The art of co-production of knowledge in environmental sciences and management: lessons from international practice

Several institutional characteristics (of management agencies, funding agencies, and academic institutions) were common among the cases including management structures, funding mechanisms, and level of support for collaborative research activities.

In two cases, inflexible management structures within the resource management agencies hindered practitioners’ ability to collaborate with the research teams. Procedural requirements in Foley et al. (2017) limited information sharing among project participants. Rules restricting field time kept practitioners from collaborating directly with the research team in the case of Cvitanovic et al. (2016). However, more flexible structures within a sponsoring agency—particularly regarding funding—supported the work of Castellanos et al. (2013) when the research team recognized that they lacked necessary skills in collaborative research. Flexible funding allowed the research team to bring on the skill set they required through a new hire. “[W]e were fortunate to have a funding agency that emphasizes the communication of scientific findings to policymakers and therefore encouraged us to incorporate new approaches and communication experts into the research process; but we recognize that not all funded projects have this opportunity” (Castellanos et al. 2013: 25).

Institutional support can also include providing education and professional development training on knowledge co-production, as described in Cvitanovic et al. (2016: 6), “[…] we need to teach scientists how to gain access to the right people and gain credibility with those people.” Further examples of how institutions can support co-production efforts come from Cvitanovic et al. (2016) and Podesta et al. (2013), who both noted the need for research institutions to formally recognize and promote activities relevant for knowledge co-production in job descriptions and integrate incentives and rewards for high performance in staff performance appraisal.

The cultural norms of an organization or institution help to determine how it prioritizes resources and time, which can affect how it perceives the process of collaborative research. Cvitanovic et al. (2016) and Campbell et al. (2016) each were challenged to reconcile different institutional cultures. Cvitanovic et al. (2016) reported that the efforts and amount of time the researchers in their case study needed to devote to academic outputs and fund raising seemed to reduce the amount of time they had available to properly engage managers and communicate their research findings. In addition, the limited planning time that managers usually face, because of their day-to-day responsibilities, prevented them from “staying abreast of the science,” and contributing to generating new knowledge. Campbell et al. (2016: 1275) point to the need for managers to have “patience to work with researchers, who often operate at slower pace than the customary management timeline.” Campbell et al. (2016) also note that, in one case, building into the project informal “hanging out” opportunities for researchers and managers translated into greater recognition and understanding between the two groups.

Logistical factors flagged in two of the case studies were the issue of geographic distance between researchers and management partners, which can constrain meetings and increase project costs. Cvitanovic et al. (2016) struggled with conducting research in a remote location that lacked internet access and was difficult to reach. The research team reflected that the remoteness prevented managers from sharing resources with scientists and having access to research outputs. Facing a similar challenge, Podesta et al. (2013) utilized information and communication technologies when possible, but still recommended face-to-face meetings to increase active learning.

Five of the case studies identified intrinsic aptitudes, individual proficiencies, and expertise that support successful design and implementation of a research program focused on co-production. A stakeholder in the Cvitanovic et al. (2016: 5) case explained: “everyone involved in the program has to have the ability to talk to people, to be friendly, to be approachable, and to be able to speak in plain English and not just science.” Cvitanovic et al. (2016), Campbell et al. (2016), Kraaijvanger et al. (2016), and Akpo et al. (2015) each provide examples of the ways in which communication, engagement, and facilitation skills among the researchers were crucial in the process of collaboration. Castellanos et al. (2013: 26) provided an example of how lack of these proficiencies hindered their work at the outset, “As typical of many researchers, we lacked experience communicating research results to the general public and policy makers.” As a remedy, the research team needed to add the capacity through hiring an external group to facilitate communication with policymakers and farmers.

Possessing a working knowledge of the decision context of one’s partners in co-production is another key proficiency. Two papers provided examples of the benefits of having resource managers who are comfortable working within a Western science framework (Cvitanovic et al. 2016; Campbell et al. 2016). For example, Campbell et al. (2016) described situations in which managers asked questions in ways that were answerable with scientific studies in one case, which they noted eased the process of producing research knowledge affecting management practices. Researchers having an understanding of local knowledge is also a crucial element; we discuss this issue in greater detail in the Process section.

Cash et al. (2002: 2) defined legitimacy as “how fair an information producing process is and whether it considers appropriate values, concerns, and perspectives of different actors.” While legitimacy is often considered part of the process of co-production, we include it in Inputs because its pre-cursors—trust and relationship-building—may need greater attention at the start of a project, according to five of the case studies.

An example of the role of trust and relationship-building as an Input comes from Foley et al. (2017), who describe the process of attempting co-production work in an area where past research was unsuccessful and damaging to the community, sowing mistrust between local residents and outside researchers. While trust building takes time (Podesta et al. 2013; Castellano et al. 2013), examples of ways to overcome history of mistrust and/or building trust are provided in the cases illustrated in Campbell et al. (2016), including harnessing pre-existing personal and professional relationships, spending time with communities as a participant observer, or participating in community activities. Castellano et al. (2013) established structured feedback mechanisms and created opportunities for open discussion. Akpo et al. (2015) used research site selection as an opportunity to demonstrate how transparency built trust with the local research participants. In that case, it was the local learning group, not researchers, who identified the three candidate sites and then came to consensus about the final site selection.

Three cases addressed the issue of inclusivity, including gender issues, in detail. Kraaijvanger et al. (2016) observed that gender representation affects the involvement of participants and gender diversity supports ideas and knowledge sharing among farmers. In Castellanos et al. (2013), the research team recognized the need for inclusivity, but were challenged to overcome language and culture barriers, such as cultural norms that dissuaded women from speaking in the presence of men and a language barrier between researchers and local participants. Akpo et al. (2015: 374) addressed a similar situation and reported, “We paid particular attention to the language issues and made sure that enough time was taken to share different ideas and gain mutual understanding. Participants were encouraged to use the local language (Nagot) instead of French, as it is the one all participants understood. The language issue was also concerned with the way participants understand and express the objects being tested.”

Setting-up is discussed in three papers as the moment when the work of building the research team begins. First, it is important to ensure that the research team possesses the appropriate expertise and experience to carry out the work (as discussed in the Inputs section). Kirono et al. (2014: 360) describe circling back to reconsider team composition after defining the research questions: “The process of assembling the research team was driven by the range of tasks and approaches envisioned during project development.” Podesta et al. (2013) recruited a new team member after the research question had been defined because a proposal reviewer noted they lacked expertise in decision-making under uncertainty.

Experience with collaborative and participatory research was also considered in team composition in several cases. Podesta et al. (2013: 40) stressed the importance of “recruiting [a disciplinarily diverse team of] investigators with an open attitude toward interdisciplinary interaction.” Castellanos et al. (2013) suggest using the Setting-up time to foster a common language and shared understanding among the research team in order to create an environment that favors the interdisciplinary collaboration that supports co-production work.

Five of the case studies identify a Development and Design component in which the project is designed collaboratively in order to incorporate the different values, interests, and insights of all the identified relevant stakeholders as well as the different scientists (Cvitanovic et al. 2016; Akpo et al. 2015; Kirono et al. 2014; Podesta et al. 2013; Castellanos et al. 2013).

Other aspects of this component include co-conceptualization, co-definition of methods, and co-planning. Three cases illustrated how co-developing research questions aligned the research with stakeholder priorities. Akpo et al. (2015: 372) conducted preliminary field visits in order to explore stakeholders’ perceptions about the seedlings the research team had proposed to focus on. Kirono et al. (2014: 360) needed to redefine their question “[a]s a result of the stakeholder consultation… to focus more strongly on climate change impacts on regional surface water resources and on adaptation options.” Cvitanovic et al. (2016: 4) illustrated what can happen when co-development does not occur. Some participants in that study remarked that “Some of the research that had been done really wasn’t what was needed … it was what the researchers wanted rather than the management agencies […] you have to have all of the different agencies and end-users, including traditional owners, at the table prioritizing what needs to be done.”

Four papers discuss ways to co-define research methods, instruments, and analytical frameworks (Akpo et al. 2015; Kirono et al. 2014; Castellano et al. 2013; Podesta et al. 2013). For example, Akpo et al. (2015) worked with all the practitioners involved to collectively agree to use the farmers’ criteria to measure successful plant nursery practices; reasoning that farmers are the people who ultimately will purchase the seedlings. Similarly, Podesta et al. (2013) and Kirono et al. (2014) incorporated stakeholders’ inputs in their co-modeling. Stakeholders’ regular reviews of an agent-based model of agricultural production was necessary to enhance model transparency, and to ensure “face validity” of concepts and features (Podesta et al. 2013).

Finally, two papers note the need to integrate the stakeholders into the project planning efforts such as managing financial decisions. Podesta et al. (2013) reflect that an equitable allocation of budget and resources may emerge from a process involving all project participants during the project design stage, while participants in Cvitanovic et al. (2016) attributed the perceived lack of meaningful engagement and collaborative activities to poor planning of knowledge co-production strategies during the program’s development.

The implementation phase is what we often consider the heart of the co-production processes because it is where the research team and stakeholders most actively collaborate to undertake the research. Three key aspects of implementation are the consistent use of engagement activities, appropriate communication strategies, and integration of local knowledge to increase usefulness. The cases also provided examples of specific research methods useful in collaborative research.

Engagement between researchers and stakeholders is the foundation of co-producing knowledge. Young et al. (2016) explain that stakeholders seek different information depending on their position (social, economic, employment, gender, among others), and this affects the manner in which they prefer to engage with researchers, which is reflected in examples from the case studies. Five of the cases provided examples of working within existing community structures to maximize outreach and engagement (Cvitanovic et al. 2016; Kraaijvanger et al. 2016; Foley et al. 2017; Akpo et al. 2015; Kirono et al. 2014). This approach included identifying the local “champions and leaders”—locally influential people (Kirono et al. 2014)—who could identify and make connections with the most relevant local participants. Although starting with local leaders can be effective, three of the cases (Kraaijvanger et al. 2016; Akpo et al. 2015; Foley et al. 2017) discuss the importance of democratizing engagement, or being aware of the ways in which local power structures can inhibit diverse participation. Akpo et al. (2015: 373–374) “made sure that all participants expressed their opinions on the ongoing activities. We [They] intervened in such way that the process was democratic and not dominated by any single stakeholder. We [They] encouraged all participants, particularly illiterate farmers, to speak out their mind…” Foley et al. (2017) encountered power asymmetries among the stakeholder groups, including uneven distribution of knowledge, resources, and decision-making power, and reflected that failure to overcome them can lessen the quality of the engagement.

Some cases directly address the role expertise bias (on the part of the researchers) may play in shutting down engagement because participants may feel that they lack that particular type of knowledge (Kraaijvanger et al. 2016; Akpo et al. 2015; Foley et al. 2017). Kraaijvanger et al. (2016) and Akpo et al. (2015) suggest that scientists should often step back, act mostly as observers when the stakeholders are active, and focus on facilitating participatory activities. One way to address expertise bias, as well as ensure the research is useful to local practitioners, is to integrate diverse types of knowledge into the research (Kraaijvanger et al. 2016; Akpo et al. 2015; Castellanos et al. 2013). For example, Akpo et al. (2015) recognized the need to focus on the actual seedling production practices of the local nursery holders, rather than research-recommended practices, because the local methods were more useful to local producers.

Communication is often only considered as a tool to disseminate research results (as discussed in the Output management and dissemination component below). However, seven of the case studies point to its role in strengthening stakeholder engagement (Cvitanovic et al. 2016; Young et al. 2016; Foley et al. 2017; Akpo et al. 2015; Kirono et al. 2014; Castellanos et al. 2013; Podesta et al. 2013). Effective communication determines the quality of facilitation, mediation, and negotiation approaches. Effective communication includes addressing language gaps between and among the stakeholders and researchers, which required the use of interpreters, knowledge brokers, or boundary organizations in four of the case studies (Cvitanovic et al. 2016; Young et al. 2016; Podesta et al. 2013; Castellanos et al. 2013). Two cases used alternate education tools, including drawing and visual representation (Young et al. 2016; Akpo et al. 2015). For example, Akpo et al. (2015) translated their experimentation protocol into drawings based on signs and symbols familiar to stakeholders, which allowed them to more easily follow the experimentation requirements in their plots. The research team also may encounter communication challenges among themselves, such as disciplinary language differences, as discussed in the setting-up component above. Castellanos et al. (2013: 23) provided an illustration from their project; “Although the social scientists knew the theoretical approach, natural scientists invited to participate in the team had to learn the terminology and theoretical framework on vulnerability and livelihoods,” and then discussed the challenges associated with finding a common language and integrating the interdisciplinary team.

Collaborative research methods were common across the cases. Here we highlight several specific examples of approaches to collaborative research. Podesta et al. (2013) used participatory modeling to develop an agent-based agricultural model. Cvitanovic et al. (2016) used citizen science approaches as a way to include decision-makers in the research and promote a sense of ownership of the research. Kraaijvanger et al. (2016) and Akpo et al. (2015) used participatory experimentation to ensure that researchers were not the sole leaders of the project. Castellanos et al. (2013) used a suite of methods, underscoring their interdisciplinary approach: (1) qualitative consultations and interviews with key informants, (2) a household-level survey, (3) remote sensing analysis, (4) community engagement and participatory workshops to consult with farmers on the findings, and (5) participatory confirmatory analysis to ensure the findings were valid. Akpo et al. (2015) used a series of restitution workshops in which feedback on the progress of the work was provided to keep participants updated on the research project.

An overarching theme among the cases was the need to be flexible about the ways in which projects are implemented. For example when stakeholders working with Podesta et al. (2013: 44) felt frustrated by the time required in meetings to keep all participants abreast of project developments, the research team “replace[d] extended plenary meetings with short, tailored updates to individual investigators or groups by the project coordinator.”

Co-production of knowledge does not end with the engagement and communication activities, according to three of our case studies (Cvitanovic et al. 2016; Young et al. 2016; Castellanos et al. 2013). Rather, the Process stage expands to include managing and communicating the outputs so that the research products are accessible to stakeholders. As Castellanos et al. (2013: 23, 26) explain, this component is often overlooked: “Most academics have little training in how to communicate research results to stakeholders, and usually they do not receive scientific recognition for such effort… Research projects rarely incorporate communication strategies from their inception.”

Outputs that are in formats accessible and available to stakeholders increase the usability and salience of the co-production research results. Cvitanovic et al. (2016) highlighted several elements that may undermine research knowledge dissemination, including outputs that are unclear and/or that fail to clearly articulate the implications of the findings, outputs that are not consolidated and easily findable, or outputs that are not accessible to those people who are in position to use them. Stakeholders in the Cvitanovic et al. (2016) study had specific requests for a searchable, regularly updated, archival database with interactive GIS maps and expressed frustration that those were not available (Cvitanovic et al. 2016).

Several cases point to the importance of making research relevant by translating the science into language commonly used by local stakeholders. Castellanos et al. (2013) used a communication specialist to translate their research outputs. Another technique, used by Young et al. (2016: 177) was story-telling, which “goes beyond substituting jargon with lay terms. Story-telling means using narrative devices such as plots, characterizations, and in-depth descriptions to connect scientific findings with the interests, values, and priorities of potential users.” Castellanos et al. (2013) used a puppet play in a similar fashion. Other examples from the case studies included providing frequent research summaries to key participants (Akpo et al. 2015), identifying and using appropriate dissemination channels (Castellanos et al. 2013), and creating multiple versions of outputs to meet multiple stakeholder needs (Castellanos et al. 2013). Castellanos et al. (2013) ultimately created reports in lay language, a puppet play, used calendars to display key findings, and created radio messages to broadcast to key communities.

Changes in practice relate to both changes in research practices and management practices. Cvitanovic et al. (2016), Kirono et al. (2014), and Podesta et al. (2013) all discuss creating opportunities for researchers (including students) to develop skills relevant to collaborative processes as an important outcome of a co-production process. Cvitanovic et al. (2016) and Akpo et al. (2015) also highlight opportunities for social learning, through development of researchers-practitioners networks, as an intangible benefit to both researchers and stakeholders.

Resource managers and other end-users can also develop beneficial management practices —from intangible to tangible—following their participation in a collaborative research project. Intangible benefit is the extent to which local collaborators are empowered and gain knowledge and new skills through the co-production process. Akpo et al. (2015) noted that the joint experimentation process has increased the participating stakeholders’ use of research processes and curiosity about specific agricultural and environmental management knowledge. With their participatory experimentation, both Kraaijvanger et al. (2016) and Akpo et al. (2015) have observed changes in farmers’ agricultural management-related literacy, network building, organizational skills, monitoring capacity, and farm experimentation skills. Similarly, Castellanos et al. (2013) noted that organizing small group activities in the villages, designed to encourage farmers to educate each other as well as scientists about local knowledge, was effective.

While tangible beneficial change is the ultimate goal of knowledge co-production particularly in the sector of climate change adaptation, such changes can take time and are affected by multiple factors often unrelated to the research project. However, Kraaijvanger et al. (2016) were able to track increased crop productivity and positive financial capital change after their project. Akpo et al. (2015) reported some changes in seedling production practices by nursery holders and new management methods instituted by the participating extension agent.

Cvitanovic et al. (2016) reflect on the need to foster collateral positive impacts (both unplanned and indirect positive impacts). For instance, improvement of tourism sector development and opportunity was an unexpected impact of their co-production work.

The intangible, tangible, and collateral benefits reported above from the cases demonstrate how the authors assessed whether their research findings were salient to the end-users. Akpo et al. (2015: 383–384) attributed the observed changes in seedling production and management practices to the research model and process, “[t]he observed changes in practices on the different participants could be explained by their full involvement in the research from the problem identification to the experiment implementation, and monitoring & evaluation.” Caution should, however, be taken in both directly attributing positive changes to a specific research project or in judging a project’s success solely based on tangible changes in practice. In some cases, researchers acknowledged the success of the process and social learning as outcomes rather than an actual impact of practical changes from knowledge co-production. Castellanos et al. (2013: 26) stated that “we can conclude with confidence that our research dissemination strategy was effective for those stakeholders… ultimately our success was in communication rather than knowledge co-production.”