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

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Potential of remote sensing to predict species invasions (2015, methodology): “In that study, models based on individual reflectance bands were more accurate than those using only NDVI, and the authors concluded that freely available Landsat imagery may be particularly useful in developing SDMs when predictions at higher-resolution are required (Shirley et al., 2013).”
Comparing species distribution models constructed with different subsets of environmental predictors (2015, background): “Fine-scale data on landscape characteristics (e.g. remotely sensed vegetation) have been demonstrated to be useful for SDMs at appropriate spatial resolutions (e.g. Lyet et al., 2013; Shirley et al., 2013).”
A species-centered approach for uncovering generalities in organism responses to habitat loss and fragmentation (2014, unknown): “We then used boosted regression trees (BRT; Elith et al. 2008) to model species distributions as a function of land-cover data (after Shirley et al. 2013).”