Try, try again: Lessons learned from success and failure in participatory modeling

Abstract

Participatory Modeling (PM) is becoming increasingly common in environmental planning and conservation, due in part to advances in cyberinfrastructure as well as to greater recognition of the importance of engaging a diverse array of stakeholders in decision making. We provide lessons learned, based on over 200 years of the authors’ cumulative and diverse experience, about PM processes. These include successful and, perhaps more importantly, not-so-successful trials. Our collective interdisciplinary background has supported the development, testing, and evaluation of a rich range of collaborative modeling approaches. We share here what we have learned as a community of participatory modelers, within three categories of reflection: a) lessons learned about participatory modelers; b) lessons learned about the context of collaboration; and c) lessons learned about the PM process. First, successful PM teams encompass a variety of skills beyond modeling expertise. Skills include: effective relationship-building, openness to learn from local experts, awareness of personal motivations and biases, and ability to translate discussions into models and to assess success. Second, the context for collaboration necessitates a culturally appropriate process for knowledge generation and use, for involvement of community co-leads, and for understanding group power dynamics that might influence how people from different backgrounds interact. Finally, knowing when to use PM and when not to, managing expectations, and effectively and equitably addressing conflicts is essential. Managing the participation process in PM is as important as managing the model building process. We recommend that PM teams consider what skills are present within a team, while ensuring inclusive creative space for collaborative exploration and learning supported by simple yet relevant models. With a realistic view of what it entails, PM can be a powerful approach that builds collective knowledge and social capital, thus helping communities to take charge of their future and address complex social and environmental problems.

Socio-technical scales in socio-environmental modeling: Managing a system-of-systems modeling approach

“…Success of a model depends on the beliefs and expectations of the intended users and in their satisfaction with the model and its results ( Hamilton et al, 2019 ). It may also depend on the biases and beliefs of the model creators ( Glynn et al, 2017 ) and in an alignment of expectations between creators and users ( Sterling et al, 2019 ). The suitability of the success criteria is dependent on the context of the project, including not only the model purpose, but also the characteristics of the problem, such as its complexity and the resources that were available ( Hamilton et al, 2019 ).…”

Toward a complete interdisciplinary treatment of scale

“…Model outcomes are therefore heavily influenced by the social context of the modeling process as well as the technical decisions made therein. Future efforts can be improved by concretely acknowledging this interplay (Catalano et al, 2019;Sterling et al, 2019;Montana et al, 2020). A sociotechnical view was taken to elicit these aspects in the reflexive process.…”

“…Although the number of steps and activities conducted may differ depending on purpose and Art. 9(1) page 18 of 28 Iwanaga et al: Treatment of scale in socio-environmental systems modeling conceptualization of the cycle (Boehm, 1986;Jakeman et al, 2006;Pianosi et al, 2016;Badham et al, 2019;Arnold et al, 2020;Zare et al, 2021), each step is intended to be revisited as often as needed to incorporate newly discovered or available knowledge, or ideas generated on deep reflection, as "[t]he first model is rarely the best model" (Sterling et al, 2019). It may at times be necessary to abandon an iteration and start over.…”

“…Interdisciplinarity is now recognized as a crucial necessity in understanding and dealing with the complexity of socioenvironmental interactions (Hall et al, 2012;Saltelli and Funtowicz, 2017;MacLeod and Nagatsu, 2018;Sterling et al, 2019). Challenges to a successful modeling process and set of outcomes necessitate effective collaboration, teamwork, and cross-disciplinary communication and discussion of a high order among team members (Nancarrow et al, 2013;Hall et al, 2018).…”

How to make socio‐environmental modelling more useful to support policy and management?

“…Several methods of citizen engagement have proven to be effective including interviews, focus groups, scenario workshops, citizen science and digital participation (Šucha & Sienkiewicz, 2020). In the context of modelling, various studies show the demand for stakeholder participation with a focus on participatory modelling (Voinov & Bousquet, 2010;Voinov et al, 2016) where different approaches have been reviewed (Sterling et al, 2019;Voinov et al, 2018), classified (Barreteau et al, 2017) and standardised (Gray et al, 2018;Seidl, 2015).…”