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Assessing the potential impacts of alternative landscape designs on amphibian population dynamics
Authors:Rustigian  HL  Santelmann  MV  Schumaker  NH
Institution:(1) Department of Geosciences, Oregon State University, Corvallis, 97331, USA;(2) Present address: Department of Ecology, Montana State University, Bozeman, 59717, USA;(3) Department of Geosciences, Oregon State University, Corvallis, 97331, USA;(4) Office of Research and Development, National Health and Environmental Effects Research Laboratory, Western Ecology Division, US Environmental Protection Agency, 200 SW 35th St., Corvallis, 97333, USA
Abstract:An individual-based, spatially explicit population model was used to predict the consequences of future land-use alternatives for populations of four amphibian species in two central Iowa (midwest USA) agricultural watersheds. The model included both breeding and upland habitat and incorporated effects of climatic variation and demographic stochasticity. Data requirements of the model include life history characteristics, dispersal behavior, habitat affinities, as well as land use and landcover in geographic information systems databases. Future scenarios were ranked according to change in breeder abundance, saturation, and distribution, compared to baseline conditions. Sensitivity of simulation results to changes in model parameters was also examined. Simulated results suggest that while all four species modeled are likely to persist under present and future scenario conditions, two may be more at risk from future landscape change. Although the study species are all widespread generalists regarded as having a low conservation priority, they depend on wetlands and ponds, increasingly endangered habitats in agricultural landscapes. Broader conservation strategies in the region would ensure that these currently common organisms do not become the endangered species of the future.This revised version was published online in May 2005 with corrections to the Cover Date.
Keywords:Agriculture  Amphibians  Future scenarios  Iowa  Landscape change  Population dynamics  Spatially explicit population model
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