Species distribution modelling for the people: unclassified landsat TM imagery predicts bird occurrence at fine resolutions
Article first published online: 7 MAY 2013
© 2013 John Wiley & Sons Ltd
Diversity and Distributions
Volume 19, Issue 7, pages 855–866, July 2013
How to Cite
Shirley, S. M., Yang, Z., Hutchinson, R. A., Alexander, J. D., McGarigal, K., Betts, M. G. (2013), Species distribution modelling for the people: unclassified landsat TM imagery predicts bird occurrence at fine resolutions. Diversity and Distributions, 19: 855–866. doi: 10.1111/ddi.12093
- Issue published online: 13 JUN 2013
- Article first published online: 7 MAY 2013
- US National Science Foundation. Grant Numbers: NSF-ARC-0941748, G11AC20255
- United States Geological Survey
Table S1 List of bird species used to assess the usefulness of raw unclassified remote-sensing data in predicting species distributions in Oregon, USA.
Table S2 Results of the Moran's I test for each bird species used to assess spatial autocorrelation in the residuals for BRT models for predicting species distributions in Oregon, USA.
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