MARINE BIOLOGY VOLUME 29
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MARINE BIOLOGY VOLUME 29
J. H. S. BLAXTER Dunstaffnage Marine Research Laboratory, Oban, Scotland and
A. J. SOUTHWARD
The Laboratory, Citadel Hill,Plymouth, England
Academic Press Harcourt Brace & Company, Publishers London San Diego New York Boston Sydney Tokyo Toronto
ACADEMIC PRESS LIMITED 24/28 Oval Road London NW17DX United States Edition published by ACADEMIC PRESS INC. San Diego, CA 92101 Copyright 01993 by ACADEMIC PRESS LIMITED ‘The Bristol Channel Sole (Solea solea (L.)): A Fisheries Case Study’ by J. Horwood - Crown Copyright 01993. All rights of reproduction in any form reserved No part of this book may be reprinted in any form by photostat, microfilm, or any other means, without written permission from the publishers A catalogue record for this book is available from the British Library.
ISBN 0-12-026129-4 ISSN 0065-2881
Filmset by Keyset Composition, Colchester Printed and Bound in Great Britain by Hartnolls Limited, Bodrnin, Cornwall.
CONTRIBUTORS TO VOLUME 29 J. HORWOOD, Ministry of Agriculture, Fisheries and Food, Directorate of
Fisheries Research, Fisheries Laboratory, Lowestoft, Suflolk NR33 OHT, UK.
T. KIORBOE,Danish Institute f o r Fisheries and Marine Research, Charlottenlund Castle, DK-2920 Charlottenlund. Denmark. H. KUOSA,Finnish Institute of Marine Research, PO Box 33, SF-00931 Helsinki, Finland.
J. KUPARINEN, Finnish Institute of Marine Research, PO BOX 33, SF-00931 Helsinki, Finland,
T. SUBKAMONIAM, Department of Zoology, University of Madras, Guindy Campus, Madras 600 025, India.
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CONTENTS CONTRIBUTORS TO VOLUME 29
Turbulence, Phytoplankton Cell Size, and the Structure of Pelagic Food Webs T. [email protected]
.. .. .. .. .. .. Introduction .. .. Turbulence, Water Column Structure and Phytoplankton Cell .. .. .. .. .. .. Size .. .. .. A. Empirical evidence . . .. .. .. .. .. .. B. Cell size and sinking .. .. .. .. .. C. Cell size and nutrient uptake kinetics: the case of diffusion .. .. .. .. .. .. limitation .. .. D. Effect of cell motility and sinking on nutrient uptake .. E . Effect of turbulence on nutrient uptake .. .. .. F. Photosynthesis, phytoplankton cell size and turbulence . . G. Predation and phytoplankton cell size .. .. .. 111. Implications of Phytoplankton Cell Size and Turbulence for the Fate of Pelagic Primary Production . . .. .. .. A . Grazing, phytoplankton cell size and turbulence . . .. B. Excretion of DOM, phytoplankton cell size and productivity of pelagic bacteria . . .. .. .. .. .. C. Sedimentation: Turbulence, cell size and the formation of phytoplankton aggregates .. .. .. .. .. IV Vertical Mixing and the Structure of Pelagic Food Webs . . A. Seasonal events .. .. .. .. .. .. .. .. .. .. .. B. Wind events .. .. .. .. .. .. .. .. C. Fronts .. .. . . . . . . Summary and Conclusions . . . . V. Acknowledgements . . . . . . . . . . . . . . VI . References . . . . . . . . . . . . . . . . VII.
4 4 8 10 12 14 15 18 22 22 29
35 41 42 47 50 60 61 61
Autotrophic and Heterotrophic Picoplankton in the Baltic Sea J. KUPARENEN A N D H. KLJOSA
Preface .. .. .. .. .. .. .. .. .. I. Introduction .. .. .. .. .. .. .. A. The Baltic Sea .. .. .. .. .. B. Picoplanktonic algae .. .. .. .. .. .. 11. Methods.. .. .. .. .. .. .. .. .. A . Autotrophic picoplankton .. .. .. .. .. B. Bacterioplankton . . . . .. .. .. .. .. .. .. .. 111. Phytoplankton Succession in the Baltic Sea .. .. .. IV. Autotrophic Picoplankton in the Baltic Sea .. .. .. A . Areal and vertical distribution .. B. Seasonal variation. . . . .. .. .. .. .. V. Bacterioplankton in the Baltic Sea .. .. .. .. A. Annual and seasonal variation of bacterioplankton pro.. .. .. .. .. .. .. .. duction B. Distribution of bacterioplankton .. .. .. .. VI. Factors Controlling Autotrophic Picoplankton . . . . .. A . Nutrients and temperature .. .. .. .. .. .. .. .. .. B. Grazing .. .. .. VII. Factors Controlling Bacterioplankton .. .. .. .. A. Nutrient- and carbon-limited bacterioplankton growth . . B. Predation control of bacterioplankton .. .. .. VIII. Bacteria in the Pelagic Food W e b . . . . .. .. .. IX. Acknowledgements . . .. .. .. .. .. .. .. .. .. .. X. References .. .. .. .. t
73 75 75 77 81 81
85 87 87 87 90 92 92 97 101 101 104 105 10s 111 1IS 119 119
Spermatophores and Sperm Transfer in Marine Crustaceans T. SUBRAMONIAM
Introduction . . .. .. .. .. .. .. Sperrnatophore Morphology, Composition and Transfer A. Decapoda . . . . .. .. .. .. .. B. Copepoda . . . . .. .. .. .. .. C. Euphausiids .. .. .. .. .. ..
. .. .. .
129 133 133 174 183
111. IV . V. VI . VII
D. Stomatopoda .. .. .. .. .. .. . . 184 E. Mysidacea and other spermatophore-producing marine crustaceans .. .. .. .. .. .. . . 184 Spermatophore Hardening .. .. .. .. . . 186 Cryopreservation of Spermatophores .. .. .. . . 187 Spermatophores and Artificial Insemination .. .. . . 189 .. .. .. .. . . 193 Spermatophore Pathology . .
Comparison with Other Spermatophore-producing Marine .. .. .. .. .. Invertebrates . . .. .. .. .. .. .. .. A . Polychaeta . . . . .. .. B. Pogonophora .. .. .. .. .. .. .. .. .. .. C. Chaetognatha .. .. .. .. .. .. .. .. D , Mollusca . . .. .. VIII. Conclusion .. .. .. .. .. .. .. .. .. .. IX . Acknowledgements . . .. .. .. .. .. .. References .. .. X. I
195 195 196 196 196 197 200 201
The Bristol Channel Sole (Solea solea (L.1): A Fisheries Case Study J. HORWOOD
Introduction . . .. .. .. .. .. A. Classification and identification .. .. .. .. B. Description and related genera Distribution and Movements .. .. .. .. A. Physical characteristics of the region . . B. Eggs and larvae . . .. .. .. .. C. Juveniles . . .. .. .. .. .. .. .. .. .. D . Adults .. .. E. The Bristol Channel “stock” . . .. .. Feeding, Size and Growth . . . . .. .. A . Feeding .. .. .. .. .. .. .. .. B. Size and growth: general aspects C. Length at age .. .. .. .. .. D . Weight at age .. .. .. .. .. .. .. .. .. Reproduction . . .. A . Spawning behaviour .. .. .. .. B. Seasonaldevelopment and time of spawning
.. .. .. .. .. ..
.. .. .. .. .. ..
.. .. .. .. ..
.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..
216 219 220 221 221 229 237 246 249 251 251 254 255 262 266 267 268
C. Distribution, size and age with maturity D. Fecundity .. .. .. V. Natural Mortality Rates .. .. .. A. Eggs and larvae . . .. .. .. .. .. .. B. Juveniles . . .. .. .. .. C. Adults .. .. D. Comments . . .. .. .. .. VI. Harvesting Options . . .. .. .. A. Yield per recruit . . .. .. B. Absolute yields . . .. .. .. C. Spawning stock biomass per recruit . . D. The stock and recruitment relationship E. Bioeconomics and dynamics . . .. F. Appropriate fishery targets .. .. VII. Exploitation of the Bristol Channel Sole A . Early fisheries .. .. .. .. B. Early trawl fisheries .. .. .. C. Early quantitative information.. .. D . Catches from 1903 .. .. .. E. Evolution to the modern fishery .. VIII. Status of the Stock . . .. .. .. A. ICES assessments .. .. .. B. Egg-production based assessments . . C. Comparison of assessment methods . . D. Mark-recapture estimates .. .. E. Simulation of population trajectories. . F. Concluding remarks .. .. .. IX. Some Final Comments .. .. .. X. Acknowledgements . . .. .. .. .. .. .. XI. References .. .. .
Taxonomic Index .. .. .. Subject Index .. Cumulative Index of Titles Cumulative Index of Authors
.. .. ..
.. .. .. ..
.. .. ..
.. .. .. ..
.. .. .. ..
.. .. .. .. .. ..
.. .. .. .. .. .. ..
.. .. .. .. .. ..
. . 29 1 . . 294 . . 295 . . 298 . . 299 . . 300 . . 311 . . 315 . . 316 . . 319 . . 32 1 . . 322 . . 323 . . 324 . . 326 . . 327 . . 330 . . 334 . . 335 . . 336 . . 339 . . 342 . . 343 . . 347 . . 348 . . 352 . . 352
.. .. ..
. . 369 . . 373 . . 389
. . 393
.. .. .. .. .. .. .. .. .. ..
.. .. .. .. .. .. ..
.. .. ..
.. .. .. ..
. . 27 5 . . 279 . . 290
.. .. ..
Turbulence, Phytoplankton Cell Size, and the Structure of Pelagic Food Webs T. Kiarboe Danish Institute for Fisheries and Marine Research, Charlottenlund Castle, DK-2920 Churlottenlund, Denmark
.. .. .. .. .. .. .. Introduction .. .. .. Turbulence, Water Column Structure and Phytoplankton Cell Size . . A . Empirical evidence . . . . .. .. .. .. .. .. B. Cell size and sinking .. .. .. .. .. .. .. C . Cell size and nutrient uptake kinetics: the case of diffusion limitation .. D. Effect of cell motility and sinking on nutrient-uptake .. .. .. E. Effect of turbulence on nutrient uptake .. .. .. .. .. F. Photosynthesis, phytoplankton cell size and turbulence .. .. .. G. Predation and phytoplankton cell size .. .. .. .. .. 111. implications of Phytoplankton Cell Size and Turbulence for the Fate of Pelagic .. .. .. .. Primary Production .. .. .. .. A . Grazing, phytoplankton cell size and turbulence .. .. .. .. B. Excretion of DOM, phytoplankton cell size and productivity of pelagic bacteria ., .. .. .. .. .. .. .. .. C. Sedimentation: Turbulence, cell size and the formation of phytoplankton aggregates . , .. .. .. .. .. .. .. .. .. .. IV. Vertical Mixing and the Structure of Pelagic Food Webs A. Seasonal events .. .. .. .. .. .. .. .. B. Wind e v e n t s . . .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. C . Fronts .. .. Summary and Conclusions .. .. .. .. .. .. .. V. VI. Acknowledgements VII. References .. .. ..
ADVANCES IN MAKINE BIOLOGY VOLUME 29 ISBN 0-12-02612Y-4
2 4 4 8 10 12
14 1s 18
35 41 42 47
1. Introduction Until a few decades ago it was generally accepted that the majority of the phytoplankton production in the oceans was consumed by mesozooplankton, first of all copepods, and that these, in turn, were eaten by planktivorous fish. According to this classical description, the pelagic food chain is mainly linear and short, and there is a relatively close coupling between the primary production and the production of (pelagic) fish in the oceans (see Steele, 1974). It was further assumed that input of organic material to the sea floor is first of all made up of sedimenting copepod faecal pellets which thus provide the ultimate fuel for benthic heterotrophic processes. During the seventies and eighties it was realized that pico- and nano-sized phytoplankton (e.g. cyanobacteria) and heterotrophic microorganisms (heterotrophic bacteria, heterotrophic nanoflagellates and ciliates) play a much larger quantitative role in production and mineralization, respectively, of the phytoplankton than formerly believed. A new concept of pelagic food webs, known as the microbial loop, was developed (Azam et al., 1983). Since the discovery of the microbial loop the study of microbial processes in the pelagic realm has become increasingly popular. This popularity was, among other things, based on budgetary scaling arguments, showing that the biological activity in the water column is primarily due to microbial processes. Because the biomass of pelagic organisms is approximately constant in logarithmic size groups (Sheldon et ul., 1972), and because specific metabolic rates depend o n the body mass raised to an exponent of c. -%, it follows that the contribution to overall community metabolism decreases with the size of the organisms. In fact, with these assumptions more than 90% of the community metabolism is due to organisms smaller than 100 pm. According to such arguments, microorganisms account for the majority of the biological activity in the water column and “huge” organisms like fish in the centimetre to metre size range are absolutely uninteresting. However, there are still fish in the ocean, and from a fisheries point of view it is still interesting to know what fraction - however small it may be - of the primary production is channelled to fish; and, particularly, what the mechanisms are that determine the magnitude of this fraction. More recently the alternative views of microbial versus classical food webs have been combined into an emerging concept, according to which strongly stratified, oligotrophic environments are dominated by smallsized phytoplankters and a microbial loop type of food web, whereas weakly stratified or mixed, turbulent environments are dominated by large-sized phytoplankters and a classical type of food chain (Legendre and Le Fevre, 1989; Legendre, 1990; Cushing, 1989; Kierrboe ef uf.,
IUKUULENCE, PHYTOPLANKTON CELL SIZE A N D I’FI AGlC F001> WEUS
1090a). The production of fish in the sea is related primarily t o t h e latter type of environment where, potentially, a relatively large fraction o f the primary production is channelled to higher trophic levels. I t is the purpose of this paper to summarize t h e theoretical and empirical basis of this concept and in particular to investigate the significance of occanic turbulence and water column structure in determining the relative significance of microbial versus classical food chains in varying environments and, thus, the magnitude of fish production in the sea. Turbulence in the ocean is generated by winds, waves, currents and tides. Turbulence modifies the physical and chemical environment of planktonic organisms in several ways. First, turbulence will tend to erode vertical density structure of the water column and, although turbulence and vertical density structure are not unambiguously related, we shall here generally assume that stratified water columns are less turbulent than mixed water columns. This simplification is made among other things because it is relatively easy to measure the vertical density structure of a water column but difficult to quantify the turbulence. A related implication of turbulence is that it generally increases the availability of inorganic nutrients in the euphotic zone due to enhanced vertical mixing or entrainment of deep water into the surface layer. Thus, turbulent, mixed water columns are typically rich in inorganic nutrients, while inorganic nutrients are most often exhausted by the phytoplankton in t h e euphotic zone of stratified waters. Finally, turbulence modifies the light climate experienced by the phytoplankton. Phytoplankton cells suspended in a vertically mixed water column generally experience a more variable and, on average, lower light intensity than phytoplankton cells occupying the photic zone of a stratified water column. Turbulence also has direct effects on planktonic organisms, first of all by moving the organisms around and increasing the contact rate between suspended plankters. In the following sections we shall discuss how these several direct and indirect effects of turbulence and water motion influence the size distribution of the phytoplankton and affect the structure of pelagic food webs and the fate of pelagic primary production. We shall first (Section 11) consider the adaptive significance of phytoplankton cell size to the contrasting environments of stratified (stagnant) and mixed (turbulent) waters (nutrient uptake, light harvesting, predation). Subscquently (Section 111) we shall discuss the implications of phytoplankton cell size and turbulence to t h e fate of pelagic primary production (grazing, exudation of solute organics, aggregate formation and sedimentation). And finally (Section 1V) we shall synthesize all the individual processes considered in the preceding sections and compare pelagic food web structure in stratified versus verticallv mixed waters.
II. Turbulence, Water Column Structure and Phytoplankton Cell Size A.
It is generally believed that small (e.g. lo o m ) entirely mixed water columns, where light is limiting, phytoplankton biomass is low, and it appears that small cells also dominate in this type of environment. Thus, net-phytoplankton is typically restricted to, and blooms at, spatio-temporal transitions between mixed and stratified water columns (Legendre et al., 1986). These empirical relations between water column structure and phytoplankton cell size have been schematically outlined in Fig. 1. Classical examples of such spatio-temporal successions in phytoplankton composition and biomasses in relation to water column structure include the vernal temperature stratification in temperate waters and the associated spring bloom of diatoms and subsequent development of a nanophytoplankton community (e.g. Hallegraeff and Reid, 1986; Sournia et al., 1987; see also Figs 2 and 10). Such successions can also be found on much smaller spatio-temporal scales, such as in association with tidal and other types of fronts (e.g. Le Fevre, 1986; Richardson et al., 1986; Kiorboe ef al., 1988b; see also Figs 3 and 4), wind-mixing events (e.g. Hitchcock et al., 1987; Tanaka et al., 1988; Marra et al., 1990; Kiorboe and Nielsen, 1990; see also Fig. 21), spatial or temporal variation in water column structure due to tides (e.g. Demers e f al., 1986; Kiorboe et al., 1990a) as well as mesoscale upwelling events (e.g. Hanson et al., 1986; Peterson et al., 1988). Yet another example of the idea outlined schematically in Fig. 1 is given in Fig. 5. Thus, small and large phytoplankters appear to characterize different physical environments. Another characteristic difference between the occurrence of small and large cells in the oceans is their different degree of variability in abundance. Much of the variability in phytoplankton biomass in the sea is due to pulses in abundance of net-phytoplankton, while the concentration of pico- and nano-sized phytoplankton is much less variable (e.g. Malone, 1980; Furuya and Marumo, 1983). As a consequence chlorophyll concentrations are typically positively correlated to t h e mean cell size of the
TURBULENCE, P€IYTOPLANKTON CELL SIZE A N D PELAGIC FOOD WEBS
Vertical stability Small flagellates
Time (days-week-season) S p a c e (km-oceanwide)
FIG.I , Schcmatic outline of the relation between spatio-temporal variation in water column structure and phytoplankton biomass, size and species composition. Modified after idea of W . T. Peterson.
'I/ 0 F
FIG.2. Seasonal variation in the relative proportion of nanoplankton (i.e. cells < 2 0 p m ) in Long Island Sound, USA. The black bar represents the period when the water column is strongly stratified (i.e. when the vertical density gradient is >0.05 sigma-t u n i t s h ) . After Peterson and Bellantoni (1987).
T. K I 0 R B O E
56"45'N 01 "50'W
90 nautical miles
FIG.3. Variation in phytoplankton biomass across a tidal front in northeastern North Sea in October. (a) Temperature distribution. (b) Distribution of chlorophyll. Data from Kimboe er crl. (1988b).
phytoplankton (Harris et al., 1987). The relative constancy of pico- and nanoplankton abundance appears also to characterize other small suspended cells; e.g. bacterioplankton that typically occur at strikingly constant concentrations. Thus, Fogg (1986) in his picoplankton review found that, independent of temperature, salinity or nutrient status of the water, the concentration of bacteria and picophytoplankton in the ocean tends to be around 10' and lo4 cellsiml, respectively. In the following sections (1I.B-I1.G) we shall consider the adaptive significance of phytoplankton cell size to physical (turbulence, vertical mixing), chemical (nutrient concentration) and biological (predation) ~~
FIG.4. Horizontal variation in water column structure (as illustrated by the distribution of sigma-t, panel b) across the Skagerrak (panel a), and associated variation in the volume-ratio of large (>S p m ) to small ( 4p m ) suspended phytoplankton (panel c) in May. Note the striking correspondence hetwen the isopycnals and volume ratio iscilines. The lower panel (d) shows for the same data the relation between the volume ratio and the depth of the upper mixed layer, as represented by the depth o f the 26 sigma-t isopycnal. Redrawn from Kiorboe ef a / . (1990a).
TIJRBULENCE, PIIYTOPLANKTON CELL SIZE A N D PELAGIC FOOD WEBS
DENMARK 1 2 3 4 5
NORWAY 11 12 Station No
24 25 26
40 Depth, rn
3 4 5
12 Station No.
40 Volume ratio of >8 prn to 8 p m i < 8 prn
Particle concentration, ppm 0'30
0-24 m 24-60 m
0.4 0.2 -
Fic;. 5. Particle (phytoplankton) size distributions (equivalent spherical diameter) at a stratified (upper panel) and a partially mixed (lower panel) station in the English Channel in July. Note the difference in size distribution and total particle volume between the two stations. The phytoplankton at the stratified station was dominated by small, naked flagellates. while diatoms (mainly Rhizosolenia stolrerfothii) characterized the partially mixed station. Modified from Holligan et al. (1984).
properties of the environment, and its implications, in an attempt to explain t h e characteristic differences in occurrence and distributional patterns related to cell size as outlined above.
Cell Size and Sinking
Sinking of organic particles out of the photic zone represents a major loss of organic matter to the sea floor. A prerequisite for a given phytoplankton species to occur in a particular environment is, of course, that it is able to remain suspended. According to Stokes' law the sinking rate (v) of a spherical particle is proportional to the square of its radius (2) and to t h e differential density between the fluid and the particle ( p - p ' ) , i.e.: v
TURBUL-ENCE, P H Y T O P L A N K T O N CELL SIZE A N D PELAGIC FOOD WEBS
where g is the gravitational acceleration (982 cm/s2) and 7) is the viscosity of the fluid (approx. lo-' cm2/s for sea water). Flagellated forms, of course, have the potential ability to regulate their vertical position in the water column, but immobile forms, such as most diatoms, are at the mercy of Stokes' law. Several species have been shown to be able to exert some degree of buoyancy control by regulating their chemical composition (Eppley et al., 1967). Thus. generally, exponentially growing populations of diatoms have a lower differential density than nutrient-limited populations (e.g. Eppley et al., 1967; Smayda, 1970) and the latter, therefore, sink faster. The emphasis of this section, however, is the effect of cell size. A typical value of differential density, 0.05 gicm', is therefore inserted in eq. 1 to generate Table 1. Sinking rates calculated on the assumption of a size-independent, constant cell density tend to overestimate the sinking rate of large cells and underestimate sinking rates of small cells, because the specific carbon content and, hence, cell density tends to decline with cell size (Mullin et al., 1966). Taking the empirical carbon content vs. phytoplankton cell size of Mullin et al. into consideration (Jackson, 1989) yields more realistic estimates of sinking rate (Table 1). However, irrespective of the analyses performed it is evident from Table 1 that sinking rates of cells smaller than say 10 pm in diameter are insignificant, while cells 3 1 0 0 p m tend to fall rapidly out of the water column. Therefore, large cells depend on water motion to remain suspended. While this does not explain the dominance of large cells in turbulent environments it shows that turbulence is a necessary prerequisite for large cells to remain suspended.
TABLE1. SFTTLINO VELOCTT~ES FOR SPHERICAL PHYTOPLANKTON CELLSOF DIFFERENTSrzb CALCULATED FROM STOKES'LAW (EQ. 1) ~
Cell diameter (Pn)
Settling velocity (miday)
1 10 100 1000
2.36 X 2.36 x lo-' 2.36 X 10' 2.36 x 10'
1.99 x 2.94 x 4.35 x 6.44 x
lo-* lo-' 10" 10'
In ( I ) a constant differential cell density of 0.0Sgicm' has been assumed; i.e. v (cm/s) = 1091 x ?cm/s. In (2) the declining cell density with cell size has been taken into
2.48 x rl "emis (Jackson. 1989).
T. [email protected]
C . Celt Size and Nutrient Uptake Kinetics: the Case of Diffusion Limitation
In the following sections nutrient uptake in single cells from fluid dynamical considerations will be considered. The classical work on this subject is that of Munk and Riley (1952), but much has been done since. The entire literature will not be reviewed here but an attempt will be made to give a fairly simple overview of the most recent results of these efforts in the context of cell size effects, the perspective of this section. It is frequently assumed that nutrient uptake rate in phytoplankters depends on the cell surface area and that nutrient uptake, therefore, is most efficient in small cells due to their higher specific surface area (e.g. Smetacek, 1985; Legendre and Le Fkvre, 1989). However, this is true only in the relatively uninteresting case of a high environmental concentration of inorganic nutrients. If the saturated nutrient uptake rate (I/) is proportional to the cell surface area ( A ) :
then the specific uptake rate in spherical cells is inversely related to cell radius:
where V is the cell volume. This is not a serious constraint to large cells because all vital rates (respiration, growth, etc.) depend on cell size in approximately the same manner (see also Section II.G, however). At low nutrient concentrations diffusion rate of molecules towards the cell surface may limit the nutrient supply to the cell. If the potential uptake rate exceeds the diffusion rate, a nutrient-depleted region around the cell will be established (Fig. 6) and the uptake rate becomes diffusion-limited. In this situation the uptake rate is independent of the cell surface area (there is always a sufficient number of uptake “sites”). Consider the extreme situation where the substrate concentration is zero at the cell surface. The substrate concentration (C) will then increase monotonically with increasing distance from the cell surface and eventually reach C’ far away. This can be described by (Berg and Purcell, 1977):
where R is the distance from the centre of the cell. Consider now a
PHYTOPLANKTON CELL SIZE AND PELAGIC FOOD WEBS
Substrate concentration, C
I;oncenrric sneiis withR>r
FIG.6. Estimating diffusion-limited nutrient uptake in phytoplankton cells. After idea of T. Fenchel. See text for further explanation.
number of concentric, imaginary shells around the cell (Fig. 6). The flux per surface area ( J ) through each shell will be (Fick's first law):
The total flux, integrated over the entire surface area, through each of these shells will be the same and equal the uptake rate (U) of the cell: U
4JnR2 = - 4nR2 DdCldR,
where D is the coefficient of diffusion. Differentiating eq. 3 and combining with eq 4 yields (e.g. Fenchel, 1987; Lazier and Mann, 1989):
and the specific uptake rate (UIV) is, therefore:
UIV = 4nrDC' (4/3rrr3)-'
Since potential vital rates are proportional to the inverse of the cell radius and the diffusion-limited nutrient uptake rate is proportional to the inverse of the squared cell radius, small size is a major competitive
advantage at low nutrient concentrations. The above considerations explain why large (immobile) phytoplankters cannot exist in oligotrophic environments, although it does not explain the dominance of large cells in turbulent environments.
D. Effect of Cell Motility and Sinking on Nutrient Uptake If the phytoplankton cell is sinking or is able to move, the microzone of nutrient-depleted water surrounding the cell will be replaced faster than if the cell remains motionless; in effect the steepness of the nutrient gradient and. hence, the nutrient uptake rate will increase due to this advective transport of nutrients towards the cell surface. The contribution of advective transport to nutrient uptake can be described by a slight modification of eq 5 (Logan and Hunt, 1987):
U = 4rrrDShC'.
where Sh, the Sherwood number, is the dimensionless ratio of rate of mass transport by advection and rate of mass transport by diffusion. If the advective transport is zero, Sh = 1, and eq. 7 reduces to eq. 5 , which describes mass transport by diffusion alone. The problem is to determine the Sherwood number. Logan and Alldredge (1989) analysed the experimental data of Canelli and Fuchs (1976) on nutrient uptake in diatoms (Tha/lasiosira weisflogi) fixed in a laminar flow field. They found that the empirical relation:
where Re is the familiar Reynolds number (dimensionless), provided a good description of the experimental data. The Reynolds number is given by:
If we first consider the case of a settling algae we can combine eqs. 8 and 9 with the settling velocities given in Table 1 to yield the Sherwood numbers for differently sized algae given in Table 2. The Sherwood numbers indicate the relative increase in nutrient uptake due to advective mass transport due to sinking. I t is evident that the advective contribution is insignificant for cells smaller than say 10 p m . For larger cells, however, the increase in nutrient uptake is significant or even dramatic. Thus. the
TURBULENCE, PHYTOPLANKTON CELL SIZE AND PELAGIC FOOD WEBS
TABLE2. REYNOLDS(Re) AND SHERWOOD (Sh) NUMBERSCALCULATED FOR SETTLING PHYTOPLANKTERS OF VARIOUS SIZE
1 10 100 1000
2.73 x lo-' 2.73 x 2.73 X 2.73 X 10'
2.30 x lop7 3.40 x lop6 5.03 X 7.45 X lop2
1.002 1.113 6.78 297
1.007 1.034 1.116 11.24
The Sherwood numbers indicate the relative increase in nutrient uptake due to sinking. The settling velocities given in Table 1 have been used. (1) and (2) refer to settling velocities calculated assuming size-independent and size-dependent differential cell densities, respectively (see footnote to Table 1).
diffusion-limited nutrient uptake in large cells may be compensated by increased advective transport to the cells due to a high settling velocity. Of course this has the fatal disadvantage that the cells will sediment rapidly out of the photic zone in a stagnant water column and it is, therefore, probably not of much help to these cells. The pattern emerging from this analysis is, therefore, consistent with the lack of large, immobile cells in stratified waters. The effect of cell motility on nutrient uptake can be analysed along very much the same lines of reasoning. Swimming velocities of small (say 10prn) flagellated forms approximate to 10 body lengths/s. For larger forms (say 100 pm), such as dinoflagellates, relative swimming velocities are lower, c. 1 body lengthis (Levandowsky and Kaneta, 1987). Sommer (1988), analysing data compiled by Throndsen (1973) and Sournia (1982), found the general relation for marine flagellates between swimming velocity ( v , cm/s) and size (equivalent spherical diameter, ESD, pm) to be: v = 9.3 x 10-2ESD".24.In Table 3 Sherwood numbers for swimming algae of different sizes have been calculated from this relation and eqs. 8 and 9. Not unexpectedly, the effect of swimming on nutrient uptake rate is insignificant for small cells. However, nutrient uptake in large cells is significantly enhanced by swimming. This is consistent with the observation that stagnant waters are characterized either by very small cells (e.g. cyanobacteria 11 p n ) biomass as chlorophyli,, (a), surface temperature (b), egg production rates (c. d) in two species of copcpods (Acarria clausi and Ccniropages hurnarus) and copepod biomass (e) at a shallow (28 m ) station in southcrn Kattcgat. Denmark. Note that copepod productivity closely follows net-phytoplankton concentration while copepod biomass follows the temperature. From Kiclrboe and Nielsen (unpublished).
TURBULENCE, PHYTOPLANKTON CELL SIZE AND PELAGIC FOOD WEBS
Eggs I ?Id C Acartia
Eggs/ ? I d
d Centropages 50
2ooot 1 1500 1000
e Copepod biomass
from a coastal station in southern Kattegat, Denmark. There is an immediate functional response in mesozooplankton productivity (here demonstrated by variation in the rates of egg production in two species of copepods) to the distinct spring and autumn blooms of diatoms, and the late summer bloom of dinoflagellates. The productivity of the copepods appears to follow quite closely the concentration of large-sized phytoplankton (>11 pm, Fig. lOa), and there is very little productivity in periods between net-phytoplankton blooms. The biomass of the copepods, on the other hand, appears to vary more or less independently of food availability on the mesoscale (week-month), although on the seasonal scale both phytoplankton and copepods are more abundant during the summer half-year than during winter. Ki0rboe (1991) provided several more examples of how episodic or localized blooms of netphytoplankton, typically generated by increased vertical mixing and enhanced availability of nutrients in the euphotic zone, give rise to locally or temporarily elevated mesozooplankton productivity but not to any obvious numerical response in the biomass (see also Figs 21, 24, 25). Kiorboe (1991) further argued that the majority of the mesozooplankton in (at least) temperate seas is in fact associated with such spatio-temporal oceanographic “events” or discontinuities in vertical water column structure, and that very little production occurs in between. Since the concentration of small phytoplankton cells in the sea is generally much less variable than is the concentration of large cells, we would by the same type of reasoning expect the availability of food to protozoan grazers, like ciliates, to be much more constant in time and space. Consequently, the growth rate of the protozoans should vary less than the growth rate of the mesozooplankton. This point is illustrated in Fig. 11, which shows the seasonal variation in the growth rate of the heterotrophic ciliate Lohmaniella spiralis at the same station and sampling period as considered above. Even though the growth rate of the ciliates varies seasonally, it does not have the same episodic character as the copepod growth rate, and 96% of the variability in ciliate growth rate can be explained by variation in temperature. When corrected for temperature dependency, ciliate growth rate thus appears to be almost constant during the year (Fig. l l d ) . 2. Grazing and turbulence It has recently become evident that turbulence also has more direct implications for the quantity of cells being eaten by predators than those being mediated by cell size. It is intuitively evident that turbulence may increase the contaa rate between planktonic predators and their (phyto-
TURBULENCE, PHYTOPLANKTON CELL SIZE AND PELAGIC FOOD WEBS
a Chlorophyll 150
o.o*[ per h 0.05
d Growth rate corrected to "C
FIG.11. Seasonal cycle of phytoplankton concentration (a) and surface temperature (b) as well as actual growth rate (c) and temperature-corrected growth rate (d) in the c. 50 Km heterotrophic ciliate Lohmuniellu spirulis at a shallow station in southern Kattegat, Denmark (same locality as in Fig. 10). For temperature correction a Q,,, = 2.9 was applied. Note that the temperature-corrected growth rate is approximately constant year round. From Nielsen and [email protected]
plankton) prey, and Rothschild and Osborn (1988) made the first serious attempt to quantify the effects. For a predator moving with velocity v the predator-prey contact rate, Z , is
where R = the predator’s reactive distance and N the concentration of Prey. Gerritsen and Strickler (1977) realized that it is the relative velocities of both predator and prey that determine the predator-prey contact rate, and modified the above expression to take prey swimming velocity into account:
(for v > u ) ,
where u is the velocity of the prey. Note that for u = 0 eq. 14 simplifies to eq. 13. The contribution of Rothschild and Osborn (1988) was to modify further this relation by taking turbulence into account. The effect of turbulence is to increase the relative velocities of both predator and prey and thus to increase the predator-prey contact rate. If w is the turbulent root-mean-square velocity of two particles separated by a distance a , u in the above equation should be replaced by (u’ + w2)’lrand v by (v’ w2)’”. Thus,
r R 2 N ( u 2 3v2 + 4w2)(v2 w2)-1/23-1
(for v > u).
Note that for w = 0, eq. 15 simplifies to eq. 14. For realistic intensities of turbulence, quantified by the turbulent dissipation rate, E , from which w can be readily calculated (see below), they found that turbulence may increase the predator-prey contact rate by 50% or more (see also Yamazaki et al., 1991). In accordance with intuition they showed that the effect is largest for slowly moving predators and prey organisms, and that it increases with the intensity of turbulence. Subsequent modelling exercises by MacKenzie and Leggett (1991) have shown that for fish larvae preying upon copepod nauplii turbulence may increase the predator-prey contact rate by a factor of up to lo! The theoretical - and somewhat provocative - paper of Rothschild and Osborn stimulated research into the effect of turbulence on predatorprey interactions in the plankton. Thus, several recent experimental studies have demonstrated that feeding, growth and egg production may indeed be significantly enhanced in herbivorous copepods by the effect of
PHYTOPLANKTON CELL SIZE AND PELAGIC FOOD WEBS
Gut contents, average no. prey/gut 5 -
........... 2 e - - -1
40 50 Food concentration, nauplii/l
FIG.12. Gut contents of &10d old cod (Gudus morhua) larvae as a function of food density (nauplii of Culanus finmarchicus) in a Norwegian fjord. Data are grouped according to the average wind speed (W,) during the 8 h prior to sampling. I: W, = 2.0mis; 2: W, = 3.7 mis; 3: W, = 6.0 mis. After Sundby and Fossum (1990) by permission of Oxford University Press.
turbulence (Alcaraz et al., 1989; Costello et al., 1990; Marrase et al., 1990; Saiz and Alcaraz, 1991). Field evidence of turbulence-mediated elevated contact and feeding rates has been provided by Sundby and Fossum (1990) who reanalysed field data on gut contents in cod larvae by applying the model of Rothschild and Osborn. They found that the functional relationship between gut contents and food (copepod nauplii) concentration depended on the wind intensity and, hence, the intensity of the wind generated turbulence (Fig. 12), and that the quantitative dependency was consistent with the prediction of the Rothschild and Osborn model. A similar example may be provided by the observation of Kiorboe et al. (1988a,b) that the egg production rate and, therefore, the feeding rate of the planktonic copepod Acartia tonsa increased significantly subsequent to a severe October storm (25-30mis) in the northwestern North Sea, even though the concentration of phytoplankton remained constant (Fig. 13). This observation is in qualitative accordance with the Rothschild and Osborn idea, but it also appears that the observed factor of 8.5 increase in the slope of the functional relationship between egg production and phytoplankton concentration, from 3.0 eggsifemaleid (mg
1 .o 1.5 Chlorophyll, rng/rn3
1 .o 1.5 Chlorophyll, mg/m3
FIG. 13. Egg production rate ( E ) in the copepod Acurtia tonsa in relation to the concentration of chlorophyll, (CHL) before (a) and immediately after (b) a severe October storm in the northwestern North Sea. The regressions are: (a) E = 1.5 3.0 CHL and (b) E = -9.6 + 25.6 CHL. From Ki0rboc ct al. (1988a).
chlorophyll/m') before the storm to 25.6 immediately after the storm (Fig. 13), is largely consistent with the quantitative predictions. For this approximate estimate we assume that the phytoplankton is dominated by 10-20 p m cells occurring in a concentration of 102/ml;these are typical values for the northwestern North Sea in October (Richardson et ul., 1986 and K. Richardson pers. comm.) and consistent with the measured concentration of chlorophyll, about 1 mg/m'. We further assume a predator velocity (v) of 0.05 cm/s and a reaction distance ( R ) of 0.05 cm (Jonsson and Tiselius, 1990; Tiselius and Jonsson, 1990); this yields a clearance or volume swept clear (= n-R2v in the present terminology) equal to 34 mlid, which is reasonable for A . tonsa grazing on 1 0 p m cells (Berggreen et al., 1988). For the situation before the storm, w (and turbulence) as well as prey velocity ( u ) are assumed to be zero, and the predator-prey contact rate can be calculated after eq. 13:
0.052 x 0.05 x lo2 cells/s
For the situation during the storm we need an estimate of w , the uncorrelated root-mean-square turbulent velocity of particles separated by a distance a. Here we follow Rothschild and Osborn (1988) who provide equations to calculate w from a and the turbulent dissipation rate, F (their eqs. 3 and 5). The separation distance can be estimated as
TUKBULENCE, PHYTOPLANKTON CELL SIZE AND PELAGIC FOOD WEBS
N - ” 3 ( N = 102 cells/ml; i.e. a = (102)”3= 0.2cm) and the turbulent dissipation rate can be estimated from the empirical relation to wind speed (W, m/s) of Oakey and Elliot (1982), E = (W/91)’ = (25/ 91)’ = 0.02 watt/m3. From Rothschild and Osborn we then get w = 0.24cm/s and the predator-prey contact rate, Z , is (eq. 15):
Z = n-X 0.0!i2 X 102[(3X 0.052) (4 x 0.242)] x (0.052+ 0.242)p”2x 3-’ = 0.25 cellsis The predicted increase in feeding rate by a factor 0.25l0.039 = 6.4 is, thus, not very different from the factor of 8.5 increase in egg production rate actually observed subsequent to the storm. There is, thus, accumulating theoretical, experimental and field evidence that turbulence does indeed enhance plankton contact and, hence, feeding rates substantially. This, in turn, calls for a re-evaluation of (the applicability of) previous laboratory experiments aimed at determining the functional response in plankton predator feeding rates to prey concentrations, because most laboratory experiments have been conducted under non-turbulent conditions.
B. Excretion of DOM, Phytoplankton Cell Size and Productivity of Pelagic Bacteria A certain fraction of the photosynthetates may be excreted or lost from the phytoplankton cells to the surrounding water in dissolved form. This dissolved organic matter (DOM) cannot, of course, sediment out of the water column or be utilized by heterotrophs by phagocytosis or engulfment. To be degraded by heterotrophs it has to be assimilated directly by cell surfaces. Due to the low concentration of (degradable) DOM in sea water, and because of the strong size dependency of diffusion-limited uptake of dissolved compounds (see Section II.C), small suspended bacteria are the only heterotrophs that can efficiently utilize this source of organic carbon in the water column (Fenchel, 1987). By analogy with the analyses in Section I1 of nutrient uptake in microalgal cells, motility, fluid motion, etc., does not materially alter this conclusion. Conversely, it has been suggested that the major source of DOM for planktonic bacteria is Phytoplankton exudates (e.g. Azam et al., 1983). While it is now generally accepted that dissolved organic compounds leak out of even healthy phytoplankters (e.g. Mague et al., 1980; Larsson and Hagstrom, 1982; Fogg, 1983; Lancelot and Billen, 1985) the magnitude of leakage is still being debated. Empirical estimates range up
to >70% of total photosynthetic carbon fixation (Fogg, 1983; Lancelot, 1983). However, there are major technical difficulties in determining exudation rates from phytoplankters, in particular artefacts from filtering samples and from the presence of small grazers during incubations, and more recent - and presumably more reliable - estimates lie in the lower range of those previously reported; mainly below 10% (Larsson and Hagstrom, 1982; Lancelot and Billen, 1985; Zlotnik and Dubinsky, 1989; Lignell, 1990) of total primary production. The reasons behind, and the mechanisms of, phytoplankton exudation are also currently being debated. It has, for example, been suggested that exudation represents an active release of surplus organic carbon when inorganic nutrients are limiting biomass formation (e.g. Fogg, 1983). However, Bjornsen (1988) argued that this would lead to an apparently paradoxical situation in which the nutrient-limited phytoplankters would stimulate the growth of bacteria that, in turn, would compete (efficiently) with the phytoplankters themselves for the limiting nutrients. B j ~ r n s e n (1988) offered an alternative explanation by suggesting that exudation is simply caused by passive diffusion of low molecular weight organic compounds across the permeable cell membrane. An extension of his analysis also, once again, emphasizes the significance of phytoplankton cell size: The permeability ( P , cmls) of the cell membrane is given by:
where J is the flux of substance (mol/cm2/s) and C (mol/cm3) is the concentration difference across the cell membrane (- internal concentration, since external concentration 0). Since the intracellular pool, S (mol), of a particular compound is
s = cv,
where V (cm3) is the cell volume, and the leakage rate E (molls) is
E = JA,
where A (cm') is the cell surface area, then the fractional leakage rate, EIS (Is), is given by EIS = P A W = ( 4 n - ? P ) / ( 4 d / 3 ) - ' = 3Plr
for a spherical cell with radius r . Thus, the fractional exudation rate is
TURBULENCE, PHYTOPLANKTON CELL SIZE AND PELAGIC FOOD WEBS
inversely proportional to cell radius; i.e. small cells lose a larger fraction of their stored dissolved compounds than large cells. This is illustrated in Table 5. For the usual four size classes of spherical phytoplankters fractional exudation rates have been calculated on the assumptions that (i) P = lO-'ccm/s and (ii) that only low molecular weight compounds, constituting about 10% of the cell carbon, can permeate the cell membrane (Bjcjrnsen, 1988). According to this analysis exudation is insignificant for cells >10 p m and substantial for smaller cells. Thus, DOM release and bacterial processing of photosynthetates is expected to be relatively more important in oligotrophic, stagnant waters characterized by nano- and pico-sized phytoplankton than in new, turbulent habitats dominated by net plankton. Experimentally determined phytoplankton exudation rates are normally expressed relative to total carbon fixation rates (primary production). I have, therefore, in Table 5 also calculated the leakage rate relative to production rate (= E / ( S g ) ) , where g is the maximum intrinsic phytoplankton growth rate. I used the empirical growth rate - size relations provided by Banse (1982b) for the two extremes, namely fast growing diatoms and slow growing dinoflagellates. Here again the size effects are evident. Moreover, the predicted exudation rates relative to production rates, up to 23% in the extreme case, but mainly 3 increase in phytoplankton abundance. Although the surface concentration of heterotrophic ciliates decreased during the storm and subsequently increased to pre-storm levels within a few days, this was ascribed to advection and/or dilution due to vertical mixing because there was no response in ciliate growth rate. Even if “noise” due to advection/dilution is corrected for, the relative significance of microbial processes, as judged from ciliate productivity, diminished significantly during the wind-induced net-phytoplankton bloom. Only the autotrophic ciliate Mesodinium rubrum responded significantly and positively to the wind-mixing event, and “behaved” almost like the net-phytoplankton. Hanson et af. (1986) monitored the production of planktonic bacteria at a locality on the Spanish west coast during the decline of a shortlived wind-induced (upwelling) diatom bloom into the subsequent stratified period; bacterial production was almost constant and only weakly related to phytoplankton biomass, while the ratio of bacterial to phytoplankton production increased by a factor of c. 5 within 3-4 days. Both of the cited examples thus suggest that microbial processes respond only weakly to windinduced vertical mixing, and that their relative importance is therefore less during wind-generated net-phytoplankton blooms.
C. Fronts Fronts can generally be defined as regions of above average horizontal gradients in properties of the water (Le Fevre, 1986); here we shall in particular consider fronts that are characterized by horizontal discontinuities in vertical water column structure, such as tidal fronts, river plume fronts and salinity fronts. Fronts have long been regarded as regions of elevated biological activity although this is not necessarily true of all types of fronts (Le Fevre, 1986). There are several mixing mechanisms, operating on different time scales, that may enrich the photic zone of frontal regions with inorganic nutrients (Loder and Platt, 1985; Le Fkvre and Frontier, 1988) and, thus, give rise to net phytoplankton blooms. Some frontal types, in particular river plume fronts, are characterized by strong surface
FIG.23. The SkagerrakiKattegat salinity front. Distribution of salinity (a), fluorescence (b), primary production (c), assimilation index (d) and concentration of copepod eggs and nauplii ( e ) across the front in April. Both phytoplankton biomass and activity as well as abundance of copepod offspring peak in the transitional zone between mixed and stratified water. Modified from Richardson (1985).
TURBULENCE, PHYTOPLANKTON CELL SIZE AND PELAGIC FOOD WEBS
Depth, m 0 10 -
a Salinity, %.
40 50 -
d Assimilation index
45 nautical miles
convergence, which may lead to accumulation of buoyant material and positive phototropic animals in the frontal region, thus further enhancing the local concentration of particulate organic material and the production of heterotropic organisms. At other fronts surface convection can be ruled out (as at the tidal front illustrated in Fig. 24, which is mainly a bottom phenomenon) and phytoplankton blooms occurring here must be caused solely by locally elevated primary production based on enhanced availability of new nutrients. For a further discussion of fronts as “accumulation” versus “high production” biotopes see Le Fevre (1986). Figs 23-26 give several examples of how various components of pelagic food webs vary across horizontal transitions (fronts) in water column structure. Richardson (1985) studied the variation in phytoplankton biomass and production and abundance of copepod eggs and nauplii across the salinity front generated by outflowing brackish water from the Baltic and Kattegat into the Skagerrak in April (Fig. 23). At this time of the year the Skagerrak is still not temperature-stratified and the surface outflow of brackish water generates a distinct discontinuity in water column structure. Phytoplankton concentration and primary production both showed pronounced peaks at the immediate stratified side of the front. The coinciding peak in assimilation index (i.e. mg of carbon fixedlmg chlorophyll a/h) suggests that the elevated concentration of chlorophyll at the front is, at least partly, due to locally enhanced growth of the phytoplankton. The concentration of copepod eggs and nauplii, indicative of recent copepod secondary production, also peaked at the immediate stratified side of the front. Similar types of data from a tidal front in October in the northwestern North Sea off the Scottish east coast are presented in Fig. 24 (Kicbrboe el a f . , 1988b). Here again phytoplankton biomass peaks in the transitional region between mixed and stratified water and this pattern closely resembles the horizontal variation in egg production in the copepod Acartia tunsa; egg production is very low in both mixed and strongly stratified water and peaks at the front. Total copepod production shows a similar spatial pattern across the front (Kiorboe and Johansen, 1986). AS in the example above and consistent with the spatial variation in copepod productivity, the concentration of copepod eggs and nauplii is significantly elevated in the frontal region (Kiorboe and Johansen, 1986). In spite of the pronounced pattern in copepod productivity the distribution of total
24. Distribution of copepod productivity and copepod biomass across a tidal front in the northwestern North Sea in October. Distribution of temperature (a), chlorophyll, (b), egg production rate in the copepod Acartia tonsa (c) and biomass of copepods (d) across the front. Modified from Kiorboe et a / . (1988b). FIG.
TUKBULENCE, PHYTOPLANKTON CELL SIZE A N D PELAGIC FOOD WEBS
Eggs/? i d 16
rng C i m 3
90 nautical miles
copepod biomass is largely independent of water column structure at the scale considered. However, in this region mesozooplankton biomass peak further offshore in the stratified region (Kiorboe and Johansen, 1986). With a few exceptions (e.g. Floodgate et al., 1981; Le Fkvre and Frontier, 1988) researchers have generally been unable to relate distributions of copepods to fronts. This lack of distributional coincidence between mesozooplankton and fronts at many frontal types led Le Fkvre and Frontier (1988) to suggest that the structure of the pelagic food web at fronts is determined mainly by the time scale of the physical processes that enrich the photic zone with inorganic nutrients. They considered two examples, a tidal front, where the fertilizing mixing process occurs in a 14 d cycle (neap-spring tide), and a shelf-break front, where the fertilization process is of high frequency (12 h periodicity). Based on distributions of zooplankton biomasses they concluded that in the latter case enhanced productivity was in the form of a classical herbivore food chain, while in the former case primary production was consumed by microorganisms, because herbivorous copepods cannot adapt to short-lived, fortnightly phytoplankton blooms. However, even though advection may prevent accumulation of mesozooplankton biomass with long generation times at dynamic fronts, both copepod growth and production may well be elevated, and the only signal left behind is higher than average abundances of eggs and nauplii that do not contribute significantly to overall biomass. As in the example above it seems to be typical that copepod biomass peaks in stratified water well away from the discontinuity (e.g. Holligan et al., 1984; Kahru et al., 1984; Moal et al., 1985). This situation thus resembles the seasonal cycle in temperate waters, where zooplankton productivity is highest concurrently with the net-phytoplankton bloom occurring at the stratification-destratification interface, while the biomass lags behind and peaks well into the subsequent stratified period. The Skagerrak between Norway and Denmark is characterized by a dome shaped pycnocline (Pingree et al., 1982; see also Fig. 25); thus, vertical water column structure varies horizontally, with mixing regions occurring along the periphery of the area, distinguished from a strongly stratified central region. This makes this region ideal for investigating relations between water column structure and pelagic processes. Fig. 25 presents results from a transect study in the Skagerrak (Kiorboe et d., FIG.25. Horizontal variation in vertical water column structure across the Skagerrak and associated variation in properties of the pelagic community in May. (a) Water density as sigma-t units; (b) volume ratio of large (>Xpm) to small ( t 8 p m ) phytoplankters; ( c ) chlorophyll as fluorescence; (d) bacteria generation time; and (e) fecundities of the copepods Acurtitr cluusi and Ternoru longicornis. Modified from Kiorboe et a / . (1990a).
TURBULENCE. PIIYTOPLANKTON CELL SIZE A N D PELAGIC FOOD WEBS
Depth, 0 m 10
DENMARK 1 2 3 4 5
12 Station No. - 11
24 24 25 26
40 0 10
40 0 05
30 40 0 10 20
generation time, d
50 Fecundity P Temora
30 20 10
0 1 2
3 4 5
1 Sediment 1
FIG.26. Comparison of primary production and pelagic food web structure in (a) rich frontal and (b) oligotrophic, stratified regions of the BeringChukchi Sea. In (a) the phytoplankton is entirely dominated by diatoms and in (b) by pico- and nanophytoplankton. Figures represent carbon flow rates as percentage of primary production rate. Modified from Andersen (1988).
TUIZBCJLENCE. PLiYTOPLANKTON CELL SIZE A N D PELAGIC FOOD WEBS
1990a) (see Fig. 4 for a map of the area and position of transect line). As expected, net-plankton blooms occur in the frontal regions at both ends of the transect, and copepod productivity peaks concurrently whereas bacterial growth rate is maximum in the central, stratified region characterized by nano- and pico-sized phytoplankton. Although the spatial pattern in pelagic processes is quite variable in this hydrographically complex region, basic patterns have been found again on subsequent sampling occasions (see Peterson ef al., 1991; Kahru and Leeben, 1991). Thus, it appears that a microbial type of food web characterizes the central, stratified part of the area and a more classical type of herbivorous food chain dominates in the frontal/mixing regions along the periphery. Pelagic food web structure in the Skagerrak thus depends on vertical water column structure in a predictable manner. Yet another example of pelagic food webs at fronts vs. stratified regions from the Bering Sea, perfectly consistent with the above, is illustrated in Fig. 26. The enhancement of net-phytoplankton and mesozooplankton producDepth, m
400 300 200 100
FK;. 27. Distribution of herring larvae across a tidal front in the northwestern North Sea in October (after Kiorboe er al.. 19XXb).
FIG.28. Distribution o f sprat larval growth rate across a coastal front in the southeastern North Sea in August. Values of surface to bottom temperature diffcrenccs (delta t, "C) are contoured by full lines in (a) and larval growth rates (mmid) as inferred from otolith microstructures in (b). Note that growth rates are highest in mixed and frontal waters and decline in strongly stratified rcgions. Unpublished data of P. Munk.
tion at some types of fronts, as illustrated in the several examples above, may have implications at higher trophic levels (e.g. fish) as well. Larger scale fronts, such as shelf break fronts. are frequently associated with fisheries (e.g. Fournier, 1978). For smaller scaled fronts, such as river plume and tidal fronts, locally enhanced feeding and growth conditions at higher trophic levels are most easy to document for plankton predators such as fish larvae. Thus, several studies have demonstrated that the distribution of fish larvae is often related to such fronts (e.g. Townsend et al., 1986; Heath and MacLachlan, 1987; Kiorboe et ul., 1988b; Govoni et al., 1989; see also Fig. 27) and that feeding and growth of fish larvae are indeed enhanced here (Govoni et al., 1985; see also Fig. 28). Such observations are also consistent with the expectation of a classical grazing food chain at oceanographic discontinuities.
TURBULENCE, PIIYTOPLANKTON CELL SIZE A N D PELAGIC F O O D WEBS
New/total production (f-ratio)
Mesozooplankton production and sedimentation
Time or space
29. Simple conceptual model of variation in pcAagic processes along spatio-temporal ting-stratification gradients. 'IG.
V. Summary and Conclusions This contribution has focused on the significance of hydrodynamic processes on various scales to patterns in pelagic food web structure. The basic relations between water column characteristics and pelagic food web structure, as schematically summarized in Fig. 29, appear to recur on a wide variety of spatio-temporal scales; from oceanwide and seasonal scales to the temporal scales characteristic of episodic wind-mixing events (days) or the horizontal scales of oceanic fronts (km), for example. It has here been suggested that the causalities behind the relation between water column characteristics and pelagic food web structure are mediated primarily by the effects of turbulence and phytoplankton cell size. The occurrence of significant concentrations of net-phytoplankton is restricted to turbulent, episodic environments occurring at spatio-tempora1 discontinuities in vertical water column structure. This is partly because turbulence both generally increases the availability of new, inorganic nutrients in the photic zone and enhances nutrient uptake in large cells, thus relaxing the competitive pressure for small size in turbulent environments. It is also partly due to the considerable timelag in the numerical response of the mesozooplankton predators of the netphytoplankton. Blooms of net-phytoplankton give rise to short, grazerbased herbivorous food chains and/or to elevated sedimentation of organic material to the sea-floor. Both grazing and sedimentation may be significantly enhanced by the effects of turbulence due to increased plankton contact rates. Nano- and pico-sized phytoplankton occur ubiquitously in the oceans while microbial processes appear less influenced by macro- and mesoscale physical processes and are more controlled by predator-prey interactions; microbial production is thus less variable in time and space. The relative contribution of microorganisms to the overall mineralization of the primary production is consequently most significant in oligotrophic, stagnant waters, where net-plankton is scarce. Because microbial food webs are typically long and primarily based upon regenerated phytoplankton production microbial production contributes insignificantly to fish production in the oceans. In contrast, classical herbivorous food chains are short and based on new nutrients and, thus, give rise to net accumulation of catchable biomass, also at higher trophic levels. Cushing (1989) and Legendre (1990) both emphasized the significance of net-phytoplankton blooms to the fisheries production in the ocean, having in mind first of all blooms associated with larger-scale physical processes, such as the major upwelling regions and the vernal temperature stratification in temperate waters. From the several examples
TUKBULENCE, PHYTOPLANKTON CELL SIZE AND PELAGIC FOOD WEBS
in Section IV it can be seen that t h e same processes recur on much smaller spatio-temporal scales. It thus becomes the spatio-temporal “frequency” of (large- or small-scaled) oceanographic discontinuities or mixing events, rather than total primary production, that eventually determines the magnitude of fish production in a particular region.
VI. Acknowledgements Thanks are d u e t o colleagues for permission t o utilize unpublished material a n d t o Professor J. H. S. Blaxter for inviting me t o write this paper.
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TCJKBULEN( E, P l f Y T O P L A N K T O N C E L L SIZE A N D PELAGIC I-000 WEUS
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Autotrophic and Heterotrophic Picoplankton in the Baltic Sea J. Kuparinen and H. Kuosa Finnish Institute of Marine Research, PO Box 33, SF-00931 Helsinki, Finland
Preface .. .. .. .. .. .. .. .. I. Introduction ., .. .. .. .. .. .. A. The Baltic Sea .. .. .. .. .. .. B. Picoplanktonic algae .. .. .. .. .. 11. Methods .. .. .. .. .. .. .. A. Autotrophic picoplankton . . .. .. .. .. B. Bacterioplankton .. .. .. .. .. .. 111. Phytoplankton Succession in the Baltic Sea .. .. .. IV. Autotrophic Picoplankton in the Baltic Sea . . .. .. A . Areal and vertical distribution .. .. .. .. B. Seasonal variation . . .. .. .. .. .. Bacterioplankton in the Baltic Sea .. .. .. .. A. Annual and seasonal variation of bacterioplankton production B. Distribution of bacterioplankton .. .. .. .. V l Factors Controlling Autotrophic Picoplankton .. .. A. Nutrients and temperature . . , . .. .. .. B. Grazing .. .. .. .. .. .. .. VII. Factors Controlling Bacterioplankton . . . . .. .. .. A. Nutrient- and carbon-limited bacterioplankton growth B. Predation control of bacterioplankton .. .. .. V11I. Bacteria in the Pelagic Food Web .. .. .. .. IX. Acknowledgements .. .. .. .. .. .. X. References .. .. .. .. .. .. ..
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73 75 75 77 81 81
87 87 87 90 92 92 97 101 101 104 105 105 111 115 119 119
Preface The introduction of the concept of a size-structured plankton food web (Williams, 1981; Azam et al., 1983) greatly stimulated studies of aquatic Copyrighr 01993 Acudemic Press Limrted All rightc of reproduction in any form reserved
ADVANCES IN MARINE BIOLOGY VOLUME 29 ISBN 0-12-026129-4
J . KUPARINEN A N D H . KUOSA
microbial ecology in the 1980s, and there was an outburst of publications on the oceans, brackish waters and lakes. In addition, the developing techniques of epifluorescence microscopy and the use of radioactive tracers have provided many new data. This review summarizes results obtained from various locations in the Baltic Sea, which has been described as one of the most intensively
6 4 '
5 4 ' 1'0
3 0 '
FIG. 1 . Map of the Baltic Sea. Study sites from which the majority of the data presented in this paper originate are marked on the map: Station 1 = 63"31'N, 19"48'E; 2 = 63"19'N, ZO"17'E; 3 = 59".50'N, 23"lO'E; 4 = S9"3S'N, 23"18'E; 5 = .59"26'N, 21"30'E; 6 = 59"02'N, 21"OS'E; 7 = S8"4S'N, 17"3S'E; 8 = S7"19'N, 20W2'E; 9 = SYlS'N, lS"S9'E; 10 = 55"00'N, IJOOS'E; I I = 54"36'N, lO"27'E.
BALTIC SEA PICOPLANKTON
studied aquatic environments (Jansson, 1980). While Baltic Sea hydrography and plankton in general are well known, the category of “most intensively studied” does not yet apply to Baltic Sea picoplankton, on which few publications are yet available. To make good this deficiency we include in this review a substantial amount of new data.
1. Introduction A.
The Baltic Sea
The Baltic Sea is a large brackish water basin with limited connection to the North Sea from the southwestern end (Fig. 1). It comprises several more or less distinct basins or subareas (Fig. 1) with pronounced density stratification prevailing throughout the year (Kullenberg, 1981; Malkki and Tamsalu, 1985). The differences in density between the surface and more saline deep waters restrict exchange between the two layers. The salinity of the surface water decreases from more than 2 0 % ~in the opening to the North Sea to below 1%0in the extreme ends of the Bothnian Bay and the Gulf of Finland. In the Baltic Proper, surface water salinities are between 6 and 8700. The primary halocline is at a depth of 60 to 7 0 m in the Baltic Proper
Flc;. 2. Typical distributions of temperature (T), salinity (S) and density (D) in the Bothnian Sea (a), Gotland Deep (b) and the southern Baltic Proper (c).
J . KUPARINEN AND H . KUOSA
and 40 to 50 m in the Bornhom Basin (Fig. 2) (Kullenberg, 1981; Malkki and Tamsalu, 1985), below which salinities between 10 and 13%0are common. This layer receives new water irregularly from inflows through the Danish sounds (Grasshoff and Voipio, 1981). A weak secondary halocline, which separates the frequently anoxic bottom water from the overlying layers, can be detected at a depth of c . 110 and 150m. The extent of this area with insufficient oxygen for macofauna has fluctuated, but is approximately 70,000 km2, mainly in the deep parts of the central Baltic Sea (Andersin and Sandler, 1988). The bottom waters of the Baltic Sea are renewed only after exceptionally strong inflows of North Sea water from the Kattegat. Such inflows occurred in 1913, 1921, 1951 and 1976. Due to the lack of major inflows during the past 14 years, the salinity and density of the deep water have decreased continuously. In most parts of the Baltic Sea a thermocline develops at depths between 15 and 2 0 m in summer (Fig. 2). The layer of cold water from the previous winter can thus be found between the thermocline and the halocline. These two water masses of about the same salinity mix during the autumn turnover. The western Baltic Sea differs from most of the Baltic Sea in its stratification; due to the water exchange from the North Sea, it is salinity rather than temperature dependent (Fig. 2), and this has implications for the picoplankton in the area (Jochem, 1989). Another key factor influencing the Baltic Sea picoplankton is the fact that the Baltic is a northern sea, with Arctic characteristics, especially in its northern parts. The winter conditions emphasize differences between the subareas and their biology. The mean number of ice days varies from 190 in the northern end of the Bothnian Bay (Lepparanta et al., 1988) and more than 140 in the easternmost part of the Gulf of Finland to less than 10 days in the central Baltic Proper and in the Kattegat. The mean maximum annual ice thickness varies from more than 70 cm in the northern Bothnian Bay to less than 10cm in the southern Baltic Proper (Climatological Ice Atlas, 1982). These winter conditions contribute to the large seasonal temperature differences, from -0.3 to about 20°C. The numerous large rivers that bring fresh water and inorganic and organic compounds into the Gulf of Bothnia and to the Gulf of Finland impart special features to the biota of these areas. In particular the Bothnian Sea receives large quantities of allochthonous organics via the rivers (Fonselius, 1986). Due to the terrestrial origin, allochthonous material is highly refractory. Levels from 3.0 to 4.7g/m3 of dissolved organic carbon (DOC) have been reported from the Baltic Proper (Ehrhardt, 1969). Only a small fraction of this pool is liable for bacterial utilization (Bolter, 1981).
BALTIC SEA PICOPLANKTON
1. Definition Pic0 is an epithet applied to pelagic organisms with a size less than 2 p m (Sieburth et al., 1978). The lower limit of pico-sized organisms, either bacteria, algae or protozoa, is 0.2pm. According to the thorough discussion by Raven (1986), the non-scalable properties of algae constrain their theoretical minimum size to just above 0.2 pm. It seems that in the pelagic environment only viruses and a small fraction of bacteria appear in the femtoplanktonic (0.02 to 0.2 p m ) size fraction. Thus according to the scheme of Sieburth et al. (1978) picoplanktonic organisms are those with cell size under 2 p m . However, this scheme is not totally straightforward when we consider algae. If algae were more or less spherical and if the cells of one species consistently showed very limited variability in size there would be few problems. However, as we know that the form of algae varies considerably, and that the size range of a given species is usually large, the precise definition of picoplanktonic algae in natural phytoplankton communities is difficult. The distinction of picoplanktonic algae as a separate group has clear ecological grounds. One of the most powerful is that it corresponds to a size fraction of pelagic organisms which is probably not effectively grazed by metazooplankton (rotifers, cladocerans and copepods) and, correspondingly, is effectively grazed by protozooplankton (see Section VI). The fraction of organic material produced by picoplankton is thus possibly an indication of the structure of the carbon transfer from primary producers to the higher predators (microbial loop vs. grazing food chain) as discussed by Azam et al. (1983); Ducklow et a f . (1986) and Sherr and Sherr (1988). If we confine ourselves to this ecologically based interest in picoplanktonic algae, the actual upper cell size becomes more a matter of choice than a strict definition. Eventually, it may be possible to choose the upper size limit according to the grazing structure in a given water body, and according to our knowledge of the particle capture ability of zooplankton species. Small algal cells also have other characteristics in common, such as Slow sedimentation rate and high nutrient uptake capacity. These characteristics are probably not as strictly correlated with cell size as grazing, but their existence further validates the separation of picoplanktonic algae as a single group. One reason for defining the fraction of the phytoplankton community to be examined in this review of the Baltic Sea is purely practical. Almost
J . KUPARINEN A N D H . KUOSA
all the material from the Baltic Sea used for size-fractionated chlorophyll or production measurements has been gathered using 3 p m polycarbonate filters. The reason for this is not really important in the present context it may be the availability of filters or pure coincidence. At the moment we lack a definitive knowledge of the grazing properties of Baltic Sea zooplankton. Because of the nature of the existing material, and the fact that all size-limits in a phytoplankton community are only loosely defined due to the variable shapes of algal species, rather variable material is included in this review. 2. Organisms (a) Eukaryotic nlgae A number of eukaryotic algae belonging to variable algal classes are of picoplanktonic size or very near its upper end. As discussed above, there is no reason to regard 2 p m diameter as a strict limit when discussing picoplanktonic algae. Thus according to Thomsen’s (1986) excellent overview the scope of this introduction is also somewhat wider than would be required by pure picoplankton. The actual upper size limit for the species depicted in the following discussion is about 5 p m (“ultraplankton”). Because of their very small size many of these algae have certainly been overlooked in routine work (see Section 11). Their positive identification is possible only by electron microscopy and the routinely used Utermohl method gives few possibilities to count these very small cells in plankton samples. From t h e variety of algal classes and genera surveyed by Thomsen (1986). some with relevance to the Baltic Sea can be depicted. Very small Cryptophyceae have been found in the Baltic Sea. Thomsen (1986) presented a photograph of a very small Hemiselmis sp. (aff. anomala) from the Gulf of Bothnia. Hemiselmis virescens Droop is a very small cryptophycean algae (cell size 4 - 6 p m long and about 3 p m wide), which has been recorded in the Western Baltic Sea (Hill, 1992). Of the large class Chrysophyceae, Pedinella tricostata Rouchijajnen (4-6 pm) has been identified from Baltic Sea material (Edler et al., 1984). It is certain that many other small chrysophytes are also present in the Baltic Sea. Similarly, a number of very small solitary flagellated species of Chlorophyceae are probably to be found in the low salinity waters of coastal areas. Some very small centric diatoms (Bacillariophyceae) are found in Baltic Sea samples. The taxonomical work, using electron microscopy, has still to be done. From the genus Thalassiosira at least one very small species, T. pseudonunu. is present in the algal flora of the Baltic Sea (Edler et al.,
BALTIC' SEA PICOPLANKTON
1984). A very small, solitary Chaetoceros species was also found in many samples, but was probably overlooked like many other small diatoms (Kuosa, unpublished). However, even small Chaetoceros cells are a borderline case in picoiultraplankton. Although the cell size of Chaetoceros may be within the picoplanktonic size range, the seta will enlarge the effective size of the cells in grazing and in fractionation procedures. The algal class Eustigmatophyceae shows specific ultrastructure and pigment composition. An algal culture maintained at the Tvarminne Zoological Station has been assigned to the genus Nannochloropsis. This small species (2-3pm) may be common in the waters of the northern Baltic Proper, but as is the case in all other small species. we have very little knowledge of its areal distribution and abundance. Micromotzas pusilla (Loxophyceae) is a species within the same size range as Nunnochloropsis sp., but although it is flagellated, it is impossible to differentiate from Ncnnochloropsis sp. in normally preserved phytoplankton samples. Micromonas pusilla has been identified by electron microscopy in samples taken near Tvarminne (Thomsen, 1979). Micrornonas pusilla (1-3 x 1 p m ) has a wide distribution in the oceans (Throndsen, 1976), and it may commonly exceed cell numbers of 10h/l (Thomsen, 1986). Another very small species (1.5-2.5 pm) of the class Loxophyceae reported from the Baltic Sea is Pedinomonas micron (Thomsen, 1986). Of the related class Prasinophyceae some small species have appeared in samples studied by electron microscopy (Hallfors and Niemi, 1986). These are: Mantoniella squamata (3-4 pm), Nephroselmis minuta (
10 Fishing mortality
FIG. 31. Yicld per recruit (girecruit age 0) for Bristol Channel females exploited at a range of mortality rates ( F = G2iyear) for mesh sizes of 70, 90. 100 and 120 mm.
returns become negligible. The values of yield and F,,, are given in Table 9. The yield per recruit plots for males are given in Fig. 32. The maximum yields are about half of those obtained from the female sole because of the slower growth rate and the smaller maximum size attained. As for the females it is shown that the stock is under-exploited for F 50
1.o Fishing mortality
FIG.32. Yield per recruit (girecruit age 0) for Bristol Channel males exploited at a range of mortality rates ( F = C2iyear) for mesh sizes of 70, 90, 100 and 120 mm.
relationship. This is unlikely to be the whole truth, and selectivity may change on older ages, and larger sizes, due to different behaviours of the fish in relation to the fishing fleet, or due to the characteristics of the fishing gear. In these cases the advantages of the sized-based approach may be outweighed by changes with age that are readily addressed, or approximated, through t h e age-based model. The differences between the
THE BRISTOL CIIANNEL SOLE ( S O L E A S O L E A (L.))
FIG.33. Yield per recruit (girecruit age 0) for Bristol Channel males and females combined. exploited at a range of mortality rates ( F = &2/year) for mesh sizes of 70, 90, I 0 0 and 120 mm.
two models can be termed second order effects - both models will give about the same answers and small improvements are being considered. However, both the above models exclude an important effect - that of the large variation in size of fish at a given age. This is considered below.
3. Variability of size at age The length of sole at any age varies considerably. For the Bristol Channel sole Fig. 14 gives +1 standard error of the mean length at age, and 95% of the fish, at age, will span a spread of lengths ten times that illustrated. Within the population, the slower-growing fish will be caught later than the larger and faster growers. The size-dependent model, developed above, allows this to be readily incorporated. On the assumption that growth of an individual fish, within the population, follows a modified von Bertalanffy equation, although the generality of the approach does not require any specific form, growth of an individual is given by,
and if q is the size of an individual at
where the symbols are those described above (p. 303). It can be recognized that growth of the individual follows with time that of the average, used above, with r ) = 0, and is of magnitude r) greater at all times. This is unrealistic at small sizes, but it is only necessary for the growth model to be valid from the time of earliest (or smallest) exploitation. Consequently the set r) represents the spread of lengths about the mean in the fishable population. This can be different from the Fize distribution in the total population, but the segregation of sole described in Section I1 (p. 242) means that such parameters can be estimated. Repeating the algebra of the previous section to give numbers and density at length s for the individual sized 77, the following relationships are obtained for the numbers alive at size s to s + as, (m(slr))), from an initial number at time 0, (n(O1r))),conditional upon r): for, s d S5" - E ,
for, SS0- E < s d SS0+ E ,
and for, s > S,,,
n(O/r)).exp(-M.to).exp - i ( S s ( , - ~ - s )
Equation 6.5 gives the density of numbers conditional upon the numbers at time zero. If we let n(01r))be the conditional probability distribution of the numbers at time zero that will follow t h e growth curve determined by r ) , then we can obtain an expression for the yield per recruit which has two related explanations. Firstly it is the deterministic realization of the
THE BRISTOL CHANNEL SOLE (SOLEA SOLEA (L.))
yield per recruit of the population standardized to a unit at time zero; secondly it is the expected yield per recruit from a population whose numbers are distributed at time zero by the form n(O(q).The yield per recruit is given by integration over all q, YPR
n (0 17).m(s IT)). a . s3 ds dq. s=
Solutions of equation 6.6 can be found numerically and no examples are provided. These new and the traditional analyses both assume that fish which pass through the net and fish which are discarded from the catch survive. This is largely because good information on survival and discard rates are rare. However, van Beek et al. (1990) estimated that 40% of large sole escaping through meshes die; if this rate is typical the additional mortality should not be neglected.
B. Absolute Yields 1. Using standard adult natural mortality rate The above analyses present results in terms of a unit recruit. To scale the results to absolute yields, and biomasses, one multiplies by the average recruitment to the stock. The average recruitment of sole at age 2 years, of males plus females, of the year classes 1969-85 was 4.50 million (Anon., 1992). The above values are given relative to a theoretical unit recruitment at age zero, and accounting for the natural mortality rate used in the models (O.l/y) the average recruitment at age 0 is 5.50 million. The yields and stock biomasses of 100g/recruit of Figs 29 and 31-34 thus correspond to an absolute weight of 550 t. The maximum from Fig. 28 is equivalent to a total yield of 1270 t and that from Fig. 33 of 1170t. Results calculated by ICES are similar. Conditional upon the validity of the estimates of growth and natural mortality rates, it can be said with confidence that long-term yields from the Bristol Channel population will not exceed 1200-1300 t. Some short-term effects such as an above average recruitment or eating into the capital of the stock will give temporarily greater yields, but any attempts to take greater yields will quickly lead to lesser catches. 2. Sensitivity to natural mortality rate Estimates of the natural mortality rate for sole stocks are imprecise and no independent estimate is available for the stock of Bristol Channel sole
J . HORWOOD
(Section V.C). The sensitivity of the yield per recruit analyses to different values of the natural mortality rate was considered by the ICES methods working group (Anon., 1986b). As the natural mortality rate increased it becomes necessary to fish harder in order to compensate for the natural loss of fish and the maximum of the yield per recruit curve is found at an increased level of fishing mortality. It can be anticipated that the yield per recruit will decrease as fish are lost naturally. So we have F,, at a higher rate and the maximum yield smaller. However, with an increased natural mortality rate and similar catch data the estimated numbers of recruits increase and compensate for the smaller yield per recruit. Unfortunately there is not a consistent relationship between revised estimates of current fishing rates and the revised values of F,,. For the Bristol Channel sole the above exercise was repeated for a mortality rate of O.2/year. The values of F,,, and the maximum yield per recruit are given in Table 10 and they can be compared with the estimates for the sexes combined in Table 9. As can be seen, the values of F,,,, are typically doubled and the yields per recruit halved. Yields per recruit at levels of F = 0.3, 0.5 and 1.0 are also given; they show that loss of yield by fishing at rates of 0.3-0.S/year, rather than Fm;ix,are small. The ICES assessment (Anon., 1991b) was repeated with the increased value of natural mortality rate and this gave an average recruitment (at age 0) of 10.78 million. The conversion to absolute yields is given in Table 10. (Results from the 1991 assessment (Anon., 1992) were similar and negligibly affect this result.) The maximum yields are [email protected]
t, similar to those based upon a natural mortality rate of O.l/year. The results indicate that the estimates of the long-term maximum yield are insensitive to the value used for the natural mortality rate.
TABLE10. VALUESOF F,,,,, MAXIMUMYIELDPER RECRUITAGE 0 (8) AND ABSOLJJTE YIELD( t ) FOR THE SIZE-BASED YIELDPER REC-RLJIT A N A L Y S I S , OF BOTHSEXESCOMBINED, WITH THE INSTANTANEOUS RATE OF NATURAL MORTALITY E Q U A L TO 0.2 /YEAR;RESULTS CAN BE COMPARED WITH THOSE OF Table 9. YIELD PER RECRUITV A L U E S A R E ALSO GIVENFOR FISHING MORTALITY RATESOF 0.3, 0.5 A N D I . O / Y E A K
Mesh size (mm)
70 90 100 120
0.42 0.88 >2.00 >2.00
1185 99 1
YPR F = 0.3
YPR F = 0.5
YPR F = 1.0
95 97 90 60
97 10s 101 72
89 108 109 84
T H E BRISTOL CfiANNEL SOLE ( S O I , E A S O L E A (L.))
TARLE 11. INTERNATIONAL CATCHES (t) OF SOLE FROMTHE BRISTOL CHANNEL AND ADJACENT WATERS,EQUIVALENT TO ICES DIVISIONS VIIf-g. FORDETAILS SEE Section V 1 I . D ~~
England and Wales
Min MaxiBest Min MaxIBest Max/Best Min MaxIBest Min Max Best 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 2 5
5 20 29 36 59 104 123 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 35 114 147 161 191 184 187 188 201 204 393 383 0 0 0 0
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 11 10 25 25 78 43 55 33 63 43 82 91 52 3 1 0 0
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 11 10 25 25 78 43 55 33 63 43 82 91 52 3 1 0 0
348 288 521 523 594 568 697 573 535 0 0 0 0 242 298 404 668 971 517 499 376 363 352 463 641 797 611 480 371 570 243 344 316
613 572 496 429 477 645 641 692 629 759 646 628 813 558 476 473 335 488 576 885 1088 646 641 536 554 558 671 849 969 775 646 532 726 411 510 480 602 239 138 115 189
615 574 498 350 290 523 525 596 570 699 575 537 2 2 2 2 244 300 406 670 973 519 501 378 375 364 490 669 877 656 537 406 635 288 427 408 656 244 141 117 191
615 615 576 575 503 501 436 393 500 395 676 600 678 602 753 674 735 653 884 792 648 612 630 583 815 409 560 281 478 240 475 239 337 291 490 395 578 492 887 778 1090 1032 648 583 643 572 538 458 567 471 605 484 811 651 1023 846 1209 1043 1011 833 887 712 754 580 978 807 657 472 798 613 965 687 1039 847 244 244 141 141 117 117 191 191
J . HORWOOD
TABLE11 - contd. Belgium
England and Wales
Year Min MaxlBest Min MaxlBest MaxIBest Min MaxIBest Min Max Best
1944 0 1945 0 1946 0 1947 0 1948 11 1949 76 1950 59 1951 70 1952 30 1953 36 1954 18 1955 60 1956 171 1957 385 1958 225 1959 158 1960 281 1961 283 1962 300 1963 162 1964 436 1965 461 1966 230 1967 418 1968 271 1969 267 1970 525 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986
0 0 48 115 137 220 103 91 67 59 31 185 422 839 622 399 281 480 444 311 746 796 353 586 401 442 961
0 0 0 4 50 0 0 5 13 9 43 91 356 100 430 302 219 224 193 257 342 836 303 334 179 194 118
0 0 0 4 50 0 0 5 13 9 43 91 356 100 430 302 219 224 193 257 342 836 303 334 653 827 537
2 2 2 -
1 1 2 1 1 2 2 2 3 2 2 2 3 4 3 -
160 288 484 766 613 425 386 399 445 637 622 533 395 282 300 285 247 148 98 67 148 227 155 185 162
22 1 200 274 445 651 766 613 425 386 399 445 637 622 533 395 282 300 285 247 148 129 80 148 227 155 185 162
223 202 162 293 547 844 674 502 431 445 507 789 1150 1020 1051 743 802 794 742 570 878 1366 684 982 609 649 808
223 202 324 566 840 988 718 523 468 468 520 914 1401 1474 1448 984 802 991 886 719 1218 1715 807 1150 1213 1457 1663
223 202 285 488 755 916 696 512 450 457 513 851 1276 1247 1250 863 802 892 814 644 1063 1548 745 1066 987 1154 1302 1861 1278 1391 1105 919 1349 96 1 780 954 1314 1211 1128 1373 1266 1328 1549
’THE BKISTOL C11ANNEL S O L E ( S O L E A S O L E A ( L . ) )
Min MaxIBest Min MaxIBest MaxIBest Min MaxIBest Min Max Best ~
1988 1989 1990
1146 992 1189
C. Spawning Stock Biomass per Recruit Fig. 30 illustrates the decline in numbers surviving with size as fishing mortality increases. The average biomass of the mature fish (often termed the spawning stock biomass, SSB) during the year can be calculated as,
where pm(t) is the proportion mature at age t , rz is the number, s is the length and a is the condition factor. This equation was applied for the female sole of the Bristol Channel, using the growth parameters as above. A convenient approximation is to assume a knife-edge fishing selection at an age commensurate with mesh sizes of 70 mm (2.42 years) and 100 mm (4.37 years), and Section 1V.C indicates that 4.5 years can be taken as a knife-edge age at maturity. Fig. 34 gives the spawning stock biomass per female recruit at age 0, against fishing mortality, for the two ages at first capture. Fig. 34 shows a rapid decline in mature female biomass as fishing mortality increases from zero to modest levels of mortality of 0.2-0.31 year, after which the rate of reduction lessens. For a 70-mm mesh net the biomass is reduced to 36% at F = O.l/year, 18% at F = 0.2/year and less than 5% at F = O.S/year. For a 100-mm mesh net the biomasses are higher at each fishing mortality, but are still reduced to 44% at F = O.l/year, 26% at F = 0.2lyear and 10% at F = 0.51year. The biomasses per recruit can be converted to stock biomasses by multiplying by the average recruitment. If we take half the average recruitment of 5.50 million to be females then 5000g/recruit is equivalent to a female spawning stock biomass of 13,750 t.
J . HOKWOOD
FIG.34. Female spawning stock biomass per recruit (glrccruit age 0) against fishing mortality rate (F, for ages at f r st capture of 2.4 and 4.4 ycars, corresponding to 70 and 100 mm mesh nets.
Fig. 34 presents the equilibrium state, but it also indicates what happens to catches and catch rates as a virgin fishery is encountered, and then fished at a constant rate. Assuming use of a 70 mm mesh net, and a fishing effort giving a steady 20% fishing mortality, the initial catch rates will be high, but will reduce as the stock falls, eventually being only 20% of what they were originally. In addition, the average size of the fish will be much less. This can give rise to a concern within the industry, which looks back to better former times, but Fig. 34 shows that there is only a once and for all bonus.
The Stock and Recruitment Relationship
Fig. 28 illustrated the number of recruits, at age 2 years, against the spawning stock biomass, of males plus females age 3 and over, that generated them (Anon., 1991b, 1992). Over the limited range of data, of the 1971-85 year-classes, there is no clear relationship between the number of recruiting young fish and the size of the adult stock. It is not correct, however, to conclude that no relationship exists, nor that the size of the adult stock is of little consequence to the management and viability of the fish and fishery. Nevertheless, the conclusions to be drawn are difficult to define in detail, and experience of the behaviour of a range of stocks is necessary to understand the dynamics of recruitment. Cushing (1975) distinguished between two elements of over-fishing: growth over-fishing and recruitment over-fishing. In the former, yield is lost if
TIiE B K l S T O L CHANNEL SOLE ( S O L E A S O L E A ( L . ) )
fishing mortality rates are too high to allow the fish to grow to a reasonable size. In the latter, recruitment itself is reduced as the stock declines. In fact both elements can be simultaneously described, as below (see e.g. Beverton and Holt, 1957; Lawson and Hilborn, 1985). The great problem with recruitment over-fishing is that it can destroy the stock. It is believed that serious damage was done to recruitment by a much reduced spawning stock of North Sea herring, North Sea mackerel and even of the Arcto-Norwegian cod. ICES attempts to comment on “safe biological limits” for the stocks reviewed and considers whether stock sizes are too low. However, the mechanisms and approaches are simplistic, relying upon an exercise of common sense in the light of experience from observing the behaviour of many stocks, world-wide. Recommendations have been made that spawning stock biomasses not be taken below historically recorded minima. One statistic detailed by ICES is Fhlgh,which is the mortality rate required to give about 110% of the lowest observed spawning stock biomass per recruit, it being thought prudent not to exceed this level. Based on the results of the 1991 ICES assessment (Anon., 1992) for the Bristol Channel sole, Fhlgh= 0.55iyear. This implies a minimally acceptable spawning biomass of male plus female sole, age 3 and over, of 2100 t. The consequences are examined of incorporating an asymptotic, Beverton and Holt (1957) stock and recruitment relationship in an age-structured model of the population dynamics of the Bristol Channel sole. The relationship is, R = a.SSB(l.O + P.SSB)-’ where R is the number of recruits in thousands and SSB the spawning stock biomass in tonnes. This form is used since it allows for a zero recruitment at zero stock size and a constant recruitment at high stock levels. Estimates of recruitment (at age 2) and of stock biomasses (of ages 3 3, of both sexes) were given by ICES (Anon., 1991b). To obtain values for a and p, it is assumed, first, that the curve will pass through the centre of the observed data (R (in thousands) = 4546, SSB = 4669 t). Second, it is assumed that a is related to the “maximum” biomass per recruit discussed above. It can be seen that at low stock sizes a = RiSSB and that this corresponds to 1.75 (1.e. 110.57) thousand recruitsit SSB. However, this second assumption gives rise to unrealistically extreme results (described below), and the value is arbitrarily doubled to give a = 3.5. The fitted curve and the data points are illustrated in Fig. 28. The weights at each age in the catch and at spawning time were calculated as the average of the male and female weights. The mature biomass is assumed to be 3 years and older. The resulting equilibrium yield curve against fishing mortality rate is given in Fig. 35. For low rates the yield curve is similar to that of the yield
J . HORWOOD '200
Fic;. 35. Equilibrium yield (t) against fishing mortality rate recruitment relationship of Fig. 28.
the stock and
per recruit analysis, since at high stock sizes the recruitment is nearly constant. However, as the mortality rate exceeds the modest level of O.lS/year, the yield falls as the stock produces a lesser number of recruits. At F = 0.77lyear the spawning stock is completely fished out and no yield can be sustained. If a had been at 1.75, corresponding to the ICES estimate for Fhigh, the stock and yield would have been reduced to zero F = 0.37Iyear. The age at maturity for females is nearer to 5 years than 3 years. If the SSB is taken to be of age 5 and over, and assuming the same stock and recruitment relationship holds, then the stock is fished out at F = 0.43/year, for a = 3.5, and at F = 0.27/year, for a = 1.75. Generally, if a stock and recruitment relationship is assumed, and fishing is allowed on immature fish, then there will be a level of fishing mortality that the stock cannot sustain. This analysis implies that, for the Bristol Channel sole, this critical level could be easily reached. Experience in the long-term management of flatfish stocks would indicate that this is too pessimistic a finding; nevertheless, the conclusion is that excessive fishing rates could destroy the stock. As we move above rates exceeding about F = 0.3-0.4/year for the Bristol Channel sole, we cannot be sure that the stock will be self-sustaining and prudence dictates a cautious approach. The analysis cannot be directly used to consider any effects of trends in recruitment with environmental changes and such possibilities have to be evaluated independently.
T H E BRISTOL CHANNEL SOLE (SOLEA S O L E A ( L . ) )
E. Bioeconomics and Dynamics 1. Maximum economic yield Economics are difficult and those of fisheries are no different, but here some simple and robust principles are highlighted. If no price elasticity is assumed then value of landings will be proportional to yield. The yield per recruit function is then the same shape as the long-term equilibrium value function. Average value of sole landings at first sale at Brixham and Milford in 1990 was f5000h. Costs are difficult to judge but there is some fixed cost, borne even if no fishing takes place, which represents aspects of capital, loans, company facilities, etc. However, when fishing occurs costs rise as more effort is expended on items such as fuel and wages. Hence running costs increase as fishing mortality rates increase. It can then be realized that, on average, for maximum economic yield (MEY) or current profit, fishing mortality must be less than that giving the maximum yield (F,,,J, and it may be much less. The consequences of such an economic structure in an open-access fishery were described by Clark (1976, 1985). Open-access is recognized as allowing new units of effort or commerce to enter the industry at will, and although this is no longer the general case in E C fisheries for sole, it was and it remains so for some components of the industry. Economists argued that in an open-access fishery, if current profits were being made, new effort would enter the fishery. Effort would rise to a point of zero profits, and the industry would remain at that level of capacity and profit. Historically, we see that the unregulated nature of our fisheries would have encouraged an over-capacity in the industry. The nature of the open-access regime is unfortunate for fisheries, since for natural living resources, quite different from other industries, an increase in effort above some level will not only result in reduced marginal returns of yield and profit, but may also result in absolute decreases in yield. The conclusion is that an external management of the fishery or a limited allocation of rights to the fishery is necessary for economic viability, or in some cases to prevent extinction of the stock. In an open-access environment the individual is forced to behave in an economic manner that is contrary to the communal good. The fact that he is working at the worst possible economic level, short of leaving the industry, encourages a drive to circumvent regulations that are for the communal good. This is identical to the problem of over-grazing of the common lands (Hardin, 1968).
J . HORWOOD
2. Optimal harvesting The above theories related yields, biomasses and profits to an equilibrium fishing mortality and the theory of fishing, as expounded by Beverton and Holt (1957), essentially takes this approach. It embodies the most crucial characters of any fishery and stock. However, the theory is weak in providing insight into how one might best respond to transient features, such as the highly variable recruitments, or a transition from one state to another. Optimality approaches encompass both the long-term features of the managed system, and the transients to, and around, particular targets. When the transient dynamics of the stock, fishery and economics are considered attention has to be given to the concept of the discount rate or discount factor. In a dynamic system one can harvest some or all, now or later. If harvesting is deferred it must be because of greater long-term rewards. However, if a reward is taken early the value realized can be invested elsewhere. Consequently the value of a reward at a deferred time from the fishery must be discounted by the loss due to inflation and other opportunities for investment. If g(F(t),s(t)) is defined as the profit taken at time t , from a fishing mortality of F(t) and stack size s ( t ) , then a criterion frequently considered for maximization is the discounted sum, over infinite time.
where 0 is the discount factor, 0 d 0 d 1. The dynamic problem solved for fisheries takes the form of finding values of F(t) which maximize the discounted revenue. If we seek to maximize this form then the solution sought is one of maximal community interest. Clark (1976, 1985) considered simple fisheries models in a bioeconomically dynamic framework, and his results are of great use. In equilibrium, for a zero discount rate ( p = 1) these models show the solution lies in bringing the fishery to the MEY. As the discount rate is increased then the optimal return is achieved at a higher long-term fishing rate and rewards are required to be taken earlier. It has been argued that an infinite discount rate leads to the same solution as an open-access fishery, that is to the point of zero profits. This is indeed the case when the annual reward (g(F,s)) and stock dynamics are linear in F , but generally the solution is found at the point where the marginal rate of return is zero. The higher the discount rate the quicker rewards need to be realized. However, it is not only inflation and opportunity costs that contribute to the value of the discount rate used in practice - risk and
THE BKISTOL CHANNEL SOLE (SOLEA SOLEA (L.))
perception of the future play perhaps an even greater role (e.g. Reed, 1984, 1988). If one is uncertain as to the future then high discount rates are frequently used. It follows that some ownership of fisheries, or strategic plan for the fisheries, would lead to lower effective discount rates and hence less pressure for high fishing mortality rates. Some work has progressed on the optimal utilization of specific fisheries, rather than the elucidation of principles from simple models; however, the mathematics are rather formidable, being essentially stochastic and non-linear (e.g. Clark, 1985; Mangel, 1985; Williams, 1989; Hilborn and Walters, 1992). Approximate solutions to the general stochastic problem were given by Horwood and Whittle (1986a,b) and Horwood (1990a, 1991). The results show how a dynamic modulation of fishing mortality rates can take maximum advantage of incoming higher than average recruitments and how this can overcome some of the disadvantages of a fixed mesh size for single and mixed fisheries.
3 . Stability in fisheries Stability of catch and of fishing effort, at some acceptable and compatible level of each, is an attractive objective. Catch is proportional to effort times stock size. For a constant effort, catches vary because of the large natural variation in recruitment. Conversely, to take a constant catch, effort must vary. It can be appreciated that if fishing mortality is low, stock size will be high, and a variable number of recruits entering the fishery will not have a great effect and vice versa. It can be reasoned that stability worsens as fishing mortality rates rise (Horwood and Shepherd, 1Y81; Horwood, 1983). At low mortality rates fisheries can be efficiently regulated through modulation of annual catches and effort, but at high fishing rates stability is only possible by maintaining a constant effort and allowing catches to fluctuate (Horwood et al., 1990; Jacobs et al., 1991).
F. Appropriate Fishery Targets
The above studies indicate that long-term yields from the Bristol Channel sole will not exceed 1000-1200 t, except for some cases of extremely high fishing mortality rates. It is an important finding. Because of the greater recruitment, the maximum yield from the North Sea sole fishery is . is no use the industry substantially greater, at 20,000 t (Anon., 1 9 91 ~ )It looking enviously at the magnitude of the North Sea quotas since the Bristol Channel stock will only sustain a fraction of them. Examination of the effect of different mesh sizes on the yield per
J . HORWOOD
recruit has shown that mesh sizes of 90-100 mm will give slightly greater yields than mesh sizes of 70 or 120mm, at fishing rates that are not excessive. For fishing mortality rates up to O.S/year the differences in yield between 90 and 100 mm mesh nets are negligible. Based o n a value for the rate of natural mortality of O.l/year and mesh sizes of 90-100 mm the maximum yields are obtained at fishing mortality rates of 0.35-0.5/ year. The highest yields are obtained with larger mesh sizes but with very high fishing rates. Such high rates are not practicable, for reasons explained below, and the differences between the maximum yield at this extreme, and the maxima for the 9C100 mm mesh sizes, are small. Stock biomasses fall with increased fishing mortality. High fishing mortality rates and associated low stock sizes mean that the naturally variable recruitments give rise to substantial variability in catches, stock and catch rates. A high target mortality also means that the stock can easily be driven much lower by accident, for example by error in the assessments. Stocks could be accidentally reduced to a size where we have no data to be confident that recruitment can be sustained. Considerations of stock size imply that if only marginal gains ensue at increased fishing mortality rates then the lower mortality rates should be maintained. Considerations of possible stock and recruitment relationships argue against mortality rates in excess of about 0.4iyear. The economic arguments suggest that the most favourable target fishing mortalities are lower than those giving rise to maximum biological yields. Only to encourage high employment does a high fishing mortality rate appear at all attractive, and even then changes in fleet structure could increase employment at modest fishing rates. Considerations of catch rate, profitability, stability, prudent levels of spawning biomass and yield all point to target fishing mortality rates being low - using the statistics here, that would be of no more than 0.3/year with mesh sizes of 9 c 1 0 0 m m . The current status of the stock, as determined by ICES, is given in Section VII1.A and current levels of fishing mortality may be 60% above that giving the maximum of the yield per recruit. Significant reductions in potential and realized effort would be required to meet the above targets. However, Sections VIII.B,C indicate some uncertainty in the assessed status of the stock.
VII. Exploitation of the Bristol Channel Sole From 1906 statistics exist of sole caught from the Bristol Channel and surrounding regions. Before that, there is some qualitative and limited quantitative information. The section focuses on those aspects that give insights into the magnitude of the catches of sole in the past.
THE BRISTOL CHANNEL SOLE (SOLEA SOLEA ( L . ) )
Records of fish caught in the Bristol Channel have been made since the Middle Ages (Matheson, 1929). Up to the seventeenth century there was a large demand for fish because of the numerous fast and fish days decreed by the Church and state, and the Welsh Port Books for 1550-1603 show a considerable import and export of fish (predominantly herring) from Milford Haven. Subsequently the industry waned and to encourage fishing from Swansea, in 1791 the town agreed to pay a premium on various fish. Sole, turbot and John Dory attracted the highest rate, with a premium of approximately f4it. All around the Bristol Channel fixed nets of different types took advantage of the strong currents (Matthews, 1934). One of the most ancient methods of capture was through weirs, which were usually owned by the manor and leased to the fishermen. Such arrangements were recorded from Cardiff in 1314 and again in 1492. Holsworth (1874) described the weirs as of wattle fences, staked into the sand. Two arms of the weir, each about 200m long, met at near low water, at which point there was a closely woven basket which trapped the fish. Many such weirs could be strung together. Holsworth was of the opinion that few flatfish were caught by this gear and an apparently single observation by him was that most fish caught were roundfish. However, in interviews of fishermen from Swansea (Great Britain Parliament, 1866), J. Bevan described “hundreds of thousands” of sole, other flatfish and roundfish destroyed in weirs, many of which were of an unmarketable size. Mr G . Harry reported that almost the entire sweep of Swansea Bay had weirs and that these caught in immense numbers, “almost millions say”, very small sole, turbot and other flatfish of a few inches in length. Another said “It is difficult to use words which would properly convey an idea of the number of small fry taken and destroyed . . . but there are hundreds of thousands of them.” The dead included small sole. In contrast D. Benson, a weir owner, considered the loss of fish to be small, that only a few sole were taken and that it was difficult for sole to be killed in such nets. We know that such bays are the nursery areas of the sole and it is quite possible that these nets did take significant numbers of small sole before they were large enough to migrate to the open sea. Matthews (1934) ascribed the decline of the local fixed net fisheries to the increased commercial fisheries and to the costly twice-daily visits and maintenance. Dillwyn (1840) described the sole as not infrequently taken in Carmarthen Bay in 1802. Various Acts affected fishing for sole in the region. In 1605 drag- or draw-nets were prohibited within five miles of creeks and havens together with the use of nets less than 1.5 inches (3.8 cm) knot-knot. In 1662 n o
J. I I O K W O O D
fishing of any sort was allowed off Devon and Cornwall within 1.5 leagues (7 km) of the coast from June to November. In 1714 the knot-knot mesh size was increased to 3.5 inches (8.9cm). In 1759 the sale of undersized fish was banned; for sole, plaice and dab this was 8 inches (20.3 cm). In 1841 trawling within one mile of the coast was banned off Devon and Cornwall from July to December. The above laws were generally not enforced (Great Britain Parliament, 1833, 1866) and a major revision of fisheries regulations was enacted in 1843 as the Fishery Convention Act (6&7 Vict. Cap. LXXIX). Outside the 3-mile belt fishing boats were to be numbered, trawl nets were to be over 1.75 inches (4.5 cm) knot-knot and the beam of the trawl was not to exceed 38 feet (11.5 m) in length. The Sea Fisheries Act of 1868 (31&32 Vict., c. 22) appears to have removed all the regulations of the 1843 Act and in 1888 responsibility for advising on regulation within the 3-mile limit was passed to the Local Fisheries Committees (Holsworth, 1874; Johnson, 1905; Great Britain Command Paper, 1908). The above reflects the early national and local interest in the sea fisheries, the ebb and flow of incentives and regulations and the concerns that are still voiced about the effects of trawling on the sea bed and on the numbers of young fish.
Early Trawl Fisheries
Sole were caught predominantly by the trawl fisheries and Brixham is reputed the home and source of the offshore trawl industry and particularly of the beam-trawl fishery (Holsworth, 1874; Russell, 1951). The earliest British record of the use of the trawl was in 1376 when it was used inshore and attracted a general condemnation for despoiling the flora, fauna and spat (Russell, 1951). Its use offshore is recorded from about 1770. Beam-trawling became successful with the introduction of the fast, fore- and aft-rigged, sloops and cutters, which could efficiently tow the beam-trawl, and with the increase in land transport available to carry fish to the rich towns of Exeter and Bath. The wooden trawl beams were 11-15 m in length. From 1810 Brixham and Plymouth boats fished from Tenby and Swansea in summer and by 1833 12 Brixham trawlers of about 3 0 4 0 t worked the Bristol Channel during summer to the end of September. Thus, over 150 years ago Brixham trawlers were taking sole from the Bristol Channel. An enquiry into the state of the sea fisheries (Great Britain Parliament, 1866) revealed that between about 1834 and 1844, 7G80 sail-trawlers worked the grounds east of St George’s Channel. A map shows trawling on the Saltees and Nymphe Bank and from Carmarthen Bay to Lundy Island. The 13 local Tenby trawlers were
TIIE BKISTOL CHANNEL SOLE ( S O L E A S O L E A (L.))
smaller and were laid up over winter due to the difficult weather conditions in the Channel. In the 1860s there was n o ground specifically known for sole and they did not fish to the south of Lundy. It is difficult to quantify the total fish landed at that time (circa 186.5) or the proportion of sole. Further, the reported number of 7 0 trawlers working grounds east of St George’s Channel seems difficult to reconcile with the details given by local fishermen, but if true a majority would have been very small trawlers working inshore grounds. To estimate landings of sole per boat it is noted that catches at Brixham were about 1 cwt (51 kg) of sole per smack (Great Britain Parliament, 1866). Later Neale (1888) reported that at Cardiff a trawler would often land 8-14 cwt of sole from a 3-day trip but by then the sole fishery was more prominent. If we assume SO smacks working 4 dayslweek from May to September, at 1 cwtlday, then the fishery may have been yielding over 200 tlyear of sole in the 1860s. However, this rate may be too high since a trip considered “exceptional” caught only 1 cwtlday of sole (Anon., 1899). From 1866 to the publication of official statistics we have to rely upon reports in books, journals and trade papers. In 1888 the fishing docks were opened at Milford Haven which allowed an expansion of the port and, in the same year, the first steam-trawler worked from Cardiff. Tylor (1882) described trawling off Lundy Island and even with a steam winch the 15 m wide beam, worked in 70m, took an hour to drag into the vessel. It can be imagined how important the steam winch was to improving fishing and safety and the steamers no longer had to rely on the wind in order to fish. Neale (1888, 1891) referred to the Bristol Channel as “the home of the sole” and claimed that the boats of Brixham and of Plymouth came primarily to take the sole. In 1872 Milford Haven had 13 first-class vessels (over 1.5 tons), Llanelli 2, Swansea 3 and Cardiff nil (Holsworth, 1874). By 1892 the numbers operating from Milford Haven had increased to 67 steam- and 110 sail-trawlers and by 1902 there were 98 steam and 362 sail-trawlers. Cunningham (1890) thought it probable that the increase in national catches of sole in 1889 was due to the large number of North Sea trawling smacks that had started to work off north Cornwall, for the first time in 1887. Little has been said of the Irish fisheries, which at this time were under British jurisdiction, but throughout the nineteenth century fishing was depressed (Holsworth, 1874). Trawling was locally unpopular and suppressed in the bays. In the mid-century Irish vessels working to the west of St George’s Channel took 3 tlweek of all fish. However, fishermen stated that on the Waterford and Nymphe Bank grounds “there are no such sole, turbot, haddock or whiting on the English grounds as we have here” (Great Britain Parliament, 1866). “Large numbers” of sole were
J . HORWOOD
also reported caught by line with lugworm bait in Dingle Bay (Holsworth, 1874). Nevertheless, Irish fishing was not well developed and can be neglected at this stage, although others visited Irish waters. Calderwood (1894) claimed that the Brixham men were first to trawl off Ireland in 1818 and in 1885 21 Plymouth smacks were reported trawling off southern Ireland with others there in 1886 (Heape, 1887). It should be noted that the naming of the Great and Little Sole Banks in the Celtic Sea was not associated with sole fisheries.
Early Quantitative Information
From 1810 the few trawlers operating in the Bristol Channel caught possibly less than 20 t/year, but by 1864 numerous small trawlers were operating and from 1850 to 1890 catches may have been 200 t/year as the number and size of boats and facilities increased, Relevant sea fishery statistics were collected from Ireland from 1887. Landings of sole into Ireland from 1887 to 1906 were given by Holt (Great Britain Command Paper, 1908). There was little annual variation with annual averages by coast of: east - 5 0 t , south - 20t and total - 160t. Probably only a minority of the 70 t came from the ICES Divisions VIIf-g. Collection of sea fisheries statistics for England and Wales has been a depressing subject for over a century (Johnson, 1905). Not in response to pleas from a series of Parliamentary committees from 1863, but because HR H the Duke of Edinburgh fortunately expressed an interest in the subject, the Board of Trade instigated data collections from 1887. Even so, quantitative data on catches of sole are sparse before 1903 but helpful comments are made in the annual Sea Fisheries Statistics and occasionally in other publications. The Glamorgan Sea Fisheries District covered landings from Swansea Bay, but excluded Cardiff. Annual landings in the District from 1890 to 1902 varied from 38 to 75 t, with an average of 60 t/year. Details of the Glamorgan fisheries by Wade (1914) appear to rely on the earlier descriptions of Neale (1888, 1891) and on these official statistics. Cardiff was of equal importance with Swansea over the decade and “fair quantities” of sole were landed at Cardiff in 1893. In 1896 trawling was banned in Carmarthen and St Bride’s Bay, but foreign trawlers worked off t h e South Wales coast. In 1899 a rail link was opened at Padstow which would have encouraged any local fishery. Milford Haven was a more important port. In 1899, 277 t were landed at Milford Haven (Great Britain Command Paper, 1902), although some of these sole may have come from trips out of ICES Divisions VIIf-g. Trips to the Bay of Biscay
n i t UKISTOL CHANNEL SOLE ( S O L E A S O L E A ( L . ) )
increased from 50 in 1896 to 200 in 1898 and to 250 in 1900, and Aflalo (1904) noted that one of the reasons for these distant trips was to harvest “a larger race of sole than they get nearer home”. Landings into England and Wales, by region, in 1906 (the first year of detailed data) show that 2 9 t came from the Bay of Biscay and 274t from off Portugal and Morocco; most of these were probably landed at Milford Haven to be taken by rail to London. In the same year 429 t came from the Bristol Channel and southwards of Ireland. Based on these catch ratios, 163 of the 277 t landed in 1899 may have come from local grounds. From 1890 to 1902 the number of vessels, and particularly of steam-trawlers. increased and catches in the later years are not likely to be representative of the first few years. From 1890 to 1895 landings in Glamorgan were 60t/year, those at Cardiff were probably about the same and landings were greatest at Milford Haven. This would indicate catches again in the region of 200t/year, but the estimate is more firmly based than for the period 1850-90. From 1895 to 1902 it is estimated that 163 t/year were landed at Milford Haven, landings increased at Padstow and in Glamorgan landings were stable. Guessing that landings outside of Glamorgan and Milford Haven were 80 t, this gives an estimate of the catches from 1895 to 1902 of 300 t/year; this is lower than estimated landings for the next decade when iuller statistics were produced.
D. Catches from 1903 Table 11 gives international catches of sole from the Bristol Channel and adjacent regions, equivalent to ICES Divisions VIIf-g. The arrangement allows inspection of how the totals are constructed, with the hope that they can be improved over the years. From 1971 total catches given are those that were used by the ICES Irish Sea and Bristol Channel assessment working group (Anon., 1991b). These are not necessarily the same as the national official statistics, but rather the estimate by the working group of the true catches. Two columns are presented for Belgium, France and England and Wales. The first is a “minimum” estimate of the catches based on the assumption that if catches were reported from two Divisions combined, such as VIIa VIIf (the Irish Sea and Bristol Channel), then it is assumed that all the catch was taken from VIIa. Conversely, a “maximum” catch is obtained by assuming that all came from either VIIf or VIIg. Where only the “maximum” column is used it signifies either that it has not been possible to quantify a realistic maximum and minimum, or else that there is no ambiguity over catches:
the value can be regarded as a “best” estimate. A dash indicates no data. The character of the statistics is described below by nation. Belgian data from 1903 to 1970 were obtained from Bulletin Statistique des Peches Maritime and from De Belgische Zeevisserij; help was also given by R . de Clerck. From 1903 to 1947 catches were given by VIIa f combined and VIIg-k combined; consequently the minimum value is assumed to be zero and the maximum the sum from the two combined regions. From 1948 to 1957 catches from the Bristol Channel (VIIf) were documented by Holden (1971b, 1973) and his values are given in Table 11. Catches given by Holden from 1958 are in error in that for some years they exclude Belgian catches landed in Belgium. French catch data from 1927 are from Revue des Travaux de L’Institut des Psches Maritimes and it is assumed that catches before 1927 were zero. For 1968-70 the catches are given for Divisions VIIf and VIIg-k; consequently the minimum value is based upon taking the VIIg catch as zero and the maximum from assuming all catches from VIIg-k came from VIIg. Data from Ireland were provided by R . Grainger and comprised landings from 1947 onwards (excluding 195g.53) into ports bordering Division VIIg. No catches were taken from Division VIIf. Landings at the above ports were of 0-4 t/year and it is thought that the VIIa+ f catches of 25 t/year were taken predominantly from the Irish Sea and those from VIIg-k of 41 tiyear predominantly from VIIj. Consequently Irish catches in VIIf-g prior to 1947 were probably about 2 tiyear. Catches of sole by the UK from 1903 to 1905 are only available by coast of landings, but from 1906 they are reported by region of capture in the Annual Reports of Proceedings Under Acts Relating to Sea Fisheries, England and Wales, for the years 190W8, and in the Sea Fisheries Statistical Tables from 1949. An estimate of the catches of sole for 1903-05 was obtained by assuming that in these years the proportion of catch from the different regions was the same as in 1906, the first year of detailed data. Catches by England and Wales vessels from 1906 to 1948 are available for Divisions VIIf and VIIg-k; maximum and minimum estimates are given accordingly. For the war years of 1915-18 catch statistics were available for western England and Wales and, for a minimum estimate, it is assumed that no catches were taken from VIIf-g, and, for a maximum estimate, that all were taken there (this is discussed further below). For the war years of 1939-44 data are incomplete, but landings are given for the ports of Cardiff, Milford Haven and Swansea and it is assumed that landings at these ports were caught locally in VIIf-g. However, Hickling (1946) showed that the Milford Haven trawlers occasionally worked, and were attacked by submarines, to the south and west of Ireland. Consequently these catches may not all have
T I i E UKISTOL C‘IIANNEL SOLE (.SOLEA .SO/2EA (L.))
been taken locally. Catches are not available for 1945 and it is assumed that they were about the same as in 1943-44 at 200 t/year. Catches from 1949 on (excluding 1964 and 1965) are given in the Statistical Tables and held on computer by separate Divisions. Data held for 1964 and 1965 are incomplete and the statistics given are of catches from VIlf and VIIf-k. Catches by the Netherlands in VIIf-g were nil or negligible, and from 1971 they have been included in the total for the region. 1. “Best” estimates of catches from 1903 Table 11 gives a final summary of the summed “minimum”, “maximum” and best estimates of international catches from 1903. The annual minimum is the sum of the national minima and where only a single “best” estimate exists (e.g. England and Wales, 1903) that is included. The maximum is similarly obtained. The best estimates are constructed so as to provide the most credible single series and details of how this is obtained are described below by nation. Prior to 1948, most of the Belgian catches from Divisions V I I a + f would have been from VIIf and it is possible that a large proportion of those from VIIg-k were from VIIj since the small Irish fleet was successful in that area. Consequently one can do little better, at this time, than to assume that half of the Belgian total came from VIIf-g. From 1948 the best estimate is obtained from taking the catch in Division VIIf and half of that in VIIg-k. For France the best estimates of catches from 1968-70 are calculated from catches in Division VIIf and 0.66 of those from VIIg-k, this being the proportion in the previous 3 years. For Ireland, it is assumed that the small catch taken in 1947-68 was maintained from 1903 to 1946 and also in 1970. For England and Wales for 1906-38 (excluding 1915-18) there is no information on which to judge the split of catches amongst Divisions VIIg-k, and the best estimate is given as catches from VlIf plus half of those from VIIg-k. During the war years of 1915-18 fishing was reduced throughout England and Wales and catches of all fish were a third of those before the war. Catch data for sole are available from western England and Wales and the proportion caught in VIIf-g is required. With the outbreak of war, Belgian and French fishermen worked from Milford Haven (Matheson, 1929). Cardiff fishermen complained that the authorities had stopped them going to sea twice because of submarines in the Bristol Channel (Great Britain Command Paper. 1920). Exchanges were reported between submarines and boats fishing outwards of 100 miles west of Lundy. The reports illustrate that fishing certainly continued in the region and was not restricted to the relatively safe waters of t h e Irish Sea. In 1914, 46% of the
J . HOKWOOD
western catches came from VIIf and about 50% from VIIf-g and in Table 11 this proportion is assumed for the best estimates for 1915-18. For 1 9 4 W 8 , it is assumed that the proportion of the catch in VIIg, as a proportion of that in VIIg-k, was the same as for the following 5 years, i.e. 0.87. For 196546 it is assumed that all the VIIg-k catch came from VIIg since contemporary catches in VIIh-k were negligible.
Evolution to the Modern Fishery
1. Development of the beam-trawl fishery
Both steam- and sail-powered effort increased in the south-west in the early 1900s. In 1914 the number of first-class fishing vessels registered at Milford Haven was 78, at Cardiff 23 and at Swansea 32; 86% of these were powered by steam and only two vessels were motor powered. In comparison, Brixham had 201 registered vessels 96% of which were of sail. By 1920 Brixham had registered 26 motor vessels, whereas the three Welsh ports had a total of four. Nevertheless, most vessels at Brixham were of sail whilst those in Wales were of steam. The last first-class sailing vessel registered in Swansea was in 1921, at Cardiff in 1921, at Milford Haven in 1932 and at Brixham in 1945. The last registered steam vessel disappeared from Milford Haven in 1965. The sole is nocturnal and lies deep in the sand during the day; consequently the otter-trawl fleet mainly caught the sole at night and with relatively low catch rates. The sole was thus an important by-catch rather than a direct target species and the catch rate of plaice in VIIf in 1989 was over seven times that for sole. In the 1960s the beam-trawl fleet developed in Holland to fish primarily for sole (de Veen, 1976). The modern beam-trawler fishes with a trawl each side of the vessel. Small vessels work beams of 4-6 m in length, weighing 1-2 t in air, whereas the larger vessels, which can be in excess of 3000hp, can work two 12-m length beams. Two types of gear are rigged on the beam-trawl, a smooth-ground or a rough-ground rig. In the Bristol Channel the rough-ground rig is by far the more common. This heavier gear has a chain-mat or stone-mat, made of inter-linking steel chains, which is in front of the net. The mat disturbs the sole from the sand and makes it accessible to capture, as do tickler-chains, but the mat also allows the net to ride over boulders and rough objects. Between the mat and the mouth of the net there are usually rubber bobbins attached to the ground-rope and often flip-up ropes to provide additional protection for the net. The heavy rig allows sole to be caught at any time and whereas the average
THE BRISTOL CHANNEL SOLE ( S O L E A SOLEA ( L . ) )
catch rate for sole by the UK otter-trawlers in VIIf-g in 1988-90 was 1.5 kg/h that for the beam-trawlers was over 10 kgih. In the Bristol Channel the UK beam-trawl fleet developed only slowly during the 1970s, averaging an aggregate time of less than 1000 h/year fishing. Expansion was rapid during 1980-85 and in 1990 the beam-trawl fleet fished for 29,000h, with vessels averaging 100 GRT and over 600hp. In contrast, that component of the otter-trawl fleet fishing for flatfish decreased its effort from about 30,000h in the early 1970s to 11,000 in the late 1980s, and the size of the vessels remained constant at about 60 GRT. The Belgian fleet is now composed almost exclusively of beam-trawlers and a similar expansion of effort occurred in the Bristol Channel. In the years 1971-73 the fleet fished about 28,000h/year whereas during 1987-89 it fished over 70,000 h/year. In comparison, the effort expended for sole by the Irish and French fleets is small. 2. The regulatory framework Current regulation and management as it affects the Bristol Channel and Celtic Sea must be understood within the E C framework. The Treaty of Rome of 1957 established objectives for E C agricultural policy (Article 39) which have been interpreted as applicable to fisheries. The Article is of a motherhood character, being only useful when applied more specifically, the Common Fisheries Policy (CFP) being just that type of application. The UK joined the EC in 1973, through the 1972 Accession Treaty, along with Denmark and Ireland, and this Treaty obliged the EC to establish, by 1983, a Common Fisheries Policy. On accession it was agreed to maintain arrangements akin to those of the 1964 London Fisheries Convention. Nations had exclusive rights out to 6 miles and other member states enjoyed restricted access in the 6-12-mile belt, based upon historical fishing patterns. In response to the establishment of 200-mile fishery limits by Iceland and other nations, the E C countries established their 200-mile exclusive fishery zones from 1 January 1977. Between then and 1983 negotiations continued to establish a CFP, the main source of disagreement being access arrangements. Eventually Council Regulation 170183 was agreed and restrictions on access similar to those above were accepted within the g12-mile belt. The CFP was agreed for a 20-year period with a mid-term review in 1992. Fishing vessels in Divisions VIIf-g are thus subject to a variety of restrictions, some E C and some national. The main instruments of UK national legislation are the Sea Fish (Conservation) Act 1967 (and amendments), which regulate most main activities such as minimum landing size, restrictions on gear, vessel licensing and protected areas, the
J . 1*0RWOOD
Sea Fisheries Acts of 1883 and 1968, which regulate to avoid conflicts at sea and the Sea Fisheries Regulation Act 1966, which allows Sea Fisheries Committees to formulate bylaws within their 3-mile coastal zones (Wise, 1984; Churchill, 1987). The most important aspect for the fishery and fish is t h e determination of an annual permitted catch from the fishery and the principles governing this were resolved in 1983 in the above E C regulation. It was agreed that management should be by a Total Allowable Catch (TAC). The distribution of TACs amongst member states was agreed mainly on a historical basis, using the average catches from 1973 to 1978. The consequence is that the TAC may be varied, perhaps increasing because of the entry of strong year-classes or decreasing as stocks decline, but the relative allocation by nation remains the same; this has been termed the principle of “relative stability”. For VIlf-g the relative allocation for sole is Belgium 6396, UK 28%, France 6% and Ireland 3%. Unfortunately for the UK industry the reference period coincided with the lowest UK catches for about a hundred years (Table 11). Within the agreed TAC for sole the allocations are managed nationally. Within the UK, for divisions Vllf-g, this is done with the assistance of the Area VII Advisory Committee which involves members of the industry. Vessels over 1 0 m in length must have a licence to fish for sole and such licences are very restricted. In addition, a special licence is required to fish with beam-trawls in Divisions VIIf-g. The sole quotas of Area VII have been allocated, usually on a bimonthly basis. to avoid a free-for-all, since for the past several years available local fishing effort has been more than sufficient to take the quota, and restrictions have been necessary. Often the beam-trawl fleet is treated separately from other members of the catching sector. As an example, in VIIf-g in 1990, the licensed fleet was constrained, in January and February, to 1 tivesselimonth and, if that was attained before the end of the period, to a 10% by-catch of sole for the remainder of the period. For March and April this was increased to 2 timonth. followed by a 10% by-catch and this reverted to 1 timonth, followed by a 10% by-catch, in May. This limit remained in force until the end of September after which another series of restrictions followed. Belgium has a licensed fleet but does not allocate in this detail, and consequently its quota has often been taken early in recent years. The Belgian sole fishery in VIIf-g was closed in December in 1988 and in October in 1989. Through E C technical measures, outside of the 12-mile limit beamtrawlers are restricted to beams of a combined overall length less than 24 m. Within the 12-mile limit only beam-trawlers under 24 m and of less than 221 kW engine power are allowed to fish, but here the combined
T H E BRISTOL C H A N N E L SOLE ( S O L E A S O L E A (L.))
length of beams must be less than 9 m . E C technical measures also regulate minimum mesh size, at 80 mm for VIIf-g, and minimum landing size of sole, at 24 cm. The Sea Fishery Committee’s bylaws also regulate within 3 miles of the coast. The bylaws of the Devon, Cornwall and South Wales Committees all restrict the size of vessels fishing within 3 miles and off South Wales beam-trawling is only allowed with a single, 4 m beam-trawl. Fishing within the Lundy Island Marine Nature Reserve is prohibited under the bylaws. 3. The market for sole
In 1990 sole realized f5000it at first auction and apart from turbot, bass and lobsters no other abundant fish or shellfish reached near that value. By weight, UK sole catches, landed into the UK from VIIf, ranked 6th in relation to other species, and 11th from VIIg; in total value of landings, however, sole was the most valuable species caught from VIIf and second only to hake in VIIg. The local fishing industry and markets rely to a significant degree on the fishery for sole. Recent landings by UK vessels of sole from VIIf-g are primarily into Newlyn (45% of the total average catch from 198G90) with Milford Haven second (21%). Other main ports of landing are Brixham (lo%), Padstow (17%) and Fleetwood (7%). Sole is important to the restaurant trade and to a lesser degree to the wet-fish market, but from the UK over 2000 t of sole are annually exported to the Continent, valued at about €8 million. The lower value, per tonne, is probably due to the export of a smaller size of sole. The UK quota for sole from all regions was 3150 t in 1990 and 75% of this was exported. In contrast, only 200-300 t is imported. 4. The fishery’s future The future of the fishery depends upon the status of the stock and the economics of fishing. It can be assumed that sole will remain the valuable commodity that it has been for the last century, but the costs and opportunities to fish are less predictable. Fishing opportunities will depend largely on international agreements arrived at within the EC, especially on any possible renegotiation of the CFP, and on any reorganization of fishing within the UK. The position of non-UK interests in the UK fisheries (the so-called flag ships), is still unresolved. However, one of the elements over which it is possible to exercise some reasonable control is the size of the stock and the fishing mortality exerted upon it. Sections VI and VIII demonstrate that on average total catches cannot be sustained in excers of 1200-1300 t/year. The ICES assessment (Anon.,
J . HORWOOD
1992) indicated that catch rates could be significantly improved by a reduction in international fishing mortality, and associated effort, which would not reduce the total yield from the stock. The supply of fish would remain unchanged but the profitability of the fishing vessels would be much improved, the problem being, of course, that only part of the catching industry would remain. Although Section VII1.C casts some doubt o n this conclusion even if international effort was not decreased then a restructuring of the UK fleet would allow a better utilization of existing fishing capacity and a reduction of t h e stop-go character of current management described above. The present conduct of the fishery has resulted in low profits, a need for short-term returns, a fire-fighting attitude to management and a deterioration in the biological statistics upon which management is based.
VIII. Status of the Stock Evaluation of the status of the stock can be approached through estimation of current size, relative depletion and future prospects. An assessment of the sole in Divisions VIIf-g is undertaken annually by ICES. Its task is to advise on catch options for the forthcoming year and the status of the stock relative to some rather general biological “reference points”. The most important assessment method used in ICES is that based upon fitting catch per unit effort (CPUE) series to catch at age data (Anon., 1988; Pope and Shepherd, 1988); this will be referred to as a tuned virtual population analysis (VPA). In instances where the relationship between stock size and CPUE is uncertain, as for many pelagic stocks, this approach is not feasible and for some stocks the spawning stock biomass (SSB) is estimated from counts of eggs released into the sea and of fish fecundity. This egg-production method has also been considered for cases where the catch and catch at age data are thought unreliable - such as for the North Sea sole. The VPA and egg-production approaches are independent, but they have not been applied to the same stock of fish in a manner that allows a rigorous and critical cross-validation of the techniques. Egg-production estimates of the western stock of mackerel have been used to scale a VPA and hence they were not independent from the VPA stock estimates. Bannister et al. (1974) and Heessen and Rijnsdorp (1989) attempted to reconcile VPA and egg-production estimates of the North Sea stock of plaice. However, problems existed in the spatial and temporal coverage of the plankton surveys, in the identity of the North Sea complex of plaice populations and the associated appropriateness of a single assess-
‘IIIE URISTOL C H A N N E L SOL,E ( S O L E A .SOl,EA ( L . ) )
ment for this complex and in the scaling (or tuning) of the VPA to catch rates. It is surprising that validation of the VPA method has not been attempted since virtually all major stocks are assessed with the method and at least one untestable assumption is required (usually the fishing mortality on the oldest age). In addition, all estimates of natural mortality are poor. There may be several reasons for this. First, the VPA model is essentially simple and biologically credible and provides a sensible basis from which to proceed - it is not of a “black-box’’ type wherein predictions are provided from a purely empirical basis, as may be the case in many regression analyses. Second, for short-term advice many likely errors cancel out; for example, if the stock size is overestimated then fishing effort will correspondingly be underestimated and the prediction of a catch with constant effort will be similar to the true value. Third, the annual assessment practices are extremely costly and time-consuming and this deployment of resources limits the opportunity to explore many important general issues. Last, the assessment practices have not developed through a traditional statistical approach to the subject that would naturally demand that, with any estimate, a variance be estimated or that alternative approaches be explored whenever possible. The sole stock of Divisions VIlf-g is thought to have a reliable, tuned VPA assessment which is used for the provision of advice for international management decisions. The stock is also amenable to assessment with the egg-production method in that the spawning sites of the VITf-g sole are known and are discrete, allowing egg production to be measured, and that the fecundity of individuals in the stock can be determined. Consequently an exercise was conducted in 1990 focused specifically on the determination of stock biomass with both methods and on an examination of the comparability of the two approaches; this is reported below. Information from a mark-recapture exercise is also reported upon, and finally, the population trajectory of the sole is estimated from the start of the fishery in 1820.
A . ICES Assessments The ICES assessment of the Bristol Channel (Divisions VIIf-g) stock of sole gave estimates of the stock size and mortality rates from 1971 to 1991 and short- and long-term predictions of catches and stock sizes (Anon., 1992) but only the essential points are presented below. The stock size was estimated using a tuned VPA approach. Catch rates from the Belgian beam-trawl fleet over the years 1982-90 and over ages 2-8 years were used for tuning and a constant catchability with time for each age was
J . HORWOOD
assumed for sole caught by the Belgian fleet. For presentation a “reference F” was chosen as the average fishing mortality on ages 4-8 years (F,). The statistic F, is generally comparable to other values of mortality used in this study, and in Section VII1.E below, since it is approximately the maximum fishing mortality rate applicable to ages 4 and above. The results show that fishing mortality rates fluctuated between 0.20 (18%) and 0.53 (41%) /year over the 20 years. The mortality rate was similar during 1971-75 and 1976-80, at 0.30 (26%) /year, but it rose to 0.40 (33%)/year over 1981-85 and again to 0.48 (38%) /year in 1986-90. In 1990, F, = 0.44 (36%) /year. The “spawning stock biomass” (SSB) was calculated as the biomass of males plus females of ages 3 and over. Associated with the increase in fishing mortality the stock size decreased from 1971. During 1971-75 the SSB was 3800 t, whereas during 1986-90 it was 2700 t, which is at or near the lowest ever stock size. If it had not been for the increases in average weights at each age (Section 111, p. 264) the stock would have been nearer to 2000t. The long-term yield per recruit analysis showed that the maximum average yield was found at F, = 0.26 /year, or 40% below the estimated current fishing mortality rate. If the fishing effort and hence fishing mortality rate was decreased by 40% then yields were predicted to increase by 3.5% and SSB by 46%. However, the yield per recruit curve is relatively flat for F values of 0.1-1.0 /year.
B . Egg-production Bused Estimates Six plankton grids were sampled over February to June 1990 for sole and larvae (Section 11). The numbers of Stage I sole eggs at each station were converted to numbers produced per day by dividing by the temperaturedependent stage duration time, the temperature being the vertically averaged value for each station. The basic unit of data is then number of eggs produced/m2/day at a sampled station. For each survey the sampled egg-production data need to be integrated over the plankton grid to find the numbers produced per day by the population at the time of the survey. As a statistical exercise this is not straightforward since there is known persistent structure in the data, whilst at the same time spatial correlation between stations is not known. Fig. 5 shows that the sampled egg distributions identified well the regions where no eggs were present and that the sampling was almost as close as practicable in regions where eggs were present. Distributions of eggs in 1989 and 1990 were similar. It is important that stations of high and low
T H E URISTOL CIIANNEL SOLE ( S O L E A SOI.EA (L.))
density are not interpreted as random sampling variation but as a major signal. Experience from other plankton egg surveys also suggests that the large variations are not due to sampling errors. Consequently it was decided to integrate the distributions rather than treat them as random samples. To spatially integrate the egg-production distributions it was necessary to first interpolate the egg-production data onto a regularly spaced grid, but since the spatial-correlation of the distribution of eggs was not known the interpolation procedure was selected subjectively. The chosen procedure calculated the numbers produced /day at a grid-point by weighting the values at sampled locations by the inverse of distance, from point to sample-station, squared. Once interpolated onto the regularly-spaced grid, a Simpson's 318th rule was used to integrate the spatial egg distribution (Abramowitz and Stegun, 1965). However, other apparently sensible choices of both interpolation procedure and integration method could not be dismissed and the effects of alternative choices were examined. Other interpolation procedures examined were (i) weighting by the inverse of the distance between the grid-point and sample locations and (ii) kreiging with a linear auto-correlation function, and for integration the alternative methods were (I) trapezoidal integration rule and (ii) Simpson's rule (e.g. Cressie, 1991). If an example is taken of the survey when most egg production occurred ( 3 April 1990) the chosen inverse distance-squared procedure gave an integrated egg production of 19.2 x 10'. Choice of integration method gave a 5% difference between the maximum and minimum for each interpolation procedure, with the originally used Simpson's 318th method giving the intermediate value in all cases. Choice of interpolation procedure was more important. Difference between the highest and lowest, for each integration, was 12%, but again the originally used inverse-square weighting gave the intermediate values. Practice within ICES has been to average stations within ICES rectangles and apply the value to the area of the rectangle. For this survey the originally used method gave an estimate 17% above the rectangle method. The conclusion is that a 1&20% error (not variation) may easily be introduced at this stage. Fig. 26 shows the integrated numbers of Stage I-IV eggs for each cruise. Given the temperatures, the time of the occurrence of the first and last eggs were calculated from the first and last cruises. The total Stage 1 egg production of 8.91 X 10" was obtained by integration of the curve assuming a linear interpolation between points. A variance will later be associated with the integration over time. The average duration of Stage I eggs on the five cruises was 2.16 days. The egg-production estimate is assumed to apply to the mid-time of the stage and numbers at
J . HORWOOD
spawning can be estimated using the egg mortality rate from Section V of 0.20/day (s.e. 0.018). This gives 1.11 x 10l2 (i.e. ex& x 2.16 X 16 x 0.2) X 8.91 x lo") eggs produced by the spawning stock (s.e. ~ 0 . 2 x2 lo", coefficient of variation (c.v.) = 1.9%) over the total spawning season. The above uses data of Stage I eggs only although additional information is available from other egg stages (see e.g. Wood et al., 1989; Wood and Nisbet, 1991), as can be seen in Fig. 26. The time that the eggs were in mid-Stage I can be calculated from the development rates. Temperatures were taken as the average depth-averaged temperature at stations with Stage I eggs present. Fig. 27 indicates that the value of mortality of 0.20 /day can be considered applicable to all stages, and this rate was applied to project back each stage to the numbers at the mid-point of Stage I. The results are illustrated in Fig. 36. A trapezoid integration of the data gave a similar production estimate of 8.84 x lo", which can be raised to 1.10 x 1OI2 to account for natural mortality during egg Stage I. Fig. 36 suggests that production may be nearly normally distributed with time. A least-squared fit resulted in an estimate of 7.50 x lo", which can be similarly raised to 0.93 x lo1*. An insight into the variation of the unraised estimates can be gleaned through an approach which is persuasive but not rigorous. The spatially integrated value for each cruise is, in a sense, a mean, derived from a set of samples. These samples have a coefficient of variation (c.v.) of magnitude u. We can then suggest that the C.V.of the integrated value is approximately v / d n , where n is the number of plankton stations with eggs. This will underestimate the variance as a significant contribution to the total variance will come from the stations with larger numbers. For this exercise the typical number of important stations is about 16. It has thus been assumed that each integrated value has a similar C.V. of vi4. The variance of the estimate of total production (8.91 x lo"), can be obtained by taking the variance of the trapezoidal formula. This results in a C.V. of 0 . 1 5 ~ .Experience with other egg surveys (e.g. Harding and Nichols, 1987) shows that v varies from 0.2 to 1.0, but except in a few cases of low egg density v