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Climate change may determine future trends of animal populations. Specifically, climate limitations may be released or tightened depending on species¿ climatic preferences. Here we assessed the limitation imposed by annual mean temperature and annual precipitation on the maximum potential abundance of 28 common bird species monitored by SACRE Program of SEO/BirdLife throughout 20 years. For each species we developed 20 models, each one corresponding to one year, and assessed their predictive capacity in the remaining 19 years. We found that 98% of models were better than the null model (dAIC<7). Moreover, both temperature and precipitation showed significantly consistent coefficients across 20 models in 24 species (p < 0.05). Model prediction had an average success rate of 90%, so that the observed maximum abundance of species fell within the range of predictions in 89-93% of the 380 tests made for each species. Variation in training data originated large differences in abundance forecasts. Nonetheless, for most species, all training models predicted consistent trends under future climate change scenarios. For 13 of these species, the maximum potential abundance was predicted to increase in peninsular Spain by 2041-2060 under the RCP8.5 scenario, while population trends were predicted to be negative in three species. Our results suggest that climate change could release the limitation imposed by climate for a large number of the study species, though other factors such as land use changes could determine the level to which these maximum numbers are effectively attained in the future.

[Aim]: While the contribution of abiotic factors to species distribution is well known, the geographic structure, if any, of biotic interactions within the species range is poorly understood. Most studies neglect biotic interactions when generating Species Distribution Models (SDMs) and projecting them, using future climatic scenarios, while others argue that biotic interactions may extend species tolerances to suboptimal abiotic conditions. Elucidating the extent to which biotic interactions play a role at a macro‐scale is challenging due to its inherent complexity. In this study, we characterized the independent contribution of prey abundance distributions on the Merlin's wintering distribution (Falco columbarius). Then, to examine the hypothesis that biotic interactions may counteract other suboptimal conditions, we tested for a differential importance of physical habitat characteristics and prey abundance distributions along the species’ wintering range., [Location]: Peninsular Spain., [Methods]: We modelled the Merlin's geographic distribution with Boosted Classification Trees as a function of environmental predictors (environmental model) and prey relative abundances (prey model), either separately or jointly (combined model). We tested whether the predictive success of environmental and prey models differ spatially., [Results]: Partialling out the variation into independent components we found that the prey abundance distributions explained the largest part of variation. Furthermore, the first four predictors with the highest contribution in our combined models were the abundances of prey species. Finally, our model predictions revealed a north‐to‐south increase in the importance of prey abundance distributions. Interestingly, our results suggest that biotic interactions can enable species to inhabit a wider range of suboptimal habitat conditions on range margins., [Main conclusions]: Relevant biotic interactions may not be always fully interchangeable with environmental surrogates. Abiotic factors and biotic interactions may shape species range limits and cores of distributions differently. Neglecting biotic interactions may compromise spatiotemporal transferability of SDMs, especially on species margins, and hence their applicability.

A comprehensive review of the natural history of the Yellow Wagtail Motacilla flava in Spain.

A comprehensive review of the natural history of the Grey Wagtail Motacilla cinerea in Spain.

A comprehensive review of the natural history of the Black Kite Milvus migrans in Spain.

Background. The availability of environmental energy, as measured by temperature, is expected to limit the abundance and distribution of endotherms wintering at temperate latitudes. A prediction of this hypothesis is that birds should attain their highest abundances in warmer areas. However, there may be a spatial mismatch between species preferred habitats and species preferred temperatures, so some species might end-up wintering in sub-optimal thermal environments. Methods. We model the influence of minimum winter temperature on the relative abundance of 106 terrestrial bird species wintering in peninsular Spain, at 10 ×10 km resolution, using 95%-quantile regressions. We analyze general trends across species on the shape of the response curves, the environmental preferred temperature (at which the species abundance is maximized), the mean temperature in the area of distribution and the thermal breadth (area under the abundance-temperature curve). Results. Temperature explains a low proportion of variation in abundance. The most significant effect is on limiting the maximum potential abundance of species. Considering this upper-limit response, there is a large interspecific variability on the thermal preferences and specialization of species. Overall, there is a preponderance of positive relationships between species abundance and temperature; on average, species attain their maximum abundances in areas 1.9 °C warmer than the average temperature available in peninsular Spain. The mean temperature in the area of distribution is lower than the thermal preferences of the species. Discussion. Many species prefer the warmest areas to overwinter, which suggests that temperature imposes important restrictions to birds wintering in the Iberian Peninsula. However, one third of species overwinter in locations colder than their thermal preferences, probably reflecting the interaction between habitat and thermal requirements. There is a high inter-specific variation in the ve

© 2015 John Wiley & Sons Ltd. Aim: Quantifying species abundances is costly, especially when many species are involved. To overcome this problem, several studies have predicted local abundances (at the sample unit level) from species occurrence distribution models (SODMs), with differences in predictive performance among studies. Surprisingly, the ability of SODM to predict regional abundances of an entire area of interest has never been tested, despite the fact that it is an essential parameter for species conservation and management. We tested whether local and regional abundances of 21 terrestrial bird species could be predicted from SODMs in an exhaustively surveyed island, and examined the variation explained by species-specific traits. Location: La Palma Island, Canary Islands. Methods: We firstly assessed two types of algorithms representing the two main families of SODMs. We built models using presence/absence (boosted classification trees) and presence/background (MaxEnt) data as a function of relevant environmental predictors and tested their ability to predict the observed local abundances. The predicted probabilities of occurrence (Pi) were translated into animal numbers (n′) using the revisited equation ni′ = -ln(1-Pi), and we obtained regional abundances (for the whole island). Results: Predictive ability of presence/absence models was superior than that of MaxEnt. At the regional level, the observed average densities of all species were highly predictable from occurrence probabilities (R2 = 93.5%), without overall overestimation or underestimation. Interspecific variation in the accuracy of predicted regional density was largely explained (R2 = 73%), with habitat breath and variation in local abundance being the traits of greatest importance. Main conclusions: Despite uncertainties associated with local predictions and the idiosyncrasies of each species, our procedures enabled us to predict regional abundances in an unbiased way. Our approach provides