Recognizing political influences in participatory social-ecological systems modeling
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participatory modeling
science policy
evidence-based policy
boundary objects
watershed management

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Lim, T. C., Glynn, P. D., Shenk, G. W., Bitterman, P., Guillaume, J. H. A., Little, J. C., & Webster, D. G. (2023). Recognizing political influences in participatory social-ecological systems modeling. Socio-Environmental Systems Modelling, 5, 18509.


Stakeholder participation in social-ecological systems (SES) modeling is increasingly considered a desirable way to elicit diverse sources of knowledge about SES behavior and to promote inclusive decision-making in SES. Understanding how participatory modeling processes function in the context of long-term adaptive management of SES may allow for better design of participatory processes to achieve the intended outcomes of inclusionary knowledge, representativeness, and social learning, while avoiding unintended outcomes. Long-term adaptive management contexts often include political influences -- attempts to shift or preserve power structures and authority, and efforts to represent the political and economic interests of stakeholders -- in the computer models that are used to shape policy making and implementation. In this research, we examine a period that included a major transition in the watershed model used for management of the Chesapeake Bay in the United States. The Chesapeake Bay watershed model has been in development since the 1980s, and is considered by many to be an exemplary case of participatory modeling. We use documentary analysis and interviews with participants involved in the model application and development transition to reveal a variety of ways in which participatory modeling may be subject to different kinds of political influences, some of which resulted in unintended outcomes, including: perceptions of difficulty updating the model in substantive ways, “gaming” of the model/participatory process by stakeholders, and increasing resistance against considering uncertainty in the system not captured by the model. This research suggests unintended or negative outcomes may be associated with both participatory decision-making and stakeholder learning even though they are so often touted as the benefits of participatory modeling. We end with a hypothesis that further development of a theory of computer model governance to bridge model impact and broader theories of environmental governance at the science-policy interface may result in improved SES modeling outcomes.
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Akerlof, G.A., 1997. Social Distance and Social Decisions. Econometrica 65, 1005–1027.

Armitage, D., Marschke, M., Plummer, R., 2008. Adaptive co-management and the paradox of learning. Glob. Environ. Change 18, 86–98.

Arnold, T., Guillaume, J.H.A., Lahtinen, T.J., Vervoort, R.W., 2020. From ad-hoc modelling to strategic infrastructure: A manifesto for model management. Environ. Model. Softw. 123, 104563.

Arnstein, S.R., 1969. A Ladder Of Citizen Participation. J. Am. Inst. Plann. 35, 216–224.

Band, L., Dillaha, T., Duffy, C., Reckhow, K., Welty, C., 2008. Scientific and Technical Advisory Committee: Chesapeake Bay Watershed Model Phase V Review (No. 08–003).

Berg, B.L., Lune, H., 2011. Qualitative Research Methods for the Social Sciences, 8th edition. Pearson, Boston.

Bicknell, B.R., Imhoff, J.C., Kittle, J.L., Donigan, A.S.Jr., Johanson, R.C., 1997. Hydrological Simulation Program--Fortran: User’s manual for version 11 (No. EPA/600/R-97/080). U.S. Environmental Protection Agency, Athens, GA.

Booher, D.E., Innes, J.E., 2010. Governance for Resilience: CALFED as a Complex Adaptive Network for Resource Management. Ecol. Soc. 15.

Cash, D., Adger, W.N., Berkes, F., Garden, P., Lebel, L., Olsson, P., Pritchard, L., Young, O., 2006. Scale and Cross-Scale Dynamics: Governance and Information in a Multilevel World. Ecol. Soc. 11.

Cash, D.W., Clark, W.C., Alcock, F., Dickson, N.M., Eckley, N., Guston, D.H., Jäger, J., Mitchell, R.B., 2003. Knowledge systems for sustainable development. Proc. Natl. Acad. Sci. 100, 8086–8091.

CBP, 2014. Chesapeake Watershed Agreement. As amended Jan 24, 2020.

CBP, 2021. Governance and Management Framework for the Chesapeake Bay Program. October 7, 2021.

CBP, 2023a. How We’re Organized: Scientific, Technical Assessment and Reporting (STAR): Modeling Workgroup [WWW Document]. URL (accessed 2.12.23).

CBP, 2023b. How We’re Organized: Water Quality Goal Implementation Team (GIT 3) [WWW Document]. URL (accessed 2.12.23).

CBP, 2023c. Learn the Issues: Population Growth [WWW Document]. Chesapeake Bay Program. URL (accessed 3.10.23).

CBP, 2023d. The Chesapeake Bay Program [WWW Document]. Chesapeake Bay Program. URL

CBP STAC, 2011. Review of the LimnoTech Report “Comparison of Load Estimates for Cultivated Cropland in the Chesapeake Bay Watershed” (No. 11– 02). Edgewater, MD.

Charmaz, K., 2014. Constructing Grounded Theory, Second edition. SAGE Publications Ltd, London; Thousand Oaks, Calif.

Cialdini, R.B., Goldstein, N.J., 2004. Social Influence: Compliance and Conformity. Annu. Rev. Psychol. 55, 591–621.

Colding, J., Barthel, S., 2019. Exploring the social-ecological systems discourse 20 years later. Ecol. Soc. 24.

Cooke, B., Cooke, P.B., Kothari, U., 2001. Participation: The New Tyranny? Zed Books.

Corbin, J., Strauss, A., 1990. Grounded theory research: Procedures, canons, and evaluative criteria 19.

Corburn, J., 2009. Cities, Climate Change and Urban Heat Island Mitigation: Localising Global Environmental Science. Urban Stud. 46, 413–427.

Crouch, J.R., Shen, Y., Austin, J.A., Dinniman, M.S., 2008. An educational interactive numerical model of the Chesapeake Bay. Comput. Geosci. 34, 247–258.

Cumming, G.S., 2016. Heterarchies: Reconciling Networks and Hierarchies. Trends Ecol. Evol. 31, 622–632.

Cumming, G.S., Cumming, D.H.M., Redman, C.L., 2006. Scale mismatches in social-ecological systems: Causes, consequences, and solutions. Ecol. Soc. 11, 14.

Dedoose, 2021. Version 9.0.17, cloud application for managing, analyzing, and presenting qualitative and mixed method research data (2021). Los Angeles, CA: SocioCultural Research Consultants, LLC Devereux, O., Rigelman, J.R., 2014. CAST: An Online Tool for Facilitating Local Involvement in Watershed Implementation Plans for the Chesapeake Bay Total Maximum Daily Load. J. Water Manag. Model. 1–8.

Dolfsma, W., Leydesdorff, L., 2009. Lock-in and break-out from technological trajectories: Modeling and policy implications. Technol. Forecast. Soc. Change 76, 932–941.

Dryzek, J.S., 2013. The Politics of the Earth: Environmental Discourses, 3rd edition. Oxford University Press, Oxford.

Easton, Z., Scavia, D., Alexander, R., Band, L., Kleinman, P., Martin, J., Miller, A., Pizzuto, J., Smith, D., Welty, C., Tech, V., 2017. Scientific and Technical Advisory Committee Chesapeake Bay Watershed Model Phase 6 Review (No. 17– 007). CBP STAC.

Edmonds, B., Hofstede. G.J., Koch, J., le Page, C., Lim, T., Lippe, M., Nöldeke, B., van Delden, H., under review. Chimaera Modelling – when the modellers have to reconcile inconsistent elements. Socio-Environmental Systems Modelling.

Elster, J., 1989. Social Norms and Economic Theory. J. Econ. Perspect. 3, 99–117.

Ernst, H.R., 2003. Chesapeake Bay Blues: Science, Politics, and the Struggle to Save the Bay, 1st Edition, Rowman & Littlefield Publishers, Inc., Lanham.

Everett, J.A.C., Faber, N.S., Crockett, M., 2015. Preferences and beliefs in ingroup favoritism. Front. Behav. Neurosci. 9.p 15

Executive Office of the President, 2009. Chesapeake Bay Protection and Restoration.Federal Register, Executive Order 13508, May 12, 2009.

Falconi, S.M., Palmer, R.N., 2017. An interdisciplinary framework for participatory modeling design and evaluation—What makes models effective participatory decision tools? Water Resour. Res. 53, 1625–1645.

Flyvbjerg, B., 2006. Five Misunderstandings About Case-Study Research. Qual. Inq. 12, 219–245.

French, R.D., 2019. Is it time to give up on evidence-based policy? Four answers. Policy Polit. 47, 151–168.

Fung, A., 2006. Varieties of Participation in Complex Governance. Public Adm. Rev. 66, 66–75.

Funtowicz, S.O., Ravetz, J.R., 1993. The Emergence of Post-Normal Science, in: Von Schomberg, R. (Ed.), Science, Politics and Morality. Springer Netherlands, Dordrecht.

Girod, B., Wiek, A., Mieg, H., Hulme, M., 2009. The evolution of the IPCC’s emissions scenarios. Environ. Sci. Policy 12, 103–118.

Glynn, P.D., 2014. W(h)ither the Oracle? Cognitive Biases and Other Human Challenges of Integrated Environmental Modeling. International Environmental Modelling and Software Society (iEMSs) 7th Intl Congrees on Env. Modelling and Software, San Diego, CA, USA.

Glynn, P.D., Chiavacci, S.J., Rhodes, C.R., Helgeson, J.F., Shapiro, C.D., Straub, C.L., 2022a. Value of Information: Exploring Behavioral and Social Factors. Front. Environ. Sci. 10.p 437

Glynn, P.D., Rhodes, C.R., Chiavacci, S.J., Helgeson, J.F., Shapiro, C.D., Straub, C.L., 2022b. Value of Information and Decision Pathways: Concepts and Case Studies. Front. Env. Sci 10, 805214.

Glynn, P.D., Voinov, A.A., Shapiro, C.D., White, P.A., 2018. Response to Comment by Walker et al. on “From Data to Decisions: Processing Information, Biases, and Beliefs for Improved Management of Natural Resources and Environments.” Earths Future 6, 762–769.

Glynn, P.D., Voinov, A.A., Shapiro, C.D., White, P.A., 2017. From data to decisions: Processing information, biases, and beliefs for improved management of natural resources and environments. Earths Future 5, 356–378.

Gray, S., Voinov, A., Paolisso, M., Jordan, R., BenDor, T., Bommel, P., Glynn, P., Hedelin, B., Hubacek, K., Introne, J., Kolagani, N., Laursen, B., Prell, C., Olabisi, L.S., Singer, A., Sterling, E., Zellner, M., 2018. Purpose, processes, partnerships, and products: four Ps to advance participatory socio-environmental modeling. Ecol. Appl. 28, 46–61.

Gregory, R., Failing, L., Harstone, M., Long, G., McDaniels, T., Ohlson, D., 2012. Structured Decision Making: A Practical Guide to Environmental Management Choices. John Wiley & Sons.

Haasnoot, M., van Deursen, W.P.A., Guillaume, J.H.A., Kwakkel, J.H., van Beek, E., Middelkoop, H., 2014. Fit for purpose? Building and evaluating a fast, integrated model for exploring water policy pathways. Environ. Model. Softw. 60, 99–120.

Hamilton, S.H., Fu, B., Guillaume, J.H.A., Badham, J., Elsawah, S., Gober, P., Hunt, R.J., Iwanaga, T., Jakeman, A.J., Ames, D.P., Curtis, A., Hill, M.C., Pierce, S.A., Zare, F., 2019. A framework for characterising and evaluating the effectiveness of environmental modelling. Environ. Model. Softw. 118, 83–98.

Hedelin, B., Gray, S., Woehlke, S., BenDor, T.K., Singer, A., Jordan, R., Zellner, M., Giabbanelli, P., Glynn, P., Jenni, K., Jetter, A., Kolagani, N., Laursen, B., Leong, K.M., Schmitt Olabisi, L., Sterling, E., 2021. What’s left before participatory modeling can fully support real-world environmental planning processes: A case study review. Environ. Model. Softw. 143, 105073.

Hewitt, C., 1988. Offices Are Open Systems, in: Bond, A.H., Gasser, L. (Eds.), Readings in Distributed Artificial Intelligence. Morgan Kaufmann, pp. 321–329.

Hood, R.R., Shenk, G.W., Dixon, R.L., Smith, S.M.C., Ball, W.P., Bash, J.O., Batiuk, R., Boomer, K., Brady, D.C., Cerco, C., Claggett, P., de Mutsert, K., Easton, Z.M., Elmore, A.J., Friedrichs, M.A.M., Harris, L.A., Ihde, T.F., Lacher, L., Li, L., Linker, L.C., Miller, A., Moriarty, J., Noe, G.B., Onyullo, G., Rose, K., Skalak, K., Tian, R., Veith, T.L., Wainger, L., Weller, D., Zhang, Y.J., 2021. The Chesapeake Bay program modeling system: Overview and recommendations for future development. Ecol. Model. 456, 109635.

Hughes, T., 1987. Evolution of Large Technical Systems, in: The Social Construction of Technological Systems: New Directions in the Sociology and History of Technology. MIT Press, Cambridge, Mass.; London, pp. 51–82.

Intemann, K., 2015. Distinguishing between legitimate and illegitimate values in climate modeling. Eur. J. Philos. Sci. 5, 217–232.

Iwanaga, T., Wang, H.-H., Hamilton, S.H., Grimm, V., Koralewski, T.E., Salado, A., Elsawah, S., Razavi, S., Yang, J., Glynn, P., Badham, J., Voinov, A., Chen, M., Grant, W.E., Peterson, T.R., Frank, K., Shenk, G., Barton, C.M., Jakeman, A.J., Little, J.C., 2021. Socio-technical scales in socio-environmental modeling: Managing a system-of-systems modeling approach. Environ. Model. Softw. 135, 104885.

Jakeman, A.J., Letcher, R.A., Norton, J.P., 2006. Ten iterative steps in development and evaluation of environmental models. Environ. Model. Softw. 21, 602–614.

Janis, I.L., 1982. Groupthink: Psychological Studies of Policy Decisions and Fiascoes, 2nd edition. Cengage Learning, Boston.

Jordan, R., Gray, S., Zellner, M., Glynn, P.D., Voinov, A., Hedelin, B., Sterling, E.J., Leong, K., Olabisi, L.S., Hubacek, K., Bommel, P., BenDor, T.K., Jetter, A.J., Laursen, B., Singer, A., Giabbanelli, P.J., Kolagani, N., Carrera, L.B., Jenni, K., Prell, C., National Socio-Environmental Synthesis Center Participatory Modeling Pursuit Working Group, 2018. Twelve Questions for the Participatory Modeling Community. Earths Future 6, 1046–1057.

Kaufman, D.E., Shenk, G.W., Bhatt, G., Asplen, K.W., Devereux, O.H., Rigelman, J.R., Ellis, J.H., Hobbs, B.F., Bosch, D.J., Van Houtven, G.L., McGarity, A.E., Linker, L.C., Ball, W.P., 2021. Supporting cost-effective watershed management strategies for Chesapeake Bay using a modeling and optimization framework. Environ. Model. Softw. 144, 105141.

Klosterman, R.E., 2012. Simple and Complex Models. Environ. Plan. B Plan. Des. 39, 1–6.

Kolar, K., Ahmad, F., Chan, L., Erickson, P.G., 2017. Timeline Mapping in Qualitative Interviews: A Study of Resilience with Marginalized Groups. Int. J. Qual. Methods 14, 13–32.

Korfmacher, K.S., 2001. The Politics of Participation in Watershed Modeling. Environ. Manage. 27, 161–176.

Kruger, J., Dunning, D., 1999. Unskilled and Unaware of It: How Difficulties in Recognizing One’s Own Incompetence Lead to Inflated Self-Assessments. J. Pers. Soc. Psychol.77 (6) p 1121

Lahtinen, T.J., Guillaume, J.H.A., Hämäläinen, R.P., 2017. Why pay attention to paths in the practice of environmental modelling? Environ. Model. Softw. 92, 74–81.

Latour, B., 2005. Reassembling the social: an introduction to actor-network-theory. Oxford University Press, Oxford; New York.

Latour, B., 1987. Science in Action: How to Follow Scientists and Engineers Through Society. Harvard University Press.

Layzer, J.A., 2011. Ecosystem-Based Management in the Chesapeake Bay, in: The Environmental Case: Translating Values Into Policy. CQ Press, Washington, D.C.

Liberatore, A., Funtowicz, S., 2003. ‘Democratising’ expertise, ‘expertising’ democracy: What does this mean, and why bother? Sci. Public Policy 30, 146–150.

Lim, T.C., 2021. Model emulators and complexity management at the environmental science-action interface. Environ. Model. Softw. 135, 104928.

LimnoTech, 2010. Comparison of Draft Load Estimates for Cultivated Cropland in the Chesapeake Bay Watershed, Prepared for the Agricultural Nutrient Policy Council. Ann Arbor, MI.

Lindner, I., Strulik, H., 2008. Social Fractionalization, Endogenous Appropriation Norms, and Economic Development. Economica 75, 244–258.

Linker, L.C., Batiuk, R.A., Shenk, G.W., Cerco, C.F., 2013. Development of the Chesapeake Bay Watershed Total Maximum Daily Load Allocation. JAWRA J. Am. Water Resour. Assoc. 49, 986–1006.

Linker, L.C., Shenk, G., Wang, P., Hopkins, K.J., Pokharel, S., 2002. A Short History of Chesapeake Bay Modeling and the Next Generation of Water Shed and Estuarine Models, in: Proceedings of the Water Environment Federation. Presented at the Water Environment Federation, Alexandria, VA, pp. 569–582.

Lubell, M., Segee, B., 2013. Conflict and Cooperation in Natural Resource Management, in: Vig, N.J., Kraft, M.E. (Eds.), Environmental Policy: New Directions for the Twenty-First Century. CQ Press, Thousand Oaks,CA.

Martin, J., Runge, M.C., Nichols, J.D., Lubow, B.C., Kendall, W.L., 2009. Structured decision making as a conceptual framework to identify thresholds for conservation and management. Ecol. Appl. 19, 1079–1090.

Meadowcroft, J., 2002. Politics and scale: some implications for environmental governance. Landsc. Urban Plan., Scaling and Environmental Understanding 61, 169–179.

Merry, S.E., 2016. The Seductions of Quantification: Measuring Human Rights, Gender Violence, and Sex Trafficking, Illustrated edition. The University of Chicago Press.

Morrison, T.H., 2017. Evolving polycentric governance of the Great Barrier Reef. Proc. Natl. Acad. Sci. 114, E3013–E3021.

Morrison, T.H., Adger, W.N., Brown, K., Lemos, M.C., Huitema, D., Phelps, J., Evans, L., Cohen, P., Song, A.M., Turner, R., Quinn, T., Hughes, T.P., 2019. The black box of power in polycentric environmental governance. Glob. Environ. Change 57, 101934.

National Research Council, 2011. Achieving Nutrient and Sediment Reduction Goals in the Chesapeake Bay: An Evaluation of Program Strategies and Implementation. National Academies Press, Washington, D.C.

Newig, J., Fritsch, O., 2009. Environmental governance: participatory, multi-level – and effective? Environ. Policy Gov. 19, 197–214.

Oreskes, N., 2003. The role of quantitative models in science, in: Canham, C.D., Cole, J.J., Laurenroth, W.K. (Eds.), Models in Ecosystem Science. Princeton University Press, NJ, USA, pp. 13–31.

Ormerod, R.J., 2009. The history and ideas of critical rationalism: the philosophy of Karl Popper and its implications for OR. J. Oper. Res. Soc. 60, 441–460.

Ostrom, E., 2011. Background on the Institutional Analysis and Development Framework. Policy Stud. J. 39, 7–27.

Paolisso, M., Trombley, J., Hood, R.R., Sellner, K.G., 2015. Environmental Models and Public Stakeholders in the Chesapeake Bay Watershed. Estuaries Coasts 38, 97–113.

Parker, C., Scott, S., Geddes, A., 2019. Snowball Sampling. SAGE Res. Methods Found.

Popper, K., 2002. The Logic of Scientific Discovery. Routledge.

Porter, T.M., 1996. Trust in Numbers: The Pursuit of Objectivity in Science and Public Life, Trust in Numbers. Princeton University Press.

Punch, M., 1986. The politics and ethics of fieldwork. Beverly Hills, CA: Sage, 1986. 93 p.

Python Software Foundation, 2023. Python Language Reference.

Rayner, S., 2012. Uncomfortable knowledge: the social construction of ignorance in science and environmental policy discourses. Econ. Soc. 41, 107–125.

Reagan, R., 1984. Address Before a Joint Session of the Congress on the State of the Union.

Ryan, G.W., Bernard, H.R., 2003. Techniques to Identify Themes. Field Methods 15, 85–109.

Saltelli, A., Bammer, G., Bruno, I., Charters, E., Di Fiore, M., Didier, E., Nelson Espeland, W., Kay, J., Lo Piano, S., Mayo, D., Pielke Jr, R., Portaluri, T., Porter, T.M., Puy, A., Rafols, I., Ravetz, J.R., Reinert, E., Sarewitz, D., Stark, P.B., Stirling, A., van der Sluijs, J., Vineis, P., 2020. Five ways to ensure that models serve society: a manifesto. Nature 582, 482–484.

Saltelli, A., Funtowicz, S.O., 2014. When All Models Are Wrong. Issues Sci. Technol. 30, 79–85.

Saltelli, A., Giampietro, M., 2017. What is wrong with evidence based policy, and how can it be improved? Futures, Post-Normal science in practice 91, 62–71.

Saltelli, A., Stark, P.B., Becker, W., Stano, P., 2015. Climate Models as Economic Guides: Scientific Challenge or Quixotic Quest? Issues Sci. Technol. 79–84.

Sarewitz, D., 2004. How science makes environmental controversies worse. Environ. Sci. Policy, Science, Policy, and Politics: Learning from Controversy Over The Skeptical Environmentalist 7, 385–403.

Scientific and Technical Advisory Committee, 2023. Chesapeake Bay Scientific and Technical Advisory Committee [WWW Document]. URL

Scott, J.C., 1999. Seeing like a State: How Certain Schemes to Improve the Human Condition Have Failed. Yale University Press, New Haven, Conn.

Shenk, G.W., Linker, L.C., 2013. Development and Application of the 2010 Chesapeake Bay Watershed Total Maximum Daily Load Model. JAWRA J. Am. Water Resour. Assoc. 49, 1042–1056.

Smith, J.A., 1995. Semi structured interviewing and qualitative analysis, in: Smith, J.A., Harre, R., Van Langenhove, L. (Eds.), . Sage Publications, pp. 9–26.

Star, S.L., 1999. The Ethnography of Infrastructure. Am. Behav. Sci. 43, 377–391.

Star, S.L., Griesemer, J.R., 1989. Institutional Ecology, `Translations’ and Boundary Objects: Amateurs and Professionals in Berkeley’s Museum of Vertebrate Zoology, 1907-39. Soc. Stud. Sci. 19, 387–420.

Sterling, E.J., Zellner, M., Jenni, K.E., Leong, K., Glynn, P.D., BenDor, T.K., Bommel, P., Hubacek, K., Jetter, A.J., Jordan, R., Olabisi, L.S., Paolisso, M., Gray, S., 2019. Try, try again: Lessons learned from success and failure in participatory modeling. Elem. Sci. Anthr. 7, 9.

Sterman, J.D., 2012. Sustaining Sustainability: Creating a Systems Science in a Fragmented Academy and Polarized World, in: Weinstein, M.P., Turner, R.E. (Eds.), Sustainability Science. Springer New York, New York, NY, pp. 21–58.

Strassheim, H., Kettunen, P., 2014. When does evidence-based policy turn into policy-based evidence? Configurations, contexts and mechanisms. Evid. Policy 10, 259–277.

Sundberg, M., 2007. Parameterizations as Boundary Objects on the Climate Arena. Soc. Stud. Sci. 37, 473–488.

U.S. EPA, 2010. Chesapeake Bay Total Maximum Daily Load for Nitrogen, Phosphorous and Sediment.

USDA, 2011. Assessment of the Effects of Conservation Practices on Cultivated Cropland in the Chesapeake Bay Region, Conservation Effects Assessment Project (CEAP).

van den Hove, S., 2007. A rationale for science–policy interfaces. Futures 39, 807–826.

van der Sluijs, J., 2005. Uncertainty as a monster in the science–policy interface: four coping strategies. Water Sci. Technol. 52, 87–92.

van der Sluijs, J.P., Petersen, A.C., Janssen, P.H.M., Risbey, J.S., Ravetz, J.R., 2008. Exploring the quality of evidence for complex and contested policy decisions. Environ. Res. Lett. 3, 024008.

van der Vaart, W., 2004. The Time-line as a Device to Enhance Recall in Standardized Research Interviews: A Split Ballot Study. J. Official Stat. 20, 301.

Voinov, A., Bousquet, F., 2010. Modelling with stakeholders. Environ. Model. Softw., Thematic Issue - Modelling with Stakeholders 25, 1268–1281.

Voinov, A., Jenni, K., Gray, S., Kolagani, N., Glynn, P.D., Bommel, P., Prell, C., Zellner, M., Paolisso, M., Jordan, R., Sterling, E., Schmitt Olabisi, L., Giabbanelli, P.J., Sun, Z., Le Page, C., Elsawah, S., BenDor, T.K., Hubacek, K., Laursen, B.K., Jetter, A., Basco-Carrera, L., Singer, A., Young, L., Brunacini, J., Smajgl, A., 2018. Tools and methods in participatory modeling: Selecting the right tool for the job. Environ. Model. Softw. 109, 232–255.

Voinov, A., Kolagani, N., McCall, M.K., Glynn, P.D., Kragt, M.E., Ostermann, F.O., Pierce, S.A., Ramu, P., 2016. Modelling with stakeholders – Next generation. Environ. Model. Softw. 77, 196–220.

Weller, D.E., Benham, B., Friedrichs, M., Naijar, R., Paolisso, M., Pascual, P., Shenk, G., Sellner, K., 2013. Multiple Models for Management in the Chesapeake Bay (No. 14– 004). Edgewater, MD.

Wesselink, A., Buchanan, K.S., Georgiadou, Y., Turnhout, E., 2013. Technical knowledge, discursive spaces and politics at the science–policy interface. Environ. Sci. Policy, SI: Environmental and Developmental Discourses: Technical knowledge, discursive spaces and politics 30, 1–9.

White, D.D., Wutich, A., Larson, K.L., Gober, P., Lant, T., Senneville, C., 2010. Credibility, salience, and legitimacy of boundary objects: water managers’ assessment of a simulation model in an immersive decision theater. Sci. Public Policy 37, 219–232.

Wu, K., Dunning, D., 2018. Hypocognition: Making Sense of the Landscape beyond One’s Conceptual Reach. Rev. Gen. Psychol. 22, 25–35.

Wyborn, C., Datta, A., Montana, J., Ryan, M., Leith, P., Chaffin, B., Miller, C., van Kerkhoff, L., 2019. Co-Producing Sustainability: Reordering the Governance of Science, Policy, and Practice. Annu. Rev. Environ. Resour. 44, 319–346.

Zellner, M.L., Milz, D., Lyons, L., Hoch, C.J., Radinsky, J., 2022. Finding the Balance Between Simplicity and Realism in Participatory Modeling for Environmental Planning. Environ. Model. Softw. 157, 105481.

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