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Habitat Suitability for Juvenile Flatfish of the Inner Danish WatersSection for Ecosystem Based Marine Management

Brown, Elliot John

Publication date:2019

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Citation (APA):Brown, E. J. (2019). Habitat Suitability for Juvenile Flatfish of the Inner Danish Waters: Section for EcosystemBased Marine Management. Technical University of Denmark.

Habitat Suitability for Juvenile Flatfish of the Inner Danish Waters

Section for Ecosystem Based Marine Management

Elliot John Brown

PhD Thesis

Supervisor: Josianne G. Støttrup

Advisor: Ulf Bergström

Preface

This thesis was submitted in partial fulfilment of the requirements for the degree Doctor of

Philosophy (PhD) at the Technical University of Denmark. The research presented in this thesis

was carried out under the supervision of Senior Researcher Josianne Støttrup within the Section

for Ecosystem Based Management of the National Institute of Aquatic Resources (DTU Aqua).

Researcher Ulf Bergström of the Department of Aquatic Resources at the Swedish University of

Agricultural Sciences acted as an informal advisor. An external research stay was undertaken at

the University of Adelaide’s Southern Seas Ecology Laboratories in collaboration with Professor

Bronwyn Gillanders and Dr. Patrick Reis-Santos.

This PhD project was supported by the Ministry of Environment and Food of Denmark’s Danish

Marine Coastal Fisheries Management Program (Marin Fiskepleje). Projects within this thesis

received funding from the European Marine Fisheries Fund, via the Danish Fisheries Agency,

through the projects “FishHab-II” and “Improvement of the biological advice for Common Sole in

Danish Waters”. Travel and participation in international conferences was partly supported by

funding from the Otto Mønsted Fund.

Personal Acknowledgements This thesis is was only possible with the practical and moral support of a vast number of colleagues, friends and family. I wish to thank my supervisor Josianne, for her support and guidance in all things academic, for including me in a range of projects and working groups, and for giving me the independence to try things out while ensuring I remained on track. I’d like to thank everyone in the Marine Habitats group who have listened and helped to hone ideas throughout my PhD. Specifically I would like to thank Ole Henriksen, Aurélia Gabellini, Thomas Møller, Dennis Andersen, Asbjørn Andreasen, and Stine Andersen for the many hours of practical help and field work. I would like to thank Alexandros Kokkalis for his thorough and continued support in all things modelling (and for donning the waders), and Mollie Brooks for her patience and insight in the nitty-gritty of my statistics. Thanks to Lis Elmsted, for all the admin situations I couldn’t handle. Bronwyn Gillanders was very kind to open her lab to me and provide guidance while I visited. A big thank you to Patrick Reis-Santos, for all of his time getting me up to speed with otolith chemistry techniques and Adelaide in general, as well as his continued advice, even post-publication of our manuscript. I would like to thank the participants of the ICES WGVHES and HELCOM FISH-PRO, who all welcomed and included me from the beginning of my PhD. Specifically I would like to thank Olivier Le Pape, Rita Vasconcelos, Karen van de Wolfshaar, Ulf Bergström Jens Olsson, and Alan Baudron for both supporting my projects and including me as a peer in their great work. I must thank Filipe Martinho and Ana Vaz for taking time out to come to Copenhagen and share their otolith microstructure methodology with me.

I would not have chosen this career path, had I not been afforded the advice and counsel of old friends who know me so well, looking at you John and Kavi. I have been very fortunate to have gained a group of very supportive friends from all over the world who’ve all aggregated in Odense at some point. A big thank you to all of you for the adventures and new experiences we’ve shared.

To my extended family of Aunts and Uncles, I thank you for all that you invested in me when I was younger, and in the same breath, I thank my cousins for their patience.

To my parents, your continual and unending encouragement gave me the opportunities and confidence to make all of the decisions that have ultimately led me to where I am today. Thank you for your patience through some of those poor decisions and your unwavering support, even for those decisions that see us living far apart.

Liza, you have been a constant source of love and support. You have both grounded me and provided me new perspectives; you’ve encouraged and made possible a life of both new experiences and real meaning. Your ethic and determination has inspired me throughout our shared PhD experience; not least, during the business end of this thesis. I thoroughly look forward to whatever it is that next comes our way.

Finally, I dedicate this collection of work to my daughter, Nora. I can only hope to provide you with the opportunities and support that I have been lucky enough to receive.

Table of Contents

English Summary 1

Dansk Resumé 2

General Introduction 3

Coastal fish 3

Quantifying habitat suitability for fish 6

Coastal habitat as juvenile fish habitat 14

Thesis aims 20

Synopses of Appended Articles 21

Synopsis 1 – Conflicts in the coastal zone: human impacts on commercially important fish species utilizing coastal habitat 21

Synopsis 2 – Juvenile fish habitat across the IDW: Habitat association models and habitat growth models for European plaice, flounder and common sole informed by a targeted survey 24

Synopsis 3 – Juvenile fish habitat across the inner-Danish waters: Suitability modelling of coastal marine habitats for commercially important species from historic surveys 29

Synopsis 4 – Juvenile fish habitat across the IDW: Using otolith chemistry to discriminate between hybridising con-familials and contiguous, coastal habitat 31

Synopsis 5 – Ancillary projects 36

Synthesis and Conclusions 37

Synthesis of presented research 37

Future perspectives 39

Conclusion 40

41 Supplementary Contributions

References

Appendices

42

55

1

English Summary

Coastal fish play important roles in ecosystem functioning in addition to their disproportionately

large contribution to fisheries. By inhabiting coastal areas, fish are exposed to a wide range of

human activities over and above their direct exploitation. This thesis illustrates the extent of these

indirect anthropogenic impacts by reviewing evidence of human activities effects on exploited,

coastal fish species from the northeast Atlantic, where ~92% of those species were impacted in at

least one life-history stage. Furthermore, there is evidence of anthropogenic impacts acting on

78% of the juvenile life-history stages as they utilise coastal habitats.

With a clear need to understand the role that coastal habitats play in provisioning juveniles for

replenishing exploited fish populations, this thesis continues by quantifying habitat suitability for

juvenile flatfish of the inner Danish waters and establishing a method to trace their contributions

to fished adult populations.

Two approaches are used to quantify habitat suitability, one obtains fish data and environmental

data from a targeted survey of near-shore habitats, the other utilises existing surveys of juvenile

fish and pairs it with modelled environmental data. Juvenile habitat suitability models are

presented describing juvenile density and growth responses to changes in the physical

environment. The results of both approaches are critically assessed and used to make

interpolative maps of predicted habitat suitability across the inner Danish waters. The species-

specific trends described in these models and predictions are discussed with reference to previous

empirical findings from across their ranges. These two studies propose potential mechanisms

creating the observed patterns of density and growth and discuss them in the context of current

theories of density dependence and population connectivity.

The fourth work included in this thesis, documents the efficacy of otolith chemistry to

differentiate between contiguous coastal juvenile habitats of the inner Danish waters, to enable

future work on the connectivity between juvenile and adult habitats in this area as well as the

neighbouring North and Baltic Seas.

Together, the four key studies that comprise the majority of this thesis provide both information

for preliminary advice on the importance of juvenile habitats of the inner Danish waters, and a

foundation for future work to further develop juvenile habitat models and describe the life-history

connectivity of important fisheries species.

2

Dansk Resumé

Fisk i det kystnære marine miljø spiller en vigtig rolle i økosystemets funktionalitet i tillæg til deres

ude af proportioner store bidrag til fiskeriet. Ved at leve kystnært, er fiskene eksponeret for en

bred vifte af menneskelig aktivitet udover den direkte udnyttelse i fiskeriet. Denne afhandling

beskriver først, med et review af litteraturen fra det nordøstlige Atlanterhav med fokus på de arter

der rådgives om af ICES (International Council for the Exploration of the Sea), hvordan der er

evidens for at 92% af kystnære fiskearter påvirkes af menneskelig aktivitet i mindst et af deres

livsstadier. Yderligere er der evidens for at menneskeskabte påvirkninger har en effekt på 78% af

de juvenile livsstadier hos fisk tilstede i kystnære habitater.

Med et klart behov for at forstå den rolle kystnære habitater spiller i tilførslen af juvenile fisk til

opretholdelse af udnyttede fiskepopulationer, fortsætter denne afhandling med at kvantificere

udbredelsen af habitater egnet til juvenile fladfisk i de indre danske farvande, og etablerer en

metode til at spore deres bidrag til adulte fiskepopulationer der udnyttes i fiskeriet.

I to studier kvantificeres udbredelsen af egnede habitater. Første studie opnår fiske og

miljømæssige data fra en målrettet undersøgelse af kystnære habitater. Andet studie bruger

eksisterende undersøgelser af juvenile fisk og sammenligner det med modelleret miljømæssige

data. Modeller over habitaters egnethed til juvenile fisk præsenteres og beskriver hvorledes

densiteten og vækst af juvenile fisk påvirkes af ændringer i det fysiske miljø. Resultaterne af begge

studier vurderes kritisk og bruges til at lave interpolerede kort over forventet egnethed af

habitater i de indre danske farvande. De artsspecifikke tendenser som beskrives i disse modeller,

og deraf udledte forventninger, diskuteres med reference til tidligere empiriske opdagelser fra

udbredelsesområderne for de pågældende fiskearter. Disse to undersøgelser foreslår potentielle

mekanismer der skaber de observerede mønstre i densitet og vækst af juvenile fisk og diskuterer

dem i kontekst af gældende teorier om densitet afhængighed og populations konnektivitet.

I et fjerde studie, dokumenteres anvendeligheden af otolit kemi til differentiering af

sammenhængende kystnære habitater, egnet tiljuvenile fisk, i de indre danske farvand. Med

denne metode muliggøres fremtidige undersøgelser af konnektiviteten mellem habitater egnet

tiljuvenile og adulte fisk i det nordøstlige Atlanterhav samt Nordsøen og Østersøen.

Samlet set tilfører de fire centrale undersøgelser, inkluderet i denne afhandling, information til

indledende rådgivning om betydningen af habitater egnet til juvenile fisk i de indre danske

farvande. Yderligere skabes der et fundament for fremtidig udvikling af modeller over sådanne

habitater samt beskrivelsen af konnektiviteten i livsstadierne af vigtige fiskearter.

3

General Introduction

“Coastal fishes are better than pelagic ones for their feeding is more abundant and better… there exists a good blend of the hot and the cold in the coastal regions of the sea…”

- Aristotle, History of Animals, 598a2 (cited in Ganias et al., 2017)

Coastal fish

Coastal fishes are those which utilise coastal habitats during one or more developmental stage

throughout their life-history (Kroodsma et al., 2018; Seitz et al., 2014). Fish habitats are deemed

coastal where they occur below the high-water mark in semi-enclosed bays, estuaries, and fjords,

but also along open exposed areas of the coast. In these open coast settings, where natural

geographic enclosures aren’t so apparent, limits are often imposed based on bathymetry (Federal

Geographic Data Committee, 2013), the distance from shore, the influence of terrestrial waters

(Council Directive 2000/60/EC), or combinations of shared environmental attributes (Aquatic

Ecosystems Task Group, 2012). Regardless of how their habitats are defined, coastal fish play

important roles in ecosystem functioning and are valuable resources for humans. To help

document and categorise the diversity and importance of these roles, they can be considered in

terms of ecosystem services (Holmlund and Hammer, 1999).

Ecosystem Services of Coastal Fish

The classifications of ecosystem services are diverse and somewhat subjective (Hattam et al.,

2015). Here I briefly describe some of the key services that coastal fish provide, in general terms,

across two broad subcategories; namely ecosystem functions and ecosystem services (Costanza et

al., 1997). I consider ecosystem functions as services provided within the community which

contribute to the maintenance and continued productivity of the system. Alternatively, I consider

ecosystem services as those which humans derive from coastal fish.

Ecosystem function

Coastal fish can play a direct role in ecosystem functioning as meso-predators of herbivorous,

grazing organisms and as piscivores predating on those meso-predators. In these roles, the

removal of fish can release pressure at either of these trophic levels thus initiating cascading

4

effects that drastically impact the ecosystem forming algal community (Leleu et al., 2012; Östman

et al., 2016). Being relatively large and mobile, demersal fish can play a role in nutrient flux at the

surface of the seafloor through sediment disturbance, or bioturbation (Yahel et al., 2008). These

energy and nutrient fluxes can be extended to larger scales as mobile coastal fish make daily

foraging migrations between productive shallow areas and more stable, deeper, coastal waters

(Lefeuvre et al., 1999). These scales increase even further when considering energy and nutrient

transport occurring as a result of migrations between different life-history stages; be they seaward

(Deegan, 1993) or shoreward (Varpe et al., 2005). Simply by foraging at the coast, fish play a role

in linking marine and terrestrial systems by accumulating energy and nutrients before being

predated by terrestrial animals (Hentati-Sundberg et al., 2018). Diversity in coastal fish

assemblages is accompanied by diversity in the ecosystem functions they perform but also the

higher-level function of ecosystem resilience (Elmqvist et al., 2003; Worm et al., 2006). The loss of

fishes and the functional services they provide, can lead to regime shifts which perpetuate lower

abundances by making the habitat less favourable for those fish initially excluded (Rocha et al.,

2014; Troell et al., 2005).

Ecosystem services

The collection of ecosystem functions that coastal fish provide are in and of themselves an

ecosystem service, in that they maintain a system from which humans derive other services

(Barbier et al., 2011). Coastal fish also provide more direct forms of ecosystem services to

humans, some examples being the recreational value of observing them whilst diving or

snorkelling (Gill et al., 2015), by providing information on ecosystem status and changes (HELCOM

et al., 2018), and their position as culturally iconic species (Poe et al., 2014; Rönnbäck et al.,

2007). The most commonly cited services provided by coastal fish are those linked to their direct

exploitation; namely recreational fishing (Toivonen et al., 2004) and food provisioning through

commercial and subsistence fisheries (Garcia and Rosenberg, 2010).

While the terminology used to identify and categorise them may change, the valuable roles that

coastal fish play, both in their environments and in supporting human populations, are well

documented.

5

Anthropogenic impacts on coastal fish

While many fish stocks are heavily exploited for the provisioning of food, coastal fish are, by

nature of the areas they inhabit, closer to dense human populations which results in their

disproportionate exploitation (Champbers, 1991 cited in Fodrie and Mendoza, 2006; Seitz et al.,

2014). This proximity to human development also means that they are exposed to a wide variety

of human activities (Airoldi and Beck, 2007). The effect of exposure to these activities are termed

anthropogenic impacts and they often operate indirectly, via fish habitat rather than directly on

fish, such as fishing gear reducing habitat complexity (Kamenos et al., 2004), excess nutrient run-

off causing eutrophication and excess algal growth (Isaksson et al., 1994), or habitat loss to coastal

development (Sundblad and Bergström, 2014). Such environmentally diffuse impacts are not

mutually exclusive and interact with one another to increase the total impact (i.e. additive effects),

to amplify each individual impact’s effect (i.e. synergistic effects) or to decrease the total impact

(i.e. antagonistic effects) (Crain et al., 2008).

Management of coastal fish and their habitats

In recent history the mitigation of these direct and indirect anthropogenic impacts have been

considered separately, with the direct exploitation by fisheries being managed independently of

other environmental considerations (Guerry, 2005). Over the past two decades, calls for an

“Ecosystem Approach to Management” (EAM) have emerged (Larkin, 1996), where the general

underlying principle is of a more holistic context to the management of human activities within

naturally variable systems. Proponents of EAM have come from both conservation and resource

management backgrounds, which exemplifies some of the pluralist views that the approach seeks

to integrate and ameliorate (Browman et al., 2004 and contributions therein).

At a policy level, the management of coastal marine resources often remains siloed but with some

shared visions; exemplified by the European Union’s combination of the Marine Strategy

Framework Directive, Water Framework Directive, and Common Fisheries Policy (Llope, 2016), as

well as the United States’ combination of Magnuson-Stevens Act, and the Outer Continental Shelf

Land Act (Harvey et al., 2017).

At an advisory level, a variety of methods to integrate the function of marine ecosystems and the

fisheries they support have been proposed, and in some cases implemented, but with a large

degree of variability in their complexity and co-ordination. Some examples of these approaches

6

are the inclusion of expert opinion and qualitative indicators of ecosystem function paired with

quantitative fisheries advice for fisheries managers (Zador et al., 2017). With more data available

some cases have been able to quantify and integrate environmental and anthropogenic drivers to

predict potential future outcomes and present alternate future scenarios for consideration by

managers of single species (Möllmann et al., 2014). In other circumstances, the overall theme of

holistic assessment that is embodied in EAM has been readily adopted by researchers but took

time to amass the relevant data and knowledge needed to inform EAM policies, especially with a

lack of political direction (Llope, 2016; Österblom et al., 2016).

Whatever the political context, providing advice for EAM policy makers is a scientifically

demanding task, requiring both a broad and a deep understanding of the natural and human

elements of the system in question (G. S. Cook et al., 2014; Oates and Dodds, 2017; Samhouri et

al., 2014). In order to establish the impact of human activities we must first understand the

natural drivers of species distributions (Crowder and Norse, 2008). The complexity of these

dynamic systems dictates that scientific understanding, and the advice it provides, can only be

attained iteratively (Langton and Steneck, 1996; Steneck et al., 1997) and must openly recognise

what it remains ignorant of, while continuing to support policy makers and managers (Auster et

al., 1997; Litvin et al., 2018).

Quantifying habitat suitability for fish

To contribute to a broad and deep understanding of coastal ecosystems and the roles that fish

play within them, we must be able to describe their habitat use and the environmental drivers of

their distributions throughout their life-history. In this section I provide an overview of methods

used to describe the relationships between fish and their environment, in terms of habitat

suitability.

Habitat suitability models

The distribution of different species in space has long been of interest to humans, indeed even in

prehistory Aristotle sought to explain why different fish species would enter estuaries while others

would not (Ganias et al., 2017). Over time, defining the geographic limits to ranges have informed

some of the most fundamental concepts in biology, such as the Wallace line dividing the

7

Indonesian archipelago and inspiring theories of natural selection (Wallace, 1863). Through the

19th and 20th centuries descriptions of different plants’ ranges were linked to environmental

factors such as topography and soil type, and extended to map areas of “terminal community”, or

potential habitat (European Environment Agency, 2014). This linking of individual environmental

components to organism ranges is the beginning of what we today recognise as habitat modelling

or Species Distribution Modelling (SDM). With the increase in computational power through the

20th and into the 21st century these methods were developed and applied to different domains,

including the three dimensional habitats of pelagic ecosystems (Hobday et al., 2016; Hüssy et al.,

2012; Planque et al., 2007). The application of SDMs in coastal settings is more traditional, in that

it is often considered in two dimensions and linked to geographic features, rather than the

dynamic movements of pelagic systems (Pittman et al., 2011). This location specificity is often

discussed as a key limitation of the SDM approach, that it is a static description of habit use based

on previous observations (Guisan and Zimmermann, 2000). Nevertheless, if the importance of a

geographic location to a certain species is what is of interest, then the results of this approach

quantify species specific habit suitability (Boyce et al., 2002), albeit with the caveat that this will

vary in time with other elements of the environment (Litvin et al., 2018; Vasconcelos et al., 2014).

The rest of this thesis refers to the use of SDMs for quantifying habitat suitability as Habitat

Suitability Models (HSMs). Before undertaking a project to create HSMs certain decisions need to

be made, such as the modelling approach to be applied, which measure will represent habitat

quality, what set of environmental features are relevant, which data sources are going to inform

the model, and what statistical tools will be used to describe the relationships.

Modelling approaches

Before we consider the statistical tools to use in an HSM project, we must consider a more

fundamental question of what we are trying to represent in a model. The trade-offs between

describing reality, creating generally applicable models, and maintaining accurate descriptions of

that reality have been well reviewed in Guisan and Zimmerman (2000).

The use of analytical models forgoes considerations of the variability observed in nature to provide

precise descriptions of generally applicable phenomena, some examples being models of density-

dependent populations sizes (MacCall, 1990) and variation of this phenomenon at different life-

history stages (Andersen et al., 2017). Analytical models are useful for developing understanding

8

of the range of possible drivers that may be acting in a system; however their simplicity limits their

ability to provide relevant descriptions of real world cases. It is this limitation that can lead to

case- specific challenges to the theories derived from them (e.g. Jutfelt et al., 2018; Pörtner et al.,

2017).

In order to move closer to reality, we could consider the use of mechanistic models; those that

utilise cause and effect relationships between individual aspects of the environment and a species’

ability to grow and survive (D. G. Cook et al., 2014; Schram et al., 2013). These relationships are

usually modelled from highly controlled experimental set-ups in order to establish the cause and

effect relationship, independent of other confounding environmental conditions (Teal et al.,

2018). These same conditions make possible the observation of responses to environmental

conditions outside of ranges experienced in nature, and thus a fuller range of possible responses

can be observed (Chabot and Claireaux, 2008). Different environmental conditions (Christensen et

al., 2018; Lavergne et al., 2015) and different fish states (Brown et al., 2011; Bucking et al., 2012;

Killen, 2014) can be varied together to provide descriptions of their interactions, but such

interactive effects are hard to scale experimentally. For species with extensively studied

physiological responses to a range of environmental variables, the combination of all of these

responses can be combined to describe the overall effect on a fish’s metabolic capacity for growth

and reproduction (Marras et al., 2015). For cases where these eco-physiological relationships are

poorly known, or the species aren’t suited to laboratory experimentation (Araújo and Peterson,

2012), general features of a species from observation can be substituted in to generic frameworks

that have been established across a range of species (such as the DEB model; van der Meer, 2006).

The result of either of these approaches can be coupled with environmental data to predict

habitat suitability in the form of maximised biomass, or individual growth and survival from

individual based models (Martin et al., 2012; Teal et al., 2012; Van De Wolfshaar et al., 2015).

To build models that most closely approximate reality, but may not be generally applicable, we

employ empirical models; sometimes called statistical models. These models are informed by

observations of species, and the environmental conditions, in their natural habitats (Le Pape et al.,

2014). In these circumstances observations of the environment vary of their own accord and so

empirical models use probabilistic methods to identifying the strongest co-variation between

environmental variables and the selected response (Lecours, 2017). This is in contrast to the

9

attempts of analytical or mechanistic models to establish general rules or causal relationships

(Guisan and Zimmermann, 2000). Because of empirical models’ reliance on natural environmental

variation, sampling design is important to ensure the complete range of environmental conditions

likely to be experienced by the species in question are covered (Austin, 2002). Because empirical

models are by design, specific and not general, their use in prediction should be limited to the

extent of the observations used to inform them, such that predictions of species distributions

should only ever be interpolative (Guisan and Thuiller, 2005). While the resulting models do not

provide evidence of causative effects, the relationships they describe can be compared to

mechanistic effects determined by other studies to aid in the biological interpretation of the

outcomes.

The three model types described above, namely analytical, mechanistic and empirical, provide

useful terminology for the comparison of different approaches; however, these are discrete

classifications of what is, in reality, a spectrum of approaches. Categorising and describing general

methodological angles in this way helps us to consider our own approaches with reference to

what we are trying to achieve or represent with our own models. The rest of this thesis deals

primarily with empirical type models.

Proxies for suitability

The most fundamental decision in creating HSMs is, perhaps, the selection of which measure will

represent a species’ response to changes in the environment, and hence represent habitat

suitability. The simplest measure is that of presence; a reflection of the environmental conditions

that are found across the entire species’ range (Elith et al., 2011). Depending on the methods of

observation that are employed, presence is usually paired with observations of absences which

provides information on exclusionary conditions of the environment (Guisan and Zimmermann,

2000; Li et al., 2017). If observation effort is standardised, then simple binary responses can be

extended to the more information rich abundance, or count data (Blanchard et al., 2007;

Sundermeyer et al., 2005). However, using the presence and abundances of individuals assumes

that the population being surveyed is large enough to utilise all areas of high-quality habitat, and

will only move to low quality habitats in low numbers to avoid some form of density dependence

(MacCall, 1990). This assumption is based on the MacCall basin hypothesis and it is unlikely to

hold for heavily exploited species with depleted populations (Morfin et al., 2012). Furthermore,

10

there are many other reasons why organisms may or may not inhabit some component of

potential habitat, such as barriers to dispersal (Stoner, 2003; Stoner et al., 2001). So while fish are

likely to move and disperse into habitats with favourable conditions, the use of presence/absence

and abundance is an imperfect representation of habitat quality.

Alternative measures have been adopted that are truer representations of habitat quality because

they are linked to the survival and fitness of the individuals inhabiting them (Vasconcelos et al.,

2014). The ability of individuals to survive and reproduce is fundamental to their fitness and so is

an ideal representation of habitat suitability, however, In field observations, survival rates can be

difficult to determine as migration confounds abundances observed during repeated sampling for

cohort size (Jager et al., 1995) or in tagging studies (Barbour et al., 2012; Sparrevohn et al., 2002).

Intensive sampling of isolated populations may overcome such limitations (Fodrie et al., 2009),

especially when paired with density by age data from otolith microstructure analyses (Geffen et

al., 2011). Tethering experiments have inherently unknown impacts on predator avoidance

(Manderson et al., 2004) and so mortality rates are linked to predation and can be unreliable.

Growth is another determinant of fitness, especially in juvenile fish, as larger sizes reduce

predation and thus increase survival (van der Veer and Bergman, 1987; van der Veer, 1986).

Furthermore, fish that grow fast reach maturity sooner (Kjesbu and Witthames, 2007), and

allocate more energy into reproduction sooner (Barneche et al., 2018). The use of cohort length

frequencies can provide information on growth rates, but similar to mortality, migration can have

confounding effects. Alternative measures of growth are possible from the field, such as RNA:DNA

ratios as proxies for cellular capacity for work and hence growth (Ciotti et al., 2010; Gilliers et al.,

2004; Vinagre et al., 2008), and the incremental widths of otolith growth (Al-Hossaini and Pitcher,

1988; Stevenson and Campana, 1992).

In fish, reproductive success of individuals is difficult to determine given the often broadcast

nature of spawning, however the survival rate of fertilised eggs can be used to reflect the

suitability of spawning habitats, whether they be pelagic (Hüssy et al., 2012; Petereit et al., 2014;

Planque et al., 2007) or demersal (von Nordheim et al., 2018).

While abundances can provide information on the degree of habitat utilisation, without evidence

that the local population is saturating its available habitats (e.g. in Fodrie and Levin, 2008;

Sundblad et al., 2014), as a single measure it can inaccurately represent habitat suitability. Where

11

logistically possible, other measures that are linked to demographic rates such as survival, growth

and reproduction, should also be used as response variables to attain a fuller representation of

habitat suitability (Vasconcelos et al., 2014).

Explanatory variable selection

In addition to the selection of an appropriate response, the environmental variables that are

selected for inclusion in the initial full models are important, not least because the inclusion of

arbitrary predictors can introduce spurious correlations (Le Pape et al., 2014). When this occurs,

the effect of the spurious correlation persists, undetected, through model selection and can have

substantial effects on predictions of habitat suitability (Lecours et al., 2016).

Quantified descriptions of the physical, or biological, environment can be classified as having

direct effects on fish physiology (e.g. temperature) or acting indirectly (e.g. nutrient load driving

productivity and prey availability) (Austin, 2002). Where possible, predictors with a known

mechanistic effect on fish growth and survival should be included in the full model, so that more

inference can be drawn from the final model (Austin, 2007). Conversely, indirect predictors can

often greatly improve model fits and hence improve the precision of their predictions. Here, even

within the realm of the empirical approach (discussed above), including predictors with proven

mechanistic effects can increase the generality of the models while the trade-off of including

indirect drivers is an increase in the model’s precision but limiting its predictions to within the

extent of the input data (Guisan and Zimmermann, 2000).

The more mechanistic an empirical habitat suitability model becomes, the more its predictions

represent the potential habitat (or fundamental niche) of that species. Alternatively with little

understanding of the mechanisms by which predictors act, predictions of habitat suitability models

will describe only the realised habitat (or ecological niche) (Guisan and Thuiller, 2005).

Interpreting the extent to which predictions represent potential or realised habitats depends on

the set of explanatory variables that are retained in the final model and the degree to which the

mechanism of each variable’s effect on the response is, or is not, known.

Data sources

Often the explanatory variables that are included in model fitting are determined by their

availability, or by the resources required to collect them in the field. While being grounded in

realistic constraints placed on researchers, there are different limitations of different data sets,

12

that when used, should be acknowledged. Where environmental data was not collected

concurrently with the species of interest, the use of modelled hydrographic data, similar to the

bioclimatic maps of the terrestrial realm, is common practice. The modelled nature of the data

extracted from these data sets means that predictors have inherent spatial uncertainties such as

interpolation errors or poor/uneven sampling resolution (Guisan and Zimmermann, 2000) in

addition to thematic uncertainty of their own (Lecours et al., 2016; Moudrý and Šímová, 2012).

Methods to combine these different levels of uncertainty and to properly represent their effects

as they are propagated through modelling and prediction are poorly developed (Lecours et al.,

2015). However, an interim solution that has been proposed is to use publicly available, or

published and well described data, so as to be as transparent as possible about the potential

sources of error (Lecours, 2017).

Relevant scales

The effect of scale has long been studied in both ecology in spatial sciences (Guisan and Thuiller,

2005; Levin, 1992). When trying to model potential habitat for a species using an empirical

approach, spatial scales should include the full range of potential levels for each explanatory

variable (Le Pape et al., 2014). These full ranges may only exist across different seasons and

possibly only on the scale of decadal meteorological phenomena (Lecours et al., 2015).

In reality, the appropriate scales are defined by the species and the system being modelled (Graf

et al., 2005). Researchers should therefore consider that the effects of environmental drivers vary

across multiple scales (Buhl-Mortensen et al., 2015) and while selecting an appropriate scale for

the research question at hand is important (Johnson et al., 2013), investigating these phenomena

at multiple scales provides a deeper understanding of habitat use (Litvin et al., 2018) and can

improve models’ predictive power (Pearson et al., 2004; Thuiller et al., 2004).

Statistical approaches

The range of statistical tools available for modelling habitat suitability was recently well reviewed

by Lecours (2017), where he also demonstrated that the choice of tool can have significant

impacts on the outcome of predicted habitat suitability. However, there are no universal decision

rules for selecting which tools to employ (Dixon Hamil et al., 2016), probably due to ambiguity

from studies that report no discernible way to pre-select the most accurate modelling approach

(e.g. Bučas et al., 2013; Elith and Graham, 2009). The current situation requires that researchers

13

review the available tools and determine which tool best matches their understanding of the

system being modelled and the desired outcomes (Austin, 2002).

Sometimes this decision is restricted by the data, an example being where presence only data is

used as a response (Elith et al., 2011). Additionally, in modelling count data, a statistical

framework that can accommodate non-gaussian response distributions is essential, because count

data regularly follow a Poisson-like distribution. Here, I use “poisson-like”, because some species

are rare, some are more likely to cluster, and sampling techniques are often imperfect in their

detection of all individuals, all of which are factors leading to systematic deviations of count data

away from a Poisson estimating distribution (Guisan et al., 2002). To accommodate this, statistical

methods for modelling habitat suitability from count data need to be flexible and able to

accommodate parameters explaining data traits such as over-dispersion and zero-inflation (Brooks

et al., 2017). Where studies are sampling over seasons and years, it is important to include

methods that can represent the cyclical nature of phenological patterns of distributions (Teal et

al., 2018) and if sites are repeatedly sampled, then statistical tools that can represent these

repeated measures need to be selected (Bolker et al., 2009). An alternative to selecting a single

approach is to undertake multiple analyses use an ensemble approach to incorporate predictions,

but this approach fits far to the empirical end of a mechanistic-empirical continuum (Bučas et al.,

2013; Loots et al., 2010; Robert et al., 2016).

Whichever statistical framework is applied, there is broad consensus that model validation be

used to describe a model’s predictive ability (Le Pape et al., 2014). Approaches can range from

including the collection of test data in the sampling design, fitting and selecting models to a subset

of a dataset and testing against the remaining data, or fitting and selecting models based on an

entire dataset and subsequently refitting the selected models to subsets of training data before

predicting test data (Radosavljevic and Anderson, 2014). Because ecological data are often

resource-intensive to collect (Jaeger, 2006), the latter of these examples is most commonly

employed in the validation of habitat suitability models. Because these datasets are often large, it

can be computationally expensive to undertake exhaustive cross validation, whereby the entire

dataset is used as test data, that the model predicts naïvely, either individually or as part of a

group (Valavi et al., 2019). Alternative methods use re-sampling from the data to extract

representative samples for testing, without having to test all data points, reducing computational

14

time. Divisions of training and test data are derived, multiple metrics of the resulting predictive

precision and accuracy should be reported (e.g. bias, measures of error, and measures of

correlation between predictions and observations), as using only a single metric only provides a

narrow insight into how the model performs (Pearce and Ferrier, 2000).

While there are many approaches and methods to be considered in planning to establish and use

habitat suitability models, there is a large focus on developing guidelines and accessible tools for

ecologists, from the spatial sciences. Updates to these methods and their proper use should be

followed closely, and warnings heeded, in the preparation of new modelling and mapping

projects.

Coastal habitat as juvenile fish habitat

Paradigms in juvenile fish habitat

It has long been known that juvenile fish can be found aggregating in shallow coastal areas, but

real research interest in the biology of these early life-history stages only developed in the 20th

century, as the role of juveniles in supplying fisheries became of concern (Browman, 2014). The

focus of much of this work has been on heavily exploited species with life-history strategies that

see juveniles concentrate in specific habitat types separate from adults (Beverton, 1995; Iles and

Beverton, 2000). This can be typified by the European plaice (Pleuronectes platessa) (Gibson,

1999), whose life-history strategy is similar to many other flatfish and coastal fish, albeit with

different timing and habitat requirements (Rijnsdorp et al., 2009). Adult plaice are found in

deeper coastal shelf waters where, in winter, they spawn pelagic eggs. These eggs move passively

with ocean currents and vertically with density gradients. This passive behaviour continues post-

hatch with early larvae, but shifts into the active use of vertical migrations to utilise different tidal

flows to move toward shallow, near-shore habitats with soft sediments. At this stage a period of

metamorphosis coincides with the juvenile fish settling out, that is it becomes more closely

associated with the seafloor, which occurs in spring or summer. During the remainder of the

summer period, juvenile fish feed and grow in these shallow habitats before moving offshore the

following winter. This pattern of spending spring and summer in shallow, near-shore habitats and

15

winters in deeper waters continues for another one or two years before the juvenile fish recruit

into the adult population, remaining mostly in deeper waters (Gibson, 2005).

Early work focussed on explaining the reasons for variability in the number of new recruits joining

the adult stock and quickly differentiated between the processes acting on pelagic eggs and larvae

and those acting on settled juveniles in benthic near-shore habitats (Leggett and Deblois, 1994;

van der Veer, 1986; van der Veer et al., 2015). It has been established that, for most species with

the above life-history, the growth and survival of pelagic stages varies greatly from year to year

due to large scale fluctuations in hydrography and meteorological forcing (Duffy-Anderson et al.,

2014; Horwood et al., 2000). The comparatively stable supply of recruits, in contrast to the large

inter-annual variation in the number of settlers arriving into juvenile habitats, is attributed to

regulating processes occurring in juvenile habitats (Iles and Beverton, 2000; van der Veer et al.,

2000).

Because of the regulating role that juvenile habitats play in governing the number of fish recruiting

into a fishery, their importance was recognised by researchers and policy makers alike.

Identification of nursery areas as essential fish habitat led to many areas of coastline being

labelled essential, due to the mere presence of juvenile fish (Minello, 1999). This broad

classification has been refined over time, starting with developing a functioning definition of what

a nursery area might be. Beck et al. (2001) provided a sensible definition, stating that “nurseries”

are those areas of juvenile habitat that contribute a greater number per unit area of recruits into

an adult stock. While intuitive, this definition overlooks the importance of scale. Dahlgren et al.

(2006) expanded on this theory to describe “effective juvenile habitats” as those that contribute a

greater proportion of the total recruits to a population, independent of the juvenile density. This

definition recognises that habitats with low densities of juveniles, but are abundant, may

contribute the majority of recruits to support and maintain adult populations.

Both of these definitions provide a nice, intuitive framework for identifying habitats and areas of

importance but they are also limited, in that they define importance solely by the contribution of

habitats to local fisheries, ignoring both the regulating mechanisms acting within these habitats

and the other ecosystem functions and services which they provide. This criticism, led by the work

of Sheaves et al. (2015) and Nagelkerken et al. (2015) once again brings the integration of resource

16

management and conservation to the fore, by illustrating the different approaches researchers

have taken to inform ecosystem approaches to management (Litvin et al., 2018).

Conditions and processes in juvenile flatfish habitats

While the definitions being developed may have glossed over the regulating mechanisms acting

within juvenile habitats, fisheries researchers and ecologists have not. A large body of work has

been accumulated looking at the different conditions and processes that act within juvenile

habitats many of which focus on flatfish species. The conditions influencing juvenile growth and

survival, and hence recruitment, can be categorised into the physical and biological elements of

the environment, while the key processes occurring can be classified as density dependence and

connectivity.

Physical conditions

The physical conditions in juvenile habitat have typically been used to define them; “shallow” and

“near-shore”, describe both the bathymetry and the degree of terrestrial influence that were

identified early-on as characteristic of habitat for juveniles of many species (Riley et al., 1981;

Zijlstra, 1972 - cited in Zijlstra et al., 1982). The relationship between size and depth for many

flatfish species has been well documented (Pihl, 1989; Riley et al., 1981), however depth’s

influence on growth and survival is indirect, with the extreme shallows being described as both a

refuge from predation (Manderson et al., 2004) and highly productive prey-rich areas (Chesney et

al., 2000; Le Pape et al., 2007). Being ectothermic, the environmental temperature dictates, to a

large extent, the metabolic condition of juvenile fish. While extremes of temperature can lead to

death or exclusion from an area, within their tolerances, temperature impacts juvenile fishes’

ability to both consume and digest food, but also their cellular capacity for growth (Petitgas et al.,

2013; Schram et al., 2013; Vinagre et al., 2013). There is some evidence that flatfish can

behaviourally regulate their body temperature, avoiding the extremes of large fluctuations

experienced in the shallows, by burying in the more stable sediment (Ziegler and Frisk, 2019). This

ability to bury also aids in flatfishes’ predator avoidance (Kristensen et al., 2014), thus a habitat’s

sediment type also plays a role in their survival (Gibson, 2000). Being found close to the coast and

to terrestrial sources of water, the salinities that juvenile flatfish experience are also variable,

relative to deeper waters. Fishes’ dependence on gas exchange with waters of varying salinities

requires a degree of physiological tolerance or behavioural avoidance (Bos and Thiel, 2006),

17

however when avoidance is not possible, juvenile fish must incur an energetic cost to maintain an

osmotic balance which can reduce their scope for growth (A. K. Andersen et al., 2005; Augley et

al., 2008). Furthermore, coastal waters are not always well oxygenated, and where hypoxia

occurs, it may limit juvenile flatfishes’ scope for growth both directly (Chabot and Claireaux, 2008),

and indirectly by limiting movement and their ability to forage (Tallqvist et al., 1999).

Biological conditions

The community that juvenile flatfish are part of also determines their ability to survive and grow.

The presence of organisms that create a lot of structure can exclude juvenile flatfish from shallow

nearshore habitats where they restrict their ability to forage and bury (B. S. Andersen et al., 2005;

Wennhage and Pihl, 1994). As newly settled juveniles, flatfish diets are primarily comprised of

small crustaceans, worms and bivalve siphons (Aarnio et al., 1996 and references therein; Beyst et

al., 1999), however these prey exist in different densities and as different species in different

habitats. While individuals can select for their preferred prey (Haynes et al., 2011), the make-up

of the local in- and epifauna determines prey-availability (B. S. Andersen et al., 2005; Wyche and

Shackley, 1986). These differences in available prey influence the foraging efficiency and

digestibility of juvenile fish diets, ultimately impacting on the energy they have available for

growth (Ciotti et al., 2013). Whilst being predators themselves, the presence and abundance of

juvenile flatfishes’ own predators has a direct impact on their survival (Bailey, 1994), but also their

ability to forage and hence their growth (Maia et al., 2009).

Density-dependent processes

Species such as flatfish experience a large reduction in their potential habitat as they transition

from pelagic larvae to settled, benthic juveniles. They move from a three-dimensional pelagic

habitat, unbounded by bathymetry, to a two-dimensional benthic habitat which is further

restricted to shallow coastal areas. This period in their life-history is described as a period of

concentration (Beverton, 1995), during which density-dependent process act to reduce

fluctuations in the size of the cohort from earlier life-history stages. For juvenile life-history stages

experiencing concentration, density-dependent processes can act directly via mortality or

indirectly through decreased growth rates to reduce the population size. It has been shown for

plaice that, early in the juvenile growth season when settled juveniles are smallest and most

susceptible to predation (Ellis and Gibson, 1997), higher densities lead to higher mortality, most

18

likely due to increased predation (van der Veer, 1986; Wennhage, 2002). This positive relationship

between density and mortality indicates that in years of large settler supply, cohorts of juvenile

flatfish will likely suffer higher mortality in juvenile habitats. The fact that this is most likely to

occur early in the juvenile growth season reduces the competition for food later in the juvenile

growth season (Le Pape and Bonhommeau, 2015). This does not, however, exclude food-

limitation as a density-dependent process; early in the settlement period, the effect of food

limitation reduces growth rate, resulting in a prolonged period of higher predation. Furthermore,

if predation is reduced over any particular period, then the early occurring density-dependent

mortality won’t occur and may give way to sporadic episodes of density-dependent growth

limitation, which is observable throughout the summer growth period (Nash et al., 2007).

Connectivity processes

Before density-dependent regulation is to act on settled fish in juvenile habitats, settling larvae

need to be able to reach them. That is, there needs to be connectivity between the habitat of the

larval life-history stage and the juvenile habitat. Because of the predominantly passive nature of

the egg and early larval dispersal (Bergman et al., 1989), the degree of connectivity between

spawning and juvenile habitats is dependent upon their proximity, the local hydrography and egg

and larval development characteristics (Hinrichsen et al., 2001). This degree of connectivity can

determine the rates of settler supply to juvenile habitats (Wennhage et al., 2007) but also the

relative supply from different spawning populations. This has been shown to create differing

degrees of dependence on local or more distant spawning aggregations (Hufnagl et al., 2013;

Petereit et al., 2014; Rochette et al., 2012). This period of interconnectivity is also an important

dispersal period between populations (Duffy-Anderson et al., 2014) acting to increase or limit gene

flow and hence influence rates of local adaptation (Diopere et al., 2018). These same rates of

genetic differentiation have been used to show that even in relatively open coastal systems,

certain areas of juvenile habitats can be interdependent with local spawning stocks, increasing

their relative importance when compared with the total potential juvenile habitat across the

species range (Cuveliers et al., 2012). Independent of the source, rate of settler supply is an

important aspect of juvenile habitat suitability, as it dictates the habitat’s production of recruits

(Nash et al., 2007). Following settlement the habitat conditions and density-dependent processes

described above will act to produce a number of potential recruits, the migration of these large

19

juveniles out to adult habitats determines the actual recruitment contribution from any one

juvenile habitat or habitat type (Beck et al., 2001; Dahlgren et al., 2006). This connectivity of the

juvenile habitat to adult populations is mediated by the species’ intrinsic dispersal capability

relative to any bathymetric and hydrographic barriers (Gillanders et al., 2003). Natural tags, such

as otolith chemistry, can be used to characterise juvenile habitat areas and subsequently link

adults back to these areas (Gillanders and Kingsford, 1996; Reis-Santos et al., 2018). The results

of such studies have shown that juvenile habitats contribute to adult populations in different

proportions over time (Reis-Santos et al., 2013), however, this method is yet to be applied to cases

where juveniles from the same habitat area recruit to different adult populations.

Proximately, environmental conditions, density-dependent effects and connectivity mediate the

demographic rates of settler immigration, survival, growth and successful recruit emigration,

which ultimately determine a habitat’s suitability. Descriptions of the relationships between these

proximate drivers and ultimate rates can be used to identify productive “source”, type habitats

and their relative importance among other habitats servicing the same population (Vasconcelos et

al., 2014). Attaining an understanding of all of these relationships for any one population is a

substantial task, however by taking an iterative approach we can build up to well described

systems where complex life cycle models can be used to disentangle natural variation and

anthropogenic impacts (Archambault et al., 2018; Meynecke and Richards, 2014). As long as we

present the iterative results appropriately and in context, then both they, and the subsequent

more complex maps and models of fish habitat use, can be useful tools for informing marine

resource management (Le Pape et al., 2014; Lecours, 2017).

20

Thesis aims

With this thesis I address three main aims: The first is to illustrate the value of studying near-

shore juvenile habitats, the second is to describe juvenile habitat suitability for important fisheries

species from the inner Danish waters (IDW), and the third aim is to demonstrate the efficacy of

otolith chemistry for differentiating between juvenile habitat areas of the IDW.

To illustrate the need to study juvenile fish habitats, I present a literature review of indirect

anthropogenic impacts acting on important coastal fish species at different life-history stages

(Synopsis 1).

I then use two empirical approaches to model juvenile habitat suitability for important fisheries

species of the IDW and I present maps of predicted habitat suitability (Synopses 2 & 3).

For the third aim, I use two important fisheries species as case studies to demonstrate the use of

otolith chemistry to discriminate between individuals from different habitat areas of the IDW

(Synopsis 4).

21

Synopses of Appended Articles

Synopsis 1 – Conflicts in the coastal zone: human impacts on commercially important fish species utilizing coastal habitat Appended Work 1: Appendix1 Brown, E.J., Vasconcelos, R.P., Bergström, U., Støttrup, J.G., Wolfshaar, K. Van De, Millisenda, G., Colloca, F., Pape, O., 2018. Conflicts in the coastal zone: human impacts on commercially important fish species utilizing coastal habitat. ICES J. Mar. Sci. 75, 1203–1213. doi:10.1093/icesjms/fsx237

Coastal habitats are widely regarded as important juvenile growth areas, foraging areas and

migration corridors for exploited marine species (Elliott and Hemingway, 2002; Seitz et al., 2014)

that provide important food and economic resources (Costanza et al., 1997; de Groot et al., 2012).

The concentration of human settlement and development at the coast means these habitats

encounter many different anthropogenic pressures (Airoldi and Beck, 2007; Lotze, 2006) which

can have additive or even synergistic impacts on reproduction, survival and growth (Halpern et al.,

2009, 2007; Vasconcelos et al., 2017).

This study critically assesses the impacts of different categories of human activities on coastal fish

populations of the northwest Atlantic. Building on the seminal work by Seitz et al (2014), a review

of literature was undertaken specifically looking for evidence of human activities impacting on fish

species for which formal scientific advice is given for fisheries management (termed ICES species).

The review collected information on the species, the specific life-history stage, and the type of

human activity having an impact.

Ninety-two percent of the fish species reviewed (22/24) were impacted by at least one type of

human activity in at least one life-history stage in coastal habitats. These impacts were broken

down across four different life history stages (Figure 1) and five different categories of human

activities (Figure 2).

22

Figure 1. Life-history stages of fish utilising

coastal habitats and the associated percentage

of species that are impacted by human activities

in those coastal habitats. S = mature adults

during spawning, J = immature juveniles, F =

feeding adults not in spawning, and arrows

represent migration (M).

Figure 2. Percentages of ICES fish species that

utilise and are impacted by human activities in

coastal habitats; broken down by categories of

human activity.

The percentage of fish species utilising coastal habitats that were impacted by human activities

was high overall and for all life-history stages, despite this review’s limitation to only those human

impacts which have been documented in primary literature. The juvenile life-history stage had the

most evidence of anthropogenic impacts in coastal habitats, while “toxicants and pollutants” were

the most commonly reported types of impact. Multiple types of human activities were found to

impact upon single species, both within single life-history stages but also across multiple life

history stages, a good example being European plaice (Pleuronectes platessa) where evidence of

all five categories of anthropogenic impact were found in the juvenile life-history stage.

23

Quantification of population level effects of human activities remain infrequently reported in the

literature. Determining the impacts of human activities requires a well-studied model system

where natural drivers of demographic rates, such as growth, survival and reproduction, are

quantified across the different life-history stages (Archambault et al., 2018; Meynecke and

Richards, 2014). In these systems anthropogenic impacts can be disentangled from natural

variation (van de Wolfshaar et al., 2011).

Once population level effects of human activities are known, spatially resolved representations of

cumulative impacts (Andersen et al., 2015; Foden et al., 2011) can be considered by planners and

managers (Goodsir et al., 2015; Knights et al., 2015).

24

Synopsis 2 – Juvenile fish habitat across the IDW: Habitat association models and habitat growth models for European plaice, flounder and common sole informed by a targeted survey Appended work 2: Brown, E.J., Kokkalis, A., Støttrup, J.G., n.d. Juvenile fish habitat across the IDW: Habitat Association Models and Habitat Growth Models for European Plaice, Flounder and Common Sole informed by a targeted survey. J. Sea Res. [Submitted].

There is a demand for models of fish habitat use and to understand the environmental drivers of

their distributions in order to inform managers and policy makers aiming to implement ecosystem

based fisheries management (Link and Browman, 2017). In the cases where exploited species

concentrate in coastal habitats for specific life history stages (Juanes, 2007), there is further

demand to understand habitat use in order to inform spatial management of coastal development

(Brown et al., 2018).

The European plaice (Pleuronectes platessa), flounder (Platichthys flesus) and common sole (Solea

solea) are all flatfish of the family Pleuronectidae that are exploited in Danish fisheries, both

recreational (Støttrup et al., 2018) and commercial (Ulrich et al., 2017). These three species also

concentrate in near-shore, coastal habitats as juveniles, after metamorphosing and settling out of

their planktonic larval stages (Gibson, 1999; Rijnsdorp et al., 1985). This study aimed to create

Habitat Association Models (HAMs) and Habitat Growth Models (HGMs) for the 0-group of each

species, informed by a targeted survey of coastal habitats across the IDW. Furthermore, it aimed

to utilise these models to predict and create maps of relative habitat suitability using both density

and growth as proxies for suitability.

A targeted survey using a juvenile beam trawl, sampled 146 sites from a range of near-shore

coastal habitats around the IDW, in July and August of 2016 (Figure 3). Juveniles of the target

species were collected together with measurements of the physical environment.

25

Figure 3. Juvenile survey of the IDW from 2016. Panel A shows sampling locations where the

juvenile trawls were made by hand ()or small boat () and the inset places Denmark within

northwest Europe. The CPUE as young of the year fish.m-2, is broken down for each target species,

namely European plaice (Pleuronectes platessa; B), flounder (Platichthys flesus; C), and common

sole (Solea solea; D). The depth scale across all panels is limited to 120m to better illustrate

changes through the study area. Figure is taken directly from Brown et al (n.d.).

26

In the laboratory, Daily Length Specific Growth Rates (DLSGR) for the ten days prior to capture

were determined, from a sub-sample of fish per site, using otolith microstructure analysis. Both

the density of individuals and the growth rates were modelled as functions of the environment

using generalised linear models and their mixed model equivalents (GLMs and GLMMs,

respectively). Full models went through selection to find the most parsimonious set per species,

and these were put through repeated sub-sampling cross validation. These models were then

utilised to predict juvenile fish densities and growth rates, as proxies for habitat suitability, across

the IDW. These predictions were based on modelled environmental data from various sources

that were sampled across a grid covering the near-shore, soft-bottom habitats of the IDW.

Predicted maps were paired with maps of standard errors to indicate the underlying uncertainty

inherent in the models (Figure 4 & Figure 5).

27

Figure 4. Maps of predicted density based on

Habitat Association Models (HAMs) for

European plaice (Pleuronectes Platessa; A & B),

flounder (Platichthys flesus; C & D), and

common sole (Solea solea; E & F). Predictions

are mean values (A, C, & E) and are paired with

standard errors of the predictions (B, D, & F) to

illustrate uncertainty. Figure is taken directly

from Brown et al (n.d.).

Figure 5. Maps of predicted Daily Specific

Growth Rates (DLSGR) based on Habitat Growth

Models (HGMs) for European plaice

(Pleuronectes Platessa; A & B), flounder

(Platichthys flesus; C & D), and common sole

(Solea solea; E & F). Predictions are mean

values (A, C, & E) and are paired with standard

errors of the predictions (B, D, & F). Figure is

taken directly from Brown et al (n.d.).

28

The correlations described in the HAMs and HGMs were discussed with particular reference to the

findings of other observational studies throughout the species’ ranges and the potential biological

mechanisms for these relationships. Furthermore the methods and approaches were critically

assessed with the intention of informing future work.

The main conclusions of this study were that drivers of 0-group density and growth were

identified. The relationships between suitability and environmental drivers were sometimes

contradictory between the metrics of density and growth, which illustrates the need to consider

multiple metrics of habitat suitability. It was also concluded that while this study is the first to

provide indications of habitat suitability for juvenile fish of the IDW, there remains substantial

scope for improving both the static habitat suitability models and our understanding of the fluxes

of settler supply and juvenile recruitment, into and out of these juvenile habitats.

29

Synopsis 3 – Juvenile fish habitat across the inner-Danish waters: Suitability modelling of coastal marine habitats for commercially important species from historic surveys Appended work 3: Brown, E.J., Kokkalis, A., Støttrup, J.G., in prep. Juvenile fish habitat across the IDW: Suitability modelling of coastal marine habitats for important fisheries species informed by historic surveys

Demand for spatially explicit descriptions of fish habitat use and importance is increasing as

resource managers implement and move toward policies based on marine spatial planning and

ecosystem based fisheries management (Leslie, 2005). Providing maps of habitat use and

importance is an effective way for researchers to communicate their findings but the methods and

data used to inform and create habitat maps can be opaque and lead to improper interpretations

(Lecours, 2017). In marine coastal habitats there is a large overlap between natural productivity

and human activities (Airoldi and Beck, 2007) which can be exemplified by the multiple

anthropogenic impacts acting on juveniles of important fisheries species in near-shore juvenile

habitats (Brown et al., 2018). Before disentangling the multiple cumulative impacts on these

systems, the natural components of juvenile fish habitat need to be described on a scale relevant

to the fishery they support. Large observational studies of this kind are resource intensive so it is

pertinent to utilise existing data, where it is available, to investigate habitat suitability. This study

used well documented, historic juvenile surveys coupled with modelled environmental data to

create habitat suitability models for 0-group juveniles of four important fisheries species from the

IDW. The most parsimonious models are selected and validated using repeated, sub-sampling

cross validation. Interpolative predictions of juvenile fish densities were mapped across the study

area and were paired with maps of lower and upper 95% confidence limits to illustrate the

uncertainty in the underlying models (for example: Figure 6). The underlying habitat association

models were discussed with reference to other works on the biology of the species and the

possible mechanisms driving the correlations before the limitations of the data, methods and

created maps were contextualised. The created maps were deemed good indicators to aid in the

development of future research.

30

Figure 6. 0-group European plaice (Pleuronectes platessa) densities predicted for July (A-C) and

August (D-F) of 1998. Predictions (A&D) are the mode of the response and are based on habitat

association models from the years 1991-2007. Uncertainty is illustrated in the lower (B&E) and

upper (C&F) 95% confidence limits of the predictions.

31

Synopsis 4 – Juvenile fish habitat across the IDW: Using otolith chemistry to discriminate between hybridising con-familials and contiguous, coastal habitat Appended work4: Brown, E.J., Reis-Santos, P., Gillanders, B.M., Støttrup, J.G., 2019. Juvenile fish habitat across the inner Danish waters: Using otolith chemistry to discriminate between hybridising con-familials and contiguous, coastal habitat. Estuar. Coast. Shelf Sci. 220, 111–119. doi:10.1016/j.ecss.2019.02.025

Many marine fish species have different habitat requirements across different life history stages,

and so knowledge of the connectivity between these different life-history stages and the areas

they inhabit is important for managers of both fisheries and marine habitats (Vasconcelos et al.,

2014). For many marine species, dispersal is most significant in the pelagic egg and larval phase,

where individuals from different spawning populations mix before settling in juvenile habitats

(Duffy-Anderson et al., 2014). In these juvenile habitats mortality and growth rates regulate the

level of recruitment back into the adult stock (Gibson, 1994). The contributions of different

spawning stocks to settlers in juvenile habitats can be traced using genetic tools (Ulrich et al.,

2017), however because of the mixed nature of populations in juvenile habitats these tools are

unable to trace the contributions of juvenile habitats back to the adult stocks. To trace adults back

to previously inhabited areas requires tags and one such naturally occurring tag is the relative

concentrations of trace elements that are incorporated into a fish’ otolith throughout its life (Reis-

Santos et al., 2018). These trace elements are incorporated at different rates depending on the

environmental exposure to different elements, the inherent physiology of the species and the

mediating effect of the environment on that physiology (Izzo et al., 2018). This study used otolith

chemistry to determine if the physiologically compatible, hybridising con-familials of European

plaice (Pleuronectes platessa) and flounder (Platichthys flesus) can be distinguished from one

another where they have been caught in the same habitat. Furthermore, it investigated whether

this natural tag can be used to differentiate between contiguous, coastal juvenile habitats using

the important fisheries species of plaice and common sole (Solea solea) from the IDW as case

studies.

32

A survey of juvenile habitats across the IDW provided samples from sites where both 0-group

plaice and flounder were caught together, as well as samples of 0-group plaice and combined 0-

and 1-group sole from four habitat areas (Figure 7). Trace element analysis was carried out on

spots at the edge of the otolith to represent the signal laid down in the habitat in which they were

caught. A Canonical Analysis of Principle-coordinates (CAP) was carried out on a suite of 8-9 trace

element concentrations to group and test reassignment of individuals back to their species or

habitat area (Anderson and Willis, 2003). All differences utilised in the CAP were confirmed via

PERMANOVA analyses (Anderson, 2006, 2001).

33

Figure 7. Sampling locations (A) indicating gear type used where juvenile trawls were made with a

boat () or by hand(), or where fyke nets were set (). The locations where European plaice

(Pleuronectes platessa) and flounder (Platichthys flesus) were captured togther are plotted as the

number of pairs (B). The locations of sites contributing plaice (C) and common sole (Solea solea)

(D) are illustrated with the size of symbols representing the number of individuals and the habitat

area they were caught in represented by shape (Skagerrak (), Northern Kattegat (), Southern

Kattegat (), and Belt Seas ()). Figure taken directly from: Brown, E.J., Reis-Santos, P.,

Gillanders, B.M., Støttrup, J.G., 2019. Juvenile fish habitat across the inner Danish waters: Using

otolith chemistry to discriminate between hybridising con-familials and contiguous, coastal

habitat. Estuar. Coast. Shelf Sci. 220, 111–119. doi:10.1016/j.ecss.2019.02.025

34

These natural tags were able to correctly assign sympatric 0-group plaice and flounder to the right

species ~72% of the time. Furthermore, more than two thirds of plaice and ~80% of sole were

correctly assigned to their juvenile habitat areas (Figure 8).

Figure 8. Proportions of individuals assigned (“Assigned”) to the different habitat areas of origin

(“Original”) using canonical analyses of principal coordinates for European plaice (Pleuronecteds

platessa; A) and sole (Solea solea; B). Cells on the diagonal represent correct allocations while

those on off the diagonal represent incorrect allocations and shading indicates the proportion of

fish assigned per origin where lighter = closer to zero and darker = closer to 1. Figure taken directly

from: Brown, E.J., Reis-Santos, P., Gillanders, B.M., Støttrup, J.G., 2019. Juvenile fish habitat across

the inner Danish waters: Using otolith chemistry to discriminate between hybridising con-familials

and contiguous, coastal habitat. Estuar. Coast. Shelf Sci. 220, 111–119.

doi:10.1016/j.ecss.2019.02.025

35

This study suggested that further work on the degree of plaice-flounder hybridisation in this area

is warranted and that the small scale ecology of each species should be investigated where they

and their hybrids are found in the same juvenile habitats. This species complex may be an

interesting model for investigating the roles of intrinsic and environmental mechanisms to the

incorporation of trace elements in otoliths. Furthermore, the successful differentiation between

contiguous juvenile habitats indicates that otolith chemistry is an appropriate tool for use in

tracing juvenile habitat contributions to adult stocks, even in systems with large areas of juvenile

habitat occur outside of discrete estuaries and fjords.

36

Synopsis 5 – Ancillary projects Appended works 5: A collection of short communication format reports on other projects undertaken during the PhD program.

An important determinant of fish densities in juvenile habitats is the supply of settling larvae ready

to colonise them. The rates of supply are determined both by growth and survival of the pelagic

eggs and larvae (Horwood et al., 2000), and also the connectivity of the juvenile habitats to the

spawning habitats (Lacroix et al., 2013; Petereit et al., 2014). The effects of settler supply are

especially observable early in the juvenile growth season, prior to the action of regulating effects

that occur in juvenile habitats over the first summer (van der Veer et al., 2015). These regulating

effects can be examined through different rates of sub-cohort survival and growth throughout the

juvenile growth season (Ciotti et al., 2014; van der Veer, 1986). Additionally, the presence and

density of other organisms influence habitat suitability in their roles as prey , predators (Modin

and Pihl, 1996) and habitat structuring organisms (Pihl et al., 2005; Wennhage and Pihl, 1994).

Quantifying biotic drivers of habitat suitability for juvenile fish is more resource intensive than

measuring physical characteristics (Le Pape et al., 2007, 2003) and can become prohibitive at

larger spatial and temporal scales (De Raedemaecker et al., 2012, vs. 2011).

This collection of reports describes two studies aimed at quantifying the supply of settling

juveniles and following their growth and survival throughout a growing season, and one study

investigating the role of biotic drivers of habitat suitability. In all three cases, catches of target

species were insufficient to address these aims; however, they are included here as ancillary

projects for two reasons. The first is to demonstrate that settler supply, sub-cohort dynamics and

biotic drivers of fish distribution were all recognised as important extensions of describing juvenile

habitat suitability and significant attempts were made to quantify and describe them. The second

reason is to document the methods applied so that future attempts to address these questions

can be informed by the experience of these three studies.

37

Synthesis and Conclusions

Synthesis of presented research

In this thesis I have demonstrated that the vast majority of exploited fish species utilise coastal

habitats during at least one life-history stage (~75% of species) and provided evidence that while

inhabiting coastal areas they (92% of coastal, exploited species) are subject to a variety of

anthropogenic impacts in addition to their direct exploitation. I have identified the juvenile life-

history stage as being the most frequently impacted in coastal habitats and described how they

are often subject to impacts from multiple human activities. The high rates and diversity of

impacts that juvenile fish in coastal habitats face warrants further attention but in order to

identify and quantify these impacts the role of natural environmental drivers needs to be more

fully understood.

I have used two different empirical approaches to address the role of natural drivers in

determining juvenile habitat suitability in the IDW, namely one of direct survey and observation,

and one utilising pre-existing data.

The first consisted of undertaking a large-scale survey of near-shore habitats throughout the

transitional waters of Denmark and using direct observation of environmental conditions to model

habitat suitability for the 0-group of three key fisheries species. In this approach, both densities

and growth rates (derived from otolith micro-structure analyses) were used as proxies for habitat

suitability, which was described in terms of the physical environment, using generalised linear

(mixed) models. These habitat suitability models showed that individual components of the

physical environment may act in a complementary or contrasting manner with regard to their

effects on density or growth; further justifying the use of multiple proxies for describing habitat

suitability.

In the second approach, I utilised records of abundances from historic juvenile trawl surveys

coupled with modelled environmental data to determine the role of different environmental

drivers in describing 0-group habitat suitability for four key fisheries species. The use of historic

surveys provided data across a much larger temporal scale than otherwise possible, but required a

critical approach to data appraisal.

38

Using these two approaches I have presented juvenile habitat suitability models, and indicative

maps of habitat suitability, at a scale relevant for resource management across the IDW. These

studies build upon local scale, more targeted descriptions of species’ responses to their

environment, reported from within the IDW. They also add to the literature on regional

descriptions of habitat suitability for these species outside of the IDW. The majority of the

relationships described in these two approaches corroborate the findings of other regional scale

studies and are supported by the results of field and laboratory studies that describe the

mechanisms underlying the species’ distributions. I applied these habitat suitability models to

produce maps of predicted densities and growth throughout the extent of the study area. These

maps, when paired with maps of their uncertainty, are an effective tool for visualising and

communicating the complex models. I have openly presented the results of model validation,

discussed the limitations of my selected methods, and contextualised these maps as static

representations in a dynamic system, all in an attempt to ensure they are properly interpreted.

A common trend described in these two works is the latitudinal gradient of 0-group fish densities

across the IDW, many of which were not attributed to other environmental co-variates. For

species such as plaice, which consistently exhibited increased densities at higher latitudes,

increased supply of settlers from populations outside of the study area is the likely mechanism

driving this correlation. This raises an important question; do juvenile fish that were spawned

from outside populations, but settle in juvenile habitats of the IDW, recruit to local adult

populations or do they migrate back to their natal spawning populations?

The answer to this question has implications for evaluating the productivity of juvenile habitats in

sustaining local fish stocks, for understanding the degree and mechanisms of population mixing,

and for understanding the source-sink dynamics of different life-history stages in different habitat

areas. The fourth study I have presented in this thesis provides a foundation for addressing this

question by demonstrating the efficacy of otolith chemistry as a tool for discriminating between

individuals that utilised different juvenile habitat areas. Using plaice and sole, I show that otolith

chemistry can differentiate between trace element signals incorporated in open coastal habitats

which, unlike estuaries and fjords, are not dominated by a single watershed’s chemical loading. In

this study I also compare the otolith chemistry of plaice and flounder juveniles caught together in

39

an area where they are reported to hybridise, which encourages further work on this under-

studied hybridising complex.

In addition to these four completed works, I have appended a collection of short reports which

describe attempts to quantify settler supply to juvenile habitats and incorporate biological drivers

of juvenile fish habitat suitability. These short communication styled reports are intended to be

used in the development and planning of future work that might look to address these questions.

Future perspectives

While the results presented in this thesis provide a foundation for quantifying juvenile habitat

suitability throughout the IDW, there are multiple areas where this work should be expanded and

further developed. There are currently no regular surveys that adequately sample the near-shore

juvenile habitats of the IDW, such as those undertaken in the past. Having multi-annual survey

data, with concurrently observed environmental conditions, would help to investigate how

juvenile habitats change under different hydrological conditions and with different rates of settler

supply. Regularly quantifying juvenile abundance at the end of the juvenile growth period may

also facilitate the development of juvenile-stock relationships to inform fisheries management.

Furthermore, multi-annual libraries of juvenile otolith chemistry are required to be able to link

adult fish from the fishery or spawning habitats back to their juvenile habitat areas, thus

describing an aspect of life-history connectivity that is not possible with genetic tools.

Increasing within-year sampling resolution could help to quantify sub-cohort population dynamics.

Knowledge of rates of settlement, growth and survival across the juvenile growth season would

allow investigations of ontogenetic habitat shifts, habitat specific density dependence, and how

juveniles of different spawning populations interact where they mix in juvenile habitats.

Combining high spatial resolution sampling at a small scale within a programme of larger scale

surveys could help to identify the mechanisms that drive patterns of habitat use observed at the

larger scale by investigating how different patches are utilised within habitats.

40

Conclusion

With the collection of works presented in this thesis I have illustrated the motivations for studying

juvenile fish habitat and based on these needs, I have focussed on juveniles of exploited flatfish

from the IDW to model aspects of the physical environment that determine habitat suitability.

From this modelling I have produced the first maps of juvenile habitat suitability for the IDW.

Furthermore, I have demonstrated the use of otolith chemistry for discriminating between

contiguous juvenile habitat areas. These results provide a foundation for larger programmes of

work to continue to improve maps of fish habitat suitability and the extent of connectivity

between life-history stages.

41

Supplementary Contributions Boje, J. (Ed.), 2019. Improvement of the biological advice for Common Sole in Danish waters. National Institute of Aquatic Resources, Technical University of Denmark, Copenhagen, Denmark. Gabellini, A.P., 2018. The Distribution of Coastal Gobies from the IDW Author. The Technical University of Denmark. (EJB as supervisor) Hamer, A.L., Lansbergen, R.A., 2017. Microplastic occurrence in marine coastal gobies and sticklebacks in the Inner Danish Coastal Waters. Van Hall Larenstein & The Technical University of Denmark. (EJB as advisor) HELCOM, Olsson, J., Naddafi, R., Brown, E.J., Lejk, A.M., Smoliński, S., Bergström, L., 2018. Status of coastal fish communities in the Baltic Sea during 2011-2016 - The third thematic assessment. Helsinki, Finland. Kraufvelin, P., Pekcan-Hekim, Z., Bergström, U., Florin, A.-B., Lehikoinen, A., Mattila, J., Arula, T., Briekmane, L., Brown, E.J., Celmer, Z., Dainys, J., Jokinen, H., Kääriä, P., Kallasvuo, M., Lappalainen, A., Lozys, L., Möller, P., Orio, A., Rohtla, M., Saks, L., Snickars, M., Støttrup, J.G., Sundblad, G., Taal, I., Ustups, D., Verliin, A., Vetemaa, M., Winkler, H., Wozniczka, A., Olsson, J., 2018. Essential coastal habitats for fish in the Baltic Sea. Estuar. Coast. Shelf Sci. 204, 14–30. doi:10.1016/j.ecss.2018.02.014 Støttrup, J.G., Kokkalis, A., Brown, E.J., Olsen, J., Kærulf Andersen, S., Pedersen, E.M., 2018. Harvesting geo-spatial data on coastal fish assemblages through coordinated citizen science. Fish. Res. 208, 86–96. doi:10.1016/j.fishres.2018.07.015 Støttrup, J.G., Kokkalis, A., Brown, E.J., Vastenhound, B., Ferreira, A.S., Olsen, J., Dinesen, G.E., 2019. Essential Fish-habitats for commercially important marine species in the IDW. Copenhagen, Denmark. Sørensen, T.K., Egekvist, J., Brown, E.J., Hansen, F.I., Carl, H., Møller, P.R., Dinesen, G.E., Vinther, M., Støttrup, J.G., 2016 Kortlægning af fiskenes levesteder i den danske del af Øresund. DTU Report to the Ministry of Environment and Food, 105pp.

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Appendices 1 – 4:

Due to copyright restrictions these four appendices have been removed from this publicly

available version. Below are links to the published articles which will be updated as articles are

published.

Appendix 1

Brown, E.J., Vasconcelos, R.P., Bergström, U., Støttrup, J.G., van de Wolfshaar, K.E., Millisenda,

G., Colloca, F., Pape, O., 2018. Conflicts in the coastal zone: human impacts on commercially

important fish species utilizing coastal habitat. ICES J. Mar. Sci. 75, 1203–1213.

doi:10.1093/icesjms/fsx237

Appendix 2

Brown, E.J., Kokkalis, A., Støttrup, J.G. (submitted) Juvenile fish habitat across the inner Danish

waters: Habitat association models and habitat growth models for European plaice, flounder and

common sole informed by a targeted survey. J. Sea Res.

Appendix 3

Brown, E.J., Kokkalis, A., Støttrup, J.G. (submitted) Juvenile fish habitat across the inner Danish

waters: Suitability modelling of coastal marine habitats for important fisheries species informed by

historical surveys. Fish Res.

Appendix 4

Brown, E.J., Reis-Santos, P., Gillanders, B.M., Støttrup, J.G., 2019. Juvenile fish habitat across the

inner Danish waters: Using otolith chemistry to discriminate between hybridising con-familials and

contiguous, coastal habitat. Estuar. Coast. Shelf Sci. 220, 111–119. doi:10.1016/j.ecss.2019.02.025

Appendix 5.

Juvenile fish habitat across the inner Danish waters: Citizen Scientists report on the arrival and abundance of juvenile flatfish settling in near-shore juvenile habitats Elliot J. Brown1, Vagn Gram2, and Josianne G. Støttrup1

1National Institute of Aquatic Resources, The Technical University of Denmark

2Danish Amateur Fishers Association

Abstract

Understanding the dynamics of larval settlement, the subsequent juvenile growth and mortality that occur

throughout a growing season, and how these vary across different juvenile habitats is an important

component of understanding juvenile habitat suitability. A citizen science observational study was

undertaken to provide the spatial scale and temporal resolution required to sample multiple juvenile

habitat areas across a whole settlement and growth season, with the aim to describe differences in timing

and abundance of settlers across the inner Danish waters. While samples were too few to address the

scientific aims, close to 1500 hours of sampling were undertaken by 22 citizen scientists and this short

communication describes the engagement and sampling effort before discussing the experience and

lessons for future citizen science projects to consider.

Introduction

Surveying the abundances of adult fish stocks and their contributions to recruitment can be carried out

through the analyses of fisheries landings but is often supplemented with fisheries independent surveys.

However, many fish populations are regulated by processes occurring in early life stages, both pelagically

and in juvenile habitats (van der Veer et al., 2015, 2000). These juvenile habitats are often geographically

removed from adult habitats (Gibson, 2005), and thus the fisheries targeting them and the surveys

targeting adult fish. Quantifying the contribution of different juvenile habitats back to adult populations is

then outside the scope of typical fisheries monitoring but is important for fisheries managers in moving

toward ecosystem approaches to fisheries management (Litvin et al., 2018) and to properly inform the

planning of coastal marine development (Sundblad et al., 2014).

Undertaking targeted juvenile surveys is resource demanding (Le Pape et al., 2007) and carrying them out

repeatedly throughout a juvenile growth season becomes logistically challenging to the point of being

prohibitive at larger spatial scales (De Raedemaecker et al., 2012, vs. 2011). Because different regulating

processes, such as changes to mortality (van der Veer, 1986) and growth rates (Ciotti et al., 2014), operate

across the first summer growth period in juvenile habitats, there is a strong motivation to try and sample

with higher temporal resolution.

Across Denmark there are many amateur fishers operating in near-shore areas who have abundant

experience and knowledge of their local systems (Sparrevohn and Storr-Paulsen, 2015; Støttrup et al.,

2018). These fishers are well organised into local, regional and national associations, and are motivated to

understand more about the biology of the species they target. They are already engaged with the national

fisheries research institute and have provided standardised catch registrations for coastal fish monitoring

over the past 15 years (Støttrup et al., 2018). This study aimed to utilise this network of trained and highly

motivated citizen scientists to undertake coastal sampling for juvenile fish with the specific research aims:

1. To identify the timing at which settlement occurs in different regions. 2. To determine the relative

abundances of settlers across different regions of the inner Danish waters. 3. To provide samples for

laboratory analyses of changes in growth across the first summer of select flatfish species’ life.

Methods

Engagement

In Autumn of 2015, a plan for the recruitment and engagement of member fishers was made with the

guidance of the liaison from the Danish Amateur Fishers Association. Information articles on the project

and its goals were published in local amateur fishing magazines and advertisements calling for volunteers

were placed in multiple issues. Volunteer registrations were mapped and selections made to enable a

broad geographic coverage. Early registering participants were informally surveyed for their advice on

catching young of the year flatfish before a final design was mutually agreed upon with the liaison from the

association. An induction and instruction meeting was held in February of 2016 with 24 participants and

extra volunteers who were interested in being substitutes in areas where there were too many volunteers.

Details regarding sampling methodology, fish identification and other questions were addressed and gear

was distributed (Figure 1). Unfortunately, in 2016, the custom made nets were delayed in manufacturing

and the project had to be postponed until 2017. In late 2016, the above engagement process started again.

Figure 1. Distribution of standardised gear and recording sheets to citizen scientists as part of project

"Småfisk" in 2016. Top panel shows authors in reverse order from left to right. Images courtesy of Viola

and Henning Nielsen from “Danske Fritidsfiskere”.

Sampling

Citizen scientists used standard gear, which were three sets of double-ended, free-standing fyke nets with

11mm mesh wings leading to 10mm and 8mm mesh in the front and back of the fyke respectively. The

traps had 55, 50, 45, and 40 cm concentric rings with square funnel openings. The three sets of fykes were

set together along the 1-1.5m depth contour for ~12hours overnight. Sampling was planned for every two

weeks from the beginning of April 2017 to the end of August 2017 and each citizen scientist used the same

location every time, in accordance with the Danish Nature Agency’s Dispensation (16-7521-000006).

Citizen scientists were provided with three levels of data-collection forms pertaining to a one-off

description of their sampling position, a sampling day record of catches and conditions, and a per-fish label

for identification information (Figure 2). Citizen scientists were responsible for identification, counting and

length measurements to the nearest cm. Once a month (every second sampling), citizen scientists

collected subsamples of target species, identified and individually froze them for confirmation of their

identifications and further laboratory analyses. Data collection forms and frozen samples were collected

once every two months throughout the study. In the middle of July, after low collections the study was

cancelled.

Figure 2. Example data collection sheets provided to citizen scientists. The left panel is filled in one time and

collects information on the site while the form on the right was filled out for each fyke net, at each sampling

occasion.

Results

Twenty citizen scientists including recreational fishers and Nature-school leaders, were able to regularly

perform coastal sampling at 22 stations using the standard gear (Figure 3). In total ~1500 hours of fishing

time were undertaken across the four and half month period (Figure 4). Reported catches during this time

were dominated by cod and flounder (Figure 5), many of which were not 0-group settlers (uncollated

length data).

Figure 3. Positions of sampling locations. Twenty citizen scientists undertook sampling across 22 fixed

locations with standard gear every two weeks from April to September of 2017. The depth scale is limited to

120m to allow for variation throughout the study area to be visualised.

Figure 4. Cumulative fishing hours undertaken by citizen scientists targeting settling juvenile fish from April

to July of 2017.

Figure 5. Catches of fisheries species from juvenile fyke nets deployed in shallow, near-shore habitats by

citizen scientists.

Discussion

Unfortunately, due to the low catch rates of the target organisms, namely 0-group settling flatfish,

participant morale fell, and the return on effort for both the volunteers and the researchers was deemed

too low to continue the study through to the planned end-date and was concluded 1.5 months early. There

were many noteworthy experiences from this project that should be considered in any future attempts at

citizen science projects; be they with this group, or matching the aims of this study but with other citizen

scientists from with different demographic profiles. The following discussion will elaborate on these in a

chronological order.

The selection of sampling equipment was made in collaboration with representatives of the participant

group. There was a consensus among fishers, who used both shrimp fykes and eel fykes close to the coast,

that juvenile flatfish were caught plentifully and often in these types of gear, and subsequently released.

The idea to combine the two designs to form a specific juvenile fish fyke seemed logical and helped to

ensure a standard gear was used across the whole study. However, due to the timeframes involved, no

pilot study was carried out using this new gear type and large numbers of crabs were found to enter the

traps and predate both juvenile and adult fish which further reduced already low catch rates. A pilot study

in a tank setting may have provided insight to the efficiency of the traps and perhaps juvenile fish

behaviour in relation to the “wings”, and the traps themselves. A recommendation for future projects

would be to pilot study the selected gear types, both in the lab and in the field if possible.

The pool of volunteers that the citizen scientists for this study were drawn from, were previously engaged

and highly-motivated. Working with pre-formed organisations and networks made communication and

recruitment much easier and taking time to identify and approach such organisations is recommended. In

the current study, many of the pool of potential volunteers had previous training in the collection and

recording of fisheries data, not to mention their wealth of experience operating in these conditions. The

fact that many citizen scientists are volunteer, means that through self-selection, the group will already be

engaged and motivated. However it is the authors’ opinion that the additional data collection training that

this volunteer pool had received, is a requirement for any project.

Prior to sampling beginning all citizen scientists were called to a planning meeting. This practice is to be

highly encouraged, as it allowed for all gear to be properly distributed, the same set of instructions to be

delivered to all participants, and the whole group could hear answers to questions they may not have

otherwise asked. Furthermore, forming a common group on some form of social media allows for these

types of discussions to continue in an open forum once everyone has dispersed.

While the direct sampling effort is distributed among the citizen scientists, there remains a large amount of

time and work for the researcher in a support and coordination capacity. Replacement gear, sample

collection, technical support and feedback are constantly required and demand a large amount of time.

Additionally, volunteers like to see the result of their contributions; in the current study updates on

progress were given verbally, in telephone conversations and during sample collection trips. It is highly

recommended that future studies operating over extended periods of time, pre-arrange a data visualisation

portal to allow citizen scientists to keep up with the data collection progress as data is collated.

As with all projects, closure is important. Although the current study did not achieve its scientific aims, a

summary of the work undertaken and the project’s reception by the wider scientific community (Brown et

al., 2017) was presented to the participants, and the wider pool of recreational fishers which they were

drawn from.

Conclusions

The current study did not achieve its scientific aims of describing juvenile fish settlement rates across the

inner Danish waters. However, this failure cannot be attributed to the citizen science approach, conversely,

the group of highly engaged and motivated volunteers involved in this study undertook a sampling effort

across temporal and spatial scales that were well in excess of any attempts a single researcher could make.

Key aspects that a researcher engaging in a citizen science project should consider are: 1) Methods and

equipment should be developed together with participants, but should be critically evaluated by the

researcher prior to the broader project commencing. 2) Appropriate audiences should be targeted for

recruitment to the project, and where possible it is beneficial to utilise existing organisation and their

networks. 3) Communication is key; where possible bring citizen scientists together for meetings to share

important information and maintain open forum style communication for the duration of the project.

Results should be presented to the citizen scientists, if this is done real time it can provide additional

motivation. 4) Researchers need to ensure they are well resourced to accommodate the increased scale

that citizen science projects can bring to observational studies.

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platessa L. in nursery areas: A review. J. Sea Res. 90, 64–82. doi:10.1016/j.seares.2014.02.010

De Raedemaecker, F., Brophy, D., O’Connor, I., Comerford, S., 2012. Habitat characteristics promoting high

density and condition of juvenile flatfish at nursery grounds on the west coast of Ireland. J. Sea Res.

73, 7–17. doi:10.1016/j.seares.2012.04.013

De Raedemaecker, F., Keating, J., Brophy, D., O’Connor, I., Mc Grath, D., 2011. Spatial variability in diet,

condition and growth of juvenile plaice (Pleuronectes platessa) at sandy beach nursery grounds on the

south-west coast of Ireland. J. Mar. Biol. Assoc. United Kingdom 91, 1215–1223.

doi:10.1017/s0025315410001505

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Le Pape, O., Baulier, L., Cloarec, A., Martin, J., Le Loc’h, F., Désaunay, Y., 2007. Habitat suitability for juvenile

common sole (Solea solea, L.) in the Bay of Biscay (France): A quantitative description using indicators

based on epibenthic fauna. J. Sea Res. 57, 126–136. doi:10.1016/j.seares.2006.08.011

Litvin, S.Y., Weinstein, M.P., Sheaves, M., Nagelkerken, I., 2018. What Makes Nearshore Habitats Nurseries

for Nekton ? An Emerging View of the Nursery Role Hypothesis. Estuaries and Coasts.

doi:10.1007/s12237-018-0383-x

Sparrevohn, C.R., Storr-Paulsen, M., 2015. Eel, cod and seatrout harvest in Danish recreational fishing

during 2011. Copenhagen, Denmark.

Støttrup, J.G., Kokkalis, A., Brown, E.J., Olsen, J., Kærulf Andersen, S., Pedersen, E.M., 2018. Harvesting geo-

spatial data on coastal fish assemblages through coordinated citizen science. Fish. Res. 208, 86–96.

doi:10.1016/j.fishres.2018.07.015

Sundblad, G., Bergström, U., Sandstrom, A., Eklov, P., 2014. Nursery habitat availability limits adult stock

sizes of predatory coastal fish. ICES J. Mar. Sci. 71, 672–680. doi:10.1093/icesjms/fst056

van der Veer, H.W., 1986. Immigration, settlement, and density-dependent mortality of a larval and early

postlarval 0-group plaice (Pleuronectes platessa) population in the western Wadden Sea. Mar. Ecol.

Prog. Ser. 29, 223–236. doi:10.3354/meps029223

van der Veer, H.W., Berghahn, R., Miller, J., Rijnsdorp, A.D., 2000. Recruitment in flatfish, with special

emphasis on North Atlantic species: Progress made by the Flatfish Symposia. ICES J. Mar. Sci. 57, 202–

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Ltd., pp. 185–206.

Timing and abundance of settling 0-group flatfish in juvenile habitats of the South Funen Archipelago Elliot J. Brown and Josianne G. Støttrup

National Institute of Aquatic Resources, The Technical University of Denmark

Abstract Attempts to describe juvenile fish habitat suitability should consider the effects of settler supply when

investigating juvenile density. A regular survey was undertaken throughout the settlement period for 0-

group plaice, flounder, turbot and brill in juvenile habitats of the South Funen Archipelago, Denmark. Too

few individuals were caught to describe settlement rates across different degrees of site exposure or

throughout the settlement period. The low catch rates are discussed in regard to methodology, site

selection and environmental drivers of larval distribution.

Introduction Many marine fish species utilise different habitats across different life-history stages. For many flatfish

species of the northwest Atlantic, juveniles concentrate in shallow, near-shore habitats following a period

of dispersal as pelagic eggs and larvae (Gibson, 2005). In these juvenile habitats, mortality (Modin and Pihl,

1996; van der Veer, 1986) and differential growth rates (Ciotti et al., 2014; Nash et al., 2007) can act to

regulate the size of a cohort before they recruit into adult stocks. Understanding the drivers of survival and

growth in these habitats is important for predicting habitat suitability (Brown et al., n.d.), however their

connectivity to adult stocks determines whether larvae will encounter suitable areas of habitat (Petereit et

al., 2014) and whether juveniles that have survived and grown out of such habitats will recruit back to

replenish the population (Beck et al., 2001; Gillanders and Kingsford, 2000; Vasconcelos et al., 2008).

European plaice (Pleurnectes platessa), flounder (Platichthys flesus), turbot (Scophthalmus maximus), and

brill (Scophthalmus rhombus) are four flatfish species of commercial and recreational importance in

Denmark (Sparrevohn et al., 2013; Støttrup et al., 2018) and which utilise shallow, near-shore areas as

juvenile habitat (Pihl, 1989). Denmark, consisting of a peninsula and an archipelago, has a relatively large

coastline with many large areas of shallow, near-shore habitat (Schwarzer et al., 2008). One such area is

the South Funen Archipelago which boarders the southern side of two out of three straights connecting the

Baltic Sea with the North Sea. The hydrography in this region is predominantly brackish but with large

fluctuations in salinity, and temperature depending on regional meteorological conditions (Nielsen, 2005;

Stedmon et al., 2010) and local wind forcing (She et al., 2007).

Ahead of a survey of the biophysical conditions in juvenile habitats of the South Funen Archipelago, this

study aimed to describe differential rates of settler supply at three different levels of exposure and to chart

length frequency distribution changes throughout the settlement and growing season to determine the

timing of sub-cohort settlement peaks and estimate growth rate changes throughout the season.

Methods Once every two calendar weeks, from the end of April to the end of July in 2015, nine sites across the South

Funen Archipelago were surveyed (Figure 1). Sampling consisted of a juvenile beam trawl (2 m beam, 5

mm stretched mesh, and a single tickler chain) being towed by hand at approximately one knot, over

~100m, at depths of approximately one metre. Sites were categorised into three localities, each with three

relative levels of exposure, and were sampled with three hauls per site per sampling day. To reduce

disturbance of the haul area prior to sampling, the trawl was set and an oversize tow with 10m markings

was walked in a large loop around the intended haul area. At 100m from the static trawl a buoy was

anchored to the sea floor and the trawl was hauled until it reached the marker. Juvenile flatfish that were

caught were identified, had length measured and were returned.

Figure 1. Sampling locations used to determine rates and timing of juvenile flatfish settlement in the South

Funen Archipelago, in 2015. For context Denmark is shown within NW Europe (A) and the South Funen

Archipelago is located within Denmark (B). The sampling locations are spread across three areas, namely:

Helnæs (), Aerø (), and Langeland (). Each location contained three sites with different categories of

exposure, namely: Inside Sheltered (IS; orange), Inside Exposed (IE; green), and Outside Exposed (OS;

purple). The depth scale is limited to a maximum of 50m to better visualise the ranges through the majority

of the study area.

Results Too few individuals of any one species were caught (Figure 2) for meaningful statistical analyses to be

conducted, so only descriptive results are presented here. Juvenile plaice from the previous year (1-group)

were initially caught but numbers quickly reduced to zero. A peak in 0-group turbot at the end of the study

period was limited to exposed locations and predominantly came from the Langeland, Internal Exposed

site. No brill were caught at any location at any time.

Figure 2. Catches of juvenile flatfish (Pleuronectes platessa, Platichthys flesus, Scophthalmus maximus, and

Scophthalmus rhombus) from April to August of 2015. The top four plots are of 0-group catches while the

bottom four are of 1-group. Catches are pooled across localities and coloured by relative site exposure.

Discussion The South Funen Archipelago was selected as a study area because of the relatively large area of shallow

coastal habitats and the variation in exposures. Additionally, the area is close to the basins of the south

western Baltic, commonly reported as spawning areas, and between two of the straights where there is

large water exchange between the Baltic and Kattegat potentially carrying settling larvae. The assumptions

that this area would provide substantial catches of 0-group juveniles did not hold up, possible reasons

being flawed sampling methodology, poor overall habitat that settlers selected against, or poor settler

supply.

To address the first of these issues, the sampling methodology was tested in a pilot study in Nivå bay

(Danish Øresund) prior to this settlement study and was subsequently successfully used in a juvenile fish

survey across the extent of the inner Danish waters in 2016 (Brown et al., n.d.). In both circumstances, high

catch rates were attained so it is not expected that gear efficacy, nor other aspects of methodology, were

the cause of low catch rates.

This survey mentioned above also predicted that the juvenile habitats within the South Funen Archipelago

could supply median levels of 0-group plaice abundance and medium to high levels of 0-group plaice

abundance relative to other Danish coastal habitats. This suggests that larvae would be unlikely actively

select against this area for settlement.

Particle tracking models of the pelagic early life stages of plaice and flounder, seeded from spawning

grounds in the southwest Baltic, predicted high rates of settlement ready larvae to the South Funen

Archipelago under different hydrographic and spawning time scenarios (Petereit et al., 2014). Only one

scenario out of six predicted low rates of settler supply to this area; a major inflow of marine water through

the Danish straits coupled with early season spawning. In December of 2014 the third largest major Baltic

inflow event on record occurred (Mohrholz et al., 2015), meaning that if spawning for plaice and flounder

occurred relatively early in the spawning season, chances that settling plaice and flounder larvae would

have encountered the juvenile habitats of the South Funen Archipelago were at their lowest.

Conclusion A fortnightly survey of juvenile fish habitats in the South Funen Archipelago of Denmark, undertaken across

the settlement period for juvenile flatfish, caught too few juvenile fish to explore the effects of exposure on

settlement or the temporal variation in settlement and growth within a season. This was likely due to a

significant hydrological anomaly reducing settling larval supply to the area.

References Beck, M.W., Heck, K.L., Able, K.W., Childers, D.L., Eggleston, D.B., Gillanders, B.M., Halpern, B.S., Hays, C.G.,

Hoshino, K., Minello, T.J., Orth, R.J., Sheridan, P.F., Weinstein, M.P., 2001. The Identification,

Conservation, and Management of Estuarine and Marine Nurseries for Fish and Invertebrates.

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Association Models and Habitat Growth Models for European Plaice, Flounder and Common Sole

informed by a targeted survey. J. Sea Res. [Submitted.

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platessa L. in nursery areas: A review. J. Sea Res. 90, 64–82. doi:10.1016/j.seares.2014.02.010

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Gillanders, B.M., Kingsford, M.J., 2000. Elemental fingerprints of otoliths of fish may distinguish estuarine

“nursery” habitats. Mar. Ecol. Prog. Ser. 201, 273–286. doi:10.3354/meps201273

Modin, J., Pihl, L., 1996. Small-scale distribution of juvenile plaice and flounder in relation to predatory

shrimp in a shallow Swedish bay. J. Fish Biol. 2, 1070–1085. doi:10.1111/j.1095-8649.1996.tb01779.x

Mohrholz, V., Naumann, M., Nausch, G., Krüger, S., Gräwe, U., 2015. Fresh oxygen for the Baltic Sea — An

exceptional saline inflow after a decade of stagnation. J. Mar. Syst. 148, 152–166.

doi:10.1016/j.jmarsys.2015.03.005

Nash, R.D.M., Geffen, A.J., Burrows, M.T., Gibson, R.N., 2007. Dynamics of shallow-water juvenile flatfish

nursery grounds: Application of the self-thinning rule. Mar. Ecol. Prog. Ser. 344, 231–244.

doi:10.3354/meps06933

Nielsen, M.H., 2005. The baroclinic surface currents in the Kattegat. J. Mar. Syst. 55, 97–121.

doi:10.1016/j.jmarsys.2004.08.004

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survival of western Baltic fish eggs. Prog. Oceanogr. 122, 131–152. doi:10.1016/j.pocean.2014.01.001

Pihl, L., 1989. Abundance, biomass and production of juvenile flatfish in southeastern kattegat. Netherlands

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The Baltic Sea. Die Küste 74, 1–17.

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Straits. J. Mar. Syst. 65, 450–459. doi:10.1016/j.jmarsys.2006.01.017

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important flatfish species during the 20th century. Fish. Oceanogr. 22, 400–408.

doi:10.1111/fog.12030

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zone using the optical properties of coloured dissolved organic matter. Estuar. Coast. Shelf Sci. 87,

156–162. doi:10.1016/j.ecss.2009.12.022

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doi:10.1016/j.fishres.2018.07.015

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Prog. Ser. 29, 223–236. doi:10.3354/meps029223

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Local scale biophysical modelling of habitat suitability for juvenile flatfish of the South Funen Archipelago Elliot J. Brown and Josianne G. Støttrup

National Institute of Aquatic Resources, The Technical University of Denmark

Abstract

Understanding the biological determinants of fish distribution can improve descriptions of habitat

suitability but require resource intensive sampling and laboratory analyses. A local scale survey of juvenile

fish habitats from around the South Funen Archipelago was carried out at the end of the juvenile growth

period in 2015. Stomach contents analysis was carried out to determine key prey items to inform further

biological sampling for juvenile habitat suitability modelling and results are compared to diets described

from other areas of the species’ ranges. Unexpectedly low catches of juvenile flatfish were attained and

this is discussed with reference to the combination of the local scale and the year’s hydrographic

conditions.

Introduction

Descriptions of fish habitat suitability are often carried out at scales relevant to fisheries management and

use physical qualities of the environment to explain variation in fish abundances and growth. While the

inclusion of biological drivers can improve models of juvenile fish habitat suitability (Le Pape et al., 2007,

2003), the sampling and processing of relevant biota is resource intensive and can be unrealistic when

studies consider large spatial or temporal scales (De Raedemaecker et al., 2012, vs. 2011). However to

understand smaller scale juvenile fish distributions and the mechanisms driving them, then higher

resolution sampling, including relevant biological predictors, is crucial (Litvin et al., 2018; Nagelkerken et al.,

2015).

The inner Danish waters support coastal fisheries for a range of flatfish species including the near-shore,

juvenile habitats that replenish them. Juveniles share these habitats with a variety of other organisms that

can influence their movements and distribution through a variety of mechanisms, such as foraging for prey

(Vinagre et al., 2009), hiding from predators (Modin and Pihl, 1996), or avoiding structural complexity

created by algae that hinder their feeding and/or burying ability (Pihl et al., 2006; Wennhage and Pihl,

1994).

This study aimed to describe the diets of juvenile fish from the South Funen Archipelago to determine

which elements of the biota should be considered as potential biological predictors of juvenile habitat

suitability. The subsequent aim was to evaluate the relative contribution of biotic variables to models of

juvenile fish habitat suitability.

Methods

Field collections From the 10th to the 19th of August in 2015, 44 sites from the South Funen Archipelago were sampled

(Figure 1). Using ArcGIS 10.1 and data sources internal to the institute, ninety sites were randomly selected

from areas that were reported to be soft bottom (not boulder reefs or sedimentary rock) and shallower

than three metres depth. Where substrate and depth did not match the randomly selected position, the

closest matching location was used, or if no such location was found close by, the site was abandoned.

Sampling consisted of a 100m trawl of a two metre wide juvenile beam trawl at approximately one knot.

The trawl was fitted with a five millimetre stretched-mesh net and one tickler chain. The physical

environment was recorded as depth, temperature and salinity at the sea-bottom, and a sediment core was

taken using a hand-held haps-corer for later grain-size analyses. A second core sample was taken for

infaunal sample analyses and epibenthic organisms caught in the trawl were also collected.

Figure 1. Denmark within NW Europe (A), the study area within Denmark (B), and the location of sampling

sites within the study area (C). The bathymetry scale is limited to 50m to allow for proper representation of

the shallow depths through the majority of the study area.

Sample preparation Juvenile fish of the target species were killed using an overdose of benzocaine (250mg.L-1) in aerated

seawater before being frozen in individual ziplock bags. Volumes of sea-grass, categorised as dead or alive,

and different types of algae were measured in volumetric jugs after having excess water removed. Infaunal

sediment samples were sorted on successively finer (4mm, 1mm, 0.5mm) sieves with each fraction being

picked through independently. The epibenthos from the trawl were sorted in a similar fashion, by size.

Infauna and epibenthic fauna from each fraction were stored in their own sample container with 4%

formaldehyde solution in borax buffered, seawater. Seawater was sieved at 0.1mm before use as a

formaldehyde solvent.

Fish Processing In the lab, individual fish were defrosted and dorsal, anal and caudal fin rays were counted. Counts were

made under binocular dissecting microscopes, using a clicker-counter and were only finalised after three

consecutive counts were in agreement. Fish were subsequently pat dry before being weighed and having

their standard lengths measured. Entire alimentary canals were removed and weighed, while the

remaining organs were removed from the body cavity and the fish re-weighed to attain a “cleaned weight”.

Sagittal otoliths were removed, cleaned, dried and stored as pairs in individual ziplock bags. The entire

alimentary canal was dissected open so as not to crush the partially digested organisms, prey items were

then identified to the lowest possible taxonomic group before being counted (if discrete bodies or body

parts could be distinguished) and added to pre-weighed crucibles for the determination of Ash-Free Dry

Weight (AFDW). Unidentifiable contents were recorded as “digesta” and treated as another taxa, while

items that were only identifiable to higher taxonomic levels were pooled into “other_*”, groups at the

lowest level identifiable.

Infauna and epibenthic fauna processing Infauna and epibenthic fauna was cleaned of formalin and stored in 80% ethanol. Samples were sorted and

identified to at least family level, but to lower taxonomic levels where possible and higher levels if the

specimens were damaged. Individuals were counted and placed in pre-weighed crucibles for the

determination of AFDW. Larger bivalves that remained closed had their shell broken or levered open

before drying.

Determining Ash-Free Dry Weight Aluminium crucibles were prepared by burning at 500° C for two hours before being weighed. The samples

were dried in the pre-weighed crucibles at 65° C for 12-16 hours. Dried samples were weighed before

being burnt in a muffle oven at 500° C for 6 hours, after which the remaining ash was weighed in the

crucibles and the change in weight from the dried samples to the ash was recorded as the AFDW.

Data analyses and visualisation All data analyses subsequent to site selection was carried out using R statistical software (R Core Team,

2018) and figures were made using ggplot2 (Wickham, 2016). Gut contents were converted to per-taxon

dietary importance metrics based on their proportion of ASFDW in individual stomach contents and

normalised across all individuals within species by weight according to the least biased gravimetric method

described in Ahlbeck et al. (2012; method “MM3”):

𝑒𝑒𝑒𝑒. 2 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝑒𝑒𝑖𝑖 = ∑

𝑤𝑤𝑖𝑖𝑖𝑖𝐼𝐼𝑖𝑖

𝑁𝑁𝐹𝐹𝐹𝐹𝐹𝐹ℎ𝑖𝑖=1

∑𝑤𝑤𝑖𝑖𝐼𝐼𝑖𝑖

𝑁𝑁𝐹𝐹𝐹𝐹𝐹𝐹ℎ𝑖𝑖=1

× 100

Where the 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝑒𝑒𝑖𝑖 represents the relative contribution of taxon 𝑖𝑖 as prey to a particular species of

predator, 𝑁𝑁𝐹𝐹𝑖𝑖𝐹𝐹ℎ is the number of stomachs from the predator species of interest, 𝑤𝑤𝑖𝑖𝑖𝑖 is the ASFDW of taxon

𝑖𝑖 in fish stomach 𝑗𝑗, 𝐼𝐼𝑖𝑖 is the cleaned/gutted wet mass of fish 𝑗𝑗, and 𝑤𝑤𝑖𝑖 is the total ASFDW of stomach

contents for fish 𝑗𝑗.

Results

Juveniles of target species were caught at just over half of sites surveyed (Table 1). Juvenile flounder were

the most abundant of the target species, both in absolute number and the number of sites they were

present in.

Table 1. Catches of juvenile flatfish from a beam trawl survey of juvenile habitats around the South Funen

Archipelago in August 2015. Totals are of the number of fish and the collated number of sites where at least

one target species was caught, the latter of which is by chance equal to the sum of the sites for each

species.

Common Name Fish Sites Present Length Ranges

(mm)

Flounder 35 13 48-134

Plaice 9 2 72-104

Dab 9 3 75-125

Turbot 13 4 39-85

Brill 1 1 82

Total 67 23 / 44 -

Flounder, being the most abundant species, had the most diverse stomach contents at the family level

(Figure 2). Amphipoda dominated their diet, especially the family Bathyporeiidae. Bivalves, especially the

families Cardiidae and Mytilidae, were the second most important group for flounder, followed by the

phylum Annelida whose members were not identifiable beyond the Phylum. Plaice diets were almost

entirely dominated by Arthropoda, especially two families of Amphipoda. Bivalves contributed little to

plaice diets and Annelids were much less important than for flounder. Bathyporeiidae was also very

important for the dab. Turbot was the most different, with two families of larger shrimps and small fishes

being the most important prey groups. The gut contents of the single brill specimen are not presented.

Figure 2. Relative importance of different Families as prey for juveniles of four flatfish species: The

European flounder (Platichthys flesus), plaice (Pleuronectes platessa), dab (Limanda limanda), and turbot

(Scophthalmus maximus). Relative importance measures are proportions of stomach contents by mass, and

are mass corrected across individual fish.

Discussion

Few specimens of target species were caught and were often caught together at only few sites, providing

little data for diet analyses and habitat association modelling. However, the taxa observed in the stomachs

and their relative importance as prey for juvenile flatfish matches what has been reported for juveniles of

these species in studies with much larger sample sizes (Augley, 2007; Beyst et al., 1999; Nissling et al., 2007;

Ustups et al., 2007; Wyche and Shackley, 1986). The size ranges of fish in the current study are also above

the lengths at which major ontological shifts in diet have been reported for these species (Aarnio et al.,

1996; Nissling et al., 2007; Ustups et al., 2007; Wyche and Shackley, 1986), meaning it is not necessary to

break the samples down further fish size .

The high importance of Bathyporeiidae in juvenile flounder diets observed here has also been reported up

to the northern reaches of the Baltic (Aarnio et al., 1996). This same study also reported juvenile turbot

diets that were dominated by Mysidae and small fishes, which matches the turbot in the present

study(Aarnio et al., 1996). Outside of the Baltic, diets of flounder in a Danish fjord, a Scottish Estuary

(Summers, 1980) and a Portuguese estuary (Vinagre et al., 2008) were largely comprised of the infaunal

amphipod Corophium volutator with a similar habit to Bathyporeia species (Hayward and Ryland, 2017).

The substitution of different amphipods was also reported across different studies of plaice diet (Beyst et

al., 1999; De Raedemaecker et al., 2011; Gibson et al., 1998). While juvenile turbot from the Irish west

coast are reported to have very different diets to those of the current study and the Baltic proper (Haynes

et al., 2011), those in juvenile, sandy coastal habitats of the Belgian coast are more similar to the current

findings, dominated by Crangon crangon, Mysidae and small fishes (Beyst et al., 1999).

Gravimetric analyses of stomach contents indicate some prey overlap between juvenile Pleuronectids,

especially with regard to the prey family Bathyporeiidae and the other Amphipoda. The dominance of

small mobile Arthropods in the diets of plaice suggests more specialised predation compared to flounder

and dab. However, De Raedemaecker et al. (2011) report that the contribution of different taxa in plaice

diets can fluctuate from extremes of dominance by one prey type to another in both space and time. The

higher diversity in the diet of the flounder is probably due to their opportunistic feeding strategy (Andersen

et al., 2005) combined with samples coming from a larger number of sites. The dab’s prey importance

were spread across more taxa than was observed for the plaice, although they were derived from the same

number of individuals perhaps indicating a more generalist foraging approach.

The low abundances of target fish species observed in this study may be attributable to poor larval supply.

This situation was indirectly predicted by Petereit et al (2014) who demonstrated that under significant

Baltic inflow conditions early in the spawning season, the area around the south Funen archipelago would

be poorly supplied with ready to settle plaice and flounder larvae. These conditions were realised in the

spawning and distribution period prior to this study (Mohrholz et al., 2015). Irrespecitve of the cause, with

a lack of fish data for model building, the analysis of infauna and epibenthos has been carried out

opportunistically among other project work and remains underway at the time of writing. The construction

of habitat models will not be attempted but further comparisons of gut contents and available fauna are

warranted.

Conclusion

The limited findings of this study do indicate that certain taxa are more relevant for inclusion as

explanatory variables in models of juvenile fish habitat suitability. Furthermore it appears that juvenile

diets in habitats of the South Funen Archipelago are more similar to those from the Baltic proper than

those of the British Isles and Ireland.

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