Modeling Spatial Trends in Estimated Species Richness using Breeding Bird Survey Data: A Valuable Tool in Biodiversity Assessment

Abstract

We used data from the French breeding bird survey to estimate local bird species richness within sampled sites, using capture–recapture models. We investigated the possible effects of habitat structure and composition (landscape fragmentation, habitat cover and diversity) on estimated species richness at a local scale, and used the identified trends to help with modeling species richness at a large spatial scale. We performed geostatistical analyses based on spatial autocorrelation – cokriging models – to interpolate estimated species richness over the entire country, providing an opportunity to predict species-rich areas. We further compared species richness obtained with this method to species and rarity richness obtained using a national atlas of breeding birds. Estimated species richness was higher in species richness hotspots identified by the atlas. Combining informations on rare species from Atlas and species richness estimates from sound sampling based schemes should help with identifying species-rich areas for various taxa and locating biodiversity hotspots to be protected as high conservation value areas, especially in temperate zones where diversity hotspots are likely to match centers of high species richness because of very few centers of true endemicity.