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Explanation of the spatial distribution patterns in species richness, and especially those of small-ranged species (endemics), bears relevance for studies on evolution and speciation, as well as for conservation management. We test a geometric constraint model, the mid-domain effect (MDE), as a possible explanation for spatial patterns of species richness in Palearctic songbirds (Passeriformes), with an emphasis on the patterns of small-ranged species. We calculated species richness based on digitised distribution maps of phylogenetic species of songbirds endemic to the Palearctic region. Data were plotted and analyzed over a one degree equal area map of the Palearctic Region, with a grid cell area of 4062 km². The emergent biogeographic patterns were analysed with WORLDMAP software. Comparison of the observed richness pattern among 2401 phylogenetic taxa of songbirds in the Palearctic Region with the predictions of a fully stochastic bi-dimensional MDE model revealed that this model has limited empirical support for overall species richness of Palearctic songbirds. Major hotspots were located south of the area where MDE predicted the highest species- richness, while some of the observed coldspots were in the centre of the Palearctic Region. Although small-ranged species are often found in areas with the highest species richness, MDE models have a very restricted explanatory power for the observed species-richness pattern in small-ranged species. Regions with a high number of small-ranged species (endemism hotspots) may contain a unique set of environmental conditions, unrelated to the shape or size of the domain, allowing a multitude of species to co-exist.

In the study of diversity patterns, the Mid-domain effect (MDE), which explains gradients in diversity solely on the basis of geometric constraints, has emerged as a null-model against which other hypotheses can be tested. The effectiveness, measured by its predictive power, of these MDE models appears to depend on the size of the study area and the range-sizes of the taxa considered. Here we test the predictive power of MDE on the species richness patterns of birds and assess its effectiveness for a variety of species range sizes. We digitised distribution maps of 889 species of songbird endemic to the Palearctic, and analysed the emergent biogeographic patterns with WORLDMAP software. MDE had a predictive power of 20% when all songbirds were included. Major hotspots were located south of the area where MDE predicted the highest species-richness, and some of the observed coldspots were in the centre of the Palearctic, contradicting the predictions of the MDE. MDE had little explanatory power (3-19%) for all but the largest range sizes, whereas MDE performed equal or better for the large-ranged species (20-34%) compared to the overall model. Overall MDE did not accurate explain species-richness patterns in Palearctic songbirds. Subsets of larger-range species did not always have a larger predictive power than smaller-range species or the overall model. Despite their low predictive power, MDE models can have a role to play in explaining biogeographic patterns but other variables need to be included in the model as well.