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Environmental Sociology

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Factors Determining Participation Quality inCollaborative Water Quality Research

Amy Freitag

To cite this article: Amy Freitag (2017): Factors Determining Participation Quality in CollaborativeWater Quality Research, Environmental Sociology, DOI: 10.1080/23251042.2017.1289592

To link to this article: http://dx.doi.org/10.1080/23251042.2017.1289592

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Factors Determining Participation Quality in Collaborative Water QualityResearchAmy Freitag

Virginia Sea Grant, NOAA Chesapeake Bay Office, Gloucester Point, VA, USA

ABSTRACTThe gold standard for citizen science projects that both integrate multiple ways of knowingand innovate new knowledge and solutions are fully collaborative research endeavors wherescientists and citizens work as equals at all stages of research. Beyond equitable structure,there are key factors within each collaborative project that help determine success. Using acase study of a collaborative research project between fishermen and scientists investigatingwater quality impacts on small-scale fisheries, I highlight these factors which have thepotential to elevate citizen science from participation to empowerment: access, space fordissent, structured negotiation, and the role of technology.

ARTICLE HISTORYReceived 16 December 2015Accepted 22 January 2017

KEYWORDSParticipatory research; waterquality; stakeholderengagement; integration;innovation

Introduction

Collaborative research efforts – like citizen science, col-laborative fisheries research, and industry-academicpartnerships – require organizing and making sense ofmultiple forms of knowledge, each in their context ofdifferent professional cultures. All forms of collaborativeresearch are growing in popularity for the promise theybring of integrating diverse forms of existing knowledgeand innovating new knowledge. This integration andinnovation is often aimed at delivering easy applicationsthat will work within the research partners’ industries.However, working with partners with different world-views and professional cultures can also prove challen-ging and present roadblocks to actually completing theresearch. A large literature deals with questions of whoparticipates (e.g. Senier et al. 2016), how participationaffects other social relations (e.g. Linke and Jentoft2016), and the potential for ‘tyranny of participation’(Cooke and Kothari 2001), among the many problemsparticipation introduces. Here, we take an optimisticapproach assuming that participation can be empower-ing if done correctly. As such, this project aims to docu-ment and investigate factors within a single project thathelp determine the quality of participation, the successof integrating and innovating, and ultimately, in meet-ing project application goals.

While participation is extensively discussed in bothresearch and management arenas to achieve aims ofsocial equity (Peluso, Humphrey, and Fortmann 1994),knowledge integration (Nadasdy 1999), problem solvingand innovation (Freitag 2014), and education (Trumbullet al. 2000), among others, few analyses take a detailedlook within a single project to look at the nuances of

collaboration and situational circumstances that canaffect participation (i.e. Avgitidou 2009). Yet, theseinner project details likely determine if these successfuloutcomes of collaboration are realized. In addition,knowledge production for environmental managementis as much about social relations and context as it isabout new information, especially when knowledge pro-duction is collaborative (Lauber et al. 2011). Throughparticipant observation, I provide an analysis of partici-pation throughout the course of a single collaborativeresearch project, documenting moments throughoutthat process where participation quality is determinedand the social relationships of participants established.The emergent key factors can help collaborative projectdesigners focus on key features that determine the qual-ity of knowledge integration and innovation.

Background

The quality and degree of participation in any scientificventure differs greatly between projects. Bonney et al.(2009) classify three main types of participation: contrib-utory where participants primarily collect data, colla-borative where participants contribute tomethodological design and data interpretation, andcocreated where participants are involved in almostevery step of the scientific process from idea generationto asking new questions that result from data. Bonneysuggests, along with others (Kania and Kramer 2011),that citizen empowerment and social impact occur atthe co-created end of the spectrum. A high degree ofparticipation is therefore necessary but not sufficient forsuccessful integration and innovation of knowledge(Figure 1). The question then becomes what other

CONTACT Amy Freitag amy.freitag@noaa.gov

ENVIRONMENTAL SOCIOLOGY, 2017http://dx.doi.org/10.1080/23251042.2017.1289592

© 2017 Informa UK Limited, trading as Taylor & Francis Group

factors do we have in order to move toward moreintegration and innovation (Shirk et al. 2012)? The litera-ture suggests that dissent, negotiation, access, and tech-nology are all important factors (each addressed, inorder, in the following paragraphs).

Dissent is a sign of active participation and criticalthought, both necessary to fully refine ideas for bothscientific innovation and community impact. Lessonsfrom participatory watershed management show theless flattering side of citizen participation, where dis-sent is rare and active involvement (as opposed tomere presence in the room) is difficult to cultivate(Irvin and Stansbury 2004). As citizen science andother participatory efforts are gaining popularity,there is the danger for organizers to disingenuouslyjoin the participation movement and not create themost productive atmosphere for participants (Cookeand Kothari 2001). Therefore, quality participationrequires the space to voice dissent through the finalstages of the research.

Dissent is often accommodated through negotiationofmethods and interpretations. Evenwhen collaboratorsgenerally agree, the goal of creating shared researchresults requires negotiating perspectives formed by peo-ple with different underlying experiences. For example,when farmers and scientists form participatory researchrelationships, each perspective must be investigatedthrough appropriate methods and represented in thefinal result – this is most likely achieved through amixed methods approach ensuring active participationfrom each group, including garden walkthroughs, agri-cultural experiments, and joint workshops for data ana-lysis (Pretty 1995). Only once all perspectives areinvestigated and represented can participants take col-lective ownership of the research. That ownership is aprerequisite to empowerment (Pretty 1995).

Equal access to participation (both in terms oflanguage used and logistics) also mediates the qualityof participation. For example, while the goal of manyparticipatory science projects is informal science edu-cation (Mueller, Tippins, and Bryan 2012), the verylearning in which citizens engage indicates unequalaccess. While participants learn to ‘think scientifically’,

following scientific logic and adopting terminology(Trumbull et al. 2000), the act of translation fromtraditional/local knowledge to scientific promulgatesunderlying power dynamics that can undermine long-term trust and continued research partnerships(Johnson 2011). In collaborative fisheries research,this translation often happens during method devel-opment, where all contributed knowledge is trans-lated to biological terms to fit the parametersrequested by managers; resulting participation candwindle in fear this information will be used to justifylower fishing quotas (Johnson 2011). In a more logis-tical sense, collaborative research often involves largernumbers of people than traditional research, and mayrequire some additional planning to make sure larger,more diverse groups can be accommodated on boats,in laboratories, etc. (Cigliano et al. 2015).

Related to access, technology often mediates a col-laborative research relationship, especially when tech-nical expertise is required for methods like thosestandard for water quality. Conversely, technologieslike geospatial tools offer a third language with whichto integrate contributing . Geospatial software becamea common language to discuss restoration needs inLouisiana estuaries, where physical scientists and fish-ers could both translate their knowledge into a tool forlearning each other’s languages (Bethel et al. 2011).Technology that is familiar to only one group of parti-cipants, however, can tip the power balance in favor ofthat group. This imbalance can come from differentialaccess to expensive technology or different abilities toinvest time to keep up with rapid technological devel-opments (Silvertown 2009). Therefore, technology canboth aid and hinder quality participation depending onaccess and complexity.

The results and discussion section chronologicallydocuments key moments in the collaborative researchprocess that determined participation quality andquantity. The conclusion section returns to the fea-tures quality participation suggested by the literature(access, dissent, negotiation, and technology) to dis-cuss how these moments tie together to determinethe overall participant experience.

Figure 1. Conceptual diagram of steps on a pathway for empowerment of citizen science participants and social impact throughintegrating their knowledge and innovating new knowledge.

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Methods

To identify moments that determine participationquality, I took an ethnographic approach by participat-ing in a collaborative fisheries research project andproviding a detailed description of some of those cri-tical moments. Recognizing my role as both an insiderand outsider, I incorporated into this ethnographicapproach both reflections on my personal experiencesas part of the collaboration and directly asked partici-pants their feelings on the project as it unfolded in theform of one-on-one meetings and evaluation forms(Colic-Peisker in Hume and Mulcock 2004). The detailsof the methodology are embedded in the projectdescription below, but this approach incorporates thebenefits of embeddedness of participant observationwhile avoiding the conflict of attempting to makeobservations of something I am personally involvedin (Tedlock 1991). Such a narrative ethnography isappropriate to be able to gain the trust of projectparticipants and the level of detail necessary to discusssocial relations in collaborative projects (Tedlock 1991).

The project was largely structured around the insti-tutional practices of the funding agency, NorthCarolina Sea Grant, and its Fishery Resource Grantprogram (FRG), which requires a cocreated model ofparticipatory science (Freitag 2015). To capture fisher,scientist, and my own experiences in this project, Itook detailed notes on and audio recordings of inter-actions, in-the-moment reflections, and decisionsmade during the research process. These momentsoccurred during grant writing, organizing projectlogistics, collecting fish samples, doing laboratoryanalyses, and discussing the results. Each of these isdiscussed in more detail in the project description.

All material (notes, workshop activity results, audiorecording transcripts) was coded in the qualitative ana-lysis software NVIVO. A subset was coded by a colleagueto validate the results. We used a combination of induc-tive and deductive coding, looking for the four determi-nants of quality participation described above (access,dissent, negotiation, and technology) deductively (pre-sented in conclusion) but letting the moments of deter-mination emerge from the data (presented in results).

The context

The coast of North Carolina boasts a unique ecologywhere the northern Labrador current meets the south-ern Gulf Stream at Cape Hatteras (Bumpus 1954). TheNeuse River forms a dividing line between north andsouth both biologically and culturally (Griffith 1999).The landscape is formed from thousands of years erod-ing the Appalachian mountains and depositing sedi-ment in a wide, sandy coastal plain forming a complexnetwork of low-lying peninsulas and estuarine bays.These shallow bays with their aquatic vegetation

serve as important nursery grounds for fishery speciesthroughout the east coast (Etherington and Eggleston2000). Locally, these estuaries support an 82 milliondollar commercial fishery including (in order of impor-tance) blue crab, shrimp, croaker, summer flounder,bluefish as well as oysters, flounder, clams, spot, andmullet (Mcinerny and Bianchi 2009).

Fishers understand rivers and estuarine waters aspublic trust (Andreatta and Parlier 2010) and thereforeexpect state responsibility for their stewardship as apublic good as well as public availability of ecosystemservices. With the state’s Coastal Habitat ProtectionPlan (Street et al. 2005), government officials and pub-lic commenters agreed on maintenance of water qual-ity as a priority in management of this public trustresource. The US Geologic Survey recognizes consis-tent water quality issues in North Carolina includingsedimentation, summer hypoxia and nuisance algae,excess nutrients, and fecal coliform bacteria (Bales et al.2003), in addition to historical legacy contaminationfrom the textile and agricultural chemical industries(West 1992). Due to financial and time constraints,not all of these issues can be consistently monitored.

The project

The collaborative research endeavor started as an ideafrom a crabber and a few of his friends in reaction toFood and Water Watch’s listing of blue crabs andoysters on the 2009 ‘Dirty Dozen’ due to mercuryand polychlorinated biphenyl (PCB) contamination.Food and Water Watch stated that ‘blue crab shouldbe avoided due to overfishing and mercury and PCBcontamination’ Concerned about his subsistence con-sumption of blue crab, the crabber went to a localmercury researcher with questions. The researchertested hair from the crabber and his wife, and foundthe samples showed low levels of mercury. This ledthe crabber to believe his largely crab diet was not as‘dirty’ as Food and Water Watch suggested.

Food and Water Watch relies on data collated bythe Environmental Defense Fund (EDF) from peer-reviewed studies and EPA monitoring across thecountry, but with no locations in North Carolina. AnEDF representative responded to email queries: ‘Whileour advice to the general public is that blue crabs onaverage have elevated PCB levels, we cannot say thatis the case specifically for NC crabs. . . based on lack ofdata’ (email from EDF 10/29/2009).

Frustrated with this response, the crabber contacteda local student who was helping to start a community-supported fishery in the area. This student recruited atoxicologist and myself to design a project to fill thedata gap. The project was designed to look at geo-graphic variation in mercury and PCB contamination ofcommercially important seafood caught in NorthCarolina waters. The goals of the study were twofold:

ENVIRONMENTAL SOCIOLOGY 3

to identify areas in need of remediation and to enablefishers from clean areas to market their products as‘healthy’. We wanted to be able to create NorthCarolina-specific advice like that produced by Foodand Water Watch. We then recruited one more fisheryrepresentative from each of the state’s three fisherydistricts to help with project design in their region(project design can be found in Freitag et al. 2012).

Participation by both fishers and scientists varied dur-ing different components of the project. Our core teamrecruited three additional toxicologists to help with che-mical analysis and fifty fishermen for initial fieldworkcollecting samples. Twenty-one fishers and four scien-tists participated in one-on-one meetings to discussresults and their interpretations, and of these, 11 partici-pants attended a wrap-up/what’s next workshop. Thephased approach to research offered participants theopportunity to join or quit as their schedules allowed.

For the one-on-one meetings, I brought a resultshandout, discussed the presented results, and thenhad them perform a map layer exercise to put projectdata in a larger context. Map layers, printed in color ontransparencies from the North Carolina geospatialdatabase, included water quality concerns that werementioned by participants during sample collection. Inaddition to project data, they included ammonia, mer-cury in sediment, PCB in sediment, dissolved oxygen,population density, areas with watershed planningefforts, and point sources. Using both project dataand these other indicators, participants were taskedwith deciding at what spatial scale seafood safetyrecommendations could be made (the original ques-tion of the project). The answer ended up being at thescale of water body (a river section, bay, or lake) and allbut known toxic spill sites were below the federalhealth advisories.

The final workshop offered an opportunity to discussthese conclusions as a result, but participants felt con-fident in the conclusions based on the one-on-one meet-ings and asked tomove on to the ‘what’s next’? question.They still suspected water quality concerns to be impact-ing fishery stocks, but now knew that while mercury andPCBs were present, they were not found at high enoughlevels to significantly impact the fishery. They chose toinvestigate pesticides commonly used in the region (gly-phosate and λ-cyhalothrin) to see if fishery nurserygrounds were exposed.

Results

This section chronicles key moments in the collabora-tive research process that helped determine qualityand/or quantity of participation in the order theyoccurred. Each of these moments contribute to atleast one of the key features described in the intro-duction, and the conclusion section will return tothese connections.

Pre-project: gaining rapport as a facilitator

Given that this mercury and PCB project could theo-retically result taking participants’ catch off the mar-ket, gaining trust of fishermen played a key role in theproject’s success. Recruiting scientists was mucheasier, as there are many in the local communitywho were interested in our research question. Trustis not a bilateral relationship but instead fits into themilieu of existing relationships and social capital,good and bad (Pretty 2003). Some gestures of trustwere small and subtle, like my acquiring a local phonenumber. Others were more direct, like answering thequestion ‘are you a state crony’? Though few wordedthe question quite so colorfully, the intent was clear,and reflects that relationships between fishermen andstate agencies are tenuous at best, intimately tied tofeelings of unjust regulations that took advantage ofpast cooperation (described in a similar situation byJohnson 2009). These represent the smallest and lar-gest signals of trust; the three vignettes in Box 1describe additional details involved in gaining trustand acceptance into the social milieu.

Building rapport and living in the coastal regiondoes not necessarily mean that fishers and scientistssee eye-to-eye to meet common goals – the first stepmay be just tolerating one another, then helping eachother as part of community culture. One fishermansaid of scientists ‘if I thought they were going to dome any damn good, I’d be down there kissing everyone of their asses. But that’s about as god-damnmuch good as having a pimple on my ass. The onlything you hope for is getting some grant money outof it’. He illustrates how cynicism and lack of trustcould serve as a barrier to access to the participatoryresearch. However, he and his family were happy tohelp if it meant someone else in the community wasemployed by said grant money. This particular skep-tical fisherman insisted that I stay for a hearty lunch offried oysters in order to meet the other fisherman intown and hear their stories. The stories told the con-textual story of the participants – environmentalchange over time, family support, economic chal-lenges of the fishery, interactions with endangeredspecies, and other issues only loosely connected towater quality. This is their way of negotiating theworldview underpinning our research, ensuring their

Box 1. Vignette of trustTrust in a fishing community also involves smoothing over a genderdivide. ‘No one will tell you the truth as a woman’, a gray-hairedfisher told me in the early morning hours, without blinking. Hiscomment made me realize that the legend of women bringing badluck at sea is alive and well. Thinking more logistically, anothercaptain asked ‘I have a 5-gallon bucket, is that okay’? Consideringthe bucket an improvement for leaning over the side of the boat touse the bathroom, I said yes. But to him, it was a signal not onlythat I would be out of the way, but that I fully understood what aday in life of a small-scale fisherman entailed.

4 A. FREITAG

methods of learning, embedded in the larger socio-ecological system, were represented (like in Gibbs2001).

Searching for mercury: collecting samples statewide

The project started with four fishermen primary inves-tigators, who recruited others who might be inter-ested in contaminant levels in their catch. Each ofthese fisherman was asked to take a scientist alongand GPS tag samples from various positions alongtheir fishing route during the day. Two problemsarose with this model, however – feasibility of havingcollaborative research teams on small fishing boatsand fishermen wanting to test tissue outside the para-meters of the research.

Since the fisheries of North Carolina are small-scale,and use shallowdraught boats, boats are often too smallfor passengers beyond maybe one mate. Because ofthis, many fishermen (33 of the 54) wanted to tag sam-ples on their own after a protocol training and tradedmaps and stories at the docks in the evening. Those whodid agree to take a scientist on board (21 of the 54) notonly collected what was needed for the study but oftendirected evenly spaced collection across environmentalgradients throughout their route (adding higher spatialresolution than originally planned), using the extra per-son to map the collection en route.

Sampling involved very little outside a normal fishingroutine, as we were trying to model typical consumerexperiences. However, some fishers wanted to find themost contaminated fish for testing – from around ports,military bombing ranges, and where they noticed eco-logical impacts. After much reiteration that the projectwas supposed to model the average consumer experi-ence, most people maintained their trajectory butexpressed the need for other areas of testing. Onegave me sponge crabs and asked – as a personal favor– if I could test them because his family considers thesponge a delicacy and he knew eggs sometimes seques-ter toxins. In cases like the sponge crab, we used extralaboratory resources to accommodate the request butdid not include them in project analysis.

In each case of in-the-field negotiation, wereferred back to the original grant proposal andthe official protocols referenced within (USEPA1998; Lasrado et al. 2003) which laid out pointswhere standardization was crucial, and opportu-nities for adapting to field conditions. Since thisprotocol was jointly negotiated between the origi-nal four project initiators, later participants gener-ally accepted it and understood their personalquestions could only be addressed as allowed byadditional resources. Methodology is often wheretranslation between knowledge groups limits thequality of participation (Johnson 2011). In this

case, having a document of agreed-upon methodswritten in simple language limited the need forspur-of-the-moment translation.

Exploding coils and other technological hiccups:lab analysis

Normally, a well-funded participatory science projectwould send fish tissue samples to a contract lab andreceive an email several months later with data from thedesired chemical analysis. Our project, however, wasalso supposed to support graduate and undergraduatetraining and operated on a small budget. These traineesperformed the laboratory analyses under the supervi-sion of our scientific partners using the EPA standardprotocol formercury (EPA 2002) and a commercial kit forPCBs. Standard protocols like these are considered cri-tical to maintain trust in collaboratively produced data(Mueller, Tippins, and Bryan 2012).

However, questions still arise during these ‘stan-dard’ protocols. Our project took longer than expected,and this longevity forced us to make decisions overwhether method calibrations established at the begin-ning of the study were still valid. There is also room forinterpretations (and mistakes) in the protocols. Forexample, protocols do not dictate a standard numberof replicate analyses to run to account for proceduralvariation. Such decisions were handled by the labdirector of the mercury and PCB labs with the traineedoing the analysis, but not with the full suite of projectparticipants. For more detail on these occurrences, seeBoxes 2 and 3 for mercury and PCB, respectively. It isworth noting, however, that with many collaborativeprojects, these decisions would have happened in con-tract labs away from all participants.

Box 2. Mercury analysis with different catalyst tubesFor those familiar with analytical chemistry, the complex innerworkings of the specialized machines involved are no surprise. Noris it surprising when that complexity means that a simple mistakeor broken part takes weeks to fix. For us, this lesson started whenthe direct mercury analyzer (DMA-80, made by Milestone Inc.),loaded two boats full of sample at the same time. These little metalboats, about an inch long and made of thin sheets of nickel, load40 at a time onto a ring, each filled with a different sample offreeze-dried, ground fish tissue. The ring rotates after each sampleso an automated arm can pick up the next boat and deliver it tothe analytical chamber, where the sample is vaporized. The vapor iscarried through a catalyst tube by pure oxygen gas, whereinterfering chemicals are captured and mercury sticks to a goldamalgamator. Elemental mercury is again vaporized, illuminated bya lamp and measured by a spectrophotometer. When two boatsgot loaded at the same time, one boat pushed the other into thecatalyst tube where interfering chemicals are sequestered. Thistechnological hiccup meant the catalyst tube cracked and releasedan unknown amount of said interfering chemicals inside themachine. The lab director ordered the new tube from the machine’scompany in Italy, stating they usually have extras lying about forwhen this happens. She had no idea what made the machinedecide to load two boats or what difference there might bebetween catalyst tubes. A month later, the machine was fixed,calibration protocol decided, and we were able to analyze the restof the samples.

ENVIRONMENTAL SOCIOLOGY 5

Chasing interpretations

Due to the independent personalities of most of theparticipants, all but three preferred to discuss results inone-on-one meetings, initially claiming remoteness oftheir towns and working waterfronts as why. However,meeting one-on-one also helped fishermen digest theinformation in relative privacy, ask questions comfortably,and tie the specifics of their life to the data at large; theylater reflected this could not happen in a group setting.

Given that this is the single largest drop in participa-tion in the project, this is a good place to discuss a loss inparticipation over the course of the research. Participantretention is a common challenge in all citizen science,and our rates were on par with other large-scale projects(Nov, Arazy, and Anderson 2014). First, participation wasmostly interest driven instead of application driven,therefore, harder to garner motivation for participation(Selman et al. 2010). Most cited curiosity as their motiva-tion to participate, therefore, a drop when competingactivities arise is expected. The laboratory analysis tookbetween 6 and 12 months after initial collection trips, atime period long enough for curiosity to wane (Hoppe2005). In addition, not all participants may have felt theyhad analysis to contribute. Especially with regard tohealth issues, statistics and data analysis is perceivedby society to be the realm of experts formally trainedto make health decisions (Karnieli-Miller, Strier, andPessach 2009); several participants expressed this con-cern with ‘I’m no doctor. . .’.

Looking at the project data, participants had trou-ble deciding what level of contaminant qualified as‘high’. Specifically, they had a hard time separatinghigh levels for a species versus high levels overall. Thiswas supported by the notion that ‘we’ve got a depart-ment of water quality – we’re one of the highest[rated] bodies of water in North Carolina. . . then it’shard to see how you’d have contaminants’. Statedesignations of ‘outstanding resource water’ ledsome to ‘consider this area to be, the fish living in itwould be healthy and there shouldn’t be a whole lot

of mercury or PCB present or contaminating any-thing’. Overall, participants had high expectationsand didn’t differentiate types of pollution, as ‘all pol-lution is bad and it’s all kind of on an equal footing’.

Converting raw data into actionable conclusionsrequires an understanding of system complexity andrisk assessment probability, an exercise no one involved– including consulting scientists – was willing to com-pute. The answer for each person as to whether theseafood was safe depended on total consumption – ofwhat species, how often, and whether they fed children.Participants found this calculation, through an exampleequation provided by Environmental Defense Fund(Fitzgerald, pers. comm.), troubling, over-simplistic, andfull of assumptions. One participant, when asked abouthis conclusions from the data, said there’s ‘no way I cananswer that. I don’t have the knowledge or the educationto answer that. I mean I’m not a doctor, I can’t tell aperson what they can eat and what they can’t’. All ofthis complexity gets boiled down to government recom-mendations, like as one participant concluded ‘there maybe an upper level where you shouldn’t eat it at all, I don’tknow if that’s posted or not’. Some thresholds are postedby EPA, FDA, and NGO groups, but they’re all different formercury – 0.3 ppm, 1 ppm, and 0.2 ppm, respectively (USEPA 2012; FDA 2000; EDF 2011). With the exception ofsome known polluted areas, locations averaged less thanthe lowest recommended levels. Therefore, whenpushed, all came to the conclusion that the data are‘low enough so that I don’t think they present a big riskto people of eating’ unless they are subsistence fishers(our final published conclusion, in Freitag et al. 2012).

The mapping activity was easier for participants,where contaminant levels were color coded relative toaverage for that species and depicted as points on aregional map (see Figure 2). Participants were mostconcerned about personal samples and connectedmore contaminated areas with local human activity,the data confirming what they had noticed throughshifts in the local ecology. Examples include changesafter the Intracoastal Waterway was dug and how thenegative influence of riverine inputs ‘definitely showsyou that the rivers are your problem’. Some of the ‘hot-spots’ had no explanation in local knowledge, vexationembodied in questions like ‘so I wonder what’s going onin the mid part of Albemarle Sound’. But the variationwas expected, as ‘[participants] would have thoughtthere would have been areas that were higher and Iguess those areas would probably be kind of the indus-trial areas, kind of Newport River and around here withthe port and the history of industry’. The most commonquestions queried the relationship between contami-nants in the sediment and levels in the fishery(Figure 3). Everyone who asked this question usedmap data to conclude that the two are unrelated – butthen wanted to know what dynamics mediated therelationship between sediment and fish, as yet an

Box 3. PCB analysis protocol optimizationThe PCB analysis relied on an undergraduate working betweenother classes. She had a month of time to focus on the project,which meant that she spent most of that time in a laboratorybuilding frequently called the ‘bunker’ of the campus. She had oneopportunity to experience fieldwork with one of the crabbers intown who was having health problems so shortened his days. Afterspending just a few hours in the field, she finally understood theproject with the community and fishery context. The pinkish-whitefluffy tissues she had been extracting for weeks finally connected toreal fish, fishermen, and places. Meanwhile, as any toxicologist willtell you, the first time you try a method is rarely perfect. It’s best topractice on a sample you have an abundance of or somethingsimilar that isn’t needed for the project. This case was no different –the kit’s instructions still left room for mistakes and we made quitea few of them. Luckily, we had more than enough extra sample, butwe needed to order one extra kit (at the cost of $1250) toaccommodate this learning. All of this method refining, however,was done on the spot by scientists (lab advisors) with littleconsultation from the fishermen.

6 A. FREITAG

unresolved question in the scientific literature (Aiken,Hsu-Kim, and Ryan 2011).

Participants wanted to know what happened nextwith the completed data set, the immediate practicalapplication. A few already had their own plan for usingthe data, like rebutting ‘people tell me don’t eatoysters because of the contamination concerns, nowI’ve got proof to eat my friggin’ oysters’. This commentreflects the utility of such data to local marketingefforts. One participant said ‘I already use the highwater quality standard that we already have in ourarea as a market tool and NC as a whole, but havingsomething like this behind you to say tests have beendone, sampling’s been done’ is even more helpful. Thedata is currently publicly available through the stategeospatial database, which participants thought usefulfor them but didn’t think would result in any manage-ment changes.

The end game: vanishing outreach finances and adistant horizon for continuity

Our funding source was a limited resource meant tofund small, exploratory projects for 1 year. Conversely,most collaborative projects are long-term efforts with

continued volunteer recruitment and relationshipbuilding (Newman et al. 2011). Given the structure ofour funding, we designed the research with a distinctend, where participants could take a deep breath anddecide if they wanted to continue thinking about con-tamination issues during a final workshop. The largenumber of requests from fisher participants to studyindividual questions, suggests that motivation couldbe maintained for a larger but more diffuse effort.

The optional final workshop was attended by 11participants. During an initial introduction period atthe workshop, participants – both scientists and fishers– rekindled long-term relationships and quickly decidedthat the one-on-one meetings each had participated inalready covered all possible discussion of mercury andPCBs. We all gave a quick update informally over dinnerand moved on to the second task of the workshop –establishing a new participatory science endeavor tolook at pesticides in nursery grounds. Like trust, fundingand flexibility determine access to and comfort withcollaborative research; the workshop offered the spaceto creatively plan new research and continue relation-ship building between a new network of colleagues. Thepesticide question was only one of several follow-onprojects initiated by new collaborators. Three newgroups submitted grant proposals for new projects

Figure 2. Sampling locations for the mercury and PCB study. Stars designate the original 4 fishery collaborators in the city ofWilmington and towns of Columbia, Smyrna, and Swanquarter.

ENVIRONMENTAL SOCIOLOGY 7

and at least 10 participants jumped to other citizenscience projects in the region (oyster restoration, larvalmonitoring, gamefish stock assessments, and others), inaddition to the team working on the pesticide question.

Discussion

Here, we take a step back to return to the key elementsof participation discussed in the introduction. Theseelements cut across all stages of the research processand serve both as important determinants of qualityparticipation and considerations for future programdesign. Note that the factors are interrelated and aretherefore discussed in tandem. The nature and impor-tance of these interactions may prove an interestingtopic of further study. First, we discuss the key ele-ments and then discuss how these elements contributeto existing theory on collaborative research design.

Forks in the research road: critical negotiationsand dissent

The first decision, and also the first controversy, revolvedaround the resolution of spatial data collectedwith eachsample. While ideally, each fish would be GPS tagged as

it was caught, there were biological reasons and socialreasons this became infeasible. First, the finfish in thestudy swim over a range much larger than the averagefishing route, so noting location at the point of nettingmay not accurately describe where the fish encounteredthe chemical contamination. One of the participantspointed out that a shrimp he tagged once in centralNorth Carolina was later caught in Northern Florida. Theother reason stems from the small boat logistical chal-lenges, where hand drawn dots on maps created at thedock at the end of the day is the best we could do.Collectively, using these facts, we decided that approx-imations using printed local maps would be adequatespatial resolution.

Another decision relates to level of participation:determining the frequency of communication andreminders for group activities. Many participants didnot have regular access to the internet, and otherspreferred not to talk by phone; either way. Afterverifying feasibility, I implemented a standard com-munication rule: try 3 times for each participantthrough at least 2 different forms of communicationfor each group event. If I heard nothing, I followed upwith a summary in the mail and listed contact infor-mation should they want to get in touch with me andcatch up. This was entirely a personal decision and

Figure 3. The most common query of the map layer exercise – how mercury levels in the sediments compared with thosemeasured in fish tissue during the project. The overall consensus is that the relationship is tenuous at best.

8 A. FREITAG

depending on personality, other facilitators couldhave put forth very different efforts; lack of negotia-tion here may have cost some participation.

One structural decision elicited the critique fromone participant that the spatial distribution of sam-pling seemed patchy and favored populated areas.Much of the eastern part of the state is sparselypopulated if at all, large tracts of land dedicated toNational Wildlife Refuge or large industrial farms.These areas did not get sampled because almost noone fishes there. His point was well taken, as theNational Wildlife Refuges are peat bog, which scientistteam members reported as a natural source of mer-cury leachates and long-standing farmland was likelydosed with mercury and lead arsenate pesticides inthe early part of the 20th century so fish may bepicking up contamination from these areas. This con-versation inspired an undergraduate research projectto take a closer look at reserve lands.

Access and technology

Access proved to be both logistical and intellectual.Small-scale fishing boats proved challenging platformsfor collaborative research and sparsely distributed par-ticipants made communication difficult. However,these were easier to overcome than access to scientificjargon. The role of technology in this case helped easecommunication, by providing geospatial languageeveryone was familiar with and online spaces to shareresults. This shonemost in what happened with results.

Many participants wondered something like, ‘sowhat are you going to do with all this’? People tookownership, especially of the data from their fishing routeand grounds, and shared the handout I gave them withbusiness colleagues and family. One participant whoalso owns a retail store said ‘I’m going to post this forcustomers to see that, so I’m going to actually put it onthat window to show [my seafood’s] safe’. The theme ofsharing the information with customers, especially forparticipants who sold to a relatively educated clientele,emerged repeatedly despite most people saying they’rerarely directly asked about contaminants.

The Walking Fish Community Supported Fisheryposted the resulting journal article on their websitefollowing a link ‘Is NC Seafood Safe to Eat’? with mycontact information for customers with questions.One participant stated ‘I’m trying to get a vendorlicense with Whole Foods Market and I need all thehelp I can get’, folding the handout of data into hisapplication packet. The fact that the scientific publica-tion with my contact information was shared widelyhints at perceived expertise in science (Gibbs 2001)and the propensity for multiple kinds of informationto be translated to scientific language, privileging thescientific way of knowing (Johnson 2011) – but in this

case, scientific language proved useful to both typesof participants.

Facilitating rural fishery research

Collaborative science theoretically removes the role ofthe expert in scientific inquiry, where each participantcontributes their own expertise and authority is nego-tiated (Callon 1995). Distributed information is col-lected and analyzed by a collective; all ideas are giventhought and time for evaluation. This new mode ofscience questions the role of the knowledge producerin a world of no experts. In this case, the expertise wasin serving as facilitator, the communication node –collecting questions and information, digesting it, andredistributing the collection as necessary. In the wordsof Collins and Evans (2002), these are the skills ofinteractional expertise required to utilize the newlyrecognized wealth of distributed knowledge.

In this case, I served as the facilitator, and in thisrole helped navigate challenges of the four key ele-ments. The most apparent of these is access, where Iserved as translator between scientific and experien-tial expertise (as described in Trumbull et al. 2000)and logistical coordinator (described as needed, espe-cially in marine situations, in Cigliano et al. 2015). But Ialso stood witness to all protocol negotiation, eventhe hasty ones (Pretty 1995) and ensured space fordissent (or personal interpretations of results) in dis-tribution of the results (Irvin and Stansbury 2004). Asproject coordinator, I also chose which technologieswe adopted for data interpretation and display, to thebenefit of participation in the case of mapping soft-ware (Bethel et al. 2011).

Lessons for the road

Many citizen science endeavors rely largely on volunteerenergy to collect data but vary in involvement duringother research stages (Bonney et al. 2009). The criticaldecisions made along the way shaped the project butalso showed adaptability in the field, responding toboth cultural and biological demands on the methods.In a way, this increased the quality of participation – therules of engagement were guided but not set in stoneby the original team designing the project (whichincluded multiple ways of knowing, unlike many parti-cipatory projects (Trumbull et al. 2000)), allowing roomfor negotiation. Instead, participants were able to notonly give contributory expertise but also interactionalexpertise (Collins and Evans 2002), which is the type ofexpertise that ended up driving the progress of theproject. One factor – trust – was not predicted in thefour factors from the literature but is an important ele-ment of stakeholder engagement discussions morebroadly, especially in fisheries (Johnson 2011). Given itsneed from day one of the research process, it should be

ENVIRONMENTAL SOCIOLOGY 9

considered a prerequisite in program design beforeconsiderations of access, dissent, negotiations, andtechnology can occur.

Participatory science takes time commitment indeveloping social relations (Lauber et al. 2011) andcoordinating larger numbers of people, more so thanfor laboratory science (Cigliano et al. 2015). This gen-erally results in long-term programs that could run inperpetuity; the best example of this is the NationalWeather Service’s rain gauge program that was madeofficial in 1896, and that relies on volunteers to collectweather data, and more recently, create research ques-tions that can be tested through that data (Doeskenand Reges 2010). However, the short time frame andvisible end of this project had added benefits for parti-cipants, soliciting a certain degree of spontaneous par-ticipation for the pure benefit of knowledge creation(Hoppe 2005). Looking at participatory science as asocial phenomenon, there are not isolated projectseach competing for participant attention; instead,there’s a fluid network of participants who help withor even instigate projects relevant to their interests atthe time. A conscious attention to the quality of parti-cipation (through a prerequisite of trust and metrics ofnegotiation, dissent, access, and technology) to ensureboth integration of knowledge types and innovation ofnew knowledge (goals set forth by Shirk et al. 2012)was key to providing an avenue to empowerment forat least some of the larger group.

Conclusions

The case study presented here highlights key ele-ments that help determine the quality and potentialfor success in integrating and innovating knowledgein collaborative research projects. These, in combina-tion with some research program structure considera-tions, can help collaborative research endeavors plantheir research program or make adjustments to exist-ing programs moving forward. Conscious attentionand program evaluation along the metrics of access,dissent, technology, negotiation, and trust will helpdetermine if participants have the appropriatechances to show their expertise and air concerns.Budget and staffing also emerged as an importantconsideration in order to enable opportunities foraccess, dissent, technology, negotiation, and trustover the desired length of project activities. In theend, collaborative research is shaped by the expertisebut also needs of the diverse worldviews and profes-sional practices incorporated. These concerns shouldbe considered early in the research process to givethe project the best chance of succeeding in meetingthe promise collaborative research has to offer.

Acknowledgments

The author would like to acknowledge all the participants inthis research, who allowed her to document much of theirlife while this project took place. She would also like toacknowledge NC Sea Grant and the Kenan Institute forEthics for funding, as well as the fishermen for donating aportion of their catch. This manuscript also benefitted fromthe careful reviews of Lisa Campbell and Barbara Garrity-Blake.

Disclosure statement

No potential conflict of interest was reported by the author.

Funding

She would also like to acknowledge NC Sea Grant and theKenan Institute for Ethics for funding, as well as the fisher-men for donating a portion of their catch.

Notes on contributor

Amy Freitag research program focuses on ways to incorpo-rate humans and their culture into our understanding ofmarine ecosystems. She is currently part of NOAA's team,which shares this mission. She received her PhD from theDuke University Marine Lab in Marine Science andConservation. Find out more at www.amyfreitag.org.

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