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The Land Transformation Model (LTM) is hierarchically coupled with meso-scale drivers to project urban growth across the conterminous USA. Quantity of urban growth 10 at county and place (i.e., city) scales is simulated using population, urban density and nearest neighbor dependent attributes. We compared three meso-scale LTMs to three null models that lack meso-scale drivers. Models were developed using circa 1990–2000 data and validated using change in the 2001 and 2006 National Land Cover Databases (NLCD). LTM and null models were assessed using the mean difference 15 in quantity between simulated and actual growth measured at multiple spatial scales. We found that LTM models performed relatively well at spatial...
Aim Assessing the influence of land cover in species distribution modelling is limited by the availability of fine-resolution land-cover data appropriate for most species responses. Remote-sensing technology offers great potential for predicting species distributions at large scales, but the cost and required expertise are prohibitive for many applications. We test the usefulness of freely available raw remote-sensing reflectance data in predicting species distributions of 40 commonly occurring bird species in western Oregon. Location Central Coast Range, Cascade and Klamath Mountains Oregon, USA. Methods Information on bird observations was collected from 4598 fixed-radius point counts. Reflectance data...


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