TY - JOUR
T1 - Try, try again
T2 - Lessons learned from success and failure in participatory modeling
AU - Sterling, Eleanor J.
AU - Zellner, Moira
AU - Jenni, Karen E.
AU - Leong, Kirsten
AU - Glynn, Pierre D.
AU - BenDor, Todd K.
AU - Bommel, Pierre
AU - Hubacek, Klaus
AU - Jetter, Antonie J.
AU - Jordan, Rebecca
AU - Olabisi, Laura Schmitt
AU - Paolisso, Michael
AU - Gray, Steven
N1 - Funding Information:
This work was supported by the National Socio-Environmental Synthesis Center (SESYNC) under funding received from the National Science Foundation DBI-1052875. The material is also based upon work supported by the National Science Foundation (NSF) under Grants No. EF-1427091, 1427453, and 1444184. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. In addition, this research was conducted by the Assessing Biocultural Indicators Working Group supported in part by SNAPP: Science for Nature and People Partnership, a collaboration of The Nature Conservancy, the Wildlife Conservation Society and the National Center for Ecological Analysis and Synthesis (NCEAS) at the University of California, Santa Barbara.
Funding Information:
Co-authors of this paper are U.S. Government employees, therefore: Any use of trade, product, or firm names in this publication is for descriptive purposes only and does not imply endorsement by the U.S. Government. We thank Nadav Gazit for comments, technical edits, and graphic design, Don Rosenberry and Collin Lawrence for U.S. Geological Survey technical reviews, and Amanda Sigouin for editing support. We appreciate the helpful comments from two outside reviewers and the thoughtful guidance from the editors. This work was supported by the National Socio-Environmental Synthesis Center (SESYNC) under funding received from the National Science Foundation DBI-1052875. The material is also based upon work supported by the National Science Foundation (NSF) under Grants No. EF-1427091, 1427453, and 1444184. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. In addition, this research was conducted by the Assessing Biocultural Indicators Working Group supported in part by SNAPP: Science for Nature and People Partnership, a collaboration of The Nature Conservancy, the Wildlife Conservation Society and the National Center for Ecological Analysis and Synthesis (NCEAS) at the University of California, Santa Barbara.
Publisher Copyright:
© 2019 The Author(s).
PY - 2019/2/14
Y1 - 2019/2/14
N2 - 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.
AB - 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.
KW - Collaborative modeling
KW - Environmental management
KW - Participatory modeling
KW - Planning
KW - Stakeholder engagement
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U2 - 10.1525/elementa.347
DO - 10.1525/elementa.347
M3 - Review article
AN - SCOPUS:85068069431
SN - 2325-1026
VL - 7
JO - Elementa
JF - Elementa
IS - 1
M1 - 9
ER -