Envisioning Alternative Futures
Experiences in the Willamette Valley and Puget Sound
Head of the Department of Bio Engineering
Oregon State University
4-5:30, Tuesday, November 17, 2009, LH 1
PLATO Royalty Lecture Series
Abstract: In the past several decades there has been a dramatic increase in the use of scientific, quantitative methods for informing landscape change and decision-making in the presence of deep uncertainty. The predominant approach in such assessments has been characterized as a predict-then-act paradigm, which pairs models of rational decision-making with methods for treating uncertainty derived largely from the sciences and engineering. The preferred course of action in predict-then-act assessments is the one that performs ‘‘best’’ given some (typically small) set of assumptions about the likelihood of various futures and the landscape processes that will be sustained if these assumptions prove true. Such assessments are strongly tied to the validity of these assumptions.
A second paradigm is emerging that differs from predict-then-act in important ways. Rather than seeking strategies and policies that are optimal against some small set of scenarios for the future, this explore-then-test approach seeks near-term actions that are shown to perform well across a large ensemble of plausible future scenarios. These approaches offer the promise (but less so the proof) of policies and patterns that are sufficiently robust against future surprise that they can seize unexpected opportunities, adapt when things go wrong and provide new avenues in forging consensus regarding the facts and values that steer landscape change. Agent-based models are central tools in the explore-then-test paradigm.
This lecture will discuss Envision, an alternative future modeling and assessment tool based on an agent-based modeling paradigm that was created to conduct research about the nature and properties of coupled human and natural environmental systems in the context of climate change. The approach employes scenarios, data and evaluative models produced by past research and built on prior work in agent-based modeling and biocomplexity. We describe our experiences with Envision in modeling alternative future trajectories in the Willamette Basin and in Puget Sound.
The Speaker: John Bolte is Professor and Head of the Biological & Ecological Engineering Department at Oregon State University. His research interests include agent based modeling for understanding coupled natural and human systems, spatial analysis and ecosystem modeling, ecosystem service assessments, and policy implications of environmental change.
Companion Reading: ( Note to Students: Please be aware that your program might have additional or different reading! Check your respective program web site. )
- Hulse, D., A. Branscomb, C. Enright, J. Bolte. 2008. Anticipating floodplain trajectories: a comparison of two alternative futures approaches. Landscape Ecology. DOI:10.1007/s10980-008-9255-2
- Guzy, M. R., C. L. Smith, J. P. Bolte, D. W. Hulse and S. V. Gregory. 2008. Policy research using agent based modeling to assess future impacts of urban expansion into farmlands and forests. Ecology and Society 13(1): 37. [online] URL: http://www.ecologyandsociety.org/vol13/iss1/art37/
- Bolte, J.P., D. W. Hulse, S. V. Gregory, C. L. Smith. Modeling biocomplexity – actors, landscapes and alternative futures. Env. Modeling and Software 22 (5): 570-579 Sp. Iss. May 2007
 This Lecture is sponsored by Evergreen’s PLATO Royalty Fund, established with royalties from computer assisted instruction (CAI) software, written by Evergreen faculty John Aikin Cushing and students in the early 1980’s, for the Control Data PLATO system.