Abstract
Many of the natural resource issues we face today cannot be fully understood using normal scientific methods or theories. When uncertainties or decision stakes are high, participation by an “extended peer community” can be critical to studying and managing complex systems since local expertise on land use and ecosystem processes may not otherwise be captured. We conducted a case study of participatory modeling to support natural resource management under a changing climate. Over a 2-year period, we convened a Knowledge to Action Network (KTAN) of scientists and stakeholders interested in exploring the impacts of climate change in Idaho’s Big Wood Basin. Through a series of workshops and webinars, participants worked together to (1) pose relevant research questions collaboratively and iteratively, (2) create models of the future landscape under a changing climate regime to explore their questions, and (3) increase knowledge about how scientific information is both used and generated within those models in order to interpret the results. We began by developing a conceptual model of the river basin and progressed to two quantitative models—a system dynamics model and a spatially-explicit integrated model—in order to explore research questions generated by the KTAN. Alternative scenarios were developed and simulated in the final quantitative model to assess the range of impacts that external drivers and management decisions could have on the system.
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Abatzoglou JT (2013) Development of gridded surface meteorological data for ecological applications and modelling. Int J Climatol 33:121–131. doi:10.1002/joc.3413
Beall A, Fiedler F, Boll J, Cosens B (2011) Sustainable water resource management and participatory system dynamics. Case study: developing the Palouse basin participatory model. Sustainability 3:720–742. doi:10.3390/su3050720
Bolte JP (2014) Envision. Oregon State University, Corvallis, OR
Bredehoeft J (2005) The conceptualization model problem—surprise. Hydrogeol J 13:37–46. doi:10.1007/s10040-004-0430-5
Buhidar B (2001) The Big Wood River Watershed Management Plan. Idaho Department of Environmental Quality, Twin Falls, Idaho
Canham CDW, Cole J, Lauenroth WK (2003) Models in ecosystem science. Princeton University Press, Princeton
Cash DW, Clark WC, Alcock F et al (2003) Science and technology for sustainable development special feature: knowledge systems for sustainable development. Proc Natl Acad Sci 100:8086–8091. doi:10.1073/pnas.1231332100
Duram LA, Brown KG (1999) Assessing public participation in US watershed planning initiatives. Soc Nat Resour 12:455–467. doi:10.1080/089419299279533
Funtowicz SO, Ravetz JR (1991) A new scientific methodology for global environmental issues. In: Costanza R (ed) Ecological economics: the science and management of sustainability. Columbia University Press, New York, pp 137–152
Holmberg J, Robert KH (2000) Backcasting - a framework for strategic planning. Int J Sustain Dev World Ecol 7:291–308. doi:10.1080/13504500009470049
Korfmacher KS (2001) The politics of participation in watershed modeling. Environ Manage 27:161–176. doi:10.1007/s002670010141
Kunstler JH (2006) The long emergency: surviving the end of oil, climate change, and other converging catastrophes of the twenty-first century. Grove Press, New York
Lach D, Sanford S (2010) Public understanding of science and technology embedded in complex institutional settings. Public Underst Sci 19:130–146. doi:10.1177/0963662508096783
Langsdale SM, Beall A, Carmichael J, Cohen SJ (2009) Exploring the implications of climate change on water resources through participatory modeling: case study of the Okanagan Basin, British Columbia. J Water Resour Plan Manage 135:373. doi:10.1061/(ASCE)0733-9496(2009)135:5(373)
Menon D, Stafinski T (2008) Engaging the public in priority-setting for health technology assessment: findings from a citizens’ jury. Health Expect 11:282–293. doi:10.1111/j.1369-7625.2008.00501.x
Morgan MS (1999) Learning from models. In: Morgan MS, Morrison M (eds) Models as mediators: perspectives on natural and social science. Cambridge University Press, Cambridge, pp 347–388
Oreskes N, Shrader-Frechette K, Belitz K (1994) Verification, validation, and confirmation of numerical models in the earth sciences. Science 263:641–646
Petersen AC, Cath A, Hage M et al (2011) Post-normal science in practice at the Netherlands Environmental Assessment Agency. Sci Technol Hum Values 36:362–388. doi:10.1177/0162243910385797
Pew Research Center (2013) Deficit reduction rises on public’s agenda for Obama’s second term. Pew Research Center, People Press. http://www.people-press.org/2013/01/24/deficit-reduction-rises-on-publics-agenda-for-obamas-second-term/. Accessed 18 Jun 2014
Ravetz JR (2011) “Climategate” and the maturing of post-normal science. Futures 43:149–157. doi:10.1016/j.futures.2010.10.003
Rupp DE, Abatzoglou JT, Hegewisch KC, Mote PW (2013) Evaluation of CMIP5 20th century climate simulations for the Pacific Northwest USA. J Geophys Res Atmos 118:10884–10906. doi:10.1002/jgrd.50843
Sarewitz D, Pielke RA, Byerly R (2000) Prediction: science, decision making, and the future of nature. Island Press, Washington, DC
Shackley S, Young P, Parkinson S, Wynne B (1998) Uncertainty, complexity and concepts of good science in climate change modelling: are GCMs the best tools? Clim Change 38:159–205
Skinner K, Bartolino J, Tranmer A (2007) Water resource trends and comparisons between partial-development and October 2006 hydrologic conditions, Wood River Valley, South-Central Idaho. United States Geological Survey
Stave KA (2003) A system dynamics model to facilitate public understanding of water management options in Las Vegas, Nevada. J Environ Manage 67:303–313
Tidwell VC, Passell HD, Conrad SH, Thomas RP (2004) System dynamics modeling for community-based water planning: application to the Middle Rio Grande. Aquat Sci 66:357–372
University of Idaho Extension (2006) County economic base codes. In: Indicators Idaho. http://www.indicatorsnorthwest.org/. Accessed 1 Oct 2014
U.S. Census Bureau (2010) American FactFinder
Ventana Systems, Inc. Vensim PLE
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This work is supported by NOAA’s Climate Program Office with funding from the Regional Integrated Sciences & Assessments (RISA) program.
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Inouye, A.M., Lach, D.H., Stevenson, J.R., Bolte, J.P., Koch, J. (2017). Participatory Modeling to Assess Climate Impacts on Water Resources in the Big Wood Basin, Idaho. In: Gray, S., Paolisso, M., Jordan, R., Gray, S. (eds) Environmental Modeling with Stakeholders. Springer, Cham. https://doi.org/10.1007/978-3-319-25053-3_14
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