Mapping breeding bird species richness at management-relevant resolutions across the United States.

Human activities alter ecosystems everywhere, causing rapid biodiversity loss and biotic homogenization. These losses necessitate coordinated conservation actions guided by biodiversity and species distribution spatial data that cover large areas yet have fine-enough resolution to be management-relevant (i.e.

Habitat heterogeneity captured by 30-m resolution satellite image texture predicts bird richness across the United States.

Species loss is occurring globally at unprecedented rates, and effective conservation planning requires an understanding of landscape characteristics that determine biodiversity patterns. Habitat heterogeneity is an important determinant of species diversity, but is difficult to measure across large areas using field-based methods that are costly and logistically challenging. Satellite image texture analysis offers a cost-effective alternative for quantifying habitat heterogeneity across broad spatial scales.

Vegetation productivity summarized by the Dynamic Habitat Indices explains broad-scale patterns of moose abundance across Russia.

Identifying the factors that determine habitat suitability and hence patterns of wildlife abundances over broad spatial scales is important for conservation. Ecosystem productivity is a key aspect of habitat suitability, especially for large mammals. Our goals were to a) explain patterns of moose (Alces alces) abundance across Russia based on remotely sensed measures of vegetation productivity using Dynamic Habitat Indices (DHIs), and b) examine if patterns of moose abundance and productivity differed before and after the collapse of the Soviet Union.