Spatial patterns in species richness and the geometric constraint simulation model: a global analysis of mid-domain effect in Falconiformes

Edge effects and geometric constraints: a landscape-level empirical test

Edge effects are pervasive in landscapes yet their causal mechanisms are still poorly understood. Traditionally, edge effects have been attributed to differences in habitat quality along the edge-interior gradient of habitat patches, under the assumption that no edge effects would occur if habitat quality was uniform. This assumption was questioned recently after the recognition that geometric constraints tend to reduce population abundances near the edges of habitat patches, the so-called geometric edge effect (GEE). Here, we present the first empirical, landscape-level evaluation of the importance of the GEE in shaping abundance patterns in fragmented landscapes. Using a data set on the distribution of small mammals across 18 forest fragments, we assessed whether the incorporation of the GEE into the analysis changes the interpretation of edge effects and the degree to which predictions based on the GEE match observed responses. Quantitative predictions were generated for each fragment using simulations that took into account home range, density and matrix use for each species. The incorporation of the GEE into the analysis changed substantially the interpretation of overall observed edge responses at the landscape scale. Observed abundances alone would lead to the conclusion that the small mammals as a group have no consistent preference for forest edges or interiors and that the black-eared opossum Didelphis aurita (a numerically dominant species in the community) has on average a preference for forest interiors. In contrast, incorporation of the GEE suggested that the small mammal community as a whole has a preference for forest edges, whereas D. aurita has no preference for forest edges or interiors. Unexplained variance in edge responses was reduced by the incorporation of GEE, but remained large, varying greatly on a fragment-by-fragment basis. This study demonstrates how to model and incorporate the GEE in analyses of edge effects and that this incorporation is necessary to properly interpret edge effects in landscapes. It also suggests that geometric constraints alone are unlikely to explain the variability in edge responses of a same species among different areas, highlighting the need to incorporate other ecological factors into explanatory models of edge effects.

Identifying contact zone hotspots of passerine birds in the Palaearctic region

Birds are known to be a group rich in pairs of closely related species that have parapatric or allopatric distributions with relatively narrow contact zones. Here we analyse the geographical distribution of these contact zones for parapatric species pairs of passerine birds of the Palaearctic region. Their contact zones are located mainly in southwestern, northern and central-southern Asia, and in northwestern Africa, with a hotspot in the Middle East. A mid-domain effect null model, where contact zone hotspots are a neutral correlate of continental geometry, had a low explanatory power of 3.8%; the observed distribution of contact zones was not sufficiently predicted. Hypotheses involving range contractions and secondary contact in areas of high topographic and habitat diversity may offer more convincing explanations and offer promising perspectives for future studies.

The mid-domain effect revisited

We revisit the proposition that boundary constraints on species' ranges cause species richness gradients (the mid-domain effect [MDE] hypothesis). In the absence of environmental gradients, species should not retain their observed range sizes as assumed by MDE models. Debate remains regarding the definition of domain limits, valid predictions for testing the models, and their statistical assessment. Empirical support for the MDE is varied but often weak, suggesting that geometric constraints on species' ranges do not provide a general explanation for richness gradients. Criticism of MDE model assumptions does not, however, imply opposition to the use of null models in ecology.