Event Detail

Event Type: 
Applied Mathematics and Computation Seminar
Date/Time: 
Friday, February 18, 2011 - 04:00
Location: 
GLK 113

Speaker Info

Institution: 
OSU Biological and Ecological Engineering
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.

We describe an approach and a modeling tool/framework (Envision) for conducting research about the nature and properties of coupled human and natural environmental systems in the context of climate change. The approach employs scenarios, data and evaluative models produced by past research, and built on prior work in agent-based modeling.  Central to Envision are the three-way interactions of agents, who have decision making authority over parcels of land, the landscape which is changed as these decisions are made, and the policies that guide and constrain decisions. In Envision, agents are entities that make decisions about the management of particular portions of the landscape for which they have management authority, based on balancing a set of objectives reflecting their particular values, mandates and the policy sets in force on the parcels they manage. They do this within the scope of policy sets that are consistent with the assumptions and intentions of a chosen future scenario. These policies are operative on particular landscape elements over which they have decision-making control.

The basic approach employed by Envision and examples of its use for conducting alternative futures assessments in the Pacific Northwest will be presented.