Document: ROL-3-26-6

Predictive, state-based dynamic modeling as an approach for decision making in individual-based models.

LAMBERSON, R.H.*

Department of Mathematics, Humboldt State University, Arcata, CA 95521, USA ¹

Abstract:
Movement rules are a critical component of spatially explicit, individual-based population models because for many species movement is the primary method used by individuals to adapt to changing environmental and competitive conditions. Individuals move to improve food intake and growth, reduce vulnerability to predation risks, seek shelter, and avoid competition. Movement rules have two basic aspects, departure rules which determine when an individual moves and destination rules which determine the new location. These rules are designed to move an individual to habitat that provides high fitness since it is generally assumed that habitat selection is at least in part based on maximizing fitness. Consequently, the fitness measure's formulation is a very important component of the movement rules. We develop two state-based fitness measures, one based on expected probability of survival to some fixed time horizon and the other based on the expectation of reaching reproductive maturity. The two state variables involved are energy reserves and (for individuals that are not currently sexually mature) the difference between size at sexual maturity and current size. The rules proposed in this paper seem to provide realistic simulation of the behavior of both individuals and populations as their environment changes without requiring unrealistic computation costs. The ability of animals to make a simple prediction of their fitness at the end of the time horizon is key to the success of this approach.

Keywords: Individual-based modeling, habitat selection, movement, prediction, state-based models

This abstract is being presented at: 9:20 AM in session:
Symposium # 27: Advancing the Individual-Based Modeling Approach: New Tools and Concepts.