Tuesday, August 5, 2008: 9:00 AM
104 C, Midwest Airlines Center
Michael McNair Fuller, Faculty of Forestry, University of Toronto, Toronto, ON, Canada, Louis Gross, Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN, Scott M. Duke-Sylvester, Population Biology, Ecology and Evolution: Center for Disease Ecology, Emory University, Atlanta, GA and Mark Palmer, The Institute for Environmental Modeling, Knoxville, TN
Background/Question/Methods To effectively manage natural reserves, resource managers must prepare for
future contingencies while balancing the often conflicting priorities of
different stakeholders. To cope with these issues, managers routinely employ
models to project the response of ecosystems to different scenarios that
represent alternative management plans or environmental forecasts. Scenario
analysis is often used to rank such alternatives to aid the decision making
process. However, model projections are subject to uncertainty in assumptions
about model structure, parameter values, environmental inputs, and subcomponent
interactions. In the face of ever-building environmental, social, and political,
challenges, there is an urgent need for efficient strategies for dealing with
these uncertainties. To address this need, we describe a systematic approach for
quantifying the impacts of uncertainty on scenario-based management policy. We
use relative assessment to quantify the impacts of uncertainty on scenario
ranking. We illustrate our approach by considering uncertainty in parameter
values and input data, with specific examples drawn from the Florida Everglades
restoration project.
Results/Conclusions Our examples focus on two alternative 30-year hydrologic management plans that
were ranked according to their overall impacts on wildlife habitat potential.
We tested the assumption that varying the parameter settings and inputs of
habitat index models does not change the rank order of the hydrologic plans.
We compared the average projected index of habitat potential for four endemic
species and two wading-bird guilds, to rank the alternative plans. Our analysis
accounted for uncertainty in field-based parameter settings as well as drastic
changes in water level inputs that simulate strong deviations from historic
climate conditions. Indices of habitat potential were based upon projections
from spatially explicit models that are closely tied to Everglades hydrology.
Our analysis revealed striking differences in how the models responded to
different types of uncertainty. We found that the rank order of the hydrologic
plans was unaffected by substantial variation in the parameters of the
reproductive model for the American alligator. By contrast, simulated major
shifts in water levels led to reversals in the ranks of the hydrologic plans in
24.1% to 30.6% of the projections for the wading bird guilds and several
individual species. Also, the relative impact of climate on habitat potential
differed among the species and changed with geographic scale. By exposing the
differential effects of uncertainty, relative assessment can help resource
managers assess the robustness of scenario choice in model-based policy
decisions.