SREL Reprint #1930

Spatially explicit population models: current forms and future uses

John B. Dunning, Jr.1, David J. Stewart1, Brent J. Danielson2, Barry R. Noon3, Terry L. Root4, Roland H. Lamberson5, and Ernest E. Stevens6

1Institute of Ecology, University of Georgia, Athens, Georgia 30602 USA
2Department of Animal Ecology, Iowa State University, Ames, Iowa 50011 USA
3Redwood Science Laboratory, U.S. Forest Service, Arcata, California 95521 USA
4School of Natural Resources and Environment, University of Michigan, Ann Arbor, Michigan 48109 USA
5Mathematics Department, Humboldt State University, Arcata, California 95521 USA
6Southeastern Forest Experiment Station, U.S. Forest Service, Department of Forest Resources, Clemson University, Clemson, South Carolina 29634 USA

Abstract: Spatially explicit population models are becoming increasingly useful tools for population ecologists, conservation biologists, and land managers. Models are spatially explicit when they combine a population simulator with a landscape map that describes the spatial distribution of landscape features. With this map, the locations of habitat patches, individuals, and other items of interest are explicitly incorporated into the model, and the effect of changing landscape features on population dynamics can be studied. In this paper we describe the structure of some spatially explicit models under development and provide examples of current and future research using these models. Spatially explicit models are important tools for investigating scale-related questions in population ecology, especially the response of organisms to habitat change occurring at a variety of spatial and temporal scales. Simulation models that incorporate real-world landscapes, as portrayed by landscape maps created with geographic information systems, are also proving to be crucial in the development of management strategies in response to regional land-use and other global change processes. Spatially explicit population models will increase our ability to accurately model complex landscapes, and therefore should improve both basic ecological knowledge of landscape phenomena and applications of landscape ecology to conservation and management.

Keywords: dispersal; land management; landscape; mobile animal populations; population dynamics; population simulation models; spatiality explicit population models

SREL Reprint #1930

Dunning, J.B., Jr., D.J. Stewart, B.J. Danielson, B.R. Noon, T. Root, R.H. Lamberson, and E.E. Stevens. 1995. Spatially explicit population models: current forms and future uses. Ecological Applications 5:3-11. 

This information was provided by the University of Georgia's Savannah River Ecology Laboratory (srel.uga.edu).