Incorporating fuzzy sets in spatially explicit ecological modelling

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Simulation models that connect animal behavior and population dynamics with spatial data represented in a geographic information system (GIS) are becoming a prominent feature in the fields such as conservation biology and landscape ecology. These models are valued in conservation efforts because of their utility in contrasting management scenarios. However, their validity is limited due to uncertainties concerning landscape data, habitat modeling, as well as parameters representing our understanding of the behavior of dispersing animals. Using an agent-based, object oriented modeling framework for data integration and synthesis, we will explore the interplay between the fuzzy representation of spatial landscape data and their subsequent use in spatially explicit population models (SEPMs). Strategies for an empirically based methodologies for deriving a spatially explicit fuzzy representation of habitat based on archival field data will be developed. The advance in GIS-based habitat representation will be incorporated into a modeling framework allowing exploration of theoretical models of dispersal behavior that will incorporate the anisotropic nature of perceptual range as well as landscape matrix effects on an individual's behavior. This extends recent work that integrates fuzzy representation in the GIS database module with the fuzzy control of animal movement behavior using the concept of Probeable objects. A general model building objective is to be able to explicitly represent the behavioral tradeoffs, or differing decision strategies, that dispersers may use to navigate the landscape. It will advance our understanding of how dispersing animals may behave under different circumstances, thus helping design spatially explicit simulations that plausibly represent both the landscape as species-relevant spatial information and the individual based model of animal movement. The improvements in such a system should advance the quality of ecological intelligence provided to conservation efforts.