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Jacobs, A., Doran, C., Murray, D.S., Duffill Telsnig, J., Laskowski, K.L., Jones,
N.A.R., Auer, S.K. and Praebel, K. (2018) On the challenges and opportunities
facing fish biology: a discussion of five key knowledge gaps. Journal of Fish
Biology, 92(3), pp. 690-698.
There may be differences between this version and the published version. You are
advised to consult the publisher’s version if you wish to cite from it.
This is the peer reviewed version of the following article: Jacobs, A., Doran, C.,
Murray, D.S., Duffill Telsnig, J., Laskowski, K.L., Jones, N.A.R., Auer, S.K. and
Praebel, K. (2018) On the challenges and opportunities facing fish biology: a
discussion of five key knowledge gaps. Journal of Fish Biology, 92(3), pp. 690-
698, which has been published in final form at http://dx.doi.org/10.1111/jfb.13545.
This article may be used for non-commercial purposes in accordance with Wiley
Terms and Conditions for Self-Archiving.
http://eprints.gla.ac.uk/159208/
Deposited on: 3 May 2018
Enlighten – Research publications by members of the University of Glasgow
http://eprints.gla.ac.uk
1
Onthechallengesandopportunitiesfacingfishbiology:1
adiscussionoffivekeyknowledgegaps2
3
A.Jacobs1†,C.Doran2,D.S.Murray3,J.DuffillTelsnig4,K.L.Laskowski2,N.A.R.4
Jones5,S.K.Auer1,&K.Præbel65
1 Institute of Biodiversity, Animal Health & Comparative Medicine, College of Medical, Veterinary & Life6
Sciences,UniversityofGlasgow,Glasgow,G128QQ,UK;2DepartmentofBiologyandEcologyofFishes,Leibniz7
InstituteofFreshwaterEcology&InlandFisheries,Müggelseedamm310,Berlin,12587,Germany;3Schoolof8
Biological Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK; 4 School of9
MarineScience&Technology,UniversityofNewcastle,NewcastleuponTyne,NE17RU,UK;5ScottishOceans10
Institute,SchoolofBiology,UniversityofSt.Andrews,St.Andrews,KY169TH,UK;6FacultyofBiosciences,11
FisheriesandEconomics,NorwegianCollegeofFisheryScience,UiTTheArcticUniversityofNorway,N-903712
Tromsø,Norway13
14
Runningtitle:Challengesandopportunitiesinfishbiology15
16
†Authortowhomcorrespondenceshouldbeaddressed:Tel:+441413306637,email:17
19
2
Abstract20
21
Many fish species face increasing challenges associated with climate change and22
overfishing.Atthesametime,aquacultureisbecomingvitalforfoodsecurity.Gaininga23
deeperunderstandingofthebasicbiologyoffishisthereforemoreimportantthanever.24
Herewesynthesiseandsummarisekeyquestions,opportunities,andchallengesinfish25
biologyhighlightedduringaround-tablediscussionatthe50thAnniversarySymposium26
ofTheFisheriesSocietyoftheBritishIsles,heldattheUniversityofExeter,UK,inJuly27
2017.Weidentifiedseveralknowledgegapsbutalsokeyopportunitiesforfishbiologyto28
informfoodsecurity,forcollectivebehaviour,evolutionaryhistory,andtraitcorrelations29
topredict responses to environmental change, and fornovel analytical approaches to30
mine existing data sets. Overall, more integrative approaches through stronger31
collaborations acrossdifferent fields areneeded to advanceourunderstandingof the32
basicbiologyoffish.33
34
Key words: Aquaculture; Integrative approaches; Behaviour; Food Security; Data35
analysis;Traitcorrelations36
37
38
39
40
41
3
Introduction42
43
Similartomostfieldsinthebiologicalsciences,fishandfisheriesbiologyhaveadvanced44
rapidly over the last decade due to technological improvements in computer science,45
Next Generation Sequencing in genetics, and novel analytical approaches such as the46
decision-tree based random forest approach (Breiman 2001, Boulesteix et al., 2012).47
However,adeeperunderstandingofthebiologyoffishismoreimportantthanever,as48
globalchallengessuchasclimatechange,overfishing,intensiveaquaculturesystems,and49
otheranthropogenicstressorshaveimpactsthatmayproveincreasinglychallengingto50
manyfishspecies(Fickeetal.2007;Halpernetal.,2008).Gapsinourknowledgeofthe51
basicbiologyofmanyspeciespreventusfromfullyunderstandingandpredictinghow52
fishspeciesandfishcommunitiesarerespondingandwillrespondtothesechallenges.53
Fillingthesegapsiscrucialifwewanttomaintainhealthyecosystemsandprovidefood54
securityforanever-growinghumanpopulation.55
Hereweoutlinefivekeyknowledgegapsthatwillbeimportantforadvancingthefieldof56
fishbiology inthenear future.Theseoutstandingquestionsandpotentialavenues for57
theirresolutionwereidentifiedaspartofadiscussionorganizedatthe50thAnniversary58
SymposiumofTheFisheriesSocietyoftheBritishIslesheldatTheUniversityofExeter,59
UK, in July 2017. They range from issues in aquaculture and fisheries, to physiology,60
behaviourandlifehistory,andtoproblemsinbioinformaticsandanalyticalapproaches.61
The overarching conclusion of this discussion was that more integrative studies are62
needed to understand fish responses to environmental change. In addition, available63
aquaticresourcesmustbeusedresponsiblyinordertoprovidefoodsecurityforfuture64
generations. In the following sections, we elaborate on each knowledge gap, outline65
4
potentialwaystofilleach,andthenconcludewithashortsynthesis.Thisarticleisnota66
comprehensivereviewofthefield,butratherastartingpointforfuturediscussions.67
68
Keyquestionsandopportunitiesinfishbiology69
70
1.Howcanweusefishbiologytoinformaquacultureandwildfisheriesinordertosecure71
foodforagrowingpopulation?72
73
Incentivesforsustainableaquacultureandfisherieshaverisenexponentiallywithinthe74
lastdecadedueaprojectedincreaseof3billionpeopleby2050(Spragueetal.,2016).75
Eventhoughfish isalreadyaprimarysourceofproteinformillionsofpeopleandthe76
contributionofaquacultureisapproachingtheleveloffisheries,boththeaquacultureand77
fisheries industries are expected to play an increasingly important role in providing78
sustainablesourcesofessentialnutrientstohumans(Troelletal.,2014;Spragueetal.,79
2016;Bernatchezetal.,2017).80
81
Inaquaculture, feedsustainability,disease,andgametequalityareagrowingconcern.82
Systematic biological approaches involving multiple aspects of fish biology can help83
resolvetheseproblems.Asanexample,themicrobiomeisonefieldoffishbiologythat84
maydramaticallyfacilitateaquaculture'sgrowth.Ourgrowingunderstandingofafish’s85
‘secondgenome’andourabilitytomanipulatemicrobiomescanimproveaquaculture’s86
understandingofnutritionalrequirements,pathogenresistance,sexualmaturationand87
survivorshipinfarmedfish(Llewellynetal.,2014).Forexample,theuseofplant-based88
productstofeedpredominantlycarnivorousteleostsisakeyissue(Murrayetal.,2014).89
Fishareunable toprocess insolublecarbohydratesand fibre, commonly foundwithin90
5
plant-based diets. Therefore, this huge, yet largely indigestible, source of nutrients is91
quickly excreted (Llewellyn et al., 2014). A considerable step towards sustainable92
aquaculture would be to 1) use our knowledge of fish microbiomes to improve93
predictionsregardinginteractionsbetweenplant-basedsustainablefeedsourcesandthe94
digestive systems of farmed fish, and 2) manipulate fish microbiomes to efficiently95
processandutilisepreviouslyindigestiblenutrients.96
97
There is also a dire need to prevent further declines inwild fisheries and tomanage98
fisheries sustainably. However, this is hindered by a lack of information and99
understandinginthreekeyareas:targetspecies’biologyandtheirspatialandtemporal100
distributionacrossalllifestages;theeffectofmultiplestressorsonfishpopulations;and101
the effectiveness of fisheries management in maintaining sustainable populations102
(Rassweileretal.,2014;Schineggeretal.,2016).Integrativeworkconnectingtheseareas103
iscrucialwhenpursuingsustainabilitygoals.Forexample,understandingthespatialand104
temporal overlap between population densities and distributions and how they are105
shapedbyanthropogenicfactorsisimperativewhenassessingsustainablemanagement106
measures(Alavaetal.,2017;Bernatchezetal.,2017;Thorsonetal.,2017).107
108
Asacaveattotheseandotherexamplesoffutureresearchprioritieswithinaquaculture109
andfisheries,scientistsmustalsocontinuetodeveloptheircoreunderstandingoffish110
biology.Despite thewealth of knowledge accruedduring decades of aquaculture and111
fisheriesresearch,fundamentalbiologicalresearchcontinuestoprovidenewinsightson112
thebasicbiologyoffish.Forexample,thegeneticbasesunderlyingecologicallyimportant113
traits(Barsonetal.,2015)orintraspecificvariabilityinphysiologicaltraits(Burtonetal.,114
6
2011), enable scientists to fully investigate behavioural, physiological or genomic115
changesfromaccuratebiologicalbaselines.116
117
2. How can we use evolutionary biology to predict contemporary responses to climate118
change,harvesting,andotheranthropogenicstressors?119
120
Understanding and predicting the response of a particular species to environmental121
change,orotherstressors,isdifficultwithouthavingadetailedbaselineknowledgeofits122
evolutionary history or its ability to respond through phenotypic changes to123
environmentalchallenges.Sincephenotypicresponsescanbeeitherheritableorplastic,124
accurate baselinesmust be obtained for both populations and species. Ultimately, by125
combiningknowledgeofevolutionaryhistorieswithothertypesofdatawecangaina126
betterunderstandingoftheevolutionarypotentialofpopulationsandspeciesandbetter127
informconservationefforts.128
129
Species may be able to cope with environmental change by either shifting their130
distributions, copingwithnewenvironments viaphenotypicplasticity, or adapting to131
novel environmental conditions (Crozier & Hutchings, 2014; Campbell et al., 2017).132
Therefore, more detailed knowledge of evolutionary responses, and the underlying133
mechanisms, on different time scales, and in different environments and species are134
neededtoenhanceourunderstandingofhowfisheswillrespondtodifferentstressors.135
Forexample,studiesontheeffectsofstrongharvestingpressuresonfishpopulations,136
e.g. through long term declines in population size and genetic diversity (Pinsky &137
Palumbi,2014)orthroughshort-termchangesingeneexpression(Uusi-Heikkiläetal.,138
2017),havealreadygivenusabetterunderstandingofhowharvestingpressuremight139
7
affecttheevolutionarypotentialoffishpopulations.Furthermore,evolutionarystudies,140
e.g. in combination with detailed ecological and developmental approaches, can141
illuminatequestionsof interest for conservation, regarding e.g. the effects of reduced142
geneticdiversityonpopulationpersistenceandadaptivepotential(Paulsetal.,2013),143
the flexibility of evolution (Elmer &Meyer, 2011), or in locating species refugia and144
driversofdiversity(Dornburgetal.,2017).145
146
We therefore argue for more collaborative studies that combine a wide range of147
informationonpopulationsandspeciesthatdifferindistribution,ecology,geneticand148
phenotypic diversity, adaptive potential, and evolutionary history. This will help to149
generatemoregenericinformationaboutthepotentialofpopulations,speciesorbiomes150
torespondtoenvironmentalandanthropogenicstressors.151
152
3.Canknowledgeofcorrelatedtraitsimprovepredictionsforfishpopulationresponsesto153
environmentalchange?154
155
Forsimplicityandclarity,weasfishbiologistsoftenconsiderourtraitofinterest-for156
examplereproductiveeffort,morphologicalspecialization,ormigrationtendencies-as157
independentoratleastinisolationfromothertraitsofthatsameindividual.However,it158
isclear that theexpressionand functionofall traitswithinan individualare, tosome159
extent,dependentoneachother.Wholesuitesoftraitscanbecorrelatedduetoeither160
mechanisticconstraints(e.g.geneticcorrelations,Steppanetal.,(2002))orbecausethey161
workwelltogetherandincreasethefitnessoftheindividual(i.e.correlationalselection,162
Sinervo & Svensson, 2002). A more complete and explicit consideration of these163
8
connections among traits is therefore needed to improve our predictions of how164
individuals,andthuspopulations,willrespondtochangesintheirenvironments.165
166
Aprimeexampleoftheimportanceofunderstandingtraitcorrelationsisthelife-history,167
morphological,andbehaviouralchangesobservedinfishpopulationsheavilyexploited168
by fishing (Hutchings & Fraser, 2008, Uusi-Heikkilä et al., 2008). Many harvesting169
regulations are size selective, so individuals are removed from the population based170
(moreorless)solelyontheirmorphology,thatis,theirbodysize.However,aswenow171
know, individual growth rates are correlated with a whole suite of physiological,172
behavioural,andlife-historytraits(Réaleetal.,2010;Uusi-Heikkiläetal.,2008;Sutteret173
al.,2012:Arlinghausetal.,2017).Therefore,highlyselectiveharvestingwillultimately174
haveconsequencesatthepopulationlevel,leadingtochangesinrecruitment,population175
recovery,andsustainableyields(Hutchings&Fraser,2008).Disentanglinghowdirect176
and indirect selection shapes these trait correlations, and the genetic mechanisms177
underlying their coupling, has led to a better understanding of how and why fish178
populations respond to harvesting as they do (Hutchings & Fraser, 2008). Similar179
approaches shouldnowbe used to understandhowenvironmental change and other180
stressors,suchasoceanacidification,anthropogenicnoise,andwarmertemperatures,181
willimpactfishpopulationsglobally.182
183
4.Howcanweuseexistingdatasetsincombinationwithnewanalyticalapproachestogain184
novelinsightsintothebiologyoffishes?185
186
Withinthelastdecadescientistshaveaccumulatedvastamountsofgenomic,phenotypic187
andecologicaldataformanyfishspecies,mainlyduetotechnologicaladvancesindata188
9
generation and rapidly decreasingmonetary costs (Muir et al., 2016). Collection and189
synthesisofexistingdataprovidesagreatopportunitytounderstandbetterthebiology190
of fish populations and communitieswithout the need to generatemore information.191
However,analyticalapproachesforjointlyanalysinglargedatasetsarestilllackingdue192
to the low accessibility of data or challenges in combining different types of data.193
Therefore, it is important that the scientific community increases their efforts in194
developingnewapproachesforextracting,combining,andanalysingexistingdata.One195
promisingavenuefor fishbiology is thatofmachine learning.Whilemachine learning196
approaches, e.g. the decision-tree based random forest approach (Breiman 2001,197
Boulesteixetal.2012),havebeenpopularinmanyfieldssuchasbiomedicalscienceor198
agriculture,theyarenowbecomingmorepopularforanalysingcomplexdatasetsinmany199
otherfields,especiallyfordatasetswithmanyindicatorsandsmallsamplesizes(Chen&200
Ishwaran,2012;Bernatchez,2016).Randomforestapproacheshavebeensuccessfully201
usedinavarietyofstudiesanalysingpopulationgenomicandphenotypedatasets,e.g.for202
predictingadaptivephenotypes related to climate (Hollidayetal., 2012),determining203
genetic loci distinguishing ecotypes (Pavey et al., 2015), detecting intra-generational204
selection through pollutants (Laporte et al., 2016), improving stock assignments in205
complexormostlypanmicticpopulations (Sylvesteretal.,2017),orpredictingof fish206
agesfromotolithmorphometricdata(Williamsetal.,2015).Theseareallsituationsin207
whichclassicalapproacheshavelowerpowerorhavefailed.Randomforestalgorithms208
havealsoprovenuseful fortheanalysisofstableisotopedatasets,usingregressionor209
classification approaches to model interactions between predictor variables, and210
imputingmissingdata(Cutleretal.,2007).Whileadetailedreviewisoutsidethescope211
ofthisarticle,therearemanyotherpromisinganalyticalframeworksandsolutionsthat212
couldbeusedto tacklecomplexbiologicaldatasets. Inorder tomakesuch largescale213
10
studiesfeasible,datahavetobecollectedandcompiledinanaccessibleandunifiedway.214
Such databases exist for some types of data or are in the process of being built, e.g.215
GenBankor IsoBank(NCBIResourceCoordinators,2017;Paulietal.,2017),butmore216
effort is needed to develop a common reporting format that permits integration of217
differenttypesofdata,suchasphenotypeandgenotypedata.218
219
5.Howcanweuseanimalcollectivebehaviourtobetterunderstandthegrouplevelimpacts220
ofenvironmentalstressors?221
222
As inmost animal groups, fish benefit from social living in a variety of ways. These223
advantagescaninfluenceindividualfitnessdirectly,suchasincreasedprotectionagainst224
predators, enhanced foraging success, better access to reproductive partners, and225
transmission of behaviour and information between individuals (Ward & Webster,226
2016).However,therearealsocostsassociatedwithgroupliving,forexample,increased227
chancesofparasitism(Côté&Poulin,1995)and increasedcompetition (Krauseetal.,228
2000).Trade-offsarisingfromthesecostsandbenefitsarelikelytobeinfluencedbylarge229
scale environmental stressors, including, but not limited to increases in water230
temperatures, ocean acidification, and fishing pressure. There has been considerable231
researchontheeffectsofthesestressorsshowingforexamplespeciesrangeshiftsdueto232
climatechange(Pecletal.,2017).However,whileconsiderableinformationisavailable233
attheindividualandpopulationlevel,fewstudiesseektoexplainorunderstandhowfish234
respondtoperturbationsorstressorsatthemoreecologicallyrelevantscaleofgroup,235
shoal,orschool.Alargeproportionoffishspeciesliveinsuchgroups,andinordertofully236
understandtheimpactsofglobalchangeonfish,studiesofgroupleveleffectsonanimal237
collectivebehaviourmaybeparamount.238
11
239
Grouplivingprovidestheopportunityforsociallearningandinmanycasesthisbenefits240
individuals within groups, thereby allowing the spread of learnt behaviours or241
knowledgethroughsocialtransmissionandavoidingpotentiallycostliertrialanderror242
learning (Rendell et al., 2010). Social learning also enables cross-generational243
transmissionofinformationlikemigratoryroutes(Helfman&Schultz,1984).However,244
traditionsandsocial learningstrategiesmay leadtomaladaptiveoutcomes; traditions245
maybecomedeleteriouswhendisadvantageousenvironmentalchangesariseorwhen246
naive fish follow leaders down sub-optimal routes (Laland & Williams, 1998). The247
potentialconsequencesofgroupmovementwhereleadersorspecificphenotypesmay248
beselectivelyremovedorimpactedbyglobalstressorsispoorlyunderstood.249
250
The argument tomove from studies focused on factorswhich affect behaviour at an251
individualleveltoconsidergrouplevelcollectivebehaviourhasbeenraisedbefore.For252
example,previousstudieshavesuggestedcombiningcognitivestudiesattheindividual253
levelwithsimilarquestionsposedatthecollectivelevel(Pelé&Sueur,2013).However,254
attemptsatdevelopingacohesiveapproachthatincorporatesindividualbehaviourinto255
collectivedecisionmakingattheshoalorschoollevelarelimited.Withrecentandrapid256
technicaladvancementsallowingimprovedvideoandtag-trackingabilities,questionson257
theimportanceofvariationattheindividuallevelingroupresponsestostressorsoron258
theeffectofenvironmentalchangeoncollectivemotion,arebecomingmoretractable.259
260
261
262
263
12
Concludingremarks264
265
Challengesandopportunitiesfacingvariousthemeswithinfishbiologyareanalyticalin266
nature.However,themethodsproposedtosolvethesedifferentissuesareinmanycases267
interchangeable, highlighting the need and possibility for stronger collaborative268
networksbetweenfishbiologistsworkingwithindifferentdisciplines.Forexample,data269
onthechangingdietaryconstituentsoffishfeedandtheircorrespondingeffectonthe270
nutritionalqualityoffarmedfishhavebeencollectedfordecadesand,whilesomeeffort271
has been made to analyse patterns within these datasets and link them to human272
nutritional trends (Spragueetal.,2016),accessibilityanddata formatting issueshave273
prevented more powerful analyses. Collaboration among scientists involved in274
aquaculture and those researching analytical approaches, such as machine learning275
algorithms,couldrevolutionisepredictivemodellingofnutrientbudgetswithinfarmed276
systems,resultinginmoreaccuratepredictionsforfuturenutritionalavailability.Other277
scientific fieldsarebeginning to turn towards thesehighlydiversecollaborations.For278
example, theGlobalLakeEcologicalObservatoryNetworkorGLEON(gleon.org) is an279
internationalgroupof limnologistsandecologistsworking tounderstand,predictand280
communicate theresponseof lakeecosystemstoachangingglobalenvironment.This281
network of scientists shares resources, and near constantmonitoring of limnological282
variables from lakes in over 50 countries, allows near real-time, web-accessible283
databasesforrapiddatatransfers,facilitatinginternationalcollaborations.Whetheras284
partofaformalorinformalnetwork,manyofthechallengesdiscussedwithinthispaper285
could benefit frommore wide-ranging collaborations, thereby ensuring a productive286
futureforresearchonfishbiology.287
288
13
Acknowledgments: The authors thank the organising committee of the 50th289
Anniversary Meeting of The Fisheries Society of the British Isles for organising and290
facilitatingthediscussionleadingtothisopinionpiece.Wealsothankthedelegatesfor291
excellentpresentationsanddiscussionsduringtheweekinExeter.Finally,theauthors292
would like to thank their respective funding bodies: A.J. was supported by an FSBI293
conference registration bursary, N.J. is supported by an FSBI studentship, J.D.T is294
supported by NERC and Cefas, K.L.L. is supported by the Deutsche295
Forschungsgemeinschaft(LA3778/1-1),andD.S.M.issupportedbyBBSRC.296
297
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