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Multi-country Ecosystem Management via Interacting Models of Political and Ecological Processes. Timothy C. Haas School of Business Administration University of Wisconsin-Milwaukee haas@uwm.edu www.uwm.edu/~haas/ems-cheetah/. Outline.
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Multi-country Ecosystem Management via Interacting Models of Political and Ecological Processes Timothy C. Haas School of Business Administration University of Wisconsin-Milwaukee haas@uwm.edu www.uwm.edu/~haas/ems-cheetah/
Outline • Ecosystem management with interacting models of political and ecological processes • Example: Management of cheetah across East Africa
System Characteristics • Probabilistic models of groups and the affected ecosystem fitted to data • Practical management strategies found from these fitted models
Group Models • President, EPA, rural residents, pastoralists, and NGOs • Groups act to reach economic, militaristic, and political goals • Internal (distorted) perceptions of other groups and the ecosystem
Endangered Species-Focused Ecosystem Model • Latest population dynamics model • Convert to a stochastic differential equation system to add uncertainty representation
East African Cheetah Management • Presidents, EPAs, rural residents, and pastoralists of Kenya, Tanzania, and Uganda • Conservation-focused NGO • Cheetah population dynamics in each political region
Data • Political actions from on-line newspapers over 1999-2006 • Artificial cheetah counts based on actual data from 1998-2000
Data-Model Agreement • 23% of observed action-target combinations matched by fitted model • Error rate: 1 – 0.23 = 77% • Blind guessing error rate:1 – 1/20 = 95% (with 20 decisionoptions)
Model-Based Most Practical Management Strategy Setup • Specify desired future ecosystem state • Example: 1000 cheetahs 50 years hence
Solution • Find smallest change in group belief systems that will result in a sequence of group actions that lead to the desired ecosystem state
Conclusions • A political-ecological model of ecosystem management decisions can be built
Conclusions continued • This model can be calibrated to political-ecological data • This fitted model can out-perform blind guessing of future group decisions