Abstract

AbstractAimBirds (class Aves) overall follow the expected latitudinal gradient in species richness. However, there is a poorly understood secondary peak in bird richness at about 45° N latitude, at least in North America. Waterfowl (Anseriformes) species richness conforms to this secondary peak, yet this group is commonly excluded from bird species richness studies and consequently the drivers of waterfowl richness are poorly understood. Here, we explore the drivers of waterfowl richness on a global scale, emphasizing the secondary peak.LocationGlobal.MethodsWe mapped total waterfowl species richness for the breeding and non‐breeding seasons. Considering a wide range of potential environmental drivers (climate, productivity and habitat), we initially ran univariate ordinary least squares models for the candidate set of predictors. We then used regression trees (RT) to multivariately assess their importance for the richness pattern while allowing for nonlinear and non‐stationary processes.ResultsWe found seasonal variability in plant productivity (measured by the normalized difference vegetation index, NDVI) to be the most important predictor of breeding season richness in both univariate regressions and multivariate RT models. For the non‐breeding season, winter actual evapotranspiration (AET) was the best predictor. In the regions of highest richness, including the secondary mid‐latitude peak, an overwhelming portion of the species were migratory species.Main conclusionsPredictors commonly used to explain the large‐scale richness patterns of birds, such as annual AET or annual NDVI explained little of the variation in richness in Anseriformes. Instead, measures reflecting intra‐annual variability and seasonal productivity in the relevant season were the best predictors. This finding, combined with the high proportion of migrants in the richness peaks, strongly suggests that the patterns of richness in Anseriformes reflect the group's exploitation of seasonal environmental variability via short‐ and long‐distance migration, i.e. temporal niche exploitation at an annual and global scale.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call