Abstract

A spatially explicit metapopulation model was used to examine the effects of landscape characteristics (patch sizes, interpatch distances, patch productivity) and dispersal behavior (maximum dispersal distance) on the source–sink dynamics of white-tailed deer ( Odocoileus virginianus) in a simulated landscape. Specifically, the model was used to test the hypothesis that patterns in primary productivity, which affect the growth of deer populations, will interact with, and potentially alter, the effects of landscape structure on metapopulation dynamics. The model, constructed in the STELLA modeling environment, combines a density-dependent Leslie matrix population model with a simple habitat/non-habitat representation of an artificial landscape to simulate the growth and spread of deer populations in a spatial framework. A set of 60 simulations were run, measuring the average net emigration per habitat patch for maximum dispersal distances of 5, 10 and 20 km and under four net primary productivity (NPP) conditions: (1) constant NPP per km 2; (2) NPP varying with patch size; (3) NPP varying inversely with patch size; and (4) NPP varying over time. Significant differences were observed for effects of patch size, dispersal distance, NPP conditions and all two- and three-way interactions on patterns of net emigration. Specifically, increasing the maximum dispersal distance led to magnifications in net emigration patterns (i.e. patches exhibiting a positive trend in net emigration became more positive and vice versa). Changes in NPP altered the magnitude of the source–sink trends, sometimes reversing the relationship, particularly for populations in smaller patches. The results illustrate the importance of multiple interacting landscape factors in influencing metapopulation dynamics, indicating that shifting patterns of productivity can significantly alter the source–sink patterns of metapopulations when spatial factors are explicitly considered. Implications for management and conservation, as well as future model improvements, are briefly discussed.

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