Species distribution modelling for the people: unclassified landsat TM imagery predicts bird occurrence at fine resolutions

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...

Categories: Publication; Types: Citation; Tags: Birds, Northwest CASC, Western Oregon, Wildlife and Plants, boosted regression trees, All tags... land-cover, model validation, species distribution modeling, unclassified remote-sensing imagery, Fewer tags