Science with society: Evidence-based guidance for best practices in environmental transdisciplinary work

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Abstract

Transdisciplinary research is a promising approach to address sustainability challenges arising from global environmental change, as it is characterized by an iterative process that brings together actors from multiple academic fields and diverse sectors of society to engage in mutual learning with the intent to co-produce new knowledge. We present a conceptual model to guide the implementation of environmental transdisciplinary work, which we consider a “science with society” (SWS) approach, providing suggested activities to conduct throughout a seven-step process. We used a survey with 168 respondents involved in environmental transdisciplinary work worldwide to evaluate the relative importance of these activities and the skills and characteristics required to implement them successfully, with attention to how responses differed according to the gender, geographic location, and positionality of the respondents. Flexibility and collaborative spirit were the most frequently valued skills in SWS, though non-researchers tended to prioritize attributes like humility, trust, and patience over flexibility. We also explored the relative significance of barriers to successful SWS, finding insufficient time and unequal power dynamics were the two most significant barriers to successful SWS. Together with case studies of respondents’ most successful SWS projects, we create a toolbox of 20 best practices that can be used to overcome barriers and increase the societal and scientific impacts of SWS projects. Project success was perceived to be significantly higher where there was medium to high policy impact, and projects initiated by practitioners/other stakeholders had a larger proportion of high policy impact compared to projects initiated by researchers only. Communicating project results to academic audiences occurred more frequently than communicating results to practitioners or the public, despite this being ranked less important overall. We discuss how these results point to three recommendations for future SWS: 1) balancing diverse perspectives through careful partnership formation and design; 2) promoting communication, learning, and reflexivity (i.e., questioning assumptions, beliefs, and practices) to overcome conflict and power asymmetries; and 3) increasing policy impact for joint science and society benefits. Our study highlights the benefits of diversity in SWS - both in the types of people and knowledge included as well as the methods used - and the potential benefits of this approach for addressing the increasingly complex challenges arising from global environmental change.

Section snippets

Introduction to transdisciplinary or science with society approaches

Global environmental change is driven largely by human activities such as production and consumption patterns, population dynamics, and technological innovations, and has led to a wide array of intractable and interconnected sustainability challenges – including biodiversity loss, food and water insecurity, and pollution (IPBES, 2019). As these challenges increasingly threaten environments and human well-being, science and society are turning to transdisciplinary work (TDW) to facilitate

Theoretical Foundations: A conceptual model for science with society

In July 2015, we convened a workshop in Serre Chevalier, France with 20 researcher and practitioner partners from the Mountain Sentinels Collaborative Network (mountainsentinels.org) who have engaged in environmental SWS around the world. Drawing on peer-reviewed literature and experiences from workshop participants, we developed a new conceptual model to guide the implementation of SWS projects with a focus on knowledge co-production and social learning (Fig. 1). This model is similar to other

Survey design and administration

We used the conceptual model described above to guide the development of a survey (Appendix A). We screened respondents to ensure they conducted SWS that matches our definition of: “sustained engagement between researchers (professional scientists or scholars) and practitioners (e.g., resource users, natural resource managers, policy makers)”. We asked respondents to draw on their overall SWS experience to rank the top three most important activities in each step, and to identify which of these

Results

The survey was available online from April 4 to October 22, 2018, and yielded 139 complete responses. An additional 29 responses were partially complete and used in our analysis where applicable (total n = 168). The number of responses per question varied as responses were voluntary throughout the survey. First we will describe the demographics and geographic patterns of the respondents (Section 4.1). Then we will analyze their insights into the SWS process, including the most desired skills

Discussion

Our results enable us to better understand the process and benefits of environmental SWS, and provide a set of specific activities for a toolbox of best practices. Transdisciplinary approaches are sometimes criticized for drawing on a broad and ill-defined set of methods for knowledge co-production (Brandt et al., 2013), but we believe this diversity is valuable and necessary given the highly context-specific nature of local knowledge (Berkes, 2012). Below, we draw on our conceptual model and

Conclusions

Transdisciplinarity has emerged as an increasingly necessary research approach in environmental sustainability. Our conceptual model of SWS seeks to expand upon existing models to foster deep, place-based understanding and equal benefits for both science and society. This emergent paradigm is particularly essential in this moment, as the world moves to recover and rebuild from COVID-19 and address systemic societal inequalities. The toolbox of 20 activities we present for consideration as best

CRediT authorship contribution statement

Conceptualization (CS; JK; RR; SL; CT; KAK; KH; RM; AN; TD; GG; RH; DK; AR; MSH; GG; MM; BML; MM; DW); Methodology (CS; JK; RR; CT; KAK; ACS; TD; KH; RM; AN; JS; JPRT; TT); Formal analysis (CS; JK; RR; JS; TT); Project administration (CS); Writing - review & editing (CS; JK; RR: SL; CT; KH; RM; TT; ACS; TD; GG; RH; KAK; DK; AN; AR; JS; MSH; JPRT; GG; MM; MM; and DW).

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

This work was supported by the US National Science Foundation through the Mountain Sentinels Research Coordination Network (NSF #1414106) and the Center for Collaborative Conservation at Colorado State University. MSH would like to thank the Slovenian Research Agency for its financial support (Core Research Funding No. P6-010; Geography of Slovenia), and DK acknowledges support by the German Federal Ministry of Education and Research (BMBF—01LN1315A). In addition, we thank the many civil

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