Computers in Fisheries Research

Computers in Fisheries Research

Bernard A. Megrey

l

Erlend Moksness

Editors

Computers in Fisheries Research Second Edition

13

Editors Bernard A. Megrey U.S. Department of Commerce National Oceanic and Atmospheric Administration National Marine Fisheries Service Alaska Fisheries Science Center 7600 Sand Point Way N.E. Seattle, WA 98115 USA [email protected]

ISBN: 978-1-4020-8635-9

Erlend Moksness Institute of Marine Research Flødevigen Marine Research Station 4817 His Norway [email protected]

e-ISBN: 978-1-4020-8636-6

DOI: 10.1007/978-1-4020-8636-6 Library of Congress Control Number: 2008935557 # Springer ScienceþBusiness Media B.V. 2009 No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Printed on acid-free paper 9 8 7 6 5 4 3 2 1 springer.com

Preface

The first edition of this book was published by Chapman and Hall Ltd. in 1996. The first edition contained nine chapters and, for all except one chapter, the original chapter authors agreed to update their chapter. Comparing these chapters gives the reader an idea of the development over a time span of more than 10 years between the two editions. In the preparation of the second edition we decided to add more chapters reflecting some important fields with significant contributions to present day fishery research. These are the use of internet for searching of information (Chapter 2), and the present state and use of remote sensing (Chapter 5), ecosystem modeling (Chapter 8) and visualization of data (Chapter 10). This second edition provides a valuable sampling of contemporary applications. Scientists have an opportunity to evaluate the suitability of different computer technology applications to their particular research situation thereby taking advantage of the experience of others. The chapters that follow are the fruition of this idea. The history behind this book started in 1989 when we were asked by Dr. Vidar Wespestad (previously: Alaska Fisheries Science Center, Seattle, USA) to prepare and convene a session at the 1992 World Fishery Congress in Athens, Greece on computer applications in fisheries. We agreed that the idea was a good one and the computer session in 1992 turned out to be very successful. The computer session was organised in three parts: training classes, informal demonstrations accompanied by posters, and oral presentations of scientific papers. We were both amazed by the high level of interest and the high quality of contributions presented at the paper session. The following year we organised together with Dr. John Ramster (Previously: Fishery Laboratory, Lowestoft, England) a theme session on the topic ‘‘Computers in Fisheries Research’’ at the ICES (International Council for the Exploration of the Sea) statutory meeting in Dublin, Ireland. The response we received from the call for papers exceeded our most optimistic expectations. A total of 62 abstracts were submitted. Nigel J. Balmforth (then at Chapman and Hall Ltd.) who attended the World Fisheries Congress, asked us to consider preparing an outline for a book on the topic. Based on our two recent experiences, we knew that the interest level in the international fisheries community was high and we were convinced that there was a need for such a book and that the idea was timely v

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since we determined that a book that reviews current and future computer trends in fisheries science applications did not exist. Individuals are quick to realize the potential of computers in fisheries and more scientists are taking advantage of these new tools. We believe this book will be of interest to any quantitative resource management course, fisheries course, or application of computers to fisheries course. It should also be useful as a background reading requirement for graduate and undergraduate students taking the above mentioned courses. Academic institutions with agriculture, fisheries or resource management programs, national fisheries laboratories, and library systems should find the book useful. The book will also prove useful to administrators, managers, research scientists, field biologists, university researchers, university teachers, graduate and undergraduate students, consultants, government researchers, and laypersons involved in the fisheries or natural resource disciplines. Finally we would like to say that we are very grateful for the positive response we received from all the chapter authors during the preparation of this book. USA, Norway October 2008

Bernard A. Megrey Erlend Moksness

Contents

1

2

3

4

Past, Present and Future Trends in the Use of Computers in Fisheries Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bernard A. Megrey and Erlend Moksness

1

The Consumption and Production of Fisheries Information in the Digital Age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Janet Webster and Eleanor Uhlinger

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Extended Guide to Some Computerized Artificial Intelligence Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Saul B. Saila

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Geographical Information Systems (GIS) in Fisheries Management and Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Geoff Meaden

93

5

Remote Sensing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Olav Rune Godø and Eirik Tenningen

121

6

Quantitative Research Surveys of Fish Stocks . . . . . . . . . . . . . . . . . . . Kenneth G. Foote

145

7

Geostatistics and Their Applications to Fisheries Survey Data: A History of Ideas, 1990–2007. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Pierre Petitgas

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Ecosystem Modelling Using the Ecopath with Ecosim Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Marta Coll, Alida Bundy and Lynne J. Shannon

225

8

9

Image Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Thomas T. Noji and Ferren MacIntyre

293

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10

Contents

Visualization in Fisheries Oceanography: New Approaches for the Rapid Exploration of Coastal Ecosystems . . . . . . . . . . . . . . . Albert J. Hermann and Christopher W. Moore

317

11

Computers in Fisheries Population Dynamics. . . . . . . . . . . . . . . . . . . Mark N. Maunder, Jon T. Schnute and James N. Ianelli

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12

Multispecies Modeling of Fish Populations . . . . . . . . . . . . . . . . . . . . Kenneth A. Rose and Shaye E. Sable

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Computers and the Future of Fisheries . . . . . . . . . . . . . . . . . . . . . . . . Carl J. Walters

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Species Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Subject Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Contributors

Alida Bundy Fisheries and Oceans, Canada Bedford Institute of Oceanography, Dartmouth, PO BOX 1006, N.S., B2Y 4A2, Canada Marta Coll Institute of Marine Science (ICM-CSIC), Passeig Marı´ tim de la Barceloneta, 37-49, 08003 Barcelona, Spain Kenneth G. Foote Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA Olav Rune Godø Institute of Marine Research, Nordnes, 5817 Bergen, Norway Albert J. Hermann Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, WA 98115, USA James N. Ianelli U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Marine Fisheries Service, Alaska Fisheries Science Center, REFM Div., 7600 Sand Point Way NE, Seattle, WA 98115-6349, USA Ferren MacIntyre Expert-center for Taxonomic Identification, U. Amsterdam, NL-1090 GT Amsterdam, The Netherlands; National University of Ireland, University Road, Galway, Ireland Mark N. Maunder Inter-American Tropical Tuna Commission, 8604 La Jolla Shores Drive, La Jolla, CA 92037-1508, USA Geoff Meaden Department of Geographical and Life Sciences, Canterbury Christ Church University, North Holmes Road, Canterbury, Kent, CT1 1QU, UK Bernard A. Megrey U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Marine Fisheries Service, Alaska Fisheries Science Center, 7600 Sand Point Way NE, Seattle, WA 98115, USA Erlend Moksness Institute of Marine Research, Flødevigen Marine Research Station, 4817 His, Norway ix

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Contributors

Christopher W. Moore Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, WA 98115, USA Thomas T. Noji U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Marine Fisheries Service, Northeast Fisheries Science Center, Sandy Hook, NJ 07732, USA Pierre Petitgas IFREMER, Department Ecology and Models for Fisheries, BP. 21105, 44311 cdx 9, Nantes, France Kenneth A. Rose Department of Oceanography and Coastal Sciences, Louisiana State University, Baton Rouge, LA 70803, USA Shaye E. Sable Department of Oceanography and Coastal Sciences, Louisiana State University, Baton Rouge, LA 70803, USA Saul B. Saila 317 Switch Road, Hope Valley, RI 02832, USA Jon T. Schnute Fisheries and Oceans Canada, Pacific Biological Station, 3190 Hammond Bay Road, Nanaimo, B.C., V9T 6N7, Canada Lynne J. Shannon Marine and Coastal Management, Department of Environmental Affairs and Tourism, Private Bag X2, Rogge Bay 8012, South Africa; Marine Biology Research Centre, Department of Zoology, University of Cape Town, Private Bag, Rondebosch, 7701, South Africa Eirik Tenningen Institute of Marine Research, Nordnes, 5817 Bergen, Norway Eleanor Uhlinger Dudley Knox Library, Naval Postgraduate School, Monterey, CA 93943, USA Carl J. Walters Fisheries Centre, University of British Columbia, Vancouver, B.C., V6T1Z4, Canada Janet Webster Oregon State University Libraries, Hatfield Marine Science Center, 2030 Marine Science Drive, Newport, OR 97365, USA

Chapter 1

Past, Present and Future Trends in the Use of Computers in Fisheries Research Bernard A. Megrey and Erlend Moksness

I think it’s fair to say that personal computers have become the most empowering tool we’ve ever created. They’re tools of communication, they’re tools of creativity, and they can be shaped by their user. Bill Gates, Co-founder, Microsoft Corporation Long before Apple, one of our engineers came to me with the suggestion that Intel ought to build a computer for the home. And I asked him, ‘What the heck would anyone want a computer for in his home?’ It seemed ridiculous! Gordon Moore, Past President and CEO, Intel Corporation

1.1 Introduction Twelve years ago in 1996, when we prepared the first edition of Computers in Fisheries Research, we began with the claim ‘‘The nature of scientific computing has changed dramatically over the past couple of decades’’. We believe this statement remains valid even since 1996. As Heraclitus said in the 4th century B.C., ‘‘Nothing is permanent, but change!’’ The appearance of the personal computer in the early 1980s changed forever the landscape of computing. Today’s scientific computing environment is still changing, often at breathtaking speed. In our earlier edition, we stated that fisheries science as a discipline was slow to adopt personal computers on a wide-scale with use being well behind that in the business world. Pre-1996, computers were scarce and it was common for more than one user to share a machine, which was usually placed in a public area. Today, in many modern fisheries laboratories, it is common for scientists to use multiple computers in their personal offices, a desktop

B.A. Megrey (*) U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Marine Fisheries Service; Alaska Fisheries Science Center, 7600 Sand Point Way NE, BIN C15700, Seattle, WA 98115, USA

B.A. Megrey, E. Moksness (eds.), Computers in Fisheries Research, 2nd ed., DOI 10.1007/978-1-4020-8636-6_1, Ó Springer ScienceþBusiness Media B.V. 2009

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personal computer and a portable laptop is often the minimum configuration. Similarly, in many lab offices, there are several computers, each dedicated to a specific computational task such as large scale simulations. We feel that because of improvements in computational performance and advances in portability and miniaturization, the use of computers and computer applications to support fisheries and resource management activities is still rapidly expanding as well as the diversity of research areas in which they are applied. The important role computers play in contemporary fisheries research is unequivocal. The trends we describe, which continue to take place throughout the world-wide fisheries research community, produce significant gains in work productivity, increase our basic understanding of natural systems, help fisheries professionals detect patterns and develop working hypotheses, provide critical tools to rationally manage scarce natural resources, increase our ability to organize, retrieve, and document data and data sources, and in general encourage clearer thinking and more thoughtful analysis of fisheries problems. One can only wonder what advances and discoveries well known theorists and fisheries luminaries such as Ludwig von Bertalanffy, and William Ricker, or Ray Beverton and Sidney Holt would have made if they had had access to a laptop computer. The objective of this book is to provide a vehicle for fisheries professionals to keep abreast of recent and potential future developments in the application of computers in their specific area of research and to familiarize them with advances in new technology and new application areas. We hope to accomplish this by comparing where we find ourselves today compared to when the first edition was published in 1996. Hopefully, this comparison will help explain why computational tools and hardware are so important for managing our natural resources. As in the previous edition, we hope to achieve the objective by having experts from around the world present overview papers on topic areas that represent current and future trends in the application of computer technology to fisheries research. Our aim is to provide critical reviews on the latest, most significant developments in selected topic areas that are at the cutting edge of the application of computers in fisheries and their application to the conservation and management of aquatic resources. In many cases, these are the same authors who contributed to the first edition, so the decade of perspective they provide is unique and insightful. Many of the topics in this book cover areas that were predicted in 1989 to be important in the future (Walters 1989) and continue to be at the forefront of applications that drive our science forward: image processing, stock assessment, simulation and games, and networking. The chapters that follow update these areas as well as introduce several new chapter topic areas. While we recognize the challenge of attempting to present up to date information given the rapid pace of change in computers and the long time lines for publishing books, we hope that the chapters in this book taken together, can be valuable where they suggest emerging trends and future directions that impact the role computers are likely to serve in fisheries research.

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1.2 Hardware Advances It is difficult not to marvel at how quickly computer technology advances. The current typical desktop or laptop computer, compared to the original monochrome 8 KB random access memory (RAM), 4 MHz 8088 microcomputer or the original Apple II, has improved several orders of magnitude in many areas. The most notable of these hardware advances are processing capability, color graphics resolution and display technology, hard disk storage, and the amount of RAM. The most remarkable thing is that since 1982, the cost of a high-end microcomputer system has remained in the neighborhood of $US 3,000. This statement was true in 1982, at the printing of the last edition of this book in 1996, and it holds true today.

1.2.1 CPUs and RAM While we can recognize that computer technology changes quickly, this statement does not seem to adequately describe what sometimes seems to be the breakneck pace of improvements in the heart of any electronic computing engine, the central processing unit (CPU). The transistor, invented at Bell Labs in 1947, is the fundamental electronic component of the CPU chip. Higher performance CPUs require more logic circuitry, and this is reflected in steadily rising transistor densities. Simply put, the number of transistors in a CPU is a rough measure of its computational power which is usually measured in floating point mathematical operations per second (FLOPS). The more transistors there are in the CPU, or silicon engine, the more work it can do. Trends in transistor density over time, reveal that density typically doubles approximately every year and a half according to a well know axiom known as Moore’s Law. This proposition, suggested by Intel co-founder Gordon Moore (Moore 1965), was part observation and part marketing prophesy. In 1965 Moore, then director of R&D at Fairchild Semiconductor, the first large-scale producer of commercial integrated circuits, wrote an internal paper in which he drew a line though five points representing the number of components per integrated circuit for minimum cost for the components developed between 1959 and 1964 (Source: http://www.computerhistory.org/semiconductor/ timeline/1965-Moore.html, accessed 12 January 2008). The prediction arising from this observation became a self-fulfilling prophecy that emerged as one of the driving principals of the semiconductor industry. As it related to computer CPUs (one type of integrated circuit), Moore’s Law states that the number of transistors packed into a CPU doubles every 18–24 months. Figure 1.1 supports this claim. In 1979, the 8088 CPU had 29,000 transistors. In 1997, the Pentium II had 7.5 million transistors, in 2000 the Pentium 4 had 420 million, and the trend continues so that in 2007, the Dual-Core Itanium 2 processor has 1.7 billion transistors. In addition to transistor density, data

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Intel 4004

10000000000

Intel 8008 Intel 8080

1000000000

Intel 8088

log(Number of Transistors)

100000000

Intel 80286 Intel 80386

10000000

Intel 80486 Pentium

1000000

AMD K5 Pentium II

100000

AMD K6 Pentium III

10000

AMD K6-III AMD K7

1000

Pentium 4 Itanium

100

AMD K8 Itanium 2

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Core 2 Duo

1 1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010 Year

Core 2 Quad G80 POWER6 Dual-Core Itanium 2

Fig. 1.1 Trends in the number of transistors placed on various CPU chips. Note the y-axis is on the log scale (Source: http://download.intel.com/pressroom/kits/IntelProcessorHistory.pdf, accessed 12 January 2008)

handling capabilities (i.e. progressing from manipulating 8, to 16, to 32, to 64 bits of information per instruction), ever increasing clock speeds (Fig. 1.2), and the number of instructions executed per second, continue to improve. The remarkable thing is that while the number of transistors per CPU has increased more than 1,000 times over the past 26 years, and another 1,000 times since 1996, performance (measured with millions of instructions per second, MIPS) has increased more than 10,000 times since the introduction of the 8088 (Source: http://www.jcmit.com/cpu-performance.htm, accessed 12 January 2008). Scientific analysts, who use large databases, scientific visualization applications, statistics, and simulation modeling need as many MIPS as they can get. The more powerful computing platforms described above will enable us to perform analyses that we could not perform earlier (see Chapters 8, 11 and 12). In the original edition we predicted that ‘‘Three years from now CPU’s will be four times faster than they are today and multi-processor designs should be commonplace.’’ This prediction has generally proven to be true. CPU performance has continued to increase according to Moore’s Law for the last 40 years, but this trend may not hold up in the near future. To achieve higher transistor densities requires the manufacturing technology (photolithography) to build the transistor in smaller and smaller physical spaces. The process architecture of

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Maximum Intel CPU Clock Speed (GHz)

4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 Year

Fig. 1.2 Trends in CPU clock speed (Source: http://wi-fizzle.com/compsci/cpu_speed_Page_3.png, accessed 12 January 2008)

CPUs in the early 1970s used a 10 micrometer (mm, 10 6m) photolithography mask. The newest chips use a 45 nanometer (nm, 109m) mask. As a consequence of these advances, the cost per unit of performance as measured in gigaflops has dramatically declined (Fig. 1.3).

log(Cost per GFLOP $USD)

$100,000.00 $10,000.00 $1,000.00

$100.00 $10.00 $1.00 $0.10 1996

1998

2000

2002 Year

2004

2006

2008

Fig. 1.3 Trends in the cost ($USD) per gigaflop (109 floating point instructions s–1) of CPU performance. Note y-axis is on the log scale (Source: http://en.wikipedia.org/wiki/Teraflop, accessed 12 January 2008)

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Manufacturing technology appears to be reaching its limits in terms of how dense silicon chips can be manufactured – in other words, how many transistors can fit onto CPU chips and how fast their internal clocks can be run. As stated recently in the BBC News, ‘‘The industry now believes that we are approaching the limits of what classical technology – classical being as refined over the last 40 years – can do.’’ (Source: http://news.bbc.co.uk/2/hi/science/nature/4449711.stm, accessed 12 January 2008). There is a problem with making microprocessor circuitry smaller. Power leaks, the unwanted leakage of electricity or electrons between circuits packed ever closer together, take place. Overheating becomes a problem as processor architecture gets ever smaller and clock speeds increase. Traditional processors have one processing engine on a chip. One method used to increase performance through higher transistor densities, without increasing clock speed, is to put more than one CPU on a chip and to allow them to independently operate on different tasks (called threads). These advanced chips are called multiple-core processors. A dual-core processor squeezes two CPU engines onto a single chip. Quad-core processors have four engines. Multiple-core chips are all 64-bit meaning that they can work through 64 bits of data per instruction. That is twice rate of the current standard 32-bit processor. A dual-core processor theoretically doubles your computing power since a dual-core processor can handle two threads of data simultaneously. The result is there is less waiting for tasks to complete. A quad-core chip can handle four threads of data. Progress marches on. Intel announced in February 2007 that it had a prototype CPU that contains 80 processor cores and is capable of 1 teraflop (1012 floating point operations per second) of processing capacity. The potential uses of a desktop fingernail-sized 80-core chip with supercomputer-like performance will open unimaginable opportunities (Source: http://www.intel.com/ pressroom/archive/releases/20070204comp.htm, accessed 12 January 2008). As if multiple core CPUs were not powerful enough, new products being developed will feature ‘‘dynamically scalable’’ architecture, meaning that virtually every part of the processor – including cores, cache, threads, interfaces, and power – can be dynamically allocated based on performance, power and thermal requirements (Source: http://www.hardwarecentral.com/hardwarecentral/ reports/article.php/3668756, accessed 12 January 2008). Supercomputers may soon be the same size as a laptop if IBM brings to the market silicon nanophotonics. In this new technology, wires on a chip are replaced with pulses of light on tiny optical fibers for quicker and more power-efficient data transfers between processor cores on a chip. This new technology is about 100 times faster, consumes one-tenth as much power, and generates less heat (Source: http://www.infoworld.com/article/07/12/06/IBM-researchers-build-supercomputeron-a-chip_1.html, accessed 12 January 2008). Multi-core processors pack a lot of power. There is just one problem: most software programs are lagging behind hardware improvements. To get the most out of a 64-bit processor, you need an operating system and application programs that support it. Unfortunately, as of the time of this writing, most

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software applications and operating systems are not written to take advantage of the power made available with multiple cores. Slowly this will change. Currently there are 64-bit versions of Linux, Solaris, and Windows XP, and Vista. However, 64-bit versions of most device drivers are not available, so for today’s uses, a 64-bit operating system can become frustrating due to a lack of available drivers. Another current developing trend is building high performance computing environments using computer clusters, which are groups of loosely coupled computers, typically connected together through fast local area networks. A cluster works together so that multiple processors can be used as though they are a single computer. Clusters are usually deployed to improve performance over that provided by a single computer, while typically being much less expensive than single computers of comparable speed or availability. Beowulf is a design for high-performance parallel computing clusters using inexpensive personal computer hardware. It was originally developed by NASA’s Thomas Sterling and Donald Becker. The name comes from the main character in the Old English epic poem Beowulf. A Beowulf cluster of workstations is a group of usually identical PC computers, configured into a multi-computer architecture, running a Open Source Unix-like operating system, such as BSD (http://www.freebsd.org/, accessed 12 January 2008), Linux (http://www.linux.org/, accessed 12 January 2008) or Solaris (http://www.sun.com/software/solaris/index.jsp?cid=921933, accessed 12 January 2008). They are joined into a small network and have libraries and programs installed that allow processing to be shared among them. The server node controls the whole cluster and serves files to the client nodes. It is also the cluster’s console and gateway to the outside world. Large Beowulf machines might have more than one server node, and possibly other nodes dedicated to particular tasks, for example consoles or monitoring stations. Nodes are configured and controlled by the server node, and do only what they are told to do in a disk-less client configuration. There is no particular piece of software that defines a cluster as a Beowulf. Commonly used parallel processing libraries include Message Passing Interface; (MPI, http://www-unix.mcs.anl.gov/mpi/, accessed 12 January 2008) and Parallel Virtual Machine, (PVM, http://www.csm.ornl.gov/pvm/, accessed 12 January 2008). Both of these permit the programmer to divide a task among a group of networked computers, and recollect the results of processing. Software must be revised to take advantage of the cluster. Specifically, it must be capable of performing multiple independent parallel operations that can be distributed among the available processors. Microsoft also distributes a Windows Compute Cluster Server 2003 (Source: http://www.microsoft.com/windowsserver2003/ccs/ default.aspx, accessed 12 January 2008) to facilitate building a high-performance computing resource based on Microsoft’s Windows platforms. One of the main differences between Beowulf and a cluster of workstations is that Beowulf behaves more like a single machine rather than many workstations. In most cases client nodes do not have keyboards or monitors, and are

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accessed only via remote login or through remote terminals. Beowulf nodes can be thought of as a CPU + memory package which can be plugged into the cluster, just like a CPU or memory module can be plugged into a motherboard. (Source: http://en.wikipedia.org/wiki/Beowulf_(computing), accessed 12 January 2008). Beowulf systems are now deployed worldwide, chiefly in support of scientific computing and their use in fisheries applications is increasing. Typical configurations consist of multiple machines built on AMD’s Opteron 64-bit and/or Athlon X2 64-bit processors. Memory is the most readily accessible large-volume storage available to the CPU. We expect that standard RAM configurations will continue to increase as operating systems and application software become more full-featured and demanding of RAM. For example, the ‘‘recommended’’ configuration for Windows Vista Home Premium Edition and Apple’s new Leopard operating systems is 2 GB of RAM, 1 GB to hold the operating system leaving 1 GB for data and application code. In the previous edition, we predicted that in 3–5 years (1999–2001) 64–256 megabytes (MB) of Dynamic RAM will be available and machines with 64 MB of RAM will be typical. This prediction was incredibly inaccurate. Over the years, advances in semiconductor fabrication technology have made gigabyte memory configurations not only a reality, but commonplace. Not all RAM performs equally. Newer types, called double data rate RAM (DDR) decrease the time in takes for the CPU to communicate with memory, thus speeding up computer execution. DDR comes in several flavors. DDR has been around since 2000 and is sometimes called DDR1. DDR2 was introduced in 2003. It took a while for DDR2 to reach widespread use, but you can find it in most new computers today. DDR3 began appearing in mid-2007. RAM simply holds data for the processor. However, there is a cache between the processor and the RAM: the L2 cache. The processor sends data to this cache. When the cache overflows, data are sent to the RAM. The RAM sends data back to the L2 cache when the processor needs it. DDR RAM transfers data twice per clock cycle. The clock rate, measured in cycles per second, or hertz, is the rate at which operations are performed. DDR clock speeds range between 200 MHz (DDR200) and 400 MHz (DDR-400). DDR-200 transfers 1,600 megabits per second (Mb s1:106 bits s1), while DDR-400 transfers 3,200 MB s1. DDR2 RAM is twice as fast as DDR RAM. The bus carrying data to DDR2 memory is twice as fast. That means twice as much data are carried to the module for each clock cycle. DDR2 RAM also consumes less power than DDR RAM. DDR2 speeds range between 400 MHz (DDR2-400) and 800 MHz (DDR2-800). DDR2-400 transfers 3,200 MB s1. DDR2-800 transfers 6,400 MB s1. DDR3 RAM is twice as fast as DDR2 RAM, at least in theory. DDR3 RAM is more powerefficient than DDR2 RAM. DDR3 speeds range between 800 MHz (DDR3-800) and 1,600 MHz (DDR3-1600). DDR3-800 transfers 6,400 MB s1; DDR3-1600 transfers 12,800 MB s1. As processors increased in performance, the addressable memory space also increased as the chips evolved from 8-bit to 64-bit. Bytes of data readily

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accessible to the processor are identified by a memory address, which by convention starts at zero and ranges to the upper limit addressable by the processor. A 32-bit processor typically uses memory addresses that are 32 bits wide. The 32-bit wide address allows the processor to address 232 bytes (B) of memory, which is exactly 4,294,967,296 B, or 4 GB. Desktop machines with a gigabyte of memory are common, and boxes configured with 4 GB of physical memory are easily available. While 4 GB may seem like a lot of memory, many scientific databases have indices that are larger. A 64-bit wide address theoretically allows 18 million terabytes of addressable memory (1.8 1019 B). Realistically 64-bit systems will typically access approximately 64 GB of memory in the next 5 years.

1.2.2 Hard Disks and Other Storage Media Improvements in hard disk storage, since our last edition, have advanced as well. One of the most amazing things about hard disks is that they both change and don’t change more than most other components. The basic design of today’s hard disks is not very different from the original 5¼’’ 10 MB hard disk that was installed in the first IBM PC/XTs in the early 1980s. However, in terms of capacity, storage, reliability and other characteristics, hard drives have substantially improved, perhaps more than any other PC component behind the CPU. Seagate, a major hard drive manufacturer, estimates that drive capacity increases by roughly 60% per year (Source: http://news.zdnet.co.uk/communications/ 0,100,0000085,2067661,00.htm, accessed 12 January 2008). Some of the trends in various important hard disk characteristics (Source: http://www.PCGuide.com, accessed 12 January 2008) are described below. The areal density of data on hard disk platters continues to increase at an amazing rate even exceeding some of the optimistic predictions of a few years ago. Densities are now approaching 100 Gbits in2, and modern disks are now packing as much as 75 GB of data onto a single 3.5 in platter (Source: http://www. fujitsu.com/downloads/MAG/vol42-1/paper08.pdf, accessed 12 January 2008). Hard disk capacity continues to not only increase, but increase at an accelerating rate. The rate of technology development, measured in data areal density growth is about twice that of Moore’s law for semiconductor transistor density (Source: http://www.tomcoughlin.com/Techpapers/head&medium.pdf, accessed 12 January 2008). The trend towards larger and larger capacity drives will continue for both desktops and laptops. We have progressed from 10 MB in 1981 to well over 10 GB in 2000. Multiple terabyte (1,000 GB) drives are already available. Today the standard for most off the shelf laptops is around 120–160 GB. There is also a move to faster and faster spindle speeds. Since increasing the spindle speed improves both random-access and sequential performance, this is likely to continue. Once the domain of high-end SCSI drives (Small Computer System Interface), 7,200 RPM spindles are now standard on mainstream desktop and

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notebook hard drives, and a 10,000 and 15,000 RPM models are beginning to appear. The trend in size or form factor is downward: to smaller and smaller drives. 5.25 in drives have now all but disappeared from the mainstream PC market, with 3.5 in drives dominating the desktop and server segment. In the mobile world, 2.5 in drives are the standard with smaller sizes becoming more prevalent. IBM in 1999 announced its Microdrive which is a tiny 1 GB or device only an inch in diameter and less than 0.25 in thick. It can hold the equivalent of 700 floppy disks in a package as small as 24.2 mm in diameter. Desktop and server drives have transitioned to the 2.5 in form factor as well, where they are used widely in network devices such as storage hubs and routers, blade servers, small form factor network servers and RAID (Redundant Arrays of Inexpensive Disks) subsystems. Small 2.5 in form factor (i.e. ‘‘portable’’) high performance hard disks, with capacities around 250 GB, and using the USB 2.0 interface are becoming common and easily affordable. The primary reasons for this ‘‘shrinking trend’’ include the enhanced rigidity of smaller platters. Reduction in platter mass enables faster spin speeds and improved reliability due to enhanced ease of manufacturing. Both positioning and transfer performance factors are improving. The speed with which data can be pulled from the disk is increasing more rapidly than positioning performance is improving, suggesting that over the next few years addressing seek time and latency will be the areas of greatest attention to hard disk engineers. The reliability of hard disks is improving slowly as manufacturers refine their processes and add new reliability-enhancing features, but this characteristic is not changing nearly as rapidly as the others above. One reason is that the technology is constantly changing, and the performance envelope is constantly being pushed; it’s much harder to improve the reliability of a product when it is changing rapidly. Once the province of high-end servers, the use of multiple disk arrays (RAIDs) to improve performance and reliability is becoming increasingly common, and multiple hard disks configured as an array are now frequently seen in consumer desktop machines. Finally, the interface used to deliver data from a hard disk has improved as well. Despite the introduction to the PC world of new interfaces such as IEEE-1394 (FireWire) and USB (universal serial bus) the mainstream interfaces in the PC world are the same as they were through the 1990s: IDE/ATA/SATA and SCSI. These interfaces are all going through improvements. A new external SATA interface (eSATA) is capable of transfer rates of 1.5–3.0 Gbits s1. USB transfers data at 480 Mbits s1 and Firewire is available in 400 and 800 Mbits s1. USB 3.0 has been announced and it will offer speeds up to 4.8 Gbits s1. Firewire will also improve to increases in the range of 3.2 Gbits s1. The interfaces will continue to create new and improved standards with higher data transfer rates to match the increase in performance of the hard disks themselves. In summary, since 1996, faster spindle speeds, smaller form factors, multiple double-sided platters coated with higher density magnetic coatings, and improved recording and data interface technologies, have substantially increased hard disk storage and performance. At the same time, the price per

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unit of storage has decreased (Fig. 1.4). In 1990, a typical gigabyte of storage cost about $US 20,000 (Kessler 2007). Today it is less than $US 1. The total hard disk capacity shipped as of 2003 (Fig. 1.5) indicates exponentially

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increasing capacity through time. Today 2.5’’ 250 GB hard disks are common and multiple terabyte hard disks collected together in RAID configurations provide unprecedented storage capacity. The trends continue as recently Seagate announced research into nanotube-lubricated hard disks with capacities of several terabits per square inch, making possible a 7.5 TB 3.5 in hard disk (Source: http://www.dailytech.com/article.aspx?newsid¼3122&ref¼y, accessed 12 January 2008). Hard disks are not the only available storage media. Floppy disks, formerly a mainstay of portable storage, have become a thing of the past. Today computers are rarely shipped with floppy disk drives. At one time, Iomega’s portable ZIP drives looked promising as a portable device to store about 200 MB of data. In 1996, we predicted that ‘‘Newer storage media such as read-write capable CD-ROM’s and WORM’s (write once read many times) will eventually displace floppy disks as the storage medium of choice’’. This has taken place and today even the CD-ROM, which in the past held promise for large capacity storage (700 MB) has been replaced with the ubiquitous ‘‘thumb drive’’ memory sticks. These marvels of miniaturization can accommodate 8–16 GB of data, use very fast USB 2.0 transfer interfaces, easily connect to any computer with a USB port, and are unusually inexpensive. As of the time of this writing a 4 GB USB 2.0 memory stick costs around $US 40. Double-sided rewritable DVD media are increasingly being used to easily store data in the 4–6 GB range.

1.2.3 Graphics and Display Technology In 1996, we predicted that in 3–5 years (1999–2001), support for 24-b color, full 3-D acceleration, broadcast quality video, and full-motion near-lifelike virtualreality capabilities would be commonplace. This forecast has proven to be true. The very first video card, released with the first IBM PC, was developed by IBM in 1981. The MDA (monochrome display adapter) only worked in text mode representing 2580 lines in the screen. It had a 4 KB video memory and just one color. Today’s graphic cards offer radically improved capabilities. Modern video cards have two important components. The first is the GPU (graphics processing unit). This dedicated microprocessor, separate from the main CPU, is responsible for resolution and image quality. It is optimized for floating point calculations, which are fundamental to 3D graphics rendering. The GPU also controls many graphic primitive functions such as drawing lines, rectangles, filled rectangles, polygons and the rendering of the graphic images. Ultimately, the GPU determines how well the video card performs. The second important component is the video RAM (or vRAM). In older graphics cards, system RAM was used to store images and textures. But with a dedicated video card, built-in vRAM takes over this role, freeing up system RAM and the main CPU for other tasks. When it comes to vRAM, there are a variety of options. If

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you’re just doing simple tasks, 64 MB is adequate. If you’re editing video, 128 MB should be the minimum, with larger amounts up to 512 MB – 1 GB available for more demanding tasks. Also as a general rule, the more powerful the GPU, the more vRAM it will require. Modern video cards also incorporate high speed communication channels that allow large amounts of graphic data to pass quickly through the system bus. Today’s video cards also contain multiple output options including S-video, super VGA (SVGA), Digital Video Interface (DVI), and High Definition Multimedia Interface (HDMI) connections are common as well as options for up to 32-b and 64-b colors, and resolutions approaching 2,5601,600 at very fast refresh rates in the range of 85 Hz. The very newest cards include television tuners, some even offering the newly emerging Highdefinition standard. This feature is mainly relevant to home computer systems for those who want to turn their computer into a personal video recorder. We are convinced a scientific application for this feature will become useful in the years to come. The ability to produce graphics is just one piece of the graphics system, with the other being the display device. Old large and power hungry analog monitors are slowly being replaced by digital Liquid Crystal Display (LCD) panels, the latter appearing sometimes in large (19–22 in) formats. LCD monitors are sleeker than bulky cathode-ray tube models and they are more energy efficient. Some LCD monitors consume 1/2 to 2/3 the energy of traditional monitors. Since Windows XP was released, with its expanded desktop feature, dual LCD monitor desktop computers have become more common. The increased popularity of multi-display systems has to do with advances in technology as well as economics. Though Windows 98 first allowed for dual display configurations, the bulky analog CRTs that sat on most desks and workspaces simply could not accommodate more than one monitor. Flat-panel displays solved the space problem. Originally expensive they were considered a luxury, with prices often exceeding $US 1000. Resolution increased along with the ability to pack more and more transistors into the LCD panel, and today’s monitors, by contrast, are just a fraction of original cost. Today a good quality 22 in LCD monitor costs around $US 300. That means adding a second or third monitor is comparable to the cost of some of the original models. Research shows that there is a productivity benefit that is almost immediate. Numerous studies estimate productivity increases of anywhere from 10 to 45% (Russel and Wong 2005; Source: http://www.hp.com/sbso/solutions/ finance/expert-insights/dual-monitor.html, accessed 12 January 2008). Efficiency experts suggest that using two LCD monitors improves efficiency by up to 35% and researchers at Microsoft also found similar results, reporting that workers increased their productivity 9–50% by adding a second or third monitor. (Source: http://www.komando.com/columns/index.aspx?id¼1488 accessed, 12 January 2008).

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1.2.4 Portable Computing Another recent trend is the appearance of powerful portable computer systems. The first portable computer systems (i.e. ‘‘luggables’’) were large, heavy, and often portability came at a cost of reduced performance. Current laptop, notebook, and subnotebook designs are often comparable to desktop systems in terms of their processing power, hard disk, and RAM storage and graphic display capabilities. In 1996, we observed that ‘‘It is not unusual, when attending a scientific or working group meeting, to see most participants arrive with their own portable computers loaded with data and scientific software applications.’’ Today, it is unusual to see scientists attending technical meetings arrive without a portable computer. Since 1996, the performance and cost gap between notebooks and desktops capable of performing scientific calculations has continued to narrow, so much so, that the unit growth rate of notebook computers is now faster than for desktops. With the performance gap between notebooks and desktop systems narrowing, commercial users and consumers alike are beginning to use the notebooks more and more as a desktop replacement since the distinction between the two as far as what work can be accomplished is becoming more and more blurred. Moreover, the emergence of notebook ‘‘docking stations’’ allows the opportunity to plug notebooks into laboratory network resources when scientists are in their office and then unplug the notebook at the end of the day to take it home or on the road, all the while maintaining one primary location for important data, software, working documents, literature references, email archives, and internet bookmarks. We have seen that miniaturization of large capacity hard disk storage, memory sticks, printers, and universal access to email made available via ubiquitous Internet connectivity (see below) all contribute to a portable computing environment, making the virtual office a reality.

1.3 Coping with Oceans of Data The information explosion is well documented. Information stored on hard disks, paper, film, magnetic, and optical media doubled from 2000 to 2003, expanding by roughly 5 EB (exabytes: over 5 billion gigabytes) each year or about 800 MB per person per year (Lyman and Varian 2003). These authors present, as of 2003, an intriguing look into the volume of digital information produced worldwide, where it originates and interesting trends through time. For example, in the United States we send, on average, 5 billion instant messages and 31 billion emails each day (Nielsen 2006). The trend is clear for scientific pursuits; the growth of data is one of the biggest challenges facing scientists today. As computer software and hardware improve, the more sensors we place into the biosphere, the more satellites we

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put into orbit, the more model runs we perform, the more data that can be – and is being – captured. In fact, Carlson (2006) tells us, ‘‘Dealing with the ‘data deluge,’ as some researchers have called it, along with applying tested methods for controlling, organizing and documenting data will be among the great challenges for science in the 21st century.’’ Unfortunately, having more data does not mean we are able to conduct better science. In fact, massive volumes of data can often become detrimental to scientific pursuits. Data originating from different sources can sometimes be conflicting and certainly require ever increasing resources, hardware and maintenance. Someone once said: ‘‘We are drowning in data, but starving of information’’. We feel this is particularly true for fisheries data. In addition to the ever increasing quantity of data we add the vexing problems of harmonizing heterogeneous data collected on different spatial and temporal scales and the ever present problem of inappropriate use of online data because the metadata are missing (Chapter 5). Documenting data by writing metadata is a task scientists are reluctant to undertake, but a necessary step that will allow efficient data discovery as volumes of data continue to grow. Scientists have been struggling with this issue for years and metadata software solutions are scarce and often inadequate. Metadata will be a major issue in the coming decade. Below we present some current examples of the increasing amounts of data we are required to accommodate. Current generation general ocean circulation models using the Regional Ocean Modeling System (ROMS; Source: https://www.myroms.org/, accessed 24 December 2007) linked to lower trophic level (NPZ) ecosystem models (see Chapter 10) using typical grid spacing (3 km horizontal and 30 vertical levels, giving 462  462 horizontal gridpoints) over a typical ocean domain such as the central Gulf of Alaska (Hermann, in press, Chapter 10) generates 484 MB of output a day (where all the physical and biological variables are saved at every horizontal/vertical gridpoint). Hence a full model year of daily output from this model generates up 484 MB  365 = 176 GB (Albert Hermann, pers. comm., NOAA, Pacific Marine Environmental Laboratory). If a relatively short time series of model simulations (say 10 years) were permanently archived, it would require almost 2 TB (TB, 1,000 GB) of storage. Data collection rates for a typical shipboard acoustic echosounder system (see Chapter 5), such as the Simrad EK60 using 3 frequencies (3 frequencies at 1 ms pulse to 250 m contains 3,131 pings; 1 frequency ¼ 16.7 MB) generates about 50 MB of data. A hypothetical acoustic mooring designed to measure down to 250 m will generate about 4 MB h1 or about 50 MB day1. In the case of a typical groundfish survey, the echosounder will generate about 95 MB1.2 GB h1, depending on the ping rate (Alex deRoberts, pers. comm. NOAA, Alaska Fisheries Science Center). Finally, newer multibeam systems, such as the Simrad ME70 will collect 10–15 GB h1 for typical applications (see e.g. Ona et al. 2006). Many of our ‘‘standard’’ field data collection devices (i.e. measuring boards, scales, and net sampling equipment) are now digital and, interact with other

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on-board ship sensors (i.e. GPS) providing large amounts of additional quality controlled information. For example, our old paradigm of net measurement (i.e. spread and height) has improved over the last decade with the use of depth sensors and bottom contact sensors. The amount of potential additional net information is about to explode with the use of automated net mensuration systems capable of providing height, spread, bottom contact, temperature, depth, net symmetry, speed, geometry of the codend, fish density, distance and angle of the net relative to the boat and even net damage reporting. In addition, there is a rapidly expanding flow of information from sounders and enhanced sonar devices capable of providing many data streams regarding the sea bottom condition and hardness, currents and other sea states. This means that even traditional data sources have the potential to rapidly expand in quantity and metadata requirements. Cabled ocean observing systems, such as VENUS (Victoria Experimental Network Under the Sea) (Source: http://www.martlet.ca/view.php?aid¼38715, accessed 12 January 2008) and NEPTUNE (North-East Pacific Time-Series Undersea Networked Experiments) (Source: http://www.neptunecanada.ca/ documents/NC_Newsletter_2007Aug31F.pdf, accessed 12 January 2008), off the North American west coast, are some of the world’s first regional permanent ocean observatories. The observing system consists of undersea nodes to regulate and distribute power and provide high bandwidth communications (4 GBs1) through fiber-optic cable, connecting more than 200 instruments and sensors, such as video cameras, a 400 m vertical profiler (to gather data at various ocean depths) and a remotely operated vehicle, as they collect data and imagery from the ocean surface to beneath the seafloor. The existing VENUS node is similarly configured and collecting data at a rate of 4 GB per day. John Dower (pers. comm.), affiliated with the NEPTUNE and VENUS cabled observing system, characterized the problems associated with coping with the vast amounts of data being delivered from ‘‘always on’’ data streams such as these new cabled system as trying to take a ‘‘Drink from a fire hose’’. The Intergovernmental Panel on Climate Change (IPCC) coordinated scientists at 17 major climate modeling centers throughout the world to run a series of climate models under various standard prescribed climate scenarios to examine the anticipated affect of factors contributing to climate change. They then prepared climate assessment reports, the most recent being the Fourth Assessment Report or AR4 (IPCC 2007). The massive output files are archived at the Lawrence Livermore National Laboratory (Source: http://www-pcmdi.llnl.gov/, accessed 12 January 2008) and are made available to the scientific community for analysis. These data consist of 221 output files from different ‘‘experiment scenario/model’’ combinations and the data volume totals approximately 3 TB. Remote sensing equipment such as the ARGO system is a global array of about 3,000 free-drifting profiling ARGO floats (Fig. 1.6) that measures the temperature and salinity of the upper 2,000 m of the ocean. The floats send their data in real-time via satellites to ARGO Global Data Acquisition Centers (GADC). Data from 380,472 individual profiles are instantly available at the

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Fig. 1.6 Location of 3071 active ARGO floats which have delivered data within the past 30 days, as of 25 December 2007) (Source: http://www.argo.ucsd.edu/Acindex.html, accessed 25 December 2007)

GDACs including 168,589 high quality profiles provided by the delayed mode quality control process. Google Earth can be used to track individual floats in real-time (Source: http://w3.jcommops.org/FTPRoot/Argo/Status/, accessed 12 January 2008). This amazing resource allows, for the first time, continuous monitoring of the temperature, salinity, and velocity of the upper ocean, with all data being relayed and made publicly available within hours after collection (Source: http://www.argo.ucsd.edu/Acindex.html, accessed 12 January 2008). Satellites offer another example of broadband high capacity data delivery systems. The Advanced Very High Resolution Radiometer (AVHRR) data set is comprised of data collected by the AVHRR sensor and held in the archives of the U.S. Geological Survey’s EROS Data Center. AVHRR sensors, carried aboard the Polar Orbiting Environmental Satellite series, consist of a 4- or 5-channel broad-band scanning radiometer, sensing in the visible, nearinfrared, and thermal infrared portions of the electromagnetic spectrum (Source: http://edc.usgs.gov/guides/avhrr.html, accessed 12 January 2008). The AVHRR sensor provides for global (pole to pole) on board collection of data from all spectral channels. Each pass of the satellite provides a 2,399 km (1,491 mi) wide swath. The satellite orbits the Earth 14 times each day from 833 km (517 mi) above its surface. The objective of the AVHRR instrument is to provide radiance data for investigation of clouds, land-water boundaries, snow and ice extent, ice or snow melt inception, day and night cloud distribution, temperatures of radiating surfaces, and sea surface temperature. Typical data file sizes are approximately 64 MB per a 12 min (in latitude-longitude coordinates) sampling swath per orbit. The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) is another example of a satellite system designed to provide quantitative data on global ocean bio-optical properties to the Earth science community (Source: http://oceancolor.gsfc.nasa. gov/SeaWiFS/, accessed 12 January 2008). Subtle changes in ocean color, and

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in particular surface irradiance on every band, signify various types and quantities of marine phytoplankton (microscopic marine plants), the knowledge of which has both scientific and practical applications. Since an orbiting sensor can view every square kilometer of cloud-free ocean every 48 h, satelliteacquired ocean color data provide a valuable tool for determining the abundance of ocean biota on a global scale and can be used to assess the ocean’s role in the global carbon cycle and the exchange of other critical elements and gases between the atmosphere and the ocean. The concentration of phytoplankton can be derived from satellite observations of surface irradiance and quantification of ocean color. This is because the color in most of the world’s oceans in the visible light region, (wavelengths of 400–700 nm) varies with the concentration of chlorophyll and other plant pigments present in the water (i.e. the more phytoplankton present, the greater the concentration of plant pigments and the greener the water). A typical SeaWiFS SST file of sea surface temperature for 1 day from the MODUS sensor can be as large as 290 MB. On-line databases of compiled and quality controlled data are another source of large quantities of information. Examples include biological databases such as a comprehensive database of information about fish (FishBase) that includes information on 29,400 species (Source: http://www.fishbase.org/, accessed 12 January 2008), a database on all living cephalopods (octopus, squid, cuttlefish and nautilus) Cephbase (Source: http://www.cephbase.utmb.edu/, accessed 12 January 2008), Dr. Ransom Myer’s Stock Recruitment Database consists of maps, plots, and numerical data from over 600 fish populations (over 100 species) from all over the world (Source: http://www.mscs.dal.ca/myers/welcome.html, accessed 12 January 2008), Global Information System about fish larvae (LarvalBase) (Source: http://www.larvalbase.org/, accessed 28 December 2007), the FAO Statistical Database consists of a multilingual database currently containing over 1 million time-series records from over 210 countries (Source: http://www.fao.org/waicent/ portal/statistics_en.asp, accessed 12 January 2008), not to mention the numerous catch and food habits databases, often consisting of tens of millions of records. Even given the sometimes overwhelming quantity of data, one trend that has definitely happened in the last decade is the movement of data from flat ASCII files and small ad-hoc databases (i.e. EXCEL spreadsheets) into relational databases with designs based on actual data relationships and collection methodology. This has been a very important and powerful step towards control of data quality. Hopefully, the problems mentioned at the beginning of this section can be addressed with the tremendous advancements in hardware mentioned above as well as software advances covered in the next section.

1.4 Powerful Software At the time of the last writing of this book, application software was only available from commercial sources. Since 1996, a remarkable development has taken place – Open Source software (free source code) is widely available

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for almost any purpose and for almost any CPU platform. Open Source software is developed by an interested community of developers and users. As Schnute et al. (2007) eloquently put it, ‘‘Open source software may or may not be free of charge, but it is not produced without cost. Free software is a matter of liberty, not price. To understand the concept, one should think of free as in free speech, not as in free beer’’. To our knowledge, no one has attempted to estimate the true cost of Open Source software. Some notable examples of Open Source or no cost software includes operating systems such as Fedora Linux (Source: http://fedoraproject.org/, accessed 12 January 2008); web sever software by Apache (Source: http://www.apache.org/, accessed 12 January 2008); high level numerical computing software such as Octave (Source: http://www.gnu.org/software/octave/, accessed 12 January 2008) and SciLab (Source: http://www.scilab.org/, accessed 12 January 2008) which is similar to MATLAB; statistical software such as R (source: http:// www.r-project.org/, accessed 12 January 2008) and WinBUGS; (Lunn et al. 2000; Source: http://www.mrc-bsu.cam.ac.uk/bugs/winbugs/contents.shtml, accessed 12 January 2008) for implementing Bayesian statistics; compilers such as the GNU Family of Compilers for C (Source: http://gcc.gnu.org/, accessed 12 January 2008) and FORTRAN (Source: http://www.gnu.org/software/ fortran/fortran.html, accessed 12 January 2008); plotting software, also from the GNU development team (Source: http://www.gnu.org/software/ fortran/fortran.html, accessed 12 January 2008 and www.gnuplot.info/ accessed 12 January 2008); database software such as MySQL (Source: http://www.mysql.com/, accessed 12 January 2008); software business productivity programs such as OpenOffice (Source: http://www.openoffice.org/, accessed 12 January 2008); ecosystem modeling software such as Ecopath with Ecosim (Source: http://www.ecopath.org/, accessed 12 January 2008) and the newly released fisheries library in R (FLR, Kell et al. 2007) (Source: http:// www.flr-project.org/, accessed 12 January 2008). Many other offerings can be located at the Free Software Foundation (Source: http://www.fsf.org/, accessed 12 January 2008). Similar to our previous observation, we still see software functionality and growing feature sets advancing in lockstep with improvements in computer hardware performance and expanded hardware capability. Today’s application software packages are extremely powerful. Scientific data visualization tools and sophisticated multidimensional graphing applications facilitate exploratory analysis of large complex multidimensional data sets and allow scientists to investigate and undercover systematic patterns and associations in their data that were difficult to examine several years ago. This trend enables users to focus their attention on interpretation and hypothesis testing rather on the mechanics of the analysis. Software that permits the analysis of the spatial characteristics of fisheries data are becoming more common. Programs to implement geostatistical algorithms (see Chapter 7) and Geographic Information System (GIS) software (see Chapter 4) have made significant advances that offer the fisheries biologist the ability to consider this most important aspect of natural

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populations in both marine and freshwater ecosystems. Image analysis software (see Chapter 9) also offers promise in the areas of pattern recognition related to fisheries science such as identification of taxa, fish age determination and growth rate estimation, as well as identifying species from echo sounder sonar records. Highly specialized software such as neural networks and expert systems (see Chapter 3), which in the past have received limited application to fisheries problems, are now becoming commonplace. Very advanced data visualization tools (see Chapter 10) offer exciting new research opportunities heretofore unavailable to fisheries scientists. Whole ecosystem analysis tools (see Chapter 8) allow the simultaneous consideration of the entirety of the biological components that make up these dynamic systems. The marriage of powerful computer systems to remote sensing apparatus and other electronic instrumentation continues to be an area of active research and development (see Chapter 5). The area of population dynamics, fisheries management, stock assessment and statistical methodology software (see Chapters 11 and 12), long a mainstay of computer use in fisheries, continues to receive much attention.

1.5 Better Connectivity No aspect of our scientific lives remains untouched by the World Wide Web and Internet connectivity. The explosive growth of the Internet over the last decade has led to an ever increasing demand for high-speed, ubiquitous Internet access. The Internet is the fastest growing communication conduit and has risen in importance as the information medium of first resort for scientific users, basically achieving the prominence of a unique, irreplaceable and essential utility. How did we do our jobs without it? In 1996, we predicted that ‘‘the Internet, other network, and Wide-AreaNetwork connectivity resources held great promise to deliver global access to a vast and interactive knowledge base. In addition, the Internet would provide to the user a transparent connection to networks of information and more importantly people.’’ This has largely proven to be true and compared to today’s Internet resources, it may seem as a bit of an understatement. Compared to 12 years ago, access has improved, speed has increased, content has exploded providing significantly more resources available over the web. We feel it is true to say that the Internet is considered the method of choice for communication in scientific circles. O’Neill et al. (2003) present a nice summary of trends in the growth of the web, current as of 2003. Figure 1.7 depicts the steadily increasing trend in the number of Internet host servers on line (Source: http://www.isc.org/index.pl?/ops/ds/host-count-history.php, accessed 12 January 2008) and the large and growing community of users (Fig. 1.8) (Source: http://www.esnips.com/doc/f3f45dae-33fa-4f1f-a780-6cfbce8be558/Internet-Users, accessed 12 January 2008; 2007 statistics from: http://www.internetworldstats.com/ stats.htm, accessed 12 January 2008). These data show that the number of hosts

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and users have increased 5.071% and 3.356%, respectively since 1996. Lyman and Varian (2003) estimate that the web accounted for 25–50 TB of information. Most electronic communication flows through four main channels: radio and television broadcasting, telephone calls and the Internet. The Internet, the

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newest electronic information medium, has proven to be capable of subsuming all three other communication channels. Digital TV stations are broadcast over IPTV (Internet Protocol Television is a system where digital television service is delivered by using Internet Protocol over a network infrastructure; See Section 1.6). We believe this relatively quick transition is a prelude of what opportunities we can expect in the near future. Today, there are three basic options available to access the Internet: The oldest method is dial-up access. Back in 1996, dial-up was one of the few options for many scientists to connect to the Internet, mainly through commercial Internet providers such as America On Line. During this era, typical fisheries laboratories did not have broadband connections or significant within-lab Internet resources (i.e. application servers, distributed electronic databases, web pages, etc.). Even email connectivity was slow by today’s standards. As the Internet grew, with its emphasis on visual and multimedia delivery, it presented a problem for the dial-up community. So much so that web pages offered ‘‘image free’’ versions of their content with the intention to speed up access to the core of their content. Ironically, in today’s telecommunication environment, this is the exact situation for the fledgling web-enabled cell phone and Personal Digital Assistant (PDA) customers. Eventually, the speed of dial-up modems simply could not accommodate the abundant digital content desired by web users. The progression of modem speed was impressive at first: 1,200 baud, 3,600, 9,600 baud. No end was in sight. But the expanding and band-width consuming Internet content continued to push the envelope. Eventually, even the speedy 56,000 baud modem was too slow. It was simply not fast enough to carry multimedia, such as sound and video except in low quality. In modern digital societies, dial-up is the method of last resort. If you are using dial-up, it is clear that either broadband access is not available, or that broadband access is too expensive. We suggest, that today, the main communication link to the web and the Internet for fisheries and resource scientists within their offices is via high-speed connections such as T1 or T3 lines (often connected via fiber optic cable) or access to proven high-speed technologies such as cable modems and digital subscriber lines (DSL). While it is true that individual situations vary, we feel confident saying that within-laboratory internet connectivity has come a long way compared to 12 years ago and we expect it will continue to improve with alarming speed. The most recent major change in Internet interconnectivity developments since 1996 involves the almost ever-present wireless Internet access. Trends in wireless communications today are vast and exciting and accelerating at the high speeds they employ. Twelve years ago, we felt privileged as scientists, if we had the opportunity to attend a meeting or working group venue that had wireless connectivity to the Internet. At the time, these services were supplied by visionary venue hosts and often our laptops were not even capable of accessing wireless signals without external adapters connected to USB or PCMCIA ports.

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Most laptops manufactured today come with Wi-Fi cards already built-in. Once the laptop’s Wi-Fi capability is turned on, software usually can detect an access point’s SSID – or ‘‘service set identifier’’ – automatically, allowing the laptop to connect to the signal without the user having to intervene. Today’s portable laptops, almost without exception, utilize some variation of the Intel Centrino CPU, which has a wireless mobile chipset, wireless interface, and WiFi adapter embedded directly onto the computational CPU. Thus, Wi-Fi capability is already built in. Wireless extends beyond Internet connectivity. We have wireless computers; wireless Internet, WANs, and LANs; wireless keyboards and mice; pagers and PDAs; and wireless printers, scanners, cameras, and hubs. The potential is very real for our children to say, ‘‘What is a cable?’’ Today, we don’t feel it is an over exaggeration to say that scientists expect SOME level of Internet connectivity when they are outside of their laboratory environment. This includes meeting locations, workshop venues, alternate work locations, not including public access points located at places such as airports, local hot spots, hotels. A minimum is access to email – and the expectation is that both hardware and software tools will be available to accomplish communication with the parent laboratories or distant colleagues. Even better would be to have access, via wired or wireless connections to files at the home lab for interactions or demonstrations for such things as examination of virtual databases, access to simulation model animations, or the ability to instantaneously access working documents, PDF publications, or library resources. Since the last edition of this book, not only has wireless connectivity become commonplace, it has gone through several iterations of improvements. The Institute of Electrical and Electronic Engineers (IEEE) standard or protocol, known as 802.11, began with the 802.11B version (a data transfer rate of around 11 Mbits s1 (Mbps) using the 2.4 G HZ band with a range of 38 m), then progressed to 802.11 G (a data transfer rate of 54 Mbps using the same 2.4 GHz band as 802.11 B with similar range) and now the emerging standard is 802.11 N (over 248 Mbps using the 5 GHz and 2.4 GHz spectrum bands and a wider range of 70 m). This is just about as fast as can be experienced over a hard-wired network. With each new iteration of the Wi-Fi standard, transmission speed and range are generally improved. Lyman and Varian (2003) report the number of users who connect wirelessly has doubled from 2002. They estimate that 4% or roughly 1.4 million users now access the Internet without wires. Just 1 year later, the estimate was updated to be over 40,000 hot spots catering to over 20 million users. Hot spots are Wi-Fi locations setup to provide Internet access through a wireless network to nearby computers. This extraordinary explosion of access points and users is a testimony to the utility and demand for Wi-Fi Internet access. Current estimates suggest that there are 100,000 Wi-Fi hot spots worldwide (Source: http://www.jiwire.com/about/ announcements/press-100k-hotspots.htm, accessed 12 January 2008). Data indicate that Europe has the fastest annual growth (239%: Source: http://ipass.com/

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pressroom/pressroom_wifi.html, accessed 12 January 2008), with most of that annual growth (255%) taking place in hotel venues (Source: http://ipass.com/ pressroom/pressroom_wifi.html, accessed 12 January 2008). The wide adoption of Wi-Fi and its rapid growth help scientists gradually become familiar with this new means of Internet access. We typically search for Wi-Fi hot spots while we are away from the home or office. Many airports, coffee bars, hotels and motels now routinely provide these services, some for a fee and some for free. According to projections, over 90 million laptops and personal digital assistants (PDAs) will have ready to access Wi-Fi LANs and local hot spots. This technology is not without problems. The main problem with wired broadband access is that it requires a cost-based subscription and it does not reach all areas. The main problem with Wi-Fi access is that hot spots are physically small, so coverage is sparse and spatially very localized. WiMAX (Worldwide Interoperability for Microwave Access) was designed to solve these problems. WiMAX, which is based on the IEEE 802.16 standard, is a new telecommunications technology designed to provide wireless data over long distances. The expectation is that WiMAX will be considered an alternative to wired broadband like cable and DSL since it will provide universal wireless access, where almost everywhere is a ‘‘hot spot’’. In practical terms, WiMAX would operate similar to Wi-Fi but at higher speeds, over greater distances and for a greater number of users. WiMAX can provide broadband wireless access up to 30 mi (50 km) for fixed stations, and 3–10 mi (5–15 km) for mobile stations. In contrast, the Wi-Fi/802.11 wireless local area network standard is limited in most cases to only 100–300 feet (30–100 m). WiMAX could potentially erase the suburban and rural blackout areas that currently have no broadband Internet access because phone and cable companies have not yet run the necessary wires to those remote locations. Another trend that is beginning to impact scientific activity is the growth of smaller devices to connect to the Internet and the convergence of cellular phones, other portable devices, and computers. Small tablets, pocket PCs, smart phones, and even GPS devices are now capable of tapping into the web, further advancing the realization of true mobile computing. Output from real time data streams from Ocean Observing Systems such as the Alaska Ocean Observing System (Source: http://ak.aoos.org/op/data.php?region¼AK, accessed 12 January 2008) can now be viewed on web-enabled hand-held mobile devices.

1.5.1 Security Increased levels of unwanted and malevolent computer intrusions are a regrettable outcome of better connectivity. They have grown so rapidly in recent years that they are no longer just an aggravation. A recent report estimates that in 2000, hacking attacks and computer viruses cost global businesses around 40,000 human years in lost productivity equaling about $US1.6 trillion dollars

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(Source: http://www.vnunet.com/vnunet/news/2113080/hackers-viruses-costbusiness-6tn, accessed 12 January 2008). The Internet was not designed with security in mind. It follows the democratic philosophy of open sharing. Because everything is interconnected, everything is vulnerable. For example, SPAM (unsolicited bulk email) is considered a threat because SPAM often contains malicious attachments. If the attachment is opened, it may unleash a virus. Because of overly aggressive SPAM filters placed on our email systems to protect us from malicious SPAM, email has become an unreliable form of communication. All too many times legitimate emails go undelivered or unread because they are incorrectly identified as SPAM. According to figures reported in Lyman and Varian (2003), unsolicited bulk email make up 40% of all email traveling over the Internet. In addition there are other serious attacks and threats delivered via email such as viruses, worms (software that attach to and take control of a normal program then spread to other computers). Very aggressive viruses can spread quickly. For example, the Sapphire/Slammer worm, released in February 2003, required roughly 10 min to spread worldwide. In the early stages of infection, the number of compromised hosts doubled every 8.5 s. At its peak infection rate, achieved approximately 3 min after it was released, the virus scanned over 55 million IP address per second and infected 1 in 12 emails on the Internet (Source: http://www.caida.org/research/security/sapphire/, accessed 12 January 2008). Other threats include, phishing (using email to search for valuable information such as a credit card number), trojan horses (software that appearing to be useful but is in reality malicious), and system monitors (software that tracks everything the user does, then emails it back to the author of the malicious software). Adware (software to display unwanted adds) and Spyware (software to secretly monitor and record what a user types) can also be serious as they tend to degrade system performance. Many of the hacker tools that required in-depth knowledge a few years ago to implement these threats have been automated and are much easier to use. A consequence to fisheries computer users is the unanticipated constraints or restrictions information technology administrators place on our use of computers because of real or perceived threats to system security. We need increased security to protect us, our computers and the computer network resources we rely on. Typically, computer security efforts focus on keeping ‘‘outsiders’’ out, through physical and technical measures such as gates, guards, passwords, locks and firewalls. In today’s computing environment, it is absolutely necessity to use virus protection software with current virus definition files. We are now often required to use ‘‘strong’’ passwords that have to be changed on a frequent schedule, use Virtual Private Network (VPN) software to remotely gain secure access to computer network resources contained behind firewalls, or encrypt entire laptop computer hard disks. As unfortunate as this situation appears, the reality is that serious computer hackers are in a cat-and-mouse dance with security professionals. We expect security issues to remain a part of the computing landscape for many years to come.

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1.6 Collaboration and Communication The old paradigm of scientific communication consisted of publishing research results in peer-reviewed printed publication outlets such as journals and books. Collaborations took place mainly through face-to-face meetings and attending scientific workshops and conferences. Today, these reliable and still pervasive outlets remain important, but we have many other alternatives for scientific communication and collaboration. It is not uncommon today, some would say required, for a scientist to prepare their research results in several different mediums and formats such a written paper for publication in a published journal or one of the newer open access digital journals, a PowerPoint presentation published on the web, and a personal or laboratory web page. Email is currently one of the most widespread and pervasive methods of communication. Extrapolated from data supplied by the International Data Corporation, and reported by Lyman and Varian (2003), it is estimated that the current worldwide email volume amounts to about 60 billion emails a day or the equivalent of 1,829 TB daily or 3.35 PB (PB: 1015 B) annually. Lyman and Varian (2003) offer more intriguing statistics that were valid 4 years ago: email ranks second behind the telephone for the largest information flow; 60% of workers with email access receive 10 or fewer messages on an average day, 23% receive more than 20, and 6% more than 50. They estimate that workers spend an hour or less per day on email. They also report that 78% of workers send 10 or fewer messages on an average day and that 11% send more than 20. In our 1996 edition, we mentioned the benefits of using electronic communication and the benefits of the Internet to help us organize the book, especially email. By our current thinking and expectations, it would be unthinkable to contemplate organizing and planning an endeavor such as the second edition of this book without the benefits of email and the Internet. The decreasing cost of video capture and display technology along with widely available high speed Internet connectivity has fostered the increased use of personal video teleconference systems based on webcams, personal computer systems, and software compression. Use of video conferencing saves valuable time and reduces the cost of collaborations since often it removes or reduces the need to travel. The hardware used for this technology continues to improve in quality, prices have dropped dramatically, and the availability of freeware (often as part of chat programs) has made software based videoconferencing accessible to many. Voice over Internet Protocol (VOIP) is a common and widely used protocol developed for the transmission of voice though the Internet. Software products have been built around this new technology allowing instantaneous voice communications between two or more people using computers connected to the Internet. Typically these computers are portable laptops with a built in or externally attached digital video camera. There are many capable software programs to facilitation communication and collaboration via VOIP. Video

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conferencing services that use VOIP are common today on most free instant message clients, such as Yahoo! Messenger (Source: http://messenger.yahoo.com/, accessed 12 January 2008) and MSN Messenger (Source: http://join.msn.com/messenger/ overview2000, accessed 12 January 2008) or the newer Windows Live Messenger (Source: http://get.live.com/messenger/features, accessed 12 January 2008). Skype is another widely used free software program using VOIP that allows users to make telephone calls from their computer to other Skype users free of charge, or to landlines and cell phones for a fee (Source: http://www.skype.com/, accessed 12 January 2008). All tools provide very similar features sets including video conferencing, instant messaging, text messaging, PC-mobile messaging, file transfer, and an ability to circumvent firewalls. One new developing medium to facilitate communication are blogs or on-line diaries where commentaries or news on a particular subject are placed for users to read. Communication is the key focus and readers can leave comments in an interactive format. A typical blog combines text, images, and links to other blogs, web pages, and other media related to its topic. As of December 2007, blog search engine Technorati was tracking more than 112 million blogs (Source: http:// en.wikipedia.org/wiki/Technorati, accessed 12 January 2008). Blogs related to the aquatic sciences exist as well. Some examples of marine and freshwater blogs are: ‘‘Thoughts from Kansas’’ (Source: http://scienceblogs.com/tfk, accessed 12 January 2008), MarineBio Blog (Source: http://marinebio.org/blog/?cat¼2, accessed 12 January 2008), blogs about fisheries (Source: http://www.blogtoplist. com/rss/fisheries.html, accessed 12 January 2008), What is Your Ecotype (Source: http://whatsyourecotype.blogspot.com/, accessed 12 January 2008), and John’s Marine and Environmental Blog (Source: http://jmcarroll-marinebio. blogspot.com/2007/10/letter-to-national-marine-fisheries.html, accessed 12 January 2008). LISTSERV, a pervasive mailing list manager, is also a newer medium for communication. Recent estimates suggest that LISTSERV’s sends approximately 30 million messages a day using approximately 300,000 mailing lists (Lyman and Varian 2003). Finally, we remind readers of the pervasiveness of PowerPoint or similar presentation software as a medium of communication. In the past, presentations at scientific meetings were made predominately using 35 mm slides and overhead transparencies. Now, it is rare to see these approaches used. Almost without exception, scientific results are communicated using presentation software such as PowerPoint, running on a computer connected to a digital computer projector. On many university campuses, open lectures are delivered using PowerPoint presentations. Often PowerPoint presentations given at scientific meetings are published to the web as a record of the meeting and a resource for those unable to attend the meeting. For example, the North Pacific Marine Science Organization (PICES) routinely performs this service (Source: http:// www.pices.int/publications/presentations/default.aspx, accessed 12 January 2008).

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1.7 Summary We will see further miniaturization of the microcomputer, increased capacity both in terms of processing speed, memory and storage capacity, and relatively stable prices. Although we eagerly anticipate these changes, we probably will never be satisfied. As performance levels markedly improve so to will the complexity of our work, the size of the data sets we are expected to handle, and our expectations of ‘‘minimum system configuration’’ and ‘‘adequate performance’’. The desire for faster machines, better graphics, and larger hard disks will not go away in the near future. Computer software will continue to provide expanded analysis capabilities to fisheries professionals. We now have microcomputer operating systems that surpass what were commonly available on large mainframe computers many years ago, communication tools that make world-wide communication not only possible but fun, great suites of consistent, powerful productivity applications, personal database applications with sophisticated development and data management tools, and wider availability of highly specialized fisheries analysis programs. Better connectivity allows fisheries scientists to more easily communicate with colleagues within the scientific community who they might not otherwise have the opportunity to meet as well as external clients. Increased microcomputer connectivity holds great promise for research collaboration and synthesis activities. Opportunities abound for scientists to effectively communicate the value and relevance of their research findings to all audiences. The Internet is a proven technology, already traveled by billions of users around the world, and it will continue to open new frontiers that are difficult to imagine today. Moreover, it will provide expanded capabilities to share databases, computer programs, and experience. Carl Walters realized the benefits of an expansion of networked microcomputers and predicted this outcome back in 1989 (Walters 1989). Storage and sharing of fisheries database and historic information products is encouraging the systematic analysis of past fisheries information and facilitating inter-regional comparison of fisheries experience. Very often data sets from a scientific perspective become valuable when they become longer in length and one is able to put the data into perspective. Environmental data sets are most valuable after they are long enough to sample the target phenomenon multiple times. It is only when we start collecting data more regularly and routinely that we gain immense understanding into various processes. We see opportunities for scientists to ask increasingly broader questions as they focus their attention on processing and analyzing large volumes of data. Our ability to understand the fast paced and considerable changes we observe gives us a distinct advantage when dealing with complex multidisciplinary issues. Improvements in hardware and software performance will help investigators sift through increasing amounts of data in a much more powerful way or

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execute computationally intensive statistical models such as the 550 parameter stock assessment model that includes a Bayesian Markov Chain Monte Carlo (MCMC) analysis (Iannelli et al. 2007). Through these activities, a deeper understanding of the data will improve the design of studies that look for associations between components of the biosphere on spatial and temporal scales relevant to biological and ecological systems. New and upcoming technologies will soon permit the ability to built truly integrated fisheries ecosystem models. For example, fine-scale biogeochemical-physical models dynamically coupled with spatially-explicit multi-trophic level ecosystem models will soon be commonplace, thus allowing holistic examination of the ecosystem and the response of its species-to-species interrelationships to management or climate change scenarios. Common patterns and trends may emerge as data sets are shared, made available for quick retrieval and analysis, and accompanied by companion data sets such as vast oceanographic and meteorological data libraries. One of the ongoing challenges will be the development of tools to provide this capacity to process large volumes of raw data and to make it available in real time over the Internet. Computers, fisheries research, and the resulting synergism are indeed exciting. We think that it is true that in any branch of science computers are essential. You can often set yourself apart as a valuable scientist and researcher by learning and using advanced computational tools (i.e. going beyond using basic computer applications). A necessary and valuable skill of future scientists will be to have some knowledge of how to solve problems and being able to look at a problem and come up with a computer solution. We hope the chapters in this book contribute to the development of this skill set. The following collection of papers, while not intended to be comprehensive, do characterize the breadth and sophistication of the application of computers to modern fisheries analysis, and documents the progression in advances in technology and their application to fisheries and resource management problems. We believe that the topics covered here are a prelude to new future opportunities and we anticipate with enthusiasm the challenges ahead.

References Carlson S (2006) Lost in a sea of science data. The Chronicle of Higher Education, Information Technology Section 52(42):A35 (Source: http://chronicle.com/free/v52/i42/42a03501.htm, accessed 12 January 2008). Hermann AJ, Hinckley S, Dobbins EL, Haidvogel DB, Mordy C (in press) Quantifying crossshelf and vertical nutrient flux in the Gulf of Alaska with a spatially nested, coupled biophysical model. Progress in Oceanography. Iannelli JN, Barbeaux S, Honkalehto T, Kotwicki S, Aydin K, Williamson N (2007) Eastern bering sea pollock. In: National Marine Fisheries Service Stock Assessment and Fishery Evaluation Report for the Groundfish Resources of the Bering Sea/Aleutian Islands Region in 2007. North Pacific Fishery Management Council, Anchorage, AK.

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IPCC (2007) Climate Change (2007) Synthesis Report. Intergovernmental Panel on Climate Change. Kell LT, Mosqueira I, Grosjean P, Fromentin J-M, Garcia D, Hillary R, Jardim E, Mardle S, Pastoors MA, Poos JJ, Scott F, Scott RD (2007) FLR: an open-source framework for the evaluation and development of management strategies. ICES Journal of Marine Science 64:640–646. Kessler M (2007) Days of officially drowning in data almost upon us. USA Today, Technology News, March, 05, 2007 (Source: http://www.usatoday.com/tech/news/2007-03-05-data_ N.htm accessed 12 January 2008). Lunn DJ, Thomas A, Best N, Spiegelhalter D (2000) WinBUGS – a Bayesian modelling framework: concepts, structure, and extensibility. Statistics and Computing 10:325–337. Lyman P, Varian HR (2003) How much information? School of Information Management and Systems, University of California at Berkeley (Source: http://www2.sims.berkeley. edu/research/projects/how-much-info-2003/, accessed 12 January 2008). Moore GE (1965) Cramming more components onto integrated circuits. Electronics Magazine 38(8) (April 19, 1965). Nielsen JL (2006) Thoughts from Kansas. President’s hook. Fisheries 31(10):480, 514–515. Ona E, Dalen J, Knudsen HP, Patel R, Andersen LN, Berg S (2006) First data from sea trials with the new MS70 multibeam sonar. Journal Acoustic Society of America 120:3017–3018. O’Neill ET, Lavoie BF, Bennett R (2003) Trends in the evolution of the public web. D-Lib Magazine, 9(4), April 2003 (Source: http://www.dlib.org/dlib/april03/lavoie/04lavoie.html, accessed 12 January 2008). DOI: 10.1045/april2003-lavoie. Russell SE, Wong K (2005) Dual-Screen monitors: a qualitative analysis of their use in an academic library. The Journal of Academic Librarianship 31(6):574–577. Schnute JT, Maunder MN, Ianelli JN (2007) Designing tools to evaluate fishery management strategies: can the scientific community deliver? ICES Journal of Marine Science 64:1077–1084. Walters CJ (1989) Development of microcomputer use in fisheries research and management. In: Edwards EF, Megrey BA (eds.) Mathematical Analysis of Fish Stock Dynamics. American Fisheries Society Symposium 6:3–7.

Chapter 2

The Consumption and Production of Fisheries Information in the Digital Age Janet Webster and Eleanor Uhlinger

2.1 The Fisheries Information Life Cycle Fisheries scientists persistently create, communicate, and use information. In fact, if they did not, there would be no fisheries science. To exist, science must be part of a continuum where shared information, from casual hallway communications to rigorously reviewed articles, documents the questions asked and the solutions suggested. Relevant information is critical to the success of basic and applied fisheries research projects. Identifying the relevant at the beginning of a project and then communicating what is important out of the project are elements of the life cycle of fisheries information. Both have become simultaneously easier and more difficult as the amount of information increases within the digital environment. The access to information is simpler and yet more nuanced. As producers and consumers, we sustain the life cycle of fisheries information. We learn to consume information as students, often modeling our behavior from our professors. They give us a stack of reprints to read, and those articles become the foundation for our exploration into fisheries sciences. Or, we start with a pivotal article and work back through its references and forward through its sphere of influence defined by citations. Now, new alerting tools and search engines broaden our information horizons, enriching our perspectives while obscuring the relevant through the deluge. Consumption can be a feast of delectable facts, theories, datasets and findings or an orgy of the same leaving indigestion rather then satisfaction. This changing information environment also affects scientists as producers of information. We are faced with a plethora of publishing options where once there were only a few selective journals. We can publish in highly specialized titles with limited audiences, target the mainstream with high impact journals, issue findings electronically through blogs or web sites, or present at conferences where all becomes part of a streaming video record. The decisions we make when J. Webster (*) Oregon State University Libraries, Hatfield Marine Science Center, 2030 Marine Science Drive, Newport, OR 97365, USA

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producing information are no longer straightforward, but require thought and preparation so the information produced is consumable and not half-baked or forgotten on a back shelf. The information life cycle has not changed fundamentally with the advent of computers, the Internet and digital resources. However, the environmental factors affecting how we produce and consume information have changed. A major factor is the growth of the digital network and how that shapes the ways information is published, disseminated and accessed. We should consider other factors as well when thinking about how to effectively consume and produce information. Fisheries science is no longer just about natural science; we need to increase our awareness of the information from the social sciences as the problems we address often have significant human components to them. The scale we work within has expanded as long term datasets become available, as genetic work reveals finer granularity, and as geographic limits diminish with extended global networks. The breadth of sources widens and we look to non-scientists for assistance with local information and insight. All these factors shape how we use information in our work. All enrich, yet none make it easier as they demand more decisions throughout the scientific process. The following attempts to assist with that decision making by describing approaches, options and challenges to consuming relevant information and then producing, or communicating, the same. On the consumption side, we will discuss how to identify, obtain and manage fisheries information. As tools change, the focus will be on strategies with specific examples of current tools. On the production end, we will explain the decisions to be made regarding intended audiences and possible outlets, publishing options, copyright considerations, access points, and archiving responsibilities. Finally, we will return to the electronic information environment to put the consumption strategies and publishing decisions into a larger context. Here we will touch on the economics of publishing and access, possible legal issues, the concept of the digital library, and information integrity and preservation.

2.2 Consuming Information 2.2.1 Identifying Fisheries Information There is a Chinese proverb that states: ‘‘Void of a long-term plan will bring you trouble soon.’’ This proves applicable to that point when you are starting a project. You need to consider your question and then your strategy for finding the answer. Uncovering the pertinent literature is a critical strategic step. Starting by typing keywords into Googleä returns reams of information, but often with a degree of randomness that may leave a queasy feeling of missing the right pieces.

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Before starting to look for information, it is useful to carefully think about what types of information you are looking for, who may produce it, and where it might appear. Then, you can tackle how to find it. Here are examples of questions to consider at this step in your research strategy.

 Broad or narrow topic?











The level of specificity may indicate where to start and where to look for information. The bigger or less focused the question, typically the more broadly you will need to look to identify as much relevant information as possible. It is difficult to answer a broad fisheries question such as the effect of global warming on salmon populations, by only referring to the work of population dynamics researchers. Limited geographic scope or global? If the problem is highly localized, you will want to concentrate on local information, yet with an eye on how others may have addressed the same problem. If global, the sources will be multinational and perhaps multi-lingual. Applied or basic research? The research continuum from basic to applied is paralleled by an information continuum. As research moves towards the more applied, different sources of information become more useful such as trade publications, patents, and government documents. Science or policy? Many fisheries questions have policy implications. So, it is smart to be aware of information that may be outside the normal scientific communication channels. Who? Understanding who has worked on the question provides a starting point as does considering who may have funded research or be interested in the outcome. Organizations as well as individuals may have a vested interest in the issue. Where? Related to the Who question is where the topic may be discussed. This suggests not only which journals may contain articles, but also which conferences or electronic discussion forums may address the topic. Considering where the conversation is generated may provide insight into where to look for current information as well as possible audiences for future communication.

2.2.2 The Tools Another proverb suggests that ‘‘A long march starts from the very first step.’’ That step after considering the types of information is identifying what tools may be helpful. These range from the general to the very specialized, from classic to contemporary, and from free to very expensive. All have a place in the information gathering process, but some will prove easier to use, more relevant,

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or more accessible depending on your circumstances and need. Tools change over time; some may become obsolete while new ones are developed. In the following, some specific tools are described with a discussion of their strengths and weaknesses in terms of content and access. They are grouped to help you identify the types of tools and then which ones you may be able to access given individual circumstances. 2.2.2.1 General Science Indexes These broad, science indexes generally cover the core fisheries literature adequately. They are solid starting points as you will find the major fisheries journals as well those in related fields such as ecology, biology and zoology. They are not the complete universe of fisheries literature, though. Additionally, almost all of those described are accessible through paid subscriptions only. Pricing usually depends on the size of the institution (e.g. number of FTEs) and size of the database (e.g. number of years covered). Web of Scienceâ Formerly known as the ISI Science Citation Index, the current electronic iteration continues to provide access to a broad suite of science journals in multiple disciplines. (A master journal list is available from the Thomson Scientific web site – www.thomsonscientific.com.) First published in the early 1960s, its continuing strength is its capacity to relate articles through citations allowing a user to investigate who is citing whom, who is working on related topics, and what are a topic’s core papers. Other resources such as CiteSeer, Google Scholarä and Scopusä are beginning to track citation patterns but currently not with the same accuracy (Roth 2005; Jacso´ 2006a). Its greatest weakness is the lack of coverage of monographs, conference proceedings, and report literature. It is also one of the most expensive general science databases so access may be very limited unless your institution subscribes. Subscriptions to Web of Scienceâ are priced in part by number of 5 year blocks of records; access to a complete range of years covered by the index increases the cost. While powerful, the search interface is not clean using some jargon that for occasional users makes searching challenging. The display of results can be cryptic until familiarity is gained with use. Web of Scienceâ remains the deepest general science index in chronological coverage and consistency of sources indexed. Its sister index, Web of Social Scienceâ, shares the same interface and is similar in construction and purpose. It is useful for delving in to the social and economics sides of fisheries. BIOSIS The tomes of Biological Abstracts are now electronically accessible as Biosis. This classic index for biological information covers over 6,500 journals

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including the core fisheries titles. Coverage includes some conference proceedings and reports. Its strength is its longevity (in print since 1927 with electronic access from the 1970s) and the depth of the indexing making it very searchable by subject and keyword for the power user. Its weakness is the lack of consistent coverage of non-mainstream publications including foreign language material and trade titles. Access is through subscription and is expensive. It can be purchased through a variety of vendors who then offer access to it through their search interface. Scopusä Scopusä is Elsevier Publishing’s foray into the general scientific index arena complete with citation tracking. It is strong competition to Thomson’s Web of Scienceâ, but may do it less consistently with noticeable gaps in coverage (Jacso´ 2007). The types of publications covered are broad including: journal articles, conference proceedings, patents, books and trade journals. The journal literature makes up its core. The depth of coverage in temporal terms varies depending on the subject area; life and health sciences coverage extends back to 1966 while the social sciences are covered from 1996 forward. For fisheries, the major journals are covered but not all the book series or potentially useful trade publications. The search interface is straight forward and the results display versatile and readable. Scopusä is competition to Web of Scienceâ, yet remains an expensive alternative resource. 2.2.2.2 Specialized Indexes Fisheries scientists are fortunate to have subject-specific indexes providing deeper access to the published literature than the more general ones. Often starting broadly and then working to the specific is recommended as you may find material that is tangentially related in the broad searching and then can hone in on the very specific. The down side of this approach is the duplication you will encounter. The following two examples are primarily accessible through paid subscriptions. While not as expensive as the general science indexes, these still represent a sizable investment for an organization. Aquatic Sciences and Fisheries Abstracts (ASFA) In the late 1950s, fisheries scientists at the Food and Agriculture Organization of the United Nations (FAO) began compiling a bibliography of documents ‘‘which contribute to knowledge of living resources of the seas and inland waters’’ (Food and Agriculture Organization of the U.N. 1958). The goal was, and remains, to provide coverage of the world literature through an international cooperative effort of monitoring and entering relevant documents. This effort is administered by the ASFA Secretariat located within the FAO Fisheries Department who then partners with Cambridge Scientific Abstracts

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(CSA), a commercial publisher, to enhance and produce the database. The current database contains over one million citations from the early 1970s to the present; older ones are added selectively. Coverage ranges from the mainstream science journals to conference proceedings to national documents. Over 50 partners including international organizations (e.g. International Council for the Exploration of the Seas and Network of Aquaculture Centres of Asia-Pacific) and national institutions (e.g. CSIRO Marine Research and IFREMER) contribute to the database making it rich in content. The official list of partners is maintained on the ASFA Secretariat web site (ASFA Secretariat 2006). The geographic diversity and variety of research foci of the contributing partners are strengths of ASFA. For some, this diversity is distracting as there is considerable non-English material as well as citations to documents difficult to access (e.g. limited distribution). The traditional subject scope was on living resources and a more applied perspective. That has broadened as more ecological journals are now monitored. ASFA is inconsistent in its coverage of the social science side of fisheries and living resources; management documents are not always included due to the reliance on local partners to contribute what they deem important. CSA does not regularly include material from social science and development journals, instead adding more science citations. ASFA consists of five subsets:

    

Biological Sciences and Living Resources; Ocean Technology, Policy and Non-Living Resources; Aquatic Pollution and Environmental Quality; Aquaculture Abstracts; Marine Biotechnology Abstracts.

To many users, these subsets are transparent. To database vendors, the subsets are useful as they can be packaged separately or in multiple configurations depending on the audience. CSA packages the complete ASFA and allows users to select subsets to search. National Information Services Corporation (NISC), another database publisher, packages the Biological Sciences and Living Resources subset with other databases to create its popular product, Aquatic Biology, Aquaculture & Fisheries Resources. Most institutions subscribe to the online version of the database through CSA or NISC for a significant annual fee. Those who contribute to the database as a partner receive free access through the internet or by CD available from the ASFA Secretariat. Institutions in low income food deficit countries are also eligible for free access. ASFA remains an excellent specialized index for fisheries scientists.

Fish and Fisheries Worldwide National Information Services Corporation (NISC) created this citation database by combining various existing databases, some ongoing and some ceased. These include:

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FISHLIT (from the J.L.B. Smith Institute of Ichthyology) U.S. Fish and Wildlife Reference Service database A fish subset of MedLine South Africa’s Fishing Industry Research Institute Database Castell’s Nutrition References NOAA’s Aquaculture database

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This approach retains the value of older databases that are no longer maintained and enhances them with the addition of new material from other sources. Too often, older indexes become inaccessible as nobody sees the value of transforming them from a stand-alone database or a print bibliography. NISC attempts to capture such historic citation caches and build with them. Fish and Fisheries Worldwide is smaller than ASFA (less than 600,000), but very useful for its coverage of taxonomic records, sub-tropical freshwater fish, and U.S. local and federal government material. It also tends to cover some geographic areas more thoroughly than ASFA, Africa in particular. It is focused on fish and fisheries rather than the aquatic environment making it a useful tool for fisheries scientists. It is not as expensive as CSA’s ASFA making it attractive to institutions not needing the breadth of the full ASFA and looking for more specificity in some areas. Its interface is simple and quite intuitive for all levels of users.

2.2.2.3 The Worldwide Web as an Index The rapid growth of digital information builds the wealth of information available through web search engines. The Web still is a morass of information, good, bad and ugly. The search engines such as Googleä, Yahooâ and Askä are useful tools for sorting through the vast amount of digital information. As these engines evolve, their differences become more apparent and users should expect to see more differentiation in how they search and display results. Scientists need to know what sources they are searching. The established indexes such as BIOSIS and ASFA clearly explain what journals and sources they draw from; the web search engines are rarely as clear, and never as focused. However, they tend to cast a broad net, useful for establishing the scope of a project or trying to find something specific fast or with little effort. Whatever the reason for using a web search engine, it is how many start and end the quest for information. It has obvious and not so obvious problems, yet can yield satisfactory results. Fisheries scientists should recognize the limitations of web searches and know when to use indexes that will go deeper into the literature. This entails checking the ‘‘about’’ on each search engines home page. Rarely does a company specify exactly how they are searching and ranking the results of the search. However, a user can get an idea and recognize why different engines come up with different results. Googleä was the first, and holds the patent, on the search and ranking system referred to as page-ranking (Page et al. 1998).

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The algorithm considers how many pages are linking to the specific page as well as relative importance of the referring page. Askä tweaks the page-ranking by attempting to cluster like pages and analyses the relationship among those pages, thus returning pages that link within a topic area and not those random linkages. Some, such as Yahooâ, integrate paid or sponsored sites into the rankings; while this practice probably does not affect search results for fisheries science information, it could for fisheries trade information. In contrast, searches within the indexes described earlier are worked through a closed set of citations with field tags (e.g. author, keyword, title) so results are ranked by matches to the contents of the fields searched and not by the complexities of relative importance among the citations. It is a controlled information environment as compared to the wide open Web. Yet, the convenience of a simple interface and direct links to the full text of articles make web search engines attractive. The rest of the information world – database vendors and libraries included – scrambles to package their resources with as simple an interface. They are also tailoring what is searched and how to provide the scholarly audience search tools that integrate with existing work patterns and computer desktops. Scirus from Elsevier and Google Scholarä are examples of free multidisciplinary indexing and abstracting databases.

Google Scholarä (http://scholar.google.com/) Googleä launched this service in 2004 with much fanfare. In essence, it is a subset of the Web providing access to ‘‘peer-reviewed papers, theses, books, abstracts and articles, from academic publishers, professional societies, preprint repositories, universities and other scholarly organizations’’ (Google 2005). Yet, it does not specify which publishers and institutions participate leaving the user to guess or take it on faith that the coverage is broad and wide (Jacso´ 2005a). Additionally, it is unclear how often and how deep various sites are mined for results, leaving gaps in coverage revealed if the publisher’s site is searched directly (Jacso´ 2005a). Research conducted on its coverage and utility suggest that it is stronger in the sciences than social sciences and has a definite English language bias (Neuhaus et al. 2006). The search interface is familiar and simple with an advanced option that increases its utility. The links to full text articles (if the user’s institution has implemented the service) make searching and getting items more efficient. With the addition of citations to the search results, some suggest that Google Scholarä can replace Web of Scienceâ or the newer, Scopus (Pauly and Stergiou 2005) while others urge scholars to use it in addition to the more structured databases (Bauer and Bakkalbasi 2005). The fisheries scientist will find it an easy place to start, but should continue exploring the literature in one of the specialized indexes for more thorough coverage of the field’s varied information.

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Scirus (http://www.scirus.com/) Elsevier Publishing started this free search service focused on its deep database of articles and over time has added other sources such as patent data and electronic theses and dissertations (Pruvost et al. 2003). Unlike Google Scholarä, Scirus is open about what is covered within its scope providing direct links to those partners. The search interface includes the familiar simple box as well as an advanced option that helps the user narrow results by terms, years, format and source. The strength for fisheries people is the coverage of Elsevier’s journals, some of the most widely cited in the field. Its weakness is the hype as Elsevier claims that it is ‘‘the world’s most comprehensive science-specific index’’ (Elsevier Ltd. 2004). Again, Scirus is more structured than Google Scholarä and more transparent giving it greater credibility. It is a decent resource as long as it is used in conjunction with others.

2.2.3 Searching Effectively The myriad of tools available to the fisheries scientists adds confusion to identifying information. The tools described above represent some of the most accessible or most useful. In deciding which to use, what you are investigating can suggest were to look. Broad, inter-disciplinary questions need to be investigated using indexes that are temporally and topically deep while geographically inclusive and covering multiple disciplines. One tool is not adequate for a thorough search for information. Each has its particular strengths in terms of coverage and search sophistication. Any sophisticated searcher should be aware of the scope of content of the database or span of coverage of a web search service. Also, the user will eventually know when to go deeper for information and when the obvious is good enough. Another consideration in choosing an index or a search engine is the search interface and the results display. Features are constantly being refined by all; however, there are basic ones that make a tool usable (e.g. searching within a field such as title) and those that increase its value (e.g. linking to full text). Some users will always execute simple searches and not experience some of the satisfaction that results from refining a search or ferreting out a resource not readily searchable by keyword. The following discusses three functions inherent in search interfaces that can reveal differences which may influence use. 2.2.3.1 Searching Options The ubiquitous search box presents the simple option of entering in a single keyword and getting results. To some, a complex search is adding more keywords. Any database or search engine should have this basic search option as there are times that a single term or a simple phrase is adequate,

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and more choices confusing or extraneous. However, there are times that a simple keyword search does not produce any results or does not reveal the relevant. One obvious possibility is misspelling; not all databases have a spell checking facility. Other possibilities to consider are the structure and the scope of the resource being searched, and the structure of the search query. Scope has been discussed earlier; however, it is useful to briefly discuss it again along with structure. The various indexes will return different results from the same search strategy. The differences reflect their scope and content. Different web search engines return varying results as they use slightly different searching algorithms and relevancy factoring (Spink and Cole 2006). Tools exist to visualize the overlap (and lack of it) between various search engines (Jacso´ 2005b). An efficient approach to the overlap issue is the ability to search across resources. Some web search engines use this approach (e.g. Dogpile). Within the citation databases, some vendors allow you to search multiple databases simultaneously, so you expand what you are searching and usually increase your results (although you also increase the duplicated citations.) Librarians are developing federated search tools so the user can generate a simple query that is executed across a wide suite of information resources (Avrahami et al. 2006). This concept is quite powerful as web search engines do not penetrate the ‘‘Deep Web’’, material protected by passwords, licenses or structure. An example of the later are library catalogues that while openly searchable are not mined by the typical web search engine as their records are within a database that is not probed by the web crawlers. The same premise holds true for a structured database such as BIOSIS or the Web of Scienceâ. Basic searches using Googleä will return many results, but will not necessarily search deeply into specialized indexes or resources. The structure of the search query is another consideration for effective searching. A simple keyword search can build into a query with multiple field-specific terms. Adding synonyms or related terms can increase search results as can searching across all fields in the resources. For example, if the basic search in a given system is limited to selected fields such as title and author, it will not return citations where the keyword is embedded in the abstract. Building effective search queries involves the above as well as informed use of phrasing and the Boolean terms (‘‘and’’, ‘‘or’’ and ‘‘not’’). Some web search engines assume multiple keywords have ‘‘and’’ between each rather than ‘‘or’’; this approach tends to restrict results. If adjacency of keywords is important, such as ‘‘population dynamics’’ or ‘‘freshwater aquaculture’’, using quotes is usually a trigger for a search engine to search for the phrase rather than the individual words. Boolean terms allow users to build sets, narrowing or expanding results, and helping them find the most relevant information. An obvious time that a fisheries scientist would use Boolean terms is searching a particular species where it is important to use the scientific and common names to retrieve all pertinent references (Fig. 2.1).

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Oncorhynchus tshawytscha

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Chinook

Fig. 2.1 Simple Boolean search indicating the possibilities of expansion (considering both sets so references with either term), and narrowing (considering references containing both terms)

Some search interfaces build Boolean searching into their advanced options using multiple boxes with connecting terms (Fig. 2.2). The option is almost always available even if query and connecting terms must be manually entered. Figure 2.3 illustrates how Boolean terms work conceptually when combining search terms. Using a basic search, each concept is placed in quotes or parentheses and searched to form a set of results. These sets are then combined with ‘‘and’’ to narrow the search to a subset. Using ‘‘or’’ as the combing terms would expand the results to include all sets. The term, ‘‘not’’, is used to exclude a concept that interferes with the results; for example, to find information on the marine phase of salmonids, the sets of keywords or phrases are searched and then the freshwater set excluded.

Fig. 2.2 Cambridge Scientific Abstracts’ Illumina search interface integrates Boolean search terms

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Fig. 2.3 Boolean search illustrating the variety of combinations possible with thoughtful searching of terms (* is a common sign for truncation and in this example will retrieve results containing the root of salmon such as salmonids)

freshwater

marine or ocean

salmon*

A basic search option is very powerful if used thoughtfully. However, a well designed advanced search option is critical as it allows for more specific and often more efficient searching. Few besides those who search daily and librarians regularly use advanced features; in fact most who use web search engines rarely exploit the great potential of more advanced searches (Jansen et al. 2000). Databases and web search engines of value offer advanced search features. Some of the features are described below:

 Field searching

 Example: if you only want to retrieve documents written by a particular author and not those containing citations to that author, you would limit your search to the author field.  Example: if you are looking for articles that have a primary focus on a topic, you may limit a keyword search to the title rather than the entire record including the abstract.

 Limiting

 Example: if you want only the most recent references, you limit your search to the current year within the publication date field.

 Example: if you only want articles from a certain journal, you specify that journal in the source field hence limiting the range of publications searched.  Example: if you want to find all articles published by authors in three countries, you add those countries within the author affiliation field to your search.

 Format

 Example: you only want those references that are readily available as full text, so you limit your search to full text.

 Example: you want a review article, so use the publication type field to refine your search.

 Example: you may want to find images so will want to limit your search by file extension such as jpeg or gif.

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 Thesaurus or keyword list

 Example: you are looking for a scientific name but cannot remember exactly how to spell it.

 Example: you are not finding anything using a particular keyword, so want to find other synonyms.

 Search history

 Example: you executed a complex search for a species that you want to combine with an earlier search on habitat and life history.

 Example: after a long search session, you want to retrieve an earlier search that had some references you forgot to note. Search interfaces constantly evolve as their creators integrate user feedback into making a better mousetrap. While laudable, it is also disconcerting as you get used to working in certain ways. Too many bells and whistles become distracting without adding much utility. So, when deciding on tools to use, it is perfectly acceptable to use those that present the most understandable and easy for you to use interface. Mastering the basic search using Boolean logic will greatly improve search results. Adding an understanding of field limiting and using controlled vocabulary will enhance efficiency and efficacy.

2.2.3.2 Displaying Results The display of results can affect their utility to the searcher. Too much information slows down the ability to scan for relevancy, yet too little leads to guessing and perhaps missing important documents. A well designed interface allows the user to tailor, to some degree, the results display showing more or less detail as desired. For instance, a simple list of titles can be easily scanned for interesting citations; yet, a more complete record with the abstract is valuable if looking for something particular. Web search engines do not currently have the same capacity for manipulating the display of results. A decent interface will also allow the user to sort the results by date or relevancy if not other factors. Again, web search engines do not currently allow this as they are not working with a controlled and limited database of citations. There are certain obvious elements of any display of results. These include the following:

 Title of the resource  Author(s) including first initials if not complete name  Basic citation information such as the journal title, volume, date and pages or conference name

 Abstract or simple description

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The last element in the list, the abstract, is often critical in deciding whether something is useful. Many citation databases have complete abstracts as written by the authors or database editors while web search engines automatically create a summary using various strategies. The content of the summary should help the user decide if the resource will be useful or relevant to the current search. Fisheries scientists are accustomed to the classic abstract so can read through a well-written one and grasp the research question, the methodology and the results. Web summaries can be problematic as they do not have a consistent structure and being short, do not always provide enough context or information (White et al. 2003). On the positive side, it is often simple to click through to the document itself or a more complete description of the item. Additional display features, while not critical, can be useful. These are usually of two types: the first group being elements that provide more information about the item and the other type being connections to additional information or the item itself. The former are most visible in citation databases with structured records. The value of the records is increased with the addition of more complete publication information including publisher information and a complete citation as well as more information on the author such as affiliation and contact information. Often subject headings or descriptors have been assigned; these allow you to search for other records with the same descriptors, a useful tactic when exploring a topic. The latter type of elements, external linkages, is a newer development as linkages to full text of articles and other resources have evolved. With web search engine results, the greatest feature is the link to the full text of an item, although too often that link is to an incomplete citation or reference buried within another document. Linking to full text is not assured as the full text of an article may be restricted to those with licenses or authority. The citation databases can be integrated with an institution’s journal databases so linkages are automatic if the institution has a subscription to that journal. This is done through implementation of an OpenURL resolver, a software that gathers the information about a user, the institution’s licenses and the information resources, and then matches the access rights (McDonald and Van de Velde 2004). Even with the limitations to access, linking out to full text resources is a boon to the fisheries scientist providing faster access to information. Another form of link is to related records or similar pages which can lead to resources of interest. Sometimes these linked resources are related only through payment to the search engines, and sometimes they are related through shared keywords or source. Within a scientific information database, the relatedness may be through shared references or shared subject descriptors. The results display in many citation databases give the user more complete information about a resource and allow some manipulation of the results set. The results display of web search engines can reveal a wealth of information not covered by the citation databases and usually provide some kind of direct

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access to the full text if available. So, the differences in display once again reinforce that one tool does not satisfy every information need or every user’s expectations.

2.2.3.3 Using Results Finally, there are differences in how to use the results. Linkages to more information including the full text exemplify one use. Others involve manipulating the results for further use. Effective use of results can ease the research process. Tracking what has been searched and found relevant allows compilation of sources in a logical manner. The web search engines are not as conducive to this more structured information search; rather than marking a list of references and then checking as a batch, you must click back and forth between the results page and possible documents of interest. When using a web search engine, one strategy is to maintain a research log and cut and paste relevant or interesting web page addresses along with the date accessed so you can return to the site. The citation databases allow the user to mark references of interest as they are perused, compiling them into a subset. Then the user can print, download, email or simply review the subset.

2.2.4 Managing Information Another Chinese proverb states ‘‘Once on a tiger’s back, it is hard to alight.’’ Ferreting out the information can become addictive and the consumer of information becomes consumed with the task. Knowing when to stop searching and start reading and synthesizing is as critical as knowing how to start searching. It is almost impossible in this age of rapid information transfer and burgeoning information resources to feel that you have found everything on a topic. However, you can be confident if you have worked through your information searching logically and systematically. The logic can be temporal – starting with the historic pieces and working forward or vice versa. Or, it can be database-centric – executing similar searches across multiple databases. Over time, you will devise your own methods and process. Maintaining a research log can be useful for managing the process. This entails simply noting what databases you have searched when and what search strategies you used. You can then re-execute those strategies at a later date if working on a long term project. You will also remember what you have already done if you get interrupted or return to a project. Another important component of managing the process and the information gathered involves organizing what you find. Random citations jotted down on slips of paper or emailed to your mailbox are easily lost and have little context. It is not enough to copy or print off various articles; you need to keep them organized so you can use them. One method is the old-fashioned list compiled as

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information is gathered with the corresponding reprint file. This method has been updated with the advent of easy-to-use bibliographic software such as EndNoteä or Zotero. One way of looking at this type of software is that it replaces the old card files; however, it has much more potential as a highly useful research tool (Mattison 2005; Webster 2003). Most bibliographic software allows the user to enter records with the typical fields of author, title, source, add personal annotations through keywords, notes and abstracts, and even link to digital versions of the item. The resulting personal citation database is searchable and serves as a tool to manage your research. Beyond that, the most valuable aspects of bibliographic software are its ability to import records you have identified while searching the citation databases and its capacity to format those citations in a variety of styles as you use them in your writing. Some see this as just another software package to learn, so procrastinate. Those that do make the effort to use one of the many available bibliographic software packages available find it a valuable tool for managing information from consumption through production.

2.2.5 Obtaining Information It is one thing to identify information resources and yet another to actually get them to read and review. This step is made easier with the increase in digital information and the integration of links to articles from the citation databases and within the Web. Those of us working within research, governmental and educational institutions often enjoy broad access to digital information and well-stocked libraries of print material. Obtaining material is not always perceived as an issue. However, we enjoy that access because the digital material is either freely available through open access repositories or web sites, or purchased by the institution. The institutional entity usually responsible for maintaining adequate access to information is the library. Remove the licenses the library has negotiated, purchased and maintained, and a fisheries scientist would be frustrated by the lack of seamless access to electronic journals in particular. So, the library should be a researcher’s first means of obtaining information whether virtually or physically. A core principle of librarianship is to connect the user with the information needed (Ranganathan 1963). The format, topic or source does not matter, but access does. If stymied in obtaining information, work with your librarian to secure electronic access or to facilitate a loan or purchase. Not all fisheries scientists have a librarian or a library. Exploring if the material is freely available in electronic format is currently the favored approach. This entails looking beyond an initial search of the Web to investigating the digital holdings of relevant organizations. For example, the Food and Agriculture Organization of the U.N. has a large digital document

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repository that is available to all; however, most web searches will not penetrate this rich source of full text documents as it is not structured to be readily mined by the search engines (Food and Agriculture Organization of the U.N. 2006). One strategy for finding electronic documents is to look to the organization responsible for publishing the document in question or funding the research. The growing trend towards institutional repositories that capture the digital output of an organization increases access. However, often these repositories must be searched individually by going to the institution’s web site. If a freely available digital version of a piece of information is not readily available, the next step is to request it from the author or producing organization. This used to be a common practice and why authors continue to get a stack of reprints from their publishers (although often at a cost.) More authors are advocating for electronic reprints usually as a pdf that can be posted on an institutional web site for sharing with colleagues. Before posting to a site that is publicly available, the authors should verify that they secured that right as part of the copyright agreement with the publisher. If this is not the case, another way of sharing electronic reprints with requestors is to put it on an FTP site that is either password protected or time limited so access is restricted to those authorized. The final option is paying for the information, something libraries do daily, but the individual researcher does rarely. Many publishers of scientific articles and reports have simplified paying for individual articles. There will be times when reviewing citations that you will link to an article that your institution does not subscribe to, or you have linked to that article in a way that the publisher does not recognize that you are affiliated with a subscribing institution. At that point, most systems will request a login and password, or your credit card number. Before despairing, check with your librarian to see if you should have access. If not, then you will have to decide if the article is worth the cost.

2.2.6 Staying Current with Information Given the perceived deluge of information, it can be daunting to stay current with research, policy changes and management decisions. Various tools are available to help address the challenge. These include electronic tables of contents, personalized alerts, discussion lists and RSS feeds. Each has its strengths and weaknesses, but all provide ways to stay informed. Browsing the tables of contents of relevant journals is a tried and true method. It is an easy way to see what is being published as well as a means of discovering information that you may overlook in a search. Most publishers maintain journal web pages containing the tables of contents by issue. These are easily browsed when accessed. A more effective method is to subscribe to email

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alerts either through the publisher or through a compiler. Setting up alerts involves going to the publisher’s web site, registering and selecting those journals which interest you. Then, you will receive an email whenever a new issue is published. You will need to go to a variety of publisher sites to cover all of the publications you may want. An alternative if available to you is to use a service such as Current Contentsä or Ingentaä that allow you to set up an account and select journals by a variety of publishers. The strength of such services is the ability to manage one account for access to multiple publishers and their journals. The drawback is the cost; both the examples above involve a substantial annual subscription fee that your institution may or may not choose to pay. In addition to table of contents alerts, many publishers and citation databases include a feature for search alerts. The concept is that you may have a search that you want to conduct regularly such as a species, an author, or citations to your own publications; a search alert provides a mechanism for running these search strategies on a regular basis and having any results emailed to you. Even if a favorite citation database or publisher does not have the alert capability, it may have a way to store your search strategies so you can easily retrieve them and run at a later date. This alleviates reconstructing a search that was productive. Some alerts are automatically run and sent weekly even if there are no new items; others only generate an alert when there is something to send. Either way, it is a simple way to keep informed on new publications by certain authors or on a particular topic. Another way to stay informed is to subscribe to relevant electronic discussion lists. Some generate too much traffic in your email box, but others may be a valuable resource for learning about new developments in your field. Lists seem to be a particularly useful for announcements of new books and reports as publishers or authors find them a useful way to generate interest in a publication. LISTSERVâ, one of the major software tools used for creating discussion lists, maintains a searchable list of those lists thus providing one tool for identifying appropriate discussion lists (http://www.lsoft.com/lists/listref.html). Asking colleagues which lists they subscribe to is often the most effective way of finding relevant lists. Most professional organizations also maintain email lists that can be useful ways to stay informed. RSS (real simple syndication or rich site summary) feeds are one more tool to mention in this day and age. Many web sites incorporate this tool as a means to ‘‘push’’ new information to those interested. A typical way that such feeds are encountered is at the bottom of many web sites where a stream of news is constantly changing; this is an RSS feed. Subscribing to RSS feeds allows you to monitor changes in a web site of interest such as a blog on marine fisheries management or a particular site that lists fisheries jobs. A simple way to do so is by using an aggregator such as Bloglines or NetVibes. A web service that allows subscribers to set up a personalized web site that monitors selected web sites and blogs.

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2.2.7 Information Consumed Searching effectively entails all of these steps.

 Learning how to structure searches.  Investigating options for displaying and using results.  Selecting the most appropriate resource to search. The last may be the most important. The best search interface is meaningless if the suite of information being searched is irrelevant to the searcher. The broadest citation database is worthless if it does not cover the discipline being investigated. The World Wide Web is multi-dimensional and searching its most accessible dimension is not adequate for scientific research. So, select your information tool carefully and search intelligently. As the Web, information resources and computing evolve, more tools will become available for consuming information.

2.3 Producing Information After completing the analysis of research findings, the penultimate step of the scientific process is communicating the results. Scientists present their findings to others for ratification, verification, and discussion, consequently contributing to a discipline’s body of literature. After building upon the work of others by ‘‘consuming’’ information, we scientists produce information. At this step, you make decisions that can help shape the body of scientific literature through effective scholarly communication.

2.3.1 Audience Various modes of communication are available to scientists and choosing the proper one begins with determining the intended audience for the work. The intended audience often shapes the focus of the content, the style and the venue. For example, the elements necessary to explain a scientific finding are different than those for recommending changes to fisheries policy; one may require more text while another may depend heavily on data presented in graphical format. Traditionally, fisheries scientists wrote for other scientists. In contemporary society, they also may need to communicate to the lay person, policy makers or students. Each audience responds best to communication directed to their information needs and use patterns (e.g. regular reading of scientific journals versus browsing of fisheries web pages). With the advent of electronic delivery, it is easy to lose sight of intention. Scientists may read research summaries on public websites rather than seek out the peer-reviewed paper. Or, students may stumble on the paper when a summary or simpler explanation may better fit their needs. This blurring is driven by practical considerations of time and effort

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(it is fast and relatively simple to find information on the Web versus sorting through the peer-reviewed journals even when available electronically). Yet, it does not negate considering audience when producing information. The blurring suggests that information once produced for a single audience of scientists can now be used by more than one audience; so, thoughtful production is necessary. Scientists write technically for other scientists, and tend to follow a prescribed structure that reflects the scientific method. The outlets are scientific journals and conference proceedings with the peer-reviewed journal article being the most credited communication piece. While individual journals have different styles and requirements for authors, all require common elements such as an introduction, an explanation of materials and methods, and a discussion and analysis of data and results. Additionally, fisheries scientists use common terminology such as internationally accepted scientific binomial names for the organisms described, international units of measurement, and technical abbreviations and acronyms that are often used without explanation. These standards facilitate the communication among scientists as readers can maneuver through the common structure. By contrast, communicating fisheries science to general audiences requires less technical language that describes the subject matter in an understandable manner as these readers do not share the common language of peer-reviewed science. Illustrations become an essential means of explaining the issues and the process for addressing them. Organisms may be referred to by their local vernacular or common names rather than their binomial scientific names. This common practice makes literature more accessible to local readers and those unfamiliar with scientific names. The methodology may be the focus of the writing rather than the findings (e.g. explaining how a pit tag works) if that addresses the interest of the audience. The purpose is usually more education and information rather than the drive to document and validate found in peer-reviewed communication. Policy communications blend the popular and the scientific. When fisheries scientists work with policy makers, they are usually providing an expert opinion or scientific findings. Policy makers are not scientists although many may have extensive scientific experience and credentials. Consequently, scientific language is adapted so concepts and findings are well articulated and understandable to the lay person. Fisheries scientists when working with policy makers decide what role they are playing – scientist or advocate – and shape their writing to reflect the decision (Lackey 2006). Some would say that this decision is arbitrary, yet the communication will be shaped by the nature of the language, the tone and the viewpoint. This makes policy communication challenging.

2.3.2 Publishing Venues Once the audience is recognized, you select a publishing venue that addresses your audience, its needs and its information seeking behavior. The growth of

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the Web adds new venues as well as expands the reach of existing ones. The borders between venues blur. Peer-reviewed articles are available electronically so become elements of websites rather than limited to a bound journal. Policy statements are posted to web sites in a timely manner so edits and revised drafts are immediately open to scrutiny by the interested public and those affected by the decision. The electronic environment opens communications in terms of access and timeliness. While venues blur, fisheries scientists still need to focus on a primary one when crafting their communication. The publishing venue is shaped by those who contribute to it, those who read what is published and then by the venue itself. 2.3.2.1 Peer-Reviewed Journals Scientists prefer peer-reviewed journals for most scholarly scientific publications as their primary audience reads them and the authors usually get greater credit for their career. Peer-review is a collaborative process whereby papers are submitted to an Editor who in turn solicits anonymous review of the work by other scientists working in the field. These anonymous reviewers assure quality control by evaluating the materials and methods; the veracity and repeatability of the findings; and the contribution, if any, that the new work makes to the field. Peer-reviewed journals can be broad in scope (Science and Nature) or more specialized (Fisheries Oceanography). They may be produced by commercial publishers (Elsevier, Wiley), societies (American Fisheries Society, World Aquaculture Society), institutions (Journal of the Marine Biological Association of the UK ), or governments/non-government organizations (National Research Council of Canada, the International Whaling Commission). The cost of peer-reviewed journals is highly variable, with commercial publications often being extremely expensive and government publications being less expensive or even free. This is an important point to consider when selecting a publishing outlet; a high cost journal may have a more limited readership than a freely available publication. Again, the intended audience is one consideration in selecting the appropriate publishing venue. Scientists debate the quality and ‘‘impact’’ of peer reviewed scientific journals. ‘‘Impact factors’’ are one method for determining the ‘‘value’’ of a journal and such factors are considered by many institutions for purposes of conferring promotion, tenure, and grant monies to those who publish in ‘‘high impact’’ journals. The term ‘‘impact factor’’ was coined by Dr. Eugene Garfield and applies only to those journals indexed by Thomson Reuters Scientific in the Web of Scienceâ (described in Section 2.2.2.1). The impact factor is determined by a simple mathematical formula that divides the number of published articles in a 2-year period of a journal title, by the number of citations to those same articles in a different 2-year period (Garfield 1994). The impact factor is highly controversial, widely misunderstood, and frequently irrelevant in fisheries science for two reasons. First, the Web of Scienceâ does not index many relevant fisheries publications that fall outside of the mainstream. Second, many

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fisheries scientists publish outside of fisheries journals, so the relative impact of the 40 titles in the fisheries cluster does not reflect the importance of an article in Conservation Biology, for example. The Web of Scienceâ does not quickly add titles due to changing research interests; for example, Fisheries Oceanography, first published in 1992, was not indexed in the Web of Scienceâ until the last issue of the 4th volume published in 1995, and Journal of Cetacean Research and Management first published in 1999 is still not covered in 2008. All the above suggests that the peer-reviewed journals have a definite place in documenting and communication fisheries science, but often too much emphasis is put on this sector of the information web (Lange 2002; Webster and Collins 2005). 2.3.2.2 Professional and Trade Journals and Newsletters Essential to fisheries science are the publications produced by scientific societies and industry organizations. These often address applied research issues and results such as stock assessment, policy discussion, and trade information and trends. Such publications also take many forms including professional journals that may be peer-reviewed (Fisheries), trade journals (National Fisherman, World Fishing) or even popular magazines (Blue Planet, Oceanus). These publications are focused on specific aspects of a discipline, or may seek to bring varying viewpoints together around a particular technology or policy issue. Because much fisheries literature is ‘‘applied’’ rather than ‘‘experimental’’ in nature, these publications provide an important outlet for best practices, describing new gear or technologies, and stimulating debates by creating a forum for policy discussions. 2.3.2.3 Grey Literature Another form of publication common to fisheries literature is the so called ‘‘grey literature.’’ As the term suggests, this venue is not obvious and often not accessible to all, yet critical as it encompasses much that is not commercially published. Finding or consuming grey literature can be problematic because not enough attention is paid by authors producing it. A prime example is a technical report containing datasets and observations that are not distilled into a format suitable for publication in a several page article. Master’s theses or doctoral dissertations may be considered grey literature, as are data sets or time series. Grey literature may be individual reports or comprise parts of long standing series (such as the many series published by FAO). It is often published by government entities, non-governmental organizations and international organizations. Distribution may be extremely limited, yet critical to those seeking to understand a particular issue or search for a specialized dataset. This limited distribution, coupled with lack of peer-review, means that grey literature is under-represented or excluded from many general abstracting and indexing services. Specialized databases (such as ASFA and Fish and Fisheries Worldwide), however, specialize in identifying such literature, which further extends

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the value and importance of the data to scholars and policy makers. Grey literature may also be assembled into aggregated databases such as the National Sea Grant Library (National Sea Grant Library 2006) or in collections at government agencies (Office of Scientific and Technical Information (U.S.) 2006) or organizational repositories (Food and Agriculture Organization of the U.N. 2006). Even though distribution is uneven and publications may be difficult to locate, the grey literature in fisheries science provides a large reservoir of important information. Some classic studies were originally published in government series (Beverton and Holt 1957). Practical management guidelines often appear in this venue. Even the fodder for ongoing debates can first appear in the grey literature (Food and Agriculture Organization of the U.N. 1995; Pew Oceans Commission and Panetta 2003). For many fisheries scientists, this is their venue as their agencies and organizations expect reports and not finely tuned journal articles; or, their annual reports or technical handbooks are more appropriate means of communicating to their audience. Grey literature takes many forms, with varying styles and differing purposes. As a venue, though, it is important to recognize and use it.

2.3.3 Copyright Copyright is an important but subtle and often confusing aspect of scientific publishing. It used to be a peripheral concern when making decisions about publishing venue. Now, copyright can be a deciding factor in whether an article is accessible to all readers and usable by the authors. It is worthwhile to have a working knowledge of copyright so authors can make thoughtful decisions. Copyright laws differ from country to country, but all seek to protect the intellectual property of an author. The World Intellectual Property Organization (WIPO) and treaties such as the Berne Convention (signed by 162 countries since its inception in 1886) work towards collaborative and shared recognition and enforcement of member nations’ copyright laws. At the most basic level, copyright confers to the copyright owner specific privileges:

 The right to reproduce the work;  The right to prepare or authorize derivative works based upon the copyrighted work;

 The right to distribute copies and collect royalties;  The right to display or perform copyrighted works. Copyright typically resides with the creator of a work. One significant exception is that the work of US Federal Government employees is not copyrighted and is in the ‘‘public domain’’ where it is freely usable by anyone anywhere in the world. This is also true for many state employees, although the law varies from state to state and institution to institution.

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A perplexing trend has taken place in scholarly scientific publishing over the years. Publishers usually require authors to sign over their copyrights to the publisher in order to have the work published in a scientific journal. Publishers claim that this right is necessary for them to protect and responsibly manage that piece of intellectual property for the legal term of the copyright. In the US, copyright currently lasts for the life of the author plus 70 years, which seems an inordinately long term for a scientific work to need protection or to be managed. Further, while copyright transfer is common practice in scientific publishing, it is not common with many other types of publishing (such as fiction and legal publishing). Because copyright assignment gives exclusive rights to the copyright holder, authors (aka creators of the work) may be prohibited from using their own work in other format or forum – such as classroom teaching, distributed learning, for inclusion in other works, or posting on a personal web site. Alternative copyright models are emerging and understanding of constraints of current practice is growing. For example, in the United Kingdom authors can assign their copyright to a publisher, while at the same time retaining the moral rights (as opposed to economic rights) to their intellectual property. Moral rights involve ‘‘the right to claim authorship of a work, and the right to oppose changes to it that could harm the creator’s reputation’’ (World Intellectual Property Organization 2006). More authors are refusing to sign away their copyright, and instead choosing to give non-exclusive rights to publishers for first publication of their work, while retaining for themselves other rights (such as classroom and instructional uses). There are also new copyright models such as the Science Commons and Creative Commons models that enable authors to retain their copyright while assigning various levels of uses of their work (Creative Commons 1999; Creative Commons 2005) (Fig. 2.4). SHERPA/RoMEO Service provides information on the copyright policies of various publishers (SHERPA and University of Nottingham 2006). It grew out of the 2002/03 RoMEO Project (Rights MEtadata for Open Archiving) of the Joint Information System Committee of the UK at the University of Loughborough (Joint Information Systems Committee 2006). The project correctly identified a need to document publisher policies as interest in self-archiving grows. Most publishers allow authors to post their work online; however many have restrictions to how this is done and what can be posted (e.g. pre-print, post-print, article pdf). This service assists authors who want to better understand their rights before or after publishing as well as others who may want to use a copyrighted article (Fig. 2.5). A wealth of copyright resources exists for authors. At times, there is too much information so we tend to ignore it and hence are faced with consequences that can be problematic. As an author, you should check your organization’s guidelines (if they exist) so you know what your rights may be. If none exist, use other available resources such as a university’s or a government’s copyright site (Table 2.1). Also, read the publisher’s copyright agreement and amend it to address your need to archive and access your work. Ignorance is not bliss when it comes to copyright in the digital age.

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ADDENDUM TO PUBLICATION AGREEMENT 1. THIS ADDENDUM hereby modifies and supplements the attached Publication Agreement concerning the following Article: _________________________________________________________________________ (manuscript title) _________________________________________________________________________ (journal name) 2.

The parties to the Publication Agreement as modified and supplemented by this Addendum are: ____________________________________(corresponding author) ____________________________________________________ ____________________________________________________ ____________________________________________________ (Individually or, if one than more author, collectively, Author)

_______________________________________ (Publisher)

3. This Addendum and the Publication Agreement, taken together, allocate all rights under copyright with respect to all versions of the Article. The parties agree that wherever there is any conflict between this Addendum and the Publication Agreement, the provisions of this Addendum are paramount and the Publication Agreement shall be construed accordingly. 4. Author’s Retention of Rights. Notwithstanding any terms in the Publication Agreement to the contrary, AUTHOR and PUBLISHER agree that in addition to any rights under copyright retained by Author in the Publication Agreement, Author retains: (i) the rights to reproduce, to distribute, to publicly perform, and to publicly display the Article in any medium for noncommercial purposes; (ii) the right to prepare derivative works from the Article; and (iii) the right to authorize others to make any non-commercial use of the Article so long as Author receives credit as author and the journal in which the Article has been published is cited as the source of first publication of the Article. For example, Author may make and distribute copies in the course of teaching and research and may post the Article on personal or institutional Web sites and in other open-access digital repositories. 5. Publisher's Additional Commitments. Publisher agrees to provide to Author within 14 days of first publication and at no charge an electronic copy of the published Article in a format, such as the Portable Document Format (.pdf), that preserves final page layout, formatting, and content. No technical restriction, such as security settings, will be imposed to prevent copying or printing of the document. 6. Acknowledgment of Prior License Grants. In addition, where applicable and without limiting the retention of rights above, Publisher acknowledges that Author’s assignment of copyright or Author’s grant of exclusive rights in the Publication Agreement is subject to Author’s prior grant of a non-exclusive copyright license to Author’s employing institution and/or to a funding entity that financially supported the research reflected in the Article as part of an agreement between Author or Author’s employing institution and such funding entity, such as an agency of the United States government. 7. For record keeping purposes, Author requests that Publisher sign a copy of this Addendum and return it to Author. However, if Publisher publishes the Article in the journal or in any other form without signing a copy of this Addendum, such publication manifests Publisher’s assent to the terms of this Addendum. AUTHOR ___________________________________________ (corresponding author on behalf of all authors)

PUBLISHER ____________________________________

_______________________________________(Date)

___________________________________(Date)

Neither Creative Commons nor Science Commons are parties to this agreement or provide legal advice. Please visit www.sciencecommons.org for more information and specific disclaimers.

SPARC (the Scholarly Publishing and Academic Resources Coalition) and the Association of Research Libraries (ARL) are not parties to this Addendum or to the Publication Agreement. SPARC and ARL make no warranty whatsoever in connection with the Article. SPARC and ARL will not be liable to Author or Publisher on any legal theory for any damages whatsoever, including without limitation any general, special, incidental or consequential damages arising in connection with this Addendum or the Publication Agreement. SPARC and ARL make no warranties regarding the information provided in this Addendum and disclaims liability for damages resulting from the use of this Addendum. This Addendum is provided on an “as-is” basis. No legal services are provided or intended to be provided in connection with this Addendum.

Access-Reuse 1.0 www.sciencecommons.org

Fig. 2.4 An example of a copyright addendum from Science Commons

SPARC Author Addendum 3.0 www.arl.org/sparc/

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Fig. 2.5 Examples of a publisher profile from SHERPA/RoMEO

Title Author’s rights (SPARC)

Table 2.1 Copyright resources Web address

Description

http://www.arl.org/sparc/author/ addendum.html

Explains your rights as an authors and includes copyright addendum Scholar’s Copyright Project http://sciencecommons.org/ Another example of a (Science Commons) projects/publishing copyright addendum Copyright Management http://www.copyright.iupui.edu/ Explains U.S. copyright, Center (Indiana University) the concept of Fair Use, and other concepts Copyright (World Intellectual http://www.wipo.int/copyright/en/ A discussion of Property Organization) copyright from an international perspective

2.3.4 Access Producing scientific information translates into providing access to it. This used to be straight forward; yet now, in the electronic environment, access issues present another set of decisions for authors. Scholarly communication as we now know it ‘‘began’’ in the 17th century when reports of scientific discovery or

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observation were presented to scholars by reading them before the assembled members of scientific societies. The resulting papers were printed in compilations, the first being the Philosophical Transactions of the Royal Society (London) in 1665, and thus ‘‘the scientific journal’’ was born (Vickery 2000). For centuries printed journals were the norm, with the number of journal titles growing as new disciplines and sub-specialties of science developed. Scholarly societies and organizations along with commercial ventures were all publishers serving different audiences and roles. The societies tended towards printing papers that had been presented and vetted within their meetings while others sought publishing as a means to broaden communication among scientists rather than within organizations (Henderson 2002; Vickery 2000). As scholarly communication grew, its audience expanded and diversified, and the cost of producing, delivering and archiving scientific information increased as well (Prosser 2005). Today, we expect producers of scientific journals to offer multiple modes of access (print and electronic), more content (e.g. pages) and archives of all. Electronic full text access to current and old items should be within one or two clicks of a search. Our broader audiences also want ready access to the information fisheries scientists produce. They want it in a digestible format that is easily accessed. They do not subscribe to the scientific journals, so electronic delivery makes sense. Thanks to the widespread adoption of personal computers, standardized software and stable file formats, nearly all scientific publications are ‘‘born digital.’’ Digital content can easily be converted into appropriate styles or formats, and delivered on the Web through the sophisticated web sites of major scientific publishers to workable government and academic sites as well as a myriad of other web presences. Digital files, distributed across the Internet, have drastically altered the reach and potential markets for scientific literature. In fact, the print journal we have known since the 1600s is considered by many to be nearing extinction or at best to being an archival format. Online journals developed from the expansion of ‘‘born digital’’ information and the global spread of Internet technologies. These are available in multiple forms and collections with associated differences in how potential readers must access the content. The two primary types are the traditional journals that are now available in electronic form (e.g. Reviews in Fisheries Science) and the open access journals (e.g. Scientia Marina). The electronic equivalent of print journals must still be purchased for the most part. They may be distributed on an individual basis, gathered into collections by the publisher, or aggregated into bundles of journals from multiple publishers. A particular journal title might even be available via any or all of these mechanisms, and such compilations may be ‘‘full text’’ cover-to-cover or just select portions of journals (for example research articles but not news or letters to the editor). Multiple mechanisms allow users to pick the one that fits their budget; however, it also means that libraries may have to duplicate purchases to capture all the content. As an author, you want to explore how your article is marketed as that affects how people access it. If too expensive or if included in an aggregated package that

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many find too confusing to purchase, your work may be essentially ‘‘lost’’ to parts of the audience. New initiatives promote ‘‘open access’’ to scientific literature, whereby articles are either published in an ‘‘open access’’ journal or posted to an electronic repository. One of the clearest definitions of ‘‘open access’’ is found in the Budapest Open Access Initiative: By ‘open access’ to this literature, we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited Chan et al. (2002)

This concept and the initiatives it has spawned change the landscape of scholarly communication and access. Authors can retain control over their copyright and hence exercise more control of the access to their work. Such radical change does not come easily, quickly or smoothly. Yet, change does seem to be happening. Driven by initiatives such as the Open Archives Initiative and the Berlin Declaration, efforts vary from country-to-country (Van de Sompel and Lagoze 2000; Gruss and German Research Organizations 2003). The Open Access movement suggests new responsibilities for authors including making sure that they retain their rights to give their work to the public and that it is stored in a stable manner. New requirements by funders and institutions are one impetus for the growth of open access. For example, in 2008 the US National Institute of Health started requiring all grantees to deposit their findings in PubMedCentral. However, compliance is spotty and slow. Others have also found authors slow to put their material in publicly accessible sites; but persistence and mandates work over time (Sale 2006). It is important to note that while open or public access is a fairly recent phenomenon, studies show that the ‘‘impact’’ and citedness of such articles is as high as or better than articles published in traditional journals (Kousha and Thelwall 2006; Antelman 2004; Harnad and Brody 2004). Considering the alternatives to commercial journals and traditional publishing outlets is valid when producing information; ‘‘open access’’ journals and e-repositories may provide better access to your work for your intended audience. Beyond the traditional scientific journal and the growing open access movement, we are learning how to share our research in other ways. No longer dependent on the mail and correspondence, we share research findings, collaborate in real time across tremendous distances, and participate in ‘‘live’’ debates with just a few keystrokes on the Internet. Technological advances and relatively inexpensive gadgets make it possible to talk (using Voice Over Internet Protocol or VOIP), participate in video conferences, and hold interactive distributed online seminars called ‘‘webinars’’. Blogs (web logs or online diaries), wikis, and other

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collaborative authoring tools are also drastically changing how scientists do business. Such low-cost tools make it possible for scientists, students, and policy-makers anywhere on the globe (or even in space) to quickly communicate with others and quickly disseminate information. Despite reports by Christopher Columbus in 1492, it appears that the world really is flat.

2.3.5 Archiving Access and archiving are linked in the electronic environment; you cannot access an electronic document unless it has been stored in some logical, stable manner. File drawers and library shelves historically held the archives of the scientific debate but the digital millennium changes this norm. Now, you are more likely to post a pdf of your article to your web site than to order a box of reprints from the publisher. Or, you rely on the publisher to maintain an electronic copy on its server. Both options are tenable, but may have legal implications or monetary limitations. You can usually satisfy the former if you reserved the right to post a copy of the pdf to a publicly accessible site when signing your copyright statement. The latter can be more complex. With access licenses comes the vulnerability that access to information ends when one stops paying ‘‘the rent.’’ Usually, the library pays ‘‘the rent’’ through contractual agreements with the publishers for access. Publishers make their digital archives available, some at a high cost to libraries and institutions, and others more altruistically, making them publicly available at no or low cost. An example of a commercial model is ScienceDirect, Elsevier’s online journal collection; an institution can subscribe to some or all of the content of Elsevier’s vast suite of scientific journals depending on the strength of its budget and the need of its researchers. PubMed Central sponsored by the US National Institute of Health is a different archiving model; here all articles are freely accessible to all. As publishing mergers continue, archives change hands and access costs and rights can change with new owners. Unstable budgets can interrupt service and libraries lose access to previously licensed archives. And, authors lose access to their work. Identifying how your work will be archived is yet another step in the production cycle. Again, there are choices and consequences of those choices. In an attempt to archive and secure ongoing access to their contribution to the scholarly process, many entities are creating institutional repositories (IR) as a digital preservation space (University of Houston Libraries, Institutional Repository Task Force and Bailey 2006). Institutional repositories provide a service to collect, archive and provide access to the information produced by members of a defined community such as a university or a discipline (Lynch 2003). They create a virtual and intellectual environment for the community’s digital output. They are an attempt to address the challenges of digital archiving, the expectations of the campus and research community for better access to

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information, and the inadequacies of the current cumbersome model for scholarly communication. Various organizational models, software and hardware are emerging as more universities and agencies implement IRs (Crow 2004).

2.3.6 Information Produced As fisheries scientists, we want to share our work with colleagues, policy makers and the public. Computers make it easier to produce work by streamlining our writing and editing. With the Web, we can now also easily publish our work making it accessible to all. However, producing quality information still involves multiple steps that affect its credibility and use. Scholarly communication is changing, and you need to recognize where and how you can change your actions to improve the information landscape. Consider your audience and its information consumption behavior. Also, consider your future audience. Such consideration will help you decide where you publish as it will suggest how your work will be identified and accessed by readers today and tomorrow.

2.4 The Future of Fisheries Information While the life cycle of fisheries information remains constant through consumption and production, its environment is changing. Much of the change is driven by the integration of technology into how we ‘‘do’’ science. The change is inevitable; however, as fisheries scientists, we can shape the environment by making the communication of science better – more timely and accessible – while maintaining our credibility and honesty. This takes effort and a willingness to modify some of our ways of consuming and producing information. Engagement in the discussion about scholarly communication is imperative, followed by action. Open and efficient access to fisheries information requires shifts in how we finance production of information. This encompasses the debate over journal pricing, the open access principles and the future of the scientific journal. Ease and stability of access require us to work with those who design and maintain search systems, databases, and archives so the systems respond to our needs.

2.4.1 Changing Economics of Fisheries Information The old system of scholarly publication cannot be sustained given changing user expectations and economics. Pricing continues to escalate with great variability among publishers. For example, in a 2004 study, median overall journal prices vary from £124 (Cambridge University Press) to £781 (Elsevier) (White and Creaser 2004). Price increases from 2000 to 2004 ranged from 27% (Cambridge University Press) to 94% (Sage), well above any inflation factor

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(White and Creaser 2004). Yet we continue to struggle to implement a new publishing model that improves access and archiving for all. Commercial publishers expect profit margins and must often pay dividends to their stockholders. Professional societies generate income from subscriptions, and use the income to provide benefits to members. All publishers need to cover costs. At issue is how to do that in an equitable manner as well as one that promotes open and efficient scholarly communication (Edwards and Shulenburger 2003). Authors provide and consume the product. Yet, the costs are usually born by their institutions. Print subscriptions are sold to individuals (or perhaps are included as a benefit of membership in a particular society) for their personal use. These same journals are sold to libraries at a higher cost because they are accessible to many potential readers. Publishers have discovered that scientific articles are themselves discrete information commodities that can be sold in a collection, bundled into packages of often unrelated journals, or one-by-one. Unlike print journals, publishers have many different market models for pricing online subscriptions, for example, charging based on the number of ‘‘FTE’’ (full time equivalents) of faculty, staff, and students; or by the total amount of grant dollars received; or the number of advanced degrees conferred in a particular subject by an institution. Publishers may offer a subscription at one price to a small marine laboratory and the same publication at a completely different price to a neighboring university. Standard pricing appears to have disappeared as ‘‘deals’’ and ‘‘negotiations’’ have become the norm (Frazier 2001). Access to the article-level is also possible via alternative means and costs, including by subscription to an entire journal or on a pay-per-view basis. In addition to the highly variable subscription prices of scientific journals, authors may face additional costs. Author fees (typically called ‘‘page charges’’ or ‘‘color charges’’) are commonly found in society journals. The charges offset the expense of printing and allow societies to sell subscriptions at a ‘‘subsidized’’ or lower cost. Author charges may or may not be payable with grant funds, or an institution may pay on behalf of its authors. Emerging models that allow ‘‘open access’’ may also come at a cost borne by the author or her/his institution. Simultaneously, open access publications such as the Public Library of Science, have been subsidized by grants and are provided to readers free. Some open access publications offer institutional subscriptions that afford authors at the institution with reduced page charge fees. Even so, the market continues to evolve and access may be ‘‘embargoed’’ whereby current articles are closed, but older articles are ‘‘open access’’ or there may be a mix of access types within current issues (for example Limnology and Oceanography where an article can be ‘‘unlocked’’ or made open access by payment of an additional ‘‘page charge’’). Theoretically, online publication should reduce costs because there are fewer steps and ‘‘consumables’’ (paper and ink) used in the production process as well as reduced costs formerly associated with postage, shipping and handling. However, in many cases the move to electronic delivery and access has

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significantly increased the cost to acquire scientific literature. Publishers insist that online publishing has raised their costs due to the need to upgrade and maintain servers and authentication mechanisms for online subscribers. So, while digital publishing increases the timeliness of access, it also compounds the ways users can access the material and the ways publishers can sell the product (Quandt 2003). It complicates things for all, just when we believe that scholarly communication should be easier, faster and cheaper. Scientific publishing is rapidly evolving and unsettled, driven by technology and the growth of Internet-based services. For centuries, libraries preserved the scientific record by purchasing journal subscriptions, binding loose issues into complete volumes, cataloguing and preserving them and making collections available to current and future generations of students and scholars. But by the late 20th century, the information moved off the printed page, and access and archiving are no longer assumed with the purchase of a subscription to a journal or electronic book. One approach to the problem is more funding for institutional purchases of electronic information; that is not going to happen at most institutions and still leaves those fisheries scientists unaffiliated with a strong library or research institution unable to get full access to the information needed. A more realistic approach requires government funded research to be published in a publicly accessible venue (Edwards and Shulenburger 2003). An immediate step authors can take is to deposit their publications in a stable electronic repository that is openly accessible and searchable (OhioLINK Governing Board 2006). Change in the publishing landscape is happening rapidly; changing our behavior as consumers and producers is slower, and we need to remedy that to maintain quality fisheries science.

2.4.2 Ensuring Access to and Preservation of Fisheries Information Ease and stability of access to information relate to changes in the publishing landscape, yet have unique issues as well. Ease of access implies improved search interfaces and algorithms as well as more connectivity among sources of information. This challenge seems overwhelming, but realistically can be addressed at various scales and by a range of users. Locally, scientists can work with their librarians and computer scientists to make sure information created and stored locally is easy to search, find and use. A concrete example is to examine how you store your article reprints; are they in a secure and searchable place, or merely tucked on your own computer? Another example is considering how you construct and host a web site for your research project; is the metadata up to standards so it is indexed by web search engines or is the coding something you had not considered? Within professional societies, you can advocate for simple and intuitive interfaces to your organization’s information and publications. Scientists should be willing to participate in studies on the

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usability of search systems, patterns of searching behavior and use of information. The more input on how search systems are used by those who really use them, the better the systems will eventually become. Stability of access dictates if future fisheries scientists will be able to find and use the information created today. With the evolution of publishing from print-only to print plus online models, there has been a cultural shift from ‘‘ownership’’ (whereby each library or individual purchases a subscription to the journal) toward an ‘‘access model’’ whereby libraries and publishers enter into contractual and license agreements that define the terms of access to and use of online content (Quandt 2003). Under this new model, instead of owning journals, content is ‘‘leased’’ and made accessible under specific terms for a specific period of time. Under the terms of contracts and licenses, when libraries cancel a subscription, they may lose access to all content they have leased in the past, thus ending up with nothing to show for their investment over time. The stable print archive the library used to represent has disappeared. So, now we debate how to preserve scholarly information that we may or may not own, and do not really understand its technical life expectancy. CDRoms, once thought to be a good preservation medium, have been shown to fail much earlier than anticipated. Publishers have rushed to digitize past volumes of scientific journals, converting millions of print pages into bits and bytes stored on computers. In fact, that first scientific journal has been digitized as part of the JSTOR initiative so that all articles from 1665 are searchable, retrievable, and printable via any Internet connected computer if the searcher is accessing the resource through an institution with a subscription to this archive (JSTOR 2000–2006). Even when digitized, where is that article stored, in what format, and will we will be able to refresh it as software and hardware changes? Fisheries scientists are not going to solve the digital preservation quandary. However, awareness of the fragility of digital information may make all of us more diligent with our decisions about storing our publications and data. Simple steps are critical, such as using standard formats for digital documents and adding basic metadata to datasets. More complex ones take greater effort and often specific expertise. These include building robust data repositories and experimenting with new ways of storing and accessing files. The keys to change here are involvement and collaboration. Waiting for the publishers to improve search interfaces and provide permanent archives may be waiting for an outcome that is untenable.

2.4.3 Checklist for Consumers and Producers In the end, the cycle of science continues. The information that feeds new ideas and questions continues to be produced and consumed. Maintaining the vigor of fisheries science in the changing environment requires attention by all who are part of the information cycle.

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When consuming information:

   

Consider your question before feasting on the information. Select the right tool and search strategy for your need. Try multiple tools and strategies. Do not assume that nothing exists on the topic. Remember that not everything is found by Googleä. Science happened before computers were invented.  Evaluate your sources. Everything you find is not true, accurate or timely.  Keep track of the sources you find so you can use them accurately and ethically.  Ask for help from an expert – a librarian or a colleague. When producing information:

 Think about your audience when writing.  Consider the practices of publishers when selecting one.

 How do they establish prices?  What is their policy for posting publicly accessible sites?  Do they allow users in developing countries free access to their publications?

 Do they charge you or your institution?  How will they store your work?  Modify your copyright agreement to retain the rights you want.  Deposit your publications in an open access repository.  As a reviewer, consider the practices of the journal that asks for your time and expertise.

 As a member of a professional society, know your organization’s policies and change the ones that inhibit the free flow of information.

 As a colleague and mentor, encourage others to join the discussion and change how we communicate.

 Check the SPARC site for current information on scholarly communication trends (Association of Research Libraries and Scholarly Publishing and Academic Resources Coalition 2006).

References Antelman K (2004) Do open access articles have a greater research impact? College & Research Libraries 65(5):372–82 ASFA Secretariat (2006) List of ASFA partners [Web Page]. Located at: ftp://ftp.fao.org/FI/ asfa/asfa_partner_list.pdf. Accessed 2006 Aug. Association of Research Libraries, Scholarly Publishing and Academic Resources Coalition (2006) CreateChange: Change & you [Web Page]. Located at: http://www.createchange. org/changeandyou.html. Accessed 2006 Sep 7 Avrahami TT, Yau L, Si L, Callan J (2006) The FedLemur project: federated search in the real world. Journal of the American Society for Information Science and Technology 57(3):347–58

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Bauer K, Bakkalbasi N (2005). An examination of citation counts in a new scholarly communication environment. D-Lib Magazine 11(9):1–7 Beverton RJH, Holt SJ (1957). On the dynamics of exploited fish populations. London, UK: Her Majesty’s Stationery Office; (Great Britain. Ministry of Agriculture, Fisheries and Food. Fishery Investigations: ser. 2, v. 19) Chan L, Cuplinskas D, Eisen M, Friend F, Genova Y, Gue´don J-C, Hagemann M, Harnad S, Johnson R, Kupryte R, La Manna M, Re´v I, Segbert M, Souza S, Suber P, Velterop J (2002) Budapest Open Access Initiative [Web Page]. Located at: http://www.soros.org/openaccess/read.shtml. Accessed 2006 Sep 7 Creative Commons (1999) About Creative Commons [Web Page]. Located at: http:// creativecommons.org/. Accessed 2006 Sep 1 Creative Commons (2005) Scholar’s copyright project [Web Page]. Located at: http:// sciencecommons.org/literature/scholars_copyright. Accessed 2006 Sep 1 Crow, R (2004) A guide to institutional repository software. Second Edition. Open Society Institute: New York Edwards R, Shulenburger D (2003) The high cost of scholarly journals (and what to do about it). Change 35(6):10–9 Elsevier Ltd (2004) Scirus White Paper: how Scirus works. Amsterdam, Netherlands: Elsevier Ltd. Food and Agriculture Organization of the U.N. (1958) Current Bibliography for Fisheries Science. Rome, Italy Vol. 1 Food and Agriculture Organization of the U.N. (1995) Code of conduct for responsible fisheries. Rome, Italy: FAO Food and Agriculture Organization of the U.N. (2006) FAO Corporate Document Repository [Web Page]. Located at: http://www.fao.org/documents/. Accessed 2006 Sep 1 Frazier K (2001) The librarian’s dilemma: contemplating the costs of the ‘‘Big Deal’’. D-Lib Magazine 7(3):10.1045/march2001-frazier Garfield E (1994) The ISI impact factor. Current Contents: Agriculture, Biology, & Environmental Sciences 25(25):3–7 Google (2005) About Google Scholarä [Web Page]. Located at: http://scholar.google.com/ intl/en/scholar/about.html. Accessed 2006 Aug. Gruss P, German Research Organizations (2003) Berlin Declaration on open access to knowledge in the sciences and the humanities [Web Page]. Located at: http://www.zim. mpg.de/openaccess-berlin/berlindeclaration.html. Accessed 2006 Sep 7. Harnad S, Brody T (2004) Comparing the Impact of Open Access (OA) vs. Non-OA Articles in the same journals. D-Lib Magazine 10(6):doi:10.1045/june2004-harnad Henderson A (2002) Diversity and the growth of serious/scholarly/scientific journals. [in] Abel RE, Newlin LW, ed. Scholarly publishing: Books, journal, publishers, and libraries in the Twentieth Century. US: John Wiley & Sons, Inc. pp 133–62 Jacso´ P (2005a) Google scholar: the pros and cons. Online Information Review 29(2):208–14 Jacso´ P (2005b) Visualizing overlap and rank differences among web-wide search engines: some free tools and services. Online Information Review 29(5):554–60 Jacso´ P (2006a) Savvy searching: deflated, inflated and phantom citation counts. Online Information Review 30(3):297–309 Jacso´ P (2007) Scopus. Pe´ter’s Digital Reference Shelf [Web Page]. Located at: http://www. gale.cengage.com/reference/peter/200711/scopus.htm. Accessed 2008 Oct 10 Jansen BJ, Spink A, Saracevic, T (2000) Real life, real users, and real needs: a study and analysis of user queries on the web. Information Processing and Management 36(2000):207–27 Joint Information Systems Committee (2006). About JISC – Joint Information Systems Committee [Web Page]. Located at: http://www.jisc.ac.uk/. Accessed 2006 Sep 1 JSTOR (2000) About JSTOR [Web Page]. Located at: http://www.jstor.org/about/. Accessed 2006 Jan Kousha K, Thelwall M (2006) Google Scholar citations and Google Web/URL citations: A multidiscipline exploratory analysis. [in] Proceedings International Workshop on Webometrics,

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Informetrics and Scientometrics & Seventh COLLNET Meeting Nancy, France. Located at: http://eprints.rclis.org/archive/00006416/01/google.pdf Accessed 2006 Sep 1 Lackey RT (2006) Axioms of ecological policy. Fisheries 31(6):286–90 Lange LL (2002) The impact factor as a phantom: is there a self-fulfilling prophecy effect of impact? The Journal of Documentation 58(2):175–84 Lynch CA (2003) Institutional repositories: essential infrastructure for scholarship in the digital age. ARL Bimonthly Report 226 Mattison D (2005) Bibliographic research tools round-Up. Searcher 13(9):10704795 McDonald J, Van de Velde EF (2004) The lure of linking. Library Journal 129(6):32–4 National Sea Grant Library (2006) National Sea Grant Library [Web Page]. Located at: http://nsgd.gso.uri.edu/. Accessed 2006 Sep 1 Neuhaus C, Neuhaus E, Asher A, Wrede C (2006) The depth and breadth of Google Scholar: an empirical study. Portal: Libraries and the Academy 6(2):127–41 Office of Scientific and Technical Information (U.S.) (2006) GrayLIT Network: A science portal to technical papers [Web Page]. Located at: http://www.osti.gov/graylit/. Accessed 2006 Sep 1 OhioLINK Governing Board (2006) OhioLINK Library Community recommendations on retention of intellectual property rights for works produced by Ohio faculty and students [Web Page]. Located at: http://www.ohiolink.edu/journalcrisis/intellproprecsaug06.pdf. Accessed 2006 Sep 7 Page L, Brin S, Montwani R, Winograd T (1998) The PageRank citation ranking: bringing order to the Web. Technical Report, Stanford University Database Group Pauly D, Stergiou KI (2005) Equivalence of results from two citation analyses: Thomson ISI’s Citation Index and Google’s Scholar service. Ethics in Science and Environmental Politics December 2005:33–5 Pew Oceans Commission, Panetta LE (2003) America’s living oceans: charting a course for sea change: a report to the nation: recommendations for a new ocean policy. Arlington, VA: Pew Oceans Commission Prosser DC (2005) Fulfilling the promise of scholarly communication – a comparison between old and new access models. [in]: Nielsen EK, Saur KG, Ceynowa K, eds. Die innovative Bibliothek: Elmar Mittler zum 65. Geburtstag. K G Saur. pp 95–106 Pruvost C, Knibbs C, Hawkes R (2003) About Scirus [Web Page]. Located at: http://www. scirus.com/srsapp/aboutus. Accessed 2006 Aug Quandt RE (2003) Scholarly materials: Paper or digital? Library Trends 51(3):349–75 Ranganathan SR (1963) The five laws of library science. [Ed. 2, reprinted with minor amendments] Bombay, New York: Asia Publishing House Roth DL (2005) The emergence of competitors to the Science Citation Index and the Web of Science. Current Science 89(9):1531–6 Sale A (2006) The acquisition of open access research articles. First Monday 11(10) [Web Page]. Located at: http://eprints.utas.edu.au/388/ SHERPA, University of Nottingham. (2006) SHERPA/RoMEO Publisher copyright policies & self-archiving [Web Page]. Located at: http://www.sherpa.ac.uk/romeo.php. Accessed 2006 Sep 1 Spink A, Cole C (2006) Human information behavior integrating diverse approaches and information use. Journal of the American Society for Information Science and Technology 57(1):25–35 University of Houston Libraries, Institutional Repository Task Force, Bailey CW (2006) Institutional repositories. Washington, DC: Association of Research Libraries, Office of Management Services Van de Sompel H, Lagoze C (2000) The Santa Fe Convention of the Open Archives Initiative. D-Lib Magazine 6(2):DOI: 10.1045/february2000-vandesompel-oai Vickery BC (2000) Scientific communication in history. Lanham, MD: Scarecrow Press Webster JG (2003) How to create a bibliography. Journal of Extension 41(3)

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Webster JG, Collins J (2005) Fisheries information in developing countries: support to the implementation of the 1995 FAO Code of Conduct for Responsible Fisheries. Rome, Italy: Food and Agriculture Organization of the U.N.; (FAO Fisheries Circular No. 1006) White RW, Jose JM, Ruthven I (2003) A task-oriented study on the influencing effects of query-biased summarisation in web searching. Information Processing and Management 39(2003):707–33 White S, Creaser C (2004) Scholarly journal prices: Selected trends and comparisons. Leicestershire, UK: Library and Information Statistics Unit, Loughborough University; (LISU Occasional Paper: 34) World Intellectual Property Organization [2006]. Copyright FAQs: What rights does copyright provide? [Web Page]. Located at: http://www.wipo.int/copyright/en/faq/faqs.htm#rights. Accessed 2006 Sep 1

Chapter 3

Extended Guide to Some Computerized Artificial Intelligence Methods Saul B. Saila

3.1 Introduction The purpose of this chapter is to reassess and extend some of the earlier concepts and developments related to computerized artificial intelligence methods described initially (Saila, 1996). These new concepts and developments were derived from about a decade of increasing activity in this subject area. Due to this increased activity a certain amount of subjectivity has been required in order to keep this review from becoming too detailed and lengthy. Therefore, most examples of various newer developments are restricted to those believed to have fishery science applications; new methodologies deemed especially useful in fishery science applications are described in more detail. During this past decade of rapid developments in artificial intelligence there has also been considerable effort to combine some computing paradigms, such as fuzzy set theory, neural networks, genetic algorithms, rough sets, and casebased reasoning as well as other methodologies for the purpose of generating more effective hybrid systems. These are now termed soft computing. In soft computing the individual tasks act synergistically, not competitively, enhancing the application domain of the other. The purpose of these combined soft computing methods is to develop flexible information processing systems that can exploit tolerance for imprecision, uncertainty, approximate reasoning, and partial truth in order to achieve tractability and close resemblance to human decision making. These methods may also provide a reduction in solution costs. The term soft computing, in contrast to conventional (hard) computing could be characterized as automated intelligent estimation. It is intended to provide an alternative to conventional computing that allows for the formal and systematic treatment of problems which, due to their complexity, size and/or uncertainty, are not practical to solve in a conventional manner. Soft computing is thought to arise from a recognition that some complex problems do not lend themselves to solution by any conventional (hard) computing methods. Soft computing attempts to emulate and articulate the techniques used by intelligent humans to S.B. Saila (*) 317 Switch Road, Hope Valley, RI 02832, USA

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deal adequately and quickly with complex problems and causes; in effect, to mimic what is often called ‘‘human intuition’’. Unfortunately, there appears to be confusion regarding some of the terminology applied to soft computing. This is believed to be due to the relatively rapid developments of this concept (Corchado and Lees, 2001). For example, although the terms case-based reasoning and rough sets apply soft computing generally, they may also be included as methodologies applied to data mining. Herein, data mining is defined as the process of extracting information and patterns, often previously unknown, from large quantities of data using techniques such as machine learning and various statistical procedures. For the purposes at hand, case-based reasoning and rough sets are considered to be soft computing techniques which may be effectively utilized in data analysis from multiple sources or with variable hypotheses. I believe that case-based reasoning and rough sets are also tools useful to and included in the more general term data mining. ‘‘Meta-analysis’’ is another term, similar to or synonymous with data mining, frequently used by fisheries scientists and ecologists to describe what I suggest is some form of data mining. The free encyclopedia wikipedia (http://en.wikipedia.org/wiki/ metaanalysis) states that ‘‘In statistics, a meta-analysis combines the results of several studies that address a set of related research hypotheses.’’ Data mining has been defined as the nontrivial extension of implicit, previously unknown, and potentially useful information from data by the above-mentioned source. On the other hand, in case-based reasoning systems expertise is embodied in a library of past cases, rather than being included in classical rules. Each case typically contains a problem description as well as a solution or outcome. These are utilized to form a solution to new data. Some examples of published work in fisheries and ecology utilizing the term meta-analysis include Myers and Mertz (1998) who utilize this approach in an effort to reduce uncertainty in the biological basis of fisheries management. Taylor and White (1992) studied the hooking mortality of nonanadromous trout from 18 studies using meta-analysis methodology. Englund et al. (1999) offer some recommendations regarding the conclusions from meta-analysis which, he asserts, could be colored by the data selection process. Myers et al. (2001) describe statistical methods to allow many data sets to be analyzed simultaneously. These methods provide some further strength to the analyzed data. A short summary of some meta-analysis applications suggests to me that the perhaps better and more generic term (data mining) might be used in the future in order to embrace all the methodologies related to the more effective utilization of complex data that address some related research hypotheses with statistical and analytical tools. This definition seems to coincide with the definition of Hastie et al. (2001). In addition, data mining is a widely used term in business applications. The recent book by Walters and Martell (2004) clearly and concisely describes the derivation, use, and abuse of various mathematical models which have been utilized for decisions regarding the management of harvested aquatic ecosystems. It is evident from this book that quantitative modeling

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methods have become a central tool in the management of harvested fish and invertebrate populations. These models are complex and they include structural diversity as well as dynamic complexity with feedbacks. The conclusion by the authors is that it is impossible to fully capture the rich behavior of ecosystems in mathematical models. However, they also offer cogent arguments for continuing efforts to build useful mathematical models in the future. Although I agree with the conclusions of the above authors regarding the need for further developments in this kind of modeling (hard computing), it also seems to me that the versatile tools of computerized artificial intelligence, now known as soft computing, should not be ignored. Indeed, they may offer some useful alternatives to conventional models in the search for effective and adaptive fishery management at both the species and system levels.

3.2 Working with Some Forms of Fisheries Data Some fisheries data can be disorganized, ambiguous, often incomplete, and yet quite detailed. These data can contain an abundance of information, but data can also be imprecise. Generally data has been examined using equations, algorithms, decision tables, and decision trees. Although many deterministic and stochastic models of fisheries systems exist, the overall quality of the input data is often inadequate; and thus, the input to the models may not adequately meet the assumptions and requirements of the models. It seems clear that these models deserve careful and thoughtful validation as well as further study, with more active consideration of other approaches to fishery management. In fishery science, as in other areas of science, there is a tendency for one to commit oneself to a particular methodology in the belief that it is that methodology alone which matters. Professor Lotfi Zadeh, an outstanding scientist, has enunciated two principles related to methodological tunnel vision. The first is the hammer principle, which states that when the only tool one has is a hammer, then everything looks like a nail. The second is the vodka principle, which states that no matter what the problem is, vodka will solve it! It seems apparent that there is a substantial amount of the ‘‘one size fits all’’ mentality in fishery science, and it therefore seems important to suggest means for countering this situation. Professor Zadeh has also made a profound statement concerning the mathematical complexity of systems. It is quoted as follows: ‘‘As the complexity of a system increases, our ability to make precise and significant statements about its behavior diminishes until we reach a threshold beyond which precision and significance (or relevance) become almost exclusive characteristics.’’ More recently, Ulanowicz (2005) has reinforced the above quotation of Zadeh by stating that emergent attributes of complex living systems render the conventional Newtonian postulates as inappropriate for ecosystem

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dynamics. He suggested the use of network analysis to describe complex systems about two decades ago (Ulanowicz, 1986), but this has not received much application to date. Frequently, knowledge can be expressed as logical rules, in spite of the fact that using rules makes representation of this knowledge less precise. An example is provided by the so-called ‘‘rule of thumb.’’ However, in spite of the loss of precision, using rules has an advantage in making knowledge easier to explain to others. We do not always need detailed data and/or mathematical models to reason about facts, events, and problems. An excellent example is provided by physicians who diagnose a patient’s condition on the basis of general data, such as whether or not the patient’s temperature is elevated. This is derived from a simple thermometer reading. Indeed, the utility of coarse data is supported by our everyday experiences. Too much data may be confusing or disturbing and may prevent us from organizing the data into useful patterns. One approach to dealing with organizing data into useful patterns will be briefly described. It is suggested that it is sometimes reasonable to analyze an empirical data set to derive the maximum amount of information from the data itself instead of developing a functional model which may often be based on unrealistic assumptions.

3.3 Rough Set Concepts, Introduction, and Example A relatively new formal framework (rough sets) for discovering facts from imperfect data has been developed by Pawlak (1982). Rough sets provide tools for data analysis and rule discovery from imprecise and ambiguous data. Some advantages of rough set theory described in Pawlak (1999) are as follows: (a) It provides for both qualitative and quantitative descriptions of data; (b) It accommodates data inconsistencies as well as different distributions; (c) It allows for selection of the most important attributes, and the generation of ‘‘if. . .then. . .’’ rules as well as classification of future events. Rough sets may sometimes be confused with fuzzy sets. Both rough sets and fuzzy sets address the need to effectively use imperfect knowledge. However, fuzzy sets address the vagueness of information, whereas rough sets address indiscernability, or imprecision and ambiguity of data. The material which follows includes a brief review and some background including an example of a fishery related utilization of rough sets. This is only a crude example of the basic concepts and the reader interested in further details is referred to Pawlak (1991) and Slowinski (1992) for a much better understanding of rough set concepts and applications. Other useful reference books include Polkowski (2002), which deals with the mathematical foundations of rough sets, and Orlowska (1998), which deals with both theory and applications.

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Rough set theory has attracted considerable attention within the scientific community for more than a decade. Although rough set theory provides a mathematical approach to deal with problems which involve uncertainty and vagueness, I am not aware of any direct applications to date in fishery science. Motivation for the use and development of this approach seems justified for fishery scientists because rough sets can be developed with both qualitative and quantitative descriptions of data, rough sets do not require specific data distributions, and the method can accommodate data inconsistencies. Other advantages of rough set theory involve a method for the selection of the most important attributes of a data set, easily interpreted ‘‘if. . .then’’ rules and classification of future events. The advantage of rough set theory according to Grzymala-Busse (1988) is that it does not need any preliminary or additional information about data, such as probability distributions as in statistics, basic probability assignment as in Dempster-Shafer theory, or grade of membership or value of possibility as in fuzzy set theory. Several contributions have already been made to the development and application of rough sets in diverse areas of science. Some specific examples include Slowinski (1995), Lin and Wildberger (1995), Ziarko (1995), Rossi et al. (1999), and Che`vre et al. (2003). These examples of rough set applications range in diversity from decision analysis to industrial and engineering applications. Of particular interest and relevance to fishery science are studies related to pollution control in aquatic ecosystems. The material which follows, largely derived from the work of Rossi et al. (1999), and Pawlak et al. (1995), is included because I believe this application is relevant to some problems in fishery science. Briefly, rough set philosophy is founded on the assumption that every object of a universe of discourse is associated with some information. Objects characterized by the same information are indiscernible (that is, they can’t be recognized as different from each other) in light of the available information about them. The indiscernability which is generated in this manner seems to provide the mathematical basis of rough set theory. Objects which are indiscernible from one another with respect to some attributes are termed an elementary set, and it forms a basic ‘‘granule’’ of knowledge about the universe being considered. Any set of objects which may be represented as a union of some elementary sets is referred to as crisp (precise) in the context of the given attributes, or otherwise the set is rough (imprecise). As a consequence, each rough set has some borderline cases. These are objects that cannot be classified with certainty as members of the set or its complement. Rough set theory handles rough sets by replacing each object with a pair of crisp sets. These are called the lower and upper approximations. The lower approximation consists of all objects which belong to the set with certainty, and the upper approximation contains objects which possibly belong to the set. An elementary example follows. Information about the real world is provided in the form of an information or decision table. Rows of the table correspond to the objects (examples, sites, entities) and the columns of the table describe

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S.B. Saila Table 3.1 Example information table for concept development using juvenile brook trout habitat variables and estimated abundance Site FN VD GS JBT s1 Y Y Low Low s2 Y Y Med High s3 Y Y High High s4 N Y Low Low s5 N N Med Low s6 N Y High High Note: FN refers to a Froude number 200 m) in the south east. This is mainly a consequence of the Somalia upwelling that brings nutrients to these waters during most of the year but particularly during the summer southwest monsoon. The author has used GIS to determine and plot maps showing temporal sequences for various species. These maps relate either catch or CPUE to variables such as sea surface temperature or bathymetry, and thus show the seasonal spatial ‘‘evolution’’ of the catches.

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Fig. 4.4 Spatial distribution of total emperor catch (kg) in Omani waters – 1996–2004

4.4.4 Preliminary Estimates of the Sea Cucumber Abundance Around Ilha Grande, Rio de Janeiro, Brazil This case study concentrates on the very local scale, one that may typify a subsistence fishery activity. The authors (Miceli and Scott 2005) have sought to establish a preliminary estimate of the abundance of Isostichopus badionotus (sea cucumber) around the Ilha Grande near Rio de Janeiro, Brazil. It is important to do this because the animal is being illegally exploited to service a high demand from Far East Asian markets. I. badionotus is now on a Brazilian endangered species list.

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If its exploitation could be regularised and stocks could be properly managed then there is the potential to supply a good living for large numbers of local subsistence fishers. In their study the authors used a low cost, raster-based GIS, ‘‘IDRISI Kilimanjaro’’ (supplied by Clark University in Massachusetts, USA). They identified the controlling parameters to local sea cucumber production as:

    

Living in coastal waters of 14 m). Five different scenarios were explored where fishing on the main species, a red alga, a scallop, a gastropod and a crab, occurred in either seagrass, sand-gravel or sand habitats exclusively, on both seagrass and sand-gravel habitats, or on all habitats. On the basis of biomass changes, the authors concluded that the sand-gravel habitat was the most resistant to fishing, and that fishing 2–3 habitats simultaneously had the greatest negative effect on the ecosystem. They further concluded that a rotational harvest policy should be recommended for this Bay. Most Ecospace applications have focused on Marine Protected areas, and indeed, Walters et al. (1999) identified Ecospace as an important exploratory tool for MPA definition and function and policy exploration. Using a simple model of Brunei Darussalam, they concluded that biomass gradients would exist along the edges of MPAs, resulting from fishing activity along the MPA boundary on the increased density of predators within the MPA, causing a decrease in the density of predators within the MPA (fishing would also lower immigration to and emigration from the MPA). At the same time, trophic cascades are likely to occur within the reserve due to the increase in density of large predators, resulting in a decrease of small fish. Density dependent effects would lead to the emigration of large predators, resulting in reduced predator biomass within the MPA. They further conclude that a few large MPAs are more effective than more small MPAs. This is largely due to the fact that a few large MPAs have a smaller boundary (where fishing takes place) than many small MPAs (for the same total area). Thus the more boundaries there are the more dispersion can take place, and the greater the effects of fishing on the boundaries. These results have been confirmed by other Ecospace studies (e.g. Pitcher et al. 2002b, Salomon et al. 2002, Martell et al. 2005) (Fig. 8.15). Indeed Salomon et al. (2002), who explored various options for marine protected area zoning policies in the Gwaii Haana National Marine Conservation Area, Canada, concluded

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% Change in biomass from baseline

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Fig. 8.15 The Single Large or Several Small (SLOSS) debate. The percent change in ecosystem component biomass from a baseline simulation of no protection as a consequence of splitting one large Marine Protected Area (MPA) into three small MPAs. Simulations were compared once they had run for 10 years. Reprinted from Salomon et al. 2004. Modelling the trophic effects of marine protected area zoning policies: a case study, Salomon et al. (2002), with permission from Springer Science and Business Media

that buffer zones were effective tools against edge effects and biomass density gradients but that there is no optimum reserve design since the design depends on the goal. Okey et al. (2004) used an Ecospace model to demonstrate how the functional extinction of sea cucumbers in a Galapagos subtidal rocky reef could be avoided by protecting some of the reef from fishing (Fig. 8.7). Martell et al. (2005) explored the relative importance of different assumptions about dispersal and advection for Ecospace predictions under different fishing policy scenarios for the central North Pacific with respect to marine protected areas and concluded that MPAs for large pelagics need to be large. They split the central North Pacific into two habitats, warm water and cool water and developed 3 movement models: the default advection-diffusion movement model where dispersal rates were random and non-directional and two models where movement responded to a fitness measure, where fitness was the difference between productivity and predation. Movement increased in areas of low fitness and decreased in areas of high fitness. In the variable emigration model, any movement in response to fitness was random; in the directed movement model, movement was directed towards cells with higher fitness. The authors imported monthly current information from sea surface topography to calculate advection fields. Primary production in each grid cell was both dynamic and assumed to be proportional to the rate of upwelling (dynamic models) or static with long term average primary productivities. The three scenarios represented different degrees of closed areas and protected species policy, including the status quo. The authors concluded the static versus dynamic models results were sufficiently different, regardless of the movement model, to indicate that the temporal differences in surface currents should be explicitly considered when exploring and developing closed area policies

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Fig. 8.16 A representation of the main Ecospace findings for closed area policies, with alternative movement models representing different hypotheses about animal behaviour and static forced distributions of production (first column) versus dynamic forced distributions of production, where monthly surface current information us used to predict spatial variability in primary production (second and third columns). The second row represents the spatial distribution of forage, were surface currents advect forage in the second and third columns. Each diagram represents a cross section or transect of the spatial distribution of abundance (and fishing effort) across an Ecospace map. Fishing effort distribution for top predators is represented by as the dotted line. Shaded polygons represent distributions of biomass along the transect at equilibrium; the area of each polygon is proportional to biomass. Vertical dashed lines represent marine protected area boundaries; arrows represent current directions; U, upwelling; D, downwelling or convergence zones. Reprinted from Martell et al. 2005. Interactions of productivity, predation risk, and fishing effort in the efficacy of marine protected areas for the central Pacific. Canadian Journal of Fisheries and Aquatic Sciences 60: 1320–1336, with permission from NRC Research Press

(Fig. 8.16). In particular, they were concerned that interannual variability in oceanic processes can affect the efficacy of MPAs since the position of convergence zones, where species aggregate, including tuna, can change from year to year, potentially lying beyond the MPA boundary. In this case, protected species would be subject to high fishing mortality. In general, the results were robust to the three movement models, suggesting that further research into the movement of large pelagics is not required.

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Like Ecosim, Ecospace can also be used for policy exploration, such as tradeoffs between compliance with fishery regulations and conservation in the Hong Kong artificial reef system (Pitcher et al. 2002b). In the latter, a scenario was explored in where fishing was permitted in one artificial reef, assuming that this would lead to greater support for the artificial reef scheme and selfenforcement.

8.4 What Ecopath with Ecosim Can Do for You (and What It Can’t) 8.4.1 Ecopath with Ecosim as a Diagnostic Tool Ecopath models have proved useful in identifying data gaps and sensitive interactions, thus guiding research (e.g. Halfon and Schito 1993, Bundy 2004b). In addition, they are useful in refining parameter estimates for poorly known groups according to the constraints of the interactions defined within the Ecopath models (Okey and Pauly 1999). By construction of an Ecopath model, the biological and ecological data available from an ecosystem is identified, analyzed, contextualized and evaluated. Ecopath models can also be used to test low quality data, for example the biomass of benthopelagic species or suprabenthos, which are difficult to estimate but represent an important proportion of the diet of many species within marine ecosystems. These models can calculate the minimum biomass necessary in the ecosystem to sustain total mortality of these groups if predation and fishing mortality are well characterized (e.g. Lam and Pauly 2005). Another example can be found in stomach contents data, where soft preys can be underestimated with respect to species with hard-body parts (like fish and crustaceans). Thus, Ecopath can be useful in the correction of trophic data given biomass of predators and prey, and estimates of consumption.

8.4.2 Dynamic Simulations as Management Tools for an Ecosystem Approach to Fisheries It is readily accepted that multispecies approaches to fisheries management should not and cannot fulfil the role of single-species fisheries management approaches, but that they should rather be considered as complementary approaches in a model ‘‘toolbox’’ from which management advice can be drawn (Starfield et al. 1988, Whipple et al. 2000). In the long-term, multispecies approaches can produce totally different management advice to the more traditional single species modelling approaches (e.g. Magnu´sson 1995, Stokes 1992), yet in the short term, advice may be similar (Christensen 1996). Cox et al.

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(2002) showed that EwE was better able to represent and explain species recoveries after severe fishing of apex predators than single species models. The lack of any formal process to reconcile (or check whether it is feasible to reconcile) the management strategies of single-species management approaches to attain different goals, has led to conflicting management advice being provided at the single-species level, and thus highlights the need for a multispecies or ecosystem approach (Murawski 1991). Dynamic Ecosim simulations can shed light on the possible ecosystem effects of different fishing strategies, although the model assumptions, such as flow control parameter settings, need to be carefully acknowledged and sensitivities of simulation results explored. The more recent development of the ability to fit EwE models to time series data, which includes refinement of vulnerability settings describing flow controls, has increased confidence in model predictions. This creates a more robust basis for testing hypothetical fishing scenarios, and leads to greater confidence in the information that these may provide for fisheries management. The fishing policy search and optimization routine provides an additional means of exploring the dynamic responses of the ecosystem to hypothetical fishing strategies which may optimize one or a combination of policy objectives, and provides managers with guidelines as to the likely trade-offs that are involved in prioritising one objective over another, or in trying to optimize several simultaneously.

8.4.3 Examining Emergent Properties Through Ecosystem Indicators The construction of EwE models facilitates the estimation of trophodynamic indicators and ecological analyses that can be useful tools for an ecosystem approach to fisheries. Trophodynamic indicators measure the strength of interactions between species or species groups within an ecosystem, and the structural and functional changes that occur in an ecosystem as a result of fishing (Cury et al. 2005). Of the 46 trophic indicators identified in the literature, Cury et al. (2005) selected six for closer examination using data and EwE models of the northern and southern Benguela ecosystems (Fig. 8.17), namely catch or biomass ratios, production or consumption ratios and predation mortality, primary production required to produce catch (PPR), trophic level of the catch (TLc), fishing in balance (FIB) index and mixed trophic impact (MTI), see above. The PPR expresses the catch in terms of equivalent flows of primary producers and detritus and can be normalized per unit of catch relative to the primary production and detritus of the ecosystem (%PPR). This measure is used as an indicator of the footprint of the fishery and can be employed as an indicator of fishing intensity (Pauly and Christensen 1995).

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Ecosystem Modelling Using the Ecopath with Ecosim Approach

Catch (’000 tons)

NORTHERN BENGUELA Hake

Sardine

2 000

Other

Large horse mackerel

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(a)

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Sardine

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Horse mackerel

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0.9

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(c) 3.9 3.7 3.5 3.3 3.1 2.9 2.7

3.8 3.7 3.6 3.5 3.4 3.3

(d) 0.7 0.6 0.5 0.4 0.3 0.2 0.1

FiB index

2.5 2 1.5 1 0.5

TL of catch

1955 3.9 3.7 3.5 3.3 3.1 2.9 2.7

1965

1975

1985

1995

1993

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1961

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5.5

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3.8 3.7 3.6 3.5 3.4 3.3

1985

1995

1991 1956

1996

1998 2000 1976

1950

1961 1959

5.5

6

6.5

Log (catch)

Fig. 8.17 Example of selected ecosystem indicators estimated using EwE models for the northern and southern Benguela ecosystems. Adapted from Cury et al. (2005) and used by permission of Elsevier

The Fishing in Balance (FIB) index can be easily calculated from catch data and TLc over time (Christensen 2000, Pauly et al. 2000) and measures whether a change in the trophic level of the catch in a given ecosystem is matched by concurrent changes in productivity (i.e. lower trophic level of the catch, higher productivity and FIB = 0). Overfishing is evident when the trophic level of the fishery decreases, but is not matched by increased productivity (FIB < 0).

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Alternatively, FIB can indicate whether there is an expansion of the fishery (FIB > 0), whether bottom–up effects are occurring (FIB > 0) or whether discarding is not considered in the analysis of impacts of fisheries on the ecosystem and is so high that its functioning is impaired (FIB < 0). The above trophodynamic indicators have been widely applied to different ecosystems. However, Cury et al. (2005) noted that these indicators were relatively conservative as they are slow to respond to large structural ecosystem changes. For example, the mean trophic level (TL) of the Namibian catch failed to reveal the sequential depletion of Namibian commercial fish stocks because the ecosystem had shifted productivity to non-exploited species that were not reflected in the catch data. On the other hand, the FIB index, viewed in conjunction with plots of TL of catches against catches, was shown to reflect the historical development and status of fisheries in South Africa and Namibia more successfully than other indicators that can be derived from catch statistics (Fig. 8.17). Ecopath mass-balance models can also be used to calculate standardized size spectra of the ecosystem, i.e. the distribution of biomass according to size of individuals (Pauly and Christensen 2004), which can be then compared between ecosystems. Size spectra is used to characterize the structure of a system and the fishing intensity over time due to the fact that the slope of size spectra plots reflects the exploitation level, being steeper when exploitation is high (Bianchi et al. 2000). Results from Ecopath and Ecosim can also be used to track functional changes of the ecosystems. Examples of emergent properties are the transfer efficiency, the flow to detritus and production ratios presented in Section 8.2.1.3. From MTI analysis, Libralato et al. (2006) developed and applied a method for identifying keystone species (or groups of species) in different ecosystems. Keystone species are those that are present at relatively low biomass levels but have a structuring role in the ecosystem (Power et al. 1996). Therefore they can be identified when the relative overall effect and the ‘‘keystoneness’’ are plotted against one another. The index is high when species or groups of species have both low biomass proportions within the ecosystem and high overall effects. Changes in keystone species can be analysed when different trophic models of an ecosystem are available, e.g. the importance of cetaceans as keystone groups was seen to decrease over time in various ecosystems (Libralato et al. 2006) (Fig. 8.18). Comparisons of ecosystem indicators from the same ecosystem in different periods of time or from different ecosystems when using standardized models can be very useful tools as discussed in the previous case studies section. However, trophodynamic indicators are mostly still descriptive at this stage and it remains for reference points to be clearly identified. Cury et al. (2005) advise that a suite of indicators be used to monitor and quantify ecosystem changes as a result of fishing. To define quantitative reference levels to analyze fishing impacts on ecosystems, a new composite index (integrating PPR, TLc and transfer efficiency TE was defined by Libralato et al. 2008): L index. This index represents the theoretical depletion in secondary production due to fishing and is formulated as a proxy for quantifying ecosystem effects of fishing. The

8

Ecosystem Modelling Using the Ecopath with Ecosim Approach 0.5

0.5

Newfoundland 0.0 13 15 14 1918 17 20 2221 24 2523 26 27 28 29 30 31 32 33 34 36 35

–0.5

–1.0

37 38 39 –1.5

–2.0

40 41

–2.5 42 43 44

Keystoness

277

–3.0

1198 710 12

6

Estern Tropic Pacific

1 4 5

3

2

0.0

98 1110 12 15

13

65 4 7 14

21

3

16

16

18

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19 20 2221 23 24

–1.0

1 Cetaceans 2 Capelin 3 Harp seals 4 Hooded seals 5 L zooplankton 6 G halibut 7 Bivalves 8 Pollock 9 G halibut juv. 10 Phytoplankton 11 Small mesopelagics 12 S zooplankton 13 Piscivorous birds 14 Polychaetes 15 Large crabs

16 Echinoderms 17 Herring 18 Shrimp 19 Juv dem pisc 20 S plank dem feed 21 Small pelagics 22 Squid 23 Sandlance 24 Redfish 25 O benthic inver 26 Arctic cod 27 L plankt dem feed 28 Skates 29 Cod + 40cm 30 Aplaice