Annual Review of Marine Science Partnering with Fishing Fleets to Monitor Ocean Conditions Glen Gawarkiewicz 1 and Anna Malek Mercer 2 1 Department of Physical Oceanography, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts 02543, USA; email: [email protected]2 Commercial Fisheries Research Foundation, Saunderstown, Rhode Island 02874, USA Annu. Rev. Mar. Sci. 2019. 11:391–411 First published as a Review in Advance on June 20, 2018 The Annual Review of Marine Science is online at marine.annualreviews.org https://doi.org/10.1146/annurev-marine-010318- 095201 Copyright c 2019 by Annual Reviews. All rights reserved Keywords collaborative research, ocean monitoring, citizen science, hydrography Abstract Engaging ocean users, including fishing fleets, in oceanographic and ecolog- ical research is a valuable method for collecting high-quality data, improving cost efficiency, and increasing societal appreciation for scientific research. As research partners, fishing fleets provide broad access to and knowledge of the ocean, and fishers are highly motivated to use the data collected to better understand the ecosystems in which they harvest. Here, we discuss recent trends in collaborative research that have increased the capacity of and access to scientific data collection. We also describe common elements of successful collaborative research programs, including definition of a scientific problem and goals, choice of technology, data collection and sampling design, data management and dissemination, and data analysis and communication. Fi- nally, we review four case studies that demonstrate the general principles of effective collaborative research as well as the utility of citizen-collected data for academic research and fisheries management. We also discuss the challenge of funding, particularly as it relates to maintaining collaborative research programs in the long term. We conclude with a discussion of likely future trends. Ultimately, we predict that collaborative research will con- tinue to grow in importance as climate change increasingly impacts ocean ecosystems, commercial fisheries, and the global food supply. 391 Annu. Rev. Mar. Sci. 2019.11:391-411. Downloaded from www.annualreviews.org by Dr John Klinck on 02/22/19. For personal use only.
Transcript
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Annual Review of Marine Science
Partnering with Fishing Fleetsto Monitor Ocean ConditionsGlen Gawarkiewicz1 and Anna Malek Mercer2
1Department of Physical Oceanography, Woods Hole Oceanographic Institution, Woods Hole,Massachusetts 02543, USA; email: [email protected] Fisheries Research Foundation, Saunderstown, Rhode Island 02874, USA
Annu. Rev. Mar. Sci. 2019. 11:391–411
First published as a Review in Advance onJune 20, 2018
The Annual Review of Marine Science is online atmarine.annualreviews.org
Engaging ocean users, including fishing fleets, in oceanographic and ecolog-ical research is a valuable method for collecting high-quality data, improvingcost efficiency, and increasing societal appreciation for scientific research. Asresearch partners, fishing fleets provide broad access to and knowledge ofthe ocean, and fishers are highly motivated to use the data collected to betterunderstand the ecosystems in which they harvest. Here, we discuss recenttrends in collaborative research that have increased the capacity of and accessto scientific data collection. We also describe common elements of successfulcollaborative research programs, including definition of a scientific problemand goals, choice of technology, data collection and sampling design, datamanagement and dissemination, and data analysis and communication. Fi-nally, we review four case studies that demonstrate the general principlesof effective collaborative research as well as the utility of citizen-collecteddata for academic research and fisheries management. We also discuss thechallenge of funding, particularly as it relates to maintaining collaborativeresearch programs in the long term. We conclude with a discussion of likelyfuture trends. Ultimately, we predict that collaborative research will con-tinue to grow in importance as climate change increasingly impacts oceanecosystems, commercial fisheries, and the global food supply.
There has always been a strong tie between science and the general public in the United States.The Founding Fathers were strongly influenced by the intellectual framework of the Enlighten-ment, and many of them pursued scientific studies, most notably Benjamin Franklin and ThomasJefferson. Recent best-selling books have described the scientific activities of the Founding Fathers(Wulf 2012, Shorto 2017), including their emphasis on botany and, pragmatically, agriculture.Throughout the history of the United States, the public has been energized and enthused by thescientific discoveries and popular writings of prominent scientists such as Alexander von Humboldt(Wulf 2016) and Louis Agassiz. Agassiz in particular was influential, becoming the head of theDepartment of Natural History at Harvard University and encouraging students to “study nature,not books”—that is, to directly observe nature and not focus solely on the writings of the past.
Broad public interest has in turn led to the development of citizen science, in which devotedcitizens collect data and engage with trained scientists to learn more about the scientific processand the academic and societal implications of scientific research (Trumbull et al. 2000, Hartley& Robertson 2008, Jordan et al. 2011). Citizen science efforts have a long history, but theyhave exploded in both scale and sophistication in the past two decades (Bonney et al. 2009).Several trends have contributed to the increasing importance of citizen science. The growth ofthe Internet has made both communication and access to specialized information far easier. Therapid advances in technology relating to the Internet of Things, including sophisticated sensors,have made scientific data collection instrumentation far more cost effective and easy to use formembers of the public. A good example of the recent advances in citizen science and the remarkableimpact that citizen-collected data may have is the recent identification of a supernova in its earlystate of formation in the galaxy NGC 613 by Victor Buso in Argentina using a new camera for histelescope (Bersten et al. 2018).
The field of oceanography presents special challenges regarding citizen science. Access to theocean is difficult and expensive. Instruments for typical oceanographic measurements, particularlythe CTD (conductivity-temperature-depth), come with significant initial costs and require regularcalibration and specialized training. As a consequence, many citizen science projects in oceanog-raphy occur near the shoreline. A good example is the Buzzards Bay Coalition’s Baywatchers pro-gram (http://www.savebuzzardsbay.org/about-us/programs-workshops/baywatchers). Cit-izens are given equipment to measure four aspects of water quality (dissolved oxygen, temperature,salinity, and water clarity) and record their measurements weekly, along with the weather condi-tions. This program has been in operation for over two decades. In addition to these measurements,the Baywatchers collect water samples for the Ecosystems Center at the Marine Biological Lab-oratory in Woods Hole for nutrient and phytoplankton analysis. The Baywatchers program is agood example of a citizen science program that provides the scientific community with a timeseries of reliable hydrographic measurements across a coastal ecosystem (Buzzards Bay), and thedata collected are regularly used by environmental managers when making decisions that affectenvironmental protection and resource management.
As mentioned above, the costly nature and complexity of many forms of oceanographic instru-mentation limit the growth of citizen science programs. However, several programs have beenable to develop useful and cost-effective sensor systems that allow for broad use. One exampleis the Smartfin program from the Scripps Institution of Oceanography (http://smartfin.org),which uses surfboard fins with thermistors to obtain high-resolution temperatures, locations, andwave characteristics in the nearshore and inner continental shelf—environments that are typi-cally difficult to reach with conventional oceanographic research vessels (for a description of theSmartfin system, see Bresnahan et al. 2016). The potential for using a group of highly motivated
individuals—surfers, in the case of the Smartfin—as data collectors is enormous and has beendiscussed by Brewin et al. (2015, 2017).
While citizen science efforts involving both the general public and recreational ocean users offermany positive aspects, another group of ocean users presents a unique set of tools and opportunitiesto the scientific community: the commercial fishing industry. Fishers are extremely motivated tocollect data, have a unique ability to access ocean regions that are far offshore, are comfortable withmany types of technology, and in many instances are more knowledgeable than academics aboutocean conditions in specific regions and how oceanographic conditions are changing over time(up to decades) (Mackinson & Wilson 2014). Because fishers frequently work in a specific area (orareas, depending on seasonality) for many years, they have great familiarity with the environment,species, and ecosystem processes and often collect quantitative data (such as sea surface temperatureand catch rates) in logbooks (Yochum et al. 2011). The practice of collaborative research, whichin this case engages the commercial fishing industry in the development, implementation, andapplication of fisheries science, has several important motivations and direct academic, practical,and economic consequences (Wendt & Starr 2009, Mackinson et al. 2011, Yochum et al. 2011).The following sections present the major components of effective collaborative fisheries researchas well as a suite of case studies.
Recent advances in technology have directly translated into more opportunity for citizen sci-ence with both the commercial fishing industry and the general public. As the tools for the Internetof Things have grown, the continued use and development of programming languages such asJava and JavaScript as well as open-source platforms for circuit boards such as Arduino maketechnology both more widely accessible and less costly. One example in the context of collabora-tive oceanographic research is the low-cost CTD available from the organization Oceanographyfor Everyone (http://oceanographyforeveryone.com). This group provides open-source CTDhardware, including technological guides, 3-D printer files, and code repositories, and will inthe future provide open-access databases with data collected using instrumentation built from itsdesigns. Present projects include OpenCTD, for collecting conductivity, temperature, and depthprofiles, and Niskin3D, which is a low-cost 3-D-printable Niskin bottle for the collection of watersamples. A second area where new avenues are opening up for collaborative oceanographic datacollection is the development of smartphone applications that collect oceanographic data. Exam-ples include applications for optical properties in seawater (Busch et al. 2016), ocean color (Leeuw& Boss 2018), water clarity [Secchi Disk (http://secchidisk.org)], and chlorophyll fluorescence(Friedrichs et al. 2017). Thus, the development of lower-cost, user-friendly oceanographic instru-mentation and software is rapid and robust and offers a wide range of possibilities for adoptionin collaborative research with the commercial fishing industry. Commercial manufacturers ofoceanographic instrumentation have also become more sensitive to citizen science applications,as discussed in the case studies presented in Section 4.
The structure of this article is as follows. Section 2 presents an overview of the motivationsfor and benefits of collaborative research that engages fishing fleets. Section 3 describes commonelements of collaborative research projects necessary for successful outcomes, including prolongedstakeholder participation and scientifically valuable data products. A suite of case studies that ex-emplify effective engagement of fishing fleets in monitoring a diversity of ocean conditions appearin Section 4, with the discussion framed around the common elements presented in Section 3.Section 5 discusses the resources needed to sustain and grow collaborative research efforts and thevariety of approaches for obtaining them. Finally, Section 6 discusses future directions, opportu-nities, and challenges for collaborative research with the fishing community, including scientificand societal contributions.
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2. MOTIVATION AND USES FOR COLLABORATIVE FISHERIESRESEARCH
Partnerships between fishing fleets and the science community can bring many benefits, includingenhanced data access and information sharing as well as economic efficiency and societal em-powerment. Below, we briefly describe these benefits, which focus on the development of strongworking relationships between members of the commercial fishing industry and the oceanographicresearch community as well as assimilation of valuable scientific data and knowledge. For the pur-poses of this discussion, collaborative fisheries research is defined as “fishermen and scientistsworking together as equal partners, each using their unique knowledge and expertise to betterunderstand the marine environment, fisheries, marine communities, and fish capture systems andto promote effective and equal use of marine resources for all” (Feeney et al. 2010, p. 206).
Feeney et al. (2010) published a comprehensive overview of the scientific and societal benefits ofcollaborative research that quantified stakeholder perspectives on collaborative fisheries researchin the northeast United States, with particular emphasis on Georges Bank. Specifically, the studypresented an assessment of the impacts of the Northeast Cooperative Research Partners Program(National Marine Fisheries Service) and the Northeast Consortium (based at the University ofNew Hampshire). The study involved public discussions on stakeholder perceptions of a decadeof collaborative fisheries research, held at eight northeastern communities at which data werecollected. The most numerous stakeholders surveyed were commercial fishers (28% of peoplesurveyed) and research scientists (24% of people surveyed).
The major benefits of collaborative research identified by the stakeholders in this study wereenhanced communication, increased research capacity, trust building, relationship building, andeconomic value. The majority of respondents identified multiple positive impacts. It is interestingthat the interactions among various groups—fishers, researchers, and managers—were seen as vi-tally important. Trust is key in collaborative fisheries research and has been identified as importantin a range of studies ( Johnson & van Densen 2007, Hartley & Robertson 2008, Bonney et al. 2009,Wiber et al. 2009). This issue is succinctly summarized in the conclusions of Feeney et al. (2010,p. 215): “Building an understanding and appreciation for both the rigors of science and the experi-ence of industry may be the foundation that has fueled trust between science and fisherman.” Sim-ilar benefits from the Northeast Consortium were also identified by Hartley & Robertson (2006).
Off the central California coast, where collaborative fisheries research has been used to monitormarine protected areas, the advantages have also been numerous (Yochum et al. 2011). Specificbenefits identified by Yochum et al. (2011) include promoting communication and trust amongfishers, scientists, and managers as well as providing high-quality scientific data needed for fish-eries management. Specifically, the collection of quantitative data by fishing fleets has enhancedscientists’ ability to detect changes in local metapopulations that are impacted by changes in theocean environment and ecosystem. This scientific benefit of collaborative research is extremelyimportant as ocean heat waves become more frequent around the globe, and high-resolution dataare needed to understand, predict, and plan for ecological and economic impacts (Hobday et al.2016). Ocean heat waves are defined as temperature anomalies larger than the highest 10% ofanomalies lasting for more than five days. The heat waves may have significant ecological impacts,including species and food web redistribution. Increasing oceanographic data coverage both tem-porally and spatially is crucial in identifying subsurface events that satellite-based sensors cannotsample. Being able to identify changes in oceanographic conditions, species biogeography, andpopulation dynamics is a major benefit from collaborative fisheries research (Devictor et al. 2010,Cigliano et al. 2015).
In addition to the scientific contributions, the societal impacts of collaborative research havebeen widely documented. For example, Wiber et al. (2009) described lessons learned from
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a collaborative research study centered on the Scotian Shelf and Bay of Fundy, where issuesregarding power imbalances among the fishing, science, and management communities wereaddressed during the early stages of collaboration. In this context, colearning and politicalengagement were also seen as vital to the success of collaborative research. This example providesa more nuanced view of the social capital involved in the collaborative process, showing howrelationships among stakeholders can change as a collaborative project evolves.
Overall, the benefits from collaborative fisheries research are common across regions andprojects. Engaging fishing fleets to monitor ocean conditions not only improves communicationand builds trust among stakeholders, but also expands data availability and scientific understandingand advances the management of living marine resources for the benefit of coastal communities,working waterfronts, and seafood consumers.
3. COMMON ELEMENTS OF COLLABORATIVE FISHERIESRESEARCH PROGRAMS
There are a wide range of scientific topics and technical approaches in the use of fishing fleets foroceanographic research. However, there are also common elements that have been recognized asessential to the success of such projects and the production of meaningful results. We briefly reviewthese components before examining a suite of collaborative research case studies. It is important tonote that all of these components are important, and failure in any one of these areas is enough todrastically impact the utility and success of the research results. This breakdown also appliesto citizen science efforts for oceanography in general. The list presented here is similar to thatdeveloped by Yochum et al. (2011), the difference being that here we assume that a collaborativeteam has been formed before the common elements are developed.
3.1. Step 1: Motivation and the Development of Program Goals
The first step in developing a collaborative fisheries research program is to identify specific sci-entific needs (i.e., data gaps) that can be addressed by engaging the fishing fleet. This involvesreviewing the scientific literature, identifying data limitations that impact fisheries management,and assessing recent changes in ocean conditions and resources. Issues such as the seasonality ofdata collection must be addressed, and the scale of resources available must be realistically eval-uated. This is particularly important in the context of identifying the suitability of specific callsfor proposals from a government agency or private foundation for collaborative research projects.Generally, ensuring a good balance between the motivations and inputs of the fishing industryand those of academic and government scientists increases the chances that the program will besuccessful.
3.2. Step 2: Choice of Appropriate Technology
The second step is to examine available technology options, including sensors from commercialvendors, in the context of the scientific and logistical needs and then choose appropriate equipmentthat meets the needs of both the scientists and the users (the fishing fleets). It is important that theproject team identify specific variables to be measured, so that the technology choices meet therequirements necessary to attain the science goals. An important aspect of the choice of technologyis the mix of commercially available sensors and technology development needed to achieve theproper sampling system. Ease of use is an important criterion during the selection of samplingtechnologies, especially in collaborative research projects where fishing fleets are expected toindependently collect data. Because many fishers are familiar with tablet technology, finding
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instrument packages that can wirelessly communicate with a tablet located in the wheelhouse oron deck is helpful. Eliminating the need for expensive computer hardware can also improve costefficiency. Reliability is an important equipment criterion owing to the harsh working environmenton most fishing vessels. As with the development of the science goals, balanced inputs, particularlyfishers’ comments on ease of use, increase the likelihood of ultimate success.
3.3. Step 3: Training
The third step is absolutely vital. In some respects this step requires the most intensive interactionbetween the scientific/technical side of the project and the fishing industry participants. Afterthe sampling packages or measurement devices have been selected and any necessary technologydevelopment is complete, engineers or technicians need to train the fishers who will be involved indata collection. Training includes demonstrating how the equipment is used, providing advice onbest practices for use and likely problems, answering questions about the data and reliability of theequipment, and establishing means of communicating early results and issues with the equipment.At an early stage in this process, it is useful to write protocol documents to guide the participants atsea. Going from initial training to regular data collection may take up to several months dependingon whether the equipment has been recently developed or has been in long-term service throughthe oceanographic community.
Because of the broad range of instrumentation types, which could include tags for followingmarine life, CTDs for measuring water mass properties, radiometers for measuring bio-opticalproperties, dissolved oxygen sensors for assessing ecosystem health, and apps for recording andcommunicating data, it is difficult to generalize about how training should be conducted. Datacollection can also involve collecting biological samples of marine species or water samples fornutrient or chlorophyll analysis.
The initial adoption of the technology is an iterative process. Issues must be identified early,and either the commercial manufacturers or the engineers involved in development (e.g., forsmartphone applications) need to be responsive and able to resolve problems efficiently and effec-tively. Rapid feedback and instructions for resolving technical problems are vital to keeping theearly momentum of a project going and to building and maintaining the motivation of the fishersparticipating in data collection.
3.4. Step 4: Data Collection
The fourth step is at the heart of collaborative fisheries research: collection of data for later analysisand use in management decision-making. Collaborative data collection also seeks to exemplify acost-effective means of increasing research capabilities and building trust.
Several aspects of data collection relate to the seasonal rhythms of fishing and should be ad-dressed during initial project formulation. For example, it is necessary to establish a sampling planwith spatial and temporal scales that are consistent with the initial motivation and science goals.Fishing fleet activity may be limited by the seasonal presence of target species, management prac-tices, weather, and vessel maintenance. Thus, developing a sampling plan that ensures that fishingfleet participants will cover key areas and times of the year involves substantial coordination. Plansmay involve using different fishers at different times of the year or in different regions. Coordi-nation also involves ongoing evaluation of the data return and level of interest of participatingfishers. It may be necessary to replace fishing fleet participants who, for a variety of reasons, areunable to make the expected level of measurements.
Another important aspect of collaborative data collection is regular communication about theperformance of scientific sampling equipment. Instrumentation that is not reliable and is not
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replaced in a timely manner can greatly hamper data collection, impact the ultimate utility ofdata, and cause the disengagement of fishing fleet partners. As such, implementing a collaborativesampling plan requires ongoing communication among fishing fleet and scientific participants,with the purpose of continually evaluating whether the approaches are effective at achieving theproject goals. The process of collaborative data collection is often adaptive, with modificationsmade to meet the scientific purpose of the project and suit the operational characteristics of thefishing fleet.
3.5. Step 5: Data Communication and Archiving
Establishing efficient and reliable communication of the data collected is key to successful col-laborative research. The use of wireless communications (e.g., satellites, Bluetooth, and wirelessInternet access) and automatic transmission of data when vessels return to port simplify the pro-cess. Evaluation of the data collected (e.g., the quality of GPS locations) is necessary. Professionalprocessing and quality control of the data are advisable. Large volumes of data may be collected,and automated data processing whenever possible is helpful. Similarly, dissemination of data toboth participants and interested parties in the fishing industry, regulatory/management agencies,and scientific community is necessary. This can be accomplished via open-access websites, dataportals, or direct transfer (e.g., over FTP).
3.6. Step 6: Analysis and Dissemination
This is perhaps the most exciting part of the collaborative research process. When volumes of dataare collected, with greater geographic range and temporal coverage than are typical, a whole hostof specific events, seasonal and interannual trends, and unexpected signals can provide tremendousavenues for learning and dialogue between fishers and academic or government scientists. Thedialogue is vital for motivating continued data collection, developing new scientific hypothesesfor competitive research proposals, and generating excitement about the project that maintainsparticipants’ attention and engages broader audiences. Regular meetings play a major role inkeeping the dialogue going. A key element of communication is interaction with media. Thereis tremendous public interest, as well as interest on the part of state and federal legislators, inhaving fishers work constructively with scientists. This has become particularly important in recentyears, when ocean warming (e.g., Pershing et al. 2015) and ocean heat waves (e.g., Chen et al.2015, Hobday et al. 2016) have had major impacts on ecosystems, sometimes in unexpected ways.Communicating the scientific results, the motivation for the cooperative efforts, and the resultsof the work enhances opportunities to continue these efforts. Given the rapid rate of change ofboth the oceanographic environment and the ecosystem dynamics in many productive fishingenvironments, a top priority of collaborative research is to disseminate results to both scientificand industry audiences. Quality media coverage in a variety of venues is also useful, as it bolstersthe societal relevance of collaborative fisheries science.
4. CASE STUDIES
4.1. Engaging Fishers to Address Data Deficiencies for Lobster and Jonah Crabin the Northeast United States
Despite the economic and cultural importance of American lobster (Homarus americanus) and therapid emergence of Jonah crab (Cancer borealis), there is consensus among scientists, managers,and fishers that additional data beyond existing surveys and harvester reporting are necessary
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Figure 1Lobster and Jonah Crab Research Fleet participants collecting biological lobster data using the On-DeckData application and digital calipers.
to inform stock assessments and properly manage the lobster and Jonah crab fisheries (ASMFC2018). In 2013, the Commercial Fisheries Research Foundation (CFRF) developed the Lobsterand Jonah Crab Research Fleet to address this need and improve industry trust in the assessmentand management process (Malek Mercer et al. 2018). This fleet integrates state-of-the-art datacollection and verification techniques into standard fishing vessel operations and develops workingpartnerships between scientists, managers, and members of the commercial fishing industry. Itsprimary goal is to provide biological data from areas and times of year that are poorly sampled byexisting surveys yet yield high landings of lobster and Jonah crab.
The 18 fishing vessels participating in the Lobster and Jonah Crab Research Fleet use a special-ized tablet application (On-Deck Data), digital calipers, and wireless water temperature sensorsto record information about their catch and the environment as part of their routine fishing prac-tices (Figure 1). All data are collected at sea by commercial fishers, stored and viewed using theOn-Deck Data application on Android tablets, and relayed to a central database at the CFRF viawireless Internet once a fishing vessel returns to shore. The CFRF manages the project databaseand provides the fishers with personalized data summaries every three months. Project data areintegrated into regional lobster and Jonah crab biosample databases at the Atlantic Coastal Co-operative Statistics Program every six months and are also delivered directly to stock assessmentscientists at state and federal agencies (ACCSP 2018).
From June 2013 to March 2018, the Lobster and Jonah Crab Research Fleet sampled morethan 107,000 lobsters and more than 46,000 Jonah crabs from the Gulf of Maine to the Mid-Atlantic Bight (Figure 2). Specifically, the fleet has collected data from four statistical areas thatwere previously unsampled, representing more than 19,000 square miles of fishing grounds. Thefleet has also collected data from eight statistical areas that were insufficiently characterized, rep-resenting an additional 38,000 square miles of fishing grounds. In total, the fleet has characterizedmore than 3 million pounds of lobster landings, resulting in improved catch data accuracy for thelobster stock assessment (ASMFC 2015a).
The lobster biosample data collected by the fleet were incorporated into the 2015 AtlanticStates Marine Fisheries Commission (ASMFC) American Lobster Benchmark Stock Assessment andPeer Review Report, filling critical data gaps, particularly in offshore waters where no other data were
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Lobster and Jonah crabsampling area
Lobster sampling area only
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Figure 2Areas sampled by the Lobster and Jonah Crab Research Fleet.
available (ASMFC 2015a). Specifically, the fleet’s data were used alongside those of other catchsampling programs (at-sea observers and port sampling) to characterize the size composition andsex ratio of commercial catch in each statistical area. Project data were also an essential componentof the ASMFC’s addendum XXVI to the American Lobster Fishery Management Plan, which wasadopted in February 2018 (ASMFC 2018).
The Jonah crab data collected by the fleet were essential in developing the Jonah Crab Inter-state Fishery Management Plan, which is the primary tool that the ASMFC uses to manage thisemerging fishery (ASMFC 2015b). The fleet is the largest source of commercial catch, retention,and discard characterization for the Jonah crab fishery, having sampled more than 46,000 Jonahcrabs since June 2014. The fleet’s data also act as the baseline for the preregulation of Jonah crabdiscarding practices.
In addition to providing valuable biological and catch data for stock assessments, the projecthas helped improve scientists’ ability to understand the changing ocean environment and itsconnection to the lobster and Jonah crab resources by collecting bottom-water temperature datain tandem with biological sampling. Specifically, the fleet’s bottom-water temperature data havebeen used as a means of tracking warm core ring penetration into bottom waters across thecontinental shelf and the associated redistribution of lobster and Jonah crabs.
The prolonged engagement of the fishing industry in the Lobster and Jonah Crab ResearchFleet is a result of consistent communication and support, ownership of the data, and acceptanceand use of the data by scientists and managers. Ultimately, the fleet presents an efficient andcost-effective approach for collecting and verifying biological lobster and Jonah crab data andbottom-water temperatures, utilizing fishers’ time on the water and applying industry-collecteddata to stock assessments and management plans.
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4.2. Using a Fishing Fleet to Understand Continental-Shelf-ScaleOceanographic Dynamics During a Time of Rapid Change: TheShelf Research Fleet in the Northeast United States
The Woods Hole Oceanographic Institution (WHOI) and the CFRF launched the Shelf ResearchFleet in 2014 to better understand both the year-to-year variability of ocean thermohaline struc-tures and the changing nature of seasonal transitions and shelf-break exchange processes over thecontinental shelf in southern New England. At the same time that significant changes in seasonaltransitions and temperature patterns are occurring over the continental shelf (e.g., Chen et al.2014, 2015; Gawarkiewicz et al. 2018b), there have been extensive budget cuts to existing hy-drographic sampling programs, resulting in significantly reduced data collection in the northeastregion (by up to 50% in some recent years). Thus, as changing oceanographic conditions requiremore novel approaches to fisheries monitoring and management, the availability of critical hydro-graphic data has become extremely limited. The Shelf Research Fleet was developed to addressthese data limitations and enhance understanding of how oceanographic conditions over the shelfare changing and, in turn, how the changes may affect the distribution and availability of resourcespecies that support fishing communities and the seafood supply chain.
To achieve the spatial and temporal data resolution required to measure cross-shelf exchangeprocesses as well as processes on temporal scales of weeks, such as warm core ring interactionswith the continental shelf (e.g., Gawarkiewicz et al. 2001) and salty intrusions from the continentalslope (e.g., Lentz 2003), the fishers participating in the Shelf Research Fleet conduct biweeklywater column profiles in designated locations during routine fishing practices. This samplingstrategy provides temporal and spatial resolution that offers a unique perspective on intraseasonaloceanographic variability and the impacts of exchange processes on the distribution and abundanceof key fisheries resources.
Participant fishers collect data at sea using RBRconcerto CTDs and the Ruskin iPad application(Black 2017). The Ruskin application enables fishers to instantly view water column profiles andwirelessly communicate data to science partners. This feature is critically important, as it enablesfishers to develop hypotheses regarding the relationship between oceanographic conditions andtheir catch.
The Shelf Research Fleet has been in operation since November 2014 and has collected morethan 420 water column profiles (Figure 3). The data are made publicly available, both as processeddata (intended for the science community) and as maps and figures (intended for the fishingcommunity and public) (Gawarkiewicz et al. 2018a).
Regular communication between the science partners and the fishing industry is as important asdata collection. The CFRF provides technical support and general encouragement to participantfishers to help minimize frustrations with sampling equipment and maintain a sense of partnership.CTD profiles are processed at WHOI by Frank Bahr. Communications among WHOI, theCFRF, and the fishing industry about significant oceanographic events such as severe storms andseasonal temperature and salinity anomalies have also been important for exploring the practicalimplications of the oceanographic processes evident in the data and enabling fishers to interpretoceanographic conditions and relate the processes to the abundance and accessibility of their targetspecies (Figure 4).
The data collected so far have been important in understanding how both continental-shelfprocesses and shelf-break exchange processes have been changing in recent years. Perhaps themost dramatic event documented by the Shelf Research Fleet was the onshore penetration of awarm core ring in January 2017 (Gawarkiewicz et al. 2018b). During this event, ring water warmerthan 10◦C was detected onshore as far as the 30-m isobath. Relative to a recent climatology of the
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Mid-Atlantic Bight using more than 100 years’ worth of data (Fleming 2016), the ring intrusionhad a warm anomaly of more than 5◦C that lasted for nearly two months and a salinity anomaly of0.8 PSU. The Shelf Research Fleet data have been used to identify several other warm core ringintrusions as well, including the pulse of fresh water in March 2015 that was likely associated withmelting of snow from the winter storms in the harsh winter of 2014–2015.
The time series of monthly averaged profiles for temperature and salinity appear in Figure 5for each of the six cross-shelf boxes. The warm temperatures in June 2015 and July 2016 arethe result of warm core rings abutting the continental shelf. This is also evident in the salinitydistributions. The near-bottom salinity in the second box, centered near 41◦00′N, approaches35.0 PSU. This is an important scientific result because in recent years warm core ring watermasses have been able to penetrate much farther shoreward than they could in previous decades.Research is currently in progress to determine the effects of warm core rings on the year-to-yeardifferences in the catch of squid south of New England. These ring intrusions appear to havesignificant effects on both the timing and magnitude of the squid landings south of New England.
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Figure 4Glen Gawarkiewicz of the Woods Hole Oceanographic Institution presenting Shelf Research Fleet data tofishers at the Commercial Fisheries Research Foundation. Meetings occur semiannually and typically runtwo to three hours, including extensive discussion.
Future plans include analysis of the seasonal cycle of heat content and relation to air–sea fluxanomalies, which would occur in parallel with a similar analysis of mooring data from the OceanObservatories Initiative’s Pioneer Array data (Chen et al. 2018). The data from the Shelf ResearchFleet complement the Pioneer Array data in terms of determining the shoreward extent of warmcore ring and slope water intrusions onto the continental shelf (Gawarkiewicz et al. 2018b).
4.3. Collaborative Research That Enables Adaptive Fisheries Managementin the Falkland Islands
The trawl fishery for Patagonian squid, Doryteuthis gahi (Loliginidae), is one of the most econom-ically important fisheries in Falkland waters (Arkhipkin et al. 2015). D. gahi, however, has a short(one-year) life cycle, which leads to a weak biomass–recruitment relationship and large biomassfluctuations from year to year. Thus, traditional stock assessment and management efforts arenot suitable for this species (Boyle & Rodhouse 2005). To address this challenge, the FalklandIslands Fisheries Department (FIFD) developed a collaborative data collection, stock assessment,and fishery management process for D. gahi that accounts for its unique life history and enablesreal-time in-season management of the resource. This process is based principally on in-seasonmodeling of stock depletion by the commercial trawl fleet and results in real-time managementof the D. gahi fishery (Arkhipkin et al. 2013) (Figure 6).
The two key sources of data that enable the FIFD to accomplish real-time management ofD. gahi are (a) an industry-based trawl survey before each D. gahi fishing season and (b) in-seasonreporting of biological and effort data by the D. gahi fishing fleet (Arkhipkin et al. 2013). Thepreseason trawl survey is conducted on commercial squid trawl vessels and incorporates bothfixed-location trawls that are maintained from season to season and year to year and adaptive
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trawls that are based on the fishing industry’s experience and are meant to capture high-biomassareas not covered by the fixed trawl stations. This collaborative survey approach ensures that thescientific requirements of randomization and repeatability (via fixed stations) are met and thatthe high spatiotemporal variability of the D. gahi population and fishery is captured (via adaptivestations).
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Figure 6Schematic of the depletion model that is used to manage the Doryteuthis gahi fishery in the Falkland Islands.The fishery shuts down when the biomass estimate (blue line) reaches 10,000 tons ( green line). Figurecourtesy of Andreas Winter, Falkland Islands Fisheries Department.
At the start of the D. gahi fishing season, the FIFD provides every fishing vessel participating inthe D. gahi trawl fishery with training and equipment that enable the fishers to record and reportD. gahi catch and effort using an electronic logbook reporting system. Throughout the D. gahifishing season, each fishing vessel reports the catch in kilograms, fishing effort (trawl dimensionsand duration), trawl location, and D. gahi size distribution from every trawl. Data are wirelesslytransmitted to the FIFD at the end of each fishing day. This comprehensive and collaborative datacollection routine enables the FIFD to track the daily production of and fishing effort for D. gahiin the northern and southern stock areas throughout the fishing season, which are critical inputsto the depletion model that is used to assess and manage the D. gahi fishery in real time (Arkhipkinet al. 2013) (Figure 6). The D. gahi size distributions that are collected by the fishing vesselsare used to convert catch weight to numbers in the depletion model. Finally, the FIFD also usesD. gahi commercial catch and effort data to analyze the relationship between D. gahi productionand oceanographic conditions. Analysis of biological and effort data has shown that increases incatch per unit effort correlate significantly with short-term increases in westerly wind and, to alesser extent, with increases in sea surface temperature (Winter & Arkhipkin 2015). These data areintegrated into the depletion model to give a more systematic approach to the stock assessmentof D. gahi.
By engaging the commercial fishery in the collection of biological and effort data, the FalklandIslands can maximize fishery production and profitability while also ensuring the sustainability ofthe D. gahi resource (Arkhipkin et al. 2013). This case study represents a uniquely coupled scienceand management system that is both collaborative and adaptive.
4.4. The Coastal Community Ocean Observing Program in Alaska
Collaborative research programs can be used to serve underrepresented communities in marinescience. An excellent example is the Coastal Community Ocean Observing (C2O2) program,which involves the University of Alaska Fairbanks and four culturally distinct island communitiesaround Alaska: St. Paul Island in the Bering Sea, Old Harbor on Kodiak Island in the Gulf ofAlaska, Kaktovik in the Beaufort Sea (the only community within the Arctic National Wildlife
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Refuge), and Sitka in southeast Alaska. The scientific goal of the program was to broaden the geo-graphic scope of long-term coastal hydrographic measurements around Alaska to complement themain long-term hydrographic time series in Alaskan coastal waters, oceanographic station GAK1.GAK1 is located within the Alaska Coastal Current at the mouth of Resurrection Bay, south ofSeward, Alaska, and has been sampled approximately monthly with CTD profiles since Decem-ber 1970. A CTD mooring has been deployed at GAK1 since 1998. The nominal goal of C2O2was to obtain CTD profiles monthly, or more frequently if possible. Each of the four samplingsites involved cooperation with Alaska Native communities. As in the programs described above,communications and educational activities involving the research team and the local communitieswere a high priority, with the research team visiting each of the communities at least once a year.These trips typically involved visits to local schools, public presentations, and meetings with localtribal councils.
The longest C2O2 time series has been collected at St. Paul Island in the Bering Sea. A timeseries of temperature, salinity, and density appears in Figure 7. The observations at this site haveoccurred weekly over much of the sampling time because of the enthusiastic involvement of theEcosystem Conservation Office (ECO) on St. Paul Island. CTD profiles have been collected atthe local dock by an ECO employee as a regular duty. ECO also purchased additional CTDs for
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Figure 7Plot showing (a) temperature, (b) salinity, and (c) density measurements from St. Paul Island, Alaska, in theBering Sea. Data collected with a YSI CastAway CTD (conductivity-temperature-depth) instrument appearin blue, and data collected with an RBRconcerto CTD appears in red. Note the low salinity in April 2017 assea ice approached the harbor. Figure courtesy of Elizabeth Dobbins, University of Alaska Fairbanks.
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sampling beyond the scope of the initial C2O2 program and has trained several people in otherBering Sea communities in their use.
The C2O2 program initially used YSI CastAway CTDs. These instruments are easy to use,have a built-in GPS, and plot the profiles on a small LCD screen. However, as shown in Figure 7,the salinity measurements in the shallow and strongly stratified water of the Bering Sea were notalways reliable, and the CastAway CTDs were replaced by RBRconcerto CTDs, the same typeof instrument used in the Shelf Research Fleet. The RBRconcerto also has the added advantageof incorporating additional sensors. C2O2 profiles now also log chlorophyll a fluorescence data,expanding the observations beyond physics alone.
St. Paul Island is also the site of a unique educational activity. During the fall, the local schoolsparticipate for a full week in Bering Sea Days, in which scientists visit the island and teach classes intopics such as physical oceanography, marine mammal physiology, archaeology, seabird ecology,and more. Data collected in the C2O2 program are discussed in the context of both the BeringSea circulation and the impacts of climate change.
Future efforts with the coastal communities in Alaska should include biological sampling.Shellfish are a possible starting point in terms of the ease of collection of samples.
The C2O2 program ended in October 2017. This highlights one of the major issues con-fronting collaborative research: the difficulty of maintaining long-term programs and interactionswhen virtually all available funding is limited to two or three years. Strong partnerships are builtduring successful collaborative research programs, but it is difficult or impossible to maintain theseprograms when follow-on proposals are turned down, as was the case with C2O2.
5. FUNDING AND RESOURCES
The funding for collaborative research projects can come in many forms: government grant pro-grams at national, regional, and local levels; private foundations and donors; environmental non-governmental organizations; and sponsorship from industry groups and businesses, among others.Initial funding to pilot a project can be short term (one to two years), but securing a dedicatedsource (or sources) of funding ultimately determines the longevity, and thus the scientific andsocietal value, of collaborative research projects. In many disciplines, long-term time series arekey to the value and utility of data (Hilborn 2003, Maunder & Watters 2003). In stock assess-ments, for example, it is preferable to have a minimum of five years of biological data prior toincorporation in modeling efforts. Similarly, in oceanography, data sources that span years anddecades are often the most useful, as they provide insight into interannual as well as long-termtrends. Despite the scientific merit of long-term collaborative research, securing year-over-yearfunding can be a major challenge, even if a project’s approaches are demonstrated to be effectiveand the results scientifically valuable.
A variety of examples of funding programs have been dedicated to collaborative research,but their persistence has been limited. A good example is the Northeast Consortium, which wascreated in 1999 to “encourage and fund effective, equal partnerships among commercial fishermen,scientists, and other stakeholders to engage in collaborative research and monitoring projects inthe Gulf of Maine and Georges Bank” (Northeast Consort. 2015; see also Hartley & Robertson2006). The Northeast Consortium funded more than 180 collaborative research projects that werelargely successful at improving science and management and building working relationships, but itbecame inactive when the congressional appropriation expired (Hartley & Robertson 2006). Thus,by necessity, most multiyear collaborative research initiatives rely on an assortment of fundingsources. The Lobster and Jonah Crab Research Fleet, described above, is a good example of this(Malek Mercer et al. 2018). This project was initially piloted using funds from the fishing industry,
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then supported first by a federal competitive research program and later by a private foundation.Despite the recognized value of this project’s approach and data, its future is uncertain.
The future of collaborative research hinges on a larger-scale recognition of its value as a cost-effective source of critically needed data as well as a means for stakeholders to become activelyengaged in ocean sciences and management ( Johnson & van Densen 2007, Feeney et al. 2010,Yochum et al. 2011, Bonney et al. 2014). The health of the world’s oceans and the sustainabilityof the world’s seafood supply are becoming issues of public concern, and thus, the time has neverbeen better to engage citizens in research to address pressing scientific questions (Bonney et al.2009, Wiber et al. 2009). This, however, is not possible if funding programs at all levels do notbegin to prioritize collaboration with stakeholders. Political pressure may be key to effecting thischange, especially at the federal level (Newman et al. 2012).
As more resources are devoted to work that both addresses scientific needs and engages fishersas participants in research, budgets will be streamlined and communities will begin to appreciatethe complexities of ocean ecosystems and their importance to climate, food security, and quality oflife (Lubchenco 1998, Bonney et al. 2009). In the case studies presented, the ivory tower mentalitythat has gripped the science community for decades has begun to break down, and a transparentand collaborative mind-set has begun to take hold (Sonnert & Holton 2002). This, we wouldargue, is the way forward.
6. FUTURE PROSPECTS
There is a dire need for more data from the world’s ocean environments and ecosystems, andcollaborative research is key to addressing this ever-growing demand. This is particularly truein coastal regions, where processes occur on much shorter temporal and spatial scales than theydo in the deep ocean. Data collection through collaborative efforts is extremely cost effectiveand allows for new perspectives in developing an understanding of how oceanographic processesaffect fisheries resources and harvest practices. This is particularly urgent because of the increasingimpacts of climate change and the tight research budgets available for ocean observations.
Collaborative research is also beneficial for the fishing fleets that participate. For example,fishers can use the data they collect during research projects to increase catch efficiency, reducebycatch (e.g., through the University of Massachusetts Dartmouth’s Bycatch Avoidance Programand the Cornell Squid Trawl Network), predict fishery performance (e.g., predicting squid catchand mortality events in scallops), and reduce loss of fishing gear due to extreme oceanographicevents (e.g., from the movement of lobster or crab gear by strong currents associated with warmcore rings or streamers). In the case of the Shelf Research Fleet, described above, salinity in-formation provides an entirely new perspective on the factors affecting catch rates and fisherydistribution.
Over the past decade, the scientific community has gradually begun to accept the quality of thedata collected via collaborative research, including data collected directly by fishers (Roman et al.2011). As such, collaborative research projects have become more successful at achieving the ulti-mate goals of providing data and tools to better understand and predict trends in fisheries resourcesand improving the reliability of stock assessments and the efficacy of fisheries management.
Most stock assessments and management plans for fisheries resources are based on data that arelimited in time and space. Collaborative research provides a method to improve the spatiotemporalresolution of the data used for stock assessments and to better understand the impact of environ-mental conditions on resource species recruitment, growth, and accessibility to the fishery. Inaddition to improving the science that informs fisheries management, collaborative research cre-ates a network of communication and trust between the community that develops regulations
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(scientists and managers) and the community that the regulations affect (fishers and fishing busi-nesses). In this way, fisheries management is transformed from a shrouded, top-down system to atransparent, collaborative system that values the quantitative contributions of stakeholders.
Collaborative research also assists in the development of ecosystem-based fisheries manage-ment (EBFM), which requires a robust network of data about the environment, food webs, andresource species (Levin et al. 2009). Given the high cost and procedural rigidity of traditionalscientific surveys, collecting the data needed to support EBFM requires alternative approaches,including collaborative research. Collaborative research provides not only an effective tool forengaging stakeholders—a stated goal of EBFM—but also a cost-effective and adaptive platformfor collecting the suite of data needed to develop and operationalize ecosystem models and man-agement systems (Leslie & McLeod 2007).
In addition to its value as a data source and community builder, collaborative research providesthe public, scientists, and fishers with a unique form of education (Dickinson et al. 2012). Sharingof the data collected and their implications creates open dialogue about ocean and ecosystemprocesses, impacts of climate change, and the use of technology in oceanography. Collabora-tive research projects also frequently involve early-career professionals in fisheries science andoceanography, providing opportunities to experience the interface between basic research andresource management, develop skills in data analysis and communication of scientific results, andidentify technological developments needed to improve the utility of scientific instrumentation.
Finally, the use of fishing fleets in oceanographic research provides a wonderful example ofhow different communities—commercial fishing and scientific research—can work harmoniouslyto study issues of economic and societal importance. There needs to be much more public andprivate investment in collaborative research efforts, and furthering these efforts will require gettingboth the general public and legislators to appreciate the magnitude of the scientific challenges ina time of rapid change as well as the ability of fishing fleets to address scientific questions.
DISCLOSURE STATEMENT
The authors are not aware of any affiliations, memberships, funding, or financial holdings thatmight be perceived as affecting the objectivity of this review.
ACKNOWLEDGMENTS
Support for G.G. and A.M.M. was provided by the MacArthur Foundation and the van BeurenCharitable Foundation of Newport, Rhode Island. G.G. was also supported by a senior scientistchair provided by the Woods Hole Oceanographic Institution and by the Link Foundation forthe writing of this review. A.M.M. was also supported by a NOAA Fisheries Saltonstall-KennedyGrant Program award and the Campbell Foundation. We thank Frank Bahr of WHOI and AubreyEllertson of the CFRF for many helpful discussions pertaining to this topic. We appreciate theassistance of Seth Danielson and Elizabeth Dobbins of the University of Alaska Fairbanks andAndreas Winter of the FIFD for information and insight on the C2O2 program in Alaska and theadaptive fisheries assessment and management program in the Falkland Islands, respectively.
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Errata
An online log of corrections to Annual Review of Marine Science articles may be found athttp://www.annualreviews.org/errata/marine
