Bird diversity: a predictable function of satellite-derived estimates of seasonal variation in canopy light absorbance across the United States

Aim  To investigate the relationships between bird species richness derived from the North American Breeding Bird Survey and estimates of the average, minimum, and the seasonal variation in canopy light absorbance (the fraction of absorbed photosynthetically active radiation, fPAR) derived from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS).
Location  Continental USA.
Methods  We describe and apply a 'dynamic habitat index' (DHI), which incorporates three components based on monthly measures of canopy light absorbance through the year. The three components are the annual sum, the minimum, and the seasonal variation in monthly fPAR, acquired at a spatial resolution of 1 km, over a 6-year period (2000–05). The capacity of these three DHI components to predict bird species richness across 84 defined ecoregions was assessed using regression models.
Results  Total bird species richness showed the highest correlation with the composite DHI R ² = 0.88, P  < 0.001, standard error of estimate (SE) = 8 species], followed by canopy nesters ( R ² = 0.79, P  < 0.001, SE = 3 species) and grassland species ( R ² = 0.74, P  < 0.001, SE = 1 species). Overall, the seasonal variation in fPAR, compared with the annual average fPAR, and its spatial variation across the landscape, were the components that accounted for most ( R ² = 0.55–0.88) of the observed variation in bird species richness.
Main conclusions  The strong relationship between the DHI and observed avian biodiversity suggests that seasonal and interannual variation in remotely sensed fPAR can provide an effective tool for predicting patterns of avian species richness at regional and broader scales, across the conterminous USA.