The Life-cycle of Sandeel
- Adaptations to a seasonal environment, from the perspective of a forage fish
Mikael van Deurs
The Gradual School of science, Faculty of Science, University of Copenhagen, Denmark. Phone:
+45 51 36 93 80, E-mail: [email protected]
Academic dissertation
By due permission of the Faculty of Science, University of Copenhagen, Denmark, to be defended at Marine Biological
Laboratory, University of Copenhagen on October 27 th 2010.
PhD Committee
Michael Olesen, Associate professor, Marine Biological Laboratory, University of Copenhagen (chair)
Peter Grønkjær, Associate professor, Department of Ecological Sciences, University of Aarhus, Denmark (opponent)
Jørgen S. Christiansen, Professor, Department of Arctic and Marine Biology, University of Tromsø, Norway (opponent)
Academic advisors
John Fleng Steffensen, Professor mso, Marine Biological Laboratory , Biological Institute , University of Copenhagen
Henrik Mosegaard, Ph.D., senior scientist and section leader, National Institute of Aquatic Resources, Danish Technical
University, DTU-Aqua
Submitted: August 14 th 2010
ABSTRACT
The aim of the Ph.D. study was to identify and describe critical ecological and physiological links between climatic variability and the life-cycle of a highly abundant and commercially targeted prey fish (sandeel, Ammodytes ssp.). The obtained results are suggestive of several pathways through which variation in the seasonal cycle of prey availability, prey species composition and sea temperature potentially could influence at the population level. Those pathways involve: i) temporal mismatches between peaks in food availability and the feeding periods, ii) intra-specific competition among juveniles exposed to time-constraints on growth and reserve accumulation prior to winter, and iii) life-history adaptations in relation to size at maturation and the overwintering. A single main message of this work is that neglecting the importance of the overwintering phenomenon and seasonality in the environment may lead to failure in understanding population fluctuations of not only sandeel but possibly forage fish populations in seasonal environments in general.
TABLE OF CONTENT:
SUMMARY (English) 1
SUMMARY (Danish) 2
OVERVIEW OF CONTENT 3
1. INTRODUCTION 4
2. OBJECTIVES 9
3. LIST OF MANUSCRIPTS 9
3.1. STUDY-I 9
3.2. STUDY-II 10
3.3. STUDY-III 10
3.4. STUDY-IV 11
4. A GENERAL INTRODUCTION TO SANDEEL IN THE NORTH SEA 12
5. METHODOLOGICAL CONSIDERATIONS 17
6. SUMMARIZING DISCUSSION AND SYNTHESIS 19
6.1. SURVIVAL OF SANDEEL LARVAE AND JUVENILES IN RELATION TO PREY COMPOSITION AND SIZE DEPENDENT CAPACITY FOR OVERWINTERING (STUDY-I AND STUDY-II) 21
6.2. ADAPTIVE BEHAVIOUR AND OVERWINTERING OF ADULT SANDEEL (STUDY-III) 28
6.3 SCHOOL BEHAVIOUR STUDIED IN THE LABORATORY (STUDY-IV) 32
7. CONCLUSIONS AND PERSPECTIVES 34
8. FUTURE RESEARCH INITIATIVES 36
APPENDIX: STUDY-I, STUDY-II, STUDY-III, AND STUDY-IV
PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
SUMMARY
In marine productive off-shore ecosystems the flow of energy from zooplankton to large predators
(fish, birds and mammals) is often channelled through a few species of highly abundant schooling planktivorous fish, the so called wasp-waist species, small pelagics or forage fish. While it is beyond doubt that many of these massive populations have varied radically in size on decadal time- scales, the underlying processes are still vaguely understood. The group of fish referred to as sandeel (or sand lance, Ammodytes ssp.) comprises several forage fish species in many temperate and boreal shelf ecosystems and is the main target of a large industrial fishery in the North Sea, where the stock have undergone large changes in size over the last decade. Sandeel species have in common that they bury in sandy substrates at night and presumably also all day during a substantial proportion of the year when feeding conditions are suboptimal. The aim of this PhD study was to identify and describe critical ecological and physiological mechanisms linking the life-cycle and burying behaviour of sandeel to environmental and climatic variability. The results I will present here are suggestive of several pathways through which variation in the seasonal cycle of prey availability, prey species composition and sea temperature could influence at the population level.
Those pathways involve: i) temporal mismatches between peaks in food availability and critical feeding periods, ii) intra-specific competition among juveniles exposed to time-constraints on growth and reserve accumulation prior to winter, and iii) life-history adaptations in relation to size at maturation and the overwintering behaviour. A single main message of this work is that neglecting the importance of the overwintering phenomenon and seasonality in the environment may lead to failure in understanding population fluctuations of not only sandeel but possibly forage fish populations in seasonal environments in general.
1 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
SUMMARY (Danish)
I marine økosystemer bliver strømmen af energi fra zooplankton til rovfisk, fugle og havpattedyr ofte kanaliseret gennem store forekomster af ganske få arter af stimefisk, de såkaldte wasp-waist species , small pelagics eller forage fish (byttefisk). Det er kendt at disse massive populationer af byttefisk varierer radikalt i størrelse fra årti til årti, mens vores viden om årsagerne til denne variation ofte er mangelfuld. Gruppen af fisk der internationalt er kendt som sandeel eller sand lance (i Danmark også kendt som tobis) omfatter adskillige arter af byttefisk. Tobis forefindes i massive forekomster i tempererede og boreale marine økosystemer kloden rundt, hvor disse små
åle-lignende fisk udgør en vigtig fødekilde for en lang række rovfisk, fugle og havpattedyr og er desuden attraktive for industrifiskeriet. De forskellige arter af tobis har til fældes at de graver sig ned i sandbunden om natten samt om dagen i perioder hvor fødekoncentrationerne er lave (f.eks. om vinteren).
Målet med dette PhD-projekt var at identificere og beskrive kritiske økologiske og fysiologiske mekanismer som forbinder tobisens livscyklus og nedgravningsadfærd med miljø-relaterede og klimatiske variationer i deres omgivelser. Resultaterne som præsenteres i denne synopsis beskriver en række mekanismer gennem hvilke ændringer i sæson-cyklussen i føde-sammensætningen, fødekoncentrationen og vandtemperaturen kan influere på tobisen. Disse mekanismer inkluderer: 1) mismatch mellem perioder med høje forekomster af føde og perioder hvor tobisen har et behov for at finde føde, 2) konkurrence om føde mellem unge fisk konfronteret med en begrænset tidsperiode i hvilken de skal opnå et minimum af vækst før vinteren indtræffer og 3) livshistorie-strategiske tilpasninger i relation til størrelse ved kønsmodning og overvintringsadfærden. Den overordnede konklusion er at overvintrings-fænomenet og sæson-variationen i miljøet er vigtige elementer hvis
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vi vil opnå en fuld forståelse af fluktueringer i verdens tobis bestande, og måske endda i forhold til bestande af byttefisk generelt.
OVERVIEW OF CONTENT
The thesis includes four separate studies (STUDY-I through STUDY-IV), attached as four separate manuscripts (where two have been published or accepted for publication in Marine Ecology
Progress Series). Laboratory work in these studies were carried out at the Marine Biological laboratory of University of Copenhagen, while modelling tasks were carried out at the Danish
Technical University, Institute for Aquatic Resources. In the synopsis I will: i) provide a general introduction to the topic, ii) review essential literature on sandeel biology (mainly Lesser sandeel in the North Sea, which will also be referred to as the North Sea sandeel stock), iii) provide a thorough synthesis and combined discussion of the results of STUDY-I through STUDY-IV, and iv) put the results in a larger perspective and propose future work initiatives. The synthesis and combined discussion will mainly focus on Lesser sandeel in the North Sea, whereas the more general ecological implications of the results and detailed comparisons of specific results with previous findings are available in the four attached manuscripts
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1. INTRODUCTION
In marine productive off-shore ecosystems the flow of energy from zooplankton to large predators
(fish, birds and mammals) is often channelled through a few species of highly abundant schooling planktivorous fish, the so called wasp-waist species, small pelagics or forage fish (the term forage fish will be used subsequently). While it is beyond doubt that many of these massive populations have varied radically in size on decadal time-scales, the underlying processes are still vaguely understood (Checkley et al. 2009).
The concepts of ecosystem-based management (EBM) of fisheries have emerged in the past two decades from a growing realization that management of fish stocks are obligated to fail if the environmental and ecosystem context of fished stocks are left out of the management considerations
(Garcia et al. 2003). Accumulating evidence suggest that fishing down the food-webs, eutrophication, and climate changes are causing re-structuring of pelagic ecosystems with lasting ecological, economic and social consequences: For example by promoting rapid shifts from ecosystems that are dominated by fish, that keep jelly fish in check through competition or predation, to one dominated by jelly fish, (Timothy et al. 2006; Richardson et al. 2009). The forage fishes play an inevitable role in relation to such issues, but lack of knowledge about forage fishes comprises a hindrance for further development of EBM strategies that accounts for such species. A tight coupling between forage fishes and the environment has long been accused for being a major
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cause of fluctuations in fish populations, and since the 1980s studies addressing this coupling have been building up. However, as stated by Checkley et al. (2009): Much has still to be done.
In temperate, boreal and arctic regions forage fishes (e.g. Lesser sandeel Ammodytes marinus ,
Atlantic herring Clupea harengus , sprat Sprattus sprattus , Atlantic silverside Menidia menidia and capelin Mallotus villosus ) experience a combination of strong seasonal fluctuations in food availability and in the physical environment, and they are often relying on transient elevations in zooplankton productions. The most important annually reoccurring peak in zooplankton production occurs in spring, fuelled by a primary production that is triggered by temperature-induced stratification and increasing day length. Abundances of the prey items for forage fishes, e.g. calanoid copepods, increase from near zero to numbers in the order of 10 5 m -2 during the spring months (e.g. Carlotti and Radach 1996; Tande et al. 2000; Samuelsen et al. 2009). The highly variable feeding regime restricts growth and reproduction to short time windows of the annual cycle
(Winder and Schindler 2004), which is often reflected in precisely timed annually reoccurring events (the life-cycle phenology) (Sydeman and Bograd 2009). They for example accumulate energy reserves prior to winter to (i) minimize starvation mortality during an overwintering period,
(ii) to allow spawning during times where food is scarce but where the timing is optimal in terms of offspring survival, or (iii) to endeavour long distance migrations between feeding grounds, overwintering grounds and spawning grounds (Hislop et al. 1991; Shultz and Conover 1997; Shultz and Conover 1999; Slotte and Fiksen 2005; Behrens et al. 2006; Hurst 2007). Matches in time between the seasonal cycles in the environment and the phenology of organisms are expected to play an essential role in life-cycle closure, and due to the trophic key-role of forage fishes any mismatch between fish phenology and environmental cycles is likely to cascade through the entire food-web (Edwards and Richardson 2004).
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While migratory strategies in relation to forage fishes (in particular herring and capelin) have received considerable attention in the literature (e.g. Mcquinn 1997; Friis-Rodel and Kanneworf
2002; Slotte and Fiksen 2005; Behrens et al. 2006), a much less studied behavioural strategy is the overwintering strategy. Some species generate enough reserves prior to winter to fully support both metabolism and gonad development during winter and presumably overwinter in a refuge (e.g. deep water, hypoxic water or burying in sand) and in a state of low activity (e.g. Winslade 1974; Ultsch
1989; Huse and Ona 1996; Paul and Paul 1998; Schultz and Conover 1997; Baumann et al. 2007;
Kaartvedt et al. 2009; Varpe and Fiksen 2010). Despite overwintering being a widespread phenomenon and despite the recognition of size-dependent physiological challenges of surviving winter at a minimum or zero food intake (e.g. Schultz and Conover 1997; Clarke and Johnston
1999; Schultz and Conover 1999; Kooka et al. 2007; Kaartvedt et al. 2009) insight into the evolutionary and ecological and physiological mechanisms underlying the overwintering phenomenon in forage fishes have so far remained largely elusive.
Sandeel or sandlance (Ammodytes ssp .) are fairly small and eel-shaped fish and comprise numerous species in temperate and boreal marine shelf ecosystems from all over the Northern hemisphere, e.g. the North Sea and Coastal regions of Alaska, Greenland, Iceland, Japan, and Newfoundland. In these ecosystems sandeel are intensively preyed upon by more than one hundred predatory species including at least 40 species of birds, 12 species of marine mammals, and 45 species of fish. Six species of sandeel are currently being recognized as key forage species: A. personatus , A. hexapterus , A. americanus , A. dubius , A. tobianus , and A. marinus (the term sandeel is used subsequently when referring to the group of species). For many sandeel-predators inter-annual fluctuations in the availability of sandeel have direct effect on breeding success, growth and
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survival in general (Robards 1999; Furness 2002; Frederiksen et al. 2005; Wanless et al. 2005;
Macleod et al. 2007; Sharples et al. 2009).
Sandeel are different from other typical forage fishes as they spent a considerable proportion of the year buried in sandy bottom habitats where they “overwinter” (I use quotation marks since the overwintering may start as early as mid summer or as is the case in some Japanese populations of A. personatus “overwintering” is restricted to the summer period). Even during the feeding season they will bury during night time and occasionally during parts of the day time as well. They are furthermore highly resident and non-migratory as opposed to many other forage fish species, e.g. herring and capelin (Pedersen et al. 1999; Gauld 1990; McQuinn 1997; Friis-Rødel and Kanneworff
2002; van der Kooij et al. 2008; Christensen et al. 2008). Most scientific data on sandeel concerns the stock of Lesser sandeel, A. marinus, in the North Sea. Second most attention has been given to
A. personatus from Japanese waters, although literature on Lesser sandeel in the North Sea by far outnumbers literature on the Japanese species.
During spring in the central North, when adult herring feed further north, Lesser sandeel A. marinus emerge from the sand to feed, and during this time they constitute, biomass vice, the most abundant of all fish species and become the main target for a large range of predators and the large
North Sea industrial fishery (Fig. 1). In this fishery peak annual catches in the 1980s and 1990s exceeded one million tonnes, which was taken out of a total stock biomass of between 1.5 million and 5 million tonnes (anonymous 2007). In comparison the maximum stock biomass of the North
Sea herring stock peaked in 1963 at just above 2 million tonnes and the Norwegian spring spawning herring stock peaked in 1950 at 16 million tonnes. In a global perspective this makes the North Sea sandeel the seventh largest commercially targeted stock ever reported world wide, and of the six stocks ever reported larger than the North Sea sandeel stock three has collapsed since (Checkley et al. 2010).
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Despite the world wide recognized ecological relevance and success of sandeel they have received relatively little attention globally. Furthermore, the role and implications of their characteristic life- history strategy, in particular the overwintering and burying behaviour, is widely unknown. Even when it comes to the North Sea sandeel stock much scientific work still has to be done, before successful management of the stock can be ensured.
Fig. 1. Time-series of estimated consumption of sandeel in the North Sea by consumer group and industrial catch, 1969-
1999 (million tonnes). (From: Furness 2002)
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2. OBJECTIVES
The main objective of this PhD thesis is to advance our knowledge about the unique life-cycle of sandeel, with a main focus on the North Sea sandeel stock. Particular attention will be paid to critical links between environmental seasonality and annually occurring life-cycle events, as well as to the ecological and life-history strategic aspects of the characteristic burying behaviour of sandeel.
3. LIST OF MANUSCRIPTS
3.1. STUDY-I
Mikael van Deurs, Ralf van Hal, Maciej T. Tomczak, Sigrun H. Jonasdottir, Per Dolmer
(2009) Sandeel ( Ammodytes marinus ) recruitment in relation to density dependence and zooplankton composition ( Status: Accepted for publication in Marine Ecology Progress Series on
February 10 th and published April 17 th 2009 in Vol. 381: 249-258; the paper is included in the thesis with permission from Marine Ecology Progress Series).
Content: This study focuses on population regulating factors acting on the larval Lesser sandeel and post-settled Lesser sandeel in the North Sea. A statistical time-series recruitment model is used to i) test a match/mismatch hypothesis regarding the match between the life-cycle of Lesser sandeel in the central North Sea and the life-cycle of the prevalent prey organism, and ii) improve our
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understanding of the intra-specific competition between last year’s cohort and the newly settled cohort.
3.2. STUDY-II
Mikael van Deurs, Martin Hartvig, John Fleng Steffensen (submitted) Size-dependent reserve depletion of overwintering sandeel (Ammodytes ssp.) in relation to size at maturation
(Status: Submitted to Oikos July 26 th 2010).
Content: In this study focus is on physiological processes and life-history plasticity. It specifically addresses the relationship between the overwintering strategy, the seasonal environment and size at maturation. A simple metabolic model of size-dependent reserve depletion is developed to demonstrate that a threshold size must exist below which overwintering is infeasible.
Parameterization as well as some validation of the model was based on experiments conducted in parallel.
3.3. STUDY-III
Mikael van Deurs, Asbjørn Christensen, Christina Frisk and Henrik Mosegaard (2010)
Overwintering strategy of sandeel ecotypes from an energy/predation trade-off perspective (Status:
Accepted for publication in Marine Ecology Progress Series on August 5 th and published October
14th 2010 in Vol. 416: 201-214; the paper is included in the thesis with permission from Marine
10 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
Ecology Progress Series; the manuscript is included in the thesis with permission from Marine
Ecology Progress Series).
Content: In this study we develop a theoretical individual based framework in which the optimal overwintering behaviour of the individual (or “super individual”) can be found. It is a theoretical analysis of the notion that the overwintering strategy has evolved in order to optimize a trade-off between energy-uptake and predation risk in seasonal environments. Parameterization of the model was based on experiments conducted in parallel.
3.4. STUDY-IV
Mikael van Deurs, Jane W. Behrens, Thomas Warnar, John Fleng Steffensen (draft) Proximate versus ultimate control mechanisms of foraging activity and the role of memory in sandeel schools
(Ammodytes tobianus ) ( Status: Manuscript draft)
Content: This study considers the behaviour of Small sandeel ( A. tobianus ) at the school level with particular focus on the primary factors determining the diel shifts between foraging in the pelagic and retreating to the sand refuge. The entire study was carried out under controlled laboratory conditions.
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4. A GENERAL INTRODUCTION TO SANDEEL IN
THE NORTH SEA
The following species of sandeel are found in the North Sea: Ammodytes marinus , A. tobianus ,
Hyperolpus lanceolatus , Hyperolpus immaculatus , and Gymnammodytes semisquamatus. However, in the North Sea the overall absolute majority are Lesser sandeel Ammodytes marinus . The geographical distribution of Lesser sandeel is closely associated with well-oxygenated bottom substrate consisting of gravel or coarse sand in which they frequently bury at water depths of 20 to
100 meters (Reay 1970). Lesser sandeel make both seasonal and diel shifts between the pelagic feeding arena and being buried in the sand refuge. The seasonal foraging window for adults lasts for only two to four months during spring, with a peak in activity around May, leaving the rest of the year (~8 months) for overwintering. This distinct pattern is reflected in both the fishery and in the gut content of predators (Macer 1966; Winslade 1974c; Harris and Wanless 1991; Reeves 1994;
MacLeod et al. 2007a,b). Juvenile Lesser sandeel have a prolonged feeding period compared to adults and large landings of age-0 (as measured from winter rings in the otoliths) sandeel have been reported as late as in December (Macer 1966; Reeves 1994; Kvist et al. 2001). Sandeel forage in schools on a range of available zooplankton including copepods (Calanus, Pseudocalanus, Temora),
Annelids and Larvacea. Larger fish tend to target larger food items (Macer 1966; Personal observations).
Lesser sandeel rarely exceed lengths of more than 15-20 cm. They are capital breeders (Boulcott and Wright 2008) and spawn during a narrow time window around January 1 st , and onset of gonad
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development (the transition to exogenous vitellogenesis) occurs in July/August, around the time at which foraging activity seizes and overwintering begins (Boulcott and Wright 2008).
Photo: Thomas Warnar
In the southern North Sea 50% mature around age 1 (Macer 1966), while 50% maturity in the northern North Sea occurs around age 2 (Bergstad et al. 2001). The eggs stick to the substrate on the banks, often partly buried. They normally hatch during February and March (Wright and Bailey
1996; Macer, 1965). Following hatching, the larvae enter the pelagic environment and are found in most of the water column (Conway et al. 1997). Metamorphosis occurs around June or around 33 to
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90 days from the time of hatching and at a length of approx. 45 mm (Wright and Bailey. 1996).
Gear avoidance (the ability to escape sampling gear) is evident from the length of only 20 mm
(Jensen et al. 2003). The metamorphosed juveniles settle into the habitats inhabited by the parental stock and juveniles from last year´s cohort (geographically overlapping generations).
Among the factors that are known to affect recruitment of North Sea sandeel is water temperature, abundance of adult calanoid copepods in February (proxy for egg and nauplii abundance in late winter), and a density-dependency driven by the age-1 population (Arnott and Ruxton 2002;
Frederiksen et al. 2006). The density-dependent regulation is reflected in sandeel recruitment data from the North Sea as a negative autocorrelation (a year of large recruitment is followed by a year of low recruitment) and seems to be a stronger regulator of recruitment than the spawning stock biomass by it self (Arnott and Ruxton 2002). The Danish sandeel fishery in the North Sea was established in the 1950s and has been monitored since the beginning of the 1980s by the Danish
Institute of Fisheries Research (today part of DTU-AQUA). There is no consensus about whteher the fishery have harmful effects on the North Sea sandeel stock. In the annual report from the
International Council of the Exploration of the Sea (ICES) it has been stated that sandeel stock fluctuations in the North Sea appears to be determined mostly by natural causes (anonymous 2005), despite annual landings of between 500 thousand and one million tonnes. However, in contrast to this view a recent data analysis suggests that local fishery-driven depletion of fishing grounds is possible (anonymous 2009).
In 2001 the spawning stock biomass dropped, for the first time in the entire assessment time- series, to below the critical reference point B lim (of 430 thousands tonnes) and recruitment to the stock reduced dramatically in size in the subsequent years. Since 2007 the stock has gradually been climbing back up and spawning stock biomass came above B lim again in 2008. However, the well being of the stock is still highly uncertain and fishing mortality have therefore since 2003 been kept
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under strict regulation from ICES. Till this day the cause of this dramatic drop in stock size has remained a mystery.
It was already in the 1990s suggested that the management framework for the North Sea sandeel stock should be completely re-evaluated. In contrast to for example the North Sea Herring stock,
Lesser sandeel show high site fidelity from settlement and onward and demographic differences between distinct geographical bank clusters are evident (Pedersen et al. 1999; Gauld 1990; personal communication with Anna Rindorf). Furthermore, spawning areas presumably coincide with the spatial distribution of adults, and dispersal is only possible during the larval phase (2-3 months), as their eggs are demersal. Drift simulations have revealed that that dispersal distances are relatively short (Proctor et al. 1998; Christensen et al. 2008; Christensen et al. 2009). The characteristic site fidelity, high retention rate, and geographically overlapping generations suggests that a meta- population structure consisting of a number of distinct sub-populations may be a more accurate description of the North Sea stock. The North Sea, despite its relatively small surface area, is characterized by large spatial environmental variation. If the meta-population hypothesis is correct, local sub-populations may be influenced by local environmental conditions, which in this case should be accounted for in the stock assessment. It is therefore also currently being debated whether the North Sea sandeel stock should be considered as one stock, several individual stocks, or a dynamic complex of several temporary stocks. However, as demonstrated by Lewy et al. (2004) such divisions should be made with care, since failing to distinguish between geographical distinct units may very well worsen the assessment performance instead of improving it. Probability- matrices of larval spreading using a bio-physically coupled larval drift-model are the latest developments in terms of these issues and are while I write this thesis being applied to suggest new geographical subdivisions of the North Sea sandeel stock (Fig. 2).
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Fig. 2. Emergent sandeel habitats aggregations in the North Sea, generated with the sac algorithm with a) k=2 clusters, b) k=3 clusters, b) k=4 clusters, and b) k=5 clusters. (From: ICES AGSAN2 REPORT 2009 P. 38)
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5. METHODOLOGICAL CONSIDERATIONS
As I attempted to meet the objective I addressed most of the life-cycle of the North Sea sandeel stock and processes at both the population level, school level, and individual level. I used a multidisciplinary approach, which included statistical time-series correlation analysis (statistical modelling), Individual Based Models (IBMs), field data, physiological experiments and behavioural experiments.
I consider the diversity of applied methods as the strength of this thesis. Statistical modelling (as applied in STUDY-I) is a valuable tool to identify co-variation (or correlations) between time-series of dependent variables (e.g. recruitment) and independent variables (e.g. prey availability and sea temperature). However, statistical models merely provide information about statistical relationships and not about causality. IBMs on the other hand make it possible to address the processes involved
(physiological, ecological, behavioural and evolutionary) and integrate environmental forcing over several months (as in STUDY-II) or over the entire life-span of an individual (as in STUDY-III).
Furthermore, by imposing certain simplifications it is often possible to analyse IBMs conceptually and analytically, which may help to identify generic features and properties of the results (e.g. as in
STUDY-III Appendix 2)
In the present thesis isolated physiological and behavioural processes were quantified in the laboratory using respirometry among other techniques. The experimentally derived physiology aided the parameterisation of the IBMs and thereby raised the level of realism in the IBMs. Lastly, by observing schools of sandeel under controlled laboratory conditions (as in STUDY-IV) hypotheses about behaviour could be tested (Fig. 3). Furthermore, overwintering scenarios simulated in the laboratory provided firm validation of the IBM model in STUDY-II.
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Detailed descriptions of applied methods are available in the four attached manuscripts (STUDY-I through STUDY-IV incl. supplementary material attached to STUDY-III).
Fig. 3. Photos of the tanks used in the behavioural experiments. A more schematic illustration is available in STUDY-
IV.
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6. SUMMARIZING DISCUSSION AND SYNTHESIS
The purpose of the discussion below is to tie the four studies of the present thesis together and tell the coherent story that was not told by the four separate and independent studies attached in this thesis. The discussion will mainly relate to Lesser sandeel in the North Sea, and selected literature is used to build a scientific argumentation and general background for conducting the specific line of research. The more general ecological implications of my results as well as a more specific comparison of specific results with previous findings are available in the four attached manuscripts.
To aid the reader on his/her way through the discussion and synthesis of the four studies the already established knowledge about the life-cycle of Lesser sandeel in the North Sea has been summarized in Fig. 4.
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Fig. 4. Schematic illustration of well established aspects of the life-cycle of Lesser sandeel ( Ammodytes marinus ). Phase
1: Adult sandeel overwinter buried in the sand which presumably provides some protection from predators. The overwintering is only swiftly interrupted during spawning where eggs are deposited on the bottom. Phase 2: Eggs hatch and sandeel larvae enter the pelagic when food is relatively scarce. Phase 3: Adults start feeding during day time on the zooplankton burst fuelled by the spring bloom while burying during the night time. Phase 4: The adults start overwintering. The larvae metamorphose, recruit (as young of the year) to the areas inhabited by adult conspecifics, and feed during day time and bury during night time. Phase 5: Now also the young of the year gradually become less active as they start overwintering.
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6.1. SURVIVAL OF SANDEEL LARVAE AND JUVENILES IN RELATION
TO PREY COMPOSITION AND SIZE-DEPENDENT CAPACITY FOR
OVERWINTERING (STUDY-I AND STUDY-II)
BACKGROUND: Recruitment of newly metamorphosed Lesser sandeel to the fishing grounds in the North Sea (estimated by back-calculations from the proportion of age-1 sandeel in the commercial landings during the subsequent spring) varies considerably from year to year. Arnott and Ruxton (2002) attempted to explain this inter-annual variation in recruitment, by expanding the traditional Ricker recruitment function (Ricker 1954) with the inclusion of the abundance of age-1 sandeel and abundance of stage IV and V calanoid copepods in February as additive explanatory variables. I will in the following sections discuss these findings.
I will first introduce some relevant scientific discoveries, not specifically related to sandeel, before discussing specific aspects of the density-dependent regulation driven by the age-1 population.
After discussing the density-dependent regulation I will move on to a discussion about the effect of copepods in February.
Mass specific rate of energy depletion during winter is a decreasing function of body weight (e.g.
Conover 1992; Schultz and Conover 1997; Schultz and Conover 1999; Kooka et al. 2007), which follows from the fact that small fish at rest consume more energy than large fish at rest per unit weight (Clarke and Johnston 1999). Consequently body size, temperature and the latitudinal gradient of growing season duration are linked to winter mortality in fish, although the source of the winter mortality is less well understood and may very well involve both complete exhaustion of reserves, thermal stress, predation and disease (e.g. Schultz et al. 1998; Munch et al. 2003; Garvey
21 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
et al. 2004; Hurst 2007) . Nevertheless size-selective winter mortality seems to play a major role in shaping energy allocation strategies and behaviour of juvenile fish. Juvenile largemouth bass
Micropterus salmoides and rainbow trout Oncorhynchus mykiss display high risk/high gain foraging behaviour in order to achieve fast growth prior to winter (Schindler 1999; Garvey and Marschall
2003; Biro et al. 2005). It has also been shown that the northern distributional limit for yellow perch
Perca flavescens , Eurasian perch P. fluviatilis , smallmouth bass M. dolomieui , and largemouth bass
M. salmoides are defined by the ability of juveniles to complete a minimum amount of growth during a growing season that shortens toward higher latitudes (Shuter and Post 1990; Fullerton et al.
2000). There is no consensus on whether fish have the ability to hibernate, in the sense that the term is typically applied to frogs and turtles (Ultsch 1989), although comatose-like conditions, impairment of sensory performance, and anaerobic metabolism (the latter only in the crucian carp
Carassius carassius ) have been observed in fish exposed to severe hypoxic environments (e.g.
Nilsson and Renshaw 2004).
So how does this relate to density-dependent regulation of sandeel recruitment? Buried sandeel appears to overwinter in aerobic environments as they suck down oxygenated water from above the sediment surface (Behrens et al. 2007), consequently hypoxia induced comatose during overwintering seems unlikely. We also know that Lesser sandeel after metamorphosis recruit (as they settle from the pelagic), after the main spring bloom, to the areas inhabited by adult conspecifics (Wright and Bailey 1996). During this time the majority of the adult population have started, or are about to start, the overwintering period buried in the sand. The newly recruited sandeel (age-0) therefore completely dominate sandeel catches in late summer (with occasional high abundances of active age-0 sandeel as late as in December) (Macer 1966; Winslade 1974c; Reeves
1994; Kvist et al. 2001). However, numerous observations indicate that age-1 juveniles also display prolonged activity period compared to the adults, although not as long as reported for age-0 sandeel
22 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
(Macer 1966; Reeves 1994; Kvist et al. 2001). It could therefore be hypothesised that in years where age-1 sandeel are highly abundant intra-specific competition for food (among juveniles) leads to slow growth and in turn increased winter mortality among the vulnerable age-0 juveniles; given that i) the availability of suitable prey during the late summer period is a limiting factor and ii) a critical minimum size and reserve level is needed prior to winter to ensure survival. The primary source of the winter mortality may either be starvation or predation; predation if the individuals compensate for slow summer growth by spending additional time foraging on the even sparser winter zooplankton, and starvation if they attempt to overwinter with insufficient reserves.
I will now discuss the second finding presented in Arnott and Ruxton (2002): The effect of Calanus abundance in February. Food availability during early larval stages is essential for successful recruitment (e.g. Noto and Yasuda 1999; Beaugrand et al. 2003). Furthermore, multiple studies support the idea that matches and mismatches in time and space between prey availability and critical periods in the life-history of larval fish is an important cause of inter-annual variation in recruitment (e.g. Cushing 1990; Bollens et al. 1992; Stenseth et al. 2002). So the notion proposed by Arnott and Ruxton (2002), stating that availability of calanoid eggs and early nauplii stages in
February affects sandeel recruitment, seems valid. However, Arnott and Ruxton (2002) use the overall abundance of stage V and VI calanoid copepods in February as a proxy for the abundance of calanoid eggs and early nauplii stages. Hence they do not acknowledge that the calanoid copepod fauna of the North Sea consists of at least two species, the cold water species Calanus finmarchicus and the warm water species C. helgolandicus . Besides from the different temperature preferences those two species also differ in terms of life-cycles and strategies. Spring egg production of C. helgolandicus reaches its maximum in May, whereas egg production by C. finmarchicus peaks in
March (Jónasdóttir et al. 2005). The early C. finmarchicus egg production seems to coincide with
23 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
the hatching of sandeel eggs. Back calculation in larval otoliths has established the hatch date of sandeel in Shetland waters to be between mid February and early April, and early larval stages (<6 mm) of sandeel have been observed in the Continuous Plankton Recorder (CPR) between mid
February and end of March (Wright & Bailey 1996). Consequently, and given that survival of
Lesser sandeel larvae depend on availability of copepod eggs as early as February/March (as indicated by Arnott and Ruxton), it could be hypothesised that climate-driven shifts from a C. finmarchicus -dominated prey community to a C. helgolandicus -dominated prey community create mismatches between prey availability and critical larval stages.
STUDY-I: STUDY-1 was motivated by the recruitment model presented in Arnott and Ruxton
(2002) and the literature discussed above. Various statistical recruitment model formulations were tested. The best model was a multiple linear model of sandeel recruitment accounting for the effect of interactions between age-1 abundances and spawning stock biomass, plus the effect of Calanus finmarchicus stage IV and V in February (used as an index for egg and nauplii abundance). The model performed considerably better than both a traditional Ricker curve (Ricker 1954) and the extended Ricker model presented by Arnott and Ruxton (2002). In addition it was demonstrated that the relationship between the spawning stock biomass and recruitment is decoupled when the age-1 population is large (Fig. 5), which supports the hypothesis that the age-1 population and the age-0 population compete for a limited food resource during the second half of the year. Finally the results supported the hypothesis that C. finmarchicus , and not C. helgolandicus , is essential for survival of sandeel larvae (Fig. 6); which in turn also supports the hypothesis proposed by Arnott and Ruxton (2002) that survival rates during early larval stages depends on availability of copepod eggs and nauplii.
24 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
Fig. 5. Exploring the relationship between spawning stock biomass, SSB (10 6 tonnes age-2+) (square root transformed),
9 and sandeel recruitment, N0 (10 numbers of age-0) (square root transformed), under different scenarios of age-1 sandeel abundances. Data was disaggregated into three data subsets of equal sizes according to the age-1 abundance of the given year. (Subset 1): Less than 145 x 10 9 age-1 individuals. (Subset 2): Between 145 x 10 9 and 275 x 10 9 age-1 individuals. (Subset 3): More than 275 x 10 9 age-1 individuals. The stock recruitment relationship in each subset was analysed using a linear regression analysis. P-values and R 2 for the linear regression are provided. A solid regression line is only provided when the relationship are significant. (Taken from the attached paper written about STUDY-I)
25 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
12 10 in in -3 10 5
8 0
6 -5 of eq. 1b eq. of
February) 4 -10
2 -15
0 -20 Model residuals from a modification residuals from modification a Model Abundance (mean numbers m numbers (mean Abundance 3 8 19 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005
Fig. 6. Exploring the importance of a species specific Calanus index. The histogram (left axis) is C. finmarchicus (dark grey columns) and C. helgolandicus (light grey columns). The line plot (right axis) is models residuals from a modification of eq. 1b (see attached paper for details on the equation) in which FIN feb was replaced by CAL feb . The horizontal broken line is the boundary between negative and positive residuals (1996 is not plotted, see attached paper for details). (Taken from the attached paper written about STUDY-I)
STUDY-II: The purpose of STUDY-II was to provide a mechanistic explanation for the density-dependent recruitment regulation induced by the age-1 population. A simple metabolic model of size-dependent reserve depletion was developed in order to demonstrate that a threshold size must exist below which full overwintering (8 months) and reproduction is infeasible. The model was validated using respirometry, bomb calorimetry and field samples.
The validation supported the assumption that reserve-depletion in overwintering sandeel can accurately be predicted by the model. A comparison between model predictions and field data indicated that only individuals above the critical threshold size reproduce, and below the threshold size individuals compensate by maintaining a level of foraging activity during winter.
26 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
Last but not least it was demonstrated that environmentally determined variation in threshold size may explain geographical variation in maturation-size of Lesser sandeel in the North Sea
(Fig. 7). These results support the hypothesis that reduced growth caused by intra-specific competition very well may affect the probability of surviving the winter. However, whether the source of winter mortality is due to winter predation or winter starvation remains unknown.
This is to my knowledge the first study to develop and validate a quantitative species specific model for predictions of size-dependent energy depletion during long periods of starvation. It is also to my knowledge the first study to specifically relate size-dependent and temperature- dependent energy expenditure to maturation-size in fish, although Downhower (1976) showed based on similar bioenergetic considerations that duration of the winter period should affect size at first reproduction in temperate non-migrating bird species, such as finches.
14
13
12
11
10
Maturation sizeMaturation [cm] 9
8 8,2 8,7 9,2 9,7 Threshold size [cm]
Fig. 7. Sandeel maturity data from Boulcott et al. (2007) plotted against predicted threshold size. Sizes at which
5% (triangles) and 50% (circles) were mature in Firth of Forth (small maturation-size), Dogger bank (medium
maturation-size) and Fisker bank (large maturation-size) plotted against threshold size calculated specifically for
each location (circles). Dotted and dashed lines are regression lines. The solid line represents a relationship of
1:1 between maturation-size and threshold size. (Taken from the attached STUDY-II manuscript)
27 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
6.2. ADAPTIVE BEHAVIOUR AND OVERWINTERING OF ADULT
SANDEEL (STUDY-III)
BACKGROUND: So far the main focus of the discussion has been on the early life stages of
Lesser sandeel (larvae and juveniles). It was established that the decision to overwinter or to prolong the active period is determined by physiological constraints until a critical threshold size has been reached. In STUDY-II an important assumption was that the overwintering strategy becomes an optimal strategy as soon as the threshold size has been reached, and that a full overwintering conforms to 8 months. However, it could be speculated that when sandeel are freed from the physiological constraints of overwintering (as when they reach the critical threshold size) the timing of the overwintering period and the associated foraging window may instead become a trade-off (on an annual time-scale) between energy uptake and risk of predation.
In the following section I will again start by providing a more general background before returning to sandeel-related issues.
On the macro-evolutionary level natural selection has resulted in a variety of different life-history strategies and foraging behaviours among species and groups of species. However at the species level, and even at the level of the individual, plasticity in life-history and behavioural traits may also be evident. Such behavioural plasticity can be a result of adaptations to local environmental conditions driven by natural selection of genotypes in the population (adaptations at the population level) or it can be a result of variation in phenotypic expressions of a common genotype (phenotypic plasticity; adaptations early in the life-history at the level of the individual) (e.g. Via and Lande
1985; Kawecki and Ebert 2004). In contrast when the individual perceives its surroundings,
28 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
processes the information, and acts accordingly, we often use the term “adaptive decision-making”
(e.g. Lima 1998), although the term phenotypic plasticity is also some times used in this context.
In a simple case an optimal strategy may simply be the behaviour that maximizes net energy gain.
However, many organisms face high mortality rates (for example forage fishes), and therefore many individuals will not live long enough to reproduce. Making trade-offs that maximize the energy gain relative to the probability of being eaten then becomes an element in the measure of reproductive success that is of equal importance to rate maximization. The evolutionary rationale behind this was clearly expressed in Lima (1998): “Natural selection should act to produce animals that can somehow arrive at an appropriate trade-off between the benefits of energy intake and the cost (in terms of Darwinian fitness) of an early death due to predation”. This is often referred to as the foraging predation trade-off or the energy/predation trade-off (I will here use the latter term).
Hence the point is that if we want to fully understand how environmental variation affects fish populations, we need to understand how the individual fish react to a given change in mortality or feeding condition (this is also in life-history sciences referred to as the reaction norms, which are defined as adaptive responses to variable environments). Sih (1980) provided one of the very first studies that experimentally documented the energy/predation trade-off at the behavioural level. In this study it was shown how backswimmers ( Notonecta hoffmanni ) balanced the conflicting demands of feeding vs. avoiding predation. The discovery of the importance of the energy/predation trade-off (e.g. Sih 1980; Mittelbach 1981; Werner et al. 1983) soon led to a bloom of research. A growing amount of studies have demonstrated how the energy/predation trade-off has impact at the population and ecosystem level through various pathways (e.g. Lima 1998; Werner and Anholt
1993), for example: Sub-optimal growth (Mangel and Stamps 2001; Biro et al. 2007), temporal and spatial variation in distribution of prey organisms and their predators (Biro et al. 2003a,b; Dill et al.
2003; Schmitz et al. 2008), and climate change induced compensatory foraging activity (Dill et al.
29 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
2003; Biro et al. 2007). In particular the line of studies by Peter Biro and colleagues (e.g. Biro et al.
2003a,b; Biro et al. 2005; Biro et al. 2007) have played a major role in emperically documenting the energy/predation trade-off. These studies were all conducted with trout populations
(Onchorhynchus mykiss ) in large ponds and the outcomes therefore provided novel information about the effect of the energy/predation trade-off at the population level. They for example showed how varying risk of cannibalism and food availability affected the willingness of juveniles to appear in the more productive pelagic areas. Consequently growth rates were found to be equal among high and low productive lakes as fish in high productive lakes reduced the time spent on foraging, but the mortality was much higher in low productive lakes.
Lastly, I should mention that also a long line of entirely theoretical studies have addressed the energy/predation trade-off, however, the details of those are to extensive to be presented here (e.g.
Houston and McNamara 1999)
STUDY-III: With a few exceptions (e.g. Brönmark et al. 2008) the majority of previous studies of the energy/predation trade-off in fish, and animals in general, have focused on short-term processes (daily or hourly time-scales), such as diel vertical migration, ontogenetic or state- dependent diurnal decisions regarding habitat choice and foraging activity (e.g. Lima and Dill 1990;
Houston et al. 1993; Burrows 1994; Railsback et al. 1999; Biro et al. 2003; Biro et al. 2006).
However, in STUDY-III we adopted the concepts of the energy/predation trade-off and developed a model framework for adult Lesser sandeel (sandeel well above the critical threshold size) in order to demonstrate that the optimal timing of the overwintering period involves a trade-off, on an annual time-scale, between energy gain and predation mortality. In this model framework the individual was allowed to make two annual decisions, when to end overwintering and when to start
30 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
overwintering, which combined comprised the timing of the foraging window. Physiological components of the model were based on results from own laboratory experiments.
An important finding was that the precise level of mortality and energy gain rates has little influence on the duration of the foraging window, as long as the overwintering refuge provides considerable protection from predation and the spring burst of zooplankton is a well defined swift transient event. However, this does not imply that predation mortality does not influence the behaviour of sandeel. On the contrary, the cost of predation related to foraging activity is what resulted in the prediction that all foraging activity should strictly coincide with the advanced stages of the zooplankton spring burst; otherwise fitness will be considerably reduced. In turn this suggests that inter-annual variation in spring bloom timing could cause the size of succeeding year-classes and spawning stock size to fluctuate. The potential mismatch effect on fitness was predicted to be stronger in populations that experience swift spring blooms and low food availability (consequently, populations will also be most vulnerable to fishing pressure under these conditions). In contrast when spring bloom lasts longer and food is in excess for several months, timing of foraging activity is less important, and mechanisms related to temperature-dependent physiology or predation takes over. Last but not least, we showed for adult sandeel that the overwintering strategy remains the optimal strategy; even in scenarios where winter prey abundances lead to a daily consumption of one third of the consumption during the spring burst of zooplankton. Winslade (1974c) presented data of monthly prey availability, sea temperature and commercial sandeel landings from before the
North Sea sandeel fishery became strictly regulated by seasonal constraints and quotas. When these environmental data were used in the model the predicted foraging window enveloped 70% of the sandeel landings (Fig. 8).
Based on these results I suggest that the energy/predation trade-off in relation to the overwintering behaviour may have played a key-role in causing the observed temporal and geographical variation
31 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
in size-composition of sandeel in commercial landings, as well as the reported demographic differences among sub-regions (e.g. Reeves 1994; Kvist et al. 2001; Macer 1966; Personal communication with Lotte Worsøe Clausen).
Fig. 8. The onset and offset (vertical grey lines) of the optimal foraging window compared to monthly North Sea sandeel catches from before the fishery became strictly regulated. Catch data (black solid line; in percentage of total annual catch), temperature (grey solid) and copepod index (dashed line; number of copepods per sample) presented in
Winslade (1974c) was used to force the model. Before using the copepod index in the model values were raised so that peak abundance in June corresponded to a daily total prey encounter of 700. Annual survival probability was 50 %, which resembles the mortality applied by ICES for adults sandeel. (Taken from the attached STUDY-III manuscript)
6.3 SCHOOL BEHAVIOUR STUDIED IN THE LABORATORY (STUDY-IV)
BACKGROUND: STUDY-III raised a number of questions related to foraging activity: What are the mechanisms involved in triggering the transition between the overwintering period and the
32 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
foraging period of Lesser sandeel. Do Lesser sandeel sense prey from their refuge in the sand by use of olfaction, as suggested in Winslade (1974b)? Or is foraging activity simply, as suggested in
Winslade (1974a,c), driven by seasonal gradients in temperature and light? Other questions raised in STUDY-III concern the extent of the daily foraging period: Do sandeel forage until full gut? If so, how do they deal with intra-school variation in gut-fullness? And should we then expect that they forage all day, at the expense of predation mortality, if prey are scarce and guts never fill up?
STUDY-IV: In STUDY-IV, I attempted to provide answers to some of these essential questions by keeping whole schools of sandeel ( A. tobianus ) in the laboratory under controlled abiotic and biotic conditions. The main findings were that the duration of the daily foraging period (from school integration in the morning to school disintegration in the afternoon) was significantly prolonged on days where fish were given a single ration opposed to being starved, and when fish were deprived from food for more than three days, the duration of the daily foraging period gradually shortened and the school size was reduced. It was also found that the duration of the daily foraging period increased with increasing daily ration-size. These results in combination with additional clarifying experiments (see the attached manuscript on STUDY-IV) finally resulted in three hypotheses concerning the foraging behaviour of sandeel:
1) An endogenous substance closely related to gut-fullness in combination with the dark/light transition, and “memory” of past days feeding history are major proximate factors in the regulation of foraging activity at the level of the school.
2) Sporadic explorative excursions from the sand refuge to the pelagic play an essential role in gaining information about foraging conditions and in deciding on whether to overwinter or forage.
3) Complicated consensus decision making at the level of the school may be explained by a few simple proximate mechanisms, and without inclusion of complicated machinery to perceive
33 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
environmental variables such as gradients in light-intensity, temperature and prey concentrations in the surrounding water.
7. CONCLUSIONS AND PERSPECTIVES
Results obtained in the present PhD thesis suggested that the copepod species-composition during the early larval phase of Lesser sandeel affects recruitment, and that the spawning stock-recruitment relationship is de-coupled in years associated with large densities of age-1 individuals (STUDY-I).
As a possible explanation for the density-dependency I demonstrate that juveniles failing to reach a critical threshold size (and full reserve capacity) before fall may suffer from starvation mortality or elevated predation mortality resulting from compensatory feeding activity during fall/winter
(STUDY-II). The critical threshold size depends on water temperature and duration of the overwintering period. I therefore demonstrate how the optimal duration of the overwintering period theoretically can be predicted from information about predation mortality and seasonal fluctuations in availability of suitable prey items (STUDY-III). I also demonstrate how geographical and inter- annual variation in winter temperature and timing of the spring burst of zooplankton at least theoretically affect population parameters such as size at maturation, fecundity and mortality
(STUDY-II & STUDY-III). However, exactly how a given change in environmental conditions affects population parameters depends on whether the individual or population have managed to adapt successfully to the given change (STUDY-II & STUDY-III). As an extension of the above mentioned findings I therefore also provide indications from experiments that foraging activity at the level of the school increases if food uptake increases and vice versa (STUDY-IV). A single
34 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
main message of this work is that neglecting the importance of the overwintering phenomenon and seasonality in the environment may lead to failure in understanding population fluctuations of not only sandeel but possibly forage fish populations in seasonal environments in general.
While the lethal aspects of predator-prey interactions and its implications for population dynamics and ecosystems in general are indisputable and relatively well understood, the implications and quantitative importance of adaptations induced by predator-prey interactions are still poorly understood (Lima and Dill 1990; Lima 1998; Dill et al. 2003). I believe that some of the model frameworks presented in the attached manuscripts offer analytical tools to interpret observations and formulate testable hypotheses regarding these issues, especially in relation to the overwintering strategy, which so far has been largely neglected in the research field of fish ecology and evolution as well as in the field of fishery biology.
Climatic variability (spatial, inter-annual or long term trends) have considerable effects on ecosystems and population dynamics (e.g. Walther et al. 2002; Alheit and Bakun 2010; Alheit et al.
2010; Finney et al. 2010; Overland et al. 2010). However, the effects may be indirect as higher trophic levels respond to fluctuations in populations of forage fishes, which again respond to climate induced changes in the zooplankton community and so on. As shown in this thesis climate- induced effects on forage fish populations are very likely to be mediated by changes in the zooplankton species composition and timing/duration of the main zooplankton bursts. These findings are particular relevant since regional changes in Calanus species composition within the
North Sea have been observed during the last decades as a result of recent climate changes
(Beaugrand 2004). Predictions indicate that these changes will persist or even increase
(Intergovernmental Panel of Climate Change (IPCC) 2007). Furthermore, it is also well documented
35 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
that the timing of the spring bloom exhibits both regional differences, inter-annual fluctuations and climate induced long-term shifts within ecosystems populated by sandeel (e.g. Brander 1994;
Edwards and Richardson 2004; Greenstreet et al. 2006; Sharples et al. 2006; Eliasen et al. 2009).
Understanding how sandeels cope with this variability therefore seems an essential prerequisite for understanding population dynamics of this widespread fish that is both commercially important and a key prey to numerous piscivorous organisms. I therefore propose that the results and models presented here can play a role in this context, and should be carefully considered during any action taken in the future toward managing the North Sea sandeel stock as several more or less geographical distinct and independent sub-populations.
A single main message of the work presented in this thesis is: Neglecting the importance of the overwintering phenomenon and seasonality in the environment may lead to failure in understanding population fluctuations of not only sandeel but possibly forage fish populations in seasonal environments in general.
8. FUTURE RESEARCH INITIATIVES
A major challenge on the path to improvement of the North Sea sandeel assessment is the interpretation of catch rate data. The main problem is that the number of sandeel available to conventional fishing gear relative to numbers of buried sandeel presumably changes over the day and season (Fig. 9) (e.g. Greenstreet et al. 2010). Hopefully the present results can help us understand and quantify the temporal and spatial patterns of numbers of sandeel in the pelagic
36 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
relative to numbers of buried sandeel. Already now it is possible to say, based on the presented results, that sandeel catch-data from early in the day and when guts are relatively full (indicating good foraging conditions and abundant prey items) are more likely to reflect the true abundance of sandeel, since fewer sandeel will be buried.
16 14 12 10 8
CPUE 6 4 2 0 May1 May4 May5 Apr12 Apr13 Apr14 Apr15 Apr15 Apr16 Apr16 Apr16 Apr17 Apr17 Apr17 Apr18 Apr19 Apr20 Apr22 Apr22 Apr23 Apr24 Apr24 Apr27 May15 May15 May29 May30
Fig. 9. Catch per unit effort (CPUE) per tow per day on a small sandeel fishing ground on the northern edge of Dogger bank in the North Sea in 2006. Note the large variability in CPUE from day to day and even within the same day.
Even though I demonstrate that each model is capable of describing or capturing general patterns in the North Sea, the modeling parts of the present thesis was mainly focused on achieving a fundamental understanding of the processes. Consequently, much more critical and scrutinizing validations should be carried out to fully understand the predictive capabilities and limitations of the models before any application to the North Sea sandeel stock is carried out. I therefore plan to combine the models in a North Sea sandeel fishery model designed to capture the geographical, seasonal and inter-annual patterns of growth rates, catch rates and landings, which have been reported in numerous publications and are evident in the long spatially resolved North Sea time- series of sandeel landing data (Pedersen et al. 1999; Bergstad et al. 2001; Bergstad et al. 2002;
Lewy et al. 2004; Greenstreet et al. 2006; Boulcott et al. 2007).
37 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
Before building a fishery-model there are still a few gaps that need to be bridged. Firstly, we are in short of knowledge about how seasonal patterns in zooplankton abundance, species composition and nutritional quality translate into seasonal patterns in energy uptake and growth of the forage fishes. Secondly, STUDY-II and STUDY-III build on the assumption that sandeel is truly iteroparous (has multiple reproductive cycles over the course of its lifetime) as opposed to semelparous which for example seems to be the case for Capelin ( Mallotus villosus ), an arctic forage fish (Friis-Rødel and Per Kanneworff 2002; Christiansen et al. 2008). Thirdly, optimal patterns of energy allocation (between growth, reserves and gonads) as a function of size and condition should be given more attention; as such issues very well may constitute an important piece of the life-history puzzle.
In order to bridge those gaps, I have initiated work with the modelling group of Professor Øyvind
Fiksen at the University of Bergen, Norway. In this work we apply an optimization modelling framework developed in the 1980s and 1990s (e.g. Houston and McNamara 1999; Clark and
Mangel 2000) and later adapted and applied by the modelling group of Professor Øyvind Fiksen for a wide range of optimality problems related to zooplankton and fish. What is unique about this model framework is that patterns of behavioural decisions and life strategies (e.g. energy allocation or maturation) are emergent properties of the model and determined by the state of the organisms
(e.g. size, energy reserves, gut fullness).
38 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
CITED LITERATURE
Alheit, J., Drinkwater, K. F. and Perry, R. I. 2010. Introduction to the workshop on impact of climate variability on marine ecosystems: A comparative approach Preface. - Journal of Marine Systems 79: 227-229.
Alheit, J. and Bakun, A. 2010. Population synchronies within and between ocean basins: Apparent teleconnections and implications as to physical-biological linkage mechanisms. - Journal of Marine Systems 79: 267-285. anonymous. 2005. Section 13: Sandeel. ICES ACFM Report. 582-662. anonymous. 2007. Working Group on the Assessment of Demersal Stocks in the North Sea and Skagerrak. anonymous. 2009. ICES AGSAN2 Report. 13-14.
Arnott, S. A. and Ruxton, G. D. 2002. Sandeel recruitment in the North Sea: demographic, climatic and trophic effects. - Marine Ecology-Progress Series 238: 199-210.
Baumann, H., Peck, M. A., Gotze, H. E. and Temming, A. 2007. Starving early juvenile sprat Sprattus sprattus (L.) in western Baltic coastal waters: evidence from combined field and laboratory observations in August and September 2003. - Journal of Fish Biology 70: 853-866.
Beaugrand, G. 2004. Long-term changes in copepod abundance and diversity in the north-east Atlantic in relation to fluctuations in the hydroclimatic envionment. - Fisheries Oceanography 12: 270-283.
Behrens, J. W., Praebel, K. and Steffensen, J. F. 2006. Swimming energetics of the Barents Sea capelin (Mallotus villosus) during the spawning migration period. - Journal of Experimental Marine Biology and Ecology 331: 208-216.
Behrens, J. W., Stahl, H. J., Steffensen, J. F. and Glud, R. N. 2007. Oxygen dynamics around buried lesser sandeels Ammodytes tobianus (Linnaeus 1785): mode of ventilation and oxygen requirements. - Journal of Experimental Biology 210: 1006-1014.
Bergstad, O. A., Hoines, A. S. and Kruger-Johnsen, E. M. 2001. Spawning time, age and size at maturity, and fecundity of sandeel, Ammodytes marinus, in the north-eastern North Sea and in unfished coastal waters off Norway. - Aquatic Living Resources 14: 293-301.
Bergstad, O. A., Hoines, A. S. and Jorgensen, T. 2002. Growth of sandeel, Ammodytes marinus, in the northern North Sea and Norwegian coastal waters. - Fisheries Research 56: 9-23.
Biro, P. A., Post, J. R. and Parkinson, E. A. 2003. From individuals to populations: Prey fish risk-taking mediates mortality in whole-system experiments. - Ecology 84: 2419-2431.
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44 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
45 PhD Thesis The Life-cycle of Sandeel Mikael van Deurs
46 MANUSCRIPT I
Status: Accepted for publication in Marine Ecology Progress Series
February 10 and published April 17 th 2009 in Vol. 381: 249-258; the paper is included in the thesis with permission from Marine Ecology Progress
Series
MANUSCRIPT II
Status: Submitted to Oikos July 26 th
Title: Size-dependent reserve depletion of overwintering sandeel (Ammodytes ssp.) in relation to size at maturation
Authors: Mikael van Deurs 1,3,4 , Martin Hartvig 2, John Fleng Steffensen 3
1National Institute of Aquatic Resources, Technical University of Denmark, Jægersborg Alle
1, Charlottenlund Castle, 2920 Charlottenlund, Denmark.
2Department of Theoretical Ecology, Lund University, Ecology Building, SE-223 62 Lund,
Sweeden.
3Marine Biological Laboratory, University of Copenhagen, Strandpromenaden 5,
3000 Helsingør, Denmark.
4Corresponding author: [email protected]
1 Abstract: Mass specific standard metabolism decrease with increasing body weight and decreasing temperature. Winter-mortality in fish therefore relates to body size, water temperature and winter duration. Very few studies have addressed these relationships from a life history perspective. We hypothesised that a critical threshold size must exist below which overwintering and maturation is infeasible and winter feeding activity required for survival. In order to test this hypothesis we developed and validated a simple metabolic model of size- dependent reserve depletion in sandeel (Ammodytes ssp.). The model was parameterized using data from the literature and respirometry, and was validated in a laboratory experiment. With this model we predicted the size-dependent energetic cost of overwintering and the critical threshold size. We there-after showed that observed reduction in total body energy of sandeel, during winter in the North Sea, increased with size and equalled predicted energetic cost of overwintering for sizes near the critical threshold size. Field data from the North Sea also confirmed that maturation starts to take place just after the critical threshold size has been reached. Lastly, we demonstrated that environmentally determined variation in threshold size may explain intra-species variation in maturation size.
2 INTRODUCTION
In high latitude regions planktivorous fish experience strong seasonal fluctuations in food availability and must often rely on transient elevations in zooplankton productions. In general the most important annually reoccurring peak in zooplankton production occurs in spring, fuelled by the primary production. This highly variable feeding regime often results in long periods of starvation and restricts growth and reproduction to short time windows of the annual cycle (e.g. Winder and Schindler 2004; Varpe and Fiksen 2010). To cope with the harsh conditions many high latitude fish species built up energy reserves prior to winter (e.g.
Hislop et al. 1991; Schultz and Conover 1997). Some species appear to generate enough reserves prior to winter to fully support both maintenance metabolism and gonad development during winter (e.g. Winslade 1974; Ultsch 1989; Huse and Ona 1996; Paul and Paul 1998;
Schultz and Conover 1997; Varpe and Fiksen 2010), and presumably overwinter without feeding in a state of low activity and at low risk of predation; a strategy which is expected to optimize the trade-off between energy uptake and predation risk on an annual time-scale (for the remaining of this text “overwintering” refers to this definition).
Mass specific rate of energy depletion during winter is a decreasing function of body weight
(e.g. Conover 1992; Schultz and Conover 1997; Schultz and Conover 1999; Kooka et al.
2007), which follows from the fact that small fish at rest consume more energy than large fish at rest per weight unit (Clarke and Johnston 1999). It is also well documented that body size, temperature and the latitudinal gradient of growing season duration are directly linked to winter mortality in fish, although the actual source of mortality may involve both complete exhaustion of reserves, thermal stress, predation and disease (e.g. Schultz et al. 1998; Munch et al. 2003; Garvey et al. 2004; Hurst 2007) . Size-dependent winter mortality is therefore
3 expected to be a key selective agent (e.g. Conover and Present 1990; Conover 1992).
However, studies attempting to shed light on how these patterns affects life history traits are scarce, and have so far mainly been concerned with growth patterns, energy allocation- strategies and scheduling of the spawning season (Schultz and Conover 1997; Schultz et al.
1998; Schindler 1999; Garvey and Marschall 2003; Munch et al. 2003). A major hindrance to accurate quantitative species specific predictions are related to lack of robust knowledge about the routine metabolism of overwintering individuals over an ecolological relevant time scale (months). Measurements of metabolic rate have typically been conducted by fish physiologists in respirometers where the time scales are of hours or days. However, it has been debated whether this methodology is adequate when it comes to estimating energy expenditure during prolonged periods of starvation (e.g. Schultz and Conover 1999).
Motivated by the simple physiological fact that mass specific resting metabolism decrease with increasing size, we hypothesize that a threshold size ( Lth ) exists where the energetic cost of overwintering equals reserve capacity. Below Lth we expect that a full scale overwintering is impossible or infeasible and a prolonged feeding period required. Furthermore, in the case of iteroparous species that develop gonads during the overwintering period size at maturation should be larger than Lth since only above Lth is investment in reproduction in parallel with a full scale overwintering possible. This hypothesis can be formulated in a conceptual model as illustrated in Fig. 1.
Sandeel (e.g. Small sandeel Ammodytes tobianus and Lesser sandeel A. marinus ) overwinter buried in sandy bottom habitats. Catch data for Lesser sandeel ( A. marinus ) indicate that overwintering in the North Sea takes place between August and April (8 months) (Winslade
4 1974; Wright et al. 2000; Høines and Bergstad 2001). The overwintering period is only interrupted by a capital spawning event in December/January (Macer 1966; Bergstad et al.
2001). When sandeel emerge during spring to feed, they become biomass vise the most abundant of all fish in the coastal and central regions of the North Sea and the main target for a large range of predators and a large North Sea industrial fishery. Allocation of energy to gonad development is initiated around transition between the growing season and the overwintering period (Boulcott and Wright 2008). Sandeel are in general non-migratory, highly residential, produce demersal eggs, and display relatively high larval retention rates
(Christensen et al. 2008). These features are expected to promote local adaptations and make it possible to sample the same pool of fish multiple times over the course of the year.
Considerable geographical variation in size and age at maturation has been reported for Lesser sandeel in the North Sea (Boulcott et al. 2007). The typical age and size at maturity reaction norm finds that organisms mature earlier and at a larger size as growth conditions improve
(Stearns 1992). However, this reaction norm fails to explain the observed variation in size at maturation of Lesser sandeel presented by Boulcott et al. (2007).
The aim of the present study was therefore to evaluate the conceptual model illustrated in Fig.
1 in relation to sandeel ecotypes. In order to achieve this we formulated a simple model of routine metabolism of overwintering sandeel. Owing to the winter burying behaviour of sandeel we hypothesised that routine metabolism is more or less constant over time
(unaffected by changes in activity) and resembles standard metabolic rate ( SMR ) as estimated from respirometry. We tested this critical assumption in a laboratory based overwintering experiment. Next we compared: i) reserve capacity (as a function of size), ii) model predictions of the energetic cost of overwintering (as a function of size), iii) observed changes
5 in energy content of various size-classes of Lesser sandeel in the central North Sea during winter, and iv) observed maturation probability for Lesser sandeel in the central North Sea (as a function of size). This comparison allowed us to approximate Lth and evaluate the conceptual model illustrated in Fig. 1. Lastly, we approximated Lth specifically for three geographically distinct locations on which size at maturation was studied by Boulcott et al.
(2007).
MATERIALS AND METHODS
Model : If the gross rate of reserve-depletion [J ind -1 h -1] during overwintering (reproductive investment excluded) is equal to the standard metabolic rate [J ind -1 h -1] as measured in a respirometer we can write:
= = n Gross rate of reserve-depletion during overwintering SMR (w,T ) S0w f (T ) (1)
where w is fish wet weight [g], n is the size scaling exponent of metabolism and was here set to 0.8 (Clark and Johnston 1999), and f(T) the SMR temperature dependency. The prefactor
= 1−n S0 we , where we is the mean wet weight of fish used in the respirometry experiments.
6 From this we can calculate the energetic cost of any individual [J ind -1] during any overwintering period 0 to time t:
t / ∆t ∆ ∆ = − ∆τ E t,( Tt ; t, w0 ) ∑ SMR (wt ,Tt ) (2) t=0
o where Tt is the temperature [ C] at time indices t, ∆τ is the size of step t in hours (for the present model simulations we used 24 hour time steps), and w0 the weight of the sandeel at t =
0 [g]. The weight at any time step can be calculated from the previous time step as:
τ = w0 for 0 wτ = (3) − −1 ∆ wτ −1 EC SMR (wτ −1,Tτ −1 ) t else
-1 where EC is the energy density of reserves [J g wet weight]. EC was in the present study
= ∆ ∆ ∆ ∆ approximated from EC ( E / wdry /() w / wdry ) using before and after measurements of total body energy and fish weights from the overwintering experiment described below.
Respirometry: Metabolic rate as a function of temperature, f(T), was measured as oxygen
-1 -1 consumption [mg O 2 g h ] using closed circuit respirometry (e.g. Behrens and Steffensen
2007). Oxygen consumption was subsequently translated into rate of energy expenditure [J g -1 h -
1 -1 ] using a general oxycaloric coefficient of 14 J mg O 2 (Brett 1973). Specimens (mean weight =
4.7 g, SD = 0.68) of Small sandeel were caught by seine and held in 1660 l circular holding tanks with fully oxygenated and recirculated seawater of 10 oC for ~6 months prior to measurements. The respirometry chamber (water volume = 6.48 l) contained rinsed and burned
(450 oC for 6 hours) sand distributed over the bottom for the sandeel to bury in. During each trial
7 ten sandeel (unfed for ~ 72 h prior to each trial) were selected randomly from the holding tanks and placed in the respirometry chamber, which immediately after was left in darkness. The measuring period (five days) consisted of alternating time intervals of twenty minutes flushing with oxygen saturated water and two hours closed circuit. By the end of the measuring period fish were carefully removed and background oxygen consumption was measured. The mean oxygen consumption measured during the last three closed time-intervals represented one data point. Measurements during all other closed time-intervals were used to validate that oxygen consumption had reached a stable level. The entire experiment consisted of twelve trials conducted at various temperatures ranging from 5.3 to 18.3 oC. Fish were acclimatized in the holding tank for at least one week after each temperature change (a change in temperature between trials was never more than 5 oC).
Maximum reserve capacity and weight prior to overwintering: Reserve capacity is defined as the maximum pool of energy that can be mobilized, and energy in the reserves plus energy of the structural mass equals total body energy. Total body energy of Lesser sandeel in the North Sea finds a maximum in August and a minimum in April, and the mean proportional difference (for sizes between 7 and 15 cm) in total body energy between August and April is 47% (Hislop et al. 1991). Based on this we calculated maximum reserve capacity prior to overwintering ( Rmax ), as 47% of the total body energy in August (it is assumed that reserve size is a fixed proportion of fish volume). From table 2 in Hislop et al. (1991) we find that total body energy in August [J ind -1] = 4.1 · {total fish length[cm]} 3.66 . The corresponding
-4 wet weight [g] prior to winter was calculated as wmax = 1 · 10 · {total body energy in
August} + 0.3 based on data from appendix 1 and table 2 in Hislop et al. (1991).
8 Overwintering experiments in the laboratory : Two separate overwintering experiments were conducted in the laboratory with Small sandeel (VAL-1 and VAL-2). In these experiments fish remained buried and inactive (not foraging) for 131 and 298 days respectively before the experiments were terminated. VAL-1 was carried out at 10 oC in three
2.5 l buckets with five young sandeel in each (mean fish wet weight 1.37 g, SD = 0.18).
Buckets were regularly inspected to ensure fish remained buried and inactive. VAL-2 was carried out with older and larger sandeel (mean fish wet weight 4.06 g, SD = 0.58) in a video- monitored 1600 l tank and varying temperature regime (100 days of 5 oC, 14 days of 14 oC and
184 days of 10 oC). Sub-samples of fish were frozen and stored at -80 oC before and after each experiment. After measuring length, wet weight and dry weight (drying at 60 oC till constant mass) total body energy was determined by bomb calorimetry in an IKA C-7000 bomb calorimeter. There were no signs of spawning or even developing gonads in any of the fish.
Field observations: The proportion of mature sandeel on the main North Sea fishing areas was determined based on 1763 Lesser sandeel sampled in December 2006 and 2007 (between
December 5 and 17) from various sampling stations between 0 oE – 8 oE and 54 oN – 58 oN.
Sampling was carried out with a modified scallop dredge (catching only buried sandeel) as part of a routine sampling program under the Danish Institute of Aquatic Resources. During the same survey another 728 sandeel were sampled from six of the stations (also between 0 oE
– 8 oE and 54 oN – 58 oN). Those six stations were revisited in February 2007 and 2008
(between February 12 and February 20). Each time a station was visited a sub-sample of fifty sandeel (or all, if < 50 sandeel were caught) distributed equally over half-centimetre groups was analyzed with respect to length [cm] (measured to nearest mm), age (based on number of winter-ring in otoliths), weight [g] (both wet weight and dry weight; dried at 60oC till constant
9 mass). Dry weight was translated into total body energy based on a linear regression model fitted to the bomb calorimetry data from the overwintering experiments above. Data were divided into December samples and February samples. Data were there-after divided into seven size classes, 6.5 (6-7 cm), 7.5 (7-8 cm), 8.5 (8-9 cm), 9.5 (9-10 cm), 10.5 (10-11 cm),
12.5 (11-14 cm), and 15.5 (14-17 cm). Mean total body energy and mean wet weight was derived from simple linear regression analyses made for each size class and sampling month.
Lastly, the observed change in energy (∆Eobs(field) ) were calculated for each size class as the difference in mean total body energy between December and February.
Sea bottom temperature: North Sea bottom temperature profiles for Firth of Forth, Dogger bank and Fisker bank (Corresponding to study locations in Boulcott et al. 2007) were taken from the NORWECOM model (Skogen et al. 1995). Dogger bank and Fisker bank are important areas to the central North Sea sandeel fishery, while a sandeel fishing closure was established in the Firth of Forth (off the SE Scottish coast) area in 2000. Temperatures are monthly, 2000-2007, mean values over rectangular boxes (0.25 lat, 0.5 long) (Fig. 2).
RESULTS
Parameterization and validation of model
From the respirometry experiment we got that f(T) = 0.08 T – 0.25 (r 2 = 0.92). A
2 . semilogoritmic fit to data performed less well (r = 0.87) (Fig. 3). EC was estimated to 8.6
10 3 10 . This estimate of EC was a mean between large fish (from the overwintering experiment
. 3 . 3 VAL-2) with EC = 9.1 10 and small fish (VAL-1) with EC = 8.2 10 (the difference between small and large fish was due to a smaller ∆w/∆wdry for the large fish). With this parameterisation we used Eq. 2 and predicted ∆E for the overwintering experiments, VAL-1 and VAL-2, and compared predictions to the observed change in total body energy. ∆E deviated from observed values by only 6% and 0.7% in VAL-1 and VAL-2 respectively
(Table 1).
Evaluating the conceptual model in Fig. 1
The energetic cost of overwintering from August to April ( ∆E8months ) in the central North Sea fishing areas was calculated for each size class (6.5, 7.5, 8.5, 9.5, 10.5, 12.5, and 15.5 cm) using Eq. 2. As input to Eq. 2 we used ∆t = 242 and a temperature profile, T(t), calculated as the mean between the profile at Dogger bank and the profile at Fisker bank. We also calculated the energetic cost of overwintering between December 11 and February 16
(∆E2months ) (input to Eq. 2: ∆t = 66, w0 = weights observed in the December samples, and T(t)
= same as used for the above calculations of ∆E8months ). An overview of the results of those calculations are presented in Table 2 together with maturation data and observed changes in total body energy between December samples and February samples. Total body energy of field sampled sandeel was calculated from the following relationship derived from bomb
-1 calorimetry in the overwintering experiment: Total body energy [KJ ind ] = 23.4wdry – 1.4
(linear regression analysis, r 2 = 0.995).
11 In order to evaluate the arguments in Fig. 1 values from Table 2 were combined in Fig. 4.
The difference between reserve capacity and energetic cost of overwintering ( Rmax - ∆E8months ;
Fig. 4 grey bars) and the difference between observed and predicted change in energy from medio December to medio February ( ∆Eobs(field) - ∆E2months ; Fig. 4 black bars) increased gradually with increasing size, shifting from negative values to positive values around size class 9.5. The shift from negative to positive values corresponds to Lth after the definition given in Fig. 1. All individuals belonging to size class 6.5 to 10.5 were 1 year of age (and therefore still age-0 in the December samples) while size-class 12.5 and 15.5 were dominated by older individuals (age-1+).
The effect of temperature on Lth and a comparison to data in Boulcott et al. (2007)
From eq. 2 Lth was calculated for various temperatures and durations of the overwintering period. Lth increased with temperature and duration of the desired overwintering period.
Elevating temperature by 1oC throughout the overwintering period resulted in an increase in
Lth of roughly 1 cm. Increasing or decreasing the duration of the overwintering period by one month resulted in an increase or decrease in Lth of roughly 0.5 cm. The magnitude of the effect of the duration of the overwintering period increased with increasing temperature (Fig.
5).
Lastly, we applied local temperature profiles (see Fig. 2) to predict local Lth specifically for each of the study locations visited in Boulcott et al. (2007). Maturation sizes on Dogger bank,
Fisker bank and Firth of Forth, from Boulcott et al. (2007), are positively correlated to Lth
12 (linear regression analysis, r2 = 0.75, n = 3). Furthermore, the sizes at which 5% of sandeel were mature closely resembled the predicted local Lth (Fig. 6).
Analytical solution
In the case of constant temperature the model could be solved analytically. The energy lost at time t is:
∆ = − ( − ) E t,( T ) EC w0 w t,( T ) (4)
dw − where the weight of a fish at time t can be found by solving = −E 1S wn f (T ) : dt C 0
− − 1 = ( 1 n − − 1 )1−n w t,( T ) w0 1( n)EC S0 f (T )t (5)
w1−n E This expression is valid for t < 0 C which is the time it would take to decrease the − 1( n)S0 f (T ) body size to the infeasible size of zero.
DISCUSSION
The present study is to our knowledge the first to specifically relate size- and temperature- dependent energy expenditure to maturation size in fish. Downhower (1976) showed based on
13 similar bioenergetic considerations that duration of the winter period should affect size at first reproduction in temperate non-migrating bird species, such as finches. In related studies of fish, to mention a few, it has been shown that (i) juvenile growth rates and sex determination of
Atlantic silversides (Menidia menidia ) have evolved in response to a selection pressure imposed by size-dependent energy depletion and latitudinal gradients in the length of the growing season
(e.g. Conover 1992; Schultz et al. 1998; Schultz et al. 2002), (ii) mean age of first spawning in
Atlantic salmon ( Salmo salar ) increases with the migration distance to its freshwater spawning grounds (Schaffer 1975), (iii) the time constraint imposed by size-selective winter mortality shape energy allocation strategies and behaviour of juvenile fish, for example largemouth bass
(Micropterus salmoides ) and rainbow trout ( Oncorhynchus mykiss ) by favouring high risk-high gain foraging behaviour and fast growth (Schindler 1999; Garvey and Marschall 2003; Biro et al.
2005), and (iv) the northern distributional limit for yellow perch (Perca flavescens ), Eurasian perch (P. fluviatilis ), smallmouth bass (M. dolomieui ), and largemouth bass ( M. salmoides ) are defined by the ability of the young of the year to complete a minimum amount of growth during a growing season that shortens toward higher latitudes (Shuter and Post 1990; Fullerton et al.
2000). However, neither of those studies made the link from size-dependent energy depletion to maturation size. Furthermore, neither of the above studies developed and validated quantitative species specific models for predictions of the integrated size-dependent energy depletion during long periods of starvation. The lack of such models in the literature may be owing to a limited knowledge about activity levels and consumption rate during the winter period (e.g. Garvey and
Marschall 2003). In the present study we took advantage of the unique burying behaviour and pronounced site fidelity of sandeel. These traits made it possible to apply respirometry-based measurements of standard metabolic rate in calculations of the basic energetic cost of overwintering (reproductive investment not included) as a function of (i) fish size, (ii) duration
14 of the overwintering period and (iii) the temperature profile in the overwintering habitat. In the introduction we hypothesised for the existence of a critical threshold size below which a full scale overwintering is impossible or infeasible and a prolonged feeding period or winter feeding activity required for survival. We also argued that investment in reproduction is not feasible until the fish passes the threshold size (see Fig. 1). In the present study we estimate a critical threshold size (Lth ) for Lesser sandeel on the main North Sea fishing areas. It was found that the observed energy expenditure in sandeel during winter in the field increased with size and equalled standard metabolic cost only in the vicinity of Lth . Furthermore, Lth appeared to be reached just prior to onset of maturation. The negative values of ∆Eobs(field) - ∆E2months for size class 9.5 and below suggest that feeding has taken place during the overwintering period. Likewise the positive values found for size class 10.5 and above suggest that energy has been used for reproductive investment. Consequently the arguments made in the introduction were supported by the results presented here. Furthermore, these patterns are consistent with observations of a prolonged activity period of age-1 sandeel in the North Sea compared to adult sandeel (age-2+), as well as with observations of high abundances of active age-0 sandeel as late as December
(Macer 1966; Reeves 1994; Kvist et al. 2001).
A shortfall of the present model may be the lack data supporting the assumption that a 47% reduction in the annual maximum energy content is the lethal lower limit of energy depletion (or the point of no return). The difference in energy content of Lesser sandeel in Scottish waters between April (onset of the growth period) and August (end of the growth period) conform to a factor of 1.7 for the smallest (7 cm juveniles) to 2 in the largest (15 cm adults) (Hislop et al.
1991). In comparison average overwinter reduction in energy content of starving juvenile
Alaskan Pacific herring ( Clupea pallasi ) has been estimated to 38% and fish began to die when they experienced energy reductions between 30% and 46% (Paul and Paul 1998).
15 Energy depletion in the VAL-1 validation experiment was slightly overestimated by the model.
This may have been due to the use of a size-scaling exponent of 0.8, which is a crude mean value for fish in general. Species specific exponents have been reported in the range from 0.65 to 0.9
(Jobling 1994). An alternative explanation for the overestimation may lie in the applied
-1 oxycaloric coefficient of 14 J mg O 2. The oxycaloric coefficient depends on the respiratory substrate and is slightly less for proteins than lipids (Jobling 1994). Therefore if the small sandeel used in VAL-1 utilized proteins as respiratory substrate to a larger degree than larger sandeel did in VAL-2 this would have caused the predicted energy depletion to be slightly overestimated for the smallest sandeel.
The typical age and size at maturation reaction norm finds that organisms mature earlier and at a larger size as growth conditions improve (e.g. Plaistow et al. 2004). In Fig. 6 we included data from a previously published study (Boulcott et al. 2007). In this study age and size at maturation for A. marinus among three study locations in the North Sea (Fisker Bank, Dogger
Bank and Firth of Forth) were compared. The presented data suggest that maturation of sandeel is not determined by age, and given the right growth conditions even age-0 sandeel may mature. Furthermore, the comparison between study locations revealed an inconsistency with the typical reaction norm, in that a considerable proportion of sandeel on Fisker Bank, despite the highest growth rate observed among the study locations, matured at older age and at significantly larger size compared to the remaining study locations. Fisker Bank is highly influenced by the coastal water system and the water column stability is weak, which presumably causes the relatively high bottom temperatures in summer and fall. Dogger Bank is also well mixed but is under influence by the off-shore water system, whereas Firth of Forth is characterized by high water column stability and cold southward bottom water current.
When we used differences in bottom temperature among the locations compared in Boulcott
16 et al. (2007) to calculate Lth , we found that differences in Lth provided a possible explanation for the variation in size at maturation. Furthermore, it prompted us to speculate if the relatively low temperatures and consequently small Lth at Firth of Forth is the main reason that high densities of sandeel (as measured from Danish commercial catch rates) persist in this area despite the low growth rates reported in Boulcott et al. (2007).
In the present study a linear relationship between SMR and temperature (SMR = aT + b) was the best, opposed to the traditionally applied curvilinear relationship (ln( SMR ) a T+ b, see
Jobling (1994)). We have no explanation for why a linear function fitted the data better.
However, measurements of SMR in sandeel at 10 oC (Behrens et al. 2007) strongly support the validity of measurements in the present study. There is no consensus on whether fish have the ability to hibernate, in the sense that the term is typically applied to frogs and turtles (Ultsch
1989), although comatose-like conditions, impairment of sensory performance, and anaerobic metabolism (the latter only in the crucian carp Carassius carassius ) have been observed in fish exposed to severe hypoxic environments (e.g. Nilsson and Renshaw 2004). However, buried sandeel appear to overwinter in aerobic environments as they suck down oxygenated water from above the sediment surface (Behrens et al. 2007). It has also been described how
Notothenia coriiceps (an Antarctic fish) entered a comatose-like state after exposure to extremely low temperatures for some time (~2 oC) (Campbell et al. 2008), but when the sandeel in the present study were disturbed after being buried for many months they appeared to be perfectly agile and showed no signs of sluggishness. Furthermore, the good resemblance between model predictions (based on respirometry measurements) and measurements of the reduction in energy content of long-term buried sandeel in the laboratory indicate that comatose or advanced metabolic depression does not occur in this species, and that the reduction in activity gained from burying is sufficient to tolerate long periods of starvation. It
17 should be added that SMR of buried sandeel is in the lower range of values reported for fish
(Behrens et al. 2007; Behrens and Steffensen 2007).
It the present study it was found that reserve depletion in an experimentally simulated long- term overwintering-scenario could be accurately predicted from short-term respirometry- based measurements of oxygen consumption. A comparison between such predictions and field data was suggestive of the existence of a critical threshold size below which a full scale overwintering and reproductive investment is highly unlikely to take place. The threshold size
Lth , as calculated in the present study, should be considered merely as a reference point that can help us understand the mechanisms underlying some important life history transitions, and it should be noted that the present Lth is calculated specifically for sandeel in the North
Sea that have reached Rmax prior to the overwintering period. Besides the life history perspective, the presented framework could also provide valuable information about the expected natural mortality rate, i.e. in years of unusually poor growth conditions fish may fail to reach Lth or Rmax and may consequently suffer from starvation mortality or elevated predation mortality due to compensatory winter feeding activity. The analytical solution presented as a result provides an easy way of approximating Lth .
Climate variability (spatially, intra-annually or long term) have considerable effects on ecosystems and population dynamics (e.g. Walther et al. 2002; Alheit and Bakun 2010; Alheit et al. 2010; Finney et al. 2010; Overland et al. 2010). However, the relationship between climatic variability and population dynamics is often indirect and the causality difficult to entangle. Population dynamics on both temporal and spatial scales are influenced by variation in life history parameters such as size (and age) at maturation and growth rates. The results presented here suggest that climatic variability manifested by changes in temperature and
18 duration of the growing season could potentially influence size at maturation of Lesser sandeel and, in the light of the general physiological principles underlying the present results, perhaps other ectotherms as well. However, further work is needed. For example we assumed a fixed duration of the overwintering period, whereas the overwintering period may in fact be a flexible trait which adapt to local conditions. Also the notion that the overwintering strategy becomes the optimal strategy as soon as the threshold size has been reached is an unsupported assumption. Lastly, the present study built on the assumption that sandeel is truly iteroparous
(multiple reproductive cycles over the course of its lifetime) as opposed to semelparous which for example seems to be the case for Capelin ( Mallotus villosus ), an arctic forage fish (Friis-
Rødel and Per Kanneworff 2002). A next step towards understanding the implications of Lth on life history strategies could therefore be to apply a fitness based life cycle optimality model to the problem (e.g. Fiksen and Carlotti 1998).
Acknowledgements. We thank Niels Gerner Andersen and Dorthe Frandsen for making the use of bomb calorimetry possible. We thank the ocean monitoring division at DTU-AQUA for providing sandeel field data, in particular Cecilia Kvaavik. We thank people behind the
NORWECOM model for providing free access to modelled North Sea temperature data.
MVD was funded by the Danish Research Council supported projects FISHNET and SLIP.
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23 Table 1. Observed and predicted energy depletion in sandeel overwintered in the laboratory
Duration Initial Initial energy Final Observed % loss Predicted Deviation
[days] wet weight content Energy Energy energy depletion [%]
-1 -1 -1 [g ind ] [KJ ind ] Content depletion (∆Elab [KJ ind ])
[KJ ind -1] [KJ ind -1]
VAL-1 131 1.37(SD = 0.18, n 6.66(SD = 1.08, n 3.98(SD = 0.49, n 2.68 40 2.85 6 = 9) = 9) = 9)
VAL-2 298 4.06(SD = 0.58, n 24.60(SD = 3.81, 12.87(SD = 2.43, 11.73 48 11.65 0.7 = 6) n = 6) n = 6)
Table 2. Observed and predicted energetic cost of overwintering of sandeel
Size Rmax Predicted cost of Predicted cost of overwintering Observed change in total body energy class [KJ ind -1] overwintering (8 months) between medio December and between medio December and medio
-1 [cm] (∆E8months [KJ ind ]) medio February February
-1 -1 (∆E2months [KJ ind ]). (∆Eobs(field) [KJ ind ]).
6.5 1.83 2.93 0.59 -0.33
7.5 3.99 0.81 0.05 3.09 8.5 4.89 5.39 1.10 0.47
9.5 7.34 7.22 1.47 1.18
10.5 10.59 9.50 1.94 2.06
12.5 20.07 15.58 3.17 4.56
15.5 44.13 29.21 5.57 12.16
24
Fig. 1. The conceptual model that is tested in the present study: Reserve size (or capacity) prior to winter as a function of fish size (dashed) and the integrated metabolic cost of overwintering (reproductive investment excluded) as a function of size (solid line). The critical threshold size ( Lth ) is where the metabolic cost of overwintering equals reserve capacity. For sizes smaller than Lth there will be a deficit of energy (light grey area) which must be paid by compensatory winter feeding activity. Above Lth there will be a surplus of energy which is available for reproductive investment (dark grey area).
25 16
14 C] o 12
10
8
Temperature [ 6
4 1 31 61 91 121 151 181 211 241 271 301
Days from August 1st
Fig. 2. Temperature profiles for Firth of Forth (dashed line), Dogger bank (solid line) and
Fisker bank (dotted line).
26 1,6
1,4
1,2
1
0,8
0,6 [J g-1[J h-1] 0,4
0,2 Standardmetabolicrate 0 4 9 14 19 Temperature ( oC)
Fig. 3. Measurements of standard metabolic rate ( SMR ) in sandeel plotted against experimental temperature. A linear relationship (solid line) on the form f(T) = 0.08 T – 0.25
(r2 = 0.92) provided the overall best fit to the data. The best semilogoritmic fit (dashed line)
2 conformed to ln{f(T)} = 0.14 T – 2.2 (r = 0.87), and a Q 10 of 4.2.
27 100 10 90 5 80 ]
70 -1 0 d
60 -1 50 -5 40 -10 30 Energy[J g
Proportion [%] mature 20 -15 10 0 -20 6.5 7.5 8.5 9.5 10.5 12.5 15.5 Size-group [cm]
Fig. 4. Test of the arguments illustrated in Fig. 1. Grey bars: Maximum reserve capacity
(0.47% of maximum total body energy) of sandeel minus standard metabolic cost of 8 months
-1 -1 of overwintering, Rmax - ∆E8months (standardized to J g d ). Black bars: Observed change in total body energy (from sandeel caught in the sand in medio December and medio February)
-1 minus standard metabolic cost for the same period, ∆Eobs(field) - ∆E2months (standardized to J g d-1). White bars: Proportion of mature sandeel caught in the sand in December. Calculations of ∆E8months and ∆E2months are based on the mean temperature profile of Fisker bank and
Dogger bank.
28 140
130
120 [cm]
110
100
90
80
Threshold size Threshold 70
60 -2 -1 0 1 2 o Temperature deviation [ C]
Fig. 5. Threshold size ( Lth ) for sandeel as a function of temperature for three different lengths of overwintering, 7 months (dashed), 8 months (solid) and 9 months (dotted). Temperature on the x-axis is deviation from the mean temperature profile applied in Fig. 4 (1 oC deviation implies that the temperature in all months was raised by 1oC).
29 14
13
12
11
10
Maturation sizeMaturation [cm] 9
8 8,2 8,7 9,2 9,7 Threshold size [cm]
Fig. 6. Sandeel maturity data from Boulcott et al. (2007) plotted against predicted threshold size ( Lth ). Sizes at which 5% (triangles) and 50% (circles) were mature in Firth of Forth (small maturation size), Dogger bank (medium maturation size) and Fisker bank (large maturation size) plotted against Lth calculated specifically for each location (circles). Dotted and dashed lines are regression lines. The solid line represents a relationship of 1:1 between maturation size and Lth .
30
31
32 MANUSCRIPT III
- INCLUSIVE SUPPLEMENTARY MATERIAL
Status: Accepted for publication (incl. supplementary material) in Marine
Ecology Progress Series on August 5 th and published October 14 th 2010 in
Vol. 416: 201-214; the manuscript is included in the thesis with permission from Marine Ecology Progress Series
MANUSCRIPT IV
Status: Manuscript draft
Title: Proximate versus ultimate control mechanisms of foraging activity in sandeel schools
(Ammodytes tobianus )
Authors: Mikael van Deurs 1,2*, Jane W. Behrens 1, Thomas Warnar1, John Fleng Steffensen 2
1National Institute of Aquatic Resources, Technical University of Denmark, Jægersborg Alle 1,
Charlottenlund Castle, 2920 Charlottenlund, Denmark.
2Marine Biological Laboratory, University of Copenhagen, Strandpromenaden 5,
3000 Helsingør, Denmark.
Key words: Ammodytes; diurnal feeding cycle; feeding periodicity; consensus decisions; state- dependent behaviour; School formation
* [email protected] , +45 35883428
1 Abstract:
In order to fully understand observed variation in foraging activity data on how organisms perceive and process information about their surroundings are essential. The commercially exploited sandeel
(Ammodytes ssp.) make distinct vertical shifts between an inactive stage, during which they seek refuge in the sand, and a pelagic schooling stage. In the present study whole schools of sandeel ( A. tobianus ) were caught in August in east Denmark (65 o02’30N; 12 o37’00E) and kept in large tanks in the laboratory. It was found that ration-size and memory of past days feeding history played an essential role in the regulation of foraging activity on the level of the entire school. This indicates that what seems as complicated consensus decision making may be explained by a few simple proximate mechanisms, and without inclusion of complicated machinery to perceive environmental variables.
2 INTRODUCTION
The individual organism is constraint by its perceptual world and its capability to translate external stimuli into useful foraging decisions. It has therefore often been stated that a major challenge to the use of optimality models addressing foraging behaviour on time-scales of days or hours is the assertion that natural selection only optimise behavioural decisions in a relative sense (e.g.
Drickamer and Gillie 1998). Nevertheless attempts to model behaviour seem to outnumber studies providing empirical data on how individual organisms perceive and handle information from their surroundings. We can assign most studies of diurnal shifts in foraging activity into one of two types. The ones that focus on feeding rhythms or diel periodicity and classify organisms as either diurnal, nocturnal or crepuscular (Løkkeborg 1998; Cardinale et al. 2003; Darbyson et al. 2003;
Boujard and Leatherland 2004; Freeman et al. 2004 ), and those that address how environmental variables determine foraging motivation (Bohl 1980; Valdimarsson et al. 1997; Marchand et al.
2002; van der Kooij et al. 2008). The first type of studies do not deal with external cues, besides that of the predictable diurnal periodicity in light intensity, and are therefore descriptions of general or archetypical diurnal activity patterns. In contrast the latter type of studies address how foraging activity respond to unpredictable or local gradients in external cues. This is typically done by applying field measurements of temperature, light and food availability as explanatory variables in statistical models describing observed patterns of diurnal foraging activity. However, studies of this type do not tell us whether a variable identified as a significant explanatory variable (e.g. temperature), is the so called proximate factor (with direct influence) perceived by the organism and translated accordingly into the observed behavioural response, or merely an ultimate factor or distal factor (with indirect effect) with more or less influence on the proximate factor. It is hence difficult, if not impossible, to know if the observed relationship between a measured variable and the
3 observed behaviour persists in environmental contexts different from the one in which the relationship was established. Furthermore, information about the role of “memory” of feeding history is also rarely available, since distinguishing between what is a result of external cues and what is a result of “memory” can be extremely difficult under natural conditions (we used memory with quotation marks as we do not distinguish between memory in the neurological sense and biochemical sense).
Consequently, in our opinion, such field studies need to be accompanied by experiments designed to distinguish between the proximate and ultimate causes driving behavioural decision-making.
Furthermore, models utilizing proximate factors as drivers are more generic and readily validated experimentally on individuals or groups of these compared to pure optimization models (Giske et al. 2003). However, we found that experimental studies concerned with proximate vs. ultimate mechanisms are rare.
Experimental studies with the purpose of accompanying foraging-models in behavioural ecology are not only of relevance in theoretical and fundamental biological research but also in applied biology. Sandeel (Ammodytes ssp.) are found on continental shelfs around the globe between 50 oN and 70 o N. In the North Sea they outnumber all other fishes during spring and early summer, where they constitute a primary target in an intense commercial fishery and for a wide range of predators
(Hobson 1986; Reeves 1994;Rindorf et al. 2000; Furness 2002; Greenstreet et al. 2006; Engelhard et al. 2008; ICES 2009). Sandeel make distinct vertical shifts between an inactive stage, during which they seek refuge in the sand, and a pelagic stage where they forage in large schools. During winter individuals are permanently in their refuge, while they during the foraging period, in spring and early summer, spent some proportion of the day foraging and bury in the sand for the remainder and during night time. Due to inadequate knowledge about the underlying mechanisms driving
4 these habitat shifts, i.e. the vertical migration and discontinuous foraging activity, it is very difficult to use catch-rates in stock assessments (Greenstreet et al. 2006; ICES 2009).
Winslade (1974a,b) showed experimentally that activity of individual sandeel increased when food was present and when water temperature was elevated from 5 to 15 oC. Giske et al. (2003) and
Rands et al. (2003) illustrated how prey organisms (e.g. small fish) in theory, in both individual and group context, can make optimal foraging decisions without a machinery for perception of temperature and prey concentrations; if provided with information about energy reserves and gut- fullness. The four studies mentioned above prompted us to experimentally investigate the role of gut-fullness, temperature and “memory” in driving foraging decisions of schooling sandeel. Among other we ask whether prey concentration and temperature are proximate factors (exerting direct effects) or merely ultimate factors (exerting indirect effects). In order to do this we kept large schools of Small sandeel ( Ammodytes tobianus ) in large video-monitored tanks under controlled conditions while systematically varying ration-size, temperature and feeding-time.
MATERIALS AND METHODS
Fish and Tank set-up: Specimens of Small sandeel (Ammodytes tobianus ) were caught by seine in
August in a small shallow cove in east Denmark (65 o02’30N; 12 o37’00E). Mean length = 10.84 cm
(SD +/- 0.43) and body wet weight = 5.06 g (SD +/- 0.57). Nine hundred fish were kept in each of two circular tanks (tank 1 and tank 2) (Fig. 1). The bottom of each tank was covered by a layer of
20 cm deep beach sand, which made up the refuge . A PVC tube (40 cm in diameter) was placed vertically in the centre of each tank in order to create a circular raceway. The raceway made up the
5 arena , being 55 cm wide, 70 cm deep, and 314 cm in mean length. Ingoing water was air saturated and held at 10 oC and 30‰ salinity, except during the temperature experiments. The light regime followed 13h:11h light:dark cycle with full light equalling approximately 1.5 x 10 -3 µE measured 2 cm below the water surface. To minimize disturbance, tanks were sheltered from the surroundings by wooden walls and light impenetrable curtains. Ten weeks before the beginning of experiments a white rectangular 50 x 15 cm white plastic plate was placed on the bottom of each tank perpendicular to the swimming direction and 20 cm above the plate a string spanned the width of the plate. This way individual fish could be identified in dark/light contrast as they passed over the plate and the vertically location could be determined relative to the string (in other words it could be determined whether they were 0-20 cm above the plate/sediment or 20-70 cm above)
School behaviour in general: The school followed a similar distinct diurnal behavioural pattern in both tanks. During the first 15 minutes after the light was turned on fish started to emerge from their refuge and aggregated close to the bottom (the lowest 0-20 cm) and gradually accumulated as more fish emerged from the refuge. After approx. 15 minutes, emerging events became fewer and fewer until no more fish came out from the refuge. Hereafter the school spread out vertically, ascended and soon occupied the upper two thirds of the water column and the entire width and length of the swimming lane. Swimming was always unidirectional against the weak current generated by the water inflow. Feeding events however caused break-up of the school but only for a few minutes.
After 4 to 7 hours of light the school gradually started to descend back into the lowest 20 cm of the water column, and over the course of approx. one hour the school was completely disintegrated as the fish gradually buried into the sediment again. After this the arena remained completely empty until the next day. On a few occasions a small number of fish (~ 5% of the school) kept schooling close to the bottom for another hour or two before joining the remaining of the school in the refuge.
To confirm school coherency and exclude the possibility that sandeel shuffled in and out of their
6 refuge during the day, fish was fed grey coloured food (thawed mysis shrimps) just after emerging and redish food (thawed artemia) four hours later. Sub-samples of those fish confirmed that 93% of fish fed in the morning appeared in the afternoon sub-samples. Furthermore, 95% of fish sampled the following morning contained both greyish and redish gut content.
Estimating the duration of the foraging period: The duration of the period during which the school was foraging in the arena, the foraging period T, was defined as the number of hours between school formation (which occurred at the dark/light transition where fish emerged from the sand) and school disintegration. A video camera mounted above the tank was directed vertically at the plate and the connected software Pinnacle TV Center Pro (Pinnacle Systems) programmed to record a short video sequence each hour. In tank 1 a mirror was used to create distance between the camera lens and the white plate (Fig. 1), hence minimizing the variation in apparent length of individual fish related to whether they were close to the sediment or the surface. Each digital video recording was subsequently converted into an image in MATLAB© by selecting the same pixel- row in each movie frame and stacking them chronologically. Each image provided a proxy for the number of fish number in the arena (Fig. 2). Even though school disintegration was a gradual process lasting for approx. one hour, we chose to define the time of school disintegration as the point in time where school size was reduced to 10% of the maximum size observed that day and T was approximated from this based on linear interpolation between the hourly estimations of fish in the arena.
Experiment 1 - Effect of ration-size on foraging period (tank 1 and tank 2): In this experiment we tested the hypothesis that ration-size affects the foraging period T. During this experiment fish in both tanks were fed a single ration of thawed artemia 2.5 hours after the light was turned on. Four different ration-sizes were applied, Ration-1 = 0 g, Ration-2 = 50 g, Ration-3 = 150 g, and Ration-4
= 500 g. The given weights are the weights of the frozen block of food which contained water as
7 well. By taking sub-samples of fish after feeding them Ration-4, we estimated that the four ration- sizes resulted in an average gut content of approx. 0 g, 0.04 g, 0.1 and 0.35 g. As the weight of the gut content of a full gut was estimated to roughly 0.5 g on average (or 10% of total body mass), this corresponded respectively to 0%, 8%, 24% and 70% of a full gut, assuming that the fish shared the food equally. The rate with which food were consumed decreased as the guts were filling up. To achieve 100% full guts fish therefore had to be fed consecutively over at least one hour, which was believed to be problematic with respect to the general design of the experiment. Ration-4 was found to be the largest ration that could be ingested by the school during a single feeding session and without notable sedimentation of food (a ration was added gradually to the tank water, and a single feeding session could last up till 5 minutes). The experiment lasted for 38 days during which the fish in each tank were fed one of the four ration-sizes in the following sequence: Ration-1, Ration-1,
Ration-1, Ration-4, Ration-4, Ration-4, Ration-4, Ration-1, Ration-1, Ration-1, Ration-3, Ration-3,
Ration-3, Ration-3, Ration-1, Ration-1, Ration-1, Ration-2, Ration-2, Ration-2, Ration-2, Ration-1,
Ration-1, Ration-1, Ration-4, Ration-4, Ration-4, Ration-4, Ration-1, Ration-1, Ration-1, Ration-3,
Ration-3, Ration-3, Ration-3, Ration-1, Ration-1, Ration-1.
Experiment 2 - Effect of feeding-time on foraging period (tank 2). In this experiment we tested if the time at which the ration was given affected T. Or we could also ask: Does ration-size affect the duration of the entire period from school formation to school disintegration (how we initially defined T) or just the time from last feeding until school disintegration? In order to answer this question we applied a daily feeding ration of 150 g thawed artemia in tank-1. Feeding-time was 15 minutes, 2.5 hours (i.e. similar to the feeding-time in Experiment 1) or 5 hours after the light was turned on. On a given day one of the three feeding-times were randomly chosen until each feeding- time had been applied 5 times. To achieve control measurements fish were starved every 6 th and 7 th day (i.e. similar to Ration-1 in Experiment 1).
8 Experiment 3 - Effect of yesterday’s ration-size on today´s foraging period (tank 1 and tank
2): In this experiment we tested if un-evacuated gut content from a ration given on day t-1 affected
T on day t. Or we could also ask: Is gut-fullness, independent of when food has been ingested, a proximate driver of foraging activity. Fish were subjected to one of two different treatment sequences representing two different feeding regimes; Feeding regime-1: fish were starved (day
1), fish were fed 750 g of thawed artemia over the course of one hour starting at noon (day 2) and fish were starved again (day 3). Feeding regime-2 was similar to feeding regime 1 except that fish were fed 150 g. For both feeding regimes we estimated average gut-fullness on day 2 (1 hour after feeding the fish) and day 3 (2 hours after the light was turned on) by capturing 10 fish and weighing their gut content. T was measured on day 2 and 3. The experiment was replicated 6 times.
Experiment 4 - Effect of temperature long-term starvation on foraging period (tank 1): In this experiment we tested the hypothesis that a reduction in temperature results in a reduction in T. We furthermore tested the effect of depriving sandeel of food for ten consecutive days, opposed to only four days in experiment 1. This experiment was divided into three parts, each lasting 15 days; Part
1: 10 oC, Part 2: 5 oC and Part 3: 10 oC. In between each part the fish were allowed to acclimatize for
5-10 days. During each part fish were exposed to the following sequence of daily ration-sizes:
Ration-3, Ration-3, Ration-1, Ration-1, Ration-1, Ration-1, Ration-1, Ration-1, Ration-1, Ration-1,
Ration-1, Ration-1, Ration-3, Ration-3, Ration-3 (see experiment 1 for a description of Ration-1 and Ration-3). The experiment was carried out in tank-1. In the present study we mainly focused on the duration of the foraging period as a measure of foraging activity. However, swimming speed may be another proxy for foraging activity. We therefore also measured swimming speed on 20 fish during Ration-3 treatments just before giving the ration. We did this using LoggerPro software
(Vernier, USA) to handle the scheduled video recordings of fish crossing the white plate on the bottom.
9 Statistical analysis: Data on foraging period T was analyzed using a generalized linear model
(GLM) with a Gaussian family. T was log transformed to meet normality criteria. The initial models tested for tank effects, effects of yesterday´s treatment, and of repeating the same ration-size for several consecutive days. The independent variables i.e. Ration-size, time of feeding and tank effect was treated as class variables, whereas the effect of consecutive days of feeding the same ration-size was treated as a co-variate. Independent variables were eliminated with a stepwise procedure, where the non-significant independent variable that contributed least to the model was eliminated first.
Bonferroni correction for multiple comparisons was used when necessary. Significance level was set to 0.05.
RESULTS
Experiment 1 to 3 - Effect of ration-size, feeding-time and gut-fullness
Experiment 1: The duration of the daily foraging period T was significantly prolonged on days where fish were being fed compared to days where fish were starved, and the larger the daily ration the longer the foraging period. The differences in mean T between Ration-1 and all other ration- sizes were highly significant (p < 0.001), and Ration-4 was significantly different from both Ration-
2 and Ration-3. However, Ration-2 and Ration-3 were not significantly different. In the final GLM we therefore pooled Ration-2 and Ration-3, and also in this model Ration-4 was significantly different from Ration-2 and Ration-3 combined (p = 0.002) (Fig. 3). There was no tank-effect and
10 no day-effect of giving the same ration-treatment for four consecutive days. We failed to generate data on 2 out of the 38 days due to technical problems.
Experiment 2: The effect of feeding-time on T was not significant and there was no trend in the data (Fig. 4), which suggested that the initiation of school disintegration was independent of time since last meal. However, all feeding-time treatments were highly significantly different from days where zero food was given, which confirmed that the fish responded to being starved as seen in
Experiment 1.
Experiment 3: Gut weight in Feeding regime-1 weight of gut content averaged 0.49 g on day 2 and gut content was only partly evacuated by day 3 and weight of the remaining gut content was reduced to an average of 0.16 g (SD ± 0.09). In Feeding regime-2 gut weight averaged 0.10 g (wet weight) on day 2 and the gut content was fully evacuated by the beginning of day 3. T on day 3 of
Feeding regime-1 was not significantly different from T on day 3 of Feeding regime-2, but significantly lower than T on day 2 of Feeding regime-2 (p = 0.012) despite the higher gut content
(Table 1). Gut-fullness can therefore not be the proximate factor determining the duration of the foraging period. The pronounced difference between T on day 2 of Feeding regime-1 and day 2 of
Feeding regime2 was used as a confirmation that the main effect observed in Experiment 1 persisted.
Experiment 4 - Effect of temperature and 10 consecutive days of starvation
Whenever fish were deprived from food for three to five days school formation occasionally failed to occur (no fish emerged from their refuge) or was incomplete (fewer than normal emerged from their refuge). Temperature (independent of whether fish were fed or not) and the number of days
11 since last meal all had significant effects on T (p = 0.006, p < 0.001, p < 0.001; days where fish were absent failed to emerge in the morning were excluded from the analysis) (Fig. 5). T decreased as the number of days since last meal increased. In contrast reducing temperature increased T. There was no significant effect of temperature on swimming speed. The effect of feeding (similar to
Ration-3 in Experiment 1) vs. starvation (similar to Ration-1 in Experiment 1) was consistent with what was observed in Experiment 1.
DISCUSSION
We conducted controlled laboratory experiments on schools of Small sandeel (Ammodytes tobianus ) and achieved insight into aspects of behavioural decision-making on the level of the school. Sandeel behaved highly synchronized. Sandeels formed one large school in each tank and made joint decisions, or consensus decisions (Conradt and Roper 2005) with respect to school formation and school disintegration. It has previously been suggested for herring ( Clupea harengus ) that the school rather than the individual constitute the behavioural unit (Fernoe et al. 1998), a notion which clearly is supported by the results presented here.
It was found that school formation was triggered by the transition from dark to light, whereas the duration of the active foraging period, varied according to ration-size, temperature, and “memory” of past days feeding history. The duration of the daily foraging period T was significantly prolonged at 5oC compared to 10 oC (Experiment 4) and on days where fish were being fed (opposed to being starved) (all experiments). It was also found that the duration of the daily foraging period increased
12 with increasing daily ration-size (Experiment 1). The role of “memory” of past days feeding history was only evident when fish were deprived from food for more than three days, which resulted in a gradual shortening of the foraging period (Experiment 1 and 4). Varying the time at which the ration was delivered did not influence the duration of the foraging period (Experiment 2), which in the light of results from the Experiment 1 indicated that ration-size affected the entire period between school formation and disintegration, instead of just the period after last meal. However, gut-fullness by itself could be rejected as the proximate factor determining the duration of the foraging period as it was shown that undigested food consumed the previous day had no influence on the foraging period (Experiment 3).
Early in the study we realized that schooling behaviour could not be established unless sandeel were kept in high numbers in large circular tanks. Due to limited laboratory space and facilities we were able to use only two large tanks. However, when the first experiment was conducted in parallel in the two separate tanks the remarkably close resemblance in the behavioural response between tanks indicated that the results were reproducible. Furthermore, by alternating treatments over time, similar to what was done in Winslade (1974a,b,c) and Behrens et al. (2010), we were able to test if the behavioural responses were reversible when conditions returned to the starting point. This was used to confirm that observed behavioural responses were due to the treatments and not due to a coincidental change in the endogenous rhythm of the fish (i.e. due to change in condition). Lastly, treatment series were interspersed by days of zero food, which provided a control for the consistency in the basic behavioural pattern. The clear and homogeneous response to zero food in all experiments was regarded as a confirmation that the fish were not significantly changing behaviour and that experiments therefore were comparable.
Many species of schooling fish have set periods during the 24-hour cycle during which the schools disintegrate and fish disperse (e.g. Nilsson et al. 2003). Sandeel is the extreme example of this
13 phenomenon. The school of these fish disintegrates every day after foraging where after the individuals bury in the sediment. In the present study school formation could be divided into two distinct phases: At the dark/light transition school members emerged and subsequently remained just above the bottom substrate in a dense vertically depressed school until all or a sufficient amount of individuals had emerged. The school thereafter left the lower part of the water column and shifted to a less dense school. These observations suggest that individuals act in response to the light transition when emerging, which are consistent with previous findings (Behrens et al. 2010).
However, in contrast to the present study this study implemented a period of dim light interspersed between the dark period and the light period, nevertheless the majority of sandeel ( A. tobianus ) emerged just after the transition from dim light to full light. It is therefore still an open question which light intensity triggers emergence.
The present finding that the duration of the foraging period was independent of the time at which the ration was delivered suggested that sandeel either do not perceive time on a scale of hours or do not use this information in this particular context. In contrast, school formation failed to occur or was incomplete (fewer fish emerged from their refuge) if fish were deprived from food for more than three days, indicating that the decision about whether or not to emerge at the dark/light transition was based on “memory” of feeding history on a time-scale of days. Previous observations of the behaviour of sandeel ( A. marinus ) and roach ( Rutilus rutilus ) supports the conclusion concerning the use of “memory” on a coarse time scale of days (Winslade 1974b; van Dijk et al.
2002).
Combined, our and Winslade`s results (1974a,b,c) provide a more complete picture of the mechanisms underlying the variation in foraging activity than it would have been possible to deduce from either of the studies alone. Winslade (1974a,b,c) found that the presence of food in the water
14 (vs. no food), light intensity (1 to 1000 lux) and temperature (5 oC to 5 oC) had positive effects on foraging activity of Lesser sandeel ( A. marinus ). In these experiments one million newly hatched live artemia nauplii were each day pumped into an aquarium containing ten sandeel. In brook charr
(Salvelinus fontinalis ) feeding rate depends on reaction radius which in turn depends on visual perception of prey items and snapping rate (or attack rate) which again depends on light intensity and temperature (Marchand et al. 2002). Assuming that this is also the case with sandeel, total number of prey consumed per day at constant prey availability would therefore be affected by the light and temperature regime. However, if the individual perceive differences in for example temperature or prey concentrations and adapt their foraging activity accordingly, rather than according to what is consumed, then we should have expected fish in the present study to behave as if they were being starved (prey concentrations was essentially zero, since fish were fed single rations which were consumed rapidly), which they did not. On the contrary, increasing the ration size and thereby the amount consumed lead to a prolonged foraging period. Furthermore, when we decreased/increased temperature from 10 oC to 5 oC and vice versa, while keeping the ration size constant, the duration of the foraging period was longest at the lowest temperature. This stands in stark contrast to Winslade (1974a), as well as to the idea that when temperature decrease toward the lower range of temperatures experienced by the species in the field it should lead to reduced activity. Combined this points to that the proximate factor is related to gut-fullness or the amount of ingested prey within the day, whereas prey concentration and temperature are more likely to be ultimate (or distal) factors with some influence on for example snapping rate and thereby indirectly on the proximate factor. Results from a study investigating the seasonal and diel changes in foraging activity of Atlantic salmon ( Salmo salar ) supports this idea as juveniles fed actively despite temperatures below 0 oC as long as high ingestion rates were possible (Bremset 2000).
15 Winslade (1974a) also suggested that temperature plays a major role in regulation of seasonal patterns in feeding activity of sandeel ( A. marinus ). However, the present study indicates that
“memory” of past days feeding history is more important. Maybe, as the production of zooplankton declines toward winter they consume less and less food and therefore gradually reduce activity. We furthermore observed that during periods of long term starvation a small school suddenly appeared after several days of inactivity, which indicated that they occasionally explore the foraging habitat.
However, we failed to explain the prolonged feeding period found at the low temperature in the present study. We speculate that the low temperature may act as a notice about a forth coming winter and a warning that if reserves are not yet full they need to be filled soon.
Results from the present study suggest that sandeel are opportunists and feed when food is available while preserving energy and reducing predation risk when food is scarce. In this context detection of prey concentrations in the surrounding water was not found to be important. Instead “memory” of past days feeding history and an endogenous stimuli closely associated with gut-fullness seems to be the major proximate regulators of foraging activity at the level of the entire school. The positive relationship between gut-fullness and foraging activity never-the-less stands in contrast to a frequently cited study. In this study sticklebacks display reduced feeding motivation as gut fullness increase (Salvanes and Hart 1998). A possible explanation for this inconsistency could be that the strategy of sandeel resembles that of the central place forager (Tamm 1989). The central place forager pays an appreciable cost in terms of energy and predation risk to get from its refuge to the foraging habitat and back again, and should therefore take full advantage of good feeding conditions whenever they arise before returning to the refuge. In line with this explanation several studies have suggested increased predation risk during the school formation and disintegration
16 phase of sandeel (Hobson 1986; Engelhard et al. 2008). Another explanation for the inconsistency between sandeel and sticklebacks may lie in the pronounced schooling behaviour of sandeel.
The present study also suggest that what may seem as complicated consensus decision-making may be explained by simple proximate mechanisms; and this without inclusion of complicated machinery to perceive environmental variables such as day light intensity, temperature and prey concentrations. This finding fit well with the predictions made by Giske et al. (2003) and Rands et al. (2003). Giske et al. (2003) demonstrated that by letting a “rule of thumb” evolve under natural selection over a sufficient number of generations (using genetic algorithms) prey organisms can adopt a surprisingly optimal vertical migration pattern, even if the only proximate driver is gut- fullness. At the same time Rands et al. (2003) demonstrated how prey organisms in a group theoretically make joint decisions about when to forage and when to seek refuge; despite within group variation in state (for example gut-fullness). The joint decision-making was driven by a simple rule of thumb “I should forage either if my reserves have fallen below a certain threshold value, or my partner chooses to forage”.
Studies like the present may turn out to be useful during future attempts to improve our understanding of how catch-rate data translate into fish abundances, which is a highly relevant issue in many stock assessments. As previously mentioned interpretation of catch-rate data is a major challenge concerning improving the North Sea sandeel assessment. A simple advice based on the present results could be that sandeel catch-data from early in the day and when the guts contain notable amounts of ingested prey are relatively more likely to reflect the true abundance of sandeel.
However, an experimental laboratory setup is always a simplification of the natural conditions. For example many sandeel fishing grounds in the North Sea are exposed to strong tidal currents, which may prevent foraging activity during certain periods of the day. We also did not address the possible effects of school-size and presence/absence of predators. One should therefore be careful
17 when attempting to draw parallels from laboratory experiments such as the one presented here. We instead suggest that data from a series of behavioural experiments, each systematically addressing a distinct mechanism, are synthesized in a generic behavioural model designed to generate hypotheses that can be tested on field data.
Acknowledgements. We thank the personal at the Øresund Aquarium for helping us with
catching and caretaking of sandeel, and Ken Haste Andersen and Uffe Høgsbro Thygesen for
help with MATLAB programming. MVD was funded by the Danish Research Council
supported projects FISHNET and SLIP.
18
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Table 1. The effect of un-evacuated gut content from the previous day vs. gut content from within the day food uptake
Feeding regime-1 (FR1) Feeding regime-2 (FR2) Statistical differences Day 1 starved starved Treatment Day 2 750 g artemia at mid day 150 g artemia at mid day Day 3 starved starved Day 1 - - Gut content [g] Day 2 0.49 (SD+/- 0.19) 0.10 (SD+/- 0.04) Day 3 0.16 (SD+/- 0.09) ~ 0 Day 1 - - FR1 day 3 vs. FR2 day 2: Foraging period, Day 2 11.38 (SD+/- 2.07) 7.67 (SD+/- 1.31) p=0.012 T [h] Day 3 5.84 (SD+/- 1.01) 4.98 (SD+/- 0.48) FR1 day 3 vs. FR2 day 3: p=0.135
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Fig. 1. Diagrammatic representation of the experimental setup for monitoring the number of fish swimming in the water column. Sandeels in circular tanks (containing a 20 cm deep sand layer) were monitored with a video camera that recorded 2 minutes every hour. In one tank a mirror was used to increase the distance between the camera and the tank. A PVC tube (40 cm diameter) was placed in the centre of each tank in order to create a circular swim lane. The swim lane was 55 cm wide, 70 cm deep, and 314 cm in mean length. A white rectangular 50 x 15 cm white plastic plate was placed in each tank perpendicular to the swimming direction and 20 cm above the plate a string spanned the width of the plate. Water intake was 0.25 l s -1.
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Fig. 2. Example of image generated from one line of horizontal pixels from 250 video frames from a 10 sec video recording, which corresponded to the average time it took the fish to swim one round in the raceway.
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Fig. 3. Effect of ration-size on foraging period. Graph shows ration-size versus foraging period T measured as the mean number of hours between school formation and disintegration. Data is presented separately for tank-1 (black) and tank-2 (grey) to illustrate the similarity in behaviour among the two tanks. School activity on days where Ration-2, Ration-3 or Ration-4 was given where significantly larger than on days where Ration-1 was given (p < 0.001). Furthermore, school activity on days where Ration-4 was given where significantly larger than on days where Ration-2 and Ration-3 were given (p = 0.002; in this model Ration-2 and Ration-3 were pooled).
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Fig. 4. Effect of feeding-time on foraging period. Graph on the right side of dashed vertical line show the mean foraging period, measured as the mean number of hours between school formation and disintegration ( T), versus deviation in hours from the feeding-time applied in Experiment 1. To ensure that the effect of ration-size was still present (as in Experiment 1) data plotted on the left side of dashed vertical line are control measurements (C) and correspond to Ration-1 in Experiment 1.
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Fig. 5. The response in activity to temperature-changes and 10 consecutive days of starvation. The experiment consisted of three parts: 2 periods of 15 days at 10 oC (white areas) interspersed by a 15 days period at 5 oC (grey area). Graph shows the daily mean foraging period measured as the mean number of hours between school formation and disintegration (T; vertical columns) together with the daily mean swimming speed measured as body lengths per second (open circles; whiskers represent +/- SD). Fish were on a given day treated with either a ration containing 150 g (grey columns), similar to Ration-3 in Experiment 1, or no ration at all (black columns), similar to Ration-
1 in Experiment 1. During the starvation periods there were days where the school remained absent in the arena throughout the day (this has been marked “a” in the graph). Video equipment suffered from technical problems during the third experimental period (this has been marked “f” in the graph). Temperature (independent of whether fish were fed or not) and day-number (1, 2, 3…10) of the starvation period had significant effect on T (p = 0.006, p < 0.001, p < 0.001; days where fish were absent from the arena were excluded from this analysis). There was no significant effect on swimming speed.
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