Abundance of a species can be a good proxy for persistence probability. However, in conservation planning, one typically only has distribution data (presence/absence) available for analysis. Species distribution models (SDMs) allow elucidation of the relationship between a species and its environment. Assuming that SDMs based on climate and land cover information capture a substantial proportion of the variation in factors that govern species ranges and population sizes, then the suitabilities (sometimes interpreted as probabilities of occurrence) output from SDMs should correlate with species abundances. I used data from the North American Breeding Bird Survey and two SDMs (GLM, GAM) to model suitability from presence-absence information across species ranges, and then tested whether the highest suitability values are associated with high abundance values for 30 test species.
For all species, high suitabilities are significantly correlated with high abundances, and further, the strength of this relationship is stronger for species for which the SDM demonstrated high sensitivity (high proportion of correctly-predicted presences). Thus, for the species considered here, species’ abundance structures across large geographic areas can be predicted with occurrence probabilities output from SDMs. These results represent a critical advance for conservation planning: allowing choices of conservation areas which are likely to enhance longer-term persistence even when abundance information is lacking.