Species distribution models (SDMs) are often calibrated using presence‐only datasets plagued with environmental sampling bias, which leads to a decrease of model accuracy. In order to compensate for this bias, it has been suggested that background data (or pseudoabsences) should represent the area that has been sampled. However, spatially‐explicit knowledge of sampling effort is rarely available. In multi‐species studies, sampling effort has been inferred following the target‐group (TG) approach, where aggregated occurrence of TG species informs the selection of background data. However, little is known about the species‐ specific response to this type of bias correction. The present study aims at evaluating the impacts of sampling bias and bias correction on SDM performance. To this end, we designed a realistic system of sampling bias and virtual species based on 92 terrestrial mammal species occurring in the Mediterranean basin. We manipulated presence and background data selection to calibrate four SDM types. Unbiased (unbiased presence data) and biased (biased presence data) SDMs were calibrated using randomly distributed background data. We used real and TG‐estimated sampling efforts in background selection to correct for sampling bias in presence data. Overall, environmental sampling bias had a deleterious effect on SDM performance. In addition, bias correction improved model accuracy, and especially when based on spatially‐explicit knowledge of sampling effort. However, our results highlight important species‐specific variations in susceptibility to sampling bias, which were largely explained by range size: widely‐distributed species were most vulnerable to sampling bias and bias correction was even detrimental for narrow‐ranging species. Furthermore, spatial discrepancies in SDM predictions suggest that bias correction effectively replaces an underestimation bias with an overestimation bias, particularly in areas of low sampling intensity. Thus, our results call for a better estimation of sampling effort in multispecies system, and cautions the uninformed and automatic application of TG bias correction.

Aim The recent recovery of large carnivores in Europe has been explained as resulting from a decrease in human persecution driven by widespread rural land abandonment, paralleled by forest cover increase and the consequent increase in availability of shelter and prey. We investigated whether land cover and human population density changes are related to the relative probability of occurrence of three European large carnivores: the grey wolf (Canis lupus), the Eurasian lynx (Lynx lynx) and the brown bear (Ursus arctos). Location Europe, west of 64° longitude. Methods We fitted multi‐temporal species distribution models using >50,000 occurrence points with time series of land cover, landscape configuration, protected areas, hunting regulations and human population density covering a 24‐year period (1992–2015). Within the temporal window considered, we then predicted changes in habitat suitability for large carnivores throughout Europe. Results Between 1992 and 2015, the habitat suitability for the three species increased in Eastern Europe, the Balkans, North‐West Iberian Peninsula and Northern Scandinavia, but showed mixed trends in Western and Southern Europe. These trends were primarily associated with increases in forest cover and decreases in human population density, and, additionally, with decreases in the cover of mosaics of cropland and natural vegetation. Main conclusions Recent land cover and human population changes appear to have altered the habitat suitability pattern for large carnivores in Europe, whereas protection level did not play a role. While projected changes largely match the observed recovery of large carnivore populations, we found mismatches with the recent expansion of wolves in Central and Southern Europe, where factors not included in our models may have played a dominant role. This suggests that large carnivores’ co‐existence with humans in European landscapes is not limited by habitat availability, but other factors such as favourable human tolerance and policy.

Urbanisation and climate change are two global change processes that affect animal distributions, posing critical threats to biodiversity. Due to its versatile ecology and synurbic habits, Kuhl's pipistrelle (Pipistrellus kuhlii) offers a unique opportunity to explore the relative effects of climate change and urbanisation on species distributions. In a climate change scenario, this typically Mediterranean species is expected to expand its range in response to increasing temperatures. We collected 25,132 high-resolution occurrence records from P. kuhlii European range between 1980 and 2013 and modelled the species' distribution with a multi-temporal approach, using three bioclimatic variables and one proxy of urbanisation. Temperature in the coldest quarter of the year was the most important factor predicting the presence of P. kuhlii and showed an increasing trend in the study period; mean annual precipitation and precipitation seasonality were also relevant, but to a lower extent. Although urbanisation increased in recently colonised areas, it had little effect on the species' presence predictability. P. kuhlii expanded its geographical range by about 394 % in the last four decades, a process that can be interpreted as a response to climate change.