Fish and Fisheries. 2018;1–21. wileyonlinelibrary.com/journal/faf  | 1© 2018 John Wiley & Sons Ltd

Received:22September2017  |  Accepted:19February2018DOI:10.1111/faf.12279

O R I G I N A L A R T I C L E

Progress in designing and delivering effective fishing industry–science data collection in the UK

Stephen C Mangi1  | Sven Kupschus2 | Steven Mackinson3 | Dale Rodmell4  |  Alexandra Lee2 | Elizabeth Bourke4 | Tom Rossiter5 | Jim Masters6 |  Stuart Hetherington2 | Thomas Catchpole2 | David Righton2

1BaylysWharfFishQuay,CentreforEnvironment,Fisheries&AquacultureScience,Plymouth,UK2CentreforEnvironment,Fisheries&AquacultureScience,Lowestoft,UK3ScottishPelagicFishermen’sAssociation,Fraserburgh,UK4NationalFederationofFishermen’sOrganisations,York,UK5SuccorfishLtd,Hull,UK6FishingintotheFuture,UnitC041,BrixhamLaboratory,FreshwaterQuarry,Brixham,UK

CorrespondenceStephenMangi,BaylysWharfFishQuay,CentreforEnvironment,Fisheries&AquacultureScience(Cefas),Plymouth,UK.Email:Stephen.mangi@cefas.co.uk

Funding informationDepartmentofEnvironment,FoodandRuralAffairs(Defra);SeafishStrategicInvestmentFund(SIF);CelticSeasPartnership(CSP)

AbstractThisstudywasundertakentoaddresstheincreasingneedforastrategicapproachtoindustry–sciencedatacollectionsinthefaceofreducingresourcesandgrowingneedforevidenceinfisheriesmanagement.Theaimwastoevaluateprogressinthedevel-opmentofplansandprocedures that canbeemployed to collect, recordandusefishingindustryknowledgeanddataintheevidencebaseformanagingfisheries.Thiswasachievedbyreviewingindustry-leddatainitiativesalreadyundertakenorongo-ingwithintheUnitedKingdomtodocumenthowtheseprojectshave/areincorporat-ingfishingindustrydataintotheprocessofmanagementdecision-making;canvassingstakeholderopinionondatagapsandwhetherthesecouldbefilledbydatagatheredbycommercial fishingvessels;establishingwhat issuesmightpreventorstimulatecommercialfishingvessels incollectingdatawhentheyhavetheopportunity;anddescribingguidanceona step-by-stepprocess forgathering scientific informationsuchthatfishersareempoweredtocollecttherightdata,attherighttimesandintherightformatfortheirfishery.Givenrecentadvancesinthecollection,interpretationandapplicationoffisheries-dependentdata,wecompareprogressmadeintheUKtoother areas of the world. We conclude that there is considerable evidence of a paradigmshiftfromtheconventionalpracticeofscientistsaskingfisherstoprovidedata for scientific analyses towards full engagement of key stakeholders in datacollection.

K E Y W O R D S

collaborativeresearch,datacollectionprotocol,fisheriesmanagement,fisheries-dependentdata,incentives,stakeholderengagement

www.wileyonlinelibrary.com/journal/fafhttp://orcid.org/0000-0001-8233-2612http://orcid.org/0000-0002-0879-7822http://orcid.org/0000-0001-8643-3672mailto:Stephen.mangi@cefas.co.uk

2  |     MANGI et Al.

1  | INTRODUC TION

Thedemandfordataandknowledgeonmarineresourcestounder-pinmanagementdecisionsisincreasing.Theecosystemapproachtomanagement requiresknowledgeofhowmarineecosystems func-tionandbeingabletopredict,withsomereliability,theirproductivecapacityandtheconsequencesofmanagementactions(Greenstreet&Rogers,2006;Jennings,2005;Shermanetal.,2005).Thisneces-sitatesinformationon(i)themarineenvironmenttounderstanditsstateandthe impactsofvariouspressuressuchasclimatechange,fishing and anthropogenic inputs (Pikitch etal., 2004); (ii) marinebiodiversity to support development and implementation of marine planning andprotectionof vulnerableor sensitivemarinehabitatsand species (Pikitch etal., 2004; Sale etal., 2005; Sherman etal.,2005);and(iii) thesustainabilityoffisheriestostrengthentheevi-dencebaseandassessmentapproachesfortargetspecies,andtode-liverlegislationandpoliticalcommitmentssuchastheDataCollectionFramework (DCF) (Apitz, Elliott, Fountain, & Galloway, 2006; EC,2008;Frid,Paramor,&Scott,2006; Jennings,2005).Fisheriesarealso increasingly recognized as an integrated systemwith ecologi-cal,economic,socialandinstitutionalaspectsthatrequire interdis-ciplinaryapproachesandamoreparticipatorygovernancestructure(Stephensonetal.,2016).Further,thereisincreasinguncertaintyinresourcemanagement,resultingfromtheimpactofclimatechangeonmanymarine ecosystem components (Littell,McKenzie, Kerns,Cushman,&Shaw,2011;Payneetal.,2016).Thesechallengesandtheexpandingobjectivesforsustainabilityneedtobesupportedbydiverse types of information and methods to provide tactical and strategicdecisionsacrossmultiplespatialandtemporalscales.

The effectiveness of fisheriesmanagement,whether it is stockmanagementorthemanagementofactivitiesfornatureconservationpurposes,isdependentonthetimelyprovisionofdataandevidence.As aminimum, data and information are needed on the biologicalcharacteristics (suchasageand lengthdistributionsofthespecies),totalcatch(landingsplusdiscards),ecologicaldata(impactsonhabi-tat,localgrowthrates)aswellasinformationaboutfishingeffort,fish-ingefficiencyandfleetbehaviour.Currently,thereareconsiderablecapacityshortfallsindatacollectionandlargeknowledgegapsinourunderstandingofthemarineenvironmentthatarepreventingeffec-tivefisheriesmanagement(Dorneretal.,2015;Grahametal.,2011;Simmonds,Doring,Daniel,&Angot,2011).Forinstance,biologicalref-erence points have not been defined for several commercially import-antfin-andshellfish,suchasbrowncrab(Cancer pagurus,Cancridae)skatesandrays(superorder:Batoidea),preventingthedevelopmentof management plans (Large etal., 2013; Pilling etal., 2008; Tullyetal.,2006).Manydata-poor(ordata-limited)stocksaredeemedasa“highrisk”bythesupplychain,whosepurchasingandsourcingpol-iciesdonotallowthemtosourcefromsuchfisheries(MRAG,2010;Parkesetal.,2010).Nomatterhowsustainablesuchfisheriesmightbe,whiletheycontinuetolackevidencetheywillremainofflimitstomany suppliers and retailers. The paucity of information on seabed habitatsevenwithindesignatedmarine-protectedareas(MPA)issuchthat fishing grounds have been closed as a precautionarymeasure

(Agardyetal.,2003;Saleetal.,2005).Fromthepointofviewofthefishingindustry,theuseofprecautionarymanagementanddecisionson fishing opportunities/access have immediate consequences forfishingbusinesses’abilitytooperate(Kraan,Uhlmann,Steenbergen,VanHelmond,&VanHoof,2013;Pita,Fernández-Vidal,García-Galdo,&Muino,2016;Stephensonetal.,2016).

Whiletheneedforbetterdata,improvedstockassessmentsandreal-timefisheriesmanagement isgrowing, research institutesand

1 Introduction 2

2Lessonsfrompastinitiatives 3

2.1Literaturereview 3

2.2Keyattributesofindustry-leddatacollection

4

2.2.1 Drivers 4

2.2.2Datarequired,scaleandtimeline 5

2.2.3Fundingandresearchpartners 5

2.2.4 Role of fishers and incentives 5

2.2.5 Objectives met and why 8

2.2.6Impact,strengths,weaknesses,opportu-nities and threats

8

2.3 Summary of lessons learnt from past initiatives

8

2.3.1 Industry participation 8

2.3.2Trustandunderstanding 9

2.3.3 Incentives 9

2.3.4Leadership 9

2.3.5 Resources 9

2.3.6Feedback 10

3Matchingdataneedsandcapacitytocollectdata

10

3.1Stakeholderinterviews 10

3.2 Data collection and analysis 10

3.3 Data opportunities and need 12

3.4Concernsoffishers 12

3.5Concernsofdata/adviceusers 13

3.6Engagement 13

3.7Summaryofmatchingneedsandcapacitytocollect data

13

4 Data collection protocol 14

4.1Guidelinesforindustry-sciencedatacollection

14

4.2Applicationofthedatacollectionprotocol 15

5HowUKprogresscomparestoothercountries

17

6Conclusion 18

Acknowledgements 19

ORCHID 19

References 19

     |  3MANGI et Al.

state-fundedresearcheffortsaresufferingfromreducedfundsandcapacity. The fishing industry, however, offers a unique opportu-nity tohelp fisheriesandmarineenvironmentmonitoring require-ments.Case studieson fisheries-dependentdata (Hoare,Graham,&Schon,2011;Lordan,Cuaig,Graham,&Rihan,2011;Pennington&Helle,2011;Roman, Jacobson,&Cadrin,2011;Sampson,2011;Uhmann,Bierman,&vanHelmond,2011)showthatthefishingin-dustrycanplayacentralrole inaddressingdatagapsacrossmanyfisheries.ExperiencesfromtheUKinvolvingthefishingindustryinthecommissioningand implementationof fisheryscienceprojectsindicatethatfishershaveakeeninterestinhelpingprovidedatathatmayavertunnecessaryprecautionarymeasuresbeingimplemented(Armstrong,Payne,Deas,&Catchpole,2013).Indeed,whenthereisinsufficientevidence,theapplicationofprecautionarymanagementoften entails an opportunity cost in untapped resources (Mangi,Dolder, Catchpole, Rodmell, & de Rozarieux, 2015;Mangi, Smith,&Catchpole,2016;Stephensonetal.,2016;Stram&Ianelli,2015).Consequently,industry-leddatacollectionschemesareincreasinglybeingturnedtowardstosupplementexistingresearchprogrammesorprovideinformationwhereitisotherwiseabsent(Johnson,2007;Johnson&vanDensen,2007;Mackinson&Wilson,2014;Neis&Felt,2001;Reid&Hartley,2006).Theseschemesarebeingencour-aged towards regionally coordinatedprogrammesbasedon soundstatisticaldesignprinciplesbecausetheyneedtobecompatiblewithexistingdatacollection,especiallyiftheyaretobecombinedinsomeway.Whilethisisencouraging,thetransferofknowledgedoesnotalwaysseemtohappeneffectively(Rice,2005),andmoreeffortisrequiredtoensurefishers’knowledgeisintegratedwithknowledgefromscientificresearchandmonitoring.

With limited financial resources and evolving assessment/managementneeds (includingmanagementstrategyevaluation),delivering the evidence base for sustainable fisheries manage-mentrequiresfishers,scientistsandmanagerstoworktogetherin a collaborative way. Here, we define industry–science datacollection as the active participation and engagement of fish-ers indatacollection.Thisdefinitionthereforeexcludespassiveparticipation where scientists, for example, use fishers’ ves-sels asplatforms tocollectdata, suchas in theCefasObserverProgramme (Catchpole, Ribeiro-Santos, Mangi, Hedley, & Gray,2017; Catchpole etal., 2011; Enever, Revill, Caslake, & Grant,2010) and many gear-based selectivity trials (e.g. Anseeuw,Moreau, Vandemaele, & Vandendriessche, 2008; Catchpole,Revill, & Dunlin, 2006; Depestele, Polet, Van Craeynest, &Vandendriessche, 2008; Revill, Dunlin, & Holst, 2006). It isworth noting that the industry is engagedwith active fisheriesdata collection and research more than ever before. Dorner et al. (2015)notethatthereisaparadigmshiftfromtheconventionalpracticeofscientistsaskingfisherstoprovidedataforscientificanalyses towards full engagement of key stakeholders in datacollection. Recent efforts towards industry–science data collec-tionprogrammeshaveinvolvedtwoICESsymposiaonfisheries-dependent information in Rome, Italy, in 2014 (Dorner etal.,2015) and in Galway, Ireland, in 2010 (Graham etal., 2011). In

both conferences, assembled scientists, fishing industry repre-sentatives, policymakers and other stakeholders discussed howtomake best use of data and information collected directly byfishersandhowtomerge that informationefficientlywithdatafromothersources.Similarly,recentprojectsonscience–industrypartnershipssuchasbridgingthegapbetweenscienceandstake-holders (GAP1and2) (Holm,Hadjimichael, Linke,&Mackinson,2018; Mackinson & Wilson, 2014) and the Canadian FisheriesResearch Network (CFRN) (Thompson & Stephenson, 2016)havepromotedactiveengagementintheplanningandexecutionof industry–science research. In Europe, the emergence of theprinciples for Responsible Research and Innovation (RRI) pro-videscompellingreasonstoactively involverelevantstakehold-ersindevelopinganddeliveringfit-for-purposescienceresearchprojects.

Thismanuscriptaddressestheincreasingneedforasystematicapproachtoindustry-leddatacollectioninthefaceofreducingre-sourcesandgrowingdemandforevidenceinfisheriesmanagement.We explore how to design and deliver effective industry–sciencedatacollectionprogrammesby:

1. reviewing industry-led data initiatives already undertaken orongoingwithin theUK to document how these projects have/are incorporating fishing industry data into the process ofmanagement decision-making, with a view to assessing theirdegree of success and any barriers experienced;

2. canvassingstakeholderopinionondatagapsandwhetherthesecouldbefilledbydatagatheredbycommercialfishingvessels;

3. establishingwhat issuesmightpreventor stimulatecommercialfishingvesselsincollectingdatawhentheyhavetheopportunity;and

4. describingguidanceonastep-by-stepprocessforgatheringsci-entific information such that fishers are empowered to collect the right data, at the right times and in the right format for theirfishery.

5. Givenrecentadvancesinthecollection,interpretationandappli-cationoffisheries-dependentdata,wecompareprogressmadeintheUKtootherareasoftheworld.

2  | LESSONS FROM PA ST INITIATIVES

2.1 | Literature review

Aliteraturereviewwasconductedtodocumentindustry-leddatainitiativesalreadyundertakenorongoingwithintheUK.Throughe-mails,fisheriesscientistsworkinginclosepartnershipwithfish-ers in the UKwere asked to provide details of recent fisheries-dependent data collection projects they have been involved in. Eachrecipientwasaskedtoprovidethenameoftheproject,statewhether it was undertaken in close partnership with fishers orcompletely independently by fishers and provide a report or other outputs from the project. Thewebsites of various organizations(e.g. Cefas www.cefas.co.uk, Marine Scotland Science www.gov.

http://www.cefas.co.ukhttp://www.gov.scot/Topics/marine/science

4  |     MANGI et Al.

scot/Topics/marine/science) were also searched to identify pro-jects inwhichcollaborativescience involvingthefishing industryhasbeenundertaken.

A list of the projects/initiatives including the name of theProjectLeadwascompiledthroughtheinformationgathered.Eachprojectonthelistwasreviewedbasedonitssuitability,relevanceandavailabilityofevidencetoelucidate thekeycomponentsofasuccessfulindustrydatacollectionprocessbutalsohighlightpitfallsthatneedtobeavoided.Tosupportthereviewprocess,amatrixofkeyattributescommontomostinitiativeswascreatedandusedtoanalysetheprojects (Table1).Where informationforanattributewasmissingfromthereport,telephoneandface-to-faceinterviewswereconductedwiththeProjectLeadtogathertheinformation.

Aqualitativeassessmentof theevidencewasmade fromeachproject,andthefindingsusedtopopulateadatatable.Eachoftheattributes was analysed to identify features that best contribute to asuccessfulinitiative.Furthermore,wesoughttocondensethe19attributesintoasmallerandsimplersetofkeycharacteristicsthatcould be more easily understood and communicated.

2.2 | Key attributes of industry- led data collection

In total, 20 projects from Shetland in the north to the EnglishChannelinthesouthwereidentifiedforanalysis.Threeofthesehadmissingdocumentsornopersontocontactandwerethereforenotreviewed.Theremaining17wereanalysed,andkeyinformationforeachattributeextractedandenteredontoamatrix(Table2).Thesecanbesummarizedintothefollowingattributes.

2.2.1 | Drivers

Thedriversofindustry-leddatacollectioninitiativesareexogenous,andcanbe largelybrokendowntospatial, scientificandchangingmanagementcontexts.Spatialdriversmainlycomefromthegrowingcompetition for the marine space with other uses such as offshore windfarmdevelopmentsandmarine-protectedareas(MPA).Forex-ample,theHoldernessFishingIndustryGroup(HFIG)datacollectionscheme is associatedwith theWesternmostRoughoffshorewindfarmownedbyDongEnergy(https://plus.google.com/+HfigOrgUk).Similarly, the Lyme Bay fully documented fishery project was inresponsetotheLymeBayclosedarea(Woo,Rossiter,&Woolmer,2013).Inthisregard,fishershavenotonlyusedthedatacollectionprocesstoevidenceandjustifytheiractivities(onethattheyhopewill showwhere they fish and protect their right to fish in thoseareas), but also to assess the scale and impactofMPAs.Similarly,alackofdatasupportingsciencehasalsoplayedanimportantpartinmotivating fishers to take part in several projects, for exampleSESAMI—self-sampling in the inshore sector (Mangi etal., 2016).Economic drivers, including the categorization of sharks, skatesand rays as data-limited stocks resulting in quota restrictions andfishing opportunities, have led skippers to engage in data collec-tion schemes, for example, in Shark By-WatchUK (Hetherington,Nicholson,&O’Brien,2016).Changingmanagementcontextssuch

as the Landing Obligation (a new rule under Europe’s CommonFisheriesPolicy(CFP)inwhichallcatchesofregulatedfisheriesaretobelandedandcountedagainstquotasofeachMemberState),re-quiringfulldocumentationofcatch,hasledfisherstotesttheeffi-cacyofremoteelectronicmonitoring(REM)devices(CCTV)asatooltomonitorcatchanddiscards(MMO,2013;Roberts,Course,Pasco,&Sandeman,2015;https://www.ssmo.co.uk/).

Mostoftheprojectsreviewedheresoughttoaddressscienceandpolicy,andrecognizedanintrinsiclink.Sciencetendstobelongtermandrequiresthecollectionofdatayearafteryear,andisthusslowto change. Policymay offermore immediate result (particularly ifassociatedwithregulatorychange)butneedspatienceandevidencewhichmustbebasedonscientificinformation.Fishershavedirectlycollected data for scientists,management authorities (e.g.Marine

TABLE  1 Keyattributesthatformedthebasisofdataextractionfrompast/ongoingindustry-ledthedatatheinitiativeneededtocollect

Attribute Details sought

Drivers The reasons behind the inception of the initiative

Objectives Whattheinitiativesoughttodo?

Datarequired Data the initiative needed to collect to meet the objectives

Scale Howbigorsmallwastheinitiative?

Timelines Whendidtheinitiativetakeplace?

Funding Whopaidfortheinitiative?

Partners Whoworkedwiththefisherstodelivertheinitiative?

Role of fishers What data were the fishers requiredtocollect?

Industry incentives Whatincentivesweregiventothefishers?

Resources employed Whatresources(peopleandequipment)weresuppliedtothefishers?

Data collection methods What methods did the fishers usetocollectthedata?

Data customer Whowasthedatacollectedfor?

Objectivesmet-Why? Were the objectives met and what were the main reasons for this?

Addressscience/Policy Was the data aimed at address-ingscienceorpolicyneeds?

Impact What,ifany,impactdidtheinitiativehave?

Strength Keystrengthsoftheinitiative

Weaknesses Keyweaknessesoftheinitiative

Opportunity What opportunities were identified to build upon the initiative?

Threats What issues were identified that wouldpreventfuturesuccess?

http://www.gov.scot/Topics/marine/sciencehttps://plus.google.com/+HfigOrgUkhttps://www.ssmo.co.uk/

     |  5MANGI et Al.

ManagementOrganisation (MMO), inshoreFisheriesConservationAgencies (IFCAs), Department of Food, Environment and RuralAffairs (Defra)), Science Technical and Economic Committee onFisheries (STECF), representative bodies such as the NationalFederation of Fishermen’s Organisations (NFFO) or local fishingassociations and commercial businesses within the supply chain. Society toowas found tobe a customer—in the formof data andinformationfortraceabilityorprovenance,ortoaidunderstandingofthemarineenvironmentandimprovethepublicimageoffisheries.

2.2.2 | Data required, scale and timeline

Data requirement as an attribute varies among the projects re-viewed here but is wholly dependent on the objectives of the pro-ject. Inaddition, theavailable technologyusedhasa considerableinfluenceonthedatacollected.Inmostprojects,thedatarequiredare usually set by the cooperating scientists. However, in somecasesthefishersprovidethelead,forexampleHoldernessFishingIndustryGroup(HFIG)ongoingwork.Mostoftheinitiativesinves-tigatedcanbebestdescribedaspilotprojects,orspecifictargetedprojectswithinawiderprogramme.Themostsuccessfulinitiativeswerefoundtobethesmallandlocal,wheretheparticipantsfeltacommonalitywiththeotherparticipants.Duetofundinglimitations,most of the projectswere short, usually lasting one or two yearsat themost.Furthermore,earlier initiativeswereoftenpioneeringbutshortterm;theirsuccesswaslimitedasaresult.Afewlonger-term initiativeshavebegun tobuild timeseriesandhave incorpo-rated the lessons learned frompast experiences, for example theShetland Shellfish Management Organisation review of progress(https://www.ssmo.co.uk/),theFisheriesSciencePartnership(FSP),whichalbeit focusedon short-term individualprojectshasa long-term approach (https://www.gov.uk/government/organisations/centre-for-environment-fisheries-and-aquaculture-science/about/research#fisheries-science-partnership-fsp),andtheFishingintotheFuture (http://www.fishingintothefuture.co.uk/) initiative,which islayingfoundationforalong-termstrategicapproach.

Aspectrumofdatacollectionmethodsisevidentinalltheproj-ects.Broadly,theyfall intotwocategories:activeandpassivepar-ticipation.Activeparticipationinvolvesfishersalteringtheirnormalactivity to collect thedata.Examples include sampling, surveying,measurement(sexing,ageing),tagging,survivalrates,identificationofspawningandnurseryareas.Passivedatacollectionutilizesthefishing operation as an opportunity to collect valuable data andcauses no real inconvenience to the fishers themselves but does re-quiretheirpermissionandcooperation.Passivecollectionnormallyinvolvedthecarryingofanobserverorthedeploymentoftechnol-ogysuchasCCTV,inshorevesselmonitoringsystem(iVMS),VMS,e-logs,appsorremotesensors.

2.2.3 | Funding and research partners

Publicfundinginoneformoranotherhasbeenimportantinsupport-ingmostof the initiatives (15of17). Findings show that initiatives

with longer timelines tend to have private income at their founda-tionstageandpublicfundingisaddedonaprojectbyprojectbasis.Overall,theindustry-leddatacollectioninitiativesreviewedherehavebeendeliveredthroughpartnershipsofoneformoranother.Scientistsarethemostfrequentresearchpartners,providingadviceandguid-ancetoensurescientificrigour.Otherpartnersincluderelevantgov-ernment agencies, environmental NGOs and private enterprise. Ingeneral,projectpartnershavebeen important inbuildingcredibilityandensuringbuy-intotheresults.Thereappearstobeaneedforamixofpartners,ideallyfishers,scientistsandsomeformofmanage-ment.Aconsiderableamountofresourceisevidentinalltheprojectsinvestigated.Byfar,themostimportantprofessionalresourcefoundwasscientificsupportintheformofprojectdesign,observers,train-ingandanalysis.Tangibleresourcessuchasequipment,premisesandmoneyarealsocommonlyused.Theexactresourcesdeployedvaryfrom project to project and are usually dictated by the objectives and theprojectbudget.

2.2.4 | Role of fishers and incentives

The main objective that fishers who collected data had in common was one of self- preservation or betterment. They see data collec-tionnotastheirprimarypurpose,butasanecessaryadjunct.Forinstance, in theNationalEvaluationofPopulationsofThreatenedand Uncertain Elasmobranchs (NEPTUNE) shark, skate and rayscientificbycatchfishery,fisherscollecteddatatoincreaseunder-standingofporbeagle(Lamna nasus,Lamnidae),spurdog(dogfishes,Squalidae)andcommonskate(Dipturus batis,Rajidae)distributionsinCelticSea fisheries (ICESVIIe-j),whiledemonstrating the levelofbycatchandon-deckvitalityofthesezeroTAC(totalallowablecatch)andprohibitedspecies. Inthecaseofspurdog,themotiva-tionforparticipationbyfisherswasthemoralprincipleofreducingspurdogbycatchandsubsequentdeaddiscards.Asecondmotiva-tionwastoexploretheeconomicopportunitytolandwhatwasal-readydead (Ellis,Bendall,Hetherington,Silva,&McCullyPhillips,2015;Hunteretal.,2016).

Fishersinalltheselectedprojectsplayedanimportantroleines-tablishingtheinitiative.Theycontributedtothedesignoftheprojectandtheexecution,oftencarryingobservers,participatedintrainingtotakemeasurements,engagedintaggingwork,andagreedtopro-videelectroniclog(e-log)data,orcarryREMdevices.Inallcases,thecostsofthedatacollectionweresubsidizedtosomeextent,varyingfromprovisionofthedatacollectiondevicethroughtoapaymentbeingmade tocompensate for time lost incollectingdata.For in-stance,participantsinthecatchquotatrialsreceivedextraquotatooffset thecostofbehaviouralchange toavoiddiscards thatcouldleadtoreducedmarketablecatches.Thevalueofthedatacollectedwas noted as an important incentive to the fishers. The rationale be-hindtheincentivebeingtominimizethechanceofchokespecies(i.e.species that are incidentally caught at a greater quota proportionthanthetargetspecies)forcingfisherstoalterbehaviourorforegofuturefishingopportunitiesascatchesfromthesestudiescountedtowardsthequota.

https://www.ssmo.co.uk/https://www.gov.uk/government/organisations/centre-for-environment-fisheries-and-aquaculture-science/about/research#fisheries-science-partnership-fsphttps://www.gov.uk/government/organisations/centre-for-environment-fisheries-and-aquaculture-science/about/research#fisheries-science-partnership-fsphttps://www.gov.uk/government/organisations/centre-for-environment-fisheries-and-aquaculture-science/about/research#fisheries-science-partnership-fsphttp://www.fishingintothefuture.co.uk/

6  |     MANGI et Al.

TABLE  2 Summaryoftheprojects/initiativesreviewedandassessmentofhowtheyaddressedthekeyattributesofindustry-led data collection

Project Objectives Driver Date, scale and data required Source of funding and research partners Role of fishers Industry incentivesObjectives met and why? Impact

Link to management and decision- making Reference

1 BlueMarineLymeBayfully documented fishery

To assess the scale and impact of the fishery to support a voluntarymanagementagreementandlocalfisherymanagers

Voluntaryagreement,marketaccess,localmanagement

2013—ongoing;fullscaleiVMS/pilot collection of catchandeffort(44vessels)

£80kfromEFF&BlueMarineFoundation; MMO,IFCA,Plymouth University,Succorfish

Signvoluntaryagreement/fitVMS,recordcatchandeffortdata

Improved port facilities/access to their data/accesstomarket(20%premium)/freeequipment

Yes—developedandtested a data collection template for inshore fishers

Medium–data collection is ongoingpostprojectanddatausedbyIFCAs

Provisionofcatchdataandlocation. Mechanism for complianceandmonitoringfishingaroundsensitivereef areas

Wooetal.(2013)

2 Welshwhelkfisherystudy Real- time spatial catch and effort data collection to advise consultation and calculateCPUE

Implementingamanagementplan

2016—ongoing;pilotpriortorollout(fivevessels);iVMS,catch and effort

£10Kfromcentralgovernment;Welsh FishermenAssociation,Welsh Government,Succorfish

FitiVMS/recordcatchandeffortdatabystring.Provideadailylandedweight

High-qualitydatafeedinginto policy/free equipment/build-uptrackrecord

Yes—collectedandanalysed high-resolutionCPUE

High—DatahavefedintoWhelkconsultationandsystems to be introduced to nationally

Provisionofdatatowardsconsultation on sustainable managementmeasuresfortheWelshwhelkfishery

Rossiter(2016)

3 SESAMI–Self-samplinginthe inshore sector

Totestcapability,willingnessand practicalities of data collectionbyskippers

Need for more and better (under10m)datathatfishers can trust to provide evidenceontheirfishingpractices

2012–2014,SEandSWofEngland(30u10vessels);catch,effort,geartype,fishinglocation,discards

£200kfromDefraandEFF;Cefas,

     |  7MANGI et Al.

TABLE  2 Summaryoftheprojects/initiativesreviewedandassessmentofhowtheyaddressedthekeyattributesofindustry-led data collection

Project Objectives Driver Date, scale and data required Source of funding and research partners Role of fishers Industry incentivesObjectives met and why? Impact

Link to management and decision- making Reference

1 BlueMarineLymeBayfully documented fishery

To assess the scale and impact of the fishery to support a voluntarymanagementagreementandlocalfisherymanagers

Voluntaryagreement,marketaccess,localmanagement

2013—ongoing;fullscaleiVMS/pilot collection of catchandeffort(44vessels)

£80kfromEFF&BlueMarineFoundation; MMO,IFCA,Plymouth University,Succorfish

Signvoluntaryagreement/fitVMS,recordcatchandeffortdata

Improved port facilities/access to their data/accesstomarket(20%premium)/freeequipment

Yes—developedandtested a data collection template for inshore fishers

Medium–data collection is ongoingpostprojectanddatausedbyIFCAs

Provisionofcatchdataandlocation. Mechanism for complianceandmonitoringfishingaroundsensitivereef areas

Wooetal.(2013)

2 Welshwhelkfisherystudy Real- time spatial catch and effort data collection to advise consultation and calculateCPUE

Implementingamanagementplan

2016—ongoing;pilotpriortorollout(fivevessels);iVMS,catch and effort

£10Kfromcentralgovernment;Welsh FishermenAssociation,Welsh Government,Succorfish

FitiVMS/recordcatchandeffortdatabystring.Provideadailylandedweight

High-qualitydatafeedinginto policy/free equipment/build-uptrackrecord

Yes—collectedandanalysed high-resolutionCPUE

High—DatahavefedintoWhelkconsultationandsystems to be introduced to nationally

Provisionofdatatowardsconsultation on sustainable managementmeasuresfortheWelshwhelkfishery

Rossiter(2016)

3 SESAMI–Self-samplinginthe inshore sector

Totestcapability,willingnessand practicalities of data collectionbyskippers

Need for more and better (under10m)datathatfishers can trust to provide evidenceontheirfishingpractices

2012–2014,SEandSWofEngland(30u10vessels);catch,effort,geartype,fishinglocation,discards

£200kfromDefraandEFF;Cefas,

8  |     MANGI et Al.

2.2.5 | Objectives met and why

These varied on a case- by- case basis. Some of the consistent rea-sons for (i) success include objectives were clear and achieved,fisherswere involved from the beginning, therewas clear leader-shipandongoingsupport,short-termbenefitswereidentifiableandgoodcommunicationstomanageexpectations.ii)failureincludeob-jectiveswerenotmetbecausetherewaslackofconsultationwithfishers,objectiveswerepoorlydefinedandtoolargescale, lackofperceivedbenefits(nofeedback),lackofleadershipandsupport,toomanydiverseinterestsinvolvedandfishers“fatigue”.

2.2.6 | Impact, strengths, weaknesses, opportunities and threats

Ingeneral,thetechnicalimpactofthedatacollectedhasbeenrela-tively low. However, much has depended on how the objectivesweredefined.Forinstance,intheConservationCreditsinitiativetheimpactoncod (Gadus morhua,Gadidae)mortalitywas lowbut theprojectbenefitedsomefishersthroughtheextradaysatsea.Duetotheinnovativeandinvestigativenatureofmanyoftheprojects,theyoftenmeettheobjectives.Thestrengthsthereforevarygreatlyfromproject toproject, but in caseswhen there isbuy-in from fishers,costswere low,andbenefitswerehigh.Strong leadership (prefer-ablyfrombothfishersandscientists)isalsoakeystrengthissomeoftheprojects,whileafeelingofcommonownershipandgoalsamongfishersandgoodcommunicationsarepositivefeaturesofothers.

Theweaknessesalsovarygreatly,butthemostsignificantonesrelatetoatop-downapproach;noperceivedbenefitseitherduringor after the project; too many interests involved; no leadership or resource to maintain momentum; and poor communication with the fishersonanongoingbasis.Themostcommonopportunitiesiden-tifiedincludethepossibilityofcreatingatimeseriesoncebaselineshavebeenestablished.Securingsuchopportunitiesinsomecases,

however,washamperedbyparticipant“fatigue”andfundingissues.The possibility of developing communications to increase widerbuy- in to the idea of industry collection of data was also identified asakeyopportunity.Inthefaceofreducingpublicfundingfordatacollection, it is important that alternativeways tocollectdataarepursuedandpromoted.Equallysomeoftheprojectsidentifiedtheopportunityoftechnologytoautomatethedatacollectionprocessandreducetheburdenonthefishers,usingthemasvesselsofop-portunity rather than research laboratories. One threat identified as substantialwas trust—where fishers feared that their datawill beusedagainstthem.Thereisaperceptionthatthishashappenedinthe past.

2.3 | Summary of lessons learnt from past initiatives

The literature review on the most important attributes of an industry- leddatacollectioninitiativewasusedtoidentifythe“musthave”or“mustavoid”pointsfromacrossalltheinitiativesinvestigated.Thesewerekeptatabroadleveltomakeiteasiertocommunicate.Thefol-lowingaspectsareconsideredfundamentalingredientsofsuccess-ful industry- led data collection initiatives as distilled by the authors. Manyofthesearesimilartothegoodpracticemessagesproducedby the GAP (bridging the gap between science and stakeholders)project(Mackinson,Neville,Raicevich,&Clausen,2008;Mackinson,Raicevich,Kraan,Magudia,&Borrow,2015).

2.3.1 | Industry participation

Itmay seemobvious,buton-the-groundsupportmustbepresentforaninitiativetosucceed.Thecoreideashouldoriginatewithinthefishingcommunityandnormallyinresponsetosomeissueorchal-lenge.Ideally,theindustrygroupshouldleadoratleastsharethepro-jectleadthroughout.Aninterestingobservationwasthatthemostsuccessfulprojectshaveastrongsharedinterestor“glue”withinthe

Project Objectives Driver Date, scale and data required Source of funding and research partners Role of fishers Industry incentivesObjectives met and why? Impact

Link to management and decision- making Reference

14 Fishface Totestthefeasibilityofusingrecreational waterproof camerastocollectfootageofcommercialfishingactivityon inshore vessels for the purposeofmonitoring

Alackofreliabledatasupportingstockassessment and management

2013–14;

     |  9MANGI et Al.

industrygroupwellbeforetheinitiativebegins.Consequently,thisexplainswhysmall-scale local initiatives tend tobemoresuccess-fulthanlargerprojects.Thepre-existingsharedinterestenablesthegrouptostayfocusedinthefaceofinevitablechallengesandissues.The smaller scale may also ensure that the share of responsibility andeffortisverifiablyequalwhichtendstoenforcethegroupvalueof the project.

2.3.2 | Trust and understanding

Animportantattributefoundconsistentlyamongthesuccessfulpro-jectswashavingasharedgoalthatwasbotheasytorecallandexplainand ultimately communicate. It was observed and commented that if thegoalsarecomplicatedorunclear,theinitiativewillfailasallthepartieswillbeaimingfordifferentoutcomes.Aswellasunderminingtheaimsoftheinitiative,thereislessacceptanceoftheresultsunderthesecircumstances,asparticipants feelbetrayedandtrust is lost.Trustisalltoooftenhardwonandeasilylost.Aswithmostprojectsrequiringavoluntarycontribution,thereisaperiodofsellingtheidea.This canbe reduced/facilitatedbydemonstratinghowprojectpar-ticipantswillworktogethereffectivelyandrespectfully.Itiscriticalthatduring thisprocess,expectationsaremanaged,andunrealisticpromises are avoided. Furthermore, it is extremely important thattheprojectteamdoexactlywhattheysaytheywill.Minorinstancessuchasnotreturningacallinatimelymannerorforgettingtoshareadocumentcanbecomeacatalystfortheunravellingofaproject.

2.3.3 | Incentives

Investigating and presenting the incentives for collaboration is animportantstepforallsuccessfulprojectstoundergo.Theincentivesshould be clear for all parties and not just fishers. They must also be realisticanddeliverable.Theincentivestocooperatecantakemanyforms.Forinstance,intheSESAMIprojectadailyratewaspaidto

skippers for recording data from their fishing operations (Mangietal.,2016).Itisworthnotingthateconomicincentivesdonothavetobemonetary. Several of the initiatives actively sought to avoidsuchmonetary incentives as it may promote short-term thinking,whilethegoalsareoftenlongterm.Manyfoundthatthiscreatedaconflictamongfishersandscientists,andhadtheeffectoferodingtrust,while indirecteconomicbenefitssuchasprovisionofequip-mentoranupliftinquotaweredeemedtobemoreappropriateandconsistentwiththeaimsofindustry-leddatacollection.Tothisend,the majority of the initiatives studied report that the assurance of betterdataandevidencebeingincorporatedintoscienceandman-agementisthesinglemostimportantincentivetoparticipants.

2.3.4 | Leadership

There aremany facets of leadership, but in terms of industry-leddatacollectioninitiatives,themostimportantwashavingthedrivetomakethingshappen.Thisroleisdifficultforaworkingfishertofulfilandrequiresapersonwithstrongadministrativeskills.Itmaybefeasibleforaprojecttobefrontloadedwithsupportandtraining.However,experiencehasshownthatthereisneedforalocalactiva-torthroughoutthelifetimeoftheinitiative.Smalltechnicalissuesorpointsneedtobeaddressedquickly,andwithoutthe interventionof a local trusted actor the responsibility falls upon the fishers to contactoftenunknownindividualswhoareunavailablewhenfish-ers have the time and inclination to pursue the issue. Experiencefrompastandongoingprojectshasshownthatthispersoncanalsofulfiltheroleofcommunicatorandassistinmaintainingmotivationamongfishers,whileprovidinganynecessarysupport.

2.3.5 | Resources

The move towards increased industry- led data collection is partly drivenbythereduction in fundingandpersonnel resources in the

Project Objectives Driver Date, scale and data required Source of funding and research partners Role of fishers Industry incentivesObjectives met and why? Impact

Link to management and decision- making Reference

14 Fishface Totestthefeasibilityofusingrecreational waterproof camerastocollectfootageofcommercialfishingactivityon inshore vessels for the purposeofmonitoring

Alackofreliabledatasupportingstockassessment and management

2013–14;

10  |     MANGI et Al.

faceofagrowingrequirementtoproviderobustevidencetosupportappropriatemanagement andmarket requirements.Here, there isusuallyanexpectationofasignificantreturnoninvestment,butforsmallfisheries,thismaybedifficulttofind.Fisherscollectingdatawillcertainlyimprovetheefficiencyoftheprocessanddataquality.However,resourcesarerequiredintrainingandvalidatingthedatasothatitsqualityisknown.Consequently,industry-leddatacollec-tion should not be seen as free science as this could underestimate thetruecostandthevalueaddedbythefishers.Onthecontrary,industry- led data collection projects must therefore be properly re-sourced if they are to deliver the benefits they set out.

2.3.6 | Feedback

A common perception of fishers following engagementwith datacollectionisthattheprocessis“downtothem,”andafterwards,theyareleft inthedarkastotheoutcomeandvalueoftheirparticipa-tion. Most successful initiatives have invested considerable time and money into the feedbackprocess, ensuring that fishersget some-thingoutofitandthatthereisanappreciationoftheircontribution.Fishersneedtohearandseethatsomethingishappeningwiththeirdata.There isan innatesuspicionthatnothingwillchange,butbydemonstratingthattheirdatameanssomething,itgivesfishershopeandmotivationtoundertakeandsustaintheirefforts.

3  | MATCHING DATA NEEDS AND C APACIT Y TO COLLEC T THE DATA

3.1 | Stakeholder interviews

Thetransitiontowardsecosystem-basedmanagementnecessitatesa broader perspective of sustainability, requiring approaches formanagingthroughecosystemchangeandstrategies formitigatingsocietal impacts—inparticularforthosewhoselivelihoodsdependon the sea. These needs demand engagement and collaborationbetweensectorsandacrossborders(Apitz,Carlon,Oen,&White,2007;Borja,2005;Ducrotoy&Elliott,1997;Elliott,Fernandes,&de Jonge, 1999; Read, Elliott, & Fernandes, 2001). For instance,in fisheriesmanagement,mostpeopleagree that thereareweak-nessesinICESstockassessmentsthatcouldbesolvedwithmoreorbetterdata(Apitzetal.,2006),andthatthefleetoffishingvesselsat seapresentsanopportunity tocollectadditionaldata (Grahametal., 2011;Mangi etal., 2015, 2016).However, realizing the po-tentialtojoinup“need”and“capacity”issomethingthatisdifficulttoachieve.As the literature reviewhasdemonstrated, the fishingindustry has been collaborating with scientists and regulators inprojects to collect fisheries and environmental data with some suc-cess.Theseprojects,whileproducingusefulinformationanddem-onstratingthatthefishingindustrycanaddvaluetoresearchsurveywork,oftenhavehadashortlifeandrarelyhavebeenadoptedasa routine model. These issues and related constraints need to be addressed to ensure that industry–science projects can collaborate andshareknowledge.

Toidentifyopportunitieswheremarinemonitoringneedandop-portunitycanbematched,astakeholdersurveywasconducted.Theobjectivewas to identify themostuseful data and the challengesthefishingindustryfacewhencontributingtothestockassessmentprocess. Through contacting UK marine monitoring authorities(MMA), environmental non-governmental organizations (eNGOs),fish processors and retailers, and fisherswe aimed to: (i) identifygapsinmonitoringdataforassessmentneeds;(ii)canvassopiniononwhetherthesedatagapscouldbefilledbyfisheries-dependentdata;(iii)identifycapacityorexpertisewithinthefishingindustrytocol-lectdata;and(iv)describedifficultiesofdatausersinincorporatingtheinformationinassessmentsandcharacterizethepotentialpitfallfacedbytheindustryincollectingsuchinformation.

3.2 | Data collection and analysis

AtechnicalassessmentquestionnairewasdevelopedandpublishedthroughtheSurveyMonkey (www.surveymonkey.com)onlinepor-tal.Participantswereonlyshownquestionsrelatingtotheirspecificactivity in themonitoring and assessmentprocess to ensure rele-vanceandtominimizethetimeneededtocompletethesurvey.Abranchedsurveydesignwasusedwithquestionsbeingdependentonprevious answers (Figure1). Thequestionnaire asked respond-entstostatethefocusareaoftheircurrentemployment,classify-ingthemselvesasinterestedinfisheriesdata/assessments,ecologyand biodiversity data/assessments, hydrographic and water qual-ity data/assessments, or other environmental data/assessments.Fisherswereaskedwhatdatatypestheycouldsupplyinformationonwhiledatausers(MMA,eNGOandfishprocessors)wereaskedwhat data they would be interested in obtaining with assistancefromthefishingindustry.

Thesurveywascirculatedtoalistof42“targeted”stakeholdersidentifiedbytheCelticSeasPartnership(CSPwww.celticseaspart-nership.eu/)viaaURLlinkcopiedintoane-mailinvitation.Targetedstakeholders included fishing industry representatives, environ-mental NGOs, individual experts, statutory nature conservationbodies, fisheries managers (MMO, Defra) and scientists. Thesewere identified througha seriesof stakeholderworkshopsundertheCelticSeaPartnershipproject.Becauseofthelimitednumberofinvitedparticipantsandtheuncertaintyregardingthelikelynum-beroftargetedresponses,thesamesurveywasalsomadeavailabletoanyoneinterestedinresponding.Potential“general”participantsweremadeawareofthepublicsurveythrough(i)requesting“tar-geted”respondentstoforwardthesurveylinktoothersthattheyfeltmightbeinterested;(ii)circulatingthelinktotheCSPsFishingforData (F4D)Group (The fishing4datagroup isacollaborationbetween fishing industry, eNGOs, retailers and scientists whoseoverarching goal is to see data gaps preventing effective fisheryandconservationmanagementaddressed);and (iii) throughpubli-cizingthesurveylinkviaablogontheCefaswebsite(www.cefas.co.uk),whichexplainedthepurposeoftheresearchandincludedalink to thegeneral survey.TheCefas twitteraccountperiodicallyadvertisedtheblog.

http://www.surveymonkey.comhttp://www.celticseaspartnership.eu/http://www.celticseaspartnership.eu/http://www.cefas.co.ukhttp://www.cefas.co.uk

     |  11MANGI et Al.

Composition of respondents was monitored throughout, ande-mailsweresenttoencouragespecificcategoriesofrespondentstoparticipatetobalancethecoverageacrosspotentialdataprovidersandvariousdatausers.TwoseparateURLsurveylinkswerecircu-lated,onetotargetedstakeholdersandanothertothegeneralre-spondents.Thelinksledtothesamesurvey,butthedatageneratedwerestoredseparatelyallowingforthegroupstobeanalysedsepa-rately.ThesurveywasconductedduringNovemberandDecember2016. Respondents were contacted by phone or e-mail where de-tailswereprovidediftheiranswersrequiredclarificationorfurtherdetail was needed to aid the interpretation.

Overall49individualsrespondedtotheonlinesurveymadeupof16fromthetargetgroupand33fromthegeneralgroup(Table3).Atotalof23fishers/vesselownersresponded,sixrespondentswerefromeNGOs,19werefrommarinemonitoringauthorities,andonlyone fish processor or retailer completed the survey. Fisherswerewellrepresentedinboththetargetedandgeneralgroup,makingup35% and 53% of respondents, respectively. Monitoring authorityrespondentscomprised46%of thegeneralgroupand25%of thetargetedgroup.FiveofthesixeNGOrespondentswerepartofthetargetedgroup.Thefishprocessorwhorespondedwaspartofthetargetedgroup.

F IGURE  1 Schematic of the branched onlinesurveyidentifyingthequestionsthe respondent had to answer to which determinedthepaththroughthesurvey

About therespondent

Fisher’s page(Data provision)

Monitoringauthority andeNGO(Data needs)

Fish processoror retailer(Data needs)

Fisher’s concerns

Data interests

Ecosystemassessment

Data concerns

Engagement

TABLE  3 Compositionoftargetandgeneralgroupdividedbyemployerandtopicfocusasinferencedbyrespondent’semploymentdetails

Employment focus Target respondent % of target General respondent % of general Total

Fishprocessororretailer 1 6% 1

Fisheriesdataorassessments

1 6% 1

Fisher/vesselowner 6 35% 17 53% 23

Fisheriesdataorassessments

5 29% 16 50% 21

Hydrographicandwaterqualitydataorassessments

1 5% 1 3% 2

Marinemonitoringauthority 4 24% 15 47% 19

Fisheriesdataorassessments

4 24% 10 31% 14

Hazardoussubstances 1 3% 1

Hydrographicandwaterqualitydataorassessments

3 9% 3

Impactoffishingonconservation features

1 3% 1

Non-Governmentalorganization

5 29% 1 3% 6

Ecologyandbiodiversitydataor assessments

2 11% 1 3% 3

Fisheriesdataorassessments

2 11% 2

Hydrographicandwaterqualitydataorassessments

1 6% 1

Total 16 33 49

12  |     MANGI et Al.

3.3 | Data opportunities and need

Results indicate that 77% of respondents focused on fisheries-relateddataor stock assessments. Theseweremainly fishers andfishprocessors.Mostmonitoringauthorityrespondents(74%)spe-cialized in fisheries data, but other specialities were represented,with 16% focussing on hydrographic andwater quality data. Twomonitoringauthorityrespondentsdidnotfocusonanyofthepro-videdoptionsandselectedthe“other”optiondescribingthemselvesasfocusingonhazardoussubstancesandimpactoffishingoncon-servationfeatures.ThefocusoftheeNGOrespondentswasbroaderwith40%focusingonfisheriesdata/assessments,40%onecologyand biodiversity data/assessments and 20% on hydrographic andwaterqualitydata/assessments.

Offersandrequestsforfisheriesinformationdominatedthedataneeds.Ofthe23fishers,17indicatedtheycouldprovidedataonfishstocks,16forfisheriesdata,11forbiodiversityfromfishingactivityand16foracousticinformationmakingup85%ofthedataoffers.The fishprocessor requestedonly information related to fisheriesdata,whereasMMAsandeNGOsshowedanincreasinginterestingeneralenvironmentalinformation,butstill

     |  13MANGI et Al.

necessarytoavoidtheerosionoftrustandtoensurethelongevityof what is a worthwhile and efficient means to improve our under-standingoffish,fisheriesandthemarineenvironment.

3.5 | Concerns of data/advice users

Concerns over using data directly collected by fishers are sur-prisingly similar across the different data sources and uses.Encouragingly,andincontrasttooptionalsurveycommentsmadebyfishers,governmentandeNGOsaregenerallypositiveaboutthedata.Only roughly 10%of respondents indicated that datawereinherently untrustworthy and therefore not suitable for assessment purposes.Roughly30%responsessuggestthatthedatacouldbeusedwith feworminorchanges to theassessmentmethodology,implying that there should be some quick wins. Responses sug-gest,formostassessments,around40%oftheconcernscouldbeovercomewithsomeinvestmentfromthefishingindustry,suchasqualityofdata,reliabilityoflong-termavailabilityandmethodologi-calprotocol.Theremaining20to30%ofresponsesindicatedthatthe information from fishers is likely to have spatial, temporal ortechnical biases. These problems are specific to the intended use ofthedataandwouldrequireadditionalworkbystockassessmentscientists in conjunction with the industry to ensure that the biases in the new data sources can be appropriately accounted for in the assessment.

Overall,theresultsareverypositivewithmajorityoftheproblemsresolvable, though in most cases at additional cost. Depending ontheobjective, industry–sciencedatacollectionschemesare likelytorequirea long-termcommitmentandmorethoughtneedstobeputintohowsuchactivitiescanbefunded.Ascommentedinthesurvey,collectingdatathatisnotusedpresentsnobenefit.Atthesametime,itmustbeclearthatinstockassessments,inparticular,shorttimese-riestendtohavelittleeffectinchangingassessmentoutcomes,andinmanycases,theycannotbeuseduntilalongenoughtimeseriesexists.

3.6 | Engagement

Thirty-fourofthe49respondentsrepliedtothequestionregardingtheirwillingness to help developmeans to overcome issues thathinder theuseof fishingvesselsasplatforms fordatacollection,all but two of them positively. It is not clear why the other 15 re-spondentsdidnotwanttoanswerthequestion.Fourfishers,fourMMAandthreeeNGOemployeeswereunconditionallywillingtoparticipate. This demonstrates that there are both fishers and data usersinterestedinmakingindustry–sciencedatacollectionwork.Over half of the fishers and data users were interested in further efforts to resolve the issueshighlighted in this survey.Those re-spondingpositivelytothisquestionfromtheMMAgroupwereal-mostexclusively thosewitha focusonfisheries.Whenwillingtoworkonotherdatasources,participantsdidsoonlyinconjunctionwithfisheriesinformationindicatingthatforindustry-leddatacol-lections,themostlikelystartingpointwillbeworkingtogetheronfisheries issues.

3.7 | Summary of matching needs and capacity to collect data

TheCelticSeasPartnership (CSP) requesteda surveyof itsmem-bers to assess what steps they could take to develop a strategyfor industry-leddatacollection in thecontextof fisheriesanden-vironmentalmonitoring for theCeltic Seas ecoregion. The limitednumberofpotentialrespondents(targetedparticipants)withinthegroupmeantthatageneralizationoftheresponseswasdifficultpar-ticularly as theCSP sees the interaction between industry, scien-tistsandmanagementasoneofitsmajorambitionsthuspotentiallypredisposing theirmembership toviewsnot representativeof theview of the entire industry. The study therefore attempted to test thewiderutilityofthelessonslearnedbyalsocanvassingindustryparticipantsfromamoreindependentpoolandinitiallytreatingtheresponsesseparatelytoinvestigatewhetherthereweredifferencesintheviewsofthetwogroups.Responsesfrombothgroupswereentirelyvoluntaryandmadeupofsmallsamplesizeswithrelativelylittle power to detect differences among the groups.While theseshortcomingsarenotdesirable,theinformationgeneratedhashigh-lightedareasofopportunitywhere fishers could cooperate in thecollectionofdatatowardsacomprehensivemonitoringprogrammedesignedtoassesstheenvironmentalconditionoftheseas.Fishersindicated that they are capable andwilling to collect a variety ofmarineenvironmentalinformationidentifiedasaneedbymanage-mentauthoritiesandeNGOssuchasbiodiversityobservations(ma-rinemammalsandbirds),marine litter,waterquality (hydrographicinformation),andinformationdirectlyrelatedtothefisherysuchasfishstocks,biodiversityfromfishingactivitiesandfisheriesacous-tics.Giventhatavailableresourcesarealimitingfactortoimprovedassessmentsand theneed tomaximize the impactof industry-leddatacollectionprogrammes,wesuggestprioritizingeffort inareaswheretheassessmentfocusofgovernmentscientistsandthedataopportunities provided by fishers overlap. Data- limited species are attractingmoreattentionbecauseadviceisneededbutdifficulttodevelop (ICES,2017).Forexample,manyelasmobranchstocksaredata-limitedand legislativecollectionsarekerbeddue to the rela-tivelysmallproportionofthesespeciesinlandings(McCully,Scott,Ellis,&Pilling,2013;Simpfendorferetal.,2011).However,theyareconsideredecologicallyimportantandseveralspecieshaverestric-tivefishingopportunities,andsocouldeasilybecomechokespeciesasthelandingobligationisphasedin(Rochet,Catchpole,&Cadrin,2014).Betterdataarelikelytoleadtoimprovedconfidenceinstatusassessments,whichwouldmake the resultingmanagementmeas-ureseasiertocommunicatetostakeholders.

There isalsoafocusonwide-rangingspeciesespeciallywheretheirdistributionhaschangedfromhistoricconditions(Christensenetal., 2003; Perry, Low, Ellis, & Reynolds, 2005). There aremanysuch stocks (e.g. cod and anglerfish), but localization of fisheriesmeansthattheremaybelimitedopportunitiesforadditional,short-termdatacollectiontoinfluencelegislativerequirementsformanydemersal species. The real opportunity for additional information that couldmake a difference to fishers is probably in the pelagic

14  |     MANGI et Al.

sector,whereabetterunderstandingofthestockdistributionandits change over time has the potential to lead to more informeddecision-makingformanagersandpolicy.Incontrast,formanyage-based demersal stock assessmentsmore of the same data wouldlikelyleadonlytomorepreciseassessments.Therewillpotentiallybe some gains in fishing opportunities, because as in data-limitedstocks, more precision means less precautionary management isneeded.Itisunlikelytofixconcernsoverbias,persistentunder-oroverestimation of stock dynamic parameters. To address such is-sues,newordifferentdataareneededtocorrectforbiasesintheassessment such as changes in productivity or natural mortality.Such changes in stock size due to causes other than exploitationarepoorlyunderstood,butrecentdataonenvironmentalconditionsare difficult to relate to these historic changes (Sheltona &MarcMangela,2011),sothatimprovementsinenvironmentaldatacollec-tionareunlikelytoimproveassessmentsintheshortterm.

Fishing industry interest, understandably, is likely to focus ontraditional stocks such as haddock (Melanogrammus aeglefinus,Gadidae)cod,sole(Solea solea,Soleidae)andplaice(Pleuronectes pla-tessa,Pleuronectidae).Ifitisdecidedtomakespeciessuchasthesethefocusofdatacollectioneffortsbecauseabroaderrangeoffish-erswouldlikelybenefit,thenitisimportanttomanagetheexpecta-tions.Moresubstantialandlonger-termcommitmentsarenecessaryto make progress for traditional demersal species. Fisheries datacollectionmethods are already standardized and developed to besuitableforuseonfishingvessels.Technologicaldevelopmentshavelargelyfocusedaroundautomatingtheelectronicdatacapture/eval-uationprocess.Specificmethodologiescanonlybeconsideredonceit is clear specificallywhatdataareneeded for aparticular stock.Inthenextsection,welookatguidelinesforindustry–sciencedatacollection that support the development of industry- led initiatives fromthebottom-up,aswellastop-downinitiativesfrommanagersand scientists.

4  | DATA COLLEC TION PROTOCOL

4.1 | Guidelines for industry–science data collection

Resultsfromthestakeholdersurveyonmatchingtheneedandca-pacity to collect data show that some data users have legitimateconcerns regarding the ability of the fishing industry to providequality-controlled data in a form that is accessible and useful forgeneratingthescientificevidenceforadviceinmanagement.Thereareconcernsalsoaboutthegovernanceofthescientificprocessandwhatpartnershipswithindustrymeanfortheintegrityofscientificinstitutions.Fishersalsohavetheirconcerns,particularlythosethatperceive thatmanagementbodiesarenotcommitted tomakeuseof their data, or management does not react quickly enough ontheir information. If they do not understand clearly how science is generatedandusedinmanagement,itcanexacerbatetheirfrustra-tionwithmanagement,potentiallyleadingtopoorcompliancewithregulation(Mackinson,Mangi,Hetherington,Catchpole,&Masters,2017).

Working in partnership therefore benefits both industry andsciencebecausethevalueofsciencetomanagement isbetterun-derstoodandacceptedwhenthescientificknowledgeisco-created(Dickinson etal., 2012; Schläppy etal., 2017). The stakeholder in-terviews,andreviewofpastandongoingdatacollectioninitiativesalso indicate that many fishers are keen to contribute data fromtheir fisheries as scientific evidence to help improvemanagementandstockassessments.Individualmotivesforthismaybecomplex,butmostfishersagreeonthelong-termgoalofsecuringaccesstofishingopportunities.Theirinterestinscienceisalsodeeplyrootedinagenuinecuriositytoknowandunderstandmoreaboutwhatishappeningunderwater.Whilethespecificdetailswillvaryforeachfishery, thecommonfeaturesforsuccessful industry–sciencedatacollectioninitiativecanbedefined(Mackinsonetal.,2017).

Based on a series ofworkshops (http://www.fishingintothefu-ture.co.uk/industry-data-collection-strategy-and-issues), reviews,conversations with key personnel and relevant agencies, and ex-periences from past projects (e.g. GAP2),Mackinson etal. (2017)developedastep-by-stepguidancetogatheringusefulanduseablescientificinformation.Theaimswereto(i)provideareferencetoolto initiateandexecute industry–sciencedatacollection initiatives,whichhavethehighestchancesofsuccess;(ii)helpscientistsunder-standhowtoworkwith industry toenhancescientificknowledgeanddata;(iii)helpfishersunderstandandcontributetothescientificevidencebaseformanagement;and(iv)supportmanager’sneedforsalientevidenceuponwhichtodevelopmanagementmeasuresthatbenefitthesustainabilityoffisheries.Theguidelinessupportthede-velopmentofindustry-ledinitiativesfromthebottom-up,aswellastop-down initiatives frommanagersandscientists,andeverythingin- between.

Thewholeprocess isbrokendown in to five stages (Figure3),eachpromptedbyasinglequestion.Stage1initiatesthedatacol-lectionprocess,conveningpeoplearoundthetaskofspecifyingtheproblem and what needs to be achieved to solve it. The data collected mustrelatedirectlytoaclearlyidentifiedmanagementneedfromtheoutset.Itisadvisabletocarefullyplanforthisstageasallsubsequentstepswillbegreatly informedby it.Stage2 involves thepracticalplanningofthedatacollectionthroughco-design.Stage3involvescollectingdataonthewaterandconsideringsurveyissuesanddataanalyses.Stage4considershowtheknowledgegatheredcanbeap-plied toachieve thedesired impactof the study.Stage5 involvescriticalevaluation,drawingoutlessonsforthefuture.Formorede-tailsoneachstageseethefullreportatwww.fishingintothefuture.co.uk/industry-science-and-data/survey-protocol-guidelines/.

The detailed guidelines are presented as series of questionsrelevantateachstageinthedatacollection.Whentheguidanceisemployedinapracticalworkshopsetting,thequestionsareusedtofacilitateplanning throughopendiscussionpertinent to theprob-lemsathand.Drillingdown,moredetailedquestionscanserveasachecklistofitemstobereviewedandconsideredwhererelevant.

Onekeyaspectindesigninganddeliveringindustry–sciencedatacollectionprogrammesishavingtherighttoolstoassistscientistsinmakingthemostoutoftheinformationavailabletothemtogenerate

http://www.fishingintothefuture.co.uk/industry-data-collection-strategy-and-issueshttp://www.fishingintothefuture.co.uk/industry-data-collection-strategy-and-issueshttp://www.fishingintothefuture.co.uk/industry-science-and-data/survey-protocol-guidelines/http://www.fishingintothefuture.co.uk/industry-science-and-data/survey-protocol-guidelines/

     |  15MANGI et Al.

robustscientificevidence,butalsotoempowerfisherstocollectrel-evant data. Industry–science data collections also need to portray thefullspectrumofpotentialcontributionrangingfromfisherspro-vidinginformationtoscientists,tocollaborationinresearch,throughtogovernancearrangementsinwhichfisherscontributeknowledgeand actively participate in research and management (Mackinson& Middleton, 2018; Mackinson, Wilson, Galiay, & Deas, 2011;Mackinsonetal.,2017;Stephensonetal.,2016).Thedatacollectionprotocoldescribestheessentialsofwhat it takestoco-designandco-deliverindustry–scienceinitiatives,helpingtoidentifythosepeo-pleandinstitutionsthatshouldbeinvolved,andtherolestheyneedtoplay.Considerationshouldbemadeonhowtomotivatepeople’sparticipationbyidentifyingthedriversandincentivesthatresonatewiththem.Thestep-by-stepprocessalsoinvolvesplanningforjointlearningand trainingactivities thatdevelop sharedunderstanding,and getting the support ofmanagers and other stakeholders, andmakingeffectivecommunicationwithawideraudience.Theevalu-ationphase(Stage5)ismeanttolookcriticallyattheresultsandtheprocessandusethis learningwhenplanningnew initiatives.Whilefocusingonfisheriesdatacollection,theguidance isnotrestrictedtotheprocessofgatheringscientificinformationrequiredforstockassessment.Itisequallyrelevanttoresearchonunderstandingthebiologyandecologyofspeciesandbehaviouroffisheries.

4.2 | Applying the data collection protocol

Todemonstratehow the stages from thedata collectionprotocolcanbeappliedtocollectdataandfeedintoamanagementsystem,

thescientificandgovernancepathways,developedbytheSpurdogBy-catch Avoidance Programme, were applied retrospectively(Figure4).Otherexamplesareprovidedinthedatacollectionpro-tocol (www.fishingintothefuture.co.uk/industry-science-and-data/survey-protocol-guidelines/). The Spurdog By-catch AvoidanceProgrammewasascience-industrytrialtomonitor,avoidandreducespurdogbycatch.Itsobjectivewastodevelopandevaluateanalter-nativeoptiontotheprohibitionofspurdogandpreventa“choke”toUKfisheriesundertheCFPlandingobligation.Althoughspurdogisaprohibitedspecies, it iscaughtindemersaltrawlandgillnetfish-erieswithinEuropeanwaters.Duetoitsstatus,currentcatchesofspurdog arediscarded, although the extentof this problem is un-known.ThenewCFPintroducedalandingobligationwithaphasedimplementationfrom2015.Previously,spurdogwasazeroTACspe-cies,meaningithadthepotentialtobecomechokespeciesinmixedfisheries,wherebyitforcesfisherstostopfishingaltogetherandtie-up theirvessels inareaswhere spurdog is caughtasbycatch.Therecent(2017)additionofspurdogtotheprohibitedspecieslisthaspreventeditfrombecomingachokespecies,ineffectoptingoutoffisherieslegislation,ensuringthatdiscardingcancontinue.However,thisisnotinthespiritofthelandingsobligation,asitdoesnotcon-tributetothereductioninfishingpressureofthestockanddoesnotaddresswastefuldeaddiscarding.

Basedonfisheries-dependentscientificevidence(Bendalletal.,2014;Hetheringtonetal.,2016),acollaborativeresearchpartnershipbetweengovernmentpolicyadvisors, scientists, the fishing indus-try and an environmental non-governmental organization (eNGO)informed the development and trial of the real- time avoidance of

F IGURE  3 Summaryoverviewofthestep-by-stepdatacollectionprotocolshowingtheparallelscienceandcollaborationprocesses,accompaniedbythekeyquestionstoconsiderateachstage[Colourfigurecanbeviewedatwileyonlinelibrary.com]

1. Initiation by co-creation

2. Planning by co-design

3. Survey and analysis

4. Applying the knowledge

5. Evaluation

What do we want to achieve?The evidence we need and how to

get itGathering evidence and making the most of it.

How do we make the knowledge count?

Did it achieve what was expected?

Scie

nce

ques

tions

to co

nsid

er

- What is the problem and why does it need to be solved?- Who wants to solve it and what

outcomes do they expect?- What are the aims for the project?- Who are the gatekeepers that will

influence how the evidence will be applied?- What is the scope, scale and timing

of the project?- Are the outcomes achievable?

- What objectives are needed?- What information is needed for it to

be fit for purpose?- Critical needs and constraints to

address?- What is needed to make the data

robust scientifically?- What skills and training are required?- What are the resource implications?- Who owns the data and what access

will they require?

- What on-board procedures are needed to make the data collection work?- How will the work be managed

to ensure quality control?- How will the team and others be

kept up to date with progress?- How will data be analysed and

interpreted?

- What routes lead scientific data to being used as evidence and applied?- What format does the data need

to be in for a quality review?- What’s required to justify any

proposal based on the findings?

- Has the aim been achieved?- Do the benefits outweigh

the costs?- What worked well and what

can be improved?- What strategic actions need

to occur for this to continue?

Colla

bora

tion

ques

tions

to co

nsid

er

- Who are the end-users and knowledge providers that need to be involved?- What understanding and

expectations do people have?- Is the aim agreed and understood?- What core values are needed to

make the collaboration work?- Who needs to be on the project

team?

- How to motivate industry’s participation?- Who needs to be involved and how?- What feedback mechanisms are

needed?- What working practices can meet the

needs of the science?- What research tools might help co-

delivery?- What communications will strengthen

collaboration?

- How can we build shared knowledge and skills?- Why is it a good idea for

scientists to be on-board fishing vessels whenever possible?- How do we keep a focus on

getting the job done to the required standard?

- How do we gain the support of relevant managers and other stakeholders?- What needs to be communicated

about the process and outcomes?- Why is it important to give

visibility to fishermen’s contributions and how they have been used?

- How did the collaboration process go?- What was the value and

benefit of co-construction?- Why should we give credit

where it is due?- What should the group do

next?

http://www.fishingintothefuture.co.uk/industry-science-and-data/survey-protocol-guidelines/http://www.fishingintothefuture.co.uk/industry-science-and-data/survey-protocol-guidelines/www.wileyonlinelibrary.com

16  |     MANGI et Al.

F IGURE  4 Architectureofthedevelopment,trailandevaluationofthereal-timeSpurdogbycatchavoidanceprogrammedemonstratinghowthedatacollectionguidelinescanbeappliedtogeneratedataandinformationformanagement[Colourfigurecanbeviewedatwileyonlinelibrary.com]

Initiation Survey

Applying the knowledge

Practical planningAnalysis

Co-delivery Co-constructing know

ledge and learning to be effective Co-creation

Co-design

ProblemThe recent addition of spurdog to the Prohibited Species list has helped to prevent it from becoming a ‘choke’ species, ensuring that discarding can continue. However, this does not contribute to the reduction in fishing pressure of the stock and does not address wasteful dead discarding.

CatalystFisheries scientists and managers, the fishing industry and ENGO recognize that in some fisheries, a Prohibited Species listing is an

ineffective management measure.

UK Govt. provides funding

Project aimAlternative management of spurdog to align

with a reformed CFPKnowledge base

Fishery-independent data, e.g. historical landings,

archival tag dataFishery-dependant data collectionSpurdog bycatch data

Project partners

ResourcesVessels.

Bycatch allowance.Scientific personnel.

Policy personnel.

ID pathway to application

Phase 1Collection of baseline data

Phase 2Limited trial

Sampling protocols

European CommissionSubmission of UK proposal for a

real-time Spurdog Bycatch Avoidance programme

ICES WGEFSubmission of UK proposal for a

real-time Spurdog Bycatch Avoidance programme

Stakeholder consultationRegular consultation on a local,

STECF Evaluation and recommendation of the proposal

December Fisheries CouncilProposal submitted for consideration

NWWACSupport for the proposal

Phase 3Roll-out to multiple vessels & sea areas

Engagement with European CommissionSubmission of revised proposal

Amendment to Council Regulation (EU) 2016/72 Provision of dead spurdog bycatch allowance to incentive industry participation and wider EU roll-out

Member StatesRelevant EU Member States consulted

Report

Evaluate voluntary avoidance of spurdog bycatch using

- Historic fishery-dependant bycatch & discarddata

- e-logbook catch & discard data- VMS data

Evaluate - Level of engagement by the fishing industry- Spatial & temporal accuracy of data provision

VesselReal-time reporting of spurdog bycatch & discard

CefasCollate real-time data and advise of spurdog bycatch

hotspots

VesselDemonstrate avoidance

VesselReal-time reporting of spurdog bycatch & discard

VesselDemonstrate voluntary avoidance

Levels of spurdog bycatch & discard

Vitality & survivability

Movements & distribution

VesselSelf-sampling of spurdog bycatch

- Location- Number/weight- Length- Sex

Genetic analysis

VesselScientist led sampling of spurdog bycatch as above, plus:- Vitality assessment- Tissue sampling- Tagging using archival tags

Prop

osal

for a

UK

Pilo

t Pro

ject

to d

evel

op a

real

-tim

e Sp

urdo

g By

catc

h Av

oida

nce

Prog

ram

me

to m

itiga

te a

cho

ke sp

ecie

s and

so m

inim

ize fi

shin

g-in

duce

d m

orta

lity

Feedback, refinement and review

www.wileyonlinelibrary.com

     |  17MANGI et Al.

spurdog.ThroughanArcGISonlineportal, fishersself-reporttheirbycatch in real time by area. This information is compiled and re-portedbacktofishersusingatrafficlightsystemwithred(highriskofspurdogbycatch),amber(mediumriskofsignificantbycatch)andgreen(lowriskofsignificantbycatch).Thisempowersthefisherstomakeinformedfishingbehaviourdecisionsinreal-time,enablingac-tiveavoidanceof recentbycatch “hotspots,” reducingspurdogby-catch, reducing fishingmortality and prevent choking the fishery.By utilizing data collected directly by the fishing industry, fishersaremorelikelytoadapttheirfishingbehaviourtoavoidspurdogby-catch as the evidence provided is based on their own observations. Whilethestakeholderengagementhelpsunderpinfuturedecisionsonavoidingbycatchesinkey“hotspot”areas,facilitatingareal-timeunderstanding of the interaction between fishers and this threat-enedstock,theprogrammeisassessingthefeasibilityofdevolvingmanagementofspurdogbycatchtothefishingindustry.

The initial phase of the programme has successfully demon-strated that a real-time spurdog bycatch reporting tool, togetherwith a small dead spurdog bycatch allowance, offers a real andprobablealternativetoan immediateProhibitedSpecies listingforspurdog, thereby providing a pragmatic solution to align spurdogwiththeCFPlandingobligation(Hetheringtonetal.,2016).Throughcontinued positive engagementwith the EuropeanCommission, astrongUKGovernmentpolicylead,supportedbytwopositive,butcautiousreviewsoftheSpurdogBy-catchAvoidanceProgrammebyScientific,TechnicalandEconomicCommitteeforFisheries(STECF)(STECF,2014,2015)ledtofishingvesselsparticipatingintheprojecttolandlimitedquantitiesofdeadspurdog,withaprecautionaryan-nuallimitof270tonnes(UKallocationof100tonnes),withavesselmonthlylimitof2tonnes.Thisincentivizedindustryparticipationintheprogramme,allowingforacomprehensivetrialforevaluation.

5  | HOW UK PROGRESS COMPARES TO OTHER COUNTRIES

Whilethetideisslowlyturningtobemoresupportiveofindustry–scienceinitiativesintheUK,thereisnooverarchingpolicyfromsci-ence,managementorendusers thatseeks tocreateandpromotethe conditions to initiate and implement such activities.What ex-istsisacollectionoflearning-by-doingcases,eachseekingtosolvelocally relevant issues. Systematic and institutional support for industry–scienceneeds to come from theorganizations that havestatutoryresponsibilityforcollecteddata,itsqualitycontrolandap-plication(Mackinson&Middleton,2018).SuchasituationisbetterreflectedinEastcoastUSA,andinNewZealandandAustraliawherededicatedprogrammesforindustry–scienceinitiativefallundertheauspices of science and management agencies. For example, theNOAA Fisheries National Cooperative Research Programwas setupthroughcongressionalfundingtoprovideameansforcommer-cial and recreational fishers to become involved in the collection of fundamental fisheries information to support the development and evaluation of management options. Through this programme, the

industry andother stakeholders canpartnerwithNOAA fisheriesanduniversityscientists, inallphasesof theresearchprogramme,includingsurvey/statisticaldesign,conductingofresearch,analysisofresults,andcommunicationofresults(https://www.st.nmfs.noaa.gov/cooperative-research/index).

Similarly, in New Zealand the Trident Systems, a limited part-nership fundedby itspartners togetherwithSeafood InnovationsLimited, aims toprovidehigh-quality research services supportingthe effective and efficient management of New Zealand’s fisher-ies for long-term sustainable use. Trident Systems’ research anddevelopmentprogrammefocuseson thedeliveryofstock-specificserviceswiththeworkcarriedoutincollaborationwithseveralin-dependent research providers including the Ministry for PrimaryIndustries (http://www.tridentsystems.co.nz/). Its purpose is to (i)develop innovative systems and processes, including for efficientdatacollectionforfisheriesmanagement,especiallyfrominshorefin-fishfisheries;(ii)applythesesystemsandprocessestoprovidestockand/or fishery- specific research services that support timely and ef-ficient fisheriesmanagementdecision-making; (iii) carry out theseactivitiesinamannerthatefficientlyutilizesindustryresources,andsupportsindustryinvolvementinfisheriesmanagementprocesses;and(iv)ensureabroadbaseofindustrycommitmenttothedevelop-mentofitssystemsandprocesses,andtheutilizationoftheresultsofapplyingthesesystemsandprocesses.

In Australia, the Fisheries Research and DevelopmentCorporation (FRDC) is a co-funded partnership between theAustralian Government and the fishing and aquaculture sectors(http://www.frdc.com.au/About-us). It was formed as a statutorycorporationin1991,undertheprovisionsofthePrimaryIndustriesResearch and Development Act 1989 and is responsible to theMinisterofAgricultureandWaterResources.TheFRDC’sroleistoplanandinvestinfisheriesresearch,developmentandextensionac-tivitiesandprovideleadershipandcoordinationofthemonitoring,evaluatingandreportingincludingfacilitatingdissemination,exten-sion and commercialization. Although FRDCworkswith a diverseand geographically dispersed groupof stakeholders, the keyonesare aquaculture, commercial fishing, indigenous fishing and recre-ationalfishingsectors.

InEurope,TheNetherlands,DenmarkandNorwayhaveongo-ingprogrammeswherescientistsareworkingcloselywithindustryon routine data collection programmes. For example, the Dutchself-sampling programme coordinated by the Institute forMarineResources and Ecosystem Studies (IMARES) undertakes discardsmonitoring in close collaboration with the Dutch fishing industry(Kraanetal.,2013).Withinthisproject,areferencefleetofvesselowners, willing to participate in a self-sampling programme, hasbeenrecruitedtoprovidekeyevidencetosupportmanagementofdiscarding practices. In 2013, the reference fleet consisted of 23vessels. Similarly, the Norwegian reference fleet, funded throughan annual quota set aside for the Institute of Marine Research(IMR), comprisesof20vessels in thecoastaldemersal,11vesselsin the offshore demersal, two vessels in the coastal pelagic andfive vessels in the offshore pelagic fisheries that systematically

https://www.st.nmfs.noaa.gov/cooperative-research/indexhttps://www.st.nmfs.noaa.gov/cooperative-research/indexhttp://www.tridentsystems.co.nz/http://www.frdc.com.au/About-us

18  |     MANGI et Al.

delivers assessment ready data on a range of stocks (Boweringetal., 2011;Nedreaas, Borge,Godoy,&Aanes, 2006; Pennington&Helle,2011).TheNorwegianreferencefleetisasourceofinfor-mationanddatatoarangeofstakeholdersincludingtheInstituteofMarineResearch(IMR),theMinistryofFisheriesandCoastalaffairs(FKD),theDirectorateofFisheries(FDIR),theNationalInstituteofNutritionandSeafoodResearch (NIFES), the InternationalCouncilfortheExplorationoftheSea(ICES),andtheNorwegianFishermenOrganization(NorgesFiskarlag).

Recent appointments of former government scientists by thedemersal and pelagic industry sectors from several EU countriesand Norway demonstrate industry’s commitment to profession-alisminundertakingtheirrolewithintheestablishedsystemsthatcollectandmakeuseofscientificdata.Forinstance,inalandmarkdevelopment,therepresentativeassociationforScotland’smackerelandherringfishersappointedachiefscientificofficertospearheadmarine research toboostunderstandingofkeypelagic fishstocksandimprovetheirmanagement(http://www.scottishpelagic.co.uk/).This appointment by the Scottish Pelagic Fishermen’s Association(SPFA)representsaninnovativenewapproachtofisheriesmanage-mentwhere fishingvesselswillplayasignificant role incollectinganddisseminatingscientificinformationonfishstocks.

The programmes and initiatives described above demonstratehowglobalmarineenvironmentalgovernanceandthemanagementoffisheriesduringthelastdecadehavebeenbuildingopportunitiesfor scientists, fishers, policymakers and stakeholders to commu-nicate, negotiate andwork together (Johnson, 2007; Neis & Felt,2001;Reid&Hartley,2006).Theyalso indicategrowingefforts inthemainstreamingof fishing industrygenerateddata for fisheriesandmarinescienceevidenceanddecision-making.Whiletheobjec-tivesoftheinitiativesvary,theyallendeavourtoprovidelegitimacyand equitable management, cost-efficient research, and more ef-ficient enforcementdue tohigher legitimacy among stakeholders.Theexpansionoftheprogrammesshowsthatittakesastructuredand balanced approach to mobilize key actors by matching theirstrategic interests and indicates that collaborative research isoneprincipleroutetoprovidingdataandinformationforevidence-baseddecision-making.Theseinitiativesencompassamodelfordatapro-vision that could be routinely adopted to overcome some of the funding limitations and short-term nature of current industry-leddata collection projects.

6  | CONCLUSION

This study was undertaken to address the increasing need for astrategicapproachto industry–sciencedatacollections inthefaceof reducing resources and growing need for evidence in fisheriesmanagementandmarineenvironmentalmonitoring.Theaimwastoevaluateprogressinthedevelopmentofplansandproceduresthatcanbeemployedtocollect,recordandusefishingindustryknowl-edgeanddataintheevidencebaseformanagingfisheriesandma-rineecosystems.Here,opportunitieswherefisherscouldcooperate

inthecollectionofdatatowardsacomprehensivemonitoringpro-grammehavebeenidentifiedandmatchedwiththeneedsofmoni-toringagencies.Further,guidelinesfordatacollection,aswellasthemanagementandadministrationoftheuseofthedata(i.e.storage,ownership and accessibility of the data) that is subsequently col-lectedhavebeendescribed.There are still barriers to achieving aroutine industry–science data collection scheme that feeds data into stock assessment andmanagement advice. These include culturalchallenges (e.g.wheremonitoringschemesandstockassessmentsarenotyetflexibleenoughtoutilizefisheries-dependentdata)andlackof resources (both financial andorganizational) toadequatelyfund and run such programmes and uncertainty around the long-termcommitment tocollecting thesedata.However, the researchconducted here has addressed some of the technical and capacity barrierstoenablethefishingindustrytoperformakeyrole inad-dressing data gaps in the science andmanagement of fisheries. Iffishers canbe supported tocollect the rightdata, about the rightfisheries,andintherightway,thencurrentdatashortagescouldbeovercome.

Our research also addresses issues of fishers- science interac-tions,engagementandcollaborativeefforts that couldbeused toimprove trust and relationships. The need for collaboration as well asaddressingthepracticalaspectsofdatacollectionmeanthattheroles people play and the way they interact with one another are key to determining success in industry–science initiatives. At thesame time, the twin processes of developing the scientific rigourand content are inseparable. These twin- strands of practical science (i.e.definingtheaims,requirements,designandprocessfortheac-tualdatacollection)andthecollaborativeprocess (i.e.establishingaframeworkforhowtheindustryandscientistswillworktogethertoco-create,co-design,co-deliverandcon-constructtheknowledgeharvested fromthe research)aremutuallysupportive. Indeed, theengagement process is unique to collaborative industry–scienceresearchwhile thepracticaldesign is relevant toanykindofdatacollection,andtherefore,thetwoprocessesshouldruninparallel.Carefulattentionisthereforeneededonhowtoworktogetheref-fectively and respectfully.

Awiderangeofscientificinformationthatcouldreasonablybecollectedby the fishing industrywithin theirnormal activitieshasbeen identified and matched with advice/policy data needs. Foreachofthesuggesteddatatypes,therewerefishersabletoprovidesuchinformationanddatausersinterestedinobtainingthesaidin-formation. The industry proposed to assist in collection of most if notalldatatypes,butinformationdirectlyrelatedtothefisherysuchasfishstocks,biodiversityfromfishingactivities, fisheriesactivityand fisheries acoustics was readily obtainable by many of the fish-ers.Opportunitiestomaximizetheimpactofindustry–sciencedatacollection scheme in the areas of fisheries mean much more detailed discussionsbetweenspecificfisheriesandstockassessmentscien-tistsarenecessary.Advicecouldfocusonareasofhighassessmentpriority which could also have a beneficial outcome for the industry. Theseincludedatacollectionsondata-poorspeciesmanagedonahighlyprecautionarybasis,especially those thatmayactaschoke

http://www.scottishpelagic.co.uk/

     |  19MANGI et Al.

species as the landing obligation is further implemented. Widelydistributedspecieswithchangingdistributionsthatcomplicatetheattributionoflandingstostockandareasprovidefurtheropportu-nities.Incontrasttostockassessments,environmentalassessmentsare lessspecific.Suchdatacollectionscouldbeappliedmoregen-erally across an ecoregionwith fewer concern over the appropri-atenessofthespatialrangeofcollectionsanddifferencesinfishingpractices.

ACKNOWLEDG EMENTS

This researchwas funded by the (i) Celtic Seas Partnership (CSP)through the Fishing-4-data initiative on informing the scope ofthe Celtic Seas fishery stakeholder data collection strategy; (ii)DepartmentofEnvironment,FoodandRuralAffairs(Defra)throughthe Fisheries Science Partnership (FSP); and (iii) Fishing into theFuture(FITF)throughagrantfromtheSeafishStrategicInvestmentFund(SIF).WewouldliketothanktheScottishPelagicFishermen’sAssociation(SPFA)forsupportingoneoftheauthors.Specialthanksto the respondents who took part in the online survey and theworkshopparticipantsfortheirthorough,productiveandengagingdiscussions.

ORCID

Stephen C Mangi http://orcid.org/0000-0001-8233-2612

Dale Rodmell http://orcid.org/0000-0002-0879-7822

David Righton http://orcid.org/0000-0001-8643-3672

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