Explaining Bird Richness With 30‐m Resolution Dynamic Habitat Indices Derived From Landsat Satellite Data Across the Conterminous <scp>US</scp>

ABSTRACT Aim Biodiversity is declining at a rapid rate, and effective conservation necessitates understanding the drivers of species richness patterns at management‐relevant scales. Vegetation productivity data derived from satellite data estimate the available energy in ecosystems, allowing the generation of relevant indices that explain biodiversity patterns. The Dynamic Habitat Indices (DHIs) summarise three metrics of annual productivity. Our goal was to compare the predictive performance of DHIs derived from higher spatial but lower temporal resolution (Landsat) versus coarser spatial but higher temporal resolution (MODIS) in models explaining bird richness. Location The conterminous United States. Methods Using North American Breeding Bird Survey data, we calculated richness overall and for nine functional guilds for two periods (1991–2000, 2011–2019). We summarised the DHIs from Landsat (1991–2000, 2011–2020) and MODIS (2011–2020) at four spatial extents, matching our bird data for (a) 85 ecoregions, (b) 5‐km squares matching the area surveyed by a full BBS route, (c) 2.5‐km squares matching the first ten stops, and (d) 0.5‐km square buffers matching the first stop. Results The predictive performance of DHIs based on Landsat and MODIS for the four spatial extents was similar, and Landsat DHIs explained up to 48% of the variance in bird richness. In multivariate models combining Landsat DHIs with topography and land cover, the DHIs complemented other variables well and explained up to 65% of the variance in bird richness. The predictive performance of 1991–2000 Landsat DHIs was similar to that of the 2011–2020 Landsat DHIs, despite considerably fewer Landsat images being available in the 1990s. Main Conclusions Despite its lower temporal resolution, the finer spatial resolution of Landsat DHIs explained species richness well. Landsat‐based DHIs offer the advantage of management‐relevant resolution over broad areas and capture more of the heterogeneity in landcover that small bodied species respond to than coarser resolution products.