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2004 THE ECOLOGICAL CAUSES AND CONSEQUENCES OF PREY CHOICE AND ONTOGENETIC NICHE SHIFTS IN THE COMMON GOBY

Jackson, Angus Charles http://hdl.handle.net/10026.1/2009

University of Plymouth

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By

Angus Charles Jackson

A thesis submitted to the University ofPlymouth

in partial fulfilment for the degree of

DOCTOR OF PHJLOSOPHY

School ofBiological Sciences

Faculty of Science

January 2004

11 ABSTRACT

THE ECOLOGICAL CAUSES AND CONSEQUENCES OF PREY CHOICE AND ONTOGENETIC NICHE SHIFTS IN THE COMMON GOBY

Angus Charles Jackson

Foraging behaviour of the common goby, Pomatoschistus microp s was investigated in both the

United Kingdom and Sweden, with the aim of establishing causes and consequences of prey choice and ontogenetic shifts in diet. Goby life-cycle could be clearly divided into two stages, where prey choice changed abruptly from meio- to macrofauna at a standard length of30 mm.

This diet-shift maximised net energy intake rates, as illustrated by a quantitatively validated optimal foraging model. Intrinsic mechanisms were of greater importance than extrinsic factors in driving this shift. Metabolism, the primary prey choice determinant, revealed canalised and predictable diet shifts in the face of variable prey availability. This was in strong contrast to the more usual determinants such as gape limitation or extrinsic factors, such as habitat shift, prey availability and predation risk. Post diet-shift gobies consumed a range of benthic macrofauna dependent on availability. This plasticity in prey choice suggested that foraging efficiency was at some level below that expected for specialist foragers.

Translocation experiments provided support for the general assertion that learning and experience are mechanisms through which generalist foragers could improve their foraging efficiency. Ontogenetic changes in prey choice did not result in a trade-off between foraging efficiency and other ecological parameters, leading to a prediction, upheld by geometric morphometries, that there would be no change in morphology associated with this change in diet. Conditions precluding diet shifts, and the resulting consequences, were explored using mesocosm manipulations. Adult gobies prevented from feeding on macrofauna suffered reduced condition and fitness. Pomatoschistus microps is an ideal species for investigations into foraging behaviour and has provided valuable support for current foraging paradigms as well as novel insights into the causes and consequences of prey choice.

Ill CONTENTS

Copyright statement ...... i

Title Page ...... i i

Abstract ...... i i i

Contents ...... iv

Acknowledgements ...... vii

Author's declaration ...... viii

Chapter 1 Introduction ...... 1 General background ...... 1 Fish as predators ...... 1 Ontogenetic diet shifts ...... 2 Causes of prey choice ...... 3 Optimal foraging models and diet shifts ...... 6 Consequences of prey choice ...... 6 Gobies as foragers ...... 7 The common gob y ...... 8 A model species ...... 10 Study locations ...... 11 Thesis aims ...... 12 Chapter 2 Ontogenetic changes in metabolism may determine diet shifts for a sit-and-wait predator ...... 15 Introduction ...... 16 Materials and methods ...... 18 Model test species ...... 18 The foraging model ...... 18 Obtaining model parameters ...... 19 Running the model...... 24 Results ...... 24 Model output ...... 24 Model parameters ...... 27 Discussion ...... 30 Chapter 3 Consistent diet shifts in a benthic predator in the face of variable prey availability ...... 36 Introduction ...... 3 7 Materials and methods ...... 38 Ambient prey availability ...... 38 Prey consumption ...... 39 Model predictions and validation ...... 40 Tests for consistency in diet shifts ...... 4 1 Sample size determination ...... 43 Results ...... 43

lV Prey availabi I ity ...... 43 Model validation ...... 43 Consistency in diet shifts ...... 48 Discussion ...... 49 Chapter 4 Foraging plasticity and feeding efficiency in the common go by ...... 53 Introduction ...... 54 Materials and methods ...... 57 Experimental species and study sites ...... 57 Reciprocal translocation experiments ...... 57 Ambient Prey availability ...... 58 Prey consumption ...... 59 Results ...... 61 Prey availability ...... 61 Prey consumption ...... 63 Discussion ...... 67 Chapter 5 Morphometric studies on the common goby ...... 72 Introduction ...... 73 Materials and methods ...... 75 Geometric morphometries and warp analysis ...... 76 Goby morphology ...... 77 Statistics ...... 78 Results ...... 78 Effects of size ...... 78 Effects of diet ...... 81 Discussion ...... 81 Chapter 6 Fitness consequences of prey depletion for the common go by, Pomatoscltistus microps ...... 86 Introduction ...... 87 Methods ...... 88 General experimental procedure ...... 88 Experimental animals: collection and preparation ...... 89 Prey availability ...... 90 Fish condition measures ...... 9l Measurement of nest-building ...... 9 1 Nest quality determinants ...... 93 Results ...... 93 Fish diets and initial prey abundances ...... 93 Fish condition measures ...... 94 Measurement of nest-building ...... 94 Nest quality determinants ...... 96 Discussion ...... 98 Chapter 7 Discussion ...... I 01 The common goby...... 101 Causes ofprey choice ...... 102 Consequences of prey choice ...... 11 0 Conclusions ...... 113 Appendices ...... 115

V Appendix 2.1 ...... 115 Length-weight relationship ...... 115 Model parameters ...... 115 Appendix 3. 1 ...... 117 Cumulative prey curves ...... 117 Power analysis ...... ll7 Appendix 4.1 ...... 119 References ...... 120

Raw data ...... CD inside back cover

VI ACKNOWLEDGEMENTS

I am grateful to the University of Plymouth for providing financial support in the form of a doctoral studentship and to the European Commission' s Transnational Access to Research Infrastructure (ARI) scheme which provided a grant to support work in Sweden.

I thank Drs Simon Rundle and Martin Attrill for their enthusiasm and able academic guidance, assistance and encouragement throughout the project. Over and above this, I am grateful for their valued support and friendship over the last three years. In particular, I have benefited from two ofSimon's useful character traits:

his ability to say what I mean, and

that his help in the field was (almost) invariably a portent for fine weather.

Sweden: Fieldwork and studies in Sweden were greatly assisted by colleagues at the Kristineberg Marine Research Station, in particular Drs LeifPihl and Elisabet Forsgren. To the many staff, students and visitors at Kristineberg who provided numerous valuable lessons in getting the most out of life - Tack for hagkomster!

Plymouth: A big thank you goes out to AJex Fraser, Ann Torr, Julie Soane, Kerry-Anne Claughton, and Tricky Ticehurst, who all made life easier by helping out in the field and laboratory. Thanks are due to Anthony Mildmay-White and Rodney Bastard, whose kind permission to access estuaries on their land greatly facilitated some ofthe experimental work in this thesis. Peter and Jean Marsh were also enormously helpful and friendly during the studies on the Avon estuary.

Without friends, the world would be a far less wonderful place. Thank you, all of you, especially the MBERG crowd who have provided much encouragement, enlightenment, and entertainment.

Chris, Katy and Jamie Jackson all deserve much credit for their unbounded support and encouragement over the last three years and beyond, for which I am always grateful.

Thank you Rester, for sharing your love, friendship and understanding, and of course, for saymg yes.

Vll AUTHOR'S DECLARATION

At no time during the registration for the degree ofDoctor ofPhilosophy has the author been registered for any other University award.

This study was supported by a University ofPlymouth doctoral studentship and a visiting scientist grant from the European Union' s Transnational Access to Research Infrastructure

(ARI) Programme.

Relevant scientific seminars and conferences were attended, at which work was presented.

Two papers have been accepted for publication, and a further two are under review.

Publications: Jackson, A.C., Rundle, S.D. & Attrill, M.J. 2002. Fitness consequences ofprey depletion for the common goby, Pomatoschistus microps. Marine Ecology Progress Series, 242,

229-235.

Jackson, A.C., Rundle, S.D ., Attrill, M.J. & Cotton, P.A. in press. Ontogenetic changes in metabolism determine diet shifts for a sit-and-wait predator. Journal ofAnimal Ecology.

Jackson, A. C. & Rundle, S.D. in review. Foraging plasticity and feeding efficiency in the common goby. Journal ofFish Biology

Jackson, A. C. & Rundle, S.D. in review. Consistent diet shifts in a benthic predator in the face of variable prey availability. Oikos.

Conference participation and presentations: Causes and consequences of ontogenetic diet shifts in the common goby (Pomatoschistus microps). (Poster). 17th Estuarine Research Federation conference, Seattle, Washington, USA. 14th - 18th September, 2003 .

Fitness consequences of prey depletion for the common goby , Pomatoschistus microps. (Oral presentation) British Ecological Society winter meeting, University of York, York, UK. 18th - 20th December 2002.

Vlll Fitness consequences of prey depletion for the common goby, Pomatoschistus microps. (Oral presentation). First postgraduate workshop of the Marine Biological Association of the United Kingdom (MBA), Plymouth, UK. 23rd April2002.

Fitness consequences of prey depletion for the common goby , Pomatoschistus microps. (Oral presentation). 31st Benthic Ecology Meeting, Orlando, Florida, USA. 21st - 24th March, 2002.

IX CHAPTER 1

INTRODUCTION

GENERAL BACKGROUND

Successful organisms are those that survive and ensure that their genes are passed on to

subsequent generations. Aside from the intrigue and intricacies of reproduction, successful

animals must: 1) avoid being eaten, and 2) ensure that they obtain sufficient food to

survive and grow. In this thesis I am concerned with the latter, the foraging demands of

individuals. The overall aim ofthis study has been to investigate several aspects of

foraging behaviour, including how and why demands change and the consequences of

these demands. These general areas have been broken down into discrete topics, described

below and dealt with in more detail in the following Chapters. To address these various

components, I have used the common goby, Pomatoschistus microps (Kreyer, 1838) as a

test organism that is easily obtainable and maintained, and highly amenable for

experimental manipulations testing hypotheses on foraging behaviour.

FISH AS PREDATORS

All predators need to offset the energetic costs of surviving, growing and reproducing, by

catching prey. To achieve this, fish tend to be selective foragers, and have evolved a vast

array of mechanisms to meet these demands (Gerking 1994; Wooton 1998). Feeding can

be categorised by either the type of food consumed (detritivore, herbivore, carnivore etc.),

the range of food consumed (euryphagous, stenophagous etc.) or the methods used to

obtain the food (ram-feeding, suction feeding and manipulation) (Liem 1980).

Unsurprisingly, with such a variety of feeding categories, the range of prey types

consumed by fish is exceptionally broad and the morphological structures associated with feeding, equally varied. Chapter 1 - Introduction

As predators, fish can play important roles in the structuring of aquatic communities.

Predation can directly influence assemblages in two ways: by consumption of prey and by

the threat of predation altering the behaviour ofthe prey in some way. The former has

been shown to exert strong effects on biomass and size structure in freshwater and marine

environments (Underwood 1980 ~ Schmidt-Moser & Westphal 1981; Bronmark 1994)

whilst the latter has been extensively demonstrated to affect avoidance, foraging and

reproductive behaviour ofthe prey species (Sih 1987; Magnhagen 1988, 1995)

Predators can also have indirect effects on other populations in food webs through

cascading interactions at multiple trophic levels (Carpenter & Kitchell 1993). Such

interactions can again be divided into two categories: density-mediated indirect effects, and trait-mediated indirect effects (Abrams 1995; Wemer & Arnholt 1996) and examples of

both are becoming increasingly common in the literature (Paine 1980; Warwick et al.

1982; Menge & Sutherland 1987; Power 1992~ Carpenter & Kitchell 1993; Persson 1999;

Turner et al. 1999; Trussell et al. 2002; Peacor & Werner 1997 ~ Schmitz & Suttle 2001).

Prey capture not only has consequences for prey populations and lower trophic levels; it

also clearly has repercussions for the predators themselves. Prey selection, whether through active choice, driven by prey availability, or interactions such as social hierarchy,

can have major effects on survivorship, energy intake rate, growth and reproductive

success (Holbrook & Schmitt 1992; Schluter 1995; Olson 1996 ~ Hjelm et al. 2000 ~ Hjelm et al. 2001; Svanback & Eklov 2002).

ONTOGENETIC DIET SHIFTS

Dietary choice can depend on a wide range of factors and is often dictated by prey availability. Simple changes in food choice, dependent on prey frequency, are known as diet switches (Hughes & Croy 1993). In variable environments, such switches through

plastic responses in phenotype (morphological or behavioural) can maintain optimal

2 Chapter 1 - Introduction performance (Werner & Hall 1988). In contrast to frequency-dependent switches, alterations in prey consumption in response to other factors are termed diet shifts.

Amongst these factors, predator body size is one of the most important factors shaping predator-prey interactions (Peters 1983; Persson & Hansson 1999). Where a predatory animal spans a large size-range during ontogeny, there will be corresponding changes in foraging ability and metabolism, and the potential to shift from small to large-bodied prey is high (Ivlev 1961; Schoener 1971 ; Stephens & Krebs 1986).

Ontogenetic shifts in diet are important in both ecological and evolutionary terms

(Schoener 1971 ). Theoretical and empirical evidence both suggest that such niche shifts are an evolutionary solution to reduce mortality risk and increase fitness of individuals as they grow and develop (Werner & Gilliam 1984; Werner & Hall 1988). Such shifts should occur when the balance between mortality and fitness differs between available strategies, often occurring at thresholds (sensu Baton 1975) between different life stages (Sempeski &

Gaudin 1996). For some species, these shifts are not fixed in terms of timing, duration or magnitude (Grossman 1980; Werner & Gilliam 1984; Hjelm et al. 2000) and for others

(see Chapters 2 & 3), there appears to be a considerable level of canalisation (i.e. the same shift occurs despite environmental variation) (Jackson et al. in press; Jackson & Rundle in review-a).

CAUSES OF PREY CHOICE

Trait shifts such as ontogenetic changes in diet are often coupled with, or caused by, shifts in habitat (e.g. from a planktonic to a benthic existence) and can be the consequence of a wide range of extrinsic and intrinsic factors (Wainwright & Richard 1995; Persson &

Hansson 1999; Nilsson & Bronmark 2000; Persson & Greenberg 1990b). In addition to habitat shifts, the main external factors affecting prey choice are prey availability, predation risk and competition (Mittelbach 1981 ; Werner & Mittelbach 1981; Werner &

3 Chapter 1 - Introduction

Hall 1988; Persson & Hansson 1999; Hughes & Croy 1993). Predators occupying environments where these extrinsic parameters vary, are highly likely to be able to feed on different prey types (Komers 1997).

Internal mechanisms, such as morphology of feeding apparatus (Wainwright 1988), sensory ability (Walton et al. 1992), locomotory capability (Webb 1986) or some unspecified genetic component (Post & McQueen 1988) can also be responsible for changes in diet. The mechanism by which physical limits of morphology can restrict prey choice (e.g. through gape limitation) is easily understood (Mittelbach 1981 ; Townsend et al. 1986; Wainwright 1988; Nilsson & Bronmark 2000; Timmerman et al. 2000) but the influence of other parameters linked to body size, such as capture rate and metabolism, on prey selection is less clear cut.

Observed changes in prey choice are presumably adaptive and function to increase fitness by improving energy acquisition and reducing predation risk (Schultz et al. 1991; Conover

L992 ; Schluter 1995). Where species inhabit environments with high variability in abiotic and biotic factors (e.g. prey availability), such as shallow coastal waters and estuaries, prey choice has potential consequences for organismal fitness (Chapter 6). Some diet shifts are of particular interest in that they occur without a concomitant change of habitat. The studies in Chapters 2 & 3 show that such diet shifts in the absence of habitat shifts, can also occur without being driven by a change in predation risk. In such cases, where external drivers appear to play little role in determining prey choice, internal mechanisms must be given due attention. For predators that swallow prey items whole, physical constraints to ingestion are a distinct possibility, and prey choice could be driven by morphological thresholds (Nilsson & Bronmark 2000). The potential for other internal parameters, such as visual acuity, locomotory ability and scope for activity (metabolic capacity) playing a role in prey choice shifts is discussed in Chapters 2 & 3.

4 Chapter J - Introduction

Behavioural decisions are not just made on an ontogenetic basis and choices will also be adaptive withjn size-specific constraints. Many studies investigate the conditions surrounding the level of flexibility or plasticity in foraging behaviour expressed by a particular size of predator (Steams 1989; Komers 1997; Relyea 2001; Mittelbach et al.

1999; Hegrenes 2001 ). Wimberger (1992) suggests that organisms using only their mouth to handle food are more likely to show a greater degree of phenotypic variation, so fish are ideal organisms for addressing questions about behavioural plasticity. Trus behavioural plasticity may be determined genetically, induced by environmental conditions or by some epigenetic interaction (Adams et al. 2003).

Where environments vary spatially and temporally (see below), flexjbility will clearly be an adaptive feature of resource exploitation, and optimal foraging theory predicts reduced selectivity, i.e. increasing generalisation (Pyke et al. 1977; Komers 1997). Behaviours used to deal with a range of conditions benefit from generality of application, but suffer from reduced efficiency (Laverty & Plowright 1988). In contrast, in environments where differences in resource availability are constant, predictable and non-limiting, variations in behaviour can be subject to divergent selection, resulting in some degree of specialisation and increased efficiency.

Predators consuming a wide range of prey types may do so because they are true generalists with highly plastic foraging allowing them to respond rapidly to environmental conditions, or because local specialisation occurs within populations. Specialist predators are highly efficient foragers on their particular prey and perform less well when exposed to novel prey types, whereas generalist predators gain from breadth of application at the cost of lower efficiency. Learned behaviours can have appreciable effects on foraging efficiency and can help to limit costs associated with generalist foraging (Hughes &

O'Brien 2001 ; Chapter 4).

5 Chapter 1 - Introduction

OPTIMAL FORAGING MODELS AND DIET SHIFTS

Given that acquisition of energy from food is essential for all non-autotrophic biological processes, it is a fair assertion that efficiency in obtaining food is positively linked to fitness. Since natural selection favours the maximisation of fitness, foraging behaviour must be adaptive (Hjelm & Johansson 2003). Behaviour can be broken down into

'decisions' between alternatives and so some combination of decisions must result in optimisation ofthat behaviour. Optimality theory has developed on the assumption that behaviour must maximise some currency, usually the rate of net energetic gain. As a widely observed phenomenon, ontogenetic diet shifts have provided an interesting basis for the application of foraging models (Werner & Mittelbach 1981; Persson & Greenberg

1990b ). Optimality theory, when applied to diet shifts, can provide predictions of diet that are accurate in terms of diet breadth, but often have some time Jag or occur at different rates (Mittelbach 1981 ; Osenberg & Mittelbach 1989; Chapter 3; Persson & Greenberg

1990b).

CONSEQUENCES OF PREY CHOICE

Variability in environmental parameters can affect an organism' s performance and, in such instances, selection should favour trait shifts that limit reductions in fitness. Reduced fitness may be ameliorated, for example, through temporal changes in morphology (Hjelm

& Johansson 2003) or by some form of environmental partitioning, such as temporal or spatial separation of resource use (Schoener 1983 ; Piatell et al. 1998a, b). With predators exhibiting differences in choice, prey selection may generate appreciable effects on energy gain (lvlev 1961; Werner & Hall1974; Wemer & Mittelbach 1981; Scharfet al. 1998;

Sherwood et al. 2002), growth rate (Oison 1996; de Roos & Persson 2001), time availability (Rovero et al. 2000) and predation risk (Mittelbach 1981 ; Persson &

Greenberg 1990b; Nilsson & Bronmark 1999).

6 Chapter l - introduction

Some drivers of prey choice can result in obvious trade-offs between foraging efficiency and survivorship, for example through competition or predation risk (Wemer & Hall 1988 ;

Svanback & Eklov 2003). Prey capture and consumption are often influenced by physical characteristics and thus, morphology and foraging efficiency are closely related

(Wainwright 1988; Schluter 1993). These trade-offs may then arise through physical limitations to foraging since morphology efficient for one feeding mode is unlikely to provide equal efficiency for other modes. ln such situations, there will be selective pressure for this compromise to be reduced through morphological changes following the diet shift, which increase foraging efficiency (Svanback & Eklov 2002, 2003). Where diet shifts occur without a trade-off being induced, there may be less selection for morphological change. Developments in morphological studies over the last decade have given rise to a suite of techniques called geometric morphometries' that compare outlines and landmarks of samples (Rohlf & Marcus 1993). These techniques can be used to measure changes in morphology causing or caused by changes in diet (Hjelm et al. 200 I;

Svanback & Eklov 2002, 2003; Chapter 5)

Given the variable nature of the environments inhabited by many fish, the conditions allowing a diet shift to occur, may not be present; a predator making a shift to a new prey resource cannot do so if that resource is not available. Recruitment of prey species can be highly variable (Moller & Rosenberg 1982, 1983), resulting in prey availability that may restrict or prevent ontogenetic diet shifts from occurring. Such variability must have potential consequences for predators.

GOBIES AS FORAGERS

The Gobiidae are a large family (- 1,800 species) of small teleost fish of inshore marine and brackish water habitats (Miller 1986). They primarily occur in tropical and warm temperate regions but 19 species have been recorded from northern European waters

7 Chapter I - Introduction

1986). The most common and abundant gobies in northern Europe belong to the genus

Pomatoschistus Gill, which contains several very similar species, viz. Pomatoschistus

microps, P. minutus, (Pallas, 1770) and P. pictus (Maim, 1865) (Edlund et al. 1980).

Pomatoschistus minutus, previously recorded as a single species, is now recognised as a

complex of three; P. minutus, P. lozanoi (De Buen, 1923) and P. norvegicus (Collet, 1903)

(Webb 1980).

The common goby

Appearance

Pomatoschistus microps, formerly Gobius microps. is highly cryptic. ln general

appearance it is sandy or grey in colour, with darker spots or bars laterally; this crypsis is

enhanced through burying in the sediment (Magnhagen 1995). The species is relatively

small, with a maximum recorded length of 70 mm (Wheeler 1969), although a more

typical adult size is ea. 50 mm. Individuals have a large, heavy, somewhat depressed head

with large eyes, on a moderately elongate, sub-cylindrical body, possessing a weak

suctorial disk formed by the fusion of the pelvic fins, a notable characteristic of the family

(Miller 1986) (Fig. 1.1).

10 mm Figure 1.1. The common goby, Pomatoschistus microps in adult male colouration.

Habitat and distribution

Pomatoschistus microps is a highly abundant, euryhaline, epi-benthic predator in shallow,

coastal waters such as estuaries (Schmidt-Moser & Westphal 1981; Pihl & Rosenberg

8 Chapter 1 - Introduction

1982· Miller 1986). The typical substrata frequented by this species are soft sediments consisting of fine gravel, sand, mud and silt (Green 1968; Miller 1975). Pomatoschistus microps is recorded as using open areas in preference to vegetated habitats, possibly through exclusion by the larger and socially superior sand goby, P. minutus (Magnhagen &

Wiederholm 1982b; Wiederholm 1987). Pomatoschistus microps is very similar toP. minutus and there is some habitat overlap, although the former tends to occur in shallower waters and lower salinities (Edlund et al. 1980; Pihl & Rosenberg 1982). Distribution in the north-eastern Atlantic extends from Trondheimfjord in Norway, south to southern

Portugal and Atlantic Morocco, the Baltic Sea and the north-west Mediterranean (Wheeler

1969; Miller 1986).

Foraging behaviour and diet

Gobies are typically sedentary species and use a sit-and-wait foraging mode, waiting for suitable prey to present itself, rather than actively searching for food. Prey are pounced upon and engulfed using suction developed by opening the large mouth. If not small enough to be swallowed immediately, the prey is manipulated until a suitable orientation is achi eved (Magnhagen & Wiederholm 1982a).

Pomatoschistus microps, as an inhabitant of environments that are highl y variable, particularly in terms of their prey assemblages (Moll er & Rosenberg 1982, 1983) and is recorded as feeding on a wide range of macrofaunal prey, depending on availability, location and season (Green 1968; Healey 1972; Zander 1979; Magnhagen & Wiederholm

1982a, b; Zander & Hartwig 1982; Magnhagen 1985). Gobies in general are noted as undertaking an ontogenetic diet shift from small to larger prey items (Gee 1989) and various studies indicate that P. microps is no exception with a shift from feeding on benthic copepods to macrofaunal prey (Pihl 1985; Doornbos & Twisk 1987; del Norte­

Campos & Temming 1994).

9 Chapter l - Introduction

Predators

Pomatoschistus microps has a variety of predators, including piscivorous birds (kingfisher, cormorants, herons, egrets and terns), fish (salmon, trout, juvenile cod, bass) and seals

(Magnhagen 1988; Hamerlynck & Cattrijsse 1994 and references therein; Magnhagen &

Forsgren 1991).

Life hist01y

The common goby is a short-lived species, rarely surviving a second winter (Miller 1975;

Fouda & Miller 1981 ; Bouchereau & Guelorget 1998). An extended summer breeding season, with repeated spawning events, gives rise to a protracted recruitment and a bimodal size-frequency distribution. Rapid growth of recruits soon causes overlap in generation size and the loss of the older_generation in late autumn returns the population to a single age-group (Jones & Miller 1966; Fouda & Miller 1981). There is some evidence for a temperature-driven downstream or sub-tidal migration in winter (Jones & Miller 1966), potentially resulting in occupation of different habitats and consumption of different prey.

Males are responsible for all parental care, building and maintaining nests in empty bivalve shells in which the female lays the eggs.

A model species

Pomatoschistus species have become popular in ecological studies for a variety of reasons.

They are widespread and abundant in shallow coastal waters and estuarine ecosystems, form a major component offood webs and are easily accessible (Green 1968; Doornbos &

Twisk 1987). Their small size makes them eminently suitable for field studies, including in situ experimental manipulations (Chapters 3 & 4). Gobies are easy to maintain in the laboratory and so investigations under more controlled conditions are also possible

(Magnhagen 1985; Jones & Reynolds 1999a; Chapter 2, 6). Of particular note is the behavioural plasticity of P. microps and P. minutus in response to abiotic and biotic

10 Chapter 1 - Introduction variability (Edlund & Magnhagen 1981 ; Magnhagen & Wiederholm 1982a, b; Magnhagen

1986, 1988).

Investigations on the trophic ecology of gobies have been very productive, in terms of general foraging behaviour (Zander & Berg 1984; del Norte-Campos & Temming 1994), for ecological determinants of foraging behaviour (Magnhagen & Wiederholm 1982a, b;

Magnhagen 198 5), and for the consequences of predation (Berge & Hesthagen 1981 ;

Schmidt-Moser & Westphal 1981 ; Evans 1984; Doornbos & Twisk 1987; Zander &

Hagemann 1987) to list a small selection.

Being highly fecund, having a long breeding season and displaying complex and varied breeding behaviours, goby reproductive biology has also received much attention (Rogers

1988; Bouchereau et al. 1990; Magnhagen 1992; Bouchereau & Guelorget 1998; Reynolds

& Jones 1999; Borg et al. 2002). A further aspect of behavioural studies on these fish has been the role of predators in behavioural determination (Magnhagen 1988, 1995; Forsgren

& Magnhagen 1993 ; Forsgren 1992; Magnhagen & Forsgren 1991). So, not only doesP. microps display interesting characteristics in its own right, it is also a highly tractable research organism for hypothesis testing.

STUDY LOCATIONS

The studies in this thesis deal with P. microps from two locations: the South Devon coast,

UK and the outer Gullmarsfjord, Sweden (Fig. 1.2). Both are shallow coastal waters, but differ markedly in biotic and abiotic character. In South Devon, I investigated gobies from the upper estuarine reaches of the Rivers Yealm and Avon where tidal range is of the order of two metres, covering mudflats at high tide and receding into narrow channels at low tide. Salinity is highly variable (0-30) and water temperature varies between 7-18 °C

(Arshad 1999). In the micro-tidal Gullmarsfjord on the west coast of Sweden, water levels

11 Chapter l - Introduction are much more constant, although variation in air pressure can affect water coverage in shallow areas. Salinity fluctuates less than in the estuarine sites ( 18-25 in summer), but temperature range is greater with shallow waters sometimes freezing in winter and reaching 24 °C in summer. In addition to differences between sites, intra-site variability in biotic and abiotic terms is also an important factor. Estuaries and shallow coastal waters are renowned as being highly dynamic and stochastic environments. As noted above, abiotic conditions range widely and biotic conditions frequently respond to this, at a range of temporal and spatial scales. Go by populations are observed to fluctuate strongly (Pihl &

Rosenberg 1982), benthic faunal abundance can be highly variable (Moller & Rosenberg

1982, 1983; Rundle et al. 1998), and predation pressure can also vary between sites (Pihl

& Wennhage 2002).

THESIS AIMS

The overall aim of this thesis was to address the causes and consequences of prey choice and ontogenetic shifts for the benthic predatory fish, P. microps. This species consumes a range of prey and the potential determinants of prey choice are varied. A range of classical and novel techniques were used to investigate what gobies feed on through their development and why. I did not deal with the direct or indirect effects of predation on prey populations but considered, rather, the repercussions of prey choice from the point of view of the predator. The common goby has been the subject of extensive studies on foraging and reproductive behaviour (see above). This background information, along with the common goby' s tractability as an experimental organism, makes it ideal for addressing ecological questions. More specifically, the areas of cause and consequence in foraging behaviour are broken down into testable hypotheses, addressed in the subsequent Chapters and outlined below.

12 Chapter 1 - Introduction

Devon

Figure 1.2. Study locations (red dots) from Skafto island, Gullmarsfjord, Sweden and South Devon estuaries, UK.

0 3000m English Channel I 0 500m 13 Chapter l - Introduction

Chapter 2 is concerned with the application of optimal foraging theory to common goby prey choice. Here I tested the hypothesis that gobies were optimal foragers, maximising energy gain rate on either side of an ontogenetic prey shift. A basic prey model (Charnov

1976; Mittelbach 1981 ), parameterised by prey encounter rates, handling times, energy gain and metabolic costs, was used to predict optimal diets and the location of ontogenetic diet shifts based on ambient prey availability.

Chapter 3 validates the model constructed in Chapter 2, using quantitative field data. I examined the relative roles of internal and external drivers in goby prey choice and tested whether internal mechanisms provided consistent results in the face of extrinsic variability.

Novel techniques for assessing the accuracy of model predictions were also developed.

In Chapter 4, I moved on from ontogenetic considerations to investigate plasticity of foraging behaviour in adult gobies. Specifically, I used reciprocal translocation experiments to test whether there were differences in feeding efficiency between naive and experienced gobies foraging on different prey assemblages and investigated the role of learning as a modifier of plastic foraging behaviour.

In Chapter 5, I applied recently developed morphometric techniques to assess morphological change associated with diet shifts and investigate whether the absence of trade-offs with foraging efficiency removed the drive for a change in morphology.

In Chapter 6, I used manipulative mesocosm experiments to test whether the absence of macro fauna affects body condition and fitness, i.e. whether there were consequences of not exhibiting a diet shift. Nest building by adult males was used as a fitness surrogate.

14 CHAPTER2

ONTOGENETIC CHANGES IN METABOLISM MAY DETERMINE DIET SHIFTS FOR A SIT-AND-WAIT PREDATOR

Part of this Chapter has been published as

Jackson, A.C., Rundle, S.D., Attrill, M.J. & Cotton, P.A. in press. Ontogenetic changes in metabolism may determine diet shifts for a sit-and-wait predator. Journal ofAnimal Ecology.

15 Chapter 2 - Does metabolism determine diet shifts?

INTRODUCTION

Predator body size is one of the most important factors shaping predator-prey interactions

(Peters 1983; Persson & Hansson 1999). Where a predatory animal spans a large size range during ontogeny, there will be corresponding changes in its foraging abilities and metabolism. Plastic responses in phenotype (physical or behavioural) can maintain optimal performance in variable environments and may be manifested as changes in diet

(Werner & Hall 1988). The positive correlation between prey size consumed and ontogenetic increase in predator size is a basic ecological tenet (Mittelbach 1981 ; Peters

L983) . Fish, in particular, may increase in size by several orders of magnitude from hatching to adulthood (Werner & Hall 1988), giving large scope for changes in prey choice

(e.g. Bodiou & Villiers 1979; Grossman et al. 1980; Mikheev & Wanzenbock 1999;

Aarnio 2001; Keeley & Grant 2001).

Size restrictions to prey choice are patent (Mittelbach 1981 ; Townsend et al. 1986;

Wainwright 1988; Nilsson & Bronmark 2000; Timmerman et al. 2000) but how other correlates of body size, such as capture rate and metabolism, affect prey selection is less apparent. Ontogenetic shifts in diet tend to be coupled with, or caused by, shifts in habitat

(e.g. from a planktonic to a benthic existence) often driven by a distinct change in lifestyle

(Gee 1989; Aarnio 2001 ), prey availability (Whiteside et al. 1985) or predation risk

(Werner & Gilliam L984). With predators of different sizes exhibiting different preferences in size of prey consumed, the consequences of selection may be considerable in terms of energetic advantage (Ivlev 196 1; Werner & Hall 1974; Werner & Mittelbach

198 1; Scharf et al. 1998; Sherwood et al. 2002), growth rate (Oison 1996; de Roos &

Persson 2001), time availability (Rovero et al. 2000) or predation risk (Mittelbach 198 1;

il sson & Bronmark 1999; Persson & Greenberg 1990b). Given the importance of foraging behaviour, it is not surprising that considerable attention has been paid to the

16 Chapter 2- Does metabolism detenuine diet shifts? determinants of prey preference. As a widely observed phenomenon, ontogenetic diet shifts have provided an interesting basis for the application offoraging models (Werner &

Mittelbach 1981; Persson & Greenberg 1990b ). Most previous tests of diet shifts are those concurrent with a change in habitat or driven by some external influence and have involved only predators that actively search for their prey (except Charnov 1976). Less frequent are observations of ontogenetic shifts in diet without any change in habitat (Horinouchi &

Sano 2000). Internal reorganisation, such as changes in morphology, e.g. dentition

(Wainwright 1988) or gape size (Timmerman et al. 2000), sensory ability (Walton et al.

1992), locomotory capability (Webb 1986) or some unspecified genetic component (Post

& McQueen 1988) can cause, as well as arise from, diet shifts. Although such internal mechanisms are no doubt important in diet shifts, I am unaware of studies whereby they have been reported as the primary element responsible for shifts in prey selection.

Here I describe the behavioural parameterisation and application of an optimal foraging model (Charnov 1976), to laboratory and field data on Pomatoschistus microps. Given the previous successful application offoraging models to diet choice, I wished to explore whether the technique could be extended to predict diet shifts driven by internal mechanisms such as metabolic constraints, rather than by external drivers such as change in habitat use. I also tested whether P. microps, as a sit-and-wait predator, used a cost minimisation foraging strategy rather than rate maximisation, typically applied in optimal foraging models This diet shift is of particular interest as it appears to be constrained between prey from ecologically distinct size classes, i.e. meiofauna and macrofauna, typical of benthic aquatic systems (Warwick 1984; Schwinghamer 1981 ).

17 Chapter 2 - Does metabolism detennine diet shifts?

MATERIALS AND METHODS

Model test species

The habitat and foraging ecology of P. microps, described in Chapter I, indicates that it is an ideal species for investigations into ontogenetic shifts. Following dispersal and adoption of a benthic habit, P. microps shows no further distinct shifts in habitat, no further metamorphosis nor any apparent change in predation risk; but prey selection changes dramatically. Juveniles feed on meiofauna, primarily harpacticoid copepods (Berge &

Hesthagen 1981; Pihl 1985; Doombos & Twisk 1987). This diet is maintained until the gobies reach a length of ea 30 mm when there is a prey shift to macro fauna such as

Corophium volutator (Pallas), Nereis diversicolor (Muller) and chironomid larvae (Healey

1972; Magnhagen & Wiederholm 1982a). Prey availability fluctuates considerably in benthic habitats (Moller & Rosenberg 1982) with consequences for goby fitness demonstrated in Chapter 6, but this is not linked with the timing of observed diet shifts

(Jackson et al. 2002). Previous foraging behaviour studies on P. microps have been mainly limited to adults (Zander 1979; Magnhagen & Wiederholm 1982a, b; Zander &

Berg 1984; Magnhagen 1986). In this study, consideration of foraging behaviour over a wide range of goby sizes provided a valuable opportunity to explore the importance of internal mechanisms in regulating prey choice through ontogeny.

The foraging model

Given the wide range of prey sizes consumed and apparent ontogenetic differences in selection, I considered the most appropriate prey model to be that of Charnov ( 1976), adapted by Mittelbach (1981) for shifts in sunfish foraging behaviour. This model has been successful in the qualitative prediction of prey selection through diet shifts with ontogeny and is as follows:

18 Chapter 2 - Does metabolism detennine diet shifts?

eqn 2.1

1 where E is the energy obtained (J), t is time (s), ;., is capture rate of prey, (items s' ), A is

assimilable fraction of energy, e1 is energetic content ofprey i (J), eh is handling cost

1 (J s·\ H1 is handling time for prey, (s), and C is the cost of searching (J s' ). A has been assumed constant at 0.7 (EIIiott 1976). Where a particular energy requirement is known, for example for maintenance and growth per day, this equation can be rearranged to determine the prey item selection that will minimise the time required to obtain that energy. 1 obtained all of the required model parameters either from existing values (i.e. respiration rates from Fonds and Veldhuis (1973) and growth rates from Doombos &

Twisk (1987)) or through laboratory and field experiments (see below). Parameterisation of the model was carried out using meiofauna (benthic Copepoda and Ostracoda) and

different sized macrofauna (eorophium) as separate prey types and values for e1, J. 1, H1, eh and C established for a range of goby sizes. Prey types were ranked in order of decreasing profitability (Ae, !H, -eh) and added to the model sequentially until Elt was maximised

(Mittelbach 1981 ). Clearly, the most profitable item should always be selected and less profitable items included only if doing so increased the net rate at which energy was obtained. Thus, the range of prey items giving maximal net energetic return constitutes the optimal diet for a given size of goby.

Obtaining model parameters

Handling times

Handling times for gobies consuming eorophium were obtained through simple feeding trials. Gobies of a range of sizes from the upper estuary of the River Avon, Devon, UK were maintained in the laboratory in holding tanks at 16 °C, salinity 15, for two weeks and fed a mixture of pellet and flake. In order to standardise hunger before trials, gobies were

19 Chapter 2 - Does metabolism determine diet shifts? deprived of food for 24 hours. At the start of a trial, a goby was introduced to a circular tank (0 IS cm) and allowed to settle. Feeding behaviour was video recorded from above, commencing on the introduction of an individual Corophium and ending after the last swallowing action (gaping and operculum flaring). Each goby was used in only one feeding trial to prevent decreases in handling time by learning through experience. Croy &

Hughes (199lc) demonstrated that behaviours modified by learning may not be retained indefinitely, so feeding behaviour modified by experience prior to capture is likely to have been forgotten following two weeks maintenance on artificial food. In addition, there are some indications that P. microps retains no search image following removal of the prey type (Magnhagen & Wiederholm 1982a) but see also Chapter 4. Handling times were therefore assumed to be representative of naive fish. As wide a range as possible of relative prey predator sizes was used, for gobies between IS and 45 mm in length.

Handling times (H;), were measured (to 0.1 s) using the Observer Video-Pro package for behavioural observation analysis (Noldus Information Technology, Wageningen, The

Netherlands). To determine the effect of relative predator and prey size on handling time, handling time was plotted against the prey volume:goby volume ratio. Prey volumes were calculated using length and width measurements, assuming simple cylindrical body forms

(Winberg & Duncan 1971 ). Mean copepod size was derived from published values

(Widbom 1984). Similarly, goby volumes were approximated to a cone using standard length and maximum width measurements. Observing and recording consumption of meiofauna was not possible due to an inability to see the prey item in situ. As meiofauna:goby volume values were all within one order of magnitude of the lowest

Corophium:goby volume values, meiofauna handling-times were calculated by applying a mean meiofauna length (O.S mm) to the regression equation derived from Corophium handling-times. I justify the use of this approach since handling times can be assumed constant below a critical value of prey to predator size (Schoener 1969). 20 Chapter 2 -Does metabolism detennine diet shifts?

Capture rates

Field experiments were conducted to establish realistic rates at which gobies of different size capture prey of different size and density. Capture rate was the mean number of prey ingested per unit search time, obtained by dividing the number of prey in the gut by the total foraging time minus total handling time (Mittelbach 1981 ). Nine enclosures were set out on mud flats in which sediment fauna was manipulated (see below). An upper estuary site of homogeneous fine sediment was chosen on the River Avon. Enclosures were plastic tanks (40x20x25 cm, lxbxh) with the base removed, pushed down 10 cm into the sediment ensuring that water was retained within during the whole tidal cycle. The enclosures were covered by fine nylon netting (ea. 250 !J.m mesh) held in place with elastic cord.

Macrofauna capture rate

All sediment (to 5 cm depth) was removed from enclosures, passed through a 500 !J.m sieve to remove macrofauna, bagged, and frozen for 24 hours to kill remaining fauna. After defrosting, the sediment was returned to the nine enclosures and left for 48 hours before being seeded with Corophium at various density-size combinations. Corophium were obtained by passing sediment from the same estuary site through a 500 !J.m sieve. Large

(5-7 mm) and medium (3-4 mm) Corophium were used at densities of 500, 1000 and 2000

2 2 m· and small Corophium (1-2 mm,) at 1000, 2000 and 5000 m- , typical ofthe range found in the natural environment (Moller & Rosenberg 1982). Corophium were left for 24 hours to establish burrows before feeding trials commenced. At least I 0 gobies (size range

15-45 mm), in separate trials, were used for each combination of prey density and size.

Meio.fauna capture rate

For meiofauna capture-rate trials, the enclosures were relocated to adjacent sediment and since, for the purposes of goby predation, meiofaunal size was considered constant, only

21 Chapter 2 - Does metabolism determine diet shifts? prey density was manipulated. Three replicates of three densities were used: low (22,000

2 2 m" ); ambient (33,000 m·\ and high (56,000 m" ). Sediment manipulation consisted of removing all sediment from the enclosures to a depth of 5 cm and passing through a 500

11m sieve to remove macrofauna before being returned to the enclosure. For the low density treatment, only half the area of sediment was sieved, the remainder being discarded and, for the high density treatment, an additional equal area of sediment was sieved and added to the enclosure. Core samples established meiofauna (Copepoda and Ostracoda) densities following this manipulation. At least 30 gobies (size range 12-46 mm) in separate trials were used for each prey density.

Feeding trials

Gobies for all· capture rate trials were caught at low tide the previous day using a small seine net (2 mm mesh) and maintained, without food, in a tank with a fine mesh cover held on the mud flat. Trials were conducted at low tide with enclosure covers removed. Two gobies were introduced to each enclosure and allowed to forage for two hours before being removed, sacrificed by overdose of anaesthetic (MS222), destruction of the brain, and fixation in 4 % formaldehyde. Gut content was examined to determine the number of prey items ingested. Water temperature in the enclosures varied between 10 - 18 oc and salinity between 5-25. As prey capture rates (C) were functions of goby size (L), prey size available (/) and prey density (D), stepwise multiple regression on these variables and their log transforms was used to investigate which combination provided the best prediction.

The handling time trials were used to provide an assumption about the limit of the relative prey sizes consumed to be included in the capture rate models.

Respiration and energy requirements

Previous studies allow predictions of oxygen consumption by gobies under given conditions (Fonds & Veldhuis 1973). Since P. microps uses a 'sit and wait' mode of

22 Chapter 2 -Does metabolism detem1ine diet shifts? foraging (Magnhagen 1986), oxygen consumption rates (as surrogates of standard respiration rate) were used to represent 'searching' gobies and active respiration rates used for catching and handling prey. Respiration calculations all assume a temperature of 15

°C, typical of water where P. microps is found. Oxygen consumption for resting gobies in relation to body mass was calculated using data from Fonds & Veldhuis (1973) (see

Appendix 2. I) thus permitting calculation of mass-specific standard respiration rates.

Active respiration rates were derived as follows. Maximal oxygen consumptions per gram of goby in relation to temperature were calculated (Fonds & Veldhuis 1973) (see Appendix

2. I), to which was applied the slope of the mass-specific standard respiration rate to weight relationship. This gave the mass-specific active respiration rate to weight relation and from this, I derived the active respiration rates for different sized gobies. The key assumption here is that the rate of change of mass-specific respiration rates is the same for standard and active respiration. Factorial scope for activity (defined as maximal respiration rate/standard respiration rate), has previously been noted as being mas independent (Wieser & Forstner 1986) i.e., the slopes of change in mass-specific standard and active respiration rates are equal. Factors used to convert derived units to Js- 1 are provided in Doornbos & Twisk (1987) and Schmidt-Nielsen (1997)

Doornbos & Twisk ( 1987) developed a method for calculating the total daily food mass requirements ofgobies. From this 1 derived a modified method (equation 2.2) incorporating ontogenetic changes in respiration rate (at 15 °C), to obtain the daily energy requirements (E) in J d·' rather than food mass intake:

0 016 24 E = (1.5oDW X a)+ kWb X · X X 22.4 X 20 08 eqn 2.2 32

Where bDW is daily growth (mg dry weight, derived from daily length increments

(Doornbos & Twisk 1987), a length-weight relationship (see Appendix 2.1) and a dry

23 Chapter 2 - Does metabolism dctenninc diet shifts? weight:fresh weight proportion of0.2 (Rumohr et al. 1987)); a is average energetic content of goby prey items (20 Jmg- 1 DW, Rumohr et al. ( 1987)); and W is fresh weight of fish (g) with k and b being constants (see Appendix 2.1 ). This provided the total daily energy requirement for growth and maintenance for gobies over a range of sizes. These values were then used to determine (using a rearrangement of equation I) how long it would take to obtain this requirement when feeding on different ranges of prey sizes.

Running the model

In order to obtain predictions from the model, samples of benthic fauna were collected in the summer of2001 from three sites in the Gullmarsfjord on the Swedish west coast

(Bokevik, Salvik and Kilviken), where gobies were abundant. Five replicate cores for meiofauna (0 2.9 cm, 5 cm depth) and macrofauna (0 10 cm, 5 cm depth) were taken on each of eight consecutive weeks from each site. Prey were divided into millimetre size classes ( 1-1 0 mm) and the mean size-frequency distribution data (see Appendix 2.1) for these prey populations were used to predict capture rates and, hence, the range of items to be included in the optimal diet. When prey items are ranked in order of decreasing net energetic return per handling time (profitability) and added sequentially to the model, the optimal diet is specified where net energetic gain is maximised. A knowledge of the optimal diet breadth and the relative abundances of sampled prey within this diet allowed the calculation of predicted mean prey size consumed for a given fish length.

RESULTS

Model output

Using the premise that an optimal diet will be one that maximises the net energetic gain rate, I calculated the optimal diet for P. microps using equation I and typical values for model parameters are provided (Table 2. I). Predictions of mean prey length in the optimal diet, based on available prey densities and their size-frequency distributions (see Appendix

24 Chapter 2 - Does metabolism determine diet shifts?

2. I), illustrated strong variation between size classes, there being a dramatic increase in the

predicted length of prey consumed by gobies >30 mm (Fig. 2.1). Mean length was

determined by the range of prey sizes in the diet and consequently this also differed

between size classes. For gobies >30 mm in length, predicted energy gain rates decreased

if meiofauna were included in the diet. Prey items that reduce energy gain rate will not

form part of an optimal diet and the increase in mean prey length was a consequence of

exclusion of meiofauna from the diet. This diet shift from meiofauna to macrofauna

allows the maximisation of energy gain rate over the range of P. microps sizes considered

here.

Table 2.1. Energetic costs, prey energy content, handling time and profitability for a range ofgoby sizes. Meiofauna length is 0.5 mm. Handling times represented by a dash indicate prey that were too large to be consumed by gobies of that length. Goby Search costs Handling costs Prey Energy Handling Prey length (C) (Ch) length content (e;) time (H;) profitability 1 5 {mm} ps-1 x 10-52 {Js- X I o- 2 {mm} {12 {s} {Ae; IH; -Ch} meiofauna 0.04 4 0.01 2 0.98 4.8 0.20 20 101 1.66 4 6.78 0 6 21.02 0 meiofauna 0.04 4 0.01 2 0.98 4.5 0.22 30 2.99 4.94 4 6.78 5.7 119 6 2102 11.4 184 meiofauna 0.04 4 0.01 2 0.98 4.4 0.22 40 6.49 10.70 4 6.78 4.8 1.41 6 2102 6.2 3.39

Calculation of daily energy requirements (equation 2), allowed me to determine the time

required to consume diets containing different ranges of prey size, indicating whether or

not such hypothetical diets could provide sufficient energy in the foraging time available.

examined the role of meiofauna in the acquisition of daily energy requirements. Assuming

a generous daily foraging window totalling 12 hours (accounting for daylight and tides),

25 Chapter 2 - Does metabolism determine diet shifts?

--- 6 Es "-' 5 .£j b.J) ~ Q) ...... 4 >... Q) 1-o 0.. 3 § Q) E 2 "'d Q) ~u -o- Kilviken ·~ l '"d --D- Bokevik Q) 1-o ----l:!r-- Salvik ~ 0 15 20 25 30 35 40 Fish length (mm)

Figure 2.1. Predicted mean prey lengths for different size classes of Pomatoschistus microps from three sites on the west coast of Sweden. Predicted values are derived from equation 1 and ambient size frequency distributions of sediment prey species. An ontogenetic shift in diet is clearly illustrated by the rapid increase in mean prey length occurring between 27 and 32 mm in length.

gobies < 17 mm cannot accrue their daily energy requirements when meiofauna are excluded from the diet (Table 2.2, boxed cells). Conversely, gobies >17 mm did not require meiofauna to meet their daily energy budget. This pattern did not tally with observed changes in P. microps diet from the natural environment, where meiofauna constitute the main dietary component up to a length of30 mm. For gobies >30 mm, including meiofauna in the diet increased the time required to obtain the daily energy requirements (Table 2.2, shaded cells).

26 Chapter 2 - Does metabolism determine diet shifts?

Table 2.2. Model predictions for the total foraging time (t, hours) necessary to obtain daily energy requirements for P. microps of different lengths from three sites. Two scenarios are provided, one for time required on consumption of an optimal diet and another for an adjusted diet. Optimal diet predictions indicated the goby length (30 mm) beyond which meiofauna were no longer included. For the adjusted diets, I used optimal diet minus meiofauna (gobies <30 mm, clear cells) and optimal diet plus meiofauna (gobies >30 mm, shaded cells). The inclusion ofmeiofauna in the diet increased foraging time for gobies >30 mm. Boxed cells indicate goby lengths where exclusion of meiofauna from the diet results in a failure to obtain daily energy requirements. Time (hours) Go by Bokevik Salvik Kilviken length 17 22 27 32 37 17 22 27 32 37 17 22 27 32 37 (mm) Optimal 5.7 4.3 3.4 2.5 1.8 6.7 5.5 3.7 2.5 1.5 9.0 4.9 3.3 2.3 1.4 diet Adjusted 12.4 5.2 3.6 b.e t.~ diet ~ -:<·:· .wr~

Model parameters

Handling time

The prey:goby size handling-time relationship (Fig. 2.2) was derived using an exponential regression and can be represented by equation 3 as:

H = 4 346 e 6s 63sv I . eqn 2.3

2 where His handling time (s) and vis the prey:goby volume ratio (n=74, r =0.37, F 1, 72 =

43 .59, p

Consequently, meiofauna handling times were obtained by extrapolation of the Corophium handling time relationship and a constant value of 4 s was used for all meiofauna.

27 Chapter 2 - Does metabolism determine diet shifts?

30

25 •

~ {/) • ~ Q) 20 • a • • ·--+-J ... b1) 15 • • ~ • ·--""d • • ~ 10 • C\:1 • • • • • ::c • • • • • • •• 5 •• • • •• • • • ' • • ••• • • • • • • 0 10-5 1o- 4 10-3 10-2 10-1 Prey volume:goby volume Figure 2.2. Handling-time relationship for Pomatoschistus microps feeding on Corophium volutator showing handling-time against the prey volume:fish volume ratio (p

Capture rate experiments

Handling trials indicated that gobies would not consume items with a prey: predator volume ratio greater than 0.026 (Fig. 2.2). This was taken into account when predicting capture rates for Corophium (i.e. macrofauna), with the best-fit model having the form:

Both complete regressions were significant, as were all variables within each regression.

Regression constants, fit and ANOV A are listed in Appendix 2.1. The plots of response

28 Chapter 2 - Does metabolism detennine diet shifts? surfaces (Fig. 2.3 a, b & c) show the relative effects of Corophium density and size on capture rate for three size classes of goby. For a given goby size, capture rate increases with increasing prey density and decreases with increasi ng size of available prey.

Meiofauna capture rate increases with increasing prey density and decreases with increasing goby length (Fig. 2.3d).

a) b) ~ /------1.2 1.2 1 l.O 1.0 0.8 0.8 ....-., I M 0.6 0.6 I 0 0.4 0.4 0.2 0.2 -X 0.0 1 0.0 1 I Cl) 2 3 4 2 3 4 5 5 Cl) hey 6 7 Prey 6 7 8 1engtb 8 length 8 Q) (QJQJ) (lb!JJ) ...... -+--> "'-.._/

----l d) -----l 1.2 I 1. 0 0.8 I 0.6 0.4 0.2 0.0 1 2 3 h ey 1 4 5 6 7 engf.b ( 8 l1Jn:ij

Figure 2.3. Response surface plots for the effect of Corophium size and density on capture rate for three size classes of P. microps. a) 17 mm, b) 27 mm, c) 3 7 mm and d) the effect of meiofauna density and goby length on capture rates.

Respiration rate

The standard and active respiration rates of gobies increased exponentially with length, with active respiration at a faster rate than standard respiration (Fig. 2.4). Hence, the discrepancy between active and standard rates widens with size.

29 Chapter 2 - Does metabolism determ.ine diet shifts?

0.0025 0

0 0.0020 0 ..- 0 -I 0 (/) ...__.,....., 0 ...... Q) 0.0015 0 ._m 0 0 c 0 0 :.o:; 0 ._m 0.0010 0 0 0. 0 (/) Q) 0 0 0:: 0 0 0.0005 0 0 0 0 0 0 0 0 0 0 0 0.0000 • • • • • • • • • • 10 15 20 25 30 35 40 Goby standard length (mm)

Figure 2.4. Active ( 0 ) and passive respiration rates (e ) against standard length for the common goby.

DISCUSSION

Existing predictions of diet shifts using optimal foraging theory illustrate the prevalence of shifts associated with changes in habitat or driven by external conditions (Werner &

Mittelbach 1981; Sih 1984; Robinson & Wilson 1998; Persson & Greenberg 1990b). This study illustrates that realistically parameterised foraging models can also predict shifts influenced by internal mechanisms such as metabolism. I suggest that metabolism may play a crucial role alongside handling time, in determining prey choice and that it should be given greater consideration in future diet shift studies.

Empirical observations for P. microps over a range of sizes ( <20 mm - >30 mm) indicate that there is a shift in feeding, from small prey items (i.e. copepods), to larger prey types at a length of around 30 mm (Pihl 1985 ; Gee 1989; del Norte-Campos & Temming 1994).

30 Chapter 2 - Does metabolism determine diet shifts?

Model predictions from this study, demonstrating clear ontogenetic shifts in diet from meiofauna to macrofauna at 30 mm in length, are consistent with these observations. This diet shift allows net energy intake rate to be maximised through ontogeny. Gee' s ( 1989) review on the importance of meiofauna as fish food proposed that meiofauna are only important for fish <60 mm in length and that diet shifts from meiofauna to other prey occur rapidly. This suggests that there is a threshold size beyond which meiofauna are no longer a viable prey type. In agreement with this, a key observation from Chapter 6, is that variability in prey availability can have serious fitness consequences for gobies (Jackson et al. 2002) so it seems eminently possible that prey availability determines prey selection patterns. Model predictions, based on the premise of energy gain rate maximisation, indicate a precipitous change in mean prey length (Fig. 2.1) at the point where the shift in prey type occurs. Here, the primary factor in determining mean prey size consumed is whether or not meiofauna are included in the optimal diet, further emphasising the fact that changes in prey selection occur as a distinct shift from meiofauna to macrofauna.

Fluctuations in prey abundance at a site may result in there being a time-dependent component to model predictions. Given, however, the regularity of the predicted shift occurring at 30 mm in length (despite major differences in prey densities between sites ­ see Appendix 2.1) I consider that, although there is temporal variation in prey abundance at each site (see Appendix 2.1), this is unlikely to affect the overall pattern. Indeed, simple tests of pattern stability by manipulation of relative densities of meio- and macrofaunal prey (plus 10% and minus 10% respectively and vice versa) revealed no change to predictions of shjft location. This consistency in the face of variation points to some degree of canalisation (Steams 1989). The slight differences observed in mean prey length between sites for gobies >30 mm (Fig. 2.1) can be explained by the variable abundance of longer chjronomids.

31 Chapter 2 - Does metabolism detennine diet shifts?

The strategy of maximising the currency of net energetic gain is a standard fitness surrogate used in many foraging models (Pyke 1984; Stephens & Krebs 1986). Schoener

( 1971) describes other strategies using the same currency to maximise fitness, for example where the time to obtain a fixed amount of energy is minimised. Primarily visual predators, such as gobies, have only a limited window in which to obtain their food

(daylight) and this opportunity may be limited further by factors such as predation risk

(Lima & Dill 1990) and tidal flow (Healey 1972). Under the definitions established by Sih

(1984), P. microps appear to act as cost or activity minimisers (Magnhagen 1986), being a rather sedentary species spending most of their time resting on the bottom, often covered with a layer of sediment. lfthis were the case, l would expect gobies to consume prey items that minimised the cost or time required to obtain their daily energy requirements, rather than just maximising net gain per se. The goby length at which a failure to include meiofauna in the diet resulted in the inability to obtain sufficient energy during the available foraging time ( 17 mm) did not correspond with the length at which diet shifts are observed (30 mm). So, although small gobies may be time limited, for a wide range of goby sizes, available foraging time does not determine diet range. Despite their sedentary nature, apparently minimising activity, this 'sit-and-wait' behaviour may in fact be the foraging strategy that maximises energy intake rate. Active searching may cause disturbance that makes potential prey retreat back into their burrows or remain immobile, reducing apparency and vulnerability. Pomatoschistus microps are therefore predicted to maximise the rate at which they take in energy either side of an ontogenetic shift in diet.

Changes in capture rate with fish length may go some way to explaining the change of prey choice that maximises energy intake, although there does not appear to be a goby size at which a discrete change in capture rate occurs (Fig 2.3).

32 Chapter 2 - Does metabolism detcnnine diet shifts?

For theoretical reasons, I used the prey:goby volume ratio in preference to the more usual prey:predator length or prey thickness: mouth-size ratios to obtain handling time relationship. Where fish have large mouths relative to body size (e.g. gobies), gape diameter may not be a limiting factor, or where prey shape differs markedly, volume may be a more sensible measure than length. Gape limitation is frequently put forward as a mechanism that determines prey choice and predictions of handling time may be based on the relationship between the thickness or length of the prey item and the diameter of the mouth (Kislalioglu & Gibson 1976a; Mittelbach 1981; Wainwright 1988). In P. microps, mouth size increases isometrically with body length and a regression of mouth diameter against standard length yields the linear relationship y = 0.084x + 0.1644 (r2 = 0.90, P <

0.05). If the relationship was allometric, an inflection point might indicate the length at which prey choice changes. It may also be, that at a length of30 mm, the gape attains sufficient size to accommodate macrofauna. Inspection of the actual gape size suggests that this is unlikely with the mouths of even quite small fish (e.g. 15 mm) having sufficient gape ( -1 mm) to ingest the smaller macrofaunal size classes (e.g. Corophium of 1-5 mm).

Other mechanisms may be invoked to explain changes in prey choice including learned behaviours, changes in sensory acuity and fast-start capability. Learning through experience can considerably modify feeding behaviour, typically through reductions in handling times (Croy & Hughes 1991 c). Such reductions may alter the relative profitabilities of prey items and consequently change the range of items to be included in an optimal diet Gobies used to estimate handling times in this study were assumed to be nai·ve to the prey type used and in the natural environment, this may not be the case.

Predictions from the model applied here were based on prey size rather than prey identity

Ifthe handling of different sized prey (rather than different prey type) is modified by experience then this may be reflected by relative changes in prey size profitability. Unless

33 Chapter 2 - Does metabolism detennine diet shifts? there are changes in gross morphology with increasing size, I anticipate that experience will modify the relative profitabilities of prey identity more than for prey size. Visual acuity in fish typically increases with increasing eye size (Bradbury & Vehrencamp 1998) and for a visual predator such asP. microps this is unlikely to explain a shift from feeding on small items to larger prey. Fast-start capability is important in predator evasion (Webb

1986) and, similarly, is likely to be important in prey capture for sit-and-wait predators. lt is possible that ontogenetic change in this capability permits larger gobies to access macrofaunal prey by reducing the chance of prey escape. Although this cannot be precluded, I consider it more likely that ontogenetic change in metabolism and handling time is the root cause of the change in foraging behaviour.

Various theoretical and empirical evidence supports the role of metabolism in determining prey choice. For instance, as prey become small in relation to the size of the predator, foraging costs should increase (Kerr 1971). Where normal diet shifts are precluded, there are considerable associated costs. Lake trout that do not make an ontogenetic diet shift become stunted relative to those that do (Pazzia 2001) and P. microps > 30mm, prevented from feeding on macrofauna, lose body condition and show reduced fitness (Jackson et al.

2002; Chapter 6). Sherwood et al. (2002) have demonstrated, using enzyme activity, the energetic advantages of ontogenetic diet shifts. Thus, prey selection through ontogeny, rather than being primarily influenced by prey availability (Magnhagen & Wiederholm

1982a; Magnhagen 1985), can be driven by internal mechanisms such as metabolic rate.

Despite wide recognition of ontogenetic changes in metabolism (Wieser & Forstner 1986;

Oikawa et al. 1991; Post & Lee 1996) and the role of metabolism in determining behavioural costs (Abrams 1992), I am not aware of any studies that make this important link between metabolism and shifts in diet.

34 Chapter 2 - Does metabolism detennine diet shifts?

In conclusion, a rate-maximising foraging model successfully predicted an ontogenetic diet shift under previously untested conditions, i.e., for predators that shift diet between ecologically distinct prey classes (meiofauna and macrofauna) within the same habitat. I suggest that a genetically controlled mechanism, such as change in metabolic rate, may canalise the size at which the diet shift occurs. Given this canalisation, gobies of a given length are limited in plasticity over the size of prey they select but, within these limitations, selection of prey identity can be variable.

35 Chapter 3 - Internal and external drivers of prey choice

CHAPTER3

CONSISTENT DIET SHIFTS IN A BENTHIC PREDATOR IN THE FACE OF VARIABLE PREY AVAILABILITY

Part of this Chapter has been submitted for publication as

Jackson, A.C. & Rundle, S.D. in review. Consistent diet shifts in a benthic predator in the face of variable prey availability. Oikos.

36 Chapter 3 - Internal and external drivers of prey choice

INTRODUCTION

Ontogenetic shifts in diet are important in both ecological and evolutionary terms,

particularly for those animals that exhibit large increases in size (Schoener 1971 ). Both

theoretical and empirical evidence suggest that niche shifts are an evolutionary solution to

reduce mortality risk and increase fitness of individuals as they grow and develop (Werner

& Gilliam 1984; Werner & Hall 1988). Such shifts should occur when the balance

between mortality and fitness differs between available strategies, often occurring at

thresholds (sensu Balon 1975) between different life stages (Sempeski & Gaudin 1996).

Metamorphosis, for example, is likely to induce a precipitous shift in diet, and like many

niche shifts, can be the consequence of a wide range of extrinsic and intrinsic factors

(Wainwright & Richard 1995; Persson & Hansson 1999; Nilsson & Bronmark 2000;

Persson & Greenberg 1990b ).

Trait shifts often occur in response to external factors such as change in habitat, prey

availability, predation risk and competition (Mittelbach 1981; Werner & Mittelbach 1981;

Werner & Hall 1988; Persson & Hansson 1999; Hughes & Croy 1993). Variability in environmental parameters can affect fitness and, in such instances, selection should favour

shifts that limit fitness costs. Costs may be ameliorated, for example, through morphological change or environmental partitioning (Hjelm & Johansson 2003; Chapter I;

Platell et al. 1998b).

Internal mechanisms, for example visual acuity or locomotory ability (see Chapters I & 2) can also be responsible for changes in diet but such factors are rarely included in optimal foraging models. The foraging model developed in Chapter 2, however, provides a mechanistic, internally driven explanation for a diet shift in the common goby,

Pomatoschistus microps. Model forecasts illustrated, for the first time, that energetically optimal prey choice could be predicted either side of a diet shift, solely on the basis of

37 Chapter 3 - Internal and ex1emal drivers of prey choice

metabolically driven parameters. In the case of P. microps, foraging model predictions

support previous studies in suggesting that there is an ontogenetic shift in prey choice at a

length of30 mm (Pihl 1985; del Norte-Campos & Temming 1994; Jackson & Rundle in

review-a) Although optimal foraging models are frequently used in diet predictions, few are derived using field studies or provide any validation of the output (Persson 1990). Gut content analysis in diet investigations has also become standard practice but lacks consistency in approach and suffers similar criticisms regarding lack of quantitative analysis (Ferry & Cailliet 1996). 'Furthermore, many studies comment on the presence of diet shifts but I am not aware of any that make an explicit test of this phenomenon.

Herd take the ..opportunity to use quantitative field data to: first verify the validity of the model predictions for the presence of a diet shift (Chapter 2), and second, alongside

predictions, to investigate the relative importance of intrinsic and extrinsic factors for the diet shift. Foraging model efficacy was assessed using an innovative sigmoid regression approach as well as the location of predicted values in relation to 95 %confidence limits of observed values. Diet shifts between predator size classes were investigated using mean prey length and an index of relative importance (/RI) and predictions from the model, in the context of field data, permitted examination of the extent to which prey availability determined diet shift location.

MATERIALS AND METHODS

Ambient prey availability

In order to ensure maximal prey variability on which goby populations foraged, I conducted preliminary surveys ofbenthic invertebrates at several sites in the outer

Gullmarsfjord, Sweden. Three locations around the island of Skafto (Bokevik, Kilviken and Salvik) were then chosen for intensive study and samples ofbenthic fauna collected on eight consecutive weeks through July and August 2000. Five replicate cores for

38 Chapter 3 - Internal and external drivers of prey choice macrofauna (0 10 cm, 5 cm depth, retained on 0.5 mm sieve) and meiofauna (0 2.9 cm, 5 cm depth, retained on 63 jlll1 sieve) were taken from each site and preserved in 70% ethanol. In the laboratory, fauna were removed from the sediment, (meiofauna by density separation using Ludox- Somerfield and WaiWick, (1996), identified to species where possible, enumerated, weekly samples pooled and length-frequency distribution calculated before conversion to abundance m·2 Prey size classes included meiofauna (assumed constant at 0.5 mm) and 1 mm increments from I to 30 mm for macrofauna.

Prey consumption

The actual diet composition of P. microps through the season was also determined at all three sites. Gobies were collected on the same dates as prey samples using a I m push-net with a 2 mm mesh collecting bag. In order to maximise gut fullness, fish were sampled in early-mid morning (Healey 1972; Pihl 1985). Fish were sacrificed as described in Chapter

2. The gut was later removed from the body cavity via a ventral incision and, since gobies lack a discrete stomach, prey items were carefully removed from the entire digestive tract and stored in alcohol. All prey items were enumerated, identified to species where possible, and then measured for body length and width. Individual fish were placed into five size classes (as per model predictions, Chapter 2) to facilitate comparison of actual prey consumption with that predicted by the model and tests for differences in prey length between size classes and sites (see below) The frequency distribution of prey sizes consumed within each size class were not normal hence standard errors were not appropriate for providing a measure of confidence in the mean prey size consumed. A bootstrapping approach was used as a suitable alternative (Efron 1979). For each goby size class, individual values of mean prey length were resampled with replacement to provide repeated estimates of the overall mean for the size class (I 0000 iterations). From

39 Chapter 3 - internal and ex1ernal drivers of prey choice

the frequency distribution ofthese estimates, 2.5th and 97.5th percentiles were calculated to

provide a 95% confidence interval.

Model predictions and validation

Optimal foraging theory has become a useful tool in the prediction of diet shifts

(Mittelbach 1981; Werner & Mittelbach I 981; Persson & Greenberg 1990b) and

qualitative accuracy of predictions has provided support for application of this technique

(Persson 1990). Mean prey length-frequency distributions from benthic samples were used

to predict capture rates for five go by size classes (5 mm class intervals from I 5- 40 mm

standard length) using equations from Chapter 2 (Jackson et al. in press). Capture rates were then incorporated alongside values for handling time and energetic costs into the

foraging model from Chapter 2 (Jackson et al. in press) to predict the optimal diets for gobies of different length at each site. Mean predicted prey lengths were determined from

knowledge of items in the optimal diet and their relative abundance in the environment.

Despite the popularity of the optimality approach, few studies provide field validation of

model predictions and even fewer present a quantitative measure of the accuracy of such

predictions (Persson I 990). Here I developed a graphical approach to gauge model

performance using a step-function regression, a plausible function in this instance (see

Discussion), where there was a clear predicted shift from meiofauna to macrofauna

(Chapter 2). Various step-function models were applied to the predicted mean prey length values for gobies from each site. The function that gave the best fit is shown in eqn 3. I.

h y = a+----;----:- eqn 3. I I + exp(- x ~ c J

Regression models, with coefficients (a-d) specific to a site were then fitted (using least- squares) to mean consumed prey-length data for individual fish from the same site. When

40 Chapter 3 - Internal and external drivers of prey choice a parameterised model was 'forced' through other data, the subsequent fit (r2 value)

provided a global measure of how well the model performed through ontogeny, rather than looking at performance at a given predator size. In addition, observed data with higher residuals also indicated areas where the model was less efficient All regression methods were carried out using the graphical software package TableCurve 20 vS (AISN Software lnc., Oregon, USA). Model performance for a given predator size was also assessed by comparison of predicted mean prey lengths with mean consumed prey lengths. Predictions have been assumed to be accurate if values fall within the 95% confidence limits of the observed values (Mittelbach 1981 ).

Tests for consistency in diet shifts

Comparisons of mean prey length and patterns in the relative importance of different prey types between size classes and sites provided formal tests for consistency in diet shift in the face of prey variability.

Prey length

1 tested for differences in prey between sites and fish sizes using mean consumed prey length for each size class, calculated fi-om ea. 10 randomly selected gobies (see below for details on sample size). Homogeneity of variance in mean prey length could not be achieved by transformation and sample sizes were not balanced so a two factor, non­

parametric ANOV A was used (Scheirer-Ray-Hare extension to Kruskaii-Wallis) (Sokal &

Rohlf 1995). A mixed, general linear model was conducted on the pooled ranked values for mean prey length (site random, size class fixed) with the test statistic (H), tested as a l variable (Sokal & Rohlf 1995). Tukey-Kramer pairwise comparisons, as an appropriate post-hoc test for unbalanced data sets, were then made to see where significant differences occurred (Sokal & Rohlf 1995).

41 Chapter 3 - Internal and external drivers of prey choice

Index of relative importance

Accurate characterisation of the importance of different prey types is essential in understanding their contribution to a predator's diet (Bowen 1996). Prey type 'worth' is often assessed using quantitative measures of importance, of which the index of relative importance (flU and %flU) is most appropriate (Pinkas et al. 1971; Liao et al. 200 I;

Cortes 1997). Patterns in such indices illustrate how the importance of different prey items changes with ontogeny, with extremes ranging from absolute importance to total non­ selection.

All available data from prey consumed were used to calculate percent numerical composition (% NCi), percent volumetric composition (% VC) and percent frequency of occurrence (% FOi) where i is the number of items in each prey type for each size class of goby from each site. Volumes of prey items were calculated by assuming simple geometric shapes (Winberg & Duncan 1971 ). Nereis diversicolor, Corophium volutator, chironomid larvae and copepods were represented by cylinders, and ostracods by spheres, with volumes calculated accordingly from length and width measurements. % NC,, % VC, and % FOi were then amalgamated into a composite measure of prey importance, IIUi from which %flU, was derived where:

IIU, =(o/oNC, +%VC,)%FO, eqn 3.2 and

eqn 3.3

where n is the total number of prey type per goby size class per site.

42 Chapter 3 - Internal and external drivers of prey choice

Measures of% /RI were calculated for the main ecological prey groupings of meiofauna and macrofauna between which the diet shift in P. microps occurs. In order to provide a robust representation ofthe importance of different prey items and to facilitate commonality and consistency, the indices % NC, % VC, % FO and %!RI are also reported for each prey type (Cortes 1997).

Sample size determination

Where there is an interest in making comparisons between diets, one needs to be confident that description of the diet is sufficient (Ferry & Cailliet 1996). Diet studies frequently consider insufficient samples (i.e. they lack statistical power) to be able to detect differences in diet, if indeed they exist. In order to ensure that my analyses of prey consumption were sufficiently powerful, 1 established an appropriate sample size using cumulative prey curves and a basic power analysis (see Appendix 3.1).

RESULTS

Prey availability

Benthic sampling confirmed that overall prey densities, as well as relative proportions of prey types and sizes, differed markedly between the three sites (Fig. 3.1). Salvik &

Kilviken had similar meiofaunal abundance and macrofaunal prey composition but differed in their prey length-frequency distributions. Bi:ikevik & Kilviken had similar macrofaunal length-frequency distributions but differed in macrofaunal composition and meiofaunal abundances.

Model validation

Predicted and actual prey consumption

The mean lengths of prey consumed by field-caught fish (Fig. 3.2, open circles) were similar to predicted values for most goby size-classes (Fig. 3.2, closed circles), validating model predictions and suggesting that a diet shift in common gobies is an actual

43 Chapter 3 - Internal and external drivers of prey choice

phenomenon. Deviations from predicted values are addressed in the Discussion. Despite

variation in prey availability across sites (Fig. 3.1), the patterns of increase in mean

predicted and consumed prey length were consistent (Fig. 3.2). However, prey availability

did appear to play some role in determining patterns of prey selection after fish had shifted

to consuming macrofauna. At Siilvik and Kilviken, fish consumed longer prey than at

Bokevik (Fig. 3 .2) due to an abundance of chironomid larvae with greater body length than

Corophium at the former sites (Fig. 3. I).

Model performance

Step functions (eqn 3.1) fitted to predicted mean prey lengths explained > 99 % of

variation with goby length at each site indicating that the sigmoidal regression approach is

appropriate for application to diet shift data. When the parameterised functions were

forced through data from individual fish, the models explained up to 40% of the variation

in mean consumed prey length with goby size (Table 3.1, Fig. 3.3). Further comparisons

showed that for four fish size-classes, model predictions of prey length fell within the 95%

confidence limits ofthe observed data (Fig. 3.2), again providing support for model

predictions and the regular occurrence of predicted and observed shifts at 30 mm (Fig.

3.3). Both approaches demonstrated that virtually all variability in prey selection occurred

post-diet shift (Figs. 3.2 and 3.3). This variability was likely to have been a consequence

of the larger range of prey sizes consumed following the diet shift.

Table 3. I. Correlation coefficients for sigmoid regression equations of predicted mean prey length. R-squared values indicate the goodness of fit of these equations to observed mean prey length data. Coefficient Site a b c d r Salvik 0.499 5.490 31.040 0.790 0.23 Bokevik 0.570 2.700 29.500 0.166 0.40 Kilviken 0.520 4.786 30.360 0.690 0.30

44 Chapter 3 - Internal and external drivers of prey choice

- Corophium volutator = Chironomid larvae IZl'ZZZZll Nereis diversicolor = Meiofauna (Copepoda and Ostracoda) ~- s: E DJ a) b) c) (") Cl) ...., 0 175000 1000 0 ...... -c w 150000 800 c- :t=>- ~ Cl) 125000 DJ c 600 0. Cl) 100000

2 Figure 3.1. Mean summer prey densities (nos. m- ) for meiofauna (0.5 mm) and macrofauna (1 mm size classes) at the three sites sampled a) Bokevik, b) Kilviken & c) Salvik. Meiofauna density (first bar only) is represented by the first y-axis and macrofauna density (remaining bars) by the second y-axis.

45 Chapter 3 - Internal and external drivers of prey choice

a) b) c) .--... E 10 E 8 -..c:..... 0> c 6 <1> >- <1> 4 1-a. c 2 CO <1> ~ 0 15 20 25 30 35 40 15 20 25 30 35 40 15 20 25 30 35 40

Goby standard length (mm) Figure 3 .2. Predicted ( • ) and observed ( o) mean prey lengths for common gobies from a) Bokevik, b) Kilviken & c) Salvik. Error bars showing 95% confidence limits around the observed mean prey length consumed (derived from 2.5th and 97.5th percentiles ofbootstrap resampled estimates ofthe mean).

46 Chapter 3 - Internal and external d.iivers of prey choice

a) b) c) 18 • • -E E 16 ~ • 14 ..c: • 0> 12 -c:: (1) 10 • • >- •• (1) 8 • • .._ • • • • c.. 6 • • c:: • • ro 4 ••• • (1) • 2 ~ •• • • • • • 0 10 15 20 25 30 35 40 45 10 15 20 25 30 35 40 45 10 15 20 25 30 35 40 45

Goby standard length (mm) Figure 3.3. Sigmoid regression for foraging model predictions of mean prey length fitted to mean consumed prey length data for a) Bokevik, b) Kilviken & c) Salvik. Coefficients and r2 values are provided in Table 3.3.

47 Chapter 3 - IntemaJ and extemaJ drivers of prey choice

Consistency in diet shifts

Highly significant differences in consumed prey length between size classes but not sites and a lack of significant site* size class interaction (Fig. 3 .2, open circles, Table 3 .2) indicated the presence of a consistent diet shift between 27 and 32 mm in goby length.

Pairwise comparisons between size classes (pooled across sites) indicated that gobies < 30 mm consumed the same sized prey and that prey lengths consumed by the two largest size classes were significantly different from both the smaller size classes and each other (Table

3.3). The graphical presentation of % flU for meiofauna and macrofauna provided further support for this consistency, demonstrating the reliability with which importance of meiofauna decreased rapidly from - 100% to - 0% (Fig. 3.4). This pattern was mirrored by a concomitant increase in the importance of macrofauna in the diet.

Table 3 .2. Analysis table for Scheirer-Ray-Hare non-parametric two-factor analysis of variance. The significance oftest statistic His found from a table of X2 critical values. Shaded values indicate significant effects referred to in the text. Effect d.f. ss MS H p Site 2 30117 4.70 Size class 4 815272 127.13 Site*Size class 8 55873 8.71 p>0.2 Error 262 868804 ••••• Total 276 1770066 6413

Table 3.3. Post-hoc pairwise comparisons for mean prey size ofgoby size class, pooled across sites. MSD is the minimum significant difference and Yi-Jj the actual pairwise differences. Shaded values indicate a significant difference (a. = 0.05).

1 2 MSD 3 25-29 1.070 4 30-34 1.141 1.057 5 >35 1.186 1.106 1.112

48 Chapter 3 - Internal and ex'temal drivers of prey choice

::R0

15 to 19 20 to 24 25 to 29 30 to 34 35 to 39 Goby size class (mm) Figure 3.4. Changes in% index of relative importance(% !RI) with goby length (mm) at Bokevik (. ,0 ), Kilviken (. ,6 ) and Salvik (e ,O) for meiofauna (open symbols) and macrofauna (closed symbols). Values ofthe component measures for % !RI for individual prey species are presented in Appendix 3 .I.

DISCUSSION

This study presents an important validation ofthe foraging model predictions from Chapter

2, and assesses the relative importance of external factors such as prey availability and intrinsic mechanisms in driving diet shifts. Common goby diet shifts from small to large prey were remarkably consistent (Figs. 3.2 & 3.4) in the face of natural variability in prey abundance and composition (Fig. 3.1) . This suggested that canalised internal mechanisms were of over-riding importance in determining prey choice for this species and should be given careful consideration in future studies.

Prey abundance is often cited as a key driver of prey choice and clearly at extremes (e.g. absence) will be a determining factor (Sih 1984; Hughes & Croy 1993). Studies on perch

(Percafluviatilis), for example, have demonstrated that resource (prey) availability was an

49 Chapter 3 - Internal and external drivers of prey choice

important determinant in the timing of diet shifts (Persson & Greenberg 1990a, b). Jones et al. (2003) suggest that if the parameters that drive shifts in diet are constant between generations then the shift should occur at a predictable point from generation to generation.

Where the parameter varies through time, plasticity in diet shift location would be expected. The same argument should apply if the responsible parameters are constant

between geographic sites. From the three sites considered here, there was considerable variation in prey availability in terms of both abundance and composition. If this was a factor that determined prey choice, then one might expect that the location of the shift in diet would vary between sites. As it was, the shift location was consistent (Fig. 3.4), suggesting some more predictable parameter such as metabolic rate was canalising the change in prey choice (Chapter 2).

Several previous studies (Mittelbach 1981; Osenberg & Mittelbach 1989; Persson &

Greenberg 1990b ), have demonstrated that optimal foraging models successfully predicted

patterns of change in prey choice, albeit with some lag in occurrence ofthe shift. In this case, support for accurate model predictions was strong, in terms of both overall pattern and timing. The semi-quantitative step-function regression and the confidence-limit analysis provided validation of model predictions. Although other functions provided a better fit to the observed data, the step function I used was appropriate in this case since the shift to larger prey was constrained by the upper size limits of preferred go by prey (e.g.

Corophium and chironomids) and the relatively small maximum size of the gobies themselves. Had more data been available for larger gobies (i.e. 40-45 mm) I anticipate that the fit of the step function to actual mean prey length would have been much closer.

Discrepancies between predicted and observed data were apparent immediately following the shift in prey choice and the observed shift in mean prey length did not occur as precipitously as predicted by the model (Figs. 3.2 and 3.4). For fish in the 30-34 mm

50 Chapter 3 - Internal and ex1emal drivers of prey choice category, mean prey length was less than that predicted by the model and the change in%

IRlless abrupt than expected from such precipitous shifts in mean prey length.

Gradual shifts in prey choice can be caused by trade-offs in the parameters driving the shift

(e.g. where the benefit of one behaviour is affected by some other behaviour) but it was not clear here what other factor(s) might have been involved (Gee 1989). The study described in Chapter 5 suggests that no trade-offs are induced by the change in diet so other mechanisms may be responsible. Deviations from predicted values may be a consequence of partial preferences in prey choice or the effects of learning on prey handling (Hughes

1979; Pyke 1984; Croy & Hughes 1991c; Persson & Greenberg 1990b). lfthere was variation in scope for activity amongst individuals of diet shift size (Reidy et al. 2000) then this may also provide a mechanism by which the observed patterns in mean prey length and %!RI could be explained. Individual gobies may be undertaking a sudden shift in prey choice but inter-individual metabolic variation may manifest itself as a more gradual change in prey length at the population level. The shifts in mean consumed prey length

(Fig. 3.2, open circles) were less precipitous than predicted values (Fig. 3.2, closed circles).

This non-precipitous change in mean prey length was likely to be a consequence of a similar change in importance of different prey types (Fig. 3 .4). For size-class four (30-34 mm), observed mean prey lengths were consistently below predicted values (Fig 3 .2). Fish from size-class four were thus feeding sub-optimally if only energy gain rate was considered (as per foraging model predictions). Actual mean prey lengths in size class four were consistently lower than optimal predictions, suggesting that some regular feature of either the environment or the gobies themselves was responsible. The 'sub-optimal' nature of this prey choice is confirmed in Chapter 6 through the quantification of reductions in reproductive fitness in P. microps > 30 mm prevented from consuming macrofaunal prey (Jackson et al. 2002).

51 Chapter 3 - Internal and external drivers of prey choice

Specific tests for the presence of changes in prey consumption using comparisons of mean prey length and patterns of% !RI clearly established that an ontogenetic shift in diet occurred at a goby length of30 mm. Mean prey lengths consumed by fish either side of the proposed shift location (30 mm) were significantly different (Fig. 3.2 open circles,

Table 3.1). This was reflected by predicted change in mean prey length (Fig. 3.2, closed circles). Some prey items will contribute more to the growth, fitness and survival of a predator and being able to quantify the contributions of different prey is necessary in helping to understanding prey choice decisions (Bowen 1996). When comparing the roles of particular prey types in a predator's diet, 'importance' is a frequently used quantitative measure (Bowen 1996) and various indices have been propounded as useful descriptors

(Hyslop 1980; Liao et al. 200 I), with %!RI deemed most appropriate (Liao et al. 200 I;

Cortes 1997). Appendix 3. I shows clearly how items of high importance change from small (i.e. copepods) to large (e.g. Corophium, Chironomids and Nereis) with ontogeny

Even more interesting is the pattern shown when prey items are pooled into the ecological groupings of meiofauna and macrofauna (Warwick 1984). The shift from near total selection to near total aversion of meiofauna (Fig. 3 .4) occurs at the size predicted by the foraging model (30 mm) (Fig. 3.2, closed circles) and supports observations in Chapter 6, of reduced fitness in gobies > 30 mm in length resulting ffom non-availability of macrofauna (Jackson et al. 2002).

This study thus provided a clear quantitative validation of the optimal foraging model for

P. microps and confirmed the consistent presence of a diet shift at a go by length of 30 mm.

This consistency supported the assertion that for this species, metabolism, (as an intrinsic mechanism) is more important than extrinsic prey availability in the determination of prey choice through ontogeny.

52 CHAPTER4

FORAGING PLASTICITY AND FEEDING EFFICIENCY IN THE COMMON GOBY

Part of this Chapter has been submitted for publication as

Jackson, A.C. & Rundle, S.D. in review. Foraging plasticity and feeding efficiency in the common goby .. Journal of Fish Biology.

53 Chapter 4 - Conunon goby foraging plasticity

INTRODUCTION

Variability in behaviour is ubiquitous, often occurring in response to environmental cues, and can be exhibited at several scales. For example, where individuals pass through a broad size range in their development, ontogenetic changes in resource use are often a way by which effective resource exploitation is maintained (Werner & Hall 1988). At the same time, behaviour can vary within a given size or developmental stage and this plasticity may be determined genetically, induced by environmental conditions or by epigenesis (Adams et al. 2003). Behavioural plasticity can incur two costs, those from behaviours being less effective (Laverty & Plowright 1988; Hughes & O'Brien 200 I) and those from an ability to be plastic (Newman 1992; Komers 1997).

Costs of exploiting different prey resources can be manifested as trade-offs, for example between foraging efficiency and predation risk. Such trade-offs can lead to strong selection pressures (Svanback & Eklov 2003). Adaptive pressures and inherent constraints both determine the morphology of the various life stages of a predator (Kirkpatrick 1988;

Werner 1988; Hjelm et al. 200 I; Svanback & Eklov 2002; Chapter 5). Within any stage, predators are often categorised as specialists or generalists, with the former developing stereotyped and invariant behaviour and morphology for efficient exploitation of a particular resource (Hughes & O'Brien 200 I). Specialists foraging on 'non-target' prey endure reduced efficiency. Generalist foragers do not achieve such high efficiency as specialists, but benefit from being able to exploit a range of prey types without loss of efficiency (Fig 4. I). This foraging plasticity may form an important mechanism to accommodate unpredictable conditions (Morse 1980; Komers 1997).

Learning can increase this plasticity and reduce the costs of lower efficiency (Hughes &

O'Brien 200 I) with skill-transfer theory indicating that performance can be enhanced through experience of similar tasks, but hampered by tasks that are dissimilar (Ell is 1965).

54 Chapter 4 - Common goby foraging plasticity

Foraging efficiency can be measured in terms of the time required to obtain a given amount of energy (Kislalioglu & Gibson 1976a), or energy gain per unit time (Mittelbach

1981), and consumption of different prey types or sizes will result in different foraging efficiencies. In the absence of handling times for specific prey types, the total amount of energy contained in the gut after a fixed period oftime can be used as a surrogate measure of efficiency.

--- Specialist - - Genera list

~ c (1) ·u lE (1) 0> c 0> m '- u..0

'Difference' in prey resource

Figure 4.1. Specialists can be highly efficient foragers but show reduced efficiency on different prey items whereas generalists do not achieve such high efficiency but maintain intermediate levels over a range of prey types. The 'difference' axis refers to increasing deviation in size and form of prey items.

Wimberger (1992) suggests that organisms using only their mouth to handle food are more likely to show a greater degree ofphenotypic variation in foraging. Fish, for example, are widely described as having different behaviours and morphologies for exploiting different resources and are particularly well suited to studies in this field (Gerking 1994; Wimberger

1994; Wooton 1998).

55 Chapter 4 - Common goby foraging plasticity

Prey availability fluctuates considerably in benthic habitats (Moller & Rosenberg 1982), and such variability may have consequences for fish foraging and fitness (Jackson et al.

2002; Chapter 6). Despite such fluctuations, some benthic feeding fish appear to exhibit fixed ontogenetic shifts. Chapters 2 and 3, for example, illustrate that the ontogenetic diet shift of Pomatoschistus microps is remarkably consistent over a range of prey abundances and compositions (Jackson et al. in press; Jackson & Rundle in review-a).

Fish often consume a wide range of prey, depending on availability (Magnhagen &

Wiederholm 1982a, b; Schindler et al. 1997; Nemeth 1998; Link & Garrison 2002) This may either be because they are true generalists with highly plastic foraging, responding immediately to environmental conditions, or because they have specialised under local conditions (Schindler et al. 1997). Where differences in prey variability are constant from year to year then there will be a tendency towards specialisation for that prey type (Jones et al. 2003). On the other hand, where prey availability is highly variable, optimal foraging theory predicts reduced selectivity, i.e. increasing generalisation (Pyke et al. 1977; Komers

1997). Chapter 3 demonstrates that although P. microps displays consistency in diet shift location, there does appear to be variation in post-shift foraging, driven by local variability in macrofaunal prey composition (Jackson & Rundle in review-a).

In this study, I took advantage of natural differences in prey assemblages between estuaries and conducted reciprocal translocation experiments to investigate flexibility in the post diet-shift foraging behaviour of Pomatoschistus microps. Prey selection and feeding efficiency of native (experienced) and translocated (nai"ve) gobies exposed to these macrofaunal prey assemblages provided a valuable opportunity to examine whether foraging was plastic and immediately adaptable or dependent on learning and prior experience. Specifically, l tested the null hypothesis that there would be no difference in feeding efficiency on two prey assemblages by nai"ve and experienced gobies.

56 Chapter 4 - Common goby foraging plasticity

MATERIALS AND METHODS

Experimental species and study sites

The habitat and foraging ecology of Pomatoschistus microps, outlined in Chapter I, makes this an ideal species for investigations into behavioural plasticity. This study was conducted in two small estuaries, noted for having different benthic assemblages, on the

English south coast: the River Avon (50° 18' 40" N; 3° 50' 20" W) and the River Yealm

(50° 20' 24" N; 4° 01' 20" W), Devon, UK (Chapter 1). 1 assumed that the prey assemblages used were representative of the areas in which P. microps naturally fed at each site, and therefore anticipated that gobies from the Yealm will have had no experience of foraging on the Avon prey assemblage and vice versa.

Reciprocal translocation experiments

Foraging of adult P. microps on the different prey assemblages at these two sites was assessed using reciprocal translocation experiments conducted in August 2003. Gobies were collected (as in Chapter 2) from both estuary sites at low tide. To standardise hunger and control for possible relocation effects, half the fish from each site were maintained, without food, for 24 hours in a tank with a fine mesh cover held on the mud flat; the remaining half were transferred to the other site and maintained in the same fashion. Six enclosures were placed out on homogeneous fine sediment nearby to where the fish were caught. Enclosures were plastic tanks ( 40x20x25 cm, lxbxh) with the base removed, pushed down I 0 cm into the sediment ensuring that water was retained, during the whole tidal cycle. Enclosures were covered by fine netting (ea 250 flm mesh) held in place with elastic cord and left for two tidal cycles to allow them to fill with water and stabilise. At each site, three enclosures were randomly allocated for native (experienced) fish and three for translocated (naive) fish. Following food deprivation, two gobies were introduced to each enclosure and allowed to forage for 24 hours before being removed, immediately

57 Chapter 4 - Common goby foraging plasticity sacrificed as per Chapter 2. Feeding trials were terminated mid-morning, just after high tide in order to maximise gut fullness (Healey 1972; Pihl 1985). Logistic constraints meant that the foraging trials at each site had to be conducted sequentially rather than simultaneously; experiments were duplicated two weeks later, when tides were again suitable. Water temperature in the enclosures varied between 10- 14 oc and salinity between 20-25.

Ambient Prey availability

Benthic sampling

In order to ensure differences in prey variability on which goby populations foraged, I conducted qualitative surveys ofbenthic invertebrates at several estuaries in South Devon.

At two sites, sediment prey assemblages were different with C. vo/utator being highly abundant in sediment at the River Avon but absent from the River Yealm site (see

Appendix 4.1). Prior to each experiment, five replicate sediment cores (0 7.5 cm, 5 cm depth) were collected and fixed in 70% ethanol to determine the ambient abundance of benthic, macrofaunal prey species (retained on 0.5 mm sieve). To ensure that goby foraging was not depleting or altering available prey and thus affecting selection preferences, l also took cores after the first pair oftranslocations. Cores beforehand were taken adjacent to the experimental enclosures, those afterwards from within the enclosures.

Fauna were removed from the sediment and prey types typically present in the diet of adult

P. microps (Healey I972; Pihl 1985; del Norte-Campos & Temming 1994; Jackson et al. in press; Chapter I) were identified to species, enumerated and frequency distributions calculated for I mm prey size classes of each species.

Prey assemblage comparisons

2 Total prey energy available in the sediment (Jm- ) was calculated by converting size­

2 frequency distributions into density m- , multiplied by the energetic content of each prey

58 Chapter 4 - Common goby fomging plasticity size, and the energy content for each prey type and size were then summed. Values of energetic content were derived from length-weight relationships and values of energy per unit mass (Pihl 1985; Rumohr et al. 1987). In the absence of length-weight equations

(only Cyathura), I used length-width relationships to calculate volume (assuming simple geometric shapes) and then dry weights were determined from density values and dry weight:wet weight ratios (Bamber 1985; Rumohr et al. 1987; Poff et al. 1993) If specific values for energy/unit mass were not available, I used average values for the main taxonomic group (Rumohr et al. 1987). Total prey energy available between sites, before and after the ~oraging experiments, was compared by two-way ANOV A, using individual core data as replicates.

In order to compare prey composition I used the frequency distributions calculated for I mm prey size classes of each species (see above). Differences between sites and occasion

(before vs after foraging experiments) were tested using two-way mixed-model non­ parametric multivariate analyses of variance (np-MANOV A) ofuntransformed frequency data, again using cores as replicates (Anderson 2001; McArdle & Anderson 2001).

Transformation of the data was considered inappropriate since I wished to emphasise the role of the main prey, rather than that of rare species. A similarity matrix was constructed using Bray-Curtis similarity coefficients and to visualise multivariate patterns in prey availability, 2-dimensional plots were produced following ordination of the data using non­ metric multidimensional scaling (nMDS) (Ciarke 1993).

Prey consumption

Experimental prey consumption

The Chapter 3 study established that gut content analysis of small sample sizes are suitable for dietary comparisons in P. microps (Jackson & Rundle in review-a). Consequently, I considered that the numbers of fish used in the translocation experiments were sufficient to

59 Chapter 4 - Common goby foraging plasticity provide adequate representation of the diet Gut contents were removed as described in

Chapter 3 and all prey items were enumerated, identified to species, and their length and width measured. Meiofaunal taxa (Copepoda and Ostracoda) were also included in these analyses. The energetic content of consumed prey was calculated as outlined for benthic samples above. Where animals were only partially consumed (i.e. Nereis), a length-weight relationship, energy per unit mass (Rumohr et al. 1987) and a length-width relationship

(derived from measurements on complete specimens) were used to establish a regression equation to predict energetic content from volume. Partial prey volume, assuming a cylindrical body, was determined from length and width measurements and could then be translated into energy consumed. Fish length and total energy consumed were then compared between, site, fish source and date using a factorial ANOV A. Frequency distributions of the amount of energy consumed by experimental fish from both sites were also used to visually interpret differences between sites in energy consumption by experimental fish. Similarly, prey assemblage compositions were also compared (np­

MANOVA) between fish source and temporal replicate for each experimental site. Sites were analysed independently here since np-MANOV A is limited to two factors. For the latter, partially consumed Nereis were dealt with by pooling all size classes and considering only total counts for this taxon.

Diet offield-caughtfish

To investigate differences in natural prey consumption, I applied the same approach as above to field-caught gobies from each experimental site (n= 19, size range 32-40 mm standard length). Student's t-test was used to compare fish length and mean total energy consumed between sites. Again, frequency distributions of the amount of energy consumed by fish from both sites provided visual representation of differences in energy

60 Chapter 4 - Common goby foraging plasticity consumption. One-way np-MANOV A indicated how native goby diet composition differed between sites and nMDS plots provided visual representation of these patterns.

Statistics

Minitab vl3.32 was used to conduct t-tests and GMAV5 for Windows (Underwood &

Chap man 1998) was used for univariate analysis of variance (ANOV A). ANOV As were preceded by Cochran's test for homogeneity of variance and, where necessary, data were subjected to a sqrt(x+ 1) transformation. Multivariate analysis was conducted using

Anderson's np-MANOVA program (Anderson 2001; McArdle & Anderson 2001) and

Primer v5.0 was used for nMDS plots (Clarke & Warwick 2001). The recent development ofnp-MANOVA permits the analysis of non-parametric data from complex experimental designs where variance can be directly partitioned, enabling tests of multivariate interactions (Anderson 200 I; Kelaher 2003).

RESULTS

Prey availability

Prey assemblages were markedly different between the two sites. Cyathura carinata and

Nereis diversicolor were present at both sites but at higher densities at the Avon, whereas

Gammams sp. and Corophium volutator were exclusive to the Yealm and Avon, respectively (Table 4.1). The two experimental sites differed significantly in total energetic content of prey biomass and foraging experiments did not deplete energy availability (Table 4.2, Fig. 4.2). np-MANOV A demonstrated a significant effect of site on prey assemblage composition and no effect of fish foraging (before and after experiments) and this pattern was clearly reflected in nMDS plots (Table 4.3, Fig. 4.3).

61 Chapter 4 - Common goby foraging plasticity

Table 4.1. Mean prey densities m-2 with standard errors, before and after foraging experiments at the Yealm and Avon sites. Yealm Avon Before After Before After mean ±se mean ± se mean ± se mean ± se Corophium volutator 0 0 0 0 19919 2254 22273 3766 Gammarus sp. 317 91 181 111 0 0 0 0 Cyathura carinata 815 115 679 72 1358 496 2128 292 Nereis diversicolor 3712 918 2943 1815 6157 988 11272 3591

Table 4.2. Two-way ANOV A for available prey energy between sites (two levels - Avon and Yealm, fixed) and sampling occasion (two levels - before and after foraging experiments, fixed).

d.f. MS F p Site (Si) 1 463293 78.59 ~~®i:Jj:{\t(tl Occasion (Oc) 800 0.14 0.717 Si*Oc 1 24 0.00 0.950 Residual 16 5895

300

250 <;l E """") £ 200 ..0ro ro 150 > ro >- 0') I- 100 Q) c Q) c ro 50 Q) ~

0 ~------.------.------before after

Figure 4.2. Mean prey energy m-2 (± s.e.) available at the Avon (A) and Yealm (e) experimental sites, before (open symbols) and after the foraging experiments (closed symbols).

62 Chapter 4 - Common goby foraging plasticity

Table 4.3. Two-way np-MANOVA for available prey assemblages (50 variables; Site, two levels- Avon and Yealm, fixed; Sampling occasion, two levels - before and after foraging experiments, fixed). d.f. MS F p Site (Si) 1 27911 23.62 Occasion (Oc) 1 1544 1.31 -0.238-·· ~ Si*Oc 1 1537 1.30 0.211 Residual 16 1182

Stress 0.07 •

0 0

0 0 • •

0 •

•

Figure 4.3. n.MDS plot for numerical composition of prey assemblages at the Yealm (e ) and Avon(_.) sites, before (open symbols) and after (closed symbols) the foraging experiments.

Prey consumption

Both experimental and naturally foraging fish in the Avon consumed primarily Corophium with some Nereis and Cyathura, whilst fish in the Yealm almost exclusively consumed

Nereis. The presence of prey specific to a site in the gut of naive fish indicated that gobies were capable of consuming novel prey types.

63 Chapter 4 - Conm10n goby foraging plasticity

Experimental fish

ANOV A comparing total energy consumption between site, fish source and date revealed significant interactions and strong temporal variation in foraging. Variability in energy consumption between dates, for native fish at both sites, resulted in significant interactions for all combinations containing date, which obscured comparisons of the other main effects

(Table 4.4) When foraging ability comparisons were considered in isolation (i.e. within dates), one out of two cases at each site indicated that native fish consumed more energy than translocated fish (Fig 4.4 a and b; t-tests, p

Table 4.4. Three-way ANOVA for mean total energy consumed (Site, 2 levels­ Avon and Yealm, fixed; Fish source, 2levels- Avon and Yealm, fixed; Temporal replicate, 2 levels, random). Shaded cells indicate to significant values referred to in the text. d.f. MS F Site (Si) 362286 5.45 0.258 Fish source (FS) 55306 1.82 0.406 ••••v•••·~•••••o•••vv•v Date replicate (Rep) 30444 7.11 0.014 . '·~~-~-'

Si*FS 24936 0.41 .. 0.639 Si*Rep 66456 15.51 0.001 FS*Rep 30407 7.10 J);Ol4 Si*FS*Rep 61299 14.31 :. ~.... Q.QQL ..... Residual 24 4248

64 Chapter 4 - Common goby foraging plasticity

...... a) b) c) ::2. 200 500 500 c 0 :.;:J 0.. 400 400 150 fJ)~ c 0 u 300 300 >- 0> s... 100 Q) c Q) 200 200 ...... CO 50 ...... 0 100 100 c CO Q)

Temporal replicate Site

Figure 4.4. Mean total energy consumption(± s.e.) from two temporal replicates at a) the Yealm (note scale ofy-axis) and b) the Avon sites by P. microps from the Yealm ( • ) and Avon ( o ). Graph c) shows energy consumption levels by naturally foraging fish at both sites.

65 Chapter 4 - Common goby foraging plasticity

There also appeared to be a clear difference in response magnitude between sites with energy consumption in the Yealm much lower than in the Avon (Fig 4.4 a and b). This

reflected patterns of actual energy availability (Fig. 4.2), but contrasted with the

observation that field-caught fish showed no difference in total energy consumption between sites (Fig. 4.4c). Frequency distributions of the amount of energy consumed by experimental fish from both sites illustrated the differences in experimental energy consumption between sites (Fig. 4.5a). There were no differences in fish length for any comparisons (three-way ANOV A, p > 0.05, mean length ea. 35 mm).

14 Yealm- experimental fish Avon - experimental fish 12 10 8 6 4 2

(.)>- c 0 Q) ::J CT ..._Q) 14 u.. Yealm - natural foraging Avon - natural foraging 12 10 8 6 4 2 0 0 100 200 300 400 500 600 0 100 200 300 400 500 600

Total energy consumption (J) Figure 4.5. a) Frequency distributions for energy consumption by experimental fish at both sites. This highlights the marked differences in energy consumption by experimental fi sh between the two sites. b) Frequency distributions for energy consumption by naturally foraging fish at both sites. Note the similarity in range of energy consumption between experimental fish at the Avon and naturally foraging fish.

66 Chapter 4 - Common goby foraging plasticity rleld-caught fish

Field-caught 'native' gobies used for between site comparisons of natural diet did not differ in the total amount of energy consumed (t = 0.67, d.f = 36, p >0.05) or in standard length (t = -1.31, df= 36, p > 0.05) (Fig 4.4c). Frequency distributions of the amount of energy consumed during natural foraging illustrate the similarity in experimental energy consumption between native fish from both sites and allow comparisons with energy consumption in experimental fish (Fig 4 5b). One-way np-MANOVA established that composition of consumed prey was significantly different between sites ( df = l, F = 3. 73, p

<0.01).

DISCUSSION

Duplicated, reciprocal translocation experiments provided some evidence for the effect of prior experience on foraging ability. Na"ive fish, with no prior experience of foraging on a prey assemblage, might be expected to perform less well, in terms of energy consumption, than those with previous experience of capturing, subduing and swallowing prey from the same assemblage. Gobies that were accustomed to feeding on a particular prey assemblage could forage more efficiently than those with no previous exposure to that assemblage.

My results show that in two out of four cases there was a significant effect of fish source, and thus experience, on amount of energy consumed. This may be due to the formation of a search image that allows predators to identify a particular prey type from a range of other stimuli (Tinbergen 1960; Pietrewicz & Kamil 1979).

The energy available to fish foraging in experimental enclosures differed greatly between sites, with the presence of Corophium being mainly responsible for the greater biomass in the Avon. Experimental fish, irrespective of source, when foraging in the Yealm site, consumed far less energy than those in the Avon (Fig. 4.4 a vs. b), reflecting biomass availability (Fig. 4.2). This was in strong contrast to the lack of observed differences in

67 Chapter 4 - Common goby foraging plasticity energy consumption levels in naturally foraging fish between the two sites (Fig. 4.4c). The total energetic content of prey consumed by experimental fish in the Avon is comparable to that of naturally foraging fish from both sites, which I assume represents typical requirements of P. microps of this size (Fig. 4.4 b & c). The very low levels of energy consumed by experimental fish in the Yealm may have been due to naturally foraging fish feeding from areas other than that selected for the experimental enclosures, although 1 consider this unlikely given the broad distribution of gobies within the estuary and the similarity of enclosure location between sites. Alternatively, the prey search method used for the Yealm prey assemblage may have been precluded by the experimental enclosures, although, with P. microps noted as a sit-and-wait predator, I also consider this unlikely. ln the case where native fish at the Avon site forage more efficiently than translocated fish, energy intake rates are considerably above the levels observed in naturally foraging gobies.

One explanation for discrepancies in inter-site foraging rate may be hunger level.

Although food deprivation was applied equally to all fish to standardise recent feeding experience, prior feeding opportunities may have had some residual influence on feeding motivation. Another explanation could be that prey availability in the enclosures containing native fish was much higher. Sediment cores were collected to establish inter­ rather than intra-site variation in prey availability so formal comparisons between enclosures containing fish from the two sites could not be made. When the five sediment cores were repeatedly randomly allocated to the two treatments, however, there were no differences in available energy (t-tests, p>O 05). Thus the reason for the notably higher than typical energy intake rates by these fish remains unclear but does not seem to be dependent on prey density in the sediment. It is possible that some influence on goby behaviour or prey behaviour and apparency may be responsible. n-MDS plots for the composition of naturally consumed prey indicate greater variability by fish foraging in the

68 Chapter 4 - Conunon goby foraging plasticity river Yealm (Fig. 4.4). A measure ofthe difference in variability is given by the multivariate dispersion index for a pairwise comparison of fish from the Avon and Yealm

(IMD = -0.806) (Clarke & Warwick 2001). This may have been due to the presence of more taxa in the multivariate analysis for the Yealm than the Avon.

Studies on a wide range of animals have investigated and emphasised the role that learning can play in foraging behaviour (Cunningham & Hughes 1984; Croy & Hughes 199lb, c) and others have investigating the stimuli responsible for prey selection (Kislalioglu &

Gibson 1976b; Croy & Hughes l99la). Movement and size appear to be the most important stimuli and others including colour, shape and location are more specific and more likely to be affected by experience (Croy & Hughes 1991 a). The assemblages present in this study consist of prey that differ in many ofthese variables and, therefore, are suitable for use in investigations into learning and foraging behaviour. Predators exposed to high densities of prey may develop a search-image, which assists in prey recognition and improves foraging efficiency (Tinbergen 1960; Pietrewicz & Kamil 1979).

Although behaviours can be modified by learning, such improvements may not be retained indefinitely (Croy & Hughes 1991 c). In my case, where the time-scale between fish capture and foraging experiments was of the order of24 hours it was unlikely that loss of memory would influence goby foraging efficiency. Croy and Hughes (l99lc) demonstrated that in the 15-spined stickleback Spinachia spinachia L, two days elapsed before the loss of learned foraging skills commenced.

Where the prey of generalist predators varies temporally, the ability to adapt search images may be important in maintaining plasticity in foraging behaviour The time taken to develop a search image will be important in determining foraging efficiency. If a search image can be developed in a matter of hours then this may provide a mechanism by which a predator can maintain energy intake efficiency where there are rapid changes in prey

69 Chapter 4 - Conuuon goby foraging plasticity availability (e.g. tidal cycles) or by changing habitat (Hughes & Croy 1993). Where changes in prey occur more slowly, the speed with which search images are developed will be less important. My results, where experienced fish could forage more efficiently than naive fish, whilst not providing direct evidence for acquisition of a search image, could be explained by this process (Hughes & Croy 1993). This contrasts with a previous study where there was no indication that a search image might be retained by P. microps

(Magnhagen & Wiederholm 1982a). In my translocation study, experimental fish were allowed to forage for 24 hours, which did not appear to be sufficient time for naive fish to develop a search image and improve their foraging efficiency to match that of experienced fish.

Pumatoschistus microps is abundant in estuarine and shallow, coastal water environments where physicochemical conditions, and biotic factors such as prey availability, are highly variable (Moll er & Rosenberg 1982; Chapter I). Theoretical predictions of optimal foraging and behavioural plasticity suggest that a generalist strategy is appropriate under these conditions (Pyke et al. 1977; Komers 1997). In line with such predictions,

P. microps clearly has the morphology and general behavioural repertoire to deal with a range of prey sizes, shapes, and activities. Some degree of local specialisation is, however, apparent, probably through modifications of behaviour through learning.

Experimental studies in highly dynamic, stochastic systems such as estuaries frequently reveal, as in this study, that biotic interactions are varied and less consistent than in other more predictable systems This should, however, not preclude such experimental investigations, for despite more variable results, interesting patterns can still emerge.

Pomatoschistus microps has the ability to forage on a wide range of items following the ontogenetic shift to macrofauna prey, where the reduced efficiency associated with this generalist lifestyle may be offset, to some extent, by the ability to specialise and adapt

70 Chapter 4 - Common goby foraging plasticity foraging behaviour appropriately for local conditions. The speed with which this adaptation occurs does not appear to be sufficiently rapid to accommodate short-term (e.g. tidal or daily) fluctuations in prey but may be more suited to other rates of change in prey availability such as stochastic and environmental variation or seasonal recruitment.

71 CHAPTER 5

MORPHOMETRIC STUDIES ON THE COMMON GOBY

72 Chapter 5 - Common goby morphology

INTRODUCTION

Behavioural traits possessed by predators, such as search mode, capture strategy and handling methods, are often influenced by morphological characteristics and thus morphology and foraging ability are closely related (Wainwright 1988; Schluter 1993)

Morphology and diet may be linked in two ways: either prey selection may be morphologically constrained (Chao & Musick 1977; Webb 1984; Luczkovich et al. 1995;

Wainwright & Richard 1995) or environmental foraging constraints result in adaptive changes in feeding morphology and lead to some degree of dietary specialisation with increased efficiency (Moyle & Senanayake 1984; Wimberger 1994; Hjelm et al. 2001;

Mittelbach et al. 1999; Adams et al. 2003). For instance, zooplanktivorous fish have been characterised as developing small mouths located terminally on a slender body, and fish foraging on benthic macro-invertebrates are typically deep bodied with a large sub­ terminal mouth, providing better foraging for small items in open environments and more complex littoral habitats respectively (Ehlinger & Wilson 1988; Schluter & McPhail 1992).

Such changes in morphology have been the source of extensive study and have been recorded in response to several parameters including diet (Hjelm & Johansson 2003;

Hegrenes 2001; Wimberger 1992), predation risk (Bronmark & Miner 1992; Tollrian &

Harvell 1999; Rei yea 2001 ), social hierarchy (Jarvi 1991 ), and reproductive strategy

(Gross 1996). Some of these studies have considered variation between pelagic and benthic morphs (Skulason et al. 1989; Schluter 1993; Wimberger 1994) although more attention has been paid recently to trophic polymorphisms and morphological trajectories through ontogeny (Arnqvist & Johansson 1998; Hjelm et al. 200 I; Svanback & Eklov

2002).

Ontogenetic niche shifts are widely recorded and provide an evolutionary solution to reduce mortality risk and increase fitness of individuals as they grow and develop (Werner

73 Chapter 5 - Common goby morphology

& Gilliam 1984; Werner & Hall 1988; Ebenman 1992). Changes in diet are one such shift

_ and often function to optimise net energy gain rate with increases in size (Werner &

Gilliam 1984; Jackson et al. in press). Shifts can also be driven by situations that are more

complex, where the balance between energy gain and other factors influencing

survivorship changes. For instance, there may be trade-offs between foraging rate and

predation risk, (Werner & Hall 1988; Schluter 1995; Svanback & Eklov 2003) or between

foraging rate and the energetic costs of different prey search and handling methods

(Anderson 1981; Norton 1991 ).

Given the link between morphology and foraging ability, there may also be a trade-off if

morphology is fixed. Although natural selection may act on foraging ability throughout

ontogeny, the stage with the greatest influence on evolutionary fitness may develop the

most efficient foraging morphology and this morphology may then become fixed through

ontogeny. A morphology that is efficient for a feeding mode at one stage of development

is unlikely to provide equal efficiency for modes that may be utilised at other stages

(Schluter 1995). Consequences of ontogenetic shifts, therefore, not only include changes

in diet, habitat, predation risk and trade-offs, but also morphological adaptation.

ln contrast, a situation described in Chapter 2 has been demonstrated, where diet shifts

occurred in the absence of habitat shifts, changes in predation risk, or different foraging

modes (Jackson et al. in press). Here, in Pomatoschistus microps, there was no apparent

trade-off associated with the change in diet. Shifts in prey choice maximised energetic

gain and were apparently driven by the metabolic demands of capture rate and handling

time of the predator changing with ontogeny. Foraging ability appeared to be energetically

optimal either side of the diet shift since other factors affecting survivorship or fitness did

not impinge on energy gain. In this case, the lack of a trade-off could indicate that there

would be no selection for a change in morphology required to improve efficiency

74 Chapter 5 - Conunon goby morphology following the diet shift. This is not to say, however, that morphological changes between stages would not confer further improvements in foraging efficiency but if a single form provides the best exploitation of resources at all stages then no divergence would be predicted (Schluter 1995).

To investigate potential morphological changes in P. microps, I applied recently developed morphometric techniques (Rohlf & Slice 1990; Bookstein 1991) to a range of go by sizes, encompassing individuals on either side of an ontogenetic prey shift. Pomatoschistus microps undergoes a canalised ontogenetic diet shift at 30 mm in length (Jackson et al. in press; Jackson & Rundle in review-a). Thus, this size threshold was used to demarcate a change in goby diet, with all fish < 30 mm assumed to have a meiofaunal diet and those>

30 mm, a macrofaunal diet (Pihl 1985; Doornbos & Twisk 1987; del Norte-Campos &

Temming 1994). Shape metrics were then related to change in diet to test whether there were no changes in morphology, as predicted from the absence oftrade-offs with other fitness correlates.

MATERIALS AND METHODS

In contrast to aspects such as foraging efficiency and predation risk, morphology is a physical parameter, more tangible, and easily assessed. Increasingly sensitive and powerful morphological techniques have been widely applied in anatomical, taxonomic, evolutionary and behavioural studies, and in some instances have been applied to shape changes associated with diet (Hjelm et al. 2001; Svanback & Eklov 2002, 2003).

Morphometric analysis was conducted on a range of sizes of Pomatoschistus microps in order to investigate how morphological parameters changed with ontogeny and diet.

75 Chapter 5 - Conunon goby morphology

Geometric morphometries and warp analysis

Over the last ten years or so, morphological studies have progressed from the traditional approach of examining how linear measurements covary, by maintaining the relative positions or geometry of multiple measurements throughout analyses and have been termed 'geometric morphometries' (Rohlf & Marcus 1993). Many of the new morphometric techniques begin with the representation of specimens by outlines or by configurations of biologically relevant co-ordinates (landmarks) in two or three dimensions

(Fig 51). Simple comparisons of specimen shape using such landmarks are not possible since they contain variation due to orientation, position and scale. This non-shape variation confounds comparisons of shape and hence must first be removed. An optimisation criterion (most commonly a least-squares approach termed Generalised

Procrustes Analysis) is used to eliminate non-shape variation by superimposing and overlaying specimens through translation, scaling and rotation (Rohlf & Slice 1990).

Configurations are superimposed, the centroids ('mid-point') translated to the origin and then scaled to a common size before being rotated to minimise the squared distances between corresponding landmarks. Iteration of this process allows the computation of a mean configuration that forms a consensus or reference shape (Rohlf & Slice 1990). The landmark variables are now true-shape variables and differences in the co-ordinates for corresponding landmarks are suitable for statistical comparison between specimens.

Principal components analysis (relative warp analysis) is conducted on the displacements

(bending energies or partial warps) required to translate consensus landmarks into the sample landmark locations. The resulting principal components or relative warps

(hereafter RW) provide a low-dimension description of the variation between specimens.

Deformations to the consensus shape, caused by RW scores can be visualised as a thin­ plate spline, where deformations are represented by stretches and compressions to a grid

(Bookstein 1991).

76 Chapter 5 - Common goby morpholo_gy

Goby morphology

Specimens were collected and sacrificed (as per Chapter 2) during September 2002 from

the upper estuary of the River Yealm, Devon, UK (50° 20' 24" N; 4° 01' 20" W). Images

of the preserved specimens were then captured for the analysis, using a digital camera. A

total of 54 gobies, between 15 and 35 mm, were measured and analysed for shape using

two-dimensional landmark morphometries. For photography, gobies were placed on a

white wax plate with all fins pinned out and all images were taken of the left side of the

fish in order to avoid asymmetrically derived variance. Nineteen landmarks were captured

from digital images using tpsDig (Rohlf2001) (Fig. 5.1). The computer program tpsRelw

was then used to scale, translate and rotate all specimens and defme the consensus shape

(Rohlf2003b). In order to control for the influence of reproductive development, I used

only young of the year fish (YOY); YOY gobies can grow rapidly and attain sufficient size

to undertake the ontogenetic diet shift at 30 mm.

Figure 5.1. Configuration of the 19landmarks (red circles) used in morphometric analysis of P. microps.

Departures from the consensus shape caused by R W scores for different size classes, were

interpreted as deformations to a thin-plate spline grid using tpsRelw (Rohlf 2003b). To

gain a better appreciation of the effect of shape changes, original landmarks, superimposed

on the specimen image, can be unwarped to a particular configuration specified by relative

warp scores using the program tpsSuper (Rohlf2003c). The set ofunwarped images can

77 Chapter 5 - Common goby morphology then be averaged to give a general representation of the shape change associated with individual relative warps.

Statistics

Gobies were placed into four size classes: 15-19, 20-24, 25-29, and 30-34 mm.

Representation of the overall change in morphology was obtained by incorporating all

principal components (relative warps) and comparing between size classes in a single analysis (MANOV A). The variance structure was first tested to ensure homogeneity

within the dependent variables. Post hoc pairwise comparisons are not possible for

MANOV A due to variance being spread across all variables, so shape differences between individual size classes cannot be valued. The change in shape between size classes caused

by individual relative warps was then assessed (ANOYA). Pearson's correlation coefficient was calculated for those warps that were significantly influenced by size.

Discrete diets exist either side of the shift in prey choice, with fish below the shift threshold(< 30 mm) assumed to have a meiofaunal diet and those above, a macrofaunal diet. As diet is directly related to goby size, knowing the sizes at which differences in shape occur allows inferences between diet and shape to be drawn. For those warps significantly related to goby size, post-hoc pairwise comparisons were conducted between size classes to see where differences in shape occurred and whether this was associated with diet. Analyses of variance were conducted in Minitab v 13.32 and morphometries software was downloaded from the Stony Brook morphometries website (Rohlf2003a).

RESULTS

Effects of size

MANOV A was conducted using the first six relative warps to assess general morphological alterations and revealed significant differences in shape between size classes (Table 5.1). RW4 displayed some heteroscedasticity but other variables were 78 Chapter 5 - Conunon goby morphology homogeneous and the overall covariance structure of the dependent variables was equal across size classes. The first six RWs described 73.51 %of the total shape variation and the remaining RWs, each explaining less than 5% of the variation, were excluded from the analysis (Table 5.2).

Table 5.1. MAN OVA of overall difference in body shape between goby size classes, based on the first six relative warps. F-values are Wilk's f... d.f. F size class 18, 127 4.800 <0 001

Goby length was significantly correlated with two warps, (RW1 and RW3), with the shape change represented by the two warps negatively related to size (Table 5.2)

Table 5.2. ANOVA on relative warp scores for the first six RWs for the effect of size class. For RWs significantly related to size, Pearson's correlation coefficient is shown. % F-ratio Correlation YOY gobies variation p (d.f. 3, 50) coefficient explained RWI 34.05 14.26 <0.001 -0.66 RW2 11.72 1.44 >0.05 RW3 9.59 3.23 <0.05 -0.33 RW4 6.37 1.78 >0.05 RWS 6.32 2.36 >0.05 RW6 5.46 0.38 >0.05

Changes in shape, correlated with a increase in size, were not extensive but were represented by a slight deepening of the overall body, a reversal ofbody curvature (RWI) and a larger head (RW3). The changes in shape between extreme values for these two

RWs for the smallest and largest goby size-classes are presented as deformations to a thin plate spline grid of the consensus shape (Fig. 5.2). Changes in average, unwarped fish shape, between the smallest and largest size classes, caused by a combination of the two

RWs correlated with size, are also shown (Fig. 5.3).

79 Chapter 5 - Common goby morphology

Head Tail

16-20 mm

a)

31-35 mm

16-20 mm

b)

31-35 mm

Figure 5 .2. Deformations to the consensus configuration represented as thin plate splines. a) RW 1 and b) RW 3. For each RW the deformation associated with smallest (16-20 mm) and largest (31-35 mm) gobies are shown.

16-20 mm 31-35 mm

Figure 5.3. Fish body shape representing the smallest and largest goby size classes. Shapes were obtained by first determining the landmark configuration specified by the combined deformations resulting from extreme warp scores for RWs 1 & 3 in each size class. Specimen images are then unwarped to this configuration and an average image derived.

80 Chapter 5 - Common goby morphology

Effects of diet

The locations of the significant differences in the scores of relative warps one and three

(see ANOV A above) were illustrated by pairwise size class comparisons (Table 5.3). For

R W I there were significant differences in shape between size classes one & three, one & four, two & three and two and four. The sizes over which the diet shift occurs (between classes three & four) does not demonstrate any significant difference in shape for this warp. For RW3 there was a significant difference in warp score between size classes two

& four. The sizes classes over which the diet shift occurs again demonstrated no significant change in shape.

Table 5.3. Post-hoc multiple pairwise comparisons (p-values) for warps significantly related to goby length. Shaded cells indicate significant differences between size class warp means. RWI Goby size class 2 3 4 (15-19 mm) (20-24 mm) (25-29 mm) (30-34 mm) I 2 0.059 3 r ...

DISCUSSION

Many species alter resource use with ontogeny as a way of maximising fitness and dealing with variable environments (Mittelbach 1981; Persson & Greenberg 1990b) (Fig 5 Aa).

Ontogenetic changes in diet can result in trade-offs, either between foraging efficiency and some external influence such as predation risk or costs between different foraging strategies (Fig 54b). Such trade-offs between ontogenetic stages may expose the predator

81 Chapter 5 - Common goby morphology to conflicting or antagonistic selection pressures (Webb 1984; Schluter 1995; Robinson et al. 1996). Given the close link between foraging efficiency and morphology, these trade­ oft's are likely to have a structural basis and selection will thus favour changes in morphology to reduce the cost of the trade-off Numerous studies have demonstrated links between diet and morphological change, whether for gill raker size and spacing (Eggold &

Motta 1992; Hjelm & Johansson 2003), change in feeding structures (Moyle &

Senanayake 1984; Adams et al. 2003; Chapter 2) or overall body shape (Hjelm et al. 200 I;

Svanback & Eklov 2002). These structural changes can, in turn, lead to morphological trade-offs (Svanback & Eklov 2002) and the trade-off costs experienced by different morphs, required for different strategies to be adaptive (Robinson et al. 1996), have been empirically demonstrated (Schluter 1995; Hjelm & Johansson 2003; Svanback & Eklov

2003)(Fig. 5.4c). Where morphological trade-offs do exist between life stages, there will be selection pressure for this compromise to be reduced and, the greater the trade-off, the greater the pressure for ameliorative shape change in one of the stages (Fig. 5.4d).

Pomatoschistus microps settle from being planktivorous larvae to a benthic, littoral lifestyle at about 12 mm standard length. Juveniles feed on meiofauna (harpacticoid copepods and ostracods) until they reach 30 mm when there is a dramatic and predictable shift in prey choice to macrofaunal items. Given the considerable differences in prey size and shape either side of the shift, there is potential for there to be morphological limitations to foraging efficiency for one of the diets (Fig 5.4c). This diet shift, however, serves to maximise energy intake through ontogeny and is driven by metabolic parameters (e.g. scope for activity and capture rate) (Jackson et a/. in press; Jackson & Rundle in review-a).

Geometric morphometries applied to a range of sizes of P. microps across the diet shift, revealed that although there were size-based allometric shape changes, there were none associated with the ontogenetic shift in prey choice.

82 Chapter 5 - Conunon goby morphology

In contrast with all this expectation of structural change, this result is in agreement with

Werner (1986) who suggests that many changes in resource use are made without any changes in morphology. Shape changes may not occur for three reasons. First, morphological improvements for foraging efficiency in one feeding mode may not be

a) -··-··· - Prey 1 --Prey 2 b) --- -foraging -- e.g. predation risk,reproduction

Cl>. c u ·- c ·----···--·------./ (/) Cl(]) (/) ro ·­ (]) .._ u c 0 ·- :!: LL~ _;------·--- LL

Ontogenetic stage Ontogenetic stage c) --···--···· Morphology 1 d)

~ ()' --Morphology 2 .E c Ql ~ ·u :::J :i: ~ Ql Ql .._Ql Clc Cl c.ro c c.C ·a, 0 u ~ t5 0 Ql LL Ql (f) Trade-off magnitude Prey type

e) c 0 :;::; ro ~ 8 u :;::; Ql c Ql ~ L______Potential for morphological change

Figure 5.4. Conceptual models illustrating patterns of foraging efficiency, trade-offs and morphological change. a) Foraging efficiency with ontogenetic change in prey type. b) Fitness trade-off between foraging efficiency and some parameter such as predation risk, reproduction or competition. c) Morphologically restricted foraging efficiency on different prey types d) Increasing trade-off size positively correlates with selective pressure for compromise reduction. e) High genetic correlation between character expression during ontogenetic stages limits the potential for morphological change.

83 · Chapter 5 - Common goby morphology possible due to physical constraints arising from structures required for other modes

(Werner 1988). Second, the degree to which selection can act differently on separate stages is determined by the level of correlation between genes controlling the morphology of the different stages (Kirkpatrick 1988) (Fig 5.4e). The presence oftrade-offs between life stages indicates that there will be strong selective pressure acting to try and break up these genetic correlations (Ebenman 1992). Finally, there may be no adaptive need for change. Where a single morph provides the best solution during different stages, then there is no reason to expect diet-driven ontogenetic change (Schluter 1995).

The lack of non size-based morphological differences shown here in P. microps, between individuals feeding on different diets could have been due to either some combination of structural constraint and strong genetic correlation preventing responses to divergent selection or an absence of divergent selection pressures between the two diet stages. In this case, with no change in habitat or predation risk, there is no trade-off between foraging efficiency and survivorship and since there is no alteration in foraging mode (i.e. sit-and­ wait), there is no trade-off between foraging efficiency and the way in which prey is caught. Intrinsically driven prey choice is energetically optimal, except for a short transitional phase (Chapter 3), and so provides no scope for trade-offs.

This absence oftrade-offs, indicates that there may be no selective pressure for divergence, whether or not there is genetic correlation, and hence no consequential change in morphology. The original prediction, based on this apparent absence oftrade-offs, that there would be no selective pressure for morphological change was borne out by the lack of diet-driven change in morphology For such diet shifts to be adaptive, there must be some cost to continued exploitation of a particular prey (Robinson et al. 1996) and this was demonstrated in Chapter 6 for P. microps, where individuals in excess of 30 mm,

84 Chapter 5 - Common goby morphology remaining on a meiofaunal diet lost condition and had reduced fitness (Jackson et al.

2002).

In conclusion, the adaptive and energy gain maximising ontogenetic diet shift, exhibited by

Pomatoschistus microps is not associated with a change in morphology. This is likely to be a consequence of no trade-off being elicited by the change in prey choice. With no trade-off to influence selective pressures either side of the diet shift, there should be no adaptive reason for morphological change. This predator has developed a generalist niche where a single morph provides the best solution during all the benthic life stages, despite considerable ontogenetic differences between diets. This generalist nature may be most appropriate for inhabiting dynamic and unpredictable environments such as the estuarine habitat of the common goby.

85 CHAPTER6

FITNESS CONSEQUENCES OF PREY DEPLETION FOR THE COMMON GOBY, POMATOSCHISTUS M/CROPS.

Part of this Chapter has been published as

Jackson, A.C., Rundle, S.D. & Attrill, M.J. 2002. Fitness consequences of prey depletion for the common goby, Pomatoschistus microps. Marine Ecology Progress Series, 242, 229-235.

86 Chapter 6- Resource depletion for common gobics

INTRODUCTION

Shallow coastal waters, including estuaries, are environments that often exhibit high variability in biotic and abiotic (e.g. temperature, salinity, pH) factors that can lead to inconsistent degrees of reproduction, recruitment, production, predation and competition.

Predators in such environments are highly likely to be able to feed on different prey types

(Komers 1997) as the abundance of prey populations may vary dramatically (Moll er &

Rosenberg 1982; Jensen & Andre 1993).

The prey ofbenthic-feeding fish in such systems fall into two distinct size-classes: the meiofauna (63 IJ.m< x <0.5 mm) and macrofauna (>0.5 mm) (Warwick 1984). Where such predatory fish show large ontogenetic increases in size, the potential to shift from small to large-bodied prey is high (Ivlev 1961; Schoener 1971; Stephens & Krebs 1986) and several fish show ontogenetic changes in diet, relying initially on meiofauna before shifting to macrofauna (Bodiou & Villiers 1979; Evans 1984; Doornbos & Twisk 1987; del Norte­

Campos & Temming 1994; Aarnio 2001). For some species, these shifts are not fixed in terms of timing, duration or degree (Grossman 1980; Pihl& Rosenberg 1982; Werner &

Gilliam 1984; Hjelm et al. 2000), suggesting an adaptive response to fluctuations in prey availability. For others, there may be some level of phenotypic canalisation (Chapters 2 &

3). Of most significance is the potential for low or failed recruitment of macrofaunal prey species, where a reversion to feeding primarily on meiofauna would be a valuable alternative strategy. Such reversions may be predictable but should incur a cost (Ebenman

1992; Komers 1997). For example, available biomass may be greatly reduced, energy expenditure for foraging increased, exposure to predation risk increase or reproductive ability may become impaired. Predictions of niche shifts and their consequences have been explored theoretically (Grossman 1980; Werner & Gilliam 1984; Persson 1990) but

87 Chapter 6- Resource depletion for common gobies few studies provide empirical evidence for the ecological consequences of ontogenetic shifts in diet in benthic predatory fish (but see Olson 1996).

The benthic goby, Pomatoschistus microps exhibits highly flexible behaviours in feeding, habitat choice and reproductive tactics in response to abiotic and biotic variability of the shallow coastal waters where it lives (Edlund & Magnhagen 1981; Magnhagen &

Wiederholm 1982a, b; Magnhagen 1986, 1988, 1998; Chapter I, 4). Here I assess the consequences of resource (macrofauna) depletion for the fitness of male P. microps, by manipulating prey assemblages in laboratory trials.

METHODS

General experimental procedure

This study was carried out during July and August 200 I at the Kristineberg Marine

Research Station (KMRS) in the Gullmarsfjord the Swedish west coast. 1 used manipulated benthic prey assemblages in mesocosms to investigate the consequences of prey availability for male gobies. Male fish were maintained in mesocosm treatments representing 'natural' sediment, sediment from which macrofauna had been removed and a sediment control for the macrofauna removal procedure (see below). The removal of macrofauna mimicked natural variation in prey availability in shallow bays of the

Gullmarsfjord that can occur due to failure in macrofauna recruitment (Moller &

Rosenberg 1982). Such variation in prey availability may alter feeding behaviour (i.e., a shift back to meiofauna) resulting in differential fitness.

I used fish of 30-35 mm standard length (SL), a size that feeds in the field primarily on macrofauna, but also meiofauna; a pilot study demonstrated that fish fed on the available fauna under the experimental conditions. The condition status of fish was assessed after being maintained in experimental mesocosms for two weeks

88 Chapter 6 - Resource depletion for common gobies

Many studies that aim to assess the implications of trait shifts simply assume that a chosen strategy is optimal and do not incorporate a direct measure of fitness. Here I use mature adult males as an ideal experimental animal for assessing fitness, recording two commonly used measures of body condition. In addition, I use nest-building ability, a male character under both natural and sexual selection (Jones & Reynolds 1999b; Svensson & K varnemo

2003), as a more direct measure of fitness.

Experimental animals: collection and preparation

Mature adult male fish were collected using a I m push-net with a 2 mm mesh collecting bag from a shallow, muddy inlet on the south side of the fjord (near Dragsmark) where they occurred in high densities. Fish length was standardised at between 30-35mm in order to reduce size-dependent influence on feeding and nesting behaviour. The mesocosm system consisted of twelve, 90-litre black plastic containers (circular, 50 cm 0,

40 cm deep) containing sediment (see below) and -60 litres of continuously flowing water abstracted from the surface of the fjord ( 17-24 °C and salinity range 18-25). Sediment was collected using cores (10 cm 0 & 4 cm depth) from the shallow, sandy Finnsbo bay on the north side of the fjord. Core locations (16 per mesocosm) were randomly selected from an homogeneous area of sediment Experiments were conducted under artificial light approximating ambient conditions (i e. 19:5 hours light: dark). Mesocosms were left to settle and establish for 24 hours before introducing fish; fish were kept in a holding tank for at least 48 hours before introduction to the mesocosms and fed chopped mussel

(Mytilus edulis L.).

There were three sediment treatment types, each replicated 4 times: 'Macrofauna removal'

-sediment cores were washed through a 0.5 mm sieve into the mesocosm and macrofauna discarded; 'Sieve control'- sediment cores were washed through a 0.5 mm sieve into the mesocosm and macrofauna were then returned to the sediment; and 'Untreated'- 16

89 Chapter 6 - Resource depletion for common gobies loaded sediment corers were placed adjacently in each mesocosm in the field, with corer tubes being removed only on return to the laboratory, thus minimising disturbance of the sediment. Using 16 cores per mesocosm gave fauna! abundances only slightly less than in the natural environment.

At the start of the experiment, four fish were added to each mesocosm giving a density of

2 20 fish m- , comparable to densities observed in the field (Pihl & Rosenberg 1982;

Doornbos & Twisk 1987). The experiment was duplicated to provide replication through time and each ran for two weeks, during which time any fish that showed signs of stress or disease were removed and not replaced. Diseased fish were sacrificed as before and where possible, stomach contents of these fish were examined to note the presence of feeding.

On termination ofthe feeding experiment and nest-building assessment, fish were sacrificed, before fixation in 4% buffered formaldehyde.

Prey availability

Prey abundance was measured at the start and end of experiments using one sediment core

(35 mm 0) from each mesocosm. Macrofauna were removed by sieving onto a 0.5 mm mesh and meiofauna were extracted using Ludox (Somerfield & Warwick 1996). Samples were fixed in 4 % buffered formaldehyde and stored in 70% alcohol. Fauna were sub­ sampled where appropriate before being identified to major group and enumerated. Initial available biomass between treatments, for the main prey types was calculated as ash-free dry weight (AFDW), using mean prey sizes from the mesocosms along with published values oflength:mass relationships, specific gravity, wet:dry weight and dry:AFDW ratios

(Warwick 1984; Doornbos & Twisk 1987). Total initial macrofaunal biomass was estimated for each treatment by adding the Corophium AFDW removed by the fish to the macrofaunal AFDW remaining at the end. The remaining AFDW was measured using a standard weight-loss on combustion procedure (Holme & Mclntyre 1984).

90 Chapter 6- Resource depletion for common gobies

Two-way ANOV A and post hoc pair-wise comparisons (SNK test) were used to test for differences in prey availability and biomass between dates and treatments. Where required

(Cochran's test), data were first square-root (x+l) transformed to achieve homogeneity of vanance.

Fish condition measures

At the end of the experiments, fish condition was measured in two ways.

I I) Hepatosomatic index HSI = -x100 eqn 6.1 b where I was the wet weight of liver (g) and h was wet body weight minus liver (g)

(Weatherley 1972).

k = IOO,OOOxW 2) Condition factor eqn 6.2 L3 here, W was wet weight (g) and L was standard length (mm) (Weatherley 1972).

Standard lengths were measured to the nearest mm using Vernier callipers and weights to the nearest mg using a top pan balance. Condition indices are frequently used as an indication of the well-being of fish. The two measures used here, HSI and condition factor

(k) are suitable since they are less dependent on maturity or reproductive status than other indices (e.g. gonadosomatic index). All between-treatment comparisons for fish condition used a three-factor, mixed model, analysis of variance (See Table 6. I).

Measurement of nest-building

Male common gobies provide all parental care, consisting of nest construction and care of the eggs until hatching. Quality of nest construction may vary considerably and this character has been previously used in experiments on goby reproduction (Jones &

91 Chapter 6 - Resource depletion for common gobies

Reynolds 1999b). Fish were maintained individually in visually-isolated 22litre glass tanks furnished with ea. 2 cm sieved muddy sand, half a ceramic flowerpot ( 4 cm 0), and continuously flowing surface water under a 19:5 hour light regime. The flowerpot, placed on its side, was used as an analogue of the bivalve shell that would be used for nest building in the natural environment (Magnhagen 1992). Nest construction was assessed after 24 hours, previous studies having shown that most nest-building males will have completed construction after this time (Magnhagen 1992; Jones & Reynolds 1999b). Nest building was also assessed in a sample of28 reference fish, removed directly from the natural environment I followed a standard method to assess nest quality (Kvarnemo et al.

1998) focussing on nest coverage with sand as the most important fitness correlate for which 1 measured two parameters.

I) Complete nest roof coverage.

For each treatment, the ratio of nests with (i.e., the whole of the flowerpot covered with sediment) and without roofs was recorded. Nest-building probability in reference fish was used to generate an extrinsic hypothesis against which the ratio of roofs: no roofs for each . treatment was compared by calculating exact binomial probabilities for the observed differences. Low expected values made the use of other frequency analyses such as chi­ square or G-tests inappropriate (Sokal & Rohlf 1995).

2) Nest entrance diameter.

On completion of nest construction, entrance diameter was measured to the nearest mm at the widest point. As with fish condition, a three-factor, mixed model, analysis of variance was used in between-treatment comparisons of nest entrance diameter.

92 Chapter 6 - Resource depletion for common gobies

Nest quality determinants

In order to investigate potential causal factors for differences in the nest-building activity of individual fish, I compared mean body length and condition (using !-tailed t-tests) between fish that covered nest roofs and those that did not. Body size has been hypothesised as a major factor affecting likelihood ofnest construction (Magnhagen 1992) and nest quality may be a predictor of fish condition (K vamemo et al. 1998). Linear regression was used to investigate whether length and condition were likely to be factors in determining nest entrance diameter. T-tests were one-tailed since nests with covered roofs were considered more likely to have been built by larger and better condition fish. All analyses of variance were carried out using the programme GMAV5 for Windows

(Underwood & Chapman 1998). T-tests and linear regressions were conducted in

Minitab™ v.l3 and binomial probabilities were calculated using MSExceL

RESULTS

Several fish showed signs of disease during the feeding trials and were removed from the mesocosms. In order to maintain a balanced design, two fish from each mesocosm were used in subsequent analyses, giving eight replicate fish per treatment from each experiment.

Fish diets and initial prey abundances

Stomach contents analysis from the pilot study and diseased individuals indicated that in fish from macrofauna removal mesocosms 83% had eaten meiofauna (Copepoda and

Ostracoda). From mesocosms with macrofauna, 82% had eaten Corophium and 36% meiofauna.

There were no differences between date or treatment in initial, meiofauna prey abundance

(F1.12= 0 12, p > 0.05, F2,2= 0.21, p > 0.05, respectively) (Fig. 6.la) or biomass (AFDW)

(F 1.12 = 0.28, p > 0.05, F2,2 = 0.21, p > 0.05, respectively (Fig. 6.1 b). In addition, mean 93 Chapter 6 - Resource depletion for common gobies meiofauna abundance did not change over the duration of the experiments (t.os. 24 = -1.39, p

> 0.05). Corophium, the principal macrofaunal prey of common gobies in the Gull mar

Fjord (Edlund & Magnhagen 1981; Pihl 1985; Magnhagen 1986), differed significantly in abundance between treatments (F2, 18 = 36.26, p < 0.001) but not date (F 1,18 = 0.00, p >0.05).

Results for Corophium biomass were almost identical. The 'macrofauna removal' sediment had the lowest and 'untreated' sediment the highest Corophium abundances.

Post hoc pair-wise comparisons (SNK test) revealed significant differences between all treatments (Fig. 6. I a). Figure 6.1 b shows how the AFDW attributable to Corophium compares with that for other macrofauna and also for meiofaunal prey.

Fish condition measures

There was no significant difference in the size or condition factor of fish between dates or treatments. However, fish maintained on 'macrofauna removal' sediment treatment had a significantly lower HSI than fish in control treatments (Fig. 6.2 and Table 6.1 ). Fish in the second experiment also had significantly lower HSI than those in the first (Table 6. I).

Table 6.1. Analysis of variance for differences in common goby hepatosomatic index arising from macrofaunal prey depletion. t The non-significant interaction Date*Treatment has been eliminated

Source d.f S.S. MS. F p Date 6.23 6.23 5.26 0.034 Treatment 2 22.76 11.38 9.61 0.001 Mesocosm (Date*Treatment) 18 21.32 I. 18 1.57 0.150 t Date*Treatment 2 2.46 1.23 1.04 0.374 Residual 24 18.12 0.76 Total 47 70.88

Measurement of nest-building

The roof: no roof ratio in the non-experimental fish was 3:1 (i.e. the probability of the nest roof being covered was 0 75) and was used as the 'expected' value. Fish from the

'macrofauna removal' treatment exhibited significantly lower nest-building activity

94 Chapter 6 - Resource depletion for common gobies

a) b) 12 D Other m acrofauna 80000 1111 Meiofaunal prey 10 rn1 Corophium Q) 70000 IEJ Corophium (.) N 11111 Meiofauna r:::: 60000 - ea - 'E 8 ,~ 50000 C') r:::: E ::I 40000 - 6 .c 1/) 3: ea 0 30000 c r:::: r:::: LL 4 ea 20000

Figure 6.1. Mean abundance and biomass of available prey with sediment treatment (macrofauna removal, sieve control and untreated). a) Mean meiofaunal (Copepoda and Ostracoda) and macrofaunal (Corophium) abundance (nos. m-2 + s.e.) showing no differences in meiofaunal abundance but a significant reduction in Corophium abundance for the macrofauna removal treatment (ANOVA, p < 0.001) and b) mean prey biomass (AFDW g m-2 + s.e.) (meiofauna, Corophium and other macrofauna) with treatment.

95 Chapter 6 - Resource depletion for common gobies

5

4 en- :I: 3 c: m 2 E 1

Macro removal Sie\€ control Untreated Treatment

Figure 6.2. Consequence ofmacrofaunal prey depletion on mean male goby HSI (+ s.e.). Fish from treatments without macrofauna had significantly lower HSI, (ANOVA, p < 0.01).

compared with this reference (p = 0.009) but neither ofthe treatments containing macrofauna differed from reference fish (Fig. 6.3). There was no significant difference in nest entrance diameter between dates CFt .18 = 1.10, p >0.05) or treatments (F2,2= 0.20, p >

0.05).

Nest quality determinants

For individual fish, probability of roof covering was not related to length (t.o5, 52 = 1.63, p >

0.05) and there was no significant correlation between length and entrance diameter.

Condition factor was not correlated with any measure of nest-building activity but there was a significant difference in HSI between fish that covered roofs and those that did not

(t.o5, 52 = 2.85, p < 0.01) (Fig. 6.4). A significant negative relationship also existed between

HSI and entrance diameter although variability was high (r2 = 0.21 , p < 0.001).

96 Chapter 6 - Resource depletion for common gobies

0.8 0.7 ·-~ 0.6 ·--.c 0.5 cu .c 0.4 0 ~ 0.3 a.. 0.2 0.1 0 Expected Macro Sie\e Untreated remo\al control Treatment

Figure 6.3. Consequence of macrofaunal prey depletion on likelihood of nest coverage compared to non-experimental fish. Fish maintained without macrofauna were less likely to cover their nest with sediment (exact binomial probability, p = 0.009).

4

en 3 J: t: 2 cu Cl) E 1

0 Roof covered Roof not covered Nest status

Figure 6.4. Mean HSI (+ s.e.) of male gobies that covered their nest with sediment and those that did not. Nest coverers had a significantly greater HSI, (t-test, p < 0.01).

97 Chapter 6 - Resource depletion for common gobies

DISCUSSION

The depletion of macrofaunal prey resources had clear effects on male common gobies, leading to significantly lower HSI and nest building when maintained in treatments with macrofauna removed compared with those containing macrofaunal prey (Figs. 6.2 and

6.3). In addition, HSI and nest quality were strongly linked (Fig. 6.4). Together, these results demonstrate a strong negative effect of macro fauna! prey depletion on fish condition and reproduction, as gauged by nest building activity. The implications for field populations may be considerable; the common goby is short-lived, breeding repeatedly through the summer before dying in its second winter (Miller 1975). Loss of condition in years where macrofaunal recruitment fails may not only increase disease and starvation

(Smith & Wooton 1995) but also affect current and future reproductive success. Pihl &

Rosenberg ( 1982) have previously shown that recruitment of common gobies can be highly variable and it may be that such variation is a consequence of prey depletion.

Male parental care involves construction and maintenance of a nest and the care of the eggs until hatching (Magnhagen 1992). Here, prey availability clearly had an effect on the males' ability to construct nests (Fig. 6.3); a lack of macro fauna! prey reducing the likelihood that high quality nests will be constructed when compared to non-experimental fish. Two important characteristics in nest construction are susceptibility to predation and ease of ventilation. High quality nests, with complete sediment coverage, are more cryptic and less susceptible to egg (e.g. Carcinus maenas) or aerial predators, resulting in greater average hatching success (Jones & Reynolds 1999b). Similarly, sediment around the front of the nest will determine entrance size, a further component of nest crypsis. Males may consequently build nests with entrances as small as they are capable of ventilating successfully with no reduction in hatching success (Jones & Reynolds 1999b). Females preferentially choose males with smaller nest entrances (Jones & Reynolds !999b;

98 Chapter 6 - Resource depletion for common gobies

Svensson & Kvarnemo 2003). Nest construction is thus a product ofboth natural and sexual selection and as such is a direct measure of male fitness. The absence of differences in nest entrance diameter between treatments and a weak correlation with HSI perhaps indicates that entrance diameter is a less sensitive measure of male quality than roof cover.

Nest entrance diameter was observed to vary with time as the fish moved in and out of the nest, so its utility as a measure of fitness may be questionable.

The clear effect of prey resource depletion on both HSI and nest quality bolsters the

K varnemo et al. (1998) assertion that nest quality may be an indicator of fish condition and suggests a potential causal link with food availability as a determining factor in nest construction ability. The failure of condition factor, k, to mirror these patterns may be further support for the utility ofHSI as a sensitive measure of fish condition as a consequence of varying resource availability.

I suggest that initial prey abundance in sediment with macrofauna was sufficient to maintain fish condition over the two-week period, i.e. macrofaunal food was in excess.

The significant reduction in HSI between the two start dates (Table 6.1) may be a consequence of males in the second experiment, which started three weeks after the first, having expended more energy in breeding. Since males are tied to the nest during courting, mating and egg development, feeding opportunities are reduced (Magnhagen

1986), potentially leading to reduced condition.

The loss of condition and subsequent influence on nest building and fitness may have arisen from one or a combination of reasons. Firstly, male gobies may simply have been unable to forage on meiofauna due to an irreversible switch to macrofaunal prey. This seems unlikely, however, as meiofauna were found in the stomach contents of fish removed from the experiment and in similar sized fish from the natural environment.

99 Chapter 6- Resource depletion for common gobies

Secondly, removal ofmacrofauna may have drastically reduced total prey biomass, with the remaining meiofaunal biomass insufficient for the energy requirements of male common gobies in this size range. The biomass contributed by meiofaunal prey was ea. I 0

% that of Corophium (Fig. 6. I b), suggesting this might be a possibility. However, meiofaunal abundance was not significantly lower in macrofauna removal treatments at the end of the experiment, which might be predicted if these prey were a limited resource.

Thirdly, gobies may have switched to meiofaunal prey, with associated costs in this plasticity in feeding behaviour (Ebenman 1992; Komers 1997) contributing to the loss of condition, e.g. through increased search and handling times for a lower energetic return. It seems likely that this is the most probable explanation for the reduction of condition in common gobies and further investigation of this mechanism would be profitable.

In conclusion, a manipulated depletion of macrofaunal prey resources appears to have caused a reversion in mature male common gobies to feeding on meiofauna, indicating a degree of plasticity in foraging behaviour. This depletion had serious consequences for the gobies, manifested here in terms of reduced hepatosomatic condition and nest building ability. This result is in clear agreement with the predictions ofthe optimal foraging model and observed prey consumption (Chapters 2 & 3) where energy gain rates, for gobies >30 mm that include meiofauna in their diet, are sub-optimaL This sub-optimality was reflected here in the loss of condition and fitness. Such reductions in the individual fitness of the most abundant benthic-feeding fish in shallow marine systems are also likely to have marked consequences and implications at the population and assemblage leveL

100 CHAPTER 7

DISCUSSION

THE COMMON GOBY

Pomatoschistus microps is an ideal model organism, and was successfully used in this thesis to test hypotheses concerning several aspects of prey choice, including optimality, morphology, fitness, and plasticity. Empirical observations have previously indicated that common gobies display a shift from feeding on small prey items (i.e. copepods), to a variety of larger prey types (Fig. 7. I) (e.g. Corophium, chironomid larvae and Nereis) at a length of around 30 mm (Pihl 1985; Gee 1989; del Norte-Campos & Temming 1994).

The life cycle of P. microps can be divided in several ways, for example in terms of habitat, size, diet and maturity, and Figure 7.1 outlines how this diet-shift fits into the general life history of P. microps. This thesis tested a range of hypotheses that together investigate the causes and consequences of prey choice and diet shifts in this species of goby although its scope was limited to stages following the pelagic larval phase. My studies dealt with individuals ranging in size from recruits, newly settled from the plankton at 12 mm, up to full grown, reproductively competent adults of 45 mm. The causes and consequences of prey choice in earlier stages are mentioned only in passing here, and may be quite different from the patterns and processes affecting juveniles and adults. Figure 7. I illustrates how the diet shift at 30 mm does not appear to be linked to other life history attributes such as change in habitat or sexual maturity. This general discussion below highlights the findings of these studies within the context of the whole life-cycle of the common goby.

101 Chapter 7 - Discussion

CAUSES OF PREY CHOICE

Where behavioural decisions and their repercussions influence fitness, an organism's response to the factors driving behaviour will be highly adaptive. Responses to prey choice decisions are consequently expected to be adaptive and function in a way that optimises fitness. Prey choice is a direct representation of energy gain and this in turn, is intimately linked with growth rate, a parameter strongly correlated with evolutionary fitness (Schultz et al. 1991; Conover 1992; Schluter 1995).

Changes in prey choice with ontogeny are widely recorded in fish, with prey size typically increasing with predator size (Mittelbach 1981; Peters 1983). Net energy gain is dependent on three main factors the energy available in the environment (prey size and abundance), the predator's ability to obtain that energy (encounter rate and handling time) and the costs associated with foraging (search and handling costs).

Energy gain, however, is not the only factor that influences fitness (Fig. 7.2). Competitive or hierarchical interactions and predation risk can directly influence fitness or survivorship.

Existing predictions of diet shifts using optimal foraging theory illustrate the prevalence of shifts associated with changes in habitat and other external conditions (Werner &

Mittelbach 1981; Sih 1984; Robinson & Wilson 1998; Persson & Greenberg 1990b).

Drivers of prey choice are not limited to extrinsic effects as internal mechanisms can also play an important role, influencing a predator's ability to obtain food and the energetic costs of doing so. In particular, morphological restraints such as gape-limitation are recognised as being central in determining prey consumption (Persson et al. 1996; Nilsson

& Bronmark 2000). Prey encounter and capture can also be regulated by other intrinsic drivers such as metabolic rate, reproductive demands, locomotory ability, sensory limitation, learned behaviours and parasite load (Fig. 7.2) (Webb 1984; Magnhagen 1986;

Hughes & O'Brien 200 I; Jackson et al. in press; Walton et al. 1992; Chapter 2, 3).

102 Chapter 7 - Discussion

Egg in nest, Pelagic Newly settled Large juvenile/ Mature adult guarded by male larva juvenile small adult Description

Upper estuary, Coastal waters, Location Upper estuary, benthic I( benthic )11( pelagic )11( )I

Size 1 mm 3-12 mm 13-30 mm 31-55 mm

Max. age Duration I( 6-19 days )I I( 6-9weeks )I I( 8-11 months )I I( 6-8 months )I 20 months Copepodites, Corophium, Nereis, rotifers, nauplii Copepods, Ostracods Diet shift Chironom.id larvae Diet I( Yolk )11( )I I( )I

UK - April to August Reproduction Sweden - June to August Figure 7 .1. Schematic illustrating various life history parameters and ontogenetic stages of Pomatoschistus microps.

103 Chapter 7 - Discussion

Pomatoschistus microps, a benthic foraging fish of estuaries and shallow coastal waters, appears to exhibit an ontogenetic shift in diet; empirical observations suggest that prey choice shifts from meiofauna to macrofauna at a standard length of30 mm (Pihl 1985;

Doornbos & Twisk \987; del Norte-Campos & Temming 1994; Chapter 3). As a sit-and­ wait predator, this species appears to act as a cost or activity minimiser (Magnhagen 1986) and rather than maximising net gain per se, I predicted go by prey choice to minimise the cost or time required to obtain their daily energy requirements.

A realistically parameterised foraging model clearly illustrated a diet shift at the predicted length, but illustrated that prey choice, rather than minimising costs, maximised net energy intake rate through ontogeny (Chapter 2). This diet shift was particularly interesting and, unlike many examples of ontogenetic prey shifts, occurred without any change in external factors such as habitat occupation, or prey availability (Fig 7.2). With no habitat shift or apparent change in prey capture technique (i.e. sit-and-wait) with ontogeny, it also seems unlikely that predation risk was driving the observed diet shift. It is possible, however, that as gobies attained a particular size they were included as a profitable item in the diet of some other predator (Fig 7.2), with this change in predation risk causing the shift in prey choice.

In the absence of external factors, intrinsic processes must be responsible for driving prey choice. Gape limitation, a major internal driver of prey choice, did not appear to be important in this case. Mouth size in P. microps increased isometrically with growth

(Chapter 5) and actual mouth sizes suggests that even quite small fish have sufficient gape to ingest the smaller macrofaunal size classes. The common goby diet shift was determined by components of the foraging model influenced by metabolism, namely search and handling costs and capture rate. It appears that ontogenetic change in the

104 Chapter 7 - Discussion Competition,, Habitat change Prey availability Predation risk t Macrofauna ~--- ~- "' y /

Extrinsic ~~ ----~-.------· ft-0:) -~Prey Intrinsic ~ choice ~ ------

Ontogeny Meiofauna Reproduction Parasites Metabolism Morphology Sensory limitation Figure 7.2. Conceptual figure illustrating the main potential causes of prey choice in the common goby. Large black arrows indicate aspects considered in this thesis. 105 Chapter 7 - Discussion difference between passive and active respiration rates (the scope for activity) is responsible for the change in net energetic benefit of prey (Fig 2.4).

Quantitative field data were used, firstly, to validate model predictions and, secondly, to examine the importance of intrinsic metabolic drivers of prey choice in the context of variability in prey availability (Chapter 3). Prey abundance is often cited as a key driver of prey choice (Magnhagen & Wiederholm 1982a; Magnhagen 1985) and clearly at extremes

(e.g. an absence) must be a determining factor (Sih 1984; Hughes & Croy 1993). Jones et al. (2003) suggest that if the parameters that drive shifts in diet are constant between generations, then the shift should occur at a predictable point from generation to generation. Where the parameter varies through time or space, plasticity in size at which the diet shift occurs would be expected. Spatial availability and composition of prey varied considerably, yet common goby diet shifts occurred consistently at 30 mm standard length, indicating that this external parameter had little influence on prey choice. This consistency also provided further support for the suggestion that metabolic rate, as a predictable intrinsic parameter, was canalising the change in prey choice (Jackson et al. in press; Chapter 3).

Optimal foraging studies may predict patterns of prey choice correctly, but often demonstrate some time lag (Mittelbach 1981; Osenberg & Mittelbach 1989; Persson &

Greenberg 1990b). Predictions for the common go by were accurate in terms of pattern and timing, but observed shifts in prey choice occurred less precipitously than predicted by the model and, for a short time after the diet shift, prey consumption was energetically sub­ optimal. The sub-optimal nature of the deviations from predicted prey choice was confirmed by quantification of reductions in go by fitness resulting from an inability to consume macrofauna (Jackson et al. 2002; Chapter 6). Deviations from predicted prey choice may be caused by trade-offs between factors driving the shift (Gee 1989), but given

106 Chapter 7 - Discussion the apparent absence oftrade-offs with the common goby diet shift (Chapter 5), this seems an unlikely cause ofthis sub-optimality. Such deviations may also arise through partial preferences in prey choice and the effects of learning on prey handling (Pyke 1984;

Persson & Greenberg 1990b). With prey choice dependent on metabolically driven parameters, inter-individual variability in metabolic rate or scope for activity (Reidy et al.

2000) may also provide a mechanism to explain the more variable prey choice following the diet shift.

A range of other factors, such as sexual development, parasites and genetic make-up, might also influence prey choice (Fig. 7.1 ). Despite sexual maturity being recorded below 30 mm (Fouda & Miller 1981; Arruda et al. 1993), most gobies achieve this length well before the onset of the breeding season in early summer and so diet shifts do not seem to be linked to sexual maturation. Parasite load can affect condition, survivorship and reproductive success as well as prey choice (Lozano 1991; Houde & Torio 1992; Lafferty

1992). Although not investigated specifically, in strong contrast to recruits from the previous year, large parasite loads were not noted in young of the year fish, many of which achieve sizes> 30 mm and have already shifted diet. It may be that the intermediate host species of P. microps parasites are only consumed following the diet shift, subsequently causing infection. Other factors influencing a predator's ability to catch prey include sensory limitation, such as visual acuity (Walton et al. 1992) and locomotory limitations such as fast-start ability (Webb 1984, 1986).

Although considerable time and effort has been devoted to investigating the causes and consequences of a diet shift at 30 mm, this is not the only change in prey choice and other stages of the life cycle demonstrate interesting features in their own right. Gobies moving from the water column down onto the substratum experience a major change in habitat and will be exposed to vastly different conditions, which is bound to influence behavioural

107 Chapter 7 - Discussion expression and is reflected by different diets (Fig. 7.1 ). Indeed, conditions prevalent at the time of a change in phenotype may not be the only factors responsible for observed consequences. Foraging history and experience early in life, can determine growth trajectories and directly influence susceptibility to predation, which in turn will have additional consequences for foraging behaviour, fitness and survivorship (Werner &

Gilliam 1984; Olson 1996). Different behavioural strategies can also have a genetic basis with phenotypic plasticity possessing a demonstrably heritable component (Steams 1989;

Zimmerer & Kallman 1989; Thompson 1991; Schlichting 2003). Conditions or incidents during sensitive developmental stages can also affect phenotypic plasticity and expression, particularly in terms of asymmetry, which has the potential to influence locomotory ability, parasitism, reproductive success (Thomas 1993; Sasal & Pampoulie 2000; Kristensen et al.

2003).

Prey consumption does not just vary with ontogeny, and predators at any given stage of their lives can exploit different prey resources that have associated costs and benefits. The costs of exploiting different resources can be manifested as trade-offs, for example between foraging efficiency or predation risk (Chapter 5). Similarly, predators can be categorised as specialists or generalists, where the former develop stereotyped and invariant behaviour and morphology for exploitation of a particular resource, whilst the latter are able to exploit a range of prey types. Specialists can achieve high foraging efficiency on their particular target prey, but suffer drastically reduced efficiency when required to forage on other prey types. Conversely, generalists can maintain intermediate levels of foraging efficiency over a wide range of prey types (Laverty & Plowright 1988).

Behaviour often varies in response to environmental cues. Where behaviour is flexible, or plastic, there may be two costs: that from behaviours being less effective (Laverty &

Plowright 1988; Hughes & O'Brien 2001) and that from the actual ability to be plastic

108 Chapter 7 - Discussion

(Newman 1992), although such plasticity may form an important mechanism to accommodate unpredictable conditions (Komers 1997). Learned behaviours can play an important role in foraging behaviour (Cunningham & Hughes 1984; Croy & Hughes

1991 b, c) and can serve to increase this plasticity and reduce the costs of lower efficiency

(Hughes & O'Brien 200 I). Although prey availability does not influence the location of ontogenetic diet shifts in the common goby, there was evidence for prey abundance and composition causing differences in prey choice in post diet-shift fish (Chapter 3).

Translocation foraging experiments with P. microps provided some evidence for the effect of prior experience and learning on foraging ability (Jackson & Rundle in review-b;

Chapter 4). Na"ive fish, with no prior experience of foraging on a prey assemblage, performed less well, in terms of energy consumption, than those with previous experience of capturing, subduing and swallowing prey from the same assemblage. Where the prey of generalist predators varies temporally, the ability to adapt search images may be important in identifying a particular prey type from a range of other stimuli and maintaining plasticity in foraging behaviour (Tinbergen 1960; Pietrewicz & Kamil 1979).

The estuarine and shallow, coastal water environments inhabited by P. microps are very dynamic and exhibit high levels of physicochemical and biotic variability (Moll er &

Rosenberg 1982; Chapter I) Theoretical predictions of optimal foraging and behavioural plasticity suggest that a generalist strategy is appropriate under these conditions (Pyke et al. 1977; Komers 1997). In line with such predictions, P. microps clearly has the morphology and general behavioural repertoire to deal with a range of prey sizes, shapes, and activities, although some degree oflocal specialisation is apparent, probably through learned modifications to behaviour and possibly the formation of search images (Chapter

4). These learned behaviours can not improve foraging ability over short time-scales (24

109 Chapter 7- Discussion hours), but may be more suited to changes in prey availability such as stochastic and environmental variation or seasonal recruitment.

CONSEQUENCES OF PREY CHOICE

Thus far, I have dealt with the adaptive nature of various factors that drive prey choice and diet shifts. The adaptive nature of prey choice means that prey-choice behaviours, under natural selection pressures, will tend to maximise fitness, often by maximising net energy gain rate or increasing survivorship (Mittelbach 1981; Werner & Gilliam 1984; Werner &

Hall 1988; Ebenman 1992). Although, in evolutionary terms, this will be the ultimate consequence of foraging behaviour, there will also be proximal patterns and processes arising from prey choice decisions (Fig. 7.3).

Prey choice not only affects foraging rate and energy gain but changes in diet can also influence predation risk, reproduction etc. (Werner & Hall 1988). Where one parameter influencing fitness is prejudiced in favour of another, there must be a trade-off.

Behavioural traits possessed by predators, such as search mode, capture· strategy and handling methods, are often influenced by morphological characteristics and thus morphology and foraging ability are closely related (Fig 7.3) (Wainwright 1988; Schluter

1993). Given this link, there may also be a trade-off if morphology is fixed, since morphology efficient for a feeding mode at one stage of development is unlikely to provide equal efficiency for modes that may be utilised at other stages (Schluter 1995). Where there is a trade-off between ontogenetic stages, the predator may be exposed to conflicting or antagonistic selection pressures (Webb 1984; Schluter 1995; Robinson et al. 1996) and the close link between foraging efficiency and morphology means these trade-offs are likely to have a structural basis.

11 0 Chapter 7 - Discussion Morphology and foraging efficiency Meiofauna --- Competition 0:~ ----- ~"' Growth and body condition Prey Variable consumption :t er:-;;~ ·~\D ... ~~~- reproductive fitness ~~ ~ ~ ~~~ l ~~~ Nest quality / ~ Predation risk Macro fauna • Figure 7.3. Conceptual figure illustrating the main consequences of prey choice for the common goby. Large black arrows indicate aspects considered in this thesis

111 Chapter 7 - Discussion

Natural selection will thus favour changes in morphology to reduce the cost of the trade-off

(Svanback & Eklov 2002, 2003). Consequences of ontogenetic shifts therefore include, not only changes in survivorship, diet, habitat, predation risk and trade-offs that may have been involved in driving changes in prey choice, but also morphological adaptation (Figure

7.2). ln Pomatoschistus microps, diet shifts, in the absence of habitat shifts, changes in predation risk, or different foraging modes, served to maximise energetic gain (Chapters 2

& 3). Optimal foraging was unaffected by these parameters, hence no trade-off was apparent with the change in diet. The lack of change in shape associated with change in diet, revealed by geometric morphometric techniques (Chapter 5), supported the notion that in the absence of a trade-off, there would be no selection for a change in morphology required to improve efficiency following the diet shift. Where a single morphology or body-form provides the best exploitation of resources at all stages, no divergence would be expected (Schluter 1995).

Although Chapter 3 demonstrated that prey availability had little influence on the location of common go by diet shifts, it is clear that at extremes, non-availability of prey could prevent a diet shift from occurring. Since ontogenetic diet shifts provide an evolutionary solution to increase survivorship and fitness through development (Werner 1988; Ebenman

1992), failing to carry out a diet shift must have some cost (Magnhagen 1986; Chapter 6).

An inability to feed on the energetically optimal prey resource is likely, not only to cause reductions in body condition, but also increase disease and starvation (Smith & Wooton

1995) and affect current and future reproductive success (Stephens & Krebs 1986).

When the energetically-optimal macrofaunal prey resource of adult gobies (Chapters 2 &

3) was removed through experimental mesocosm manipulations, clear fitness

112 Chapter 7 - Discussion consequences for male common gobies were apparent (Chapter 6). Depletion of

macrofaunal prey resources lowered hepatosomatic index and nest building ability, which were strongly linked, and led to reduced reproductive fitness (Jackson et al. 2002; Chapter

6). Male P microps, responsible for all parental care, construct nests in which the eggs are laid (Magnhagen 1992).

Nest quality was a good fitness surrogate, inferred from both natural and sexual selection

pressures. Nest crypsis reduces egg predation risk and nest quality is a character used by females for mate choice (Jones & Reynolds 1999b; Svensson & Kvarnemo 2003). The common goby spawns repeatedly over one season only, so condition influences on reproductive success, caused by prey depletion can have considerable implications not only for individual fitness, but also for population dynamics. Pihl & Rosenberg ( 1982) have

previously shown recruitment of common gobies to be highly variable and prey depletion may be the root cause of this variation. The cost ofthe sub-optimal consumption of meiofaunal prey by adult gobies, indicated by optimal foraging predictions (Chapter 3), is clearly illustrated under these experimental conditions.

CONCLUSIONS

From a range of factors including gape limitation and extrinsic factors such as prey availability, predation risk and habitat shift, Chapters 2 and 3 provide compelling evidence that common goby prey choice is, instead, driven by metabolically influenced parameters.

This intrinsic mechanism causes the location of the diet shift to be canalised over a wide range of prey availability. Adult gobies are generalist predators that can exhibit some degree of local specialisation through learned behaviours. This specialisation may serve to offset the reduced efficiency costs associated with the plastic behaviours of a generalist lifestyle (Chapter 4). The diet shift from meiofauna to macrofauna occurring at 30 mm standard length maximises net energy intake rate, elicits no trade-off's and hence no

113 Chapter 7 - Discussion consequential change in morphology (Chapter 5). Where ambient conditions do not permit a diet shift to occur, gobies will suffer loss of body condition and reduced reproductive fitness (Chapter 6).

Pomatoschistus microps occupies a niche where a single morph provides the best solution during all the benthic life stages, despite considerable ontogenetic differences between diets. Metabolic canalisation causes a predictable and consistent ontogenetic diet shift but following this shift, selection of prey identity can be variable and dependent on ambient availability. This generalist strategy, with the ability to specialise and adapt to local conditions, may be most appropriate for inhabiting dynamic and unpredictable environments such as estuaries and shallow coastal waters.

114 APPENDICES

APPENDIX 2.1

Length-weight relationship

Regression analysis on values of fresh weight in grams (W) with standard length in mm (L)

3 1 revealed a relationship where W = 0.000004L .4 .

Model parameters

Re.~piration rate

For passive respiration, R =kw", k = 0.927, Wis fresh weight (g) and b =0.789, for active respiration, log R= a+c?: a is 1.183, c is 0.023 and T is temperature (0 C) (Fonds &

Veldhuis 1973).

Capture rates

Regression constants from capture rate trials with standard errors, fit, and significance values. Prey type constant SE r2 n ANOVA 5 5 Corophium a -2.0 X 10" 4.8 X 10· 0.34 103 F2. 102 = 18.68, p <0.00 I 6 b1 6.0 X J0·6 J.Q X 10" 5 b2 -J. 9 X J0" 0.6 X ]Q·S 8 8 b3 3.0 X J0· J.Q X 10· 3 Meiofauna a 1.8 X 10" o.6 x 1o-J 0.23 105 F2.1o4= 16.62, p <0.001 bl -7.9 X I o-s J.8 X ]Q·S 8 8 b2 4.0 X 10· 1.8 X J0"

Prey abundance

Mean prey abundances± 95% confidence intervals and size frequency distributions for prey size classes used in predicting optimal diets at the three sites.

Mean abundance (m· ) Bokevik Salvik Kilviken Corophium 2272 ± 1067 231 ± 161 297 ± 290 Chironomidae 3±6 1061 ± 412 1529 ± 674 Copepoda 142167± 73475 84923 ± 25026 60633 ± 38358 Ostracoda 22973 ± 3404 22596 ± 3221 35965 ± 16614

115 Appendices

Size frequency distribution Size class {mm} Bokevik Salvik Kilviken meiofauna 0.9864 0.9881 0.9879 1 0.0002 0.0000 0.0000 2 0.0036 0.0007 0.0007 3 0.0049 0.0017 0.0012 4 0.0026 0.0019 0.0019 5 0.0014 0.0007 0.0025 6 0.0006 0.0011 0.0023 7 0.0003 0.0020 0.0017 8 0.0001 0.0008 0.0003 9 0 0000 0.0006 0.0002 10 0.0000 0.0023 0.0012

116 Appendices

APPENDIX 3.1.

Cumulative prey curves

Cumulative prey curves were used to determine the sample size required to provide an adequate description of goby diet (Ferry & Cailliet 1996). Diet breadth increased with goby size ranging between two and five prey types, but was highly consistent within size class. Small sample sizes (e.g. six) described the diet breadth of a given size class well.

Power analysis

A priori power analysis was conducted in order to determine the sample size required to establish whether differences in mean prey length were significant between size classes (Cohen 1988). Parameters required to determine an effect size for inter size-class comparisons of prey length were estimated from foraging model predictions and cumulative prey curves. Power analysis using the programme G*Power (Erdfelder et al. 1996) provided an effect size estimate of 1.2 (in biological terms, an extremely large response (Cohen 1988)), permitting a very powerful analysis (1-P >0.9), even with sample sizes as small as four. Consequently, a conservative sample size of I 0 individuals per goby size class was considered appropriate.

117 Appendices

Indices of importance for the main prey items of the common goby. % NC is numerical composition, %VC is volumetric composition, % FO is freguenc~ of occurrence and %!RI is index of relative im12ortance. Corophium Chironomidae Nereis Copepoda Ostracoda

~ 2 .) 4 5 2 3 4 5 2 3 4 5 I 2 3 4 5 2 3 4 5 Size 25- 30- 15- 20- 25- 30- 15- 20- 25- 30- 15- 20- 25- 30- class 15- 20- 25- 30- >35 15- 20- >35 >35 >35 >35 19 24 29 34 19 24 29 34 19 24 29 34 19 24 29 34 19 24 29 34 Salvik %NC 0 0 5 9 27 6 0 2 9 12 0 0 2 15 13 86 94 74 40 33 5 14 5 3 %VC 0 0 10 21 28 8 4 11 14 13 6 5 10 30 48 68 74 36 9 0 5 16 26 7 0 %FO 0 0 21 31 45 13 7 29 29 45 13 7 25 57 64 100 100 96 69 55 13 53 58 26 18 %/RI 0 0 2 11 25 I 0 3 8 I I 0 0 2 30 39 97 93 72 39 18 0 6 16 3 I Bokevik %NC 6 I 7 75 54 0 0 0 0 0 0 0 13 25 23 83 88 72 0 3 9 8 5 0 0 %VC 14 8 18 21 39 0 0 0 0 0 I 3 17 29 36 65 70 47 0 0 17 I I 10 0 0 %FO 43 31 36 100 85 2 3 0 0 0 5 9 32 100 62 100 100 82 0 8 45 43 32 0 0 %/RI 5 2 7 64 65 0 0 0 0 0 0 0 8 36 30 88 93 80 0 0 7 5 4 ·o 0 Kilviken %NC 0 5 4 6 41 3 10 7 19 29 0 0 7 20 23 97 80 65 32 0 0 3 14 10 0 %VC 1 15 4 18 29 13 20 15 16 13 0 4 19 29 52 84 52 34 16 0 2 5 24 12 0 %FO 10 29 24 IS 62 40 53 62 54 54 0 12 29 46 62 100 100 95 54 0 10 24 38 31 0 %!RI 0 4 2 4 38 3 10 I I 23 20 0 0 6 27 41 96 84 71 32 0 0 I I 1 8 0

118 Appendices

APPENDIX 4.1

25000

.....-... N I E 20000

(/) 0 c ...... 15000 Q}u c ro -o c 10000 ::::1 ..0 ro >. Q} I- 5000 a..

0 Corophium Gammarus Cyathura Nereis Prey species Appendix 4.1. Data from exploratory surveys illustrating inter-site prey variability of mean prey abundance(± s.e.) in Devon estuaries. Shaded bars represent the River Avon and clear bars the River Yealm.

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138 COPYRIGHT STATEMENT

This copy of the thesis has been supplied on condition that anyone who consults it is understood to recognise that its copyright rests with its author and that no quotation from the thesis and no information derived from it may be published without the author's prior consent.

Angus Charles Jackson

January 2004

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