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Aim: The need to forecast range shifts under future climate change has motivated an increasing interest in better understanding the role of biotic interactions in driving diversity patterns. The contribution of biotic interactions to shaping broad‐scale species distributions is, however, still debated, partly due to the difficulty of detecting their effects. We aim to test whether spatial exclusion between potentially competing species can be detected at the species range scale, and whether this pattern relates to fine‐scale mechanisms of coexistence. Location: Western Palearctic. Methods: We develop and evaluate a measure of geographic avoidance that uses outputs of species distribution models to quantify geographic exclusion patterns expected if interspecific competition affects broad‐scale distributions. We apply the measure to 10 Palearctic bat species belonging to four morphologically similar cryptic groups in which competition is likely to occur. We compare outputs to null models based on pairs of virtual species and to expectations based on ecological similarity and fine‐scale coexistence mechanisms. We project changes in range suitability under climate change taking into account effects of geographic avoidance. Results: Values of geographic avoidance were above null expectations for two cryptic species pairs, suggesting that interspecific competition could have contributed to shaping their broad‐scale distributions. These two pairs showed highest levels of ecological similarity and no trophic or habitat partitioning. Considering the role of competition modified predictions of future range suitability. Main conclusions: Our results support the role of interspecific competition in limiting the geographic ranges of morphologically similar species in the absence of fine‐scale mechanisms of coexistence. This study highlights the importance of incorporating biotic interactions into predictive models of range shifts under climate change, and the need for further integration of community ecology with species distribution models to understand the role of competition in ecology and biogeography. [ABSTRACT FROM AUTHOR]

Inferences of the interactions between species' ecological niches and spatial distribution have been historically based on simple metrics such as low-resolution dietary breadth and range size, which might have impeded the identification of meaningful links between niche features and spatial patterns. We analysed the relationship between dietary niche breadth and spatial distribution features of European bats, by combining continent-wide DNA metabarcoding of faecal samples with species distribution modelling. Our results show that while range size is not correlated with dietary features of bats, the homogeneity of the spatial distribution of species exhibits a strong correlation with dietary breadth. We also found that dietary breadth is correlated with bats' hunting flexibility. However, these two patterns only stand when the phylogenetic relations between prey are accounted for when measuring dietary breadth. Our results suggest that the capacity to exploit different prey types enables species to thrive in more distinct environments and therefore exhibit more homogeneous distributions within their ranges. Ecological niche breadth may help explain spatial distribution patterns in animals. In this study on European bats, Alberdi et al. combine DNA metabarcoding and species distribution modelling to show that dietary niche breadth is related to hunting flexibility and broad-scale spatial patterns in species distribution. [ABSTRACT FROM AUTHOR]

The Iberian Peninsula supports a high diversity of bumblebees, with 38 species all of which are at or near the south-western edge of their range. We might expect them to be threatened by climate change, but their distributions within Iberia are poorly documented., In this study, we examine the climatic conditions that explain the distribution of Iberian bumblebees. Species distribution models (SDMs) were built using a presence-only technique (Maxent), incorporating presence data of Iberian bumblebees (initially 5795 records for 38 species) with seven climatic variables., We observed that: (i) mountain regions were highlighted as rich in species (bumblebee hot spots); (ii) rare species are climatic specialist species that mainly inhabit mountain regions; (iii) common species are more tolerant of a broader range of climates, notably of higher temperatures; (iv) some areas of Iberia are largely undersampled, including areas predicted to support high bumblebee diversity., We identify areas where targeted searches may reveal undiscovered populations of rare bumblebee species. Obtaining a good knowledge of the current distribution of species is a vital first step towards devising approaches for their conservation. [ABSTRACT FROM AUTHOR]

Species distribution models (SDMs) offer an effective tool for identifying species conservation requirements and forecasting how global environmental changes will affect species diversity and distribution. This approach is particularly relevant for bats because their nocturnal behaviour hinders detectability and identification in flight. Despite their important contribution to global biodiversity and wide geographical ranges, bats have been under-represented in early SDM studies, and only in the last few years has this approach become more widely used in bat research. We carried out a meta-analysis of the published literature to review the history of the use of SDMs in bat research and their application in conservation, climate change assessments and genetic studies. We focus on the geographical coverage, theme and modelling algorithm of published studies, and compare studies that are uniquely dedicated to bats to multi-taxa studies that include bats. We provide recommendations for good modelling practices through considering spatial scale and spatial biases, selecting ecologically relevant variables, following rigorous modelling protocols, and recognising the limitations of extrapolation across temporal scales. We suggest future developments that will further favour the use of SDMs to study bat ecology and biogeography, as well as inform conservation management. We conclude that despite an increase in bat SDM studies, their scope and application can be further enhanced through incorporating dispersal, landscape connectivity and biotic interactions between bats, their prey and their pathogens. [ABSTRACT FROM AUTHOR]

Species distribution models were used to predict bat species richness across southern Africa and to identify potential drivers of these spatial patterns. We also identified species richness within each biotic zone and the distributions of species considered of high conservation priority. We used this information to highlight conservation priorities for bats in southern Africa (defined here as between the latitudes of 8° S, slightly north of Zambia, to the southern tip of Africa 34° S, an area of approximately 9781840 km²). We used maximum entropy modelling (Maxent) to model habitat suitability for 58 bat species in order to determine the key eco-geographical variables influencing their distributions. The potential distribution of each bat species was affected by different ecogeographic variables but in general, water availability (both temporary and permanent), seasonal precipitation, vegetation, and karst (caves/limestone) areas were the most important factors. The highest levels of species richness were found mainly in the eastern dry savanna area and some areas of wet savanna. Of the species considered to be of high priority due to a combination of restricted distributions or niches and/or endemism (7 fruit bats, 23 cave-dwellers, 18 endemic and near-endemic, 14 niche-restricted and 15 range-restricted), nine species were considered to be at most risk. We found that range-restricted species were commonly found in areas with low species richness; therefore, conservation decisions need to take into account not only species richness but also species considered to be particularly vulnerable across the biogeographical area of interest. [ABSTRACT FROM AUTHOR]

Aim A common pattern in biogeography is the scale-dependent effect of environmental variables on the spatial distribution of species. We tested the role of climatic and land cover variables in structuring the distribution of genetic variation in the grey long-eared bat, Plecotus austriacus, across spatial scales. Although landscape genetics has been widely used to describe spatial patterns of gene flow in a variety of taxa, volant animals have generally been neglected because of their perceived high dispersal potential. Location England and Europe. Methods We used a multiscale integrated approach, combining population genetics with species distribution modelling and geographical information under a causal modelling framework, to identify landscape barriers to gene flow and their effect on population structure and conservation status. Genotyping involved 23 polymorphic microsatellites and 259 samples from across the species' range. Results We identified distinct population structure shaped by geographical barriers and evidence of population fragmentation at the northern edge of the range. Habitat suitability (as captured by species distribution models, SDMs) was the most important landscape variable affecting genetic connectivity at the broad spatial scale, while at the fine scale, lowland unimproved grasslands, the main foraging habitat of P. austriacus, played a pivotal role in promoting genetic connectivity. Main conclusions The importance of lowland unimproved grasslands in determining the biogeography and genetic connectivity in P. austriacus highlights the importance of their conservation as part of a wider landscape management for fragmented edge populations. This study illustrates the value of using SDMs in landscape genetics and highlights the need for multiscale approaches when studying genetic connectivity in volant animals or taxa with similar dispersal abilities. [ABSTRACT FROM AUTHOR]

Competition may lead to changes in a species’ environmental niche in areas of sympatry and shifts in the niche of weaker competitors to occupy areas where stronger ones are rarer. Although mainland Mediterranean (Rhinolophus euryale) and Mehely’s (R. mehelyi) horseshoe bats mitigate competition by habitat partitioning, this may not be true on resource-limited systems such as islands. We hypothesize that Sardinian R. euryale (SAR) have a distinct ecological niche suited to persist in the south of Sardinia where R. mehelyi is rarer. Assuming that SAR originated from other Italian populations (PES) – mostly allopatric with R. mehelyi – once on Sardinia the former may have undergone niche displacement driven by R. mehelyi. Alternatively, its niche could have been inherited from a Maghrebian source population. We: a) generated Maxent Species Distribution Models (SDM) for Sardinian populations; b) calibrated a model with PES occurrences and projected it to Sardinia to see whether PES niche would increase R. euryale’s sympatry with R. mehelyi; and c) tested for niche similarity between R. mehelyi and PES, PES and SAR, and R. mehelyi and SAR. Finally we predicted R. euryale’s range in Northern Africa both in the present and during the Last Glacial Maximum (LGM) by calibrating SDMs respectively with SAR and PES occurrences and projecting them to the Maghreb. R. mehelyi and PES showed niche similarity potentially leading to competition. According to PES’ niche, R. euryale would show a larger sympatry with R. mehelyi on Sardinia than according to SAR niche. Such niches have null similarity. The current and LGM Maghrebian ranges of R. euryale were predicted to be wide according to SAR’s niche, negligible according to PES’ niche. SAR’s niche allows R. euryale to persist where R. mehelyi is rarer and competition probably mild. Possible explanations may be competition-driven niche displacement or Maghrebian origin. [ABSTRACT FROM AUTHOR]

To determine what shapes the distributions of cryptic species, we aimed to unravel ecological niches and geographical distributions of three cryptic bat species complexes in Iberia, Plecotus auritus/ begognae, Myotis mystacinus/ alcathoe and Eptesicus serotinus/ isabellinus (with 44, 69, 66, 27, 121 and 216 records, respectively), considering ecological interactions and biogeographical patterns. Species distribution models ( SDMs) were built using a presence-only technique ( Maxent), incorporating genetically identified species records with environmental variables (climate, habitat, topography). The most relevant variables for each species' distribution and respective response curves were then determined. SDMs for each species were overlapped to assess the contact zones within each complex. Niche analyses were performed using niche metrics and spatial principal component analyses to study niche overlap and breadth. The Plecotus complex showed a parapatric distribution, although having similar biogeographical affinities ( Eurosiberian), possibly explained by competitive exclusion. The Myotis complex also showed Eurosiberian affinities, with high overlap between niches and distribution, suggesting resource partitioning between species. Finally, E. serotinus was associated with Eurosiberian areas, while E. isabellinus occurred in Mediterranean areas, suggesting possible competition in their restricted contact zone. This study highlights the relevance of considering potential ecological interactions between similarly ecological species when assessing species distributions. © 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 112,150-162. [ABSTRACT FROM AUTHOR]

1. We evaluated the accuracy of presence-only modelling for predicting the distribution of rare species, when data are scarce and usually collected with sampling biases. We modelled the potential distribution in Portugal of one of the rarest European bats Barbastella barbastellus and subsequently ground-validated predictions by using acoustic transects. 2. We used ecological niche factor analysis (ENFA) and maximum entropy (Maxent) modelling to build distribution models of B. barbastellus, and determined which ecological factors were more relevant for each model. As ENFA only accepts continuous variables, we built one Maxent model using the same variables as ENFA and another using land cover as a categorical variable. 3. Ecological niche factor analysis and both Maxent models predicted similar areas of occurrence in central and northern regions of Portugal, although ENFA predicted suitable habitat over a wider range. Conversely, there was substantial disagreement on the location of high-suitability areas in the south. This could be a consequence of a different choice of important variables made by each model. Native woodland and average temperature were the most relevant variables for Maxent, while in ENFA B. barbastellus was linked to higher altitudes although avoiding production forests and infrastructures. 4. Threshold-independent and -dependent statistics showed that Maxent models outperformed ENFA, probably as a consequence of divergent predictions in the new areas of occurrence. Overall, 15 new B. barbastellus sites were discovered and known distribution was extended c. 100 km to the south. 5. Synthesis and applications. Our results support the use of presence-only modelling as an indispensible tool for survey design as shown by the discovery of B. barbastellus populations outside of the previously known range. ENFA seems to be more suited to determining a species’ potential distribution, although failing to extrapolate it. In contrast, Maxent is better suited to determining a species’ realized distribution. It was successful in predicting occurrence in previously unsurveyed areas and can be recommended as a technique for determination of a conservative distribution for a species. Maxent modelling would greatly aid biodiversity conservation, especially when it is necessary to develop survey plans or first assessments of a species’ distribution. [ABSTRACT FROM AUTHOR]

Abstract: Bats are often killed in large numbers at wind farms over a wide geographical range. We aimed to predict which areas conferred higher fatality risks to bats at wind farms. In an innovative approach, we combined species distribution modelling with mortality data and the ecological conditions at wind farms located in Portugal. We then generated predictive models to determine areas of probable mortality and which environmental factors were promoting it. Mortality data for four bat species, Hypsugo savii, Nyctalus leisleri, Pipistrellus kuhlii and Pipistrellus pipistrellus, were used. These experienced the highest levels of fatalities at wind farms in Portugal, comprising 290 of the 466 fatalities recorded from 2003 to 2011. The mortality risk models showed robust performances. Wind farms sited at humid areas with mild temperatures, closer than 5km to forested areas and within 600m of steep slopes showed higher probabilities of mortality. High mortality risk areas also overlapped highly with the potential distribution of N. leisleri in Portugal, suggesting that populations of this species may be at high risk due to wind farm fatalities. Moreover, a large extent of the area predicted to be a hotspot for mortality (i.e. areas likely to confer high mortality risk for four species) overlaps with sites highly suitable for wind farm construction. In summary, the approach used in this study could be paradigmatic for the development of important pre-emptive conservation measures for bat populations by identifying mortality risk in areas prior to wind farm installation and determining which conditions promote mortality. [Copyright &y& Elsevier]