The abundance and distribution of natural populations can be strongly influenced by the types and arrangement of habitat patches within a landscape. The impact of landscape changes on population dynamics is difficult to study using conventional population models and field techniques. Spatially explicit simulation models provide a powerful method for modelling landscape and population changes at large spatial scales and may prove useful as a management tool for mobile animal populations. As an example of this approach, we present a model designed to elucidate the effects of landscape-level variation in habitat dispersion on the size and extinction probability of avian populations in a region managed for timber production. In the model, habitat suitability and availability within the landscape change annually as a function of timber harvest and management strategies. The model incorporates life history characteristics of Bachman's Sparrow (Aimophila aestivalis), a species of management concern in the southeastern United States, and the landscape characteristics of the Savannah River Site, South Carolina, an area managed for timber production where the sparrow is relatively common. Life history characteristics used in the model include dispersal, survivorship, and reproductive success information reported for Bachman's Sparrow at this site or elsewhere in its range. Results of the simulations suggest that variation in demographic variables affects population size more than variation in dispersal ability. Changes in adult and juvenile survivorship have especially large impacts on the probability of population extinction. The presence of habitat types that serve as permanent sources of dispersers increases the total population size in the landscape, and lowers the probability of extinction. Results of models such as BACHMAP can suggest modifications to current management plans that would increase the probability of population persistence for species of special concern in managed landscapes.

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http://dx.doi.org/10.2307/1941773DOI Listing

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