Ecologists now recognize that the dynamics of populations, communities,
and ecosystems are strongly affected by adaptive individual behaviors.
Yet until now, we have lacked effective and flexible methods for
modeling such dynamics. Traditional ecological models become impractical
with the inclusion of behavior, and the optimization approaches of
behavioral ecology cannot be used when future conditions are
unpredictable due to feedbacks from the behavior of other individuals.
This book provides a comprehensive introduction to state- and
prediction-based theory, or SPT, a powerful new approach to modeling
trade-off behaviors in contexts such as individual-based population
models where feedbacks and variability make optimization impossible.
Modeling Populations of Adaptive Individuals features a wealth of
examples that range from highly simplified behavior models to complex
population models in which individuals make adaptive trade-off decisions
about habitat and activity selection in highly heterogeneous
environments. Steven Railsback and Bret Harvey explain how SPT builds on
key concepts from the state-based dynamic modeling theory of behavioral
ecology, and how it combines explicit predictions of future conditions
with approximations of a fitness measure to represent how individuals
make good-not optimal-decisions that they revise as conditions change.
The resulting models are realistic, testable, adaptable, and invaluable
for answering fundamental questions in ecology and forecasting
ecological outcomes of real-world scenarios.