Details zur Publikation

Kategorie Textpublikation
Referenztyp Zeitschriften
DOI 10.1086/286212
Titel (primär) Reconciling classical and individual-based approaches in theoretical population ecology: A protocol for extracting population parameters from individual-based models
Autor Fahse, L.; Wissel, C.; Grimm, V.
Quelle American Naturalist
Erscheinungsjahr 1998
Department OESA
Band/Volume 152
Heft 6
Seite von 838
Seite bis 852
Sprache englisch
Abstract

The two main approaches in theoretical population ecology-the classical approach using differential equations and the approach using individual-based modeling-seem to be incompatible. Linked to these two approaches are two different timescales: population dynamics and behavior or physiology. Thus, the question of the relationship between classical and individual-based approaches is related to the question of the mutual relationship between processes on the population and the behavioral timescales. We present a simple protocol that allows the two different approaches to be reconciled by making explicit use of the fact that processes operating on two different timescales can be treated separately. Using an individual- based model of nomadic birds as an example, we extract the population growth rate by deactivating all demographic processes-in other words, the individuals behave but do not age, die, or reproduce. The growth rate closely matches the logistic growth rate for a wide range of parameters. The implications of this result and the conditions for applying the protocol to other individual-based models are discussed. Since in physics the technique of separating timescales is linked to some concepts of self-organization, we believe that the protocol will also help to develop concepts of self-organization in ecology.

dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=8621
Fahse, L., Wissel, C., Grimm, V. (1998):
Reconciling classical and individual-based approaches in theoretical population ecology: A protocol for extracting population parameters from individual-based models
Am. Nat. 152 (6), 838 - 852 10.1086/286212