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Hierarchical Spatiotemporal Matrix Models for Characterizing Invasions

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The growth and dispersal of biotic organisms is an important subject in ecology. Ecologists are able to accurately describe survival and fecundity in plant and animal populations and have developed quantitative approaches to study the dynamics of dispersal and population size. Of particular interest are the dynamics of invasive species. Such nonindigenous animals and plants can levy significant impacts on native biotic communities. Effective models for relative abundance have been developed; however, a better understanding of the dynamics of actual population size (as opposed to relative abundance) in an invasion would be beneficial to all branches of ecology. In this article, we adopt a hierarchical Bayesian framework for modeling the invasion of such species while addressing the discrete nature of the data and uncertainty associated with the probability of detection. The nonlinear dynamics between discrete time points are intuitively modeled through an embedded deterministic population model with density-dependent growth and dispersal components. Additionally, we illustrate the importance of accommodating spatially varying dispersal rates. The method is applied to the specific case of the Eurasian Collared-Dove, an invasive species at mid-invasion in the United States at the time of this writing.
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Keywords: Animal dispersal; Detection probability; Hierarchical Bayesian models; Invasive species; Population models; Spatiotemporal dynamics

Document Type: Research Article

Affiliations: 1: Department of Statistics, University of Missouri, Columbia, Missouri 65211, U.S.A. 2: USGS Florida Integrated Science Center and Department of Statistics, University of Florida, Gainesville, Florida 32611-0339, U.S.A. 3: USGS Patuxent Wildlife Research Center, 12100 Beech Forest Road, Laurel, Maryland 20708, U.S.A.

Publication date: 2007-06-01

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