alanine

M

NOS

O2

Nucleus

L-citrulline

(1) (2) MN HP Oxidative stress

L

(3)

Figure 4. Immunotoxic arsenite functional attributes the Figure 4. Immunotoxiceffect effectof ofsodium immunotoxins onon thethe functional attributes of theofhaemocytes of L. marginalis involving inhibition in phagocytosis of foreign particles (FP) and suppression in generation of cytotoxic molecule - nitric oxide. In absence of proper scavenging of superoxide anion (O2 ) generated by NADPH oxidase, oxidative stress might develop causing: (1) generation of nuclear aberration like micronucleus (MN), (2) inducing leakage in the lysosome (L) biomembrane releasing self destructive hydrolytic particles (HP), (3) destabilisation of structural integrity of biomembrane of cell.

LYSOSOMAL STABILITY Arsenic has been reported to have prominent adverse effect on the lysosomal membrane stability in the freshwater mussel haemocyte [10].The retention of the neutral red, a cationic probe, within the lysosomal compartment over time is determined as an indicator of damage to the lysosomal membrane. The lysosomes of the haemocytes of L. marginalis exposed to 1, 2, 3, 4 and 5 ppm of sodium arsenite for 24, 48, 72, 96 hours, 15 and 30 days exhibited significantly low neutral red retention time. The retention time for the neutral red decreased in a dose and time dependent manner under the exposure of sodium arsenite. The lysosomal compartment stores several hydrolytic enzymes which upon released in the cell cytoplasm can cause self destruction of the cell. Arsenic rendered destabilisation of the lysosomal membrane of the haemocytes making the cells vulnerable to its own reactive molecules of immunological importance. The observation indicates the potential immunotoxicological threat induced by arsenic on the mussels and similar freshwater organisms in contaminated habitat. Recent reports indicate that the selected environmental chemicals like arsenic, azadirachtin, cadmium [11, 12] and other pesticides and detergents are imparting serious

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damage to the freshwater ecosystem of India [Table 1]. Several groups of invertebrates are under the physiological threat of selected toxins. Since many of these species including pearl forming mussel are of special economical importance, a sustainable strategy need to be adopted for protection and utilisation of this bioresource for human welfare. Table 1: Common environmental contaminants of freshwater environment of India Types of Chemical Acid

Alkali Detergent Bleaching agent Metal

Metalloid Pesticide

Name Sulphuric acid Hydrochloric acid Nitric acid Sodium hydroxide Potassium hydroxide Different commercial brands Bleaching powder Cadmium Chromium Lead Mercury Arsenic Organophosphate Pyrethroids Azadirachtin based biopesticides

REFERENCES [1] Chen, J. H. and Bayne, C. J. (1995). Bivalve mollusc hemocyte behaviors: characterization of hemocyte aggregation and adhesion and their inhibition in the California mussel (Mytilus californianus). Biol. Bull., 188, 255–266. [2] Roitt, I., Brostoff, J. and Male, D.(2001). Evolution in immunity. In: Immunology, (sixth Ed.) pp. 211-233, Mosby, Ediburgh, London. [3] Chakraborty, S., Ray, M. and Ray, S. (2008). Sodium arsenite induced alteration of hemocyte density of Lamellidens marginalis - an edible mollusk from India. Clean– Soil Air Water, 36 (2),195-200. [4] Mukherjee, S., Ray, M. and Ray, S. (2006). Azadirachtin induced modulation of total count of haemocytes of an edible bivalve Lamellidens marginalis. Proc. Zool. Soc., 59(2), 203-207. [5] Mukherjee, S., Ray, M. and Ray, S. (2008). Dynamics of hemocyte subpopulation of Lamellidens margiialls exposed to a neem based pesticide. In: Zoological Research in Human Welfare, Vol.1, Paper 40, pp.389-394, Kolkata, India. [6] Mukherjee, S., Ray, M. and Ray, S. 2009. Immunotoxicity of azadirachtin in freshwater mussel relation to surface adhesion of hemocytes and phagocytosis. Animal Biol. J., 1(2), 1-7. [7] Chakraborty, S., Ray, M., and Ray, S. (2009b). Evaluation of phagocytic activity and nitric oxide generation by molluscan haemocytes as biomarkers of inorganic arsenic exposure. Biomarkers, 14(8), 539-546.

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[8] Chakraborty, S., Ray, M. and Ray, S. 2010. Cytotoxic response and nonself phagocytosis as innate immunity of mollusc under arsenic exposure. Animal Biol. J., 1(3),173-183. [9] Bogdan, C. (2001). Nitric oxide and the immune response. Nat. Immunol., 2(10), 907916. [10] Chakraborty, S. and Ray, S. (2009a). Nuclear morphology and lysosomal stability of molluskan hemocyte as possible biomarkers of arsenic toxicity. Clean- Soil Air Water, 37 (10), 669-675. [11] Das, S. and Jana, B. B. (2003). Oxygen uptake and filtration rate as animal health biomarker in Lamellidens marginalis (Lamarck). Indian J. Exp. Biol., 41(11), 1306-1310. [12] Das, S. and Jana, B. B. (2004). Distribution pattern of ambient cadmium in wetland ponds distributed along an industrial complex. Chemosphere, 55(2), 175-185.

In: Mussels: Anatomy, Habitat and Environmental Impact ISBN: 978-1-61761-763-8 Editors: Lauren E. McGevin ©2011 Nova Science Publishers, Inc.

Chapter 20

ANTICOAGULANT AND CARBOHYDRATE INDUCED INTERFERENCE OF AGGREGATION OF MUSSEL HAEMOCYTE UNDER AZADIRACHTIN EXPOSURE Suman Mukherjee, Mitali Ray and Sajal Ray* Aquatic Toxicology Laboratory, Department of Zoology, University of Calcutta, West Bengal, India

ABSTRACT Lamellidens marginalis (Mollusca; Bivalvia; Eulamellibranchiata) is a freshwater edible mussel distributed in the wetland of different districts of WestBengal, India. Natural habitat of the species is under risk of contamination by multineeem, a newly introduced azadirachtin (limonoid) based pesticide.Blood or haemolymph of L. marginalis contains haemocytes, capable of performing diverse physiological functions. Haemocytes, the circulating blood cells are considered as immunoreactive agent capable of performing phagocytosis, nonself adhesion and aggregation. Magnitude of haemocyte aggregation was studied in depth under the exposure of 0.006, 0.03, 0.06 and 0.03 ppm of azadirachtin for varied span of exposure. Azadirachtin exposure yields decrease of haemocyte aggregation against a control level of aggregation of 34.21%. In the dynamic ecosystem of freshwater, the inhabitants participate in the struggle of niche occupation for survival and existence. Situation often leads to a state of acute predation and fight among animals. As a result, the animals experience physical wounding and loss of body fluid. Aggregation of haemocyte at wound site prevents the loss of blood and entry of microorganism and considered as an immunological response. Magnitude of hemocyte aggregation of mussel was screened under the experimental exposure of EDTA and mannose at different concentrations. Study was aimed to screen the effect of chelating agent and sugars on aggregation. For all the chemicals screened, a drastic increase in the occurrence of free cells were reported which is suggestive to role of these agents in the physiological process of haemocyte aggregation. Moreover, exposure to azadirachtin may lead to gradual loss of blood cell homeostasis of freshwater mussel distributed in its natural habitat. Continuous exposure to toxic azadirachtin may lead to a population

*

Corresponding author : [email protected], Department of Zoology, Aquatic Toxicology Laboratory, University of Calcutta, 35 Ballygunge Circular Road, Kolkata-700019, WestBengal, India,

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Suman Mukherjee, Mitali Ray And Sajal Ray decline of freshwater mussel and loss of biodiversity in the freshwater ecosystem of India.

Keywords: Azadirachtin, Bivalve, Haemocyte.

INTRODUCTION Lamellidens marginalis is a freshwater filter feeding mussel distributed in the wetlands and water bodies of WestBengal and other states of India. This edible species is a common dietary item of rural human population and is an ingredient of artificial feed for fish and poultry (Chakraborty et al., 2008). The species is not cultured and is harvested indiscriminately from its natural habitat. Natural pearl is often found in the species which emphasizes its potentiality to be a commercial aquacrop. L. marginalis, a burrowing bivalve has the natural ability to increase sediment homogenization and provide clear substratum for the colonization of epiphytic and epizoic biota thereby increasing their importance as a member of freshwater ecosystem. Rapid urbanization, toxic contamination of wetland and indiscriminate harvestation pose a serious threat to the existence and propagation of the species in its natural habitat. Azadirachtin based biopesticides are efficient in controlling pest population and considered as relatively less hazardous in relation to environmental stability and bioaccumulation (Schmutterer, 1990). Chemically azadirachtin is a tetraterpenoid which is present in the seed kernal of neem tree (Azadirachta indica). During monsoon, agricultural runoffs loaded with azadirachtin residues contaminate the natural habitat of L. marginalis. Haemocytes, the circulating cells of the bivalves act as the major immune effector cells (Adema et al., 1991; Cheng et al., 1996). Cell mediated immune response of L. marginalis is elicited through discrete subpopulation of haemocytes under the exposure of pathogen and toxins (Pattnaik et al., 2007). Phagocytosis of non-self particulates, recognition of non-self surface and cell-cell aggregation are the distinct responses offered by circulating haemocytes (Rustishauser et al., 1988; Cheng et al., 1996). Optimum aggregation of haemocyte in the haemolymph of L. marginalis is a normal physiological phenomenon. Cell-cell attachment is a significant metabolic behaviour (Chen and Bayne, 1995) exhibited by molluscs. In this present study, degree of cell aggregation was detyermined under the toxic exposure of azadirachtin. Simultaneously aggregation in vitro was experimentally interfered with ethylene diamine tetraacetic acid (EDTA) (5 to 50 mM) and mannose (5 to 50 mM) under the exposure of sublethal concentration of azadirachtin. Study was aimed to analyze the degree of aggregation, magnitude of interference under the exposure of 0.006, 0.03, 0.06 and 0.09 ppm of azadirachtin. Information will provide an information base in understanding the degree of haemocyte aggregation in presence of sublethal concentration of azadirachtin.

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MATERIAL AND METHOD Collection and Treatment of Mussels The adult healthy L. marginalis with shell size of 7-8 cm were manually collected from the selected wetlands of the district of South 24 Parganas of West Bengal, India. Animals were transported to the laboratory in rectangular plastic containers with a dimension of 12‘x18‘x 6‘ at a density of 4-6 individuals per box in moist condition. Prior to experimentation, animals were acclimatized for 15 days in the laboratory. During acclimatization, L. marginalis were maintained in aquaria with fresh supply of pond water with temperature of 29°C±3°C and the animals received uniform ration of illumination. During the course of acclimatization and experiment, the animals were fed with chopped Hydrilla sp. and common aquatic weeds (Raut, 1991). Routine replenishment of water was carried out in every 12 hours to avoid residual toxicity. Aqueous solutions of Multuneem (Multiplex, India Private Limited, Azadirachtin E.C. 0.03%) formulations were prepared in Borosilicate glass containers with azadirachtin concentrations of 0.006, 0.03, 0.06, and 0.09 ppm. The pH of the solution was maintained at 7.2. Each experimental set consisted of 10 animals of same shell length. Animals were exposed to a volume of 5 litre of pesticide solution for varied span of exposure i.e. 1,2,3,4,7,15 and 30 days. For control, a set of animals were kept in identical volume of pesticide free analytical grade water. The experiments were carried out in static water environment and fresh solutions of pesticide were replenished in every 12 hour.

Collection of Haemolymph Shells of the animals were cleaned by gentle brushing under running tap water to remove adhered plant species and clay particles. The shells of control and posttreated animals were sterilised with ethanol and were bled aseptically, and the haemolymph was collected from posterior adductor muscle (Brousseau et al., 1999) by a sterile syringe with needle of 22 gauge at a volume not exceeding 1ml per bleed per day .The bleeding and collection procedure was carried out at 4C (Cold laboratory, Blue Star) to prevent cell aggregation.

Cell Viability and Enumeration The viability of haemocytes of L. marginalis of all experimental variants was tested with 2% Trypan blue for 10 min following the dye exclusion principle. Cell enumeration was carried out by Neubauer hemocytometer. Total number of viable haemocytes was determined microscopically by estimating the percentage of stained and unstained cells (Suave et al., 2002). Experiments were carried out with cell suspension with greater than 95 % viable haemocytes.

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Aggregation Assay of Haemocyte Aggregation assay (Chen and Bayne, 1995) involved preparation of free cell suspension by treating the freshly collected control and toxin exposed haemolymph with 20% formalin (Merck, India) at a ratio of 1:1 (V/V). Percent aggregation was determined using following formula:

Total free cell numbers in test treatment The percentage of free cells =

× 100 Total free cell numbers in fixed fresh haemolymph

The experiment was repeated for five times. Fixed monolayer of cells was stained with Giemsa‘s stain (Himedia, India) or hematoxylin- eosin stain (Himedia, India) on slide for examination and photo-documentation under microscope (Axiostar, Zeiss, Germany) with digital image recording facility. Phase contrast image analyses of live cells were carried out using phase optics fitted with digital camera.

Aggregation Interference by EDTA and Mannose in vitro Control and treated haemocytes were mixed with 5mM, 10mM, 25mM and 50mM of EDTA (SRL, India) and mannose (SRL, India) as possible interfering agent at a ratio of 1:1 (V/V), (Kenney et al., 1972). To obtain values for ‗no aggregation‘ we proceeded as follows: fresh haemolymph was mixed with 20% formalin (1: 1, V/V) to immediately block cell aggregation. Percent aggregation was determined using the formula of Chen and Bayne (1995).The experiment was repeated for five times.

RESULT Cell Aggregation under Azadirachtin Exposure Immediately after collection of haemolymph from mussel, the haemocytes remain dispersed and appeared as round in shape (Figure1). However, their shape gradually changed from round to elongated ones within ten minutes. Sometimes, aggregation (Figure 2) occurred rapidly during the process of bleeding. After initial intercellular contact, cells were found to form aggregate (Figure 3) and form clump.

Anticoagulant and Carbohydrate Induced Interference …

Figure 1. Phase contrast microscopic image of weak aggregation response of haemocytes of L. marginalis. x1000.

Figure 2. Phase contrast microscopic image of moderate aggregation response of haemocytes of L. marginalis. x1000.

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Figure 3. Phase contrast microscopic image of cohesive aggregation response of haemocytes of L. marginalis. x1000.

Cell aggregation or clump formation (Figure 4) is involved in maintaining blood homeostasis and wound healing (Sminia, 1981) process in molluscs. The aggregation of haemocyte in bivalves is reversible and aggregated haemocytes may disperse and re-enter the circulatory system partially as wound healing progresses. An increase in percentage of haemocyte aggregation was recorded against all the concentrations of pesticide formulations for 1 and 2 days of exposure (Figure 5). However, haemocytes collected from L. marginalis exposed to 0.006 ppm of azadirachtin showed a progressive increase of aggregation from 2 to 30 days (Figure 5). A decrease in percentage haemocyte aggregation was recorded against 0.03, 0.06 and 0.09 ppm of azadirachtin exposure after 2 days in comparison to control (Figure 5).

Figure 4. Light microscopic image of strong aggregation response of haemocytes of L. marginalis. x100.

Anticoagulant and Carbohydrate Induced Interference …

Control

0.006ppm

0.03ppm

0.06ppm

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0.09ppm

Figure 5. Dynamics of aggregated haemocytes of L. marginalis exposed to azadirachtin.

100Aggregation in Presence of EDTA and Mannose Cell

0.09pp m

0.06pp m

0.03pp m

0.006p pm

Control

50 0 Interference of haemocytes aggregation was studied extensively by treating the cells with anticoagulent agent, EDTA and carbohydrate mannose of varying concentrations to determine highest and lowest values of free cells in respect to control (Figure 6 & 7). Azadirachtin induced modulation of interference of aggregation was recorded under the exposure of 0.006, 0.03, 0.6 and 0.09 ppm of azadirachtin for highest span of exposure. A concentration of 50 mM of EDTA was found to be the effective concentration in generation of 80% free haemocytes in control against generation of 95% free haemocytes in treated set (0.09 ppm/ 7 days). A concentration of 50 mM of mannose was found to be the effective concentration in generation of 72% free haemocytes in control against generation of 90% free haemocytes in treated set (0.09 ppm/ 7 days). Data is indicative to azadirachtin induced modification of haemocyte surface characters.

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100 90

Free haemocyte (%)

80 70 60 50 40 30 20 10 0

5

10

25

50

EDTA (mM)

Control

0.006ppm

0.03ppm

0.06ppm

0.09ppm

Figure 6. EDTA induced interference of aggregation of haemocytes of L. marginalis exposed to azadirachtin.

10 0

0.09pp m

0.06pp m

70

0.006p pm

Free haemocyte (%)

80

0.03pp m

90

Control

100 50 0

60 50 40 30 20 10 0

5

10

25

50

Mannose (mM)

Control

0.006ppm

0.03ppm

0.06ppm

0.09ppm

Figure 7. Mannose induced interference of aggregation of haemocytes of L. marginalis exposed to azadirachtin.

0.09pp m

0.06pp m

0.03pp m

0.006p pm

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100 50 0

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DISCUSSSION Haemocytes, the circulatory blood cells are considered as immunoreactive agents capable of performing aggregation. Optimum aggregation of haemocyte in the haemolymph of L. marginalis is a normal physiological phenomenon. Cell-cell attachment is a significant metabolic behaviour (Chen and Bayne, 1995) exhibited by molluscs. Aggregation of haemocytes at the wound site prevents the loss of blood and entry of microorganisms and considered as an immunological response. Aggregation of haemocytes around invaded microorganisms or pathogen is considered as an effective immune reaction. Many workers termed this phenomenon as ―encapsulation reaction‖ or ―encapsulation response‖, an important cellular immunological reactivity (Nappi and Christensean, 2005). Through successful encapsulation, a molluscan host species restricts the unsafe proliferation and invasion of pathogen through physical detachment. Most of cellular aggregation is mediated through divalent cations or sugar residues as evident from the studies carried out in other invertebrate species (Takahashi et al., 1994). Bivalve often experiences subchronic and chronic exposures of pesticide residues in its natural habitat. In this present study, haemocyte aggregation was screened in depth under the experimental exposure of azadirachtin and possible interference of aggregation was studied under the treatment of EDTA, a cation chelator and mannose. Aggregation of haemocytes of invertebrates is considered as an important metabolic function (Chen and Bayne, 1995) and less studied in L. marginalis. In normal physiological condition, 34.21% of haemocytes expressed cell aggregation. Exposure to 0.03, 0.06 and 0.09ppm of azadirachtin expressed an increase in aggregation for 48 hours of exposure followed by a decrease in aggregation. Exposure to 0.09 ppm of azadirachtin for 7 days yielded a lowest of cell aggregation as 7%. Azadirachtin induced inhibition of aggregation after 48 hours of exposure is indicative to a state of immunological alteration and partial breakdown of blood homeostasis. Such a situation may lead to uncontrolled loss of blood following an injury at natural habitat contaminated by azadirachtin. Azadirachtin treated haemocytes, when exposed to varying concentrations of EDTA and mannose resulted dose responsive aggregation. A highest concentration of 50 mM of EDTA and mannose yielded the highest degree of free cell. In this experiment, azadirachtin treated haemocytes were exposed to specific chemical agent like EDTA and mannose for screening the possible shift in aggregation magnitude. Stepwise increase of occurrence of free cell under the exposure of EDTA is indicative of possible role of divalent cations and sugar residues in the physiological event of intercellular attachment. The control level of occurrence of free haemocytes was less in comparison to experimental exposure to EDTA and mannose. Decrement of aggregation response by interfering agents under azadirachtin exposure was indicative to the involvement of cations in the process of intercellular aggregation. Exposure of haemocytes to azadirachtin resulted in a chronic stress at the level of haemocyte aggregation. Exposure resulted in a shift in aggregation response of haemocytes. In the competitive environment of freshwater, animals struggle for food, space and mate and are often subjected to accidental tissue injury. Haemocyte aggregation is reported to be a major mechanism of blood clot formation at the site of injury thus arresting the fatal loss of blood (Holmblad and Soderhall, 1999; Theopold et al., 2004).Simultaneously, formation of larger clot or thrombus and their persistence in blood may lead to cardiac arrest resulting instant death of the species. However, the maintenance of blood homeostasis is an essential

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physiological requirement which controls the optimum level of haemocyte aggregation as effective physiological reaction. Azadirachtin induced alteration of haemocyte aggregation is a precarious physiological condition which may lead to death of the species following tissue injury. EDTA and mannose interfered with haemocyte aggregation at different concentrations. Data is suggestive of positive roles of divalent ions and carbohydrate residues in the cellular process of haemocyte aggregation of L. marginalis.

ACKNOWLEDGMENT Authors thankfully acknowledge DST FIST and UGC SAP Government of India, for departmental instrumental facility and necessary fund support.

REFERENCES Brousseau, P., Payette, Y., Tryphonas, H., Blakley, B., Boernaus, H., Flipo, D., Fournier, M., 1999. “Manual of Immunological Methods”. CRS Press, Boca Raton, FL. Chakraborty, S., Ray, M. and Ray, S. 2008. Sodium arsenite induced alteration of hemocyte density of Lamellidens marginalis – an edible molluscs from India. Clean Soil Air Water., 36 (2):195-200. Chen, J. H. and Bayne, C. J. 1995. Bivalve Mollusc Hemocyte Behaviours: Characterization of Hemocyte Aggregation and Adhesion and Their Inhibition in the California Mussel (Mytilus californiasus). Biol. Bull., 188: 255-256. Cheng, J. H., Yang, H. Y. Y., Peng, S. W., Cheng, Y. J. and Tsai, K.Y. 1996. Characterization of abalone (Haliotis diversicolor) hemocytes in vitro. Biol. Bull., 31(1): 31 – 38. Holmblad, T. and Soderhall, K. 1999. Cell adhesion molecules and antioxidative enzymes in a crustacean, possible role in immunity. Aquacult., 172: 111 – 123. Kenney, D. M., Belamarich, F. A. and Shepro, D. 1972. Aggregation of horseshoe crab (Limulus polyphemus) amebocytes and reversible inhibition of aggregation by EDTA. Biol. Bull., 143: 548 – 567. Nappi, A.J. and Christensean, B.M. 2005. Melanogenesis and associated cytotoxic reactions: application to insect innate immunity. Insect. Biochem. Mol. Biol., 35: 443-459. Pattnaik, S., Chainy, G.B.N. and Jena, J.K. 2007. Characterization of Ca2+-ATPase activity in the gill microsomes of freshwater mussel, Lamellidens marginalis (Lamarck) and heavy metal modulations. Agricult., 270 (1-4): 443-450. Raut, S.K. 1991. Laboratory Rearing of Medically and Economically Important Molluscs. In “Snails, Flukes and Man”. ( M.S. Jairajpuri, Ed.), pp.79- 83. Zoological Survey of India Pub. Rustishauser, U., Acheson, A., Hall, A. K., Mann, D. M. and Sunshine, J. 1988. The neural cell adhesion molecule (NCAM) as a regulator of cell-cell interaction. Sci., 40: 53 – 57. Sauve, S., Brousseau, P., Pellerin, J., Morin, Y., Senecal, L., Goudreau, P. and Fournier, M. 2002. Phagocytic activity of marine and fresh water bivalves: in vitro exposure of hemocytes to met (Ag, Cd, Hg and Zn). Aquat. Toxicol., 508 (3-4)189-200.

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Schmutterer, H. 1990. Properties and potential of natural pesticides from the neem tree Azadirachta indica. Annu. Rev. Entomol., 35: 271-297. Sminia, T. 1981. Gastropods pp 191-232 In ―Invertebrate blood cells”, N.A. Ratcliffe and A.F. Rowiay. Eds. Academic Press. New York Takahashi, K.G.., Azuma, K. and Yokosawa, H. 1994. Hemocyte aggregation in the solitary ascidian Halocynthia roretzi: plasma factors, magnesium ion and met-lys- bradykinin induced the aggregation. Bio. Bull., 186: 247-253. Theopold, U., Schmidt, O., Soderhall, K. and Dushay, S. 2004. Coagulation in arthropods: defence, wound closure and healing. Trends in Immunol., 25(6): 289 – 294.

In: Mussels: Anatomy, Habitat and Environmental Impact ISBN 978-1-61761-763-8 Editor: Lauren E. McGevin ©2011 Nova Science Publishers, Inc.

Chapter 21

THE ORIGIN OF POPULATIONS OF DREISSENA POLYMORPHA NEAR THE NORTH-EASTERN BOUNDARY OF ITS DISTRIBUTION AREA I. S. Voroshilova1, V. S. Artamonova2 and V. N. Yakovlev1 1

Papanin Institute of the Biology of Inland Waters, Russian Academy of Sciences, Borok, Nekouzskii raion, Yaroslavl oblast, 152742 Russia 2 А. N. Severtsov Institute of Ecology and Evolution Moscow, 33 Leninskij prosp., 119071, RUSSIA

ABSTRACT The expansion of the zebra mussel, Dreissena polymorpha, is observing during at least two hundred years. It has increased the speed at the end of the twentieth century. Adaptation of these species to new natural conditions beyond bounds of ecological optimum is interesting in evolutionary aspect. However, populations of the northern boundaries of the present range, which are the most essential in this respect, practically are not studied until now. For studies of microevolution processes the phylogeographic methods with application of mitochondrial DNA analysis are widely used. Haplotype diversity of the mtDNA locus, encoding cytochrome c oxidase subunit I for D. polymorpha is learned across the large part of its distribution area, however the previous investigations have no included the boundary populations of the north-eastern regions. Samples of the zebra mussels located at 580 – 640 N were studied in our investigation. Two of Caspian haplotypes have been found here, that supported the assumption about the spread of the zebra mussel into the northern area from Caspian Sea. The results of our work supply the general pattern of gene geography of D. polymorpha, and suggested to possible existence of secondary sources of the zebra mussel spread beyond the bounds of Ponto-Caspian region.



E-mail: [email protected]

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Keywords: Boundary populations, zebra mussels, Allele-specific PCR.

INTRODUCTION The bivalve zebra mussel (Dreissena polymorpha (Pallas)) is one of the most rapidly expanding species. The original geographic range of the zebra mussel comprised fresh and brackish waters of Ponto-Caspian sea basins (Andrusov 1897; Kinzelbach 1986; Starobogatov and Andreeva 1994). This species began to expand as early as prehistoric times; however, the greatest increase in its range has been due to shipping traffic (Andrusov 1897; Skorikov 1903; Dekzbakh 1935; Mordukhai-Boltovskoi 1960; Kharchenko 1995; Marsden et al. 1995; Müller et al. 2001; Orlova 2002; Stepien et al. 2002; Minchin et al. 2003; Astanei et al. 2005; Gelembiuk et al. 2006; etc.). In Europe, D. polymorpha invaded Italian and Irish waters and the northeastern Gulf of Finland in the past decades (Antzulevich and Lebardin 1990; Valovirta and Porkka 1996; Ram and McMahon 1996; Minchin et al. 2003, Orlova and Panov 2004; Quaglia et al. 2007). In the 20th century it even reached North America, where it invaded the Great Lakes and expanded southwards to the Gulf of Mexico (Hebert et al. 1989; Strayer et al. 1991). Invasions of the zebra mussel have had serious ecological and economic consequences (Karataev et al. 1994; Kharchenko 1995; Mackie and Schloesser 1996; Ram and McMahon 1996), which has made the sources and trends of the species' expansion a particularly important issue. Phylogeographic methods using molecular markers have been employed to determine the origin of zebra mussel populations (Boileau and Hebert 1993; Marsden et al. 1995, 1996; Stepien et al. 2002, 2003, 2005; Astanei et al. 2005; Gelembiuk et al. 2006; May et al. 2006). The polymorphism and geographic distribution of the haplotypes of the mitochondrial DNA (mtDNA) locus encoding subunit I of cytochrome oxidase (COI) have been studied in most detail. May et al. (2006) used DNA sequencing to identify five haplotypes within the D. p. polymorpha range. Only in the Caspian Sea basin were all the five haplotypes found. In populations of the Black Sea basin, as well as in all other samples, May et al. found only two haplotypes, A and B. These results led the authors to the conclusion that all invasive populations of D. p. polymorpha, including those of the northeastern part of the range, originated from the Black Sea basin. It should be noted, however, that the northeastern part of the range was not analyzed sufficiently in the cited study. It was represented by only two small samples (20 and 14 animals) from the Gulf of Finland (the Baltic Sea) and the Rybinskoe Reservoir (the Volga River) (May et al. 2006). At the same time, most previous researchers had a different view on the origin of zebra mussel populations of northern Russian waters. It was assumed that this species expanded northwards from the Volga via natural water bodies and artificial canals connecting the rivers that belong to the basins of the Baltic, Caspian, and White seas (Skorikov 1903; Dekzbakh 1935; Mordukhai-Boltovskoi 1960; Starobogatov and Andreeva 1994). Although large populations of zebra mussel existed only in the middle Volga River until reservoirs were constructed (Bening 1924), small populations of the mollusc were often found in the upper river, as well as in the water bodies connecting the Volga basin with those of the

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Baltic and White seas (Skorikov 1903; Kutshina 1964; Stalmakova 1977; Vygolova 1977; Slepukhina and Vygolova 1981; Sergeeva 2008). Many authors believe that large D. polymorpha populations cannot exist for a long time north of 59° N because of adverse climatic conditions (Bening 1924; Starobogatov and Andreeva 1994; Kharchenko 1995). Indeed, data on northern populations are contradictory. For example, Gassies and Lokard included the zebra mussel in the lists of molluscs inhabiting lakes Ladoga and Onega in the period from 1868 to 1900, whereas Kessler and Linko did not mention the species among bivalves living in these water bodies (Skorikov 1903). However, the existence of the northernmost D. p. polymorpha population in the Severnaya Dvina River has been repeatedly confirmed by subsequent reviews (Skorikov 1903; Ostroumov 1957; Kutshina 1964; Sergeeva 2008). The origin and characteristics of marginal zebra mussel populations is an issue of critical importance. Indeed, microevolution is assumed to be considerably more rapid in marginal populations than in the central part of a species range. When considering the periphery of a species range, Mayr (1974) distinguished a boundary region where the reproductive capacity and mortality due to adverse environmental conditions incessantly compete with each other. Like many other researchers, Mayr believed that the extreme conditions of the periphery of a species range could cause an increase in the differences between its marginal and central populations (Ford 1971; Mayr 1974; Lewontin 1978, etc.). Therefore, we analyzed the distribution of the haplotypes of the mtDNA COI locus in marginal populations of D. p. polymorpha and compared samples from these populations with those collected in the lower reaches of the rivers belonging to the Black Sea and Caspian Sea basins.

MATERIALS AND METHODS Molluscs were collected in the years 2004–2006 in water bodies belonging to the Vyshnii Volochek, Volga–Baltic, and Severnaya Dvina water systems (natural water bodies and canals between them), which connect the basins of the White, Caspian, and Baltic seas (Figure 1). To determine the characteristics of marginal populations, we also analyzed samples from the original species range in the basins of the Black Sea (the Dniester estuary and the Dnieperodzerzhinskoe Reservoir) and the Caspian Sea (the Volga Delta). Table 1 shows the sizes of the samples. The molluscs were sampled by means of a trapezoid dredge and collected from stake nets and bottom trawls; in addition, they were manually collected from natural substrates. When sampling the molluscs from the water bodies where a related species D. bugensis occurs along with D. polymorpha, we used morphological and allozyme analyses for diagnosing these species and their hybrids (Voroshilova et al., in press). Soft tissues of each individual mussel were fixed in 96% ethanol (1 : 5). The valves of the shells were dried in the air at room temperature. Phenol–chloroform extraction (Sambrook et al. 1989) was used to isolate total DNA from ethanol-fixed tissues. A 710-bp PCR fragment of the region encoding COI was obtained

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using the primers described by Folmer et al. (1994) according to the amplification protocol recommended by the authors. The nucleotide sequences of the primers were the following: LCO1490: 5'–GGTCAACAAATCATAAAGATATTGG–3', HCO2198: 5'–TAAACTTCAGGGTGACCAAAAAATCA–3'. Polymorphism of mtDNA was analyzed as shown in Figure 2.

Figure 1. Sampling locations of populations of the zebra mussel, Dreissena polymorpha, and some directions of its dispersal in Eastern Europe. Populations are numbered from 1 to 12 (listed in Table 1). Arrows indicate possible directions of the zebra mussel dispersal. 1 – the boundary of its range as described by Starobogatov (Starobogatov & Andreeva 1994). 2 – artificial canals. Artificial canals and water systems: A. Dnieper-Neman system (via a canal between Jaselda and Shara rivers); B. BerezinaDaugava system; C. Dnepr-Bug system; D. Volga-Don Canal; E. Vyshnii Volochek system; F. Tikhthin system; G. Moskva-Volga Canal; H. Volga-Baltic system; I. Severo-Dvinskii Canal; J. White SeaBaltic Canal; K. Kama-Severnaya Dvina Canal.

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Table 1. Sampled populations of D. p. polymorpha Site

Sample location

1 2 3 4 5

Dniester River Dnieper River, Dnieperodzerzhinskoe Reservoir Volga Delta Sutka River, Rybinskoe Reservoir Suda River, Rybinskoe Reservoir Cooling pond of the Cherepovets thermoelectric power plant, Suda River Siz,menskii Pool, Sheksninskoe Reservoir Sheksna River, Sheksninskoe Reservoir Lake Kubenskoe Belousovskoe Reservoir Lake Uzhin Severnaya Dvina River

6 7 8 9 10 11 12

Basin Black Sea Black Sea Caspian Sea Caspian Sea Caspian Sea Caspian Sea Caspian Sea Caspian Sea White Sea Baltic Sea Baltic Sea White Sea

Sample size 36 29 32 35 27 33 34 35 29 26 31 27

Figure 2. The design of nucleotide sequence analysis for the fragment of СОI mtDNA Dreissena polymorpha. The sequence is included in the GenBank international database (AF510508).

The nucleotide polymorphism at position 31 (Figure 2) was determined by digesting the full-length PCR product with the DraI restriction endonuclease (Fermentas, Lithuania) under the conditions recommended by the manufacturer. The enzyme cleaved the nucleotide sequence that contained A but not G at this position (Figures. 2, 3). Allele-specific PCR (AS PCR) was performed to identify the nucleotide polymorphisms at positions 153 and 333. For this purpose, we developed two pairs of allele-specific primers: Fc and Fd for identifying the nucleotide at position 333 and Ra and Rb for position 153:

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I. S. Voroshilova, V. S. Artamonova and V. N. Yakovlev Fc: 5'–CTAGAGTTATAGGACATTCAGAG–3', Fd: 5'-CTAGAGTTATAGGACATTCAGAC–3', Ra: 5'–CTAGTATTATTGGTACCAATCTA–3', Rb: 5'–CTAGTATTATTGGTACCAATCTG–3'.

Each of these nucleotide positions was tested in two parallel experiments. Along with the primers LCO1490 and HCO2198 (the synthesis of the full-length PСR product served as a positive control), one of the allele-specific primers was added to the amplification mixture. The appearance of a truncated PCR product along with the full-length one in the course of amplification indicated that the nucleotide complementary to the 3' end of the allele-specific primer was at the tested position in the given DNA sample.

Figure 3. Restriction of PCR products using the endonuclease Dra I. Lanes1–5 are D. polymorpha; lane 6, 50 bp ladder; 7, 8 are D. bugensis (positive control).

We used a PTC-100™ (MJ Research, Inc.) or Amply 4 (Biokom) thermocycler to carry out AS PCR in 25 μl of an amplification buffer solution (Fermentas) containing 10 mM Tris– HCl (pH 8.9), 50 mM KCl, and 0.08% Nonidet P40. The buffer solution for testing the samples with the use of the allele-specific primers contained 2.0 mM MgCl2 in the case of the Fc and Fd primers and 3.0 mM MgCl2 in the case of the Ra and Rb primers. In all cases, the amplification mixture contained 100–300 ng of total DNA, 10 pmol of each primer, 200 nmol of each of the four deoxyribonucleotides, and 0.5–1.0 U of Taq polymerase (Bionem, Russia).

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Figure 4. Selection of optimal condition for allele-specific amplification using the 3-primer system. (A) Lanes 1, 3, 5, 8 are PCR products with using universal primers (LCO1490, HCO2198) and allelespecific primer Fc; lanes 2, 4, 6, 9 are PCR products with using universal primers (LCO1490, HCO2198) and with allele-specific primers Fd; lane 8, 50 bp ladder. (B) Lanes 1, 3, 6, 8 are PCR products with using universal primers (LCO1490, HCO2198) and allele-specific primer Ra; lanes 2, 4, 7, 9 are PCR products with using universal primers (LCO1490, HCO2198) and with allele-specific primers Rb; lane 5, 50 bp ladder.

The following reaction profile was optimal: 95°C for 4 min; 35 DNA synthesis cycles of 95°C for 50 s, 62°C for 1 min, and 72°C for 1 min; and final extension at 72°C for 10 min.

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Table 2. Haplotypes of СОI mtDNA, which are detected according to the design in this study Haplotype А В D I tip

Positions of nucleotide substitutions in the fragment of СО I mtDNA* 31 bp 153 bp 333 bp G T C G T G G C G А T С

In the rare cases when a truncated PCR product was absent or, conversely, present in both variants (Fc + Fd and Rа + Rb), the annealing temperature was varied between 54 and 64°C, which always allowed us to eventually determine which nucleotide is contained at the analyzed position of the given sample (Figure 4). The PCR and restriction products were identified by 1.5–2.0% agarose gel electrophoresis with the use of Tris–acetate buffer solution (pH 8.0). Gene Ruler™ DNA Ladder double-stranded markers with a step of 50 bp (Fermentas) were used as markers of nucleotide sequence length. A combined haplotype was defined as the combination of nucleotides at positions 31, 153, and 333 (Table 2, Figure 2). The χ2 test modified for small samples (Zhivotovsky 1991) was used to estimate the significance of differences in mtDNA haplotypes between samples. The primary DNA sequence was analyzed in nine samples of the full-length fragment of the COI mtDNA locus. The sequencing was performed by means of an automated sequencer with a MegaBACE-500 electrophoretic chamber (48 capillaries) with the use of a DYEnamic ET, Dye Terminator Cycle Sequencing KIT for Mega BACE DNA Analysis System in the EvroGen Laboratory (Moscow, Russia). The SeqMan 4.00 software (DNASTAR, Inc.) was used to analyze the nucleotide sequence.

RESULTS We searched for D. polymorpha populations at the northeastern periphery of its current range in the years 2004 and 2005. As a result, small populations were found in the Sheksninskoe and Belousovskoe reservoirs of the Volga–Baltic Waterway and water bodies belonging to the White Sea basin, including Lake Kubenskoe, the mouths of its tributaries, and the Severnaya Dvina River (Figure 1). It is noteworthy that only small colonies of D. polymorpha (no more than three aggregations of 20–30 mussels each), which were distributed very irregularly, were found on natural substrates in the Belousovskoe Reservoir and Lake Kubenskoe. Single zebra mussels and small groups (up to 10 molluscs) on the shells of Unionidae were found on silty ground in the Sheksninskoe Reservoir. The largest aggregations of zebra mussels were found on stake nets in Lake Kubenskoe, as well as in the Siz'menskii Pool of the Sheksninskoe Reservoir and in the Severnaya Dvina. Samples for sequencing were taken from northern water bodies belonging to the basins of the Caspian, Baltic, and White seas (from the Rybinskoe and Sheksninskoe reservoirs and the Severnaya Dvina River, two samples from each; from the Belousovskoe Reservoir, three

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samples). All nucleotide sequences proved to correspond to those published earlier and included in the GenBank international database. Earlier, they were called haplotypes A, B, C, and D (May et al. 2006; Gelembiuk et al. 2006; Gen Bank: DQ840121, DQ840122, DQ840123, DQ840124). Zebra mussels with the A haplotype were found in the Sheksninskoe and Belousovskoe reservoirs; those with the B haplotype, in the Belousovskoe Reservoir; those with the C haplotype, in the Sheksninskoe Reservoir, and those with the D haplotype, in the Severnaya Dvina River. Since these haplotypes only differed from one another at three nucleotide positions (6, 153, 333), we developed two pairs of allele-specific primers permitting large-scale analysis of samples for identifying the nucleotides at positions 153 and 333 (the nucleotide at position 6 was not analyzed because it was difficult to identify the truncated PCR product against a background of the full-length one in agarose gel). In addition, an earlier study on zebra mussels from the Bug River estuary of the Black Sea (Therriault et al. 2004) found a characteristic nucleotide substitution at position 31 that could be identified using the DraI restriction endonuclease. The procedure of the large-scale analysis is described under "Materials and Methods." Having analyzed the molluscs from the detected populations according to our methodology, we found carriers of three haplotypes of the COI mtDNA locus (A, B, and D). The A and B haplotypes were prevailing in all samples studied (Figure 5, Table 3).

Figure 5. Haplotype frequency of COI for sampling Dreissena p. polymorpha. (1) Dniester River, (2) Dnieperodzerzhinskoe Reservoir, Dnieper River, (3) Volga Delta, (4) Rybinskoe Reservoir, Sutka River, (5) Rybinskoe Reservoir, Suda River, (6) Cooling pond of the Cherepovets thermoelectric power plant, Suda River, (7) Siz,menskii Pool, Sheksninskoe Reservoir, (8) Sheksna Reservoir, (9) Lake Kubenskoe, (10) Belousovo Reservoir, (11) Lake Uzhin, (12) Severnaya Dvina River, (13) Seine River, (14) IJsselmeer Lake, (15) Danube River, (16) Ingulets River, (17) Kherson, Dnieper River, (18) Kiev Reservoir, Dnieper River, (19) Lagan, Caspian Sea canal, (20) Liman, Caspian Sea canal, (21) Astrakhan, Volga River, (22) Ural River, (23) Volgograd, Volga River, (24) Rybinsk Reservoir, Volga River, (25) Gulf of Finland. 1-12 - our data (marked by points), 13-15 - data of May et al. 2006.

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I. S. Voroshilova, V. S. Artamonova and V. N. Yakovlev Table 3. Haplotype frequencies of СОI mtDNA in investigated samplings of D. polymorpha

Site

Haplotype frequencies Sample location

А

В

D

1

Dniester River

0,03

0,97

0,00

2

Dnieper River, Dnieperodzerzhinskoe Reservoir

0,89

0,11

0,00

3

Volga Delta

0,44

0,56

0,00

4

Sutka River, Rybinskoe Reservoir

0,74

0,26

0,00

5

Suda River, Rybinskoe Reservoir

0,93

0,07

0,00

6

0,85

0,15

0,00

7

Cooling pond of the Cherepovets thermoelectric power plant, Suda River Siz,menskii Pool, Sheksninskoe Reservoir

0,73

0,27

0,00

8

Sheksna River, Sheksninskoe Reservoir

0,57

0,40

0,03

9

Lake Kubenskoe

1,00

0,00

0,00

10

Belousovskoe Reservoir

0,69

0,27

0,04

11

Lake Uzhin

0,61

0,35

0,03

12

Severnaya Dvina River

0,04

0,59

0,37

However, the rarer D haplotype was also found in mollusc populations of water bodies belonging to all the sea basins studied except the Black Sea one (i.e., the basins of the Caspian, Baltic, and White seas). It was found in samples from the Sheksna River of the upper Volga basin (which is part of the Caspian Sea basin), Lake Uzhin and the Belousovskoe Reservoir of the Baltic Sea basin, and the Severnaya Dvina River of the White Sea basin. We did not find significant differences in the haplotype frequencies between samples collected from different parts of the same water body (the Sheksna River and Siz'menskii Pool; the cooling pond of the Cherepovets thermoelectric power plant and the Suda River proper). The differences between the samples from the Rybinskoe and Belousovskoe reservoirs and Lake Uzhin were also nonsignificant. The frequencies of the prevailing haplotype (A) in the zebra mussel populations of Lake Kubenskoe, the Suda River, and the cooling pond were close to 1; therefore, the samples from these populations significantly differed from most samples from all other zebra mussel populations of the Volga–Baltic system (p < 0.001–0.025). In addition, the sample from the Severnaya Dvina considerably differed in the mtDNA haplotype frequencies from the samples from all other northern waters (p < 0.001). Molluscs with the B haplotype were prevailing in this sample, and the frequency of the D haplotype was substantially higher than in other populations.

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DISCUSSION To the north of the Rybinskoe Reservoir, zebra mussels are mainly distributed in the form of small groups that are often impossible to detect by the standard methods of collecting zoobenthos. The study of populations at the periphery of the species range is substantially complicated by the difficulty to find again some of the mollusc populations that were detected earlier. The origin of the zebra mussel populations of the upper Volga is being actively discussed, but there is no consensus on this issue thus far. For example, mussel populations of the Caspian Sea basin have long been regarded as the most probable source of D. polymorpha in the upper Volga region (Andrusov 1897; Skorikov 1903; Starobogatov and Andreeva 1994). Subsequent analysis of the frequency distribution of the COI mtDNA haplotypes led to the assumption that the upper Volga D. polymorpha populations had most probably originated from the Dnieper River basin populations (Gelembiuk et al. 2006; May et al. 2006). However, of all D. polymorpha populations of the upper Volga, only a small sample (14 animals) from the Rybinskoe Reservoir has been analyzed; hence, it cannot be excluded that this sample contained no molluscs with characteristic Caspian haplotypes for merely accidental reasons. To test the hypothesis that the upper Volga populations of the zebra mussel originated from the Dnieper basin, we analyzed a more representative sample from the Rybinskoe Reservoir (35 mussels) and, in addition, the samples from the mollusc populations of the Volga–Baltic system (the Sheksninskoe and Belousovskoe reservoirs). Our methodology for the analysis of the nucleotide sequence of the COI locus without sequencing allowed us to identify four haplotypes (A, B, D, and type I) that were earlier found in the basins of the Black and Caspian seas (Therriault et al. 2004; Gelembiuk et al. 2006; May et al. 2006). Therefore, we could substantially increase the sizes of the samples compared to previous researchers. Note, however, that our methodology does not allow the detection of nucleotide polymorphisms at positions 6 and 232 and, hence, the identification of the rare haplotypes C and D2 that were earlier found in zebra mussels from the Caspian Canal and the Ural River (May et al. 2006). Our method identifies the D2 haplotype as D and the C haplotype as B. In addition, this method does not allow the identification of four unique haplotypes (LC1, LC2, LG2, and LG4) that have been found in zebra mussels from German and Italian lakes (Quaglia et al. 2007). However, this is unlikely to have considerably distorted our estimation of the haplotype distribution in the populations studied, because the C and D2 haplotypes were very rare even in the samples where they were originally found (May et al. 2006) and the LC1, LC2, LG2, and LG4 haplotypes occurred only locally. Our analysis has demonstrated that the A and B haplotypes are prevailing in the populations studied, as they are in other parts of the species range, their frequencies varying even in neighbouring water bodies belonging to the same basin (Figure 5). For example, it was earlier found that at lest half zebra mussels from the Caspian Canal and the lower Volga River carried the B haplotypes, whereas this haplotype was entirely absent in mussels from the lower Ural River, although the Ural runs into the Caspian Sea and the sample from this river was as large as 20 molluscs (May et al. 2006). The considerable differences in haplotype frequencies between neighbouring zebra mussel populations are still poorly understood; they may have resulted from the founder

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effect. Anyway, this indicates that a similarity in haplotype frequencies is not a reliable criterion for common origin of D. polymorpha populations. In particular, we cannot conclude that the zebra mussel populations of the upper Volga have originated from the Black Sea basin. Analysis of the distribution of unique haplotypes over the species range seems much more promising. These are, e.g., the C, D, and D2 haplotypes found in the zebra mussel populations of the Caspian Sea and the mouths of the Volga and Ural rivers (Gelembiuk et al. 2006). In addition, Therriault et al. (2004) found a haplotype that they called type I of the COI mtDNA locus in zebra mussels from the Bug River (the Black Sea basin). Later studies outside of the basins of the Caspian and Black seas (Albrecht et al. 2007; Quaglia et al. 2007; Grigorovich et al. 2008) failed to detect these unique haplotypes. We have found that the Caspian haplotype D, which has not been found in the Black Sea basin thus far, is rather common in the zebra mussel populations of the northeastern periphery of the species range. Therefore, this part of the range is most likely to have been populated by zebra mussels from the Volga basin. The populations from which the species range extended north-eastwards were probably located in the upper or middle Volga River. Even the first studies on the fauna of the upper and middle Volga region published as early as the 18th century reported on the findings of zebra mussels. Zebra mussels have been regularly found in the upper Volga since 1880 (Skorikov 1903, Derzhavin et al. 1921; Bening 1924), although Bening (1924) believed that D. polymorpha could not steadily acclimatize there because of the high humic acid content of the water and assumed that the zebra mussels occurring in collection of molluscs were regularly brought there by barges and steamers. At the same time, relatively large aggregations of zebra mussels occurred in the middle Volga basin downstream of the Oka River mouth before the system of reservoirs was constructed (Bening 1924). Probably, these populations became the source of the northward expansion of the species. The populations of D. polymorpha in the Severnaya Dvina belonging to the White Sea basin (at the northernmost margin of the current species range) are of special interest. It was recently suggested that D. polymorpha could migrate to the Severnaya Dvina from the Volga basin via the Severnaya Dvina Canal (Starobogatov and Andreeva 1994); earlier, Skorikov (1903) considered it possible that the zebra mussel could migrate to this river via the Kama– Severnaya Dvina water system, which existed in the period between 1822 and 1838. In theory, zebra mussels might (though rarely) spread to the Severnaya Dvina from the Baltic region via the White Sea–Baltic system. However, this is hardly the case, because there are no zebra mussel populations in the rivers and lakes of the White Sea–Baltic Canal. In addition, zebra mussels were found in the Severnaya Dvina before the canal was constructed; hence, this cannot have been the main route of the northward expansion of the mollusc. Starobogatov and Andreeva (1994) hypothesized that stable populations of the mollusc could not exist in the Severnaya Dvina, and the mussel aggregations found in the river originated from molluscs that were constantly brought there. However, our data do not confirm this hypothesis. Indeed, if the Severnaya Dvina population had existed exclusively owing to molluscs regularly brought from another water body, zebra mussels from the Severnaya Dvina and the donor population would have had the same prevailing mtDNA haplotype. However, the

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Severnaya Dvina sample of the molluscs considerably differs from the samples from all other northern water bodies in mtDNA haplotype frequencies (Figure 5, Table 3). The Severnaya Dvina populations of the zebra mussel also differ from its population in Lake Kubenskoe belonging to the Severnaya Dvina catchment area. In the sample from Lake Kubenskoe, we found only the A haplotype, whose frequency in the Severnaya Dvina is as low as 0.04. In addition, the shipping route through Lake Kubenskoe and the segment of the Severnaya Dvina near its mouth is very seldom used at present. This leads to the conclusion that considerable numbers of zebra mussels cannot be regularly brought to the Severnaya Dvina from Lake Kubenskoe. Nor can the molluscs be brought through the Kama–Severnaya Dvina route, which is not used at all now. The unique composition and frequency distribution of the COI haplotypes in the zebra mussel sample from the Severnaya Dvina River can be explained only by a long isolation of the local population, which is most likely to have originated from the Volga populations (Figure 5). Anyway, we have good grounds to conclude that the D. polymorpha population of the Severnaya Dvina reproduces independently, rather than is replenished by veligers or adult mussels brought from neighbouring populations. This is further confirmed by our earlier data on the phenotypic structure of D. polymorpha populations, which showed that the sample from the Severnaya Dvina considerably differed from samples collected in neighbouring water bodies in the frequencies of shell colour variants. In this population, we found the combinations of phenes that were apparently absent in all other parts of the species range (Sergeeva 2008). Thus, the results of analysis of the COI mtDNA locus and morphological data indicate that the zebra mussel population of the Severnaya Dvina living at temperatures that are extreme for this species is unique. At present, numerous peripheral populations of the zebra mussel are unlikely to affect aquatic ecosystems as strongly as large populations from the central part of the species range do. It cannot be excluded, however, that they have some unusual characteristics; e.g., they may be more resistant to adverse environmental conditions. This should be taken into consideration in predicting the routes of further expansion of D. polymorpha.

ACKNOWLEDGMENTS We thank N.M. Mahnovic, V.A. Cherepanov, D.P. Karabanov, D.L. Layus and colleagues of GosNIORKH laboratory in Vologda for help in collecting samples, and A.A. Makhrov, E.N. Pakunova for help in preparing this article. This study was supported by the program of the Russian Academy of Sciences "Biological Diversity" (subprogram "Gene Pools and Genetic Diversity").

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In: Mussels: Anatomy, Habitat and Environmental Impact ISBN 978-1-61761-763-8 Editor: Lauren E. McGevin ©2011 Nova Science Publishers, Inc.

Chapter 22

UNIONIDAE FRESHWATER MUSSEL ANATOMY Diana Badiu,1 Rafael Luque2 and Ovidiu Teren3 1

Department of Biochemistry Faculty of Natural and Agricultural Sciences Ovidius University of Constanta 124, Mamaia Blvd., 900527 Constanta (Romania) 2 Departamento de Quimica Organica Universidad de Cordoba Campus de Rabanales Edificio Marie Curie (C- 3) Ctra Nnal IV, Km 396 Cordoba (Spain), E-14014 3 Department of Biophysics Faculty of Medicine Ovidius University of Constanta 1, University Al., Campus (B Part) Constanta (Romania)

ABSTRACT Freshwater mussels of the family Unionidae, also known as naiads, have inhabited fresh waters around the world for the past 400 million years. The presence of these unique mussels ensures our water quality and helps support the worldwide pearl industry. Yet their continued survival is by no means certain, due to overharvesting, environmental degradation and the rapid spread of exotic mussel species. Most research related to mussels has dwelt on different topics as fine-scale, intradrainage distribution patterns and life history traits relevant to applied conservation and propagation issues but there are only a few reports on anatomy studies. This chapter provides baseline reference material regarding the anatomy of Unionidae freshwater mussels, focusing in particular on the subfamily Unioninae with the aim to improve the knowledge in mussels of professional biologists and amateur naturalists as well as their preservation.

Keywords: shell, valve, mantle, muscle, stomach.

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E-mail: [email protected]

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1. THE GENERAL MORPHOLOGY AND ANATOMY OF UNIONIDAE The Unionoida, commonly known as freshwater pearly mussels or naids, is a diverse order of bivalved molluscs. Comprised of over 150 genera and flung widely upon all continents except Antarctica, the Unionoida is a conspicuous member of the macrobenthos of the world‘s rivers and stable lacustrine habitats (Turgeon et al., 1998). The general morphology and anatomy of family Unionidae (naiads) is well known, but the special features are frequently not mentioned, or very fragmentarily, in text books on zoology, and not even in recent special works on mollusca. It is necessary to first orient ourselves on the Tree of Life. Although there has been some incongruence among molluscan classification schemes, most arrangements are consistent with the bivalvia split among two subtaxa: Protobranchia and Autobranchia (= Isofilibranchia + Pteriomorpha + Anomalodesmata + Heterodonta + Palaeoheterodonta). According to the current consensus (Brusca and Brusca, 2003), the Unionoida belong to the latter in the subclass Palaeoheterodonta. The recent Palaeoheterodonta, however, receives only a single non-unionoid genus, the marine Neotrigonia. The divisions among the Autobranchia and the inclusion of the Unionoida among the Palaeoheterodonta have been based, traditionally, upon hinge morphology (Badra, 2004). The order Unionoida nominally includes two superfamilies, the Unionoidea and Etherioidea, distinguished by larval forms. The superfamily Unionoidea, with glochidia larvae, includes Unionidae (Africa, Eurasia, India, North America), Hyriidae (Australasia, South America) and Martaritiferidae (Eurasia, North America). The Etherioidea (Muteloidea) with lasidia larvae includes the Etheridae (= Mycetopodidae) (Africa, South America) and Iridinidae (Mutelidae) (Africa) (Heard and Vail, 1976). The same authors argument that ―the two different types of larvae cannot be considered to be derived one from the other or from any hypothetical direct ancestry‖. Ideas of continental drift were not widely accepted of course, at the time of McMichael and Hiscock (1958). The two authors postulated from scant evidence that an ancestral form invaded Australia from SE Asia, but soon afterward McMichael and Iredale (1959) acknowledged that dispersal via an Antarctic land bridge were feasible. The families Unionidae, Hyriidae and Margaritiferidae have in recent decades been associated as the superfamily Unionoidea based upon their shared possession of glochidiumtype parasitic larvae. Glochidia are small, bivalved larvae. Besides the morphological differences among the glochidia of the three families, the Unionidae, Hyriidae and Margaritiferidae are readily distinguishable based upon their adult anatomy (Heard, 1979; Graf and Cummings, 2006). Several species of the subfamily Unioninae, the main focus of this chapter, are highlighted below: Amblema plicata (Say, 1817), Cyclonaias tuberculata (Rafinesque, 1820), Elliptio crassidens (Lamark, 1819), Elliptio dilatata (Rafinesque, 1820), Fusconaia ebena (Lea, 1831), Fusconaia flava (Rafinesque, 1820), Megalonaias nervosa (Rafinesque, 1820), Plethobasus cyphyus (Rafinesque, 1820), Pleurobema sintoxia (Rafinesque, 1820), Quadrula metanevra (Rafinesque, 1820), Quadrula nodulata (Rafinesque, 1820), Quadrula pustulosa

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(Lea, 1831), Quadrula quadrula (Rafinesque, 1820) and Tritogonia verrucosa (Rafinesque, 1820). While there seems to be widespread agreement upon the recognition of these taxa, there is confusion regarding their precise generic composition and phylogeny.

2. DESCRIPTION OF SUBFAMILY UNIONINAE. CYCLONAIAS TUBERCULATA (RAFINESQUE, 1820) Biology Like most freshwater mussels of the subfamily Unioninae, this species requires a fish host to complete its life cycle. Eggs are fertilized and develop into larvae within the female. These larvae, called glochidia, are released into the water and must attach to a suitable fish host to survive. After attachment, epithelial tissue from the host fish grows over and encapsulates the glochidium, usually within a few hours. The glochidia then metamorphoses into a juvenile mussel within a few days or weeks. After metamorphosis, the juvenile is sloughed off as a free-living organism. Juveniles are found in the substrate where they develop into adults. (Arey, 1921; Lefevre and Curtis, 1912). When first discovered by Leeuwenhoek in 1697, glochidia were considered by some (but not by Leeuwenhoek) to be parasites living in the mussel‘s gills, and were given the scientific name Glochidium parasiticum by Fuller (1974). For nearly threequarters of a century, a lively debate ensued as to whether these ―agglomerations of animicules,‖ as some called them, were mussel parasites or mussel larvae. Houghton (1862) appears to have been the first to identify glochidia on fishes, and Fuller (1974) experimentally demonstrated their parasitic role and their true identity as larval mussels. The females of some Unioninae have structures resembling small fish, crayfish, or other prey that are displayed when the larvae are ready to be released. Other Unioninae display conglutinates, packets of glochidia that are trailed out in the stream current, attached to the mussel by a clear strand. These ―lures‖ may entice fish into coming in contact with glochidia, increasing the chances that glochidia will attach to a suitable host. Some Unioninae are winter breeders that carry eggs, embryos, or glochidia through the winter and into the spring, while others are summer breeders whose eggs are fertilized and glochidia released during one summer (Brusca and Brusca, 2003). North American freshwater Unioninae are historically divided into two behavioral groups based upon the duration that glochidia are held in the marsupia. Tachytictic or short-term breeders spawn in the spring or summer and release their glochidia later the same year, usually by July or August. Bradytictic or long-term breeders spawn in the summer or early autumn, form glochidia, and typically hold these larvae in the marsupium until the following spring or summer. But some otherwise ―bradytictic‖ individuals release glochidia in autumn or winter to overwinter on their hosts. They remain dormant on their host until a threshold temperature is reached the following spring, at which time they metamorphose and excyst (Watters and O‘Dee, 1999).

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The purple wartyback (Cyclonoias tuberculata) is a tachytictic breeder with a reproductive period beginning in June and ending in August (summer breeder) (Badra, 2004). Glochidia remain on the fish host for a couple weeks to several months depending on the species and other factors. During this time the glochidia transforms into the adult form then drops off its host (Kat, 1984). Although the advantages of having fish hosts are not fully understood in which two factors are known to provide benefits. Similar to animal facilitated seed dispersal in plants, fish hosts allow mussels that are relatively sessile as adults to be transported to new habitat and allow gene flow to occur among populations. The fish host also provides a suitable environment for glochidia to transform in. Some of them are able to utilize many different fish species as hosts while others have only one or two known hosts. General known hosts for the purple wartyback are the yellow bullhead (Ameiurus natalis) and channel catfish (Ictalurus punctatus). These species were identified as hosts in laboratory experiments. It is possible that additional species are utilized as hosts in natural environments (Oesch, 1984).

Conservation and Management Eastern North America is the global centre of diversity for freshwater mussels with over 290 species. In a review of the status of U.S. and Canadian Union by the American Fisheries Society one third of these were considered endangered (Williams et al., 1993). Thirty-five Unioninae are thought to have gone extinct in recent times (Turgeon et al., 1998). There are forty five species native to Michigan. Nineteen of these are state-listed as endangered, threatened, or special concern (Box and Mossa, 1999). The decline of this group over the last couple hundred years has been attributed mainly to our direct and indirect impacts to aquatic ecosystems. Threats include habitat and water quality degradation from changes in water temperature and flow, the introduction of heavy metals, organic pollution such as excessive nutrients from fertilizers, pesticides and herbicides, dredging, and increased sedimentation due to excessive erosion (Fuller, 1974; Bogan 1993). High proportions of fine particles (sand and silt) were found to be a limiting factor regarding density and species richness across several watersheds in Lower Michigan (Badra and Goforth, 2002). Using certain agricultural practices such as conservation tillage, grass filter strips between fields and streams, and reforestation in the floodplain can help reduce the input of silt and other pollutants. Forested riparian zones help maintain a balanced energy input to the aquatic system, provide habitat for fish hosts in the form of large woody debris, reduce the input of fine particles by stabilizing the stream banks with roots, and provide shade which regulates water temperature (Walker et al., 2001). Due to the unique life cycle of this species, fish hosts must be present in order for reproduction to occur. The loss of habitat for these hosts can cause the extirpation of populations. Barriers to the movement of fish hosts such as dams and impoundments also prevent migration and exchange of genetic material among populations that helps maintain genetic diversity within populations (Bogan, 1993). Cyclonaias tuberculata is mainly found in rivers with definite riverine conditions and stronger current, like the Lake Erie drainage and the Kalamazoo, St. Joseph, Thornapple and Grand Rivers of the Lake Michigan drainage. It has also been recorded in the Menominee

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River in the Upper Peninsula, Lake St. Clair drainage, the Detroit River and Lake Erie (Van der Schalie, 1938).

Anatomy of Subfamily Unioninae Unioninae bivalves or freshwater pearly-mussels serve as an exemplary system for examining many of the problems facing systematises and conservation biologists today. Most of the species and genera were described in the late 1800s and early 1900s, but few phylogenetic studies have been conducted to test conventional views of species and classification. The purple wartyback is up to 12.7 cm (5 inches) long, and is round. The shell is fairly thick, heavy and compressed. The anterior end is rounded, the posterior end somewhat angled. The dorsal margin is straight to slightly round and the ventral margin is broadly rounded (Oesch, 1984) Like other freshwater mussels from subfamily Unioninae, C. tuberculata have soft inner bodies and hard outer shells. The soft tissues include a large muscular foot used for locomotion, an enveloping mantle that secretes the shell, anterior and posterior adductor muscles that enable to the animal to close its shells, labial palps that move food particles to the mouth, and two pairs of gills. The gills have three functions: (1) respiration like fish, mussels use their gills to breathe, (2) filter feeding, the gills move food particles to the mouth, and (3) in females, the gills incubate baby mussels (larvae) until they are mature and ready to be released (Watters et al., 2009). The middle lobe of the mantle edge has most of a bivalve's sensory organs. In the mussel‘s foot are found paired statocysts, which are fluid filled chambers with a solid granule or pellet (a statolity). The statocysts help the mussel with georeception or orientation. Mussels are heterothermic, and therefore are sensitive and responsive to temperature (Cummings and Mayer, 1992). Unioninae in general may have some form of chemical reception to recognize fish hosts. How the purple wartyback attracts or if it recognizes its fish host is unknown (Watters et al., 2009). Internal organ systems include an open circulatory system powered by a heart; a digestive system that consists of mouth, stomach, gut, and anus; a decentralized nervous system that controls movement of the foot and adductor muscles; and reproductive organs that usually occur separately in male and female mussels (Bogan and Roe, 2008) (Figure 1). C. tuberculata species have two shells, or valves, arranged left and right. The earliest part of the shell is called the beak or umbo. The shell expands along the margins as the animal grows. Most freshwater mussels have a dorsal area called the hinge, which has interdigitating projections called teeth. These teeth serve to keep the shells aligned and prevent shearing during burrowing. The anterior- most teeth are called the cardinal (or pseudocardinal) teeth, whereas the posterior teeth are the lateral (or pseudolateral) teeth. Some Unioninae lack teeth all together. The shells are held together in life by two adductor muscles which close the shells. These muscles counteract the ligament, a non-living proteinaceous structure which acts as a spring to open the shells. The muscular foot protrudes from the anterior half of the shells; the siphons, the openings through which water enters and exits the shells, are located posteriorly (Watters et al., 2009).

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Figure 1. The basic anatomy of freshwater Unioninae (here with foot, which is absent in adults) 1) (shell; 2) umbo; 3) digestive gland; 4) stomach; 5) cerebropleural ganglion; 6) anterior adductor muscle; 7) labial palp; 8) mouth; 9) foot; 10) mantle; 11 gonad; 12) intestine; 13) gills; 14) visceral ganglion; 15) anus; 16) posterior adductor muscle; 17) ligament; 18) kidney; 19) heart (adapted from Burch, 1975).

The shells have three different layers. The outer layer (called the periostracum) is made of organic material that may be yellow, green, brown, or black. The middle layer (prismatic layer) is made of elongate crystals of calcium carbonate (CaCO3). The lustrous inner layer (nacre or mother-of-pearl layer) is made of plate-like crystals of calcium carbonate and may be white, pink, salmon, or purple. The mussel's external shell is composed of two hinged halves or "valves" (Silverman et al., 1985). The valves are joined together on the outside by a ligament, and are closed when necessary by strong internal muscles. Mussel shells carry out a variety of functions, including support for soft tissues, protection from predators and protection against desiccation (Figure 2) (Walker et al., 2001). On the inner surface of the shells are scars, sites of attachment for various muscles, including the adductors and the pallial line, the linear scar where the mantle tissue is anchored to the shell. Freshwater mussels live by filter-feeding food from the surrounding water with their gills, or ctenidia. Because of their food-gathering function, these gills are much larger than is needed for respiration. North American species lack true siphons, or tubes for water intake and release, such that many species are confined to burrowing only to the posterior edge of the shell during much of the year. This renders them susceptible to predators, desiccation, temperature and other environmental extremes (Bauer and Wachtler, 2001) (Figure 3). Cyclonaias tuberculata (Rafinesque, 1820) is also filter feeders. The mussel use cilia to pump water into the incurrent siphon where food is caught in a mucus lining in the demibranchs. Particles are sorted by the labial palps and then directed to the mouth. Mussels

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have been cultured on algae, but they may also ingest bacteria, protozoans and other organic particles (Arey, 1921; Meglitsch and Schram, 1991; Watters et al., 2009).

Figure 2. Morphology of a freshwater Cyclonaias tuberculata (Rafinesque, 1820), illustrating structures and terminology. a. exterior of right valve; b. interior of left valve (adapted from Burch, 1975).

The periostracum (outer shell layer) has several pustules, and ridges on the dorsal wing. Younger specimens are yellowish to greenish brown, while older specimens tend to be more uniformly (Oesch, 1984) (Figure 4). The beak cavity is very deep. The nacre is almost always purple, and rarely white (Cummings and Mayer, 1992; Oesch, 1984; Watters et al., 2009). In Michigan, this species can be confused with the pimpleback. The pimpleback usually has a prominent green ray, lacks a dorsal wing and purple nacre (Oesch, 1984).

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Like most bivalves C. tuberculata has a large organ called a foot, which disappear in oldness. This foot is large, muscular, and generally hatchet-shaped. It is used to pull the animal through the substrate (typically sand, gravel, or silt) in which it lies partially buried. It does this by repeatedly advancing the foot through the substrate, expanding the end so it serves as an anchor, and then pulling the rest of the animal with its shell forward. It also serves as a fleshy anchor when the animal is stationary (Watters et al., 2009).

Figure 3. Morphology of a general freshwater mussel shells (adapted from Watters et al., 2009).

Figure 4. Morphology of a general freshwater mussel shells (adapter from Watters et al., 2009).

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Shell shape is variable and somewhat subjective in C. tuberculata. A kidneyshell may appear elongate as a juvenile, but become something entirely different as an adult. While shape is an ideal starting point, its best used as just a piece of the identification puzzle. Figures 5, 6, 7, 8 and 9 summarize some examples (Lefevre and Curtis, 1912; Van der Schalie, 1938).

Figure 5. Eliptical shape of a general freshwater mussel shell (adapted from Bogan & Roe, 2008).

Figure 6. Elongate shape of a general freshwater mussel shell (adapted from Bogan & Roe, 2008).

Figure 7. Round shape of a general freshwater mussel shell (adapted from Bogan & Roe, 2008).

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Figure 8. Quadrate shape of a general freshwater mussel shell (adapted from Bogan & Roe, 2008).

Figure 9. Triangular shape of a general freshwater mussel shell (adapted from Bogan & Roe, 2008).

To distinguish left from right the posterior ridge and beak will be orientated so that diagonals drawn along the posterior ridge converge anteriorly and diverge posteriorly (Figure 10). The pseudocardinal teeth (if present) will always be anterior of the lateral teeth. The age of mussels can be determined by looking at annual rings on the shell, but generally the maximum life-span is not longer than 25 years. However, no demographic data on this species has been recorded. Unioninae in general and C. tuberculata especially are rather sedentary, although they may move in response to changing water levels and conditions. Although not thoroughly documented, the mussels may vertically migrate to release glochidia and spawn. Often this species is buried under the substrate (Oesch, 1984). Unioninae food continues to be the subject of debate. Allen (1914, 1921) and Churchill and Lewis (1924) found the gut to contain mostly diatoms and other algae, although the diatoms passed through the digestive system intact. However, Imlay and Paige (1972) believed that mussels fed on bacteria and protozoans. Bisbee (1984) found different

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proportions of algal species in the guts of two mussel species, suggesting that not all species fed upon the same food.

Figure 10. Shell orientation (wabash pigtoe, Fusconaia flava) (adapted from Van Der Schalie, 1938).

Recently, Nichols and Garling (1998) demonstrated that mussels were omnivores, feeding on detritus and zooplankton, as well as algae and bacteria. Newly metamorphosed juveniles do not filter-feed with their gills, but may feed on interstitial nutrients using cilia on their foot, gills, and mantle. This stage may last several years before changing to a filterfeeding mode (Tankersley et al., 1997). Yeager et al. (1993) believed that food for juveniles consisted of interstitial bacteria, yet an algal mix including silt was suggested as food by Gatenby et al. (1993). Small amounts of silt have been found to enhance survivorship in cultured mussels, both adults and juveniles (Hudson and Isom, 1984; Hove and Neves, 1991), probably by introducing bacteria and zooplankton. Gametogenesis, the formation of eggs and sperm, is initiated by changes in water temperature and/or light levels. It appears to be threshold temperatures or light levels that cue reproductive events. For those species relying on some upper temperature threshold, constant low water temperatures, such as are found below some dams, may prevent reproduction from ever taking place. In such conditions, populations of adult mussels may live out their normal lives and die without ever producing offspring (Howard, 1915; Gordon and Smith, 1990). Typically, sexes are separate, although small numbers of hermaphrodites have been found in many species (Fischerstrom, 1761; Van der Schalie, 1966; 1970; Heard, 1979). Males liberate sperm into the water, sometimes as spherical (Lynn, 1987; Barnhart and Roberts, 1997) or disc-shaped aggregates termed spermatozeugmata. Females downstream take up the sperm with incoming water. Fertilization success may be related to population density, with a threshold density required for any reproductive success to occur (Downing et al., 1993). Eggs are fertilized in the suprabranchial chambers of the gills and then apparently are moved to the marsupia. The marsupia are regions of the gill that act as brood chambers for the glochidia. Their placement and structure vary from genus to genus and have been used as key taxonomic characteristics. The marsupium may change in shape and structure during the breeding season (Smith, 1979; Kays et al., 1990; Richard et al., 1991).

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During this time, the marsupium either does not function as a site of respiration (Richard et al., 1991) or operates at greatly reduced efficiency (Allen, 1921; Tankersley and Dimock, 1992). This region may remain non-respiratory during the non-breeding season as well (Richard et al.,1991). The developing embryos are physiologically isolated in the marsupium from the outside water (Kays et al., 1990). Muscles associated with the water tubes may be responsible for maintaining this isolation. Cyclonaias tuberculata is listed as Endangered in Wisconsin, Threatened in Illinois, Iowa and Minnesota, and significantly rare in North Carolina. In Michigan it is listed as Special Concern. The IUCN Red List considers this species Lower Risk, Near Threatened.

CONCLUSION AND FUTURE RESEARCH Advancement of our knowledge of the subfamily Unioninae in the areas of systematics anatomy and evolution will require a renewal of effort in already established areas of research, reviewed earlier here, and a concerted effort aimed at the development and application of new tools. Therefore, the fossil record of freshwater bivalves should be carefully reviewed, and phylogenetic hypotheses including fossil taxa must be developed. In conclusion, the freshwater malacological community has made great strides in understanding the life history, distribution, ecology and anatomy of unioniform bivalves, but we have really only laid the groundwork for the future. Exploration of new genetic data sources must continue, and new methods of describing the shells and the anatomy of freshwater mussels must be developed. However, the importance of collecting basic naturalhistory information cannot be overstated. The study of systematics and evolution is an historical endeavor and one that seeks to integrate various sources of data to develop hypotheses that are then subjected to further tests. Only by fostering research along the many diverse lines of interest in freshwater mussels will we begin to see real progress toward a more complete understanding of them.

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Barnhart, M.C.; Roberts, A.D. (1997). Reproduction and fish hosts of unionids from the Ozark uplifts. 16–20. In: K.S. Cummings, A.C. Buchanan, C.A. Mayer and T.J. Naimo (eds.), Conservation and management of freshwater mussels II: Initiatives for the future. Proceedings of a UMRCC symposium, St. Louis, MO: Upper Mississippi River Conservation Committee, Rock Island, IL. Bauer, G.; Wachtler, K. (2001). Ecology and evolution of the naiads. 83-388. In: G. Bauer, Wachtler K., (eds.), Ecology and evolution of the freshwater mussels Unionoida. Ecological Studies, Vol. 145. Berlin: Springer-Verlag. Bisbee, G.D. (1984). Ingestion of phytoplankton by two species of freshwater mussels, the black sandshell, Ligumia recta, and the three ridge, Amblema plicata, from the Wisconsin River in Oneida County, Wisconsin. Bios. 55, 219–225. Bogan, A.E. 1993. Freshwater bivalve extinctions (Mollusca: Unionoida): A search for causes. Am. Zool., 33, 599-609. Bogan, A.E.; Roe, K.J. (2008). Freshwater bivalve (Unioniformes) diversity, systematics, and evolution: status and future directions, J. North Am. Benthol. Soc., 27(2), 349-369. Box, J.B.; Mossa, J. (1999). Sediment, land use, and freshwater mussels: prospects and problems. J. North Am. Benthol. Soc.,18, 99-117. Brusca, R.; Brusca, G. (2003). Invertebrates. Sunderland, Massachusetts: Sinauer Associates, Inc., 365pp. Churchill, E.P.; Lewis, SI. (1924). Food and feeding in fresh water mussels. Bulletin of the United States Bureau of Fisheries, 39, 439–471. Cummings, K., Mayer C., 1992. Field guide to freshwater mussels of the Midwest. Champaign, Illinois: Illinois Natural History Survey Manual 5. Accessed at http://www.inhs.uiuc.edu/cbd/collections/mollusk/fieldguide.html. Downing, J.A.; Rochon, Y.; Perusse, M. (1993). Spatial aggregation, body size, and reproductive success in the freshwater mussel Elliptio complanata. J. North Am. Benthol. Soc , 12, 148–156. Fischerstrom, I. (1761). De concharum margaritiferarum natura. Commentarii de Rebus in Scientia Naturali et Medicina Gestis, 10, 204–205. Fuller, S. (1974). Clams and mussels (Mollusca: Bivalvia). In: Hart, C.W. Jr., Fuller S.L.H. eds. Pollution ecology of freshwater invertebrates. Academic Press, New York, 228-237. Gatenby, C.M.; Neves RJ.; Parker BC. (1993). Preliminary observations from a study to culture recently metamorphosed mussels, J.NorthAm.Benthol.Soc., 10, 128 -130. Gordon, M.E.; Smith, DG. (1990). Autumnal reproduction in Cumberlandia monodonta (Unionoidea: Margaritiferidae). T.Am.Microsc.Soc., 109, 407–411. Graf, D.L.; Cummings, K.S. (2006). Palaeoheterodont Diversity (Mollusca: Trigonioida + Unionoida): what we know and what we wish we knew about freshwater mussel evolution. Zool. J.Linn.Soc., 148, 343-394. Heard, W.H.; Vail, V.A. (1976). Anatomical systematics of Etheria elliptica (Pelecypoda, Mycetopodidae), Malacol.Rev., 9, 15-24. Heard, W. H. (1979). Hermaphroditism in Elliptio (Pelecypoda: Unionidae). Malacol. Rev., 12, 21–28. Houghton, W. (1862). On the parasitic nature of the fry of Anodonta cygnea. Quart.J.Micros.Sci. (n.s.), 2, 162–168.

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Hove, M.; Neves, R. (1991). Distribution and life history of the James River spinymussel. Endangered Species Buletin, 16, 9. Howard, A.D. (1915). Some exceptional cases of breeding among the Unionidae. The Nautilus, 29, 4–11. Hudson, R.G.; Isom, B.G. (1984). Rearing juveniles of the freshwater mussels (Unionidae) in a laboratory setting. The Nautilus, 98, 129–135. Imlay, M.J., Paige, M.L., (1972). Laboratory growth of freshwater sponges, unionid mussels, and sphaeriid clams. Progressive Fish Culturist, 34, 210–216. Kat, P.W. (1984). Parasitism and the Unioniacea (Bivalvia). Biol.Rev. 59, 189-207. Kays, W.T.; Silverman, H.; Dietz, T.H. (1990). Water channels and water canals in the gill of the freshwater mussel, Ligumia subrostrata: Ultrastructure and histochemistry. J.Exp.Zool., 254, 256–269. Lefevre, G.; Curtis, W. (1912). Experiments in the artificial propagation of fresh-water mussels. Proc. Internat. Fishery Congress, Washington. Bull. Bur. Fisheries, 28, 617-626. Lynn, J.W. (1987). Release of motile spermatophores from the freshwater mussel Anodonta grandis. Am.Zool. 27, 90A [abstract]. McMichael, D.F., Hiscock, I.D., (1958), A monograph of the freshwater mussels (Mollusca: Pelicypoda) of the Australian Region. Aust.J.Mar.Freshwater Res., 9, 372-507. McMichael, D.F., Iredale, T. 1959, The land and freshwater Mollusca of Australia, In: Keast A., Crocker RL., Christian CS. (eds.), Biogeography and ecology in Australia, Dr. W. Junk. The Hagne, 224-245. Meglitsch, P.; Schram, F. (1991). Invertebrate Zoology, Third Edition. New York, NY: Oxford University Press, Inc. Nichols, S.J., Garling D., (1998). Food web dynamics of Unionidae in a canopied river and a non-canopied lake. Program and Abstracts, Freshwater Mussel Symposium, Columbus, OH, 28–29. Oesch, R.D. (1984). Missouri Naiades: A Guide to the Mussels of Missouri. Missouri Department of Conservation. 270 pp. Richard, P.E.; Dietz TH.; Silverman H. (1991). Structure of the gill during reproduction in the unionids Anodonta grandis, Ligumia subrostrata, and Carunculina parva texasensis. Can.J.Zool., 69, 1744–1754. Silverman, H.; Steffens, W.L.; Dietz, T.H. (1985). Calcium from extracellular concretions in the gills of freshwater unionid mussels is mobilized during reproduction. J.Exp.Zool., 236, 137–147. Smith, D.G. (1979). Marsupial anatomy of the demibranch of Margaritifera margaritifera (Lin.) in northeastern North America (Pelecypoda: Unionacea). J.Molluscan Stud., 45, 39–44. Tankersley, R.A.; Hart, J.J.; Weiber, M.G. (1997). Developmental shifts in feeding biodynamics of juvenile Utterbackia imbecillis (Mollusca: Bivalvia). Pp. 282–283. In: Cummings KS., Buchanan AC., Mayer CA., Naimo TJ. (eds.), Conservation and management of freshwater mussels II: Initiatives for the future. Proceedings of a UMRCC symposium, St. Louis, MO. Upper Mississippi River Conservation Committee, Rock Island, IL. Tankersley, R.A.; Dimock, R.V. (1992). Quantitative analysis of the structure of the marsupial gills of the freshwater mussel Anodonta cataracta. Biol. Bull., 182, 145–154.

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Turgeon, D.D.; Quinn, J.F.Jr.; Bogan, A.E.; Coan, E.V.; Hochberg, F.G.; Lyons, W.G.; Middelsen, P.M.; Neves, R.J., Roper, C.F.E.; Rosenberg, G.l; Roth, B.; Scheltema, A.; Thompson, F.G.; Vecchione, M.; Williams, J.D. (1998). Common and scientific names of aquatic invertebrates from the United States and Canada: mollusks, 2nd edition. American Fisheries Society, Special Publication 26, Bethesda, Maryland. Van der Schalie, H. (1966). Hermaphroditism among North American freshwater mussels. Malacologia, 5, 77–78. Van der Schalie, H. (1970). Hermaphroditism among North American freshwater mussels. Malacologia, 10, 93–112. Van der Schalie, H. (1938). The naiad fauna of the Huron River, in southeastern Michigan. Miscellaneous Publications of the Museum of Zoology, University of Michigan, 40, 1-83. Walker KF., Byrne M., Hickey W., Rober D.S. (2001). Ecology and evolution of freshwater mussels Unionoida, In: Freshwater Mussels (Hyriidae) of Australasia, Bauer G. and Wachtles E. ed., p.6. Watters, G.T.; Hoggarth, M.A.; Stansbery, D.H. (2009). The freshwater mussels of Ohio, Sheridon Books Inc., The Ohio University Press, Columbus. Watters, G.T.; O‘Dee, SH. (1999). Glochidia of the freshwater mussel Lampsilis overwintering on fish hosts. J. Molluscan Stud., 65, 453–459. Williams, J.D.; Warren, M.L.Jr.; Cummings, K.S.; Harris, J.L.; Neves, R.L. (1993). Conservation status of freshwater mussels of the United States and Canada. Fisheries, 18, 6-22. Yeager, M.M.; Cherry, D.S.; Neves, R. (1993). Interstitial feeding behavior of juvenile unionid mussels. ASB Bulletin, 40, 113-117.

In: Mussels: Anatomy, Habitat and Environmental Impact ISBN 978-1-61761-763-8 Editor: Lauren E. McGevin ©2011 Nova Science Publishers, Inc.

Chapter 23

THE CYTOGENETICS OF MYTILUS MUSSELS Andrés Martínez-Lage and Ana M. González-Tizón Departamento de Biología Celular y Molecular, Universidade da Coruña, La Coruña, Spain

Mussels within the genus Mytilus are one of the most thoroughly studied marine molluscs at both the ecological and physiological levels. A great number of studies on morphology, morphometry, proteins and DNA markers have been performed, but origin and taxonomy of this genus still remains unclear. Based on these studies, different authors recognised the existence of different species, semi-species or subspecies within this genus. For example, according to McDonald et al. (1991) these are five taxa: M. edulis, M. galloprovincialis, M. trossulus, M. californianus and M. coruscus, and Gosling (1992) includes M. (edulis) desolationis as a subspecies of M. edulis. Data from different mitochondrial and nuclear DNA markers have revealed strong biogeographic and phylogenetic relationships among M. edulis, M. galloprovincialis and M. trossulus -these three forming the M. edulis complex- (Varvio et al. 1988; Koehn 1991; McDonald et al. 1991; Rawson and Hilbish, 1998; Quesada et al. 1998; Martinez-Lage et al. 2002; Riginos and McDonald 2003; Riginos and Cunningham 2005; Pereira Silva and Skibinski 2009). According to Blot et al. (1988) and Gérard et al. (2008) M. desolationis seems to be a ―semispecies in the super-species Mytilus edulis complex‖, whereas M. californianus and M. coruscus constitute two separate species as shown by the results obtained from the 18S ribosomal DNA (Kenchington et al. 1995), mitochondrial DNA (Hilbish et al. 2000), and satellite DNA Apa I (Martínez-Lage et al. 2002, 2005) analyses. The three species included in the M. edulis complex hibridise to a greater or lesser extent in the regions where they cohabit. Mytilus edulis and M. galloprovincialis hybrids occur off the western coast of Europe from the Bay of Biscay along the French coast to Great Britain and Ireland (Skibinski et al. 1978, Coustau et al. 1991, Gosling, 1992; Gardner 1996; Bierne et al. 2003). M. galloprovincialis x M. trossulus have been found on the Pacific coast of North America (McDonald and Koehn 1988; Rawson et al. 1999; Wonham 2004), and M. trossulus x M. edulis in Newfoundland (Toro et al. 2002), in the Danish straits separating the Baltic and North Seas (Väinölä and Hvilsom 1991; Riginos and Cunningham, 2005), in Nova Scotia (Saavedra et al. 1996; Comesaña et al. 1999), and recently in the Netherlands

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(Śmietanka et al. 2004), possibly in the Norwegian fjords near Bergen (Ridgway and Nævdal, 2004), and in Scotland (Beaumont et al. 2008, Zbawicka et al 2010). Due to the ecological importance, the worldwide distribution and its high economic value in aquaculture, cytogenetic analyses of Mytilus species are of a special interest. The knowledge on cytogenetic characteristics gives information about the number and morphology of chromosomes, differential distribution of euchromatin-heterochromatin regions, chromosomal rearrangements, provides new data about phylogenetic relatedness between taxa, and helps to clarify taxonomy. At present, a great variety of banding techniques are available to analyse chromosomes, allowing a thorough knowledge of the genetics of numerous animal and plant species. However, this is not the case of molluscs and particularly of bivalves. In these species the development of banding techniques has been hampered by a lack of in vitro cell lines, the high degree of chromosome condensation and their small size that, subsequently, leads to the failure of a satisfactory banding. Cytogenetic studies of Mytilus mussels have mainly provided information about genome size (C-value), chromosome number and morphology, location of ribosomal loci, and identification of heterocromatin-euchromatin regions. Genome size or C-value, i.e., the total amount of DNA within the haploid genome, is a valuable character for evolutionary studies. C-value is species specific, although shows high intraespecific and interspecific variability (C- value paradox). Although C- value does not show relation neither with systematics and phylogeny of species nor with chromosome number and organismal complexity, it is a very important factor in evolution and sequence-based genomic analyses. ―Mutation pressure‖ and ―optimal DNA‖ theories are the most accepted to explain the C-value paradox. Mutation pressure theories consider the large portion of non-coding DNA as ―junk‖ or ―selfish‖ DNA, whereas optimal theories emphasize the strong link between DNA content and cell and nuclear volumes (for a review see Ryan Gregory 2001). In genus Mytilus, genome size was determined for M. edulis (Hinegardner 1974; Rodríguez-Juiz et al. 1996), M. galloprovincialis (Ieyama et al. 1994; Rodríguez-Juiz et al. 1996), M. trossulus (González-Tizón et al. 2000), M. californianus (Hinegardner 1974; González-Tizón et al. 2000), and M. coruscus (Ieyama et al. 1994), with values ranging from 1.35 to 1.91 picogrames (table 1). First studies on Mytilus species concerned data on their chromosome number, all of them having a diploid chromosome number of 2n=28. However, karyotypes showed differences in chromosome morphology. For chromosome classification, authors followed the criteria stablished by Levan et al. (1964) [meaning that the chromosomes should be previously measured to determine the centromeric index, CI, (i.e., length of short arm/ total chromosome length)]. Chromosomes are classified as metacentric (m) when CI is 37.5 - 50.0; submetacentric (sm) when values are 25.0 - 37.5; subtelocentric (st) if the ratio is 12.5 - 25.0; and telocentric (t) when CI ranges from 0.0 to 12.5. Karyotypes for M. edulis from the different European localities studied always show 6 pairs of metacentric chromosomes and 8 of submetacentric or subtelocentrics (figure 1a) (Thiriot-Quiévreux 1984; Dixon and Flavell 1986; Cornet 1993; Insua et al. 1994; MartínezLage et al. 1995, 1996). However M. galloprovincialis and M. trossulus from different localities showed chromosome polymorphisms (differences in morphology). Interestingly, M. galloprovincialis from Atlantic coasts and from a big part of the Mediterranean Sea and M. edulis have identical karyotypes (figure 1b) (Dixon and Flavell 1986; Pasantes 1990; Martínez-Lage et al. 1994, 1996), whereas those from Gulf of Lion and from the east coast of

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the Iberian Peninsula show karyotypes with 5 metacentric chromosome pairs and 9 submetacentric or subtelocentrics (Thiriot-Quiévreux 1984; Insua et al. 1994; Martínez-Lage et al. 1996). Mytilus trossulus from Baltic Sea have 6 metacentric and 8 submetacentric or subtelocentric pairs (figure 1c) (Insua et al. 1994; Martínez-Lage et al. 1995, 1996; Wolowicz and Thiriot-Quiévreux 1997), and those from west America show 7 metacentric and 7 submetacentric or subtelocentric pairs (Martínez-Lage et al. 1997) (figure 1d). a)

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Figure 1. Idiograms of the six mussel Mytilus species and mapping of ribosomal loci in the M. edulis, M. galloprovincialis, M. trossulus and M. californianus: black blocks correspond to 18S+5.8S+28S ribosomal loci which always are detected; grey blocks indicate the polymorphic 18S+5.8S+28S ribosomal loci; striped blocks show the 5S ribosomal loci. Grey circles correspond to the positive chromomycin A3 bands (guanine-citosine rich regions) in the three European Mytilus. (Based on Martínez-Lage et al. 1994, 1995, 1996, 1997; Insua et al. 1994, 2001; Thiriot-Quievreux 1984; Ieyama 1984; Martínez-Expósito et al. 1997; Insua and Mendez 1998; González-Tizón et al. 2000).

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Andrés Martínez-Lage and Ana M. González-Tizón Table 1. C-values (given in picogrames) for the Mytilus species analysed

The mussel M. desolationis has 6 metacentric and 8 submetacentric or subtelocentric chromosomes (figure 1e) (Thiriot-Quiévreux 1984), whereas M. coruscus possess 5 metacentrics and 9 submetacentrics or subtelocentrics (figure 1f) (Ieyama 1984). Lastly, karyotype of M. californianus consists of 7 metacentric and 7 submetacentric pairs (figure 1g) (Martínez-Lage et al. 1997). None of the karyotypes of these Mytilus species have showed the presence of sexual chromosomes. Banding patterns are very scarce in Mytilus species. First of being applied on chromosome metaphases were sister chromatid exchanges (SCEs) on M. edulis as an approach to detect chromosome damage caused by environmental mutagens (Dixon and Clark 1982; Dixon 1983). Afterwards, ―classical‖ bandings (as C-, G-, R-, fluorochrome stainings, and Ag-NORs) and molecular banding (fluorescent in situ hybridisation) were applied. Longitudinal banding patterns on M. galloprovincialis chromosome are restricted to a ―Gbanding-like‖ obtained after treatment with 2xSSC solution (Méndez et al. 1990), G-bands using trypsin enzyme (Martínez-Lage et al. 1994), and R-banding by treatment with BrdU (Martínez-Expósito et al. 1994), all of them with very limited reproducibility. C- banding patterns and chromosome staining with fluorochromes as chromomycin A3 or DAPI, allowed the location of heterochromatin (Adenine-Timine rich) and/or euchromatin (Guanine-Citosine rich) regions in M. edulis, M. galloprovincialis and M. trossulus. Heterochromatin in interphase nuclei and chromosomes of M. edulis were initially performed by Dixon et al. (1986) and Dixon and McFadzen (1987). Later, in M. galloprovincialis, Martínez-Lage et al. (1994), by means of the combined use of C-banding, staining with the fluorochromes chromomycin A3 and DAPI, and chromosome treatment with some restriction endonucleases (REs) described different types of heterochromatin. The treatment of M. galloprovincialis chromosomes with REs showed that these enzymes acted differentially and determined specific banding patterns on the chromosome complement, and also the existence of C-heterochromatin heterogeneity in mussel chromosomes. Later, C-banding, Ag-NORs and fluorochrome stainings on M. edulis, M. galloprovincialis and M. trossulus identified changes in the constitutive heterochromatin among these species, allowing the identification of these three mussels (Martínez-Lage et al. 1995). These analyses proved that Mytilus

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possess small amounts of constitutive hetechromatin. A posterior study of the C-band polymorphism was carried out in M. galloprovincialis by Pasantes et al. (1996). The silver staining method applied on chromosome metaphases allows the detection of the nucleolar organisers regions (NORs) which were active at the precedent interphase. Chromosomal Ag-NORs were obtained for M. edulis, M. galloprovincialis, M. trossulus and M. californianus by different authors. With the development of the molecular FISH techniques, mapping of major ribosomal loci (18S-5.8S-28S) was more reliable, and extensively applied in mussels and other several bivalve species. Results obtained from AgNORs and FISH revealed that in M. edulis, M. galloprovincialis, M. trossulus and M. californianus, these loci locate on telomeric or subtelomeric regions of metacentric and/or submetacentric/subtelocentric chromosomes in a number varying from 4 to 6 (figure 1) (Insua et al. 1994, 2001; Martínez-Expósito et al. 1994, 1997; Martínez-Lage et al. 1995, 1997; Insua and Méndez 1998; González-Tizón et al. 2000). FISH to locate the minor ribosomal loci (5S rRNA) was performed in M. galloprovincialis and M. edulis (Insua et al. 2001), which displayed two loci on one metacentric chromosome pair (occasionally, some metaphases showed one additional locus on another metacentric pair) (figure 1). Lastly, FISH was used to locate the telomeric repeat arrays (Plohl et al. 2002), and the histone H1 and the core histones H2A-H2B-H3-H4 in M. galloprovincialis (Eirín-López et al. 2002, 2004). These histone loci mapped at telomeric/subtelomeric regions on three chromosome pairs. Results obtained from cytogenetic data let us observe great karyotype similarities. First, M. edulis and M. galloprovincialis are nearly identical considering karyotypes, and the number and location of ribosomal loci (figure 1), but differences in C-bands are clear (figure 2). However, we must mention here that the number of C-bands varies depending on the material used; it is high when using chromosomes from nauplius larvae (Martínez-Lage et al. 1995), but lower when using chromosomes from adults. Second, karyotype differences are more pronounced between M. trossulus from American and European coasts, not only regarding to the chromosome morphology but also the location of ribosomal loci. Maybe, chromosome pair 9 of M. trossulus from American coasts and chromosome pair 8 from the European populations be alike in morphology and location of the major ribosomal loci, but the rest of chromosomes and the locations of ribosomal loci are different (figure 1). Third, the karyotype of M. californianus is more similar to M. trossulus than to the rest of Mytilus, but both species can be clearly differentiated by karyotyping. Fourth, cytogenetic analyses in M. desolationis and M. coruscus are limited exclusively to the description of karyotypes, which unravel obvious karyotype differences among them and the rest of Mytilus analysed. Karyotype differentiation is an important mechanism for reproductive isolation and speciation (Navarro and Barton 2003). Closely related species often differ by chromosome rearrangements that might give problems at meiosis and to reduce the fertility of F1 hybrids, and thus to confer postzygotic isolation. Genetic isolation is more likely to be accomplished by sucessive chromosome rearrengements (mainly inversions), each of which slightly reduces fertility, than by a single substitution that reduces it severely (White 1978; Walsh 1982; King 1993; Futuyma, 1998). Despite these genetic mechanisms, the existence of hybrids among different Mytilus species is well documented. Hybrid M. trossulus x M. galloprovincialis populations have been described on the Pacific coast of North America (McDonald and Koehn 1988; Rawson et al. 1999; Wonham 2004), M. edulis x M. trossulus in European and

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American coasts (Toro et al. 2002; Riginos and Cunningham 2005), and M. edulis x M. galloprovincialis in different European coasts (Gardner 1996; Bierne et al. 2003). a)

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Figure 2. Idiograms for C-banding in Mytilus edulis, M. galloprovincialis and M. trossulus. Black and grey blocks indicate the intensities of the C-bands. (Based on Martínez-Lage et al. 1994, 1995).

The existence of hybrid populations in some of Mytilus species seems to be in accordance with chromosomal rearrangements producing balanced meiosis, in which normal segregation of the meiotic products occurs, but they will no longer be able to form a postmating isolating mechanisms, and will generally result in chromosomal polymorphisms (King 1987). The high similarity in chromosome morphology between M. edulis and M. galloprovincialis easily explains the occurrence of hybrids which are able to produce F2 and backcrosses. Karyotype similarity would also explain the high viability of the European M. edulis x M. trossulus hybrid populations. So, chromosome similarity would reduce the probabilities of unbalanced meiosis and, subsequently, not many acentric and dicentric meiotic products will be produced. This would explain why no strong reproductive barriers are currently acting to maintain the integrity of the European M. trossulus genome (Riginos and Cunningham 2005). However, the differences in karyotypes of M. trossulus and M. edulis from American coasts would produced unbalanced meiosis which cause non-viable gametes in a very high proportion, and so it would explain why M. trossulus x M. edulis hybrids are rare and only appear in a frequency of 0%-2.5% (Saavedra et al. 1996; Rawson et al. 2001). In conclusion, cytogenetic studies are needed to investigate the chromosome rearrangements occurred in Mytilus. There is still quite to be done regarding all these mussels, specially on M. galloprovincialis from west American coast, M. trossulus from east American coast, M. desolationis and M. coruscus. Karyotype analyses and chromosome banding give information on chromosomal rearrangements playing a role in the majority of speciation events and, subsequently, explain the effects of the rearrangements on the fitness of heterozygous hybrids.

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ACKNOWLEDGMENTS The authors thank Joaquín Vierna for his comments.

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Martínez-Expósito MJ, Méndez J, Pasantes JJ (1997) Analysis of NORs and NOR-associated heterochromatin in the mussel Mytilus galloprovincialis. Chromosome Research 5, 268273. Martínez-Lage A, González-Tizón AM, Ausió J, Méndez J (1997) Karyotypes and Ag-NORs of the mussels, Mytilus californianus and M. trossulus from the Pacific Canadian coasts. Aquaculture 153, 239-249. Martínez-Lage A, González-Tizón AM, Méndez J (1994) Characterization of different chromatin types in Mytilus galloprovincialis L. after C-banding, fluorochrome and restriction endonuclease treatments. Heredity 72, 242-249. Martínez-Lage A, González-Tizón AM, Méndez J (1995) Chromosomal markers in three species of the genus Mytilus (Mollusca: Bivalvia). Heredity 74, 369-375. Martínez-Lage A, González-Tizón AM, Méndez J (1996) Chromosome differences between European mussel populations (genus Mytilus). Caryologia 49, 343-355. Martínez-Lage A, Rodríguez F, González-Tizón AM, Prats L, Cornudella L, Méndez J (2002) Comparative analysis of different satellite DNAs in four mussel Mytilus species. Genome 45, 922-929. Martínez-Lage A, Rodríguez-Fariña F, González-Tizón AM, Méndez J (2005) Origin and evolution of Mytilus mussel satellite DNAs. Genome 48, 247-256. McDonald JH, Koehn RK (1988) The mussels Mytilus galloprovincialis and Mytilus trossulus on the Pacific coast of North America. Marine Biology 99, 111-118. McDonald JH, Seed R, Koehn RK (1991) Allozymic and morphometric characters of three species of Mytilus in the Northern and Southern Hemispheres. Marine Biology 111, 323335. Méndez J, Pasantes JJ, Martínez-Expósito MJ (1990) Banding pattern of mussel (Mytilus galloprovincialis) chromosomes induced by 2xSSC/Giemsa-stain treatment. Marine Biology 106, 375-377. Navarro A, Barton NH (2003) Chromosomal speciation and molecular divergence-accelerated evolution in rearranged chromosomes. Science 300, 321-324. Pasantes JJ, Martínez-Expósito MN, Martínez-Lage A, Méndez J (1990) Chromosomes of Galician mussels. Journal of Molluscan Studies 56, 123-126. Pasantes JJ, Martínez-Expósito MJ, Méndez J (1996) C-band polymorphism in the chromosomes of the mussel Mytilus galloprovincialis. Caryologia 49, 233-245. Pereira Silva E, Skibinski DOF (2009) Allozymes and nDNA markers show different levels of population differentiation in the mussel Mytilus edulis on British coasts. Hydrobiologia 620, 25-33. Plohl M, Prats E, Martínez-Lage A, González-Tizón A, Méndez J, Cornudella L (2002) Telomeric localization of the vertebrate-type hexamer repeat, (TTAGGG)n, in the wedgeshell clam Donax trunculus and other marine invertebrate genomes. The Journal of Biological Chemistry 277, 19839-19846. Quesada H, Gallagher C, Skibinski DAG, Skibinski DOF (1998) Patterns of polymorphism and gene flow of gender-associated mitochondrial DNA lineages in European mussel populations. Molecular Ecology 7, 1041-1051. Rawson PD, Agrawal V, Hilbish TJ (1999) Hybridization between the blue mussels Mytilus galloprovincialis and M. trossulus along the Pacific coast of North America: evidence for limited introgression. Marine Biology 134, 201-211.

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Rawson PD, Hayhurst S, Vanscoyoc B (2001) Species composition of blue mussel populations in the northern Gulf of Maine. Journal of Shellfish Research 20, 31-38. Rawson PD, Hilbish TJ (1998) Asymmetric introgression of mitochondrial DNA among European populations of blue mussels (Mytilus spp.). Evolution 52, 100-108. Ridgway G, Naevdal GN (2004) Genotypes of Mytilus from waters of different salinity around Bergen. Norway Helgoland Marine Research 58, 104-109. Riginos C, Cunningham CW (2005) Local adaptation and species segregation in two mussel (Mytilus edulis x Mytilus trossulus) hybrid zones. Molecular Ecology 14, 381-400. Riginos C, McDonald JH (2003) Positive selection on an acrosomal sperm protein, M7 lysin, in three species of the mussel genus Mytilus. Molecular Biology and Evolution 20, 200207. Rodríguez-Juíz, A. M., M. Torrado, and J. Méndez. 1996. Genome-size variation in bivalve molluscs determined by flow cytometry. Marine Biology 126:489-497. Ryan Gregory T (2001) Coincidence, coevolution, or causation? DNA content, cell size, and the C-value enigma. Biological Reviews 76, 65-101. Skibinski DOF, Ahmad M, Beardmore JA (1978) Genetic evidence for naturally occurring hybrids between Mytilus edulis and Mytilus galloprovincialis. Evolution 32, 354-364. Śmietanka B, Zbawicka M, Molowicz M, Wenne R (2004) Mitochondrial DNA lineages in the European populations of mussels (Mytilus spp.). Marine Biology 146, 79-92. Saavedra C, Sewart DT, Stanwood RR, Zouros E (1996) Species-specific segregation of gender-associated mitochondrial DNA types in an area where two mussel species (Mytilus edulis and M. trossulus) hybridize. Genetics 143, 1359-1367. Thiriot-Quiévreux C (1984) Chromosome analysis of three species of Mytilus (Bivalvia : Mytilidae). Marine Biological Letters 5, 265-273. Toro JE, Thompson RJ, Innes DJ (2002) Reproductive isolation and reproductive output in two sympatric mussel species (Mytilus edulis, M. trossulus) and their hybrids from Newfoundland. Marine Biology 141, 897-909. Varvio SL, Koehn RK, Väinölä R (1988) Evolutionary genetics of the Mytilus edulis complex in the North Atlantic region. Marine Biology 98, 51-60. Väinölä R, Hvilsom MM (1991) Genetic divergence and a hybrid zone between Baltic and North Sea Mytilus populations (Mytilidae; Mollusca). Biological Journal of the Linnean Society 43, 127-148. Walsh JB (1982) Rate of accumulation of reproductive isolation by chromosome rearrangements. The American Naturalist 120, 510-532. White MJD (1978) Modes of Speciation. WH Freeman and Co. San Francisco. Wolowicz M, Thiriot-Quiévreux C (1997) The karyotypes of the most common bivalves species from the south Baltic. Oceanological Studies 2-3, 209-221. Wonham MJ (2004) Mini-review: distribution of the Mediterranean mussel Mytilus galloprovincialis (Bivalvia: Mytilidae) and hybrids in the Northeast Pacific. Journal of Shellfish Research 23, 535-543. Zbawicka M, Burzyński A, Skibinski D, Wenne R (2010) Scottish Mytilus trossulus mussels retain ancestral mitochondrial DNA: complete sequences of male and female mtDNA genomes. Gene 456, 45-53.

In: Mussels: Anatomy, Habitat and Environmental Impact ISBN 978-1-61761-763-8 Editor: Lauren E. McGevin ©2011 Nova Science Publishers, Inc.

Chapter 24

A NEW APPROACH IN BIOMONITORING FRESHWATER ECOSYSTEMS BASED ON THE GENETIC STATUS OF THE BIOINDICATOR DREISSENA POLYMORPHA Godila Thomas1, Göran I. V. Klobučar2, Alfred Seitz1 and Eva Maria Griebeler1 1

Department of Ecology, Zoological Institute, University of Mainz, Germany 2 Department of Zoology, Faculty of Science, University of Zagreb, Croatia

ABSTRACT Evolutionary toxicology investigates population genetic effects caused by environmental contamination. Toxicant inputs of increasing industry, agriculture and fast growing cities have severely modified freshwater ecosystems. These anthropogenic stressors are expected to influence population genetic patterns by causing mortalities, so that, e.g., a recent reduction in genetic diversity would be indicative of deteriorating environmental conditions. The amount of genetic diversity can therefore be applied as a biomarker for the condition of freshwater ecosystems in a biomonitoring system. The zebra mussel is a common bioindicator for passive as well as active biomonitoring of freshwater ecosystems. Here, we suggest a novel approach to establish the genetic status of zebra mussel populations as an independent indicator of environmental condition. In this strategy, the well-established techniques of comet assay, micronucleus test and microsatellite analysis are combined to assess the health of freshwater habitats.

Keywords: ecotoxicology, population genetics, genetic diversity, biomonitoring, genotoxicity, comet assay, micronucleus test.



microsatellites,

Corresponding author: [email protected], Fon: +49 6131 3923956, Fax: +49 6131 3923731

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Ecotoxicology is an interdisciplinary field which encompasses the impact of anthropogenic stressors on the living environment. Due to an ever increasing human population and its activities associated with agriculture, defense, industry and commerce, anthropogenic pollutants are widely distributed in ecosystems (Vitousek et al. 1997, Bickham et al. 2000). The majority of the toxicant inputs terminate in aquatic ecosystems. They have severely modified freshwater ecosystems, and the long-term ecological effects of these hazardous substances are largely unknown (Anderson et al. 1994). Evolutionary toxicology is an important focus in the field of ecotoxicology. It investigates population genetic effects caused by environmental contamination. Pollution can clearly be a selective force and it is probable that organisms that inhabit polluted environments are continuously exposed to mutational pressure (Crow 1997). Toxicant inputs can have impacts on wildlife populations causing somatic and heritable mutations (Bickham et al. 2000). Bearing in mind the importance of DNA in maintaining homeostasis of all organisms and for the transfer of information to offspring, it is important to assess genotoxicity (damage of DNA and chromosomes) to determine pollution-related stress in an ecosystem (Klobučar et al. 2003). Genotoxic effects in germ cells can result in rapid alterations of gene frequencies in natural populations (Depledge 1998). However population genetic effects are not only due to molecular toxic mechanisms. Stochastic effects leading to inbreeding in small populations, overall loss of genetic diversity and loss of heterozygosity, as well as the accumulation of deleterious mutations in a gene pool (mutational load) are compounding factors that reduce fitness and accelerate the process of population extinction (Saccheri et al. 1998, Bickham et al. 2000, Theodorakis 2001). Genetic changes in a population due to toxicants, especially the loss of genetic diversity, might be permanent and could only recover if the population survived for a very long time, if there was no considerable gene flow from other populations. On the other hand, due to the mutagenic effect of chemicals, new alleles and genes could arise and increase population genetic diversity. While selection and genetic drift typically reduce genetic diversity, mutation and migration are the major processes that increase genetic variability in a population. If no catastrophe is happening, these evolutionary processes act slowly, so the timescale relevant for the response of genetic diversity is rather years than months. Therefore, one advantage of monitoring genetic diversity is that footprints of toxicants in population genetic patterns may still be detectable after years or decades, even if the abundance of the population has already recovered. As there is often a time lag before changes in genetic diversity become significant, a genetic diversity indicator is expected to be primarily useful for multigenerational exposures (Bickham et al. 2000, Bagley et al. 2002). A bioindicator is an organism reflecting environmental conditions of its habitat by its presence or absence and its function (van Gestel and van Brummelen 1996). The zebra mussel Dreissena polymorpha has been established as a bioindicator for passive as well as active biomonitoring of freshwater ecosystems (Sues et al. 1997, Roditi et al. 2000, Bervoets et al. 2005, Pain et al. 2005). It has been applied as an early warning system for freshwater quality (Sluyts 1996, Bocherding and Jantz 1997). Moreover, the zebra mussel has been used as a model organism for freshwater mussels in several studies dealing with anthropogenic impacts on environments (Griebeler and Seitz 2007, Hidde 2008). The genetic diversity of D. polymorpha, analysed by the neutral microsatellite markers, seemed to be sensitive to environmental conditions in our preliminary studies: We observed a highly

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significant negative correlation between genetic diversity (assessed as expected heterozygosity He) and water conductivity in populations of the rivers Danube (in Hungary), Thaya (Austria) and Sio (Hungary) (Figure 1, n = 12, r = -0.9637, p < 0.0001). 1,22

1,2 1.20 1,18 1.18

arcsin (√He)

1,16 1.16 1,14 1.14 1,12 1.12 1,1 1.10 1,08 1.08 1,06 1.06

1,04

00

200 200

400 400

600 600

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conductivity (µS/cm) Figure 1. Genetic diversity of zebra mussel populations measured as expected heterozygosity (He), versus water conductivity (µS/cm). He was arcsin (√) transformed.

Water conductivity can provide information on salinity, water inflows, hydrodynamics, but also on water pollution, like agricultural runoff and industrial discharges (JDS 2001). At the sampling site with the highest conductivity (1084 µS, Figure 1), the water was highly polluted. It could be suggested that the observed correlation between the conductivity and the heterozygosity of the bioindicator D. polymorpha indicates sensitivity of its genetic diversity to freshwater pollution. Furthermore, zebra mussel populations are ideal for studying long-term effects of anthropogenic stressors. Individuals of different generations of zebra mussel populations can be well distinguished, as it is possible to identify the age of the individuals by counting annual rings on the shells (Jantz 1998). By establishing age classes of a population, we were able to show the process of an important long-term effect in a population genetic pattern: In the river Drava in Croatia, we detected an increase in the percentage of heterozygotes in one population with an increasing age of individuals reaching a steady state He of about 60% (Figure 2). The increasing percentage of heterozygotes with increasing age could reflect a heterosis effect (selection against homozygotes) in this population. Although we can only speculate on the causes of this pattern, the clear trend in change suggests that selective forces have impacted this population.

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percentage of heterozygotes (%)

In total, due to its aforementioned properties, we hypothesize that the zebra mussel could be a suitable indicator for biomonitoring freshwater ecosystems based on population genetic diversity studies. 100 90 80 70 60 50 40 30 20 10 0 1

2

3

4

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age Figure 2. Percentage of heterozygote individuals of five successive age classes at one microsatellite locus in a sample of 83 zebra mussel individuals.

Biomonitoring is the measurement of the response of living organisms to man-made changes in their environment. Following the approach of biomarker-based biomonitoring (Shugart et al 1992), we will measure responses to pollution at different levels of biological organisation, from population down to molecular level. As defined by the National Academy of Sciences (1989), a biomarker is a xenobiotically-induced variation in cellular or biochemical components or processes, structures, or functions that is measurable in a biological system or sample. Here, we suggest a novel approach in biomonitoring freshwater habitats based on the genetic status of D. polymorpha. In 2000, Bickham et al. proposed population genetic changes as the ―ultimate‖ biomarker of effect. Consequently, we will measure the genetic diversity of zebra mussel populations as an independent long term indicator of environmental pollution in our approach. This ―ultimate‖ biomarker has a slower response time than conventional biomarkers, but it is highly relevant in ecological concerns as it reflects the genetic plasticity of the population (Shugart et al. 1992). We will assess the genetic diversity of populations by microsatellite analysis. Due to their high variability and codominant mode of inheritance, microsatellites are very suitable markers to detect fast changes in genetic diversity within and among populations that are caused by environmental contamination (Bickham et al. 2000, Dimsoski and Toth 2000). Additionally, the effects of anthropogenic stressors at the population level will be assessed by measuring the population characteristics abundance and age structure. Populations exposed to pollution may have significantly reduced sizes compared to reference populations, resulting in a genetic bottleneck (Whitehead et al. 2003).

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If an ecological effect at the population level is due to chemical exposure, responses at lower levels of biological organization should also be or have been apparent (Shugart et al. 1992). Consequently, we will also measure short term indicators of pollution exposure at the molecular and cellular level of D. polymorpha. We will assess two biomarkers of genotoxicity whose response is more relevant of a recent toxic influence by comet assay and micronucleus test. These are relatively simple and rapid techniques for the detection of genotoxic pressure and common and well established in the field of ecotoxicology. They have been successfully applied for zebra mussels and have provided reliable and significant results with respect to freshwater pollution (Pavlica et al. 2001, Klobučar et al. 2003). To detect the unknown chemical stressors, a broad range of parameters will be measured, e.g., physico-chemical parameters, heavy metals and organic compounds. In this new approach, we will measure biomarkers at different levels of biological organisation as well as water quality parameters to assess the short and long-term impacts of environmental contamination on the genetic status of zebra mussel populations. This is a strategy to monitor instantaneous and long-term effects of pollution on freshwater ecosystems, and could aid in managing pressures on these ecosystems. In a current project, we test our new approach in biomonitoring. We assess and compare the genetic status of zebra mussel populations of polluted and non-polluted sites in the river Drava in Croatia.

ACKNOWLEDGMENTS A slightly modified version of this commentary is a part of the PhD thesis of Godila Thomas. We thank S. Winkelmann, M. Paunovic, B. Csanyi and R. Erben for help with field work, N. Hammouti, D. Berens and M. Šrut for valuable discussions and F. Jung and T. Schneider for help with the microsatellite analyses in the laboratory. This study is funded by the Johannes Gutenberg-University of Mainz.

REFERENCES Anderson, S.; Sadinski, W.; Shugart, L.; Brussard, P.; Depledge, M.; Ford, T.; Hose, J.; Stegeman, J.; Suk, W.; Wirgin, I. and Wogan, G. (1994). Genetic and Molecular Ecotoxicology. A Research Framework. Environmental Health Perspectives, 102, 3-8. Bagley, M. J.; Franson, S. E.; Christ, S. A.; Waits, E. R. and Toth, G. P. (2002). Genetic Diversity as an Indicator of Ecosystem Condition and Sustainability: Utility for Regional Assessment of Stream Condition in the Eastern United States. Cincinnati, OH: U.S. Environmental Protection Agency. Bervoets, L.; Voets, J.; Covaci, A.; Chu, S.; Qadah, D.; Smolders, R.; Schepens, P. and Blust, R. (2005). Use of transplanted zebra mussels (Dreissena polymorpha) to assess the bioavailability of microcontaminants in flemish surface waters. Environmental Science and Technology, 39, 1492-1505.

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Bickham, J. W.; Sandhu, S.; Hebert, P. D. N.; Chikhi, L. and Athwal, R. (2000). Effects of chemical contaminants on genetic diversity in natural populations: implications for biomonitoring and ecotoxicology. Mutation Research, 463, 33-51. Bocherding, J. and Jantz, B. (1997). Valve movement response of the mussel Dreissena polymorpha - the influence of pH and turbidity on the acute toxicity of pentachlorophenol under laboratory and field conditions. Ecotoxicology, 6, 153-165. Crow, J. F. (1997). The high spontaneous mutation rate: is it a health risk? Proceedings of the National Academy of Sciences of the United States of America, 94, 8380-8386. Depledge, M. H. (1998). The ecotoxicological significance of genotoxicity in marine invertebrates. Mutation Research, 399, 109-122. Dimsoski, P. and Toth, G. P. (2000). Development of DNA-based Microsatellite Marker Technology for Studies of Genetic Diversity in Stressor Impacted Populations. Ecotoxicology, 10, 229-232. Griebeler, E. M. and Seitz, A. (2007). Effects of increasing temperatures on population dynamics of the zebra mussel Dreissena polymorpha: implications from an individualbased model. Oecologia, 151, 530-543. Hidde (D). Auswirkungen des Klimawandels auf die klein- und großräumige genetische Populationsstruktur von Makrozoobenthos in Rhein, Main und Mosel [online]. 2008 [cited 2008 july 17]. Available from: URN: http://nbn-resolving.de/urn/ resolver.pl?urn=urn:nbn:de: hebis:77-16591. Jantz, B. (1998). Size and age structure of a riverine zebra mussel population (River Rhine, Rh-km 168-861). Limnologica, 28, 395-413. Joint Danube Survey (JDS). Results of on-board analyses: Conductivity [online]. 2001 [cited 2008 01 25]. Available from: URL: www.icpdr.org/JDS. Klobučar, G. I. V.; Pavlica, M.; Erben, R. and Papeš, D. (2003). Application of the micronucleus and comet assays to mussel Dreissena polymorpha haemocytes for genotoxicity monitoring of freshwater environments. Aquatic Toxicology, 64, 15-23. National Academy of Sciences/National Research Council (1989). Biologic Markers in Reproductive Toxicology (pp. 395). Washington, DC: National Academy Press. Pain, S.; Biagianti-Risbourg, S. and Parant, M. (2005). Relevance of the Multixenobiotic Defence Mechanism (MXDM) for the Biological Monitoring of Freshwaters - Example of its Use in Zebra Mussel. In: J. V. Livingston (Ed.), Trends in Water Pollution Research (pp. 203-220). New York, NY: Nova Science Publishers. Pavlica, M.; Klobučar, G. I. V.; Mojaš, N.; Erben, R. and Papeš, D. (2001). Detection of DNA damage in haemocytes of zebra mussel using comet assay. Mutation Research, 490, 209-214. Roditi, H. A.; Fisher, N. S. and Sanudo-Wilhelmy, S. A. (2000): Field testing a metal bioaccumulation model for zebra mussels. Environmental Science and Technology, 34, 2817-2825. Saccheri, I.; Kuussaari, M.; Kankare, M.; Vikman, P.; Fortelius, W. and Hanski, I. (1998). Inbreeding and extinction in a butterfly metapopulation. Nature, 392, 491-494. Shugart, L. R.; McCarthy J. F. and Halbrook, R. S. (1992). Biological Markers of Environmental and Ecological Contamination: An Overview. Risk Analysis, 12, 353-360. Sluyts, H.; Van Hoof, F.; Cornet, A. and Paulussen, J. (1996). A dynamic new alarm system for use in biological early warning systems. Environmental Toxicology and Chemistry, 15, 1317-1323.

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Sues, B.; Taraschewski, M. and Rydlo, M. (1997). Intestinal Fish Parasites as Heavy Metal Bioindicator: A Comparison between Acanthocephalus lucii (Palaeacanthocephala) and the Zebra Mussel, Dreissena polymorpha. Bulletin of Environmental Contamination and Toxicology, 59, 14-21. Theodorakis, C. (2001). Integration of Genotoxic and Population Genetic Endpoints in Biomonitoring and Risk Assessment. Ecotoxicology, 10, 245-256. Van Gestel, C.A.M. and Van Brummelen, T. C., (1996). Incorporation of the biomarker concept in ecotoxicology calls for a redefinition of terms. Ecotoxicology, 5, 217–225. Vitousek, P. M.; Mooney, H. A.; Lubchenco, J. and Melillo J. M. (1997). Human domination of earth´s ecosystems. Science, 277, 494-499. Whitehead, A.; Anderson, S. L.; Kuivila, K. M.; Roach, J. L. and May, B. (2003). Genetic variation among interconnected populations of Catostomus occidentalis: implications for distinguishing impacts of contaminants from biogeographical structuring. Molecular Ecology, 12, 2817-2833.

In: Mussels: Anatomy, Habitat and Environmental Impact ISBN: 978-1-61761-763-8 Editors: Lauren E. McGevin ©2011 Nova Science Publishers, Inc.

Chapter 25

MUSSELS: THEIR COMMON ENEMIES AND ADAPTIVE DEFENSES Devapriya Chattopadhyay Department of Earth Sciences, Indian Institute of Science Education & ResearchKolkata, Mohanpur Campus, Mohanpur, India

ABSTRACT Mussels are bivalves that are variously adapted for relatively immobile nature. They are characterized by the presence of short byssal threads attached close to exposed surface of hard substrates. Majority of them occur in intertidal areas, although some of them have occasionally been reported from deep water. Because of their relatively immobile nature and ubiquitous presence in the littoral and shallow sublittoral waters, they have been commonly targeted by their natural enemies. The natural enemies of mussels can be categorized in four main groups. The first group consists of predators like fish, crabs, birds, starfish and snails. Fish, crabs and birds just peel or crush the hard shell. Starfish uses whole body consumption. Predatory snails drill holes in the hard shell and consume the soft tissue; this kind of predation can be identified postmortem. Predation could be responsible for up to 50% of the mortality of a mussel population. The severity of predation generally is size and locality selective. Often the smaller size class of mussels takes the heaviest hit. The second groups of natural enemies are the competitors, fighting for similar food and space such as barnacles, crepidula, tunicates. These competitions could be severe enough to drive entire mussel population to the brink of extinction. However, these competitors are often serving as prey items for the same predators that prey upon mussels. In those scenarios, these competitors often render a positive feedback on the mussels by sharing the predation stress. The third group is the shell destroyers such as demosponges, polychaete. They are known to damage the calcitic shells of mussels by boring them. These boreholes are different from predatory drillholes as they are generally non-lethal. However, those boreholes damage the structural integrity of the shell and eventually lead them to disintegration by wave action. The fourth group of natural enemies are the parasites such as mytilicola, pinnotheres. These parasites often cause significant damage to the vital organs affecting respiration, filtration, ventilation and digestion. Although primarily these natural enemies render negative effect on mussel

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INTRODUCTION Mussels are bivalves that belong to the order Mytiloida. The members of this order are generally byssate and epifaunal throughout life or secondarily burrowing. The dominant bivalves in this group are solitary (many Modiolus) or gregarious forms (e.g. Mytilus, Brachidontes) oriented with the plane of the commisure approximately perpendicular to the substrate. These groups of closely attached byssate bivalves are generally inhabitants of shelf environments and are concentrated in and especially adapted to high energy shallow water conditions of littoral and shallow sublittoral benthic zones (sometimes they are found in fresh water too). Generally littoral and sublittoral areas are also the prime hunting area of numerous invertebrate and vertebrate predators. Because of their limited mobility and ubiquitous presence in this zone, mussels have been commonly targeted by these predators. Apart from predation, modern mussel community is also affected by competition and parasitism. In modern marine environment biological interactions such as these are one of the important sources of natural selection. Unfortunately, it is often difficult to trace these influences over the evolutionary timescale. The evolutionary history of mussels shows development of certain characters that are clearly advantageous against common natural enemies. So it has been suggested that these natural enemies have played an important role in shaping the evolutionary lineage of mussels through time.

EVOLUTIONARY HISTORY The order Mytiloida has a long evolutionary history starting from Devonian continuing till Recent. Bivalves of this order adapt to high energy shallow water conditions in having hydrodynamically streamlined shells which are tightly affixed to the substrate by short byssus. This also provides effective protection against the predators. It is comprised of two superfamilies, Mytilacea and Pinnacea. The first superfamily is represented by the family Mytilidae and Mysidiellidae. The fossil record of the family Mytilidae dates back to Early Paleozoic. Fossil records seem to indicate that Modiolus- and Lithophaga-like species probably originated in the Silurian and Devonian, as such forms occur early in the Paleozoic strata. Mytilus-like species may have evolved from the Brachidontes group during the Jurassic. The fossil record of the other family Mysidiellidae is relatively short continuing from Lower Triassic to Upper Triassic. Sperfamily Pinnacea is represented by the family Pinnidae. It has a fossil record continuing from Lower Carboniferous to Recent. This family, secondarily members of the order, is usually arbitrarily classed as Pteriacea. They are morphologically isolated but also have much in common with the Mytilicea and there is no paleontological evidence that Pinnidae were derived from inequivalve ancestors.

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NATURAL ENEMIES As mentioned before, most of the mussel groups are inhabitant of the shallow marine area which is also the very place of hunting for many invertebrate and vertebrate predators. Apart from the predators, this area is the habitat of other invertebrate groups (such as barnacles) that often compete with mussels for food and resources. In addition to predation and competition, there are two other types of biotic interaction that commonly affects the mussel population, namely the parasitism and the shell destruction. The natural enemies affect the mussel population in two different ways; some of them target the planktonic and postveliger stage while others attack the attached stage. It may be argued that since the mussel mortality is highest in planktonic and postveliger stage (Molloy et al., 1997), the mortality of attached mussels (both juvenile and adult) that is inflicted by natural enemies is of little importance to overall population dynamics of most of the mussels. However, the question that is most commonly being asked is what biotic factors limit the densities of attached mussels since the planktonic mussels are not known to cause ecological and economic problems, only attached stages do. Consequently, in this study, the natural enemies of the attached stage were discussed in greater details.

PREDATION Of all potential mortality factors, predation plays perhaps the most important role. Many species feed on mussels and amongst the most important are crabs, gastropods, starfish and birds. Most of these predators attack both the larval and the attached phase.

Durophagous Predation Durophagous or shell crushing predation is one of the major modes of predation affecting mussel population. Laboratory and field experiments show that crabs (Cancer and Carcinus) can take large numbers of mussels in their diets (Kitching et al., 1959; Seed, 1969a; Walne & Dean, 1972; Harger, 1972b). The results suggest that size selection occurs and that the upper size limit which can be opened is directly related to the size of the crab. Kitching et al., (1959) and Ebling et al. (1964) reported extensive crab predation in Lough Ine and tentatively attributed the absence of mussels sublittorally in many localities to this cause (Kitching and Ebling, 1967). The littoral crab population, however, varies seasonally, with an offshore migration into deeper water during winter (Naylor, 1962). In their experiments with crabs in the Menai Straits (North Wales), Walne & Dean (1972) found that the mortality from crab predation is generally most intense in the low shore and sublittoral areas where crabs are most abundant and where they can feed for longer periods. Since all size ranges of crabs can crush small mussels whilst the large mussels are only available to larger, stronger crabs, a disproportionate mortality among the smaller mussels is to be expected. Heavy mortality of plantigrades due to crab predation has been demonstrated by Edwards (1968), Reynolds (1969) and Harger (1972b). Spatfall may be effective only when there are sufficient plantigrades to satisfy the needs of the predators and also provide a surplus to stock

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the mussel beds. Growth in M. edulis would therefore be accompanied by a relative decrease in crab predation. Feeding habit of Carcinus was examined by Ropes (1968), who showed that feeding is influenced by abundance, size and type of food. Temperature, tides and time of day also appeared to be important. Walne & Dean (1972) also demonstrated that crabs can discriminate between the size of prey when given a choice, but the numbers eaten could be modified by experimental conditions. Prey density seemed to be important, and a competitive element between crabs may also have been involved. Perkins (1967) showed that Carcinus would feed on a greater proportion of smaller mussels even though larger ones could be opened without difficulty. He suggested that a learning process may be involved, which enables crabs to feed with minimum effort. Seed (1980) have observed that the mud crab Panopeus herbst and the blue crab Calllnectes sapidus can consume large numbers of the Atlantic ribbed mussel Geukensia (=Modiolus) demlssa. He also observed that although the crabs could consume mussels over a wide size range they showed a marked reluctance to feed on larger mussels whilst smaller, more easily predated prey was still available. Under regimes of unlimited prey availability both crabs showed a pronounced preference for specific size classes of mussels. Harger (1972a) showed that both Cancer antennarius and Pachygrapsus crassipes had a preference for M. edulis over M. californianus. The maximum length of the mussels eaten by both crabs was dependent on the size of the predator. Predation rates were such that the mussels required six to eight weeks from settlement before they become large enough to escape predation by crabs, and he concluded that to survive on most rocky shores inabitated by crabs, mussels must settle at densities in excess of 10000 per square meter. When the two species of mussel occurred together, M. californianus was afforded some protection from predation by the presence of M. edulis, but the later species only settled in high enough densities to survive during summer months. Oystercatchers (Haematopus) feed extensively on Mytilus (Webster, 1941; Drinnan, 1958; Tinbergen & Kruuk, 1962; Tinbergen & Norton-Griffiths, 1964; Dare, 1966; NortonGriffiths, 1967; Heppleston, 1971), particularly over the winter months. This frequently results in heavy mortality in commercial mussel beds. On exposed shores, however, although mussels are taken in small numbers, oystercatchers seem to feed chiefly on limpets and dogwhelks (Feare, 1971). Sandpipers (Feare, 1966), knot (Prater, 1972), various species of duck (Belopolskii, 1961; Manikowski, 1968; Theisen, 1968; Nilsson, 1969) and gulls (Oldham, 1930; Rooth, 1957) are also known to feed on Mytilus. Milne & Dunnet (1972) record around 70% of the net annual production of a mussel bed passed to bird predators (oystercatchers, eider and gulls).

Drilling Predation There are two main families of gastropods, muricid and naticid, that are responsible for the mortality due to drilling predation. These groups are carnivorous gastropods who drill a hole on the outer shell of mussels. After drilling, they ingest the soft inner part. Since the drill holes often get preserved along with the shell, it is of particular interest to paleontologists studying ancient predator-prey interaction. In modern marine environment, drilling predation is one of the major causes of mortality among bivalve population. Since, mussels that have been attacked by predatory gastropods, can generally be identified by presence of a small hole

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drilled through the shell, it is easier to evaluate their impact on the prey population even without direct monitoring of the attack. The dogwhelk Nucella lapillus is a widely distributed littoral predator in Europe, especially abundant on exposed rocky shores, where it is known to feed extensively on mussels (Fishcher-piette, 1935; Pleissis, 1958; Kitching, Sloane & Ebling, 1959; Largen, 1967; Seed, 1969a; Menge, 1976, 1977). It has also been reported from North American coasts (Kowalewski, 2004; Chattopadhyay & Baumiller, 2007; Casey & Chattopadhyay, 2008). The distribution of Nucella on the mussel beds is markedly seasonal – during the winter, few adult whelks are found actively feeding since at this time of the year they aggregate in cracks and pools in order to breed (Feare, 1972). Laboratory experiments indicate that the adult whelks could each consume an average of 2.17 mussels (1-3 cm in length) per week during the summer months whilst the immature individuals took an average of 1.01 mussels of this size range (Seed, 1969a). Whether such experiments reflect the normal feeding rate in natural population is, however, uncertain. Examination of drilled shells in some studies showed that the thinnest parts of the shell are most commonly attacked, especially at the umbonal end and around the region where the adductor muscles are inserted (Kitchell et al., 1981). They have also demonstrated that for naticid gastropod Polinices duplicatus, selection of prey size is determined by the net-energy gain of the attack. Chattopadhyay and Baumiller (2009) have demonstrated the same to be true for muricid gastropod preying upon Mytillus trossulus. However, Kowalewski (2004) observed no significant cite stereotypy in drilled Mytillus trossulus preyed upon by Nucella lamellosa. Harger (1972a) observed that Thais emarginata showed a strong preference for M. edulis over M. californianus in the low intertidal. Several other gastropods, such as Ocenebra (Chew & Eisier, 1958), Urosalpinx (Human, 1971) and Acanthina, Ceratostoma and Jaton (Harger, 1972b) are known to eat mussels.

Starfish Attacks Asteroid starfish are major predators of mussels in many areas. Although Asterias rubens is usually present on most rocky shores in northern Europe in low densities, periodically their numbers rise dramatically such that they form a blanket over much of the middle and lower shore. Such areas may become devoid of Mytilus (Seed, 1969a; Dare, 1973, 1975). Dare (1975) recorded large invasions of Asterias onto beds of mussels just above low water mark in Morecambe Bay (England). Such swarms of starfish are clearly a major factor in controlling the distribution of M. edulis in the low shore and sublittorally. Other varieties of sea stars (such as Asterias vulgaris, Pisaster ochraceus, Leptasterias polaris) were reported to prey upon mussel beds from North America (Paine, 1966, 1969; Himmelman & Dutil, 1991). As a result of some interesting experiments, Hancock (1965) concluded that Asterias has difficulty in opening mussels from Denmark, which had large adductor muscles than mussels of comparable size from British water. However, these results can also be explained by differences in chemical attraction. Castilla (1972) has shown that Asterias orientates towards Mytilus in Y-maze experiments, especially between November and May, but less readily between June and October. He suggested that this seasonal difference may be due a lowered chemosensitivity, or to seasonal changes in the production of attractants by the prey.

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Kitching, Sloane & Ebling (1959) concluded, as a result of transplantation experiments, that the seastar Marthasterias glacialis was responsible for preventing the establishment of Mytilus sublittorally in Lough Ine (Ireland). Paine (1966, 1969, 1971, 1974) has studied the predation of Stichaster australis on Perna canaliculus in New Zealand and Pisaster ochraceus on Mytilus californianus on the west coast of America. In both cases, the character of intertidal community is dependant in part on the predatory activities of the starfish and, in particular, on their preferential consumption of the mussels (Landenberger, 1968; Paine, 1969; Feder, 1970). Removal of the starfish from the shore results in encroachment by the mussels (both vertically downwards and horizontally) into areas not previously occupied, eventually producing a virtual monoculture of mussels. Predation by Pisaster and Stichaster controls the distribution of the mussels on the low shore. In addition to the predators already mentioned, various fish (eg. plaice, flounder) also feed on mussels, especially in flat sandy areas. Zebra mussel has been targeted by various fish groups such as round goby, freshwater drum, common carp and pumpkinseed (summarized by Molloy et al., 1997). The grazing activities of limpets (Connel, 1972) and sea urchins may also account for some mortality, particularly amongst young mussels on low shore. Mammals such as seals, sea otters and walrus are also reported to take limited numbers of mussels in certain localities.

MULTIPLE PREDATOR EFFECT (MPE) In many classical studies on predator–prey interactions, the system has been treated from a two-taxon perspective, that of the predator and its prey; interactions with other predators have generally not been considered. However, among ecologists the past few decades have seen much discussion devoted to the interaction between different predatory groups and the resulting ‗emergent effects‘ (Sih et al. 1985, 1998; Lima and Dill 1990). Given that natural communities typically have multiple predators feeding on many prey, understanding emergent multiple predator effects (MPEs) is a critical issue for community ecology (Wilbur and Fauth 1990; Wooton 1994). Studies suggest two main types of emergent effects: (1) risk reduction caused by predator–predator interactions and (2) risk enhancement caused by conflicting prey responses to multiple predators. Many studies have observed the first type of emergent effect where the interaction of multiple predators reduced the net risk for mussels. Kitching, Sloane and Ebling (1959) studied the predation of mussels in Lough Ine (Ireland). Thais lapillus was the most conspicuous predator of mussels (M. edulis) on the open coast nearby, but was absent in the Lough proper, probably due to intense predation by crabs. Consequently, the mussels escaped drilling predation in that area. Paine (1971) reported that, rather surprisingly, Neothais scalaris seemed to have little influence on Perna canaliculus populations in New Zeland. The gastropod was capable of eating both large and small mussels, and was present on the shore in high densities. He concluded that small Perna was more accessible to predators than large mussels and these small individuals are the preferred prey of the starfish Stichaster. In order to attack the small Perna, the drilling gastropods need to compete with starfish. Going for large mussels high in the intertidal is not an option either since the gastropod then exposes itself to higher physical hazards. Consequently, the prey population is virtually unharmed by the drilling predators. In a

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laboratory experiment, Chattopadhyay & Baumiller (2007) have demonstrated that the presence of a crab, Cancer gracilis, drilling gastropods change their behavior and largely abstain from drilling mussels. That can significantly reduce the mortality rate of Mytilus trossulus due to decreased drilling predation by Nucella lamellosa.

ANTI-PREDATORY STRATEGIE Clumping Clumping behavior in mussels has been shown to act as a successful anti-predatory defense against durophagous predators like crabs and lobsters (Okamura, 1986; Lin, 1991). This interpretation of clumping behavior is further supported by experimental evidence showing that exposure to chemical cues derived from crushing predators can induce clumping behavior (Côté and Jelnikar, 1999) and increased number and diameter of byssal threads produced by the mussel Mytilus edulis (Côté, 1995). Okamura (1986) showed that the risk of crushing predation is lowest for individuals on the interior of clumps where the negative effects of aggregate living are highest. Aggregate living is ubiquitous in natural populations of mussels in spite of the reduced growth rate and decreased fecundity experienced by aggregated mussels, especially those in the center (Bertness and Grosholz, 1985). The mussels experience a trade-off between the negative effects of living in clumps and the protection afforded by aggregate living. Casey & Chattopadhyay (2008) have observed a significant decrease in the drilling frequency within the group containing clumped mussels compared to the mussels kept in isolation, confirming that clumping acts as a successful antipredatory strategy against drilling predators.

Shell Structure Shell Morphology has been observed to be highly plastic in response to chemical cue from the predators. Changing the growth rate could be beneficial against predation in different ways. Increasing growth rate often results in thickening the shell that plays an important role against durophagous predation since thicker shells require higher strength to crush. On the other hand, increase in growth rate results in attaining larger size that might serve as a protective defense (―size-refuge‖). Blue mussels Mytilus edulis have been observed to show induced defense in the presence of a durophagous predator (Leonard et al., 1999). In the presence of intense crab predation, they develop thicker shells and produced more byssal threads that are firmly attached to the substrate. Similar results have been studied in the presence of starfish (Reimer & Tedengren, 1996). Mytilus edulis, were cultured in field enclosures in close vicinity of and in absence of its predator, the starfish Asterias rubens. After four weeks, the morphology differed such that predator-exposed mussels were significantly smaller in outer size (shell length, height and width), but had significantly larger posterior adductor muscle, thicker shell, and more meat per shell volume. Sommer et al. (1999) have demonstrated the size refuge for Mytilus edulis attacked by starfish Asterias rubens in a laboratory experiment.

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Small individuals of Mytilus sp. are extremely vulnerable to predation by invertebrate predators, but the general opinion is that the predation pressure is limited when mussels reach larger sizes (e.g. starfish predation, Paine 1976 and Oneill et al. 1983). However, Reimer & Tedengren (1996) study shows that the expression "escape by growth", commonly used to describe life history traits of Mytilus sp. (e.g. Paine 1976), needs some modification. Mussels may as well "escape by growth reduction", i.e. become more compact and improve their defenses, in response to presence of predators.

Behavioral Defense In addition these physiological defenses, mussels often show behavioral modifications that are beneficial against predation. For instance, mussels sometime use a ―reverse size refuge‖. They share habitat with barnacles in the intertidal zone. It has been observed that the smaller size class of Modiolus modiolus takes refuge in dead barnacle shells (personal observation). This behavior often protects them from drilling and avian predators. Mussels can, most likely, reduce their attractiveness to predators by reducing the activity and thereby the release of attracting substances. Such behaviors, i.e. lowered activity when exposed to chemical stimuli from predators, are reported in marine mussels (Doering 1982, Vial et al. 1992, Reimer et al. 1995). Another, more speculative, possibility is that M. edulis have a "chemical camouflage", involving release of substances that repels starfish (Castilla 1972).

COMPETITION FOR FOOD AND RESOURCES This group of natural enemies consists of the competitor, fighting for similar food and space such as barnacles, crepidula, tunicates and sponges. Competition could be severe enough to drive entire mussel population to the brink of extinction. However, these competitorss often serve as prey items for the same predators that prey upon mussels. In those scenarios, the competitors render a positive feedback on the mussel population by sharing the predation stress.

Intraspecific Intense spatfalls of young plantigrades can constitute a major mortality factor through intraspecific competition, since the underlying mussels suffocate, thereby loosening the entire population from the surface of the substratum. Under such conditions, large areas are denuded of mussels, especially during stormy weather (Dare, 1975). Small mussels may become attached amongst larger individuals where they find competition too severe and die. Alternatively, the attachment of plantigrades around the bases of adult mussels may afford the former some protection from predators (Kitching and Ebling, 1967). Competition for space can be especially acute in areas of fast growth, and this occasionally leads to ‗hummocking‘, mussels in the center of the hummock often having no direct contact with the substratum.

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This in turn may lead to instability, with much of the population being easily torn away during rough seas. However, in terms of general population dynamics this should be considered as emigration rather than mortality, since some of these mussels will survive to colonize other areas. Knight-Jones & Moyse (1961) concluded that intraspecific competition may be more severe in colder than warmer latitudes, or in difficult environments, where species are few and primary production less.

Interspecific On most rocky shores space is the major resource (Dayton, 1971; Connell, 1972) and competition for space amongst barnacles, algae and mussels may be intense. Under these conditions, mussels are often the competitive dominants (Paine, 1971, 1974). There is often competition between different species of mussels. Competition between Mytilus edulis and Mytilus californianus has been studied in great detail and in most of the cases M. californianus establishes itself as the competitive dominant (Harger, 1972b; Paine & Levin, 1981). Besides competing different mussel species, they also compete with other invertebrate groups in shallow water. The freshwater sponge Ephydatia fluviatilis and the zebra mussel Dreissena polymorpha were found to compete for space in Lake Trasimeno, because they colonize the same hard substrata (rocks and concrete) (Gaino, 2005). Sponges tend to be encrusting but they can give rise to massive forms on concrete. In both cases, sponges grow and can gradually envelop the valves up to the final encapsulation of the mussels. Asexual reproduction by means of resistant bodies, or gemmules, allows sponges to withstand the environmental stress, such as desiccation of the habitat or temperature values beyond the limit that are acceptable for mussel survival. The suppressive influence of E. fluviatilis allows this sponge to be considered a natural enemy of D. polymorpha, acting as a biological control agent on the spreading of the mussel population. The interaction between barnacles and mussels are often competitive as far as the food and resources are concerned. However, it becomes fairly complicated with the presence of a predator. Lively & Raimondi (1987) observed the interaction between three intertidal groups, barnacle and mussels (competitors) and gastropod (predator). They observed that barnacle clumps enhance the recruitment of mussels and therefore have a positive effect on both barnacle survivorship and mussel recruitment. Morula, the gastropods predator, had a negative effect on mussel density and the mussels have a negative effect on barnacle density. The density of Morula on barnacle density is positive due to its selective removal of mussels. These results suggest an indirect mutualism between barnacle and the predator, because barnacles attract settlement or enhance the survival of the mussels, and the predator reduces the competitive effect of mussels on barnacles. Similar scenario has been observed in the western coast of North America. Although the barnacles generally compete with Mytilus trossulus, they also share the predation pressure imposed by the drilling gastropod Nucella lamellosa. Consequently, in the intertidal habitat very few drilled mussels can be found while most of the drillholes are concentrated in the barnacles (Kowalewski, 2004; Chattopadhyay & Baumiller, 2007; Casey & Chattopadhyay, 2008). Such instances of multiple interactions leading to a positive effect have also been discussed in the prior section on MPE.

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SHELL DESTRUCTION This group is the shell destroyers such as demosponges, polychaete. They are known to damage the calcitic shells of mussels by boring them. These boreholes are different from predatory drillholes as they are generally nonlethal. However, such boreholes damage the structural integrity of the shell and eventually lead them to disintegration by wave action. Compression tests showed that high levels of Polydora ciliata infestation tended to weaken the shells of Mytilus edulis. A predation experiment indicated that the heavily infested, weakshelled mussels may be more vulnerable to the predatory activities of the crab, Cancer pagurus (Kent, 1981). Damage and removal of the protective periostracum layer of deep-sea mussels by various eukaryotic and prokaryotic microorganisms (Hook & Golubic, 1988, 1990, 1992) exposes the mineral portion of the shell to microbial destruction. This biogenic destruction exceeds the rates of inorganic carbonate dissolution in the infested area. Two types of destructive agents attack the shells of live mussels. The first type forms shallow caries along the interface between periostracum and the mineral shell, primarily attacking intercrystalline organic matrix. The second type represents boring microorganisms, morphologically similar to chytrids that penetrate and permeate the entire mineral portion of the shell. These activities significantly weaken the shell structure and increase its internal porosity (Hook & Golubic, 1993).

PARASITISM The numerous parasites which mussels may harbor are not generally thought to cause substantial mortality, though infected mussels may occasionally show symptoms of disease. Numerous larval trematodes have been described from Mytilus (Nicol, 1906; Lebour, 1912; Jameson & Nicoll, 1913). Whilst the encysted metacercaria do little harm, the presence of rediae and sporocysts may injure the molluscan host. Sporocysts of certain forms, e.g., Bucephalus, can damage the gonad and may even lead to castration. Pinnotheres (pea crabs) are commonly encountered in the mantle cavity of Mytilus and whilst their presence does not seem to affect growth or mortality of the host, they could be an important factor when food is in short supply. Wright (1917), however, points out that Pinnotheres is rarely encountered in poorly nourished mussels. Hancock (1965) and Seed (1969b) found that tissue weights of infected mussels were significantly lower than those of non-infected mussels. The relationship is a parasitic one, the crab often causing extensive gill damage (Seed, 1969b). In a related species, Fabia, Pearce (1966) found palp damage and mantle blisters to be additional problems. Some species of pea-crabs are known to be hostspecific, but there is a considerable variation amongst the Pinnotheridae (Pearce, 1966). The rate of infection is related to the size of the host (Houghton, 1963; Seed, 1969b). Seed also found differences in infection rates within coexisting populations of M. edulis (highly infected) and M. galloprovincialis (poorly infected). Of all the parasites of Mytilus, the ‗red-worm‘, Mytilicola intestinalis, has received the greatest attention. Much of this work was simulated after it was thought that it was responsible for the massive mortality of mussels on the Dutch beds in 1950. First described

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by Steuer (1902) in M. galloprovincialis, Mytilicola is a cyclopoid copepod which occurs in the gut, often as many as several dozens found in a single mussel. It was first recorded in Britain by Ellenby (1974) but since that time it has been shown to be widespread in Northern Europe (Grainger, 1951; Hockley, 1951; Korringa, 1951; Thomas, 1953; Bolster, 1954; Waugh, 1954; Hepper, 1955; Leloup, 1960; Davey & Gee, 1976; Robledo et al, 1994). Genovese (1958) maintained that Mytilicola causes little or no damage in M. galloprovincialis. However, it is more generally accepted that the presence of the parasite may lead to loss of condition and even death, although the degree of infection may be important (Cole & Savage, 1951; Mayer-Waarden & Mann, 1951). Andreu (1963) found an inverse relationship between flesh weight and number of parasites present. Hepper (1955) suggested that infection is not always harmful, particularly if conditions are generally favorable. Infection in more stressful situations, on the other hand, can cause serious harm. Reduced filtration rates by parasitized mussels have been reported by Caspers (1939) and Mayer-Waarden & Mann (1951). Mann (1956) drew attention to the adverse effects on gonad development. Electron microscope studies (Giusti, 1967) have shown Mytilicola to be a true parasite causing mechanical removal of the microvillar border of the intestinal epithelium. Mytilicola is estuarine, occurring especially in sandy or muddy bays (Mayer-Waarden & Mann, 1954 a, b) where water movement is sluggish and salinity is slightly lowered (Vilela & Monteiro, 1958). Campbell (1970) suggested that the amount of silt in the intestine of the mussel may be important in controlling the number of parasite present, and she also maintained that juvenile stages in the hepatopancreas may cause most damage. Andreu (1963) found greatest infestations in areas encountering little mixing with oceanic waters, but suggested that low salinity is probably not a decisive factor. Williams (1967, 1968) and HrsBrenko (1967) found a relationship between size of host and degree of infection; the latter worker also examined some of the factors which might influence the degree of infection and spread of parasite. Mussels higher in the littoral zone, and those raised from the bottom, are generally less infected since the infective copepodid stage crawls close to the sea bed. Williams (1969) examined the breeding cycle of Mytilicola, especially in relation to temperature and suggested that the disaster observed in the north European shellfish industry, and in which Mytilicola infection was implicated, could have been due to the unusually high sea temperature. Besides Mytilicola, there are other worms that often parasitize mussels. Polyclad worm (Stylochus mediterraneus Galleni) frequently infest Mytilus galloprovincialis Lm. They first straddle the valves at the posterior edge of the shell and then, after having digested the posterior adductor muscle, remove and swallow the soft parts of the mussels (Gallanil et al., 1980). Molloy et al., (1997) has identified 34 species that are involved in parasitic relationship with zebra mussel.

DISCUSSION The biotic interaction between the mussel and their natural enemies are far from being simple. Although, we refer groups of animal as ―natural enemies‖ based on the negative primary effect of the interaction, it is often evident that the interactions yield multiple effects. In the case of mussels, the predators generally do have negative effects on the population.

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However, multiple predators could result in risk reduction. Siddon and Witman (2004) studied the effect of interaction between urchin, crab, lobster and mussels. They observed no significant risk reduction for urchins occurred in mussel habitats when crabs and lobsters were combined. Lobsters also produced a positive indirect effect on mussels by reducing crab predation. Thus, lobsters modify crab behavior and dampen changes in community structure. The competitors could have both positive and negative effects. When they are competing for food and space, they could result in a negative effect on the mussel population. However, these competitors are often victims of the same predators that prey upon the mussel. Consequently the competitors share the predation pressure and yield a positive effect on the mussel population by being the ―favorite prey‖ for the predator (eg. barnacle-mussel interaction). Shell destroyers are primarily having a negative effect on the population. None the less, often they act as a predator avoidance entity. Parasites have negative effect by affecting different organs of the host; however, they can contribute in predator avoidance. Competitors, shell destroyers and parasites are often epibiotic. Recent studies (e.g. Wahl et al. 1997; Laudien and Wahl 1999; Saier 2001) have demonstrated that epibiosis can substantially affect predation in two different ways. Laudin & Wahl (2004) has observed the effect epibionts on mussel predation by the two common predators, the shore crab Carcinus maenas and the starfish Asterias rubens. Low-preference epibionts such as hydrozoans simply led to avoidance of the basibiont by both consumer species. In contrast, barnacles increased predation by shore crabs (shared doom effect) while they decreased predation by starfish (associational resistance effect). The high trophic connectivity of communities, such as mussels, can produce large numbers of indirect interactions. Although many trait-mediated indirect interactions (TMII) are caused by changes in prey behavior, less is known about the effects of changes in predator behavior such as prey switching or multiple predator effects (MPE) on indirect interactions, especially in marine systems. These changes in the behaviors of the natural enemies could have substantial effect on the population dynamics of mussel community.

REFERENCES Andreu, B., 1963, Propagacion del copépodo parasito Mytilicola intestinalis en el mejillón cultivado de las rias gallegos (N. W. de Espana). Investigación Presquera, 24: 3-20 Belopolskii, L.O., 1961, Ecology of the sea colony birds of the Barents Sea. H. A. Humphrey, London Bertness, M.D., Grosholz, E., 1985, Population dynamics of the ribbed mussel, Geukensia demissa: the costs and benefits of an aggregated distribution. Oecologia, 67: 192–204 Bolster, G.C., 1954, The biology and dispersal of Mytilicola intestinalis Steuver, a copepod parasite of mussels. Fisheries Investigations. Ser. II, 18:1-30 Campbell, S. A., 1970, The occurrence and effects of Mytilicola intestinalisin Mytilus edulis. Marine Biology, 5: 89-95 Casey, M. & Chattopadhyay, D., 2008, Clumping behavior as a strategy against drilling predation: Implications for the fossil record. Journal of Experimental Marine Biology and Ecology, 367: 174–179

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Caspers, H., 1939, Uber Vorkommen und Metamorphose von Mytilicola intestinalis Steuer (Copepoda parasitica) in der südlichen Nordsee. Zoologischer Anzeiger, 126:161-171 Castilla, J.C., 1972, Responses of Asterias rubensto bivalve prey in a Y maze. Marine Biology, 12:222-228 Chattopadhyay, D. & Baumiller, T. K., 2009, An experimental assessment of penetration, excavation and consumption rates of the muricid gastropod, Nucella lamellosa. Journal of Shellfish Research, 28: 1-7 Chattopadhyay, D. & Baumiller, T. K., 2007, Drilling under threat: An experimental assessment of the drilling behavior of Nucella lamellosa in the presence of a predator. Journal of Experimental Marine Biology and Ecology, 352: 257–266 Chew, K. K. & Eisler, R.E., 1958, A preliminary study of the feeding habits of the Japanese oyster drill Ocenebra japonica. Journal of the Fisheries Research Board of Canada, 15: 529-535 Cole, H. A. & Savage, R. E., 1951, The effect of parasitic copepod Mytilicola intestinalis(Steur) upon the condition of mussels. Parasitology,41:156-161 Connell, J. H., 1972, Community interactions on marine rocky intertidal shores. Annual Review of Ecology and Systematics,31: 169-192 Côté, I.M., 1995, Effects of predatory crap effluent on byssus production in mussels. Journal of Experimental Marine Biology and Ecology, 188: 233–241. Côté, I.M., Jelnikar, E., 1999, Predator-induced clumping behaviour in mussels (Mytilus edulis Linnaeus). Journal of Experimental Marine Biology and Ecology, 235: 201–211. Dare, P. J., 1966, The breeding and wintering populations of the oystercatcher (Haematopus ostralegus L.) in the British Isles. Fishery Investigations, Ser. II, 25:1-69 Dare, P. J., 1973, The stock of young mussels in Mrecambe Bay, Lancashire. Ministry of Agriculture Fisheries and Food, Shellfish Information Leaflet, 28:1-14 Dare, P. J., 1975, Settlement, growth and production of mussel Mytilus edulis L. in Morecambe Bay. Fisheries Investigations, London, Ser. II, 28:1–25 Davey, J. T. & Gee, J. M., 1976, The occurrence of Mytilicola intestinalis Steuer, an intestinal copepod parasite of Mytilus, in the south-west of England, Journal of the Marine Biological Association of the United Kingdom, 56:85-94 Dayton, P. K., 1971, Competition, disturbance and community organisation: the provision and subsequent organisation: the provision and subsequent utilisation of space in a rocky intertidal community. Ecological Monographs, 41: 351-389 Doering,P . H. 1982, Reduction of attractivenes to the seastar Asterias forbesi (Desor) by the clam Mercenaria mercenaria(Linnaeus). Journal of Experimental Marine Biology and Ecology, 60: 47-61. Drinnan, R. E., 1958, The winter feeding of the oystercatcher (Haematopus ostralegus L.) on the edible mussel (Mytilus edulis) in the Conway estuary. Fishery Investigations, Ser. II, 22: 1-15 Ebbling, F. J., Kitching, J. A., Muntz, L. & Taylor, C. M., 1964, The ecology of Lough Ine. 13. Experimental observations of the destruction of Mytilus edulisaand Nucella lapillus by crabs. Journal of Animal Ecology,33:73-82 Edwards, E., 1968, A review of mussel production by raft culture. Irish Sea Fisheries Board, Resources Record Paper, 7pp Ellenby, C., 1947, A copepod parasite of the mussel new to the British fauna. Nature,159: 645-646

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INDEX A absorption, 100, 121, 122, 152, 204, 208, 335, 382, 390 absorption spectroscopy, 390 abuse, 282 accessibility, 341 acclimatization, 443 accounting, xvi, 80, 357, 358, 362 accuracy, 304, 332 acetic acid, 399 acetylcholine, 58, 185 acetylcholinesterase, 54, 58, 62, 63, 66, 98, 120, 124, 206, 208 acid, ix, xi, 1, 2, 3, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 23, 25, 27, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 55, 56, 57, 58, 65, 100, 108, 110, 115, 116, 122, 145, 148, 149, 150, 151, 152, 153, 154, 156, 157, 158, 160, 161, 162, 163, 167, 170, 171, 176, 179, 190, 191, 212, 250, 254, 257, 259, 261, 262, 268, 301, 344, 345, 346, 347, 349, 414, 417, 418, 425, 426, 427, 433, 439, 442, 464 activated carbon, 344 active site, 151, 164, 166 active transport, 199 activity level, 287 adaptation, xiii, 85, 121, 206, 207, 222, 237, 239, 245, 246, 248, 250, 256, 257, 260, 266, 269, 334, 494 adaptations, 40, 207, 234, 246, 262 adductor, xviii, 429, 431, 432, 443, 473, 507, 509, 513 adhesion, xii, xix, 145, 146, 147, 149, 150, 152, 153, 154, 157, 160, 163, 166, 167, 169, 170, 171, 431, 436, 439, 441, 450 adhesions, xi, 145, 152 adhesive properties, 148, 163, 167

adhesive strength, 159, 160 adhesives, xii, 145, 147, 150, 162, 168, 169, 171 adjustment, 250, 340 ADP, 368, 370, 371 adrenaline, 150 adsorption, 106, 293, 382 advantages, xv, 104, 130, 337, 338, 339, 346, 472 Aegean Sea, 193 aerobic capacity, 248, 249 AFM, 157 Africa, 76, 198, 286, 470 agglutination, 433 aggregation, xix, 307, 431, 433, 434, 439, 441, 442, 443, 444, 445, 446, 447, 448, 449, 450, 451, 481, 516 agriculture, xx, 49, 80, 82, 200, 224, 286, 292, 296, 495, 496 albumin, 269 alcohols, 2, 175 aldehydes, 176, 255 algae, 41, 93, 170, 202, 204, 209, 215, 390, 474, 478, 479, 511 algorithm, 185 alienation, 83 alkaline hydrolysis, 417 alkenes, 176 alkylation, 253 allele, 223, 231, 233, 457, 458, 459, 461 allergy, 434 alters, 114 aluminium, 152 amines, 157 amino acids, xii, 48, 58, 108, 110, 117, 132, 133, 145, 152, 157, 161, 165, 168, 179, 182, 206, 250, 257, 339, 344 ammonia, 3, 5, 9, 10, 33, 124, 211, 257 amphibia, 134, 141

522

Index

amplitude, 408 amylase, 418 amyotrophic lateral sclerosis, 125 anaphylaxis, 434 anatase, 169 anatomy, ix, x, xvii, xx, 43, 170, 395, 432, 469, 470, 474, 480, 482 anchoring, 84, 359, 361, 362, 364, 365 aneuploidy, 103, 224, 231 animal disease, 201 animal diseases, 201 annealing, 460 ANOVA, 272 anoxia, 98, 111, 123, 127, 192, 211, 248 antagonism, 384 anthropogenic agents, xii, 173 anti-apoptotic role, 99 antibody, 110, 175, 422, 431, 433 antioxidant, xiv, 54, 56, 57, 58, 69, 70, 98, 111, 114, 126, 174, 175, 176, 177, 185, 187, 188, 189, 192, 248, 249, 251, 252, 253, 256, 264, 265, 269, 276, 277, 278, 279, 280, 282, 283, 287 anus, 473 apoptosis, 64, 98, 112, 119, 122, 136, 141, 142, 202 apoptotic mechanisms, 131 appropriations, 82 aquaculture, x, xv, xvi, xviii, 73, 82, 84, 85, 87, 88, 93, 174, 224, 240, 303, 333, 338, 357, 358, 359, 360, 361, 362, 371, 373, 374, 375, 376, 414, 423, 486 aquatic habitats, 174, 248 aquatic systems, 66, 281, 391, 392 arabinoside, 178 archaeological sites, 395, 397 architecture, 119 Argentina, 40, 44, 251, 256 arginine, 149, 157, 437 arithmetic, 403, 404 aromatic compounds, 52, 59, 150, 168, 282 aromatic hydrocarbons, 50, 60, 68, 101, 140, 144, 176, 212, 217, 236, 240, 298, 300 aromatic rings, 291 aromatics, 157, 161, 162 arsenic, xix, 199, 430, 434, 435, 437, 438, 439, 440 arthropods, 151, 451 aryl hydrocarbon receptor, 291 asbestos, 52, 55, 434 Asia, 198, 217, 242, 286, 470 Asian countries, 200, 217, 218 aspartic acid, 344

assets, 74 assimilation, 37, 205, 213, 215, 278, 382, 383, 384, 385, 387 asthma, 434 astrocytes, 144 atmospheric deposition, 276 atomic force, 169 atoms, 152, 199, 295 ATP, 98, 117, 118, 182, 194 attachment, 146, 149, 151, 159, 168, 171, 423, 436, 442, 449, 471, 474, 510 Australasia, 470, 483 Austria, 497 authorities, 139 autoimmune diseases, 111, 117 avoidance, 215, 514 azadirachtin, xix, 434, 436, 438, 439, 441, 442, 443, 446, 447, 448, 449

B bacteria, ix, 1, 3, 35, 37, 38, 39, 142, 180, 209, 325, 418, 423, 426, 431, 474, 478, 479 bacterial infection, 131, 143 bacterium, 424, 427 Balkans, 465 banks, 93, 472 Barents Sea, 393, 514 barriers, xiii, 91, 221, 431, 490 barriers to entry, 91 Beagle Channel, 187 beams, 359 behavioral variation, x, 43, 51 behaviors, 253, 439, 510, 514 Belgium, 301, 381 benzene, 290, 434 benzo(a)pyrene, 69, 136, 142, 178, 181, 203, 204, 284, 293, 294, 297, 300, 362 benzophenone, 183 beryllium, 434 beverages, 338, 339 bile, 193, 282 bioaccumulation, xiii, 101, 119, 130, 187, 190, 191, 198, 199, 200, 201, 202, 203, 204, 205, 206, 208, 212, 215, 216, 217, 222, 258, 262, 263, 264, 276, 277, 284, 287, 288, 383, 391, 392, 393, 442, 500 bioavailability, xvi, 50, 103, 186, 202, 209, 211, 212, 215, 218, 243, 254, 281, 288, 289, 298, 379, 380, 382, 383, 384, 385, 386, 387, 388, 389, 391, 392, 393, 499

Index biochemistry, xiii, 123, 187, 188, 191, 206, 245 biodegradability, 159 biodegradation, 199 biodiversity, xvi, xix, 60, 138, 237, 255, 379, 432, 442 biogeography, 261, 465 bioindicators, x, xiii, 43, 56, 61, 97, 98, 211, 245, 280, 380, 385 biological consequences, 386 biological control, 511 biological processes, 289 biological responses, 51, 137 biological systems, 334 biologically active compounds, 255 biomass, 304, 316, 317, 318, 320, 321, 326, 327, 329, 334, 373, 388 biomaterials, xii, 145, 151, 160, 161, 162, 168 biomonitoring, xiii, xvii, xxi, 51, 52, 56, 57, 59, 60, 63, 68, 71, 72, 103, 104, 125, 130, 139, 186, 196, 222, 235, 238, 239, 246, 247, 251, 253, 257, 261, 281, 282, 380, 385, 386, 387, 389, 390, 391, 392, 495, 496, 498, 499, 500 biosensors, 159 biosphere, 389 biosynthesis, 41, 98, 130, 253, 254 biotechnology, ix, xii, 145, 160 biotic factor, 48, 174, 383, 505 birds, xxi, 381, 385, 503, 505, 514, 517 birth control, 201 birth rate, 227 bisphenol, 131, 183 Black Sea, 68, 253, 260, 280, 289, 454, 455, 457, 461, 462, 464, 468 bleaching, 433 bleeding, 443, 444 blood clot, 449 body fat, 291, 292 body fluid, xix, 51, 441 body size, 213, 215, 384, 389, 481 body weight, x, 43, 48, 63, 204, 316, 319, 320, 384, 390 bonds, 154, 341, 342 bone, 281, 430 boreholes, xxi, 503, 512 boundary conditions, 306, 326, 330 bradykinin, 451 brain, 112, 252 Brazil, 177, 188, 337, 392 breakdown, 175, 382, 449 breast cancer, 111, 182, 193, 194, 299 breathing, 292

523

breeding, 228, 479, 480, 482, 513, 515 bridges, 349 Britain, 513 brominated flame retardants, 215 budding, 82 Bulgaria, 245 by-products, 175, 287, 354

C cadmium, 51, 55, 61, 63, 66, 69, 71, 111, 112, 119, 121, 125, 141, 143, 177, 179, 180, 183, 189, 191, 192, 199, 209, 213, 218, 238, 268, 279, 390, 391, 438, 440 calcium, 45, 154, 291, 399, 406, 407, 430, 432, 474 calcium carbonate, 45, 399, 406, 407, 432, 474 calibration, 6 canals, 44, 184, 432, 454, 455, 456, 482 cancer, 108, 111, 126, 182, 193 capillary, 6, 268 capital goods, xvi, 357, 361, 365, 368, 369, 370, 371, 374, 375 capitalism, 80 carbohydrate, 177, 447, 450 carbohydrates, 48, 55, 206, 346 carbon, xiv, xix, 2, 40, 77, 157, 158, 165, 204, 205, 264, 265, 268, 270, 272, 273, 276, 277, 278, 281, 283, 288, 290, 292, 307, 316, 319, 320, 327, 329, 344, 383, 384, 388, 393, 429 carbon atoms, 2, 158 carbon dioxide, xix, 429 carbonyl groups, 142 carcinogen, 59, 192 carcinogenesis, 66, 121, 123, 189 carcinogenicity, 189, 294 carcinoma, 111, 119, 120 cardiac activity, 247 cardiac arrest, 449 caries, 512 carotenoids, 56 carp, 239, 508 carrier agents, xv, 337, 347, 349, 353 cartel, 91 case study, 218, 219, 362, 365, 371, 376, 377 casein, 120, 123 Caspian Sea, xx, 453, 454, 455, 457, 461, 462, 463, 464 castration, 287, 512 catabolism, 72 catalysis, 124

524

Index

catalytic activity, 111 catastrophes, 212 catfish, 472 cation, 58, 72, 124, 191, 393, 449 causation, 494 cDNA, 110, 127, 132, 195 cell culture, 141, 159, 189 cell cycle, 63, 112, 114, 117, 122, 123 cell death, 237 cell line, 182, 486 cell lines, 182, 486 cell membranes, xiii, 245, 246 cell signaling, 130, 131, 139, 140, 216 cellular homeostasis, 48, 278 cellulose, 106 cercaria, 517 chaperones, 99, 111, 118 chelates, 154 chemical properties, 64, 201 chemical reactions, 339 chemical stability, 347 chemisorption, xi, 145 chemotaxis, 436 chemotherapeutic agent, 182 chicken, 342, 346, 347, 375 Chile, 44, 91, 358, 424 China, 40, 44, 88, 91, 196, 200, 213, 225, 226, 241, 358, 376 chlorination, xviii, 414 chlorine, 290, 292, 295 chloroform, 5, 455 chlorophyll, ix, 2, 5, 9, 33, 36, 37, 39, 306, 307, 312, 313, 418, 423 cholesterol, 184, 250, 252 cholinesterase, 67, 71 chromatid, 491 chromatography, 167, 268, 344, 349, 350, 425 chromium, 240, 382 chromosome, 486, 488, 489, 490, 491, 492, 494 chronic diseases, 286 chronology, xvii, 161, 395, 402, 403, 405, 407, 408 ciguatera, xvii, 413 ciguatera fish poisoning, xvii, 413 cilia, 46, 474, 479 circulation, xv, 49, 76, 77, 285, 384 City, 1, 251, 300 class, xxi, 58, 175, 179, 194, 200, 201, 251, 288, 290, 503, 510 cleaning, 201, 335 cleavage, 149, 342

climate, xvi, 55, 75, 198, 207, 210, 211, 259, 379, 399, 401, 406, 407, 408, 409, 410 climate change, xvi, 210, 211, 379 cloning, 122, 127, 182 closure, 247, 257, 261, 421, 451 cluster analysis, xiii, 17, 18, 32, 221, 236 clustering, 227, 229, 230 clusters, 228, 234 CO2, 368 coal, 253, 294 coal tar, 294 coatings, 165 cobalt, 253, 261 coding, 181, 184, 486 codominant, 223, 498 codon, 113 coenzyme, 187 collagen, 146, 147, 165, 168 colon, 111 colonization, 88, 442 color, iv, 45, 150 combined effect, 334 combustion, 199, 200, 293, 370 combustion processes, 199 community, 2, 38, 40, 41, 74, 81, 174, 206, 209, 237, 380, 386, 388, 480, 504, 508, 514, 515, 518 compensation, 248, 262 competition, ix, xv, 48, 85, 86, 87, 91, 92, 93, 246, 303, 304, 305, 316, 317, 320, 322, 326, 327, 331, 332, 341, 384, 504, 505, 510, 511, 517, 519 competitors, xxi, 151, 503, 510, 511, 514, 518 compilation, 359 complement, xii, 173, 431, 488 complementary DNA, 66 complexity, xii, 61, 197, 198, 201, 205, 209, 210, 387, 486, 518 composites, 382 composition, ix, xiii, xiv, 1, 35, 36, 38, 39, 40, 104, 108, 111, 114, 153, 160, 206, 222, 245, 246, 249, 254, 255, 256, 258, 260, 261, 262, 264, 266, 268, 276, 277, 279, 281, 298, 299, 333, 335, 344, 345, 346, 388, 409, 465, 471, 494 compounds, xiii, 51, 52, 55, 56, 57, 58, 59, 60, 65, 66, 98, 136, 141, 151, 162, 164, 166, 169, 175, 178, 181, 182, 183, 193, 195, 199, 200, 201, 204, 208, 214, 218, 219, 245, 267, 269, 270, 273, 276, 277, 278, 280, 287, 288, 289, 290, 292, 293, 294, 295, 297, 298,鿘339, 341, 344, 349, 381, 382, 384, 421, 422, 426, 433, 434 comprehension, xiv, 263

Index conceptual model, 374 condensation, 147, 347, 486 conditioning, 466 conduction, 201 conductivity, 306, 497 conference, 392 configuration, 290 conflict, 91, 92 conjugation, 166, 175 connectivity, 514 consensus, xvi, 148, 170, 357, 372, 463, 470 conservation, xi, xx, 98, 129, 131, 144, 276, 388, 390, 397, 409, 469, 472, 473 constant rate, 327 Constitution, 82 consumption, xiv, xv, xvi, xxi, 44, 89, 90, 92, 205, 245, 253, 285, 290, 292, 298, 303, 304, 305, 307, 308, 313, 320, 321, 329, 331, 332, 344, 357, 358, 361, 362, 364, 370, 373, 374, 424, 430, 503, 508, 515, 518 consumption rates, xv, 303, 304, 305, 308, 313, 329, 331, 332, 515 contaminant, 55, 66, 68, 69, 71, 176, 181, 185, 211, 213, 218, 219, 232, 234, 235, 265, 268, 269, 277, 283, 288, 289, 386, 388, 435, 436 contamination, xi, xiii, xiv, xvi, xviii, xix, 50, 59, 63, 70, 71, 122, 129, 130, 133, 139, 140, 141, 178, 180, 187, 192, 193, 195, 198, 209, 211, 217, 218, 221, 222, 232, 236, 242, 243, 253, 259, 264, 265, 277, 279, 280, 287, 288, 292, 293, 294, 296, 297, 298, 300, 379, 380, 385, 386, 387, 388, 389, 391, 392, 414, 415, 417, 419, 421, 430, 441 contradiction, 418, 433 control condition, 59, 248 convention, 174 cooking, 89, 91, 201, 339, 344 cooling, 5, 345, 349, 462 coordination, 151 copolymers, 160, 167 copper, 51, 55, 61, 62, 66, 69, 72, 122, 143, 150, 151, 154, 164, 165, 166, 169, 175, 177, 179, 180, 183, 185, 189, 192, 196, 199, 238, 240, 390 Coriolis effect, 76, 77 correlation, xiv, 6, 33, 34, 35, 36, 38, 102, 103, 111, 131, 139, 235, 264, 269, 273, 275, 278, 288, 401, 402, 403, 405, 407, 410, 497 correlation analysis, 6, 103, 235 correlation coefficient, 38, 102, 269, 403, 405 correlations, xiv, 104, 125, 235, 254, 264, 269, 276, 277, 278, 279, 403, 405, 406, 411

525

corrosion, 160, 165, 400 cosmetics, 201 cost, 50, 56, 82, 92, 104, 185, 198, 339 cotton, 360, 361, 364, 370 Council of Ministers, 200 covalent bond, 154, 157 covering, 174, 182, 198, 200, 204, 208, 210, 286 critical value, 349 critics, 92 Croatia, 129, 133, 137, 140, 261, 495, 497, 499 cross-linking reaction, xi, 145, 147, 152, 161 crude oil, 190 crystal structure, 119, 126 crystalline, 382 crystals, 45, 474 cues, 431, 509, 517 cultivation, 79, 80, 81, 82, 83, 84, 85, 88, 89, 90, 113, 228, 304, 359, 360, 364, 370, 376 culture, ix, x, xvi, 73, 74, 80, 93, 94, 98, 159, 239, 332, 333, 340, 357, 358, 359, 360, 362, 363, 364, 365, 367, 368, 369, 370, 373, 374, 375, 390, 420, 481, 491, 492, 515 curing process, xi, xii, 145, 146 cuticle, 148, 153, 157, 166, 169 cyanide, 150, 151 cycles, 36, 38, 49, 153, 154, 177, 210, 392, 459 cycling, 126, 213, 376 cyclooxygenase, 203 cyst, 424 cysteine-rich protein, 101, 179, 252 cystine, 169 cytochrome, xx, 50, 56, 181, 182, 192, 193, 207, 249, 269, 282, 453, 454 cytogenics, ix cytometry, 140, 494 cytoplasm, 108, 114, 117, 135, 435, 438 cytosine, 178 cytoskeleton, 112 cytotoxic agents, 437 cytotoxicity, 189, 434

D damages, iv, 178 danger, 78 Danube River, 254, 461 data analysis, 409 database, 122, 366, 457, 461 datasets, 405 decay, xviii, 45, 246, 414, 417, 421

526

Index

decentralisation, 82 decomposition, 269, 310, 314, 325, 329 defecation, 288 defects, 339 defence, xix, 54, 55, 56, 58, 111, 140, 187, 188, 189, 194, 276, 277, 279, 301, 430, 431, 432, 433, 437, 451 defense mechanisms, 103 deficiencies, 230, 238 deficiency, 47, 224, 243 deficit, 231 degradation, xiii, 49, 53, 55, 66, 68, 72, 124, 141, 176, 204, 245, 246, 265, 268, 295, 300, 339, 349, 418, 422, 423, 437, 472 degradation process, xiii, 245, 246 degradation rate, 72 dehydration, 340 democracy, 82 demographic data, 478 demographic structure, 388 denaturation, 60 Denmark, 44, 225, 358, 376, 377, 392, 507 Department of Commerce, 268 deposition, 293, 347, 388 deposits, 75, 382, 397 depression, 126, 247, 248 derivatives, 57, 169, 176, 183, 190, 200, 208, 347, 415, 417, 426 desiccation, 45, 246, 474, 511 desorption, 154 destination, 89 destruction, 117, 437, 438, 505, 512, 515 detachment, 47, 449 detection, 51, 71, 120, 125, 139, 140, 167, 169, 190, 202, 212, 219, 256, 269, 270, 271, 276, 279, 289, 350, 362, 385, 387, 399, 421, 425, 426, 463, 489, 499 detection system, 139 detergents, 58, 434, 438 detoxification, xviii, 50, 58, 59, 119, 179, 181, 191, 192, 212, 252, 255, 265, 278, 279, 287, 382, 386, 391, 414, 417, 420, 422, 425 developing countries, 49, 242 deviation, xiii, 76, 222, 246, 250, 364 dibenzo-p-dioxins, 299, 301 diesel fuel, xi, 129 diet, 36, 186, 205, 257, 286, 293, 430, 517 dietary intake, 293 diffusion, 199, 289

digestion, xxi, 2, 46, 53, 207, 213, 333, 340, 382, 436, 503 dihydroxyphenylalanine, 155, 156, 166, 169, 170, 171 dimerization, 123 dioxin, 290, 291, 292, 299 dioxin-like PCBs, 291, 292 dioxins, xiv, 49, 199, 236, 264, 267, 269, 270, 291, 292, 299, 300 dipeptides, 157, 160, 161, 162 diploid, 486 direct measure, xiii, 263, 264 disadvantages, 159 disaster, 513 discharges, 49, 201, 286, 497 discrimination, 151, 210 displacement, 358 dissociation, 98, 162 dissolved oxygen, 3, 7, 33, 38, 247, 256, 283, 304, 306, 307, 310, 311, 312, 313, 314, 319, 326, 327, 330, 381, 383 distillation, 293 distilled water, 5, 340 disturbances, 254, 386, 403, 419 divergence, 227, 238, 242, 493, 494 diversity, xx, xxi, 143, 170, 192, 201, 204, 210, 233, 234, 240, 241, 346, 431, 432, 453, 472, 481, 495, 496, 497, 498, 518 DNA, x, xiii, xx, 41, 47, 52, 54, 60, 61, 63, 64, 65, 69, 70, 71, 72, 97, 123, 130, 142, 144, 174, 177, 178, 181, 188, 189, 190, 193, 199, 203, 206, 210, 211, 212, 213, 221, 222, 223, 224, 225, 226, 227, 229, 230, 231, 232, 235, 236, 237, 239, 240, 241, 242, 251, 253, 255, 256, 287, 293, 454, 455, 458, 459, 460, 467, 485, 486, 492, 494, 496, 500 DNA damage, 52, 54, 60, 61, 63, 64, 71, 144, 177, 178, 189, 190, 203, 210, 251, 253, 255, 500 DNA lesions, 178, 189 DNA repair, 64, 178, 189, 287 DNA sequencing, 454 DNA strand breaks, 178, 190, 193, 211, 251 docosahexaenoic acid, 2 dominance, 2 dopamine, 150, 206, 214 double bonds, 176 down-regulation, 111 draft, 86 drainage, xx, 159, 202, 469, 472 drinking water, 290 Drosophila, 116

Index drug carriers, 160 drug delivery, 201 drugs, 55, 160, 180, 217, 218 drying, xv, 267, 293, 294, 337, 338, 345, 346, 347, 349, 353

E early warning, 52, 174, 185, 186, 205, 206, 208, 287, 496, 500 East Asia, 340 Eastern Europe, 456 ecology, 62, 144, 187, 190, 213, 222, 281, 282, 381, 389, 390, 392, 466, 467, 480, 481, 482, 491, 492, 508, 515, 516, 519 economic consequences, 454 economic efficiency, 81 economic performance, 74, 94 economic policy, 86 economic problem, 505 economy, 53, 74, 358 ecosystem, xix, 40, 49, 60, 75, 120, 139, 142, 174, 192, 198, 206, 207, 210, 215, 216, 246, 261, 265, 280, 304, 358, 388, 394, 432, 434, 439, 441, 442, 496 ecotoxicological genetics, xiii, 222, 233, 237, 238 editors, 281 effluent, 3, 165, 184, 194, 195, 209, 210, 217, 218, 236, 515 effluents, 100, 184, 185, 201, 206, 208, 210, 213, 214, 218, 236, 280 EGF, 148 egg, 169, 184, 207, 262, 289, 292, 298, 300 Egypt, 39 eicosapentaenoic acid, 2 eigenvalues, 273 elaboration, 94 elastin, 146 election, 266 electricity, 369, 370 electrodes, 169 electromagnetic, 131 electromagnetic field, 131 electron, 121, 151, 152, 154, 155, 175, 201, 207, 208, 210, 249, 268 electron microscopy, 121 electron paramagnetic resonance, 154 electrons, 252 electrophoresis, 71, 178, 190, 228, 232, 234, 460 ELISA, xi, 129, 133, 134, 135, 136, 138, 139, 422, 425

527

elongation, xi, 97, 98, 105, 106, 107, 111, 114, 124 elucidation, 424 embryogenesis, 47 emigration, 511 emission, 368 employment, 104 emulsions, 346 encapsulation, 345, 346, 430, 431, 434, 449, 511 encoding, xi, xx, 129, 131, 132, 133, 195, 453, 454, 455 endangered species, 397 endocrine, 183, 184, 195, 201, 207, 213, 222, 240, 293, 300 endocrine system, 183, 195, 201 endocrinology, 213 endonuclease, 457, 458, 461, 493 enemies, xxi, 503, 504, 505, 513, 518 energy consumption, 370 energy efficiency, 370 energy transfer, 388 enforcement, 74, 81 engineering, 166, 170 England, 281, 492, 507, 515, 519, 520 enlargement, 80, 259 environmental change, xii, xvi, 48, 173, 222, 262, 379, 391, 408, 410 environmental characteristics, 205 environmental conditions, xiii, xxi, 47, 50, 108, 182, 203, 245, 246, 249, 266, 288, 329, 381, 388, 423, 455, 465, 495, 496 environmental contamination, xi, xx, 66, 97, 287, 495, 496, 498, 499 environmental degradation, xx, 469 environmental effects, 238, 253, 333 environmental factors, x, xvii, 3, 41, 43, 47, 48, 130, 137, 139, 177, 250, 251, 282, 289, 290, 296, 298, 395 environmental impact, ix, x, xvi, 43, 50, 56, 67, 206, 217, 245, 281, 357, 359, 360, 368, 369, 370, 373, 374, 375, 377 environmental influences, 386 environmental protection, 279 Environmental Protection Agency (EPA), 2, 65, 200, 205, 214, 391, 499 environmental quality, 174, 186, 200, 202, 203, 251 environmental risks, 144 enzymatic activity, 50, 176 enzyme immobilization, 169 enzyme induction, 290

528

Index

enzymes, xii, 47, 53, 54, 56, 57, 58, 60, 61, 69, 70, 98, 102, 115, 119, 126, 131, 133, 146, 149, 151, 159, 160, 162, 168, 174, 175, 176, 180, 181, 185, 187, 188, 192, 193, 206, 213, 228, 234, 248, 249, 251, 252, 253, 256, 257, 266, 278, 283, 290, 293, 340, 341, 344, 387, 437, 438, 450, 488 epithelium, 46, 513 equality, 85 equilibrium, 49, 88, 203, 205, 206, 433 equipment, 93, 290, 339, 361, 363, 367, 368 erosion, 242, 472 erythrocytes, 62 esophagus, 46 ester, 161, 212, 418 estrogen, 183, 184, 195, 291, 293, 301 etching, 398 ethanol, 443, 455 ethers, 258 ethology, 431 ethylene, 160, 442 ethylene glycol, 160 eucalyptus, 88 euchromatin, 486, 488 Eurasia, 466, 470 European Commission, xviii, 413, 424 European Community, 174 European Parliament, 292, 299 European Union (EU), xviii, 174, 200, 294, 299, 377, 414, 424 evolutionary principles, 262 examinations, 294 excision, 60, 71 exclusion, 83, 443 excretion, 203, 205, 250, 257, 289, 295 exocytosis, 437 exoskeleton, 406 expenditures, 209 experiences, 80, 449 experimental condition, 139, 234, 437, 506 experimental design, 340 expertise, 104, 389 exploitation, xviii, 83, 84, 253, 414 exploration, xi, 98 exporter, 90 exports, 90 expressed sequence tag, 142 external environment, 381, 384, 385 extinction, xxi, 397, 496, 500, 503, 510 extraction, 5, 39, 79, 81, 83, 90, 122, 159, 267, 289, 339, 344, 455

extrusion, 345 exudate, 346

F fabrication, 164, 169 factor analysis, 240 fairness, 85, 87 false positive, 421, 422 family members, 122, 182 farmers, 85, 88, 91, 92, 360, 365 farming techniques, 81 farms, x, 73, 74, 79, 80, 82, 83, 84, 85, 88, 91, 281 fat, 292, 295 fat soluble, 292 fatty acids, x, 2, 6, 32, 34, 35, 36, 37, 39, 41, 180, 249, 257, 258, 260, 415, 417, 426 fauna, xvi, 250, 379, 388, 464, 466, 467, 483, 515, 518 feces, xiv, 285, 304, 317, 320 fermentation, 339, 340 ferritin, 382 fertility, 489 fertilization, 47, 231, 253, 289 fertilizers, 200, 472 fiber, 349 fibers, 146, 165 filament, 46 film thickness, 6 films, 164 filters, 106, 130, 320 filtration, x, xviii, xxi, 5, 38, 50, 97, 199, 202, 203, 234, 319, 327, 334, 381, 388, 429, 440, 503, 513 financial support, 353, 374 fingerprints, 204 Finland, 359, 395, 396, 397, 407, 409, 411, 454, 461, 467, 468 fish, xv, xxi, 3, 59, 60, 61, 62, 65, 66, 67, 69, 71, 84, 90, 93, 138, 181, 195, 201, 216, 218, 227, 233, 237, 256, 257, 278, 280, 281, 282, 283, 284, 286, 290, 291, 292, 293, 294, 296, 300, 304, 337, 338, 339, 340, 343, 344, 346, 347, 359, 376, 377, 381, 385,鿘387, 388, 426, 427, 442, 467, 471, 472, 473, 481, 483, 503, 508 fish oil, 292 fisheries, 85, 86, 87, 95, 283, 338, 354, 357, 358, 359, 373, 375, 376 fishing, 80, 81, 82, 83, 85, 95, 359, 360, 376 fission, 121 fitness, 233, 234, 237, 240, 490, 496

Index flame, 200 flame retardants, 200 flavor, xv, 337, 338, 339, 340, 344, 345, 346, 349, 350, 353 flexibility, 153 flight, 154 flooding, 75 flora, xvi, xix, 287, 379, 418, 430 flora and fauna, xix, 287, 430 flotation, 359 fluctuations, 102, 130, 180, 246, 250, 381 fluid, 250, 431, 473 fluorescence, 178, 212, 268, 282, 362, 419, 426 fluoxetine, 253 follicles, 47 food particles, 46, 381, 473 food products, 350 food safety, xvii, 413 Ford, 238, 455, 466, 499 forecasting, 407 formula, 82, 90, 400, 444 fouling, 160, 289, 306, 332 foundations, 75, 88, 94 founder effect, 464 fragments, 60, 178, 396, 402 France, xvi, 40, 44, 70, 88, 93, 129, 210, 214, 261, 266, 281, 282, 283, 333, 358, 375, 376, 379, 381, 425, 491 free radicals, 71, 107, 174, 188, 252 freedom, 93 freezing, 89, 111, 127, 203, 381 frequencies, 223, 231, 236, 239, 462, 463, 465, 496 frequency distribution, 314, 315, 463, 465 friction, 76 functional changes, 51, 386 fungi, ix, 1, 35, 37, 38, 39, 40, 180 furan, 291, 292 fusion, 159, 252, 437

G gamete, 237 gametogenesis, 47, 48, 184, 203, 207, 214, 215, 289 gel, 60, 71, 115, 167, 178, 190, 228, 232, 234, 344, 460, 461 gel formation, 167 gene expression, 47, 58, 64, 119, 193, 195, 214, 236 gene pool, 496

529

genes, 59, 64, 113, 115, 123, 131, 132, 133, 144, 166, 167, 181, 182, 183, 192, 223, 236, 248, 255, 291, 300, 491, 492, 496 genetic alteration, 103 genetic diversity, xx, 233, 234, 236, 237, 238, 242, 472, 495, 496, 497, 498, 500 genetic drift, 496 genetic information, 224, 228 genetic marker, 235 genetic traits, 210 genetics, xii, 221, 222, 232, 233, 237, 238, 239, 241, 242, 332, 390, 466, 486, 492, 494, 495 genome, 67, 113, 143, 486, 490 genotoxicology, 71, 242 genotype, 223, 233, 240, 242 geography, xx, 453 germ cells, 496 Germany, 129, 145, 444, 495 Gibraltar, 286 gill, xiv, xviii, 46, 53, 60, 64, 67, 71, 72, 100, 103, 124, 125, 132, 176, 178, 188, 189, 190, 249, 253, 258, 264, 270, 273, 382, 429, 450, 479, 482, 512 gland, xiv, 40, 46, 53, 54, 55, 56, 58, 60, 64, 69, 70, 72, 100, 101, 104, 105, 106, 122, 131, 140, 148, 150, 166, 177, 178, 181, 187, 188, 189, 190, 192, 193, 203, 210, 247, 261, 264, 268, 270, 272, 273, 275, 276, 277, 278, 279, 280, 418, 426, 434 glass transition, xvi, 338, 347, 348, 349, 353 glass transition temperature, xvi, 338, 347, 348, 349, 353 globalization, 239 glochidium, 47, 470, 471 glucose, 48, 159, 347 glucose oxidase, 159 glue, ix, xi, 145, 150, 166, 170 glutamate, 344 glutamic acid, 344 glutathione, xiv, 56, 57, 64, 175, 187, 188, 194, 251, 264, 266, 268, 272, 281, 282, 299, 389 glycerol, 114 glycine, 149, 161, 344 glycogen, 247, 304 gonads, 6, 18, 31, 32, 33, 35, 36, 37, 39, 46, 181, 184, 210, 214, 385, 517 governance, 75, 94 gracilis, 509 grading, 365 graduate students, 332 granules, 55, 58, 175, 382, 435 grass, 233, 240, 472

Index

530

grazing, 39, 373, 508 Great Britain, 485 Great Lakes, 67, 213, 241, 454, 466, 468, 480 Greece, 43, 71, 97, 99, 117, 120, 122, 189, 200, 219, 261, 280 grounding, 398 groundwater, 434 growth dynamics, 383, 401 growth factor, 131, 149, 166 growth mechanism, 79 growth rate, 3, 47, 48, 108, 114, 227, 247, 248, 249, 289, 327, 329, 338, 381, 404, 410, 509 growth rings, 410 guanine, 487 guidelines, 179, 190, 199, 226, 368, 375 Gulf of Mexico, 226, 238, 454 gum Arabic, 346, 347, 348, 349, 350, 352, 353

H habitats, ix, xii, xiv, xxi, 44, 47, 173, 246, 256, 258, 285, 288, 304, 332, 376, 381, 396, 399, 437, 470, 495, 498, 514 hair, 246 half-life, 51, 57, 186, 204 haploid, 486 haplotypes, xx, 453, 454, 455, 460, 461, 463, 464, 465 hardness, 154, 383 harmful effects, 382 harvesting, xvii, 84, 413, 415, 423, 424 hazardous substances, 69, 496 hazards, 508 haze, 346 HDPE, 361, 364, 367 health effects, 198, 293, 300 health problems, 205 health status, x, 43, 52, 53, 54, 61, 68, 206, 209, 211, 215, 247, 260, 261 heart rate, 207 heat loss, 347 heat shock protein, 130, 248 heavy metals, x, 47, 49, 52, 58, 59, 63, 97, 98, 99, 101, 106, 107, 111, 120, 131, 142, 178, 179, 180, 183, 189, 192, 203, 208, 211, 214, 222, 225, 228, 233, 235, 240, 243, 252, 280, 284, 286, 384, 390, 391, 393, 472, 499 height, 77, 509 helium, 6 heme, 151, 175, 180

hemisphere, 44, 76, 210 hemp, 377 hepatocellular carcinoma, 111, 119 hepatoma, 136 herbicide, 178 heterochromatin, 486, 488, 493 heterogeneity, 210, 234, 388, 488 heterosis, 497 heterozygote, 231, 243, 498 hexachlorobenzene, 281 hexachlorobiphenyl, 193 hexane, 282 high density lipoprotein, 418 high density polyethylene, 361 histidine, 147, 154, 157, 171 histochemistry, 482 histone, 489, 491 homeostasis, xix, 48, 49, 53, 57, 58, 59, 65, 72, 174, 179, 191, 248, 252, 393, 434, 441, 446, 449, 496 Hong Kong, ix, xvi, 1, 3, 39, 40, 41, 175, 187, 256, 280, 379 host, 144, 392, 431, 437, 449, 471, 472, 473, 512, 513, 514, 517 hot spots, 286, 374 human exposure, 292 human welfare, 439 humoral immunity, 433 Hungary, 497 hunting, 504, 505 hybrid, 83, 126, 160, 166, 167, 168, 242, 490, 491, 494 hybridization, 492 hydrocarbons, 41, 176, 179, 188, 190, 200, 286, 299, 349, 423 hydrogen, xi, 49, 56, 129, 134, 149, 151, 153, 175, 178, 180, 189, 192, 292 hydrogen bonds, 149, 153 hydrogen peroxide, xi, 56, 129, 134, 151, 175, 178, 180, 189, 192 hydrolases, 58, 124 hydrolysis, xi, xv, 98, 113, 182, 337, 338, 339, 340, 341, 342, 343, 344, 347, 353 hydrolysis kinetics, 341 hydroperoxides, 175 hydrophobic properties, 203, 254 hydrophobicity, 204, 290 hydroquinone, 161, 167 hydrothermal activity, 281 hydroxide, 433, 439 hydroxyapatite, 153, 164

Index hydroxyl, 70, 125, 252, 384 hypersensitivity, 434 hypothesis, 104, 134, 135, 136, 233, 242, 249, 418, 423, 463, 464 hypoxia, 3, 41, 98, 104, 131, 247

I Iceland, 391 ideal, 75, 200, 202, 264, 287, 477, 497 illumination, 443 image, 66, 444, 445, 446 image analysis, 66 images, 435 imbalances, 92 immersion, 266, 519 immobilization, xii, 145, 178 immune function, 140, 430, 434 immune reaction, 431, 449 immune response, 207, 430, 432, 433, 436, 440, 442 immune system, 141, 207, 211, 291, 431, 434 immunity, xix, 386, 427, 430, 431, 432, 433, 439, 450 immunocompetent cells, 433 immunogenicity, 159 immunosuppression, 434 impact assessment, xii, 197, 359, 368, 376, 377 Impact Assessment, vi, 197, 285 impacts, x, 43, 49, 61, 178, 185, 207, 209, 210, 218, 287, 303, 304, 333, 358, 359, 369, 375, 377, 383, 472, 496, 499, 501, 519 imports, 90 in situ hybridization, 192 in vivo, xviii, 108, 113, 114, 124, 159, 174, 178, 185, 190, 279, 293, 414 inbreeding, 224, 228, 231, 496 inbreeding coefficient, 224 incidence, 434, 519 incompatibility, 238 incomplete combustion, 253 independence, 249 independent variable, 340 indexing, 399 India, vi, xviii, xix, 226, 227, 429, 430, 431, 432, 434, 436, 439, 441, 442, 443, 444, 450, 470, 503 indirect effect, 514, 519, 520 indirect measure, 224 inducer, 163 inducible protein, 184, 287

531

induction, xi, 55, 56, 59, 61, 62, 65, 66, 114, 129, 130, 144, 177, 178, 179, 180, 181, 183, 189, 191, 192, 193, 195, 206, 207, 208 industrial chemicals, 434 industrial processing, xvii, 362, 413 industrialisation, 90 industrialization, 295 inertia, 401 infancy, 211 infestations, 513, 516 inflammation, 101, 142, 202, 252 infrared spectroscopy, 152 infrastructure, 81 ingestion, xv, 199, 205, 289, 303, 304, 317, 319, 320, 325, 387, 417 inheritance, 498 inhibition, 65, 70, 98, 108, 114, 124, 165, 171, 208, 246, 341, 435, 436, 437, 438, 439, 449, 450 inhibitor, 111, 114, 115, 134, 136, 165, 423 initiation, xi, 97, 98, 105, 106, 113, 114, 122, 124, 125, 203, 393, 433 innate immunity, 142, 431, 432, 440, 450 inoculation, 65 insecticide, 292 insects, 292 insertion, 146 instant noodles, xv, 337 institutional change, 81 institutional economics, 94 insulation, 347 integration, 91, 186, 205, 256 interdiction, xvii, 413 interface, 112, 117, 153, 169, 173, 333, 346, 512 interference, 278, 423, 442, 447, 448, 449 intermediaries, 278 internal environment, 431 internal growth, 398, 399, 411 internalised, 56 interphase, 488, 489, 491 interrelations, 240 intestine, 513 introns, 143 invertebrates, xi, xiii, xiv, 35, 40, 47, 60, 61, 64, 65, 66, 71, 72, 98, 99, 119, 129, 130, 141, 142, 145, 170, 175, 178, 179, 181, 183, 186, 191, 192, 194, 198, 201, 205, 212, 213, 217, 222, 234, 237, 239, 240, 253, 255, 256, 257, 259, 260, 261, 262, 285, 290, 296, 300, 381, 382, 384, 385, 387, 388, 390, 393, 433, 439, 449, 481, 483, 500 ion transport, 252

Index

532

ionization, 154, 162 ions, 52, 55, 126, 152, 153, 154, 160, 178, 182, 253, 261, 382, 383, 384, 392, 450 Ireland, 467, 485, 508 iron, xvi, 55, 122, 150, 152, 153, 154, 155, 160, 164, 170, 171, 175, 177, 180, 357, 362, 368, 369, 370, 374, 382 iron transport, 164 Islam, 265, 276, 281, 283 isolation, 119, 159, 168, 225, 227, 465, 480, 489, 494, 509 isomers, xiv, 136, 263, 267, 432 isotope, 40, 200, 265, 266, 268, 276, 278, 280, 281, 282, 283, 284 isozymes, 241, 248 Italy, vi, 63, 68, 69, 92, 93, 193, 195, 208, 213, 225, 282, 285, 286, 300, 354, 358, 381, 467, 516

J Japan, xv, 44, 225, 303, 304, 305, 332, 334, 380, 427 Japan, Sea of, 427 Jordan, vi, 245 judiciary, 81 justification, 93 juveniles, 3, 184, 253, 479, 482

K karyotype, 488, 489 karyotyping, 489 kidney, 144, 290, 383 kinase activity, 144 kinetics, 204, 205, 212, 213, 215, 264, 341, 424 Korea, 44

L labeling, 175 lactate dehydrogenase, 41, 256, 257 lakes, 44, 208, 209, 392, 432, 455, 463, 464, 468 larva, 47, 289 latency, 124 leaching, 201 lead pollution, 143 leakage, 438 learning, 82, 506 learning process, 506 legality, 86

legislation, xviii, 84, 85, 413, 421 leisure, 201 lesions, 66 leucine, 344 liberalisation, 84 life cycle, ix, 231, 359, 361, 362, 365, 374, 375, 376, 377, 381, 383, 392, 471, 472 ligament, 45, 397, 473, 474 ligand, 183 linear function, 317 linearity, 405 Lion, 486 lipid metabolism, 57 lipid oxidation, xv, 337, 339, 343 lipid peroxidation, 55, 56, 65, 72, 175, 176, 177, 187, 188, 189, 210, 251, 252, 255, 269, 273, 278 lipids, 2, 5, 40, 41, 48, 55, 56, 107, 174, 182, 203, 206, 209, 210, 250, 253, 254, 255, 261, 262, 304 lipoproteins, 423 liquid chromatography, 176, 212, 421, 426 Lithuania, 457 liver, 46, 62, 64, 66, 69, 71, 111, 120, 124, 136, 195, 281, 283, 290, 340 liver cells, 136 living environment, 496 localization, 117, 121, 141, 175, 248, 409, 418, 493 locus, xx, 223, 228, 231, 256, 453, 454, 455, 460, 461, 463, 464, 465, 489, 498 longevity, 403, 406, 410, 411 low temperatures, 48, 117, 248 lying, 358, 397 lysine, 157, 160, 161, 162, 344 lysosome, 55, 211, 418, 438 lysozyme, 433

M machinery, xi, 98, 99, 119, 254, 361, 362, 366, 368 macroalgae, 265, 280 macromolecules, 387 macrophages, 433 magnesium, 104, 106, 451 magnetic field, 142 Maillard reaction, 344 Maine, 248, 260, 494 Maine, Gulf of, 248, 260, 494 majority, 90, 91, 349, 388, 417, 490, 496 majority group, 91 malaria, 292 malate dehydrogenase, 208, 260

Index Malaysia, vi, xii, 221, 222, 223, 224, 225, 227, 228, 230, 232, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243 maltodextrins, 346, 347 management, 68, 81, 83, 90, 91, 94, 142, 183, 276, 283, 359, 375, 388, 467, 481, 482 manganese, 154, 175, 180, 382, 391 mangroves, 188 MANOVA, 6, 8, 17, 31, 32 mantle, xviii, 45, 46, 47, 53, 54, 134, 135, 177, 250, 429, 469, 473, 474, 479, 512 manufacture, 201 manufacturing, 93, 170, 286 MAP kinases, 129, 131, 132, 133, 135, 137, 138, 139, 144 mapping, 127, 377, 487, 489, 492 marine environment, x, xvi, 2, 3, 35, 39, 41, 43, 50, 58, 59, 61, 63, 67, 68, 142, 143, 178, 183, 187, 189, 218, 238, 246, 247, 253, 255, 265, 276, 287, 288, 295, 298, 380, 383, 385, 386, 387, 390, 392, 393, 411, 419, 504, 506 markers, xiii, xx, 2, 36, 37, 40, 50, 53, 68, 139, 143, 186, 206, 207, 208, 209, 216, 221, 222, 223, 225, 226, 227, 230, 234, 235, 236, 239, 240, 241, 242, 259, 260, 269, 278, 282, 343, 387, 418, 425, 454, 460, 485, 493, 496, 498 marketing, 92 marsh, 40, 239 masking, 344 mass loss, 156 mass spectrometry, 157, 212, 268, 421, 426 mastectomy, 159, 164 matrix, 45, 149, 154, 169, 283, 289, 512 meat, xv, 292, 337, 338, 339, 340, 341, 342, 343, 344, 345, 347, 348, 349, 350, 353, 430, 509 media, 60, 174, 222, 250, 290 median, 403, 404, 405, 406 mediation, 425 medication, 201 Mediterranean, vi, xi, xiv, xv, 44, 61, 62, 70, 71, 72, 79, 93, 98, 108, 126, 129, 139, 141, 174, 180, 181, 185, 186, 193, 196, 200, 213, 218, 251, 257, 258, 260, 264, 265, 280, 281, 282, 283, 285, 286, 289, 294, 296, 297, 301, 333, 380, 389, 420, 486, 491, 494 meiosis, 489, 490 melt, 75, 345 melting, 178 membrane permeability, 176, 289

533

membranes, xiii, 102, 103, 117, 182, 206, 245, 246, 249, 258 memory, 306 mercury, 55, 63, 71, 100, 121, 124, 125, 141, 142, 143, 177, 178, 179, 183, 187, 189, 199, 238, 283 Mercury, 100, 142, 439 messages, 407 messenger RNA, 119 messengers, 2, 252 metabolic pathways, 254 metabolism, ix, 48, 56, 63, 65, 66, 71, 121, 175, 180, 192, 204, 205, 206, 210, 233, 240, 247, 248, 250, 251, 252, 257, 261, 262, 265, 277, 289, 301, 334, 383, 389, 423 metabolites, xiii, 56, 60, 69, 183, 206, 212, 217, 219, 245, 250, 287, 290, 292, 419, 424 metacentric chromosome, 486, 489 metal oxides, 152, 159, 384 metalloids, 49, 434 metals, xiii, xvi, 3, 41, 49, 52, 55, 57, 58, 59, 64, 67, 69, 70, 72, 98, 100, 101, 104, 106, 107, 120, 143, 152, 153, 159, 164, 176, 177, 178, 179, 180, 188, 191, 192, 198, 199, 200, 201, 206, 207, 208, 214, 216, 219, 222, 224, 232, 234, 240, 245, 252, 253, 258, 259, 266, 280, 281, 286, 287, 368, 379, 381, 382, 383, 384, 385, 386, 387, 388, 389, 390, 391, 392, 393, 423, 434 metamorphosis, 47, 260, 471 metaphase, 59 meter, 306, 506 methanol, 5, 268 methodology, 185, 266, 342, 377, 399, 408, 461, 463 methylation, 254, 298 Mexico, 258 mice, 113, 120, 136, 294, 421, 426 microencapsulation, 345, 346, 353 micronucleus, xxi, 59, 62, 63, 67, 71, 103, 104, 117, 120, 122, 178, 185, 189, 190, 252, 438, 495, 499, 500 microorganism, xix, 436, 441 microsatellites, 222, 235, 239, 241, 495, 498 microscope, 398, 399, 444, 513 microscopy, 153, 157, 169 microsomes, 450 migration, 50, 60, 472, 492, 496, 505 mining, 199, 209, 280 Ministry of Education, 374 Mississippi River, 481, 482 mitochondria, 48, 53, 180, 208, 210, 248, 262 mitochondrial DNA, xx, 64, 453, 454, 485, 493, 494

534

Index

mitogen, 142, 144, 250 mitosis, 112 mixing, 76, 513 model system, 105, 287 modeling, xv, 109, 110, 115, 116, 205, 283, 303, 304, 317, 332, 400 modelling, 119, 278, 387, 401 modification, xi, 71, 83, 86, 98, 107, 159, 286, 423, 447, 510 moisture, 338, 349 moisture content, 349 mold, 147 molecular biology, 186, 192, 237 molecular mass, 56, 146, 147, 149, 418 molecular oxygen, 151 molecular weight, 58, 101, 114, 162, 179, 209, 252, 288, 296, 300, 343, 346, 347, 349 molecules, xii, 48, 98, 117, 131, 155, 156, 157, 162, 167, 168, 171, 180, 182, 197, 199, 201, 202, 203, 207, 265, 346, 431, 433, 438, 450 mollusks, 60, 122, 181, 213, 222, 240, 250, 255, 258, 260, 261, 299, 333, 395, 408, 483 monitoring, ix, x, xii, xiii, xiv, xvi, xvii, 36, 43, 49, 50, 51, 52, 53, 54, 57, 61, 62, 63, 64, 68, 71, 120, 125, 126, 143, 173, 174, 176, 177, 180, 181, 182, 183, 185, 186, 187, 190, 191, 194, 198, 199, 201, 203, 205, 211, 213, 215, 217, 222, 238, 240, 246, 249, 251, 252, 255, 258, 259, 260, 279, 285, 287, 288, 306, 379, 380, 381, 385, 386, 388, 391, 392, 393, 413, 421, 423, 426, 496, 500, 507 monoclonal antibody, 109 monolayer, 444 monomers, 104 monosodium glutamate, 344 monounsaturated fatty acids, ix, 1 Montana, 143 Moon, 166 Morocco, 124, 142 morphology, xvi, xx, 338, 353, 431, 433, 440, 470, 485, 486, 489, 490, 509 morphometric, 492, 493 mortality rate, 178, 218, 227, 509 mosaic, 491 Moscow, 394, 453, 460, 466, 467, 468 motif, 117, 148, 170 MPI, 232 mRNA, 104, 107, 113, 181, 182, 248 mtDNA, xx, 453, 454, 455, 456, 457, 460, 461, 462, 463, 464, 465, 494 mucus, 474

multiple factors, 434 multiplication, 291 muscles, 45, 431, 432, 473, 474, 507 Mussel Watch Program, xvi, 379, 388 mutant, 123 mutation, 242, 496, 500 mutation rate, 242, 500 myosin, 342, 347

N NaCl, 115 naiad, 483 nanomaterials, 201, 215 nanoparticles, 52, 55, 67, 69, 160, 171, 201, 216 nanotechnology, 201, 214 naphthalene, xiv, 264, 268, 273, 276, 362 national product, 358 National Research Council, 69, 77, 500 native species, 93, 253, 289 natural enemies, xxi, 503, 504, 505, 510, 513, 514 natural habitats, 183, 246 natural killer cell, 140 natural resources, xiii, 222, 390 natural selection, 227, 241, 504 nature of time, 411 negative consequences, 253 negative relation, 103, 204 nematode, 63 nerve, 144 nervous system, 383, 473 Netherlands, 44, 201, 213, 332, 333, 375, 381, 424, 425, 485 neurodegeneration, 123 neurotoxicity, 206, 291, 301 neurotransmitter, 150 neutral lipids, 56, 69, 218 New England, 517 New Zealand, 44, 91, 225, 259, 283, 358, 425, 508, 518 nickel, 126, 175, 180, 191, 200, 434 Nile, 279 nitrate, 3, 5, 9, 10, 33, 36, 106, 214 nitrates, 77 nitric oxide, 124, 252, 437, 438, 439 nitric oxide synthase, 437 nitrogen, xiv, 5, 6, 157, 165, 199, 214, 250, 251, 264, 265, 268, 270, 272, 273, 276, 277, 278, 280, 283, 284, 366, 367, 373, 377 NK cells, 135

Index NMR, 155, 157, 166, 169 North America, 44, 198, 199, 248, 253, 262, 299, 420, 454, 466, 468, 470, 471, 472, 474, 482, 483, 485, 489, 493, 507, 511 North Sea, 62, 66, 144, 219, 225, 242, 485, 494 Norway, 212, 281, 359, 377, 406, 494 nuclear magnetic resonance, 155 nuclei, 59, 178, 435, 488, 491 nucleic acid, 106, 107, 213, 252, 387 nucleophiles, 157, 158 nucleotides, 339, 344, 460, 461 nucleus, 59, 108, 135, 136, 178 numerical analysis, 334 nutrients, x, 2, 3, 38, 49, 73, 74, 76, 77, 78, 79, 304, 325, 333, 372, 472, 479 nutrition, 35, 38, 288, 339

O objectivity, 87 oceans, xiv, xv, 76, 198, 285, 368, 380 oil, 49, 64, 129, 133, 136, 139, 160, 179, 181, 182, 190, 193, 218, 251, 259, 282, 286, 294, 339, 346, 362, 364, 367, 368 oil production, 368 oil spill, 64, 133, 179, 181, 190, 193, 251, 282, 294 Oklahoma, 280 oligomers, 162 one dimension, 201 oogenesis, 195 operating system, 433 optimization, 340, 374 organ, xviii, 46, 49, 60, 82, 133, 206, 290, 384, 429, 473, 475 organelles, 53, 54, 57 organic chemicals, 199, 200 organic compounds, xiv, xvi, 65, 213, 264, 273, 278, 290, 345, 380, 499 organic materials, 3 organic matter, xiv, xv, 35, 40, 253, 281, 285, 303, 307, 310, 311, 314, 319, 320, 321, 329, 381, 384 organism, xv, 48, 49, 50, 51, 52, 53, 57, 60, 61, 113, 138, 139, 147, 183, 206, 213, 234, 246, 247, 248, 250, 251, 252, 253, 255, 264, 267, 277, 278, 279, 285, 288, 289, 293, 334, 380, 383, 396, 423, 431, 433, 434, 471, 496 organochlorine compounds, xiv, 57, 217, 274, 285 organotin compounds, 141, 240 oscillations, 327 osmolality, 250

535

overharvesting, xx, 469 overlap, 254, 402 ownership, 83 ox, 278 oxidation, xi, 57, 72, 123, 145, 150, 151, 155, 156, 162, 165, 177, 199, 251, 339, 343, 345, 346, 383, 384, 419, 420, 426 oxidation rate, 151, 165 oxidative damage, 55, 56, 175, 176, 177, 188, 251, 252, 260, 278, 282 oxidative reaction, 176 oxidative stress, 54, 55, 56, 57, 59, 65, 70, 72, 115, 121, 124, 125, 126, 142, 144, 174, 177, 180, 187, 188, 189, 193, 202, 203, 210, 251, 252, 254, 256, 260, 261, 262, 265, 278, 279, 280, 438 oxygen, xv, xix, 5, 7, 34, 48, 60, 63, 71, 98, 150, 151, 152, 154, 155, 156, 165, 174, 199, 247, 256, 257, 265, 278, 289, 303, 304, 305, 306, 307, 308, 310, 311, 312, 314, 325, 329, 331, 332, 333, 335, 337, 373, 376, 383, 384, 429 oxygen consumption, 247, 256, 257, 307, 310, 314, 329, 331, 335, 376 oxygen consumption rate, 307, 329, 331 oyster, 62, 142, 194, 195, 226, 241, 249, 258, 261, 421, 430, 515, 516 oysters, xv, xvii, xviii, 41, 55, 65, 70, 200, 217, 227, 238, 256, 258, 337, 380, 414 ozone, xvi, 357, 368, 369

P Pacific, 3, 44, 195, 210, 217, 241, 242, 260, 380, 485, 489, 492, 493, 494, 517, 518 packaging, 90, 360, 362 PACs, 215 paints, 133, 200 palladium, 180, 192 parallel, 76, 112, 114, 458 paralysis, 419 parasite, 433, 436, 513, 514, 515, 516, 518 parasites, xxi, 93, 258, 430, 431, 471, 503, 512, 514, 516, 518 Parliament, 85, 86 parotid, 168 partition, 203 path analysis, 520 pathogens, 247, 431, 433, 435, 437 pathology, 55

536

Index

pathways, x, xi, 67, 97, 101, 104, 131, 140, 141, 142, 143, 145, 152, 185, 203, 210, 237, 246, 252, 290, 339, 388 PCA, xiv, 264, 269, 270, 272, 273, 274 PCBs, xiv, 49, 50, 52, 55, 57, 69, 176, 181, 196, 213, 254, 259, 264, 265, 267, 268, 269, 271, 273, 274, 275, 276, 277, 278, 279, 281, 285, 290, 291, 292, 294, 295, 296, 301 PCR, 59, 64, 111, 112, 192, 225, 226, 240, 454, 455, 457, 458, 459, 460, 461 Pearson correlations, 402, 405, 406 PEP, 228, 231 pepsin, 146, 147 peptide chain, xi, 97 peptides, 110, 151, 152, 153, 156, 157, 160, 161, 163, 167, 168, 170, 182, 341, 343, 344, 347 performance, 52, 176, 248, 249, 250, 255, 261, 359, 360, 362, 368, 374 pericardium, 433 periodicity, xvii, 395 permeable membrane, 218 permit, 151, 211, 387, 389 peroxidation, 52, 55, 57, 64, 176, 177, 249 peroxide, 56, 151, 175, 420 peroxynitrite, 70, 437 perylene, 293, 297, 362 pesticide, xix, 58, 286, 292, 436, 439, 441, 443, 446, 449 pesticides, 49, 51, 58, 65, 72, 98, 101, 176, 180, 183, 200, 204, 206, 208, 253, 261, 265, 266, 282, 283, 286, 296, 300, 423, 434, 438, 451, 472 PET, 361, 367 phagocytosis, xix, 54, 140, 202, 207, 431, 433, 434, 436, 437, 438, 439, 440, 441 pharmaceuticals, 55, 200, 214, 218, 253 pharmacology, 301 phase transitions, 114 phenol, 147 phenylalanine, xi, 145, 147, 161, 162, 165 phosphates, 77, 382, 389 phosphatidylcholine, 254 phosphatidylethanolamine, 254 phosphoenolpyruvate, 257 phospholipids, xiii, 177, 245, 250, 251, 254, 256, 257, 259 phosphorous, 373 phosphorylation, xi, 98, 99, 108, 110, 114, 115, 117, 118, 122, 126, 127, 129, 131, 132, 133, 134, 135, 136, 138, 140, 141, 142, 143, 149, 251 photosynthesis, 77

phthalates, 183 phylum, 253 physical environment, 35, 94 physical interaction, 152 physical properties, xiii, 245, 246, 249 physical stability, 353 physiological factors, 289, 401 physiology, x, 41, 43, 50, 56, 182, 183, 202, 205, 239, 282, 289, 332, 381, 382, 390, 423, 432, 492 phytoplankton, xiv, xvii, 2, 3, 35, 36, 37, 38, 39, 40, 75, 77, 249, 250, 265, 278, 283, 285, 335, 372, 376, 387, 413, 423, 425, 481 pigments, 55, 188 pilot study, 68, 218 plaque, 146, 148, 149, 153, 154, 166, 171 plasma membrane, 175 plasticity, 498 plastics, 368 platform, 88, 112, 305, 306, 307, 308, 309, 326, 330, 360 poison, 420, 424, 426 Poland, 97, 379, 517 polarity, 346 polarization, 112 police, 81 polonium, 200 polybrominated biphenyls, 434 polybrominated diphenyl ethers, 200 polychlorinated biphenyls (PCBs), 55, 176, 265 polychlorinated dibenzofurans, 300 polycyclic aromatic hydrocarbon, xiv, 41, 49, 55, 67, 69, 133, 142, 176, 190, 193, 199, 212, 215, 217, 219, 222, 236, 251, 256, 261, 265, 268, 283, 285, 293, 299, 300, 301, 362 polydimethylsiloxane, 349 polymer, 152, 157, 162, 165, 346 polymer chains, 152 polymerase, 458 polymerization, 156, 164 polymers, xi, 145, 146, 165, 347 polymorphism, 226, 237, 238, 454, 457, 489, 493 polymorphisms, 122, 227, 232, 234, 241, 243, 457, 463, 486, 490 polypeptide, 56, 160, 170, 171 polyphenols, 178, 194 polypropylene, 361 polystyrene, 359 polyunsaturated fat, ix, xiii, 1, 2, 11, 12, 13, 14, 15, 16, 19, 21, 23, 25, 27, 29, 40, 176, 188, 245, 252, 349

Index polyunsaturated fatty acids, xiii, 2, 40, 176, 188, 245, 252, 349 polyvinyl chloride, 307 pools, 104, 507 population density, 305, 316, 319, 320, 322, 326, 330, 479 population growth, 198, 338 population size, 60 Porifera, 143 porosity, 512 Portugal, 79, 141, 191, 381, 413, 415, 421, 424, 426 positive correlation, xiv, 33, 35, 176, 264 positive feedback, xxi, 503, 510 positive relationship, 180 potassium, 104, 106, 433 poultry, 339, 430, 442 power plants, 304 praxis, 386 precedent, 489 precipitation, 202, 344 predation, xix, xxi, 246, 441, 503, 504, 505, 506, 508, 509, 510, 511, 512, 514, 516, 517, 518 predators, x, xxi, 43, 45, 47, 48, 304, 474, 503, 504, 505, 506, 507, 508, 509, 510, 513, 518, 519, 520 prevention, 159, 164 primate, 168 principal component analysis, 269, 270, 272, 274 private ownership, 83 probability, 199, 224 probe, 65, 438 procurement, xix, 429 producers, x, 44, 73, 74, 86, 90, 91, 92, 93, 94, 415 product market, 91 production capacity, 373 productivity, 75, 76, 78, 80, 82, 373, 518 profitability, 87, 93 project, 63, 87, 186, 279, 332, 377, 499 proliferation, xi, 52, 57, 61, 62, 69, 78, 98, 108, 111, 112, 120, 449 propagation, xix, xx, 430, 442, 469, 482 property rights, 74, 81, 83, 85, 93, 95 prostaglandins, 261 protective coating, 166 protective mechanisms, 266 protein family, 150, 169 protein hydrolysates, 340, 344 protein kinase C, xi, 98, 99, 110, 113, 115, 116, 119, 120, 124, 125, 127 protein kinases, 112, 115, 122, 140, 143 protein oxidation, 57, 252

537

protein sequence, 132, 133, 171 protein signatures, 185 protein structure, 109, 110, 115, 116, 119, 123 protein synthesis, xi, 71, 97, 98, 99, 100, 104, 106, 107, 111, 113, 117, 121, 123, 124, 126, 177, 253 protein-protein interactions, 126 proteins, xi, xx, 48, 53, 54, 55, 56, 58, 59, 64, 98, 99, 106, 107, 108, 109, 110, 111, 114, 117, 118, 121, 122, 123, 124, 125, 126, 127, 129, 130, 131, 133, 139, 143, 145, 146, 147, 148, 149, 150, 151, 152, 153, 155, 156, 157, 159, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 174, 181, 182, 183, 184, 190, 191, 192, 193, 194, 206, 207, 209, 211, 261, 287, 338, 341, 344, 347, 356, 382, 387, 418, 432, 485 proteolysis, 342 proteome, 185 proteomics, 67, 187 prototype, 421, 422 Prozac, 259 public administration, 80 public domain, 83, 84 public health, 195, 288, 294, 382 public sector, 90, 91 pulp, 218, 236, 242 purification, 39, 89, 115

Q qualitative differences, 66, 300 quality assurance, 180, 191 quality of life, 201 quinone, xi, 145, 148, 150, 151, 152, 155, 156, 157, 158, 160, 170, 171 quinones, 150, 155

R radiation, 236, 237 radicals, 60, 70, 154, 174, 176, 252, 384 radio, 200 Raman spectroscopy, 168 reactants, 155 reaction rate, 248, 341, 342 reaction temperature, 342 reactions, xii, xv, 54, 55, 68, 145, 162, 176, 180, 192, 206, 217, 252, 337, 338, 339, 450 reactive oxygen, 56, 69, 71, 106, 111, 174, 178, 248, 249, 251, 252, 260, 262, 265, 282

538

Index

reactivity, 162, 201, 422, 449 reading, 365, 409 reagents, 104, 154, 168 real terms, 90 reality, 425 reception, 473 receptors, 63, 183 recognition, 117, 127, 193, 430, 431, 434, 436, 442, 471 recommendations, iv, xviii, 93, 389, 414 recreational areas, 3 recycling, 369, 376 Red List, 480 Red Sea, 62 redistribution, 295 regeneration, 373, 393, 433 regression, 408, 409, 410 regulatory framework, 179 relative toxicity, 291 relatives, 349, 518 relevance, xvi, 141, 161, 164, 181, 186, 193, 206, 237, 371, 375, 379, 385, 386 reliability, 406 repair, 60, 71, 178, 179, 189, 265, 403 replacement, 206 replication, x, 97 reproduction, x, xii, 2, 3, 36, 38, 39, 40, 53, 93, 195, 197, 207, 209, 211, 289, 295, 300, 304, 360, 383, 472, 479, 481, 482, 511 reproductive cells, 385 reproductive organs, 473 research and development, 338 reserves, 206, 207, 304 residues, xi, 58, 68, 110, 113, 117, 118, 145, 148, 149, 153, 154, 156, 157, 158, 179, 276, 293, 434, 437, 442, 449 resilience, 423 resistance, 48, 57, 66, 101, 144, 160, 165, 182, 193, 194, 207, 216, 241, 265, 287, 381, 403, 514, 517 resolution, 86, 120, 121, 126, 387, 468 resorcinol, 165 resources, xvi, 74, 81, 83, 209, 276, 290, 357, 426, 505, 511, 518 respiration, xxi, 199, 205, 207, 208, 247, 260, 304, 314, 316, 319, 325, 334, 473, 474, 480, 503 response time, 498 responsiveness, 58, 174 restructuring, 85 reticulum, 53, 68, 180 rhinitis, 434

ribosomal RNA, 98, 107, 124, 127, 492 ribosome, xi, 97, 106, 107, 110, 111, 114, 117, 120, 121, 125 rights, iv, 74, 81, 82, 83, 85, 95, 96 rings, 155, 290, 298, 396, 406, 408, 409, 478, 497 risk assessment, 67, 130, 195, 201, 206, 209, 254, 255, 262, 284, 291, 292, 298, 387, 388 risk management, 388 river basins, 227 RNA, 63, 107, 121, 123, 124, 206, 213 RNAi, 108 rocks, xv, 44, 79, 88, 303, 358, 511 rodents, 434 Romania, 469 room temperature, 455 roughness, 347 Rouleau, 212 Royal Society, 425 runoff, 36, 210, 286, 497 rural population, 430 Russia, 44, 259, 453, 458, 460, 467

S salinity, x, xiii, xv, 3, 5, 7, 33, 38, 43, 47, 48, 51, 75, 76, 137, 138, 139, 174, 185, 186, 196, 211, 245, 246, 250, 251, 254, 255, 258, 259, 261, 285, 288, 289, 290, 296, 306, 307, 310, 311, 312, 314, 319, 326, 327, 329, 330, 334, 381, 383, 384, 391, 494, 497, 513 saliva, 168 salmon, 50, 340, 359, 370, 375, 474 salts, 5, 77, 78, 250, 339, 382 saltwater, ix, x, 43, 44 sanctions, 85 SAP, 450 saturated fat, ix, 1, 2, 11, 12, 13, 14, 15, 16, 19, 21, 23, 25, 27, 29 saturated fatty acids, ix, 1, 2 saturation, 319 scaling, 319, 404, 408 scars, 474 scavengers, xii, 56, 57, 145, 179, 388 sclerochronology, xvii, 395, 396, 399, 403, 404, 405, 406, 409, 410 screening, 3, 38, 166, 178, 179, 185, 194, 332, 449 SEA, 259 seafood, xiii, xiv, xv, xvi, 80, 84, 218, 222, 245, 285, 288, 290, 337, 338, 339, 340, 357, 358, 359, 368, 376, 380, 381, 419, 425

Index seasonal changes, ix, 1, 6, 18, 31, 32, 38, 121, 177, 192, 507 seasonality, 186 secondary sector, 89 secretion, 46, 55, 430 sediment, 40, 41, 78, 93, 140, 153, 173, 191, 199, 202, 205, 213, 214, 215, 217, 218, 232, 236, 252, 280, 289, 293, 298, 300, 333, 385, 388, 389, 390, 391, 419, 423, 442 sedimentation, 78, 104, 472 sediments, 55, 100, 101, 114, 141, 175, 187, 199, 202, 212, 215, 216, 218, 225, 243, 280, 286, 293, 298, 333, 373, 381, 383, 384, 385, 387, 388, 389, 397 seed, 39, 74, 88, 255, 334, 360, 362, 367, 376, 442, 472 segregation, 490, 494 selectivity, 69 selenium, 71, 175, 187 self-control, 93 self-fertilization, 231 semi-permeable membrane, 53, 212 sensing, 141 sensitivity, 62, 174, 179, 208, 219, 248, 249, 253, 257, 388, 420, 497 sensors, 306, 307, 308 sequencing, 166, 182, 460, 463 serine, 58, 113, 117, 118, 149, 259 serotonin, 206, 214 serum, 114, 335, 431 sewage, xii, 3, 38, 100, 197, 201, 208, 209, 210, 217, 218, 265, 280, 281, 282, 283, 284, 286 sex, 47, 203, 206, 227, 290, 301, 391 sex chromosome, 47 sex ratio, 206, 227 shade, 472 shape, 44, 46, 74, 88, 112, 289, 349, 382, 391, 396, 399, 411, 444, 476, 477, 478, 479 shear, 160 sheep, 281 shelf life, xvi, 338, 345, 353 shell destroyers, xxi, 503, 512, 514 shellfish, xvii, xviii, 84, 205, 213, 217, 333, 339, 358, 413, 414, 419, 421, 424, 425, 426, 427, 513 ships, 151, 160, 303 shock, 143, 144, 146 shoreline, 360, 367 shores, xiv, 44, 285, 506, 507, 511, 515, 519 short supply, 512 shortage, 325

539

shrimp, 167, 233, 238, 240, 281, 339, 340, 342, 370, 376 shrinkage, xix, 349, 430 sibling, 299 signal peptide, 167 signal transduction, 63, 112, 120, 140, 142, 291 signaling pathway, xi, 129, 131, 138, 140, 141 signalling, 141, 142, 143, 258 signals, 52, 124, 251, 287, 409, 410 signs, 90 silica, 344 silicon, 168 silk, 146, 168 silkworm, 108, 123 silver, 160, 179, 180, 192, 199, 489 simulation, 306, 329, 334 Singapore, 39 siphon, 46, 474 sister chromatid exchange, 488 skeletal remains, 397 skeleton, xvii, 395 skin, 45, 47, 346, 383 sludge, 93, 218 smoking, 293, 294 social benefits, 74, 81 social institutions, 81 social sciences, 94 sodium, 153, 433, 435, 436, 437, 438 sodium hydroxide, 153, 433 software, 6, 269, 366, 460 solid phase, 204, 349 solid surfaces, 146 solid waste, 368 solubility, 201, 310, 344, 346 somatic cell, 293 sorption, xvi, 338, 349, 353 sorption isotherms, xvi, 338, 349, 353 South Africa, 298, 301 Southeast Asia, 68, 240 Southern Africa, 225, 239 Spain, xvi, xviii, 44, 79, 82, 90, 91, 96, 98, 126, 141, 187, 257, 263, 312, 327, 329, 333, 334, 335, 357, 358, 359, 362, 366, 369, 375, 376, 377, 381, 410, 413, 415, 421, 424, 425, 469, 485, 519 specialists, 94 speciation, 222, 281, 383, 388, 391, 392, 489, 490, 492, 493 species richness, 472 specifications, 85 spectrophotometer, 269

540

Index

spectrophotometric method, 72, 126 spectrophotometry, 100, 121, 122 spectroscopy, 157, 390 sperm, 254, 479, 494 spermatogenesis, 113, 254 spin, 152 spindle, 59, 178, 435 sponge, 132, 139, 511, 516 Spring, 280, 468 St. Petersburg, 466 stabilization, 147, 149, 345, 346 stabilizers, 338 stable isotopes, 264, 265, 269, 277, 281, 283, 284 stakeholders, 212 standard deviation, 210, 268, 345, 404 standardization, 399, 400, 407, 408, 409 starch, 228, 232, 234, 347 stars, 47, 48, 507 starvation, xv, 256, 299, 303, 325 statistics, xiii, 221, 223, 228, 236, 403, 410 steel, 51, 160, 164, 165, 186, 267, 361, 367, 368 stem cells, 433 sterile, 443 steroids, 184 sterols, xiii, 193, 245, 249, 253 stomach, 2, 46, 469, 473 storage, xv, 2, 51, 56, 67, 163, 164, 252, 295, 304, 337, 345, 349, 352, 353, 382 streams, 472 stress factors, 47, 114 stressors, xx, 48, 55, 141, 198, 206, 207, 208, 209, 210, 211, 247, 258, 495, 496, 497, 498, 499 strong interaction, 49 strontium, 281 structural protein, 146, 164, 171 structuring, 501 subdomains, 116 substitution, 290, 461, 489 substitutions, 460 substrates, xi, xxi, 3, 56, 115, 124, 135, 145, 162, 166, 168, 170, 175, 180, 181, 183, 380, 381, 423, 455, 460, 503 succession, 2 sucrose, 104 sulfur, 40 sulphur, 199, 265, 377, 382 Sun, 148, 167, 170 suppression, 98, 123, 438 supraventricular tachycardia, 256 surface area, 83, 88, 201

surface layer, 78, 326 surgical intervention, 159 surplus, 505 surveillance, 279 survey, 201, 213, 215, 362, 363, 390 survival, xix, xx, 47, 52, 60, 106, 112, 113, 130, 177, 185, 207, 209, 210, 234, 237, 240, 242, 300, 431, 441, 469, 511, 519 survival rate, 185 susceptibility, xv, 65, 70, 279, 337 suspensions, 61 sustainability, xii, 174, 198, 281, 376 sustainable development, xvi, 379 Sweden, 407, 408, 409, 410, 518 swelling, 55 Switzerland, 195, 218, 340, 375 symptoms, xvii, 383, 413, 512 synaptic clefts, 58 syndrome, 64, 78, 121, 185, 196, 233, 240, 419 synthesis, xi, xii, 56, 58, 59, 61, 97, 98, 100, 105, 106, 107, 108, 111, 118, 130, 140, 146, 147, 151, 159, 162, 168, 178, 179, 200, 208, 283, 393, 458, 459

T Taiwan, 200, 216 tanks, 417, 419 tannins, 178, 190 taphonomy, 409 tar, 362, 364, 368 target organs, 382, 387 taxonomy, xx, 485, 486, 492 teeth, 473, 478 temperature, x, xiii, xv, 3, 5, 6, 33, 37, 38, 39, 40, 43, 47, 48, 51, 69, 75, 76, 77, 104, 121, 124, 130, 131, 137, 138, 139, 140, 174, 176, 183, 186, 202, 207, 208, 210, 211, 245, 246, 247, 248, 249, 250, 254, 255, 260, 261, 267, 285, 288, 289, 290, 296, 306, 307, 310, 311, 312, 313, 319, 326, 330, 332, 334, 335, 338, 340, 341, 343, 347, 349, 381, 383, 385, 408, 410, 443, 460, 471, 472, 473, 474, 479, 511, 513 tendons, 146, 168 tensile strength, 160 tensions, 63 testing, xvii, 65, 182, 185, 190, 213, 214, 333, 411, 413, 458, 500 tetrachlorodibenzo-p-dioxin, 291 Thailand, 173, 186, 358, 359

Index thermal oxidation, 349 thermal resistance, 98 thermosets, 170 thinning, 335, 360 threshold level, 253 thrombus, 449 thyroid, 291 tides, 78, 209, 246, 506 time periods, 86, 387 time series, 399, 405, 408, 411 time use, 133 tin, 199, 209, 268 tissue, xii, xiv, xxi, 2, 5, 6, 33, 36, 37, 39, 41, 46, 47, 48, 51, 52, 60, 71, 99, 125, 142, 145, 159, 166, 170, 175, 176, 177, 206, 211, 216, 249, 250, 253, 256, 259, 264, 267, 268, 272, 273, 278, 279, 281, 282, 287, 288, 289, 293, 383, 384, 385, 387, 388, 393, 421, 430, 433, 449, 471, 474, 503, 512 titanium, 165 Title V, 85 toluene, 434 total product, 91, 363 tourism, xvi, 49, 380 toxic contamination, 442 toxic effect, xii, 51, 58, 64, 173, 174, 197, 203, 205, 234, 252, 286, 287, 291, 382, 384 toxic metals, 59, 101, 252, 434 toxic substances, 174, 386 toxicity, xvi, xix, 51, 55, 56, 64, 70, 72, 126, 136, 185, 199, 200, 201, 206, 207, 208, 209, 211, 214, 216, 239, 250, 265, 290, 291, 292, 293, 300, 357, 358, 368, 369, 370, 372, 373, 374, 379, 382, 383, 385, 387, 392, 415, 419, 421, 424, 426, 430, 433, 440, 443, 500 toxicology, xx, 54, 65, 190, 202, 216, 222, 238, 287, 301, 389, 495, 496 toxicology studies, 202 toxin, xviii, xix, 413, 414, 415, 417, 418, 419, 421, 424, 425, 426, 427, 430, 436, 444 trace elements, 41, 142, 382 trade-off, 261, 509 training, 305, 332 traits, xx, 469, 510 transaction costs, 74, 94 transactions, 74 transcription, x, 72, 97, 112, 141, 248, 291 transcripts, 111 transduction, 130 transformation, 41, 91, 199, 204, 389, 400, 417 transformation product, 199

541

transformations, 387 transition metal, 122, 153 transition temperature, 347, 349, 353 translation, xi, 97, 98, 99, 104, 106, 107, 108, 111, 114, 118, 122, 124, 125 translocation, 64, 127 transmission, 223 transparency, 85, 87 transplantation, 41, 63, 68, 70, 228, 266, 282, 283, 508 transport, 50, 133, 182, 193, 194, 207, 208, 210, 249, 286, 289, 291, 384, 424, 433 transport processes, 384 tributyltin chloride, 141 triggers, 123 triglycerides, 48 trypsin, 149, 488 tryptophan, 161, 167, 344 tumorigenesis, 112 tumours, 60, 294 turbulence, xiv, 285 Turkey, 280, 390 turnover, 53, 89, 124, 233, 248, 278, 286, 287, 358, 373, 387, 418 tyrosine, 140, 147, 148, 149, 150, 151, 155, 159, 160, 161, 164, 167, 168, 345 Tyrosine, 161, 165, 345 tyrosine hydroxylase, 150, 164

U ultrastructure, 164 UNESCO, 68, 424, 425, 426 uniform, 435, 443 United Kingdom (UK), xvi, 41, 191, 192, 193, 208, 259, 299, 334, 335, 353, 354, 379, 389, 390, 391, 491, 515, 516 United Nations, 61, 68, 199, 354, 424 urban area, 184, 195, 214 urbanisation, 252 urbanization, 49, 198, 442 USSR, 255, 466, 467

V vacuum, 5 Valencia, 280 validation, 179, 187, 192, 234, 256, 280, 327, 391 valleys, x, 73, 74, 75

Index

542

vanadium, 180, 191 vapor, 100 variations, xvii, 6, 51, 104, 105, 131, 138, 170, 187, 188, 212, 215, 234, 235, 241, 261, 282, 288, 298, 320, 325, 332, 335, 362, 385, 387, 390, 395, 399, 401, 403, 405, 407, 435 vector, 293 vegetables, 293, 299, 338 vegetation, 260 vehicles, 253 ventilation, xxi, 335, 503 Venus, 492 vertebrates, xi, 98, 129, 132, 290, 381 vesicle, 437 vessels, x, xvi, 3, 73, 88, 186, 357, 360, 362, 363, 364, 365, 366, 367, 368, 370, 374 victims, 514 virus replication, 112 viruses, 431 viscera, 431 viscosity, 346, 349 vision, 74 visualization, 332 vitamin E, 56 vitamins, 2 volatility, 346 volatilization, 293

W Wales, 505 waste, 57, 144, 203, 286, 292, 338, 339, 342, 344 waste water, 203, 286 wastewater, xvi, 3, 141, 192, 217, 218, 357, 362, 364, 365, 366, 368, 374, 377 water activity, 347, 348, 349 water ecosystems, 281, 387 water quality, ix, xiii, xvi, xx, 1, 3, 35, 38, 63, 70, 87, 131, 139, 175, 176, 225, 234, 239, 257, 263, 264, 277, 283, 290, 305, 306, 307, 308, 332, 376, 379, 469, 472, 499 water resources, 174

watershed, 217, 281 waterways, 57, 200 weakness, 139 wealth, 81, 208 weight loss, 304 welfare, 254 western blot, 111 wetlands, 276, 442, 443 wettability, 171 wholesale, 88 wild animals, 51 wildlife, 58, 282, 292, 496 wind farm, 304, 332 withdrawal, 83 wood, 111, 127, 253, 359, 361, 365, 368 workers, 181, 183, 332, 431, 435, 449 World Health Organisation, 292 World Wide Web, 41 worms, 513 wound healing, 433, 434, 446

X X-ray, 362

Y yarn, 366 yeast, 105, 107, 108, 111, 113, 114, 115, 118, 119, 121, 123, 124, 126, 127, 138, 144, 339, 435, 436, 437 yolk, 184, 207 young women, 299

Z zinc, 61, 66, 67, 69, 70, 72, 117, 140, 143, 175, 179, 180, 183, 200, 242, 280, 391 zoology, 470 zooplankton, ix, 1, 3, 35, 37, 38, 39, 479