MAXENT is now a common species distribution modeling (SDM) tool used by conservation practitioners for predicting the distribution of a species from a set of records and environmental predictors. However, datasets of species occurrence used to train the model are often biased in the geographical space because of unequal sampling effort across the study area. This bias may be a source of strong inaccuracy in the resulting model and could lead to incorrect predictions. Although a number of sampling bias correction methods have been proposed, there is no consensual guideline to account for it. We compared here the performance of five methods of bias correction on three datasets of species occurrence: one “virtual” derived from a land cover map, and two actual datasets for a turtle (Chrysemys picta) and a salamander (Plethodon cylindraceus). We subjected these datasets to four types of sampling biases corresponding to potential types of empirical biases. We applied five correction methods to the biased samples and compared the outputs of distribution models to unbiased datasets to assess the overall correction performance of each method. The results revealed that the ability of methods to correct the initial sampling bias varied greatly depending on bias type, bias intensity and species. However, the simple systematic sampling of records consistently ranked among the best performing across the range of conditions tested, whereas other methods performed more poorly in most cases. The strong effect of initial conditions on correction performance highlights the need for further research to develop a step-by-step guideline to account for sampling bias. However, this method seems to be the most efficient in correcting sampling bias and should be advised in most cases.

Aim Studies of environmental niche shift/niche conservatism that are based on species distribution modelling require a quantification of niche purity and potential overlap. Although various metrics have been proposed for this task, no comparisons of their performance are available yet that express the linearity of range shifts and error-proneness. Herein, we assess the performance of six niche overlap metrics using three sister pairs of plethodontid salamanders as well as artificial species to test for linearity of overlap curves, impacts of varying potential distribution sizes and study area sizes.Location North America, artificial environments.Methods Species distribution models for the salamanders were performed with Maxent, and artificial species were created in the R environment. Potential distributions of species with varying range sizes and extents of the study area were compared using the Bray-Curtis distance BC, Schoener's D, two different modifications of the Hellinger distance Imod, Icor, Pianka's O and Horn's R. Niche overlaps in ecological space were compared using linear discriminant analyses based on principal components. ResultsSimulations of niche overlaps revealed strong variations in the performance of the niche overlap metrics. In artificial species, BC and D performed best, followed by O, R and Icor, but the modified Hellinger distance Imod showed a nonlinear slope and a truncated range. Furthermore, the simulations suggest that, in proportionally small potential distributions on large grids, an inclusion of a high proportion of grid cells with low occurrence probabilities representing background noise may bias assessments of niche overlaps. Main conclusions Both the salamander examples and simulations suggest thatSchoener's D and the Bray-Curtis distance BC are best suited to compute niche overlaps from potential distributions derived from species distribution models. However, like all analysed metrics, both D and BC are seriously affected by the inclusion of high numbers of grid cells where the species are probably absent, i.e. with low occurrence probabilities. Therefore, pre-processing to eliminate background noise in the potential distribution grids is highly recommended.

Anthropogenic global climate change has already led to alterations in biodiversity patterns by directly and indirectly affecting species distributions. It has been suggested that poikilothermic animals, including reptiles, will be particularly affected by global change and large-scale reptile declines have already been observed. Currently, half of the world's freshwater turtles and tortoises are considered threatened with extinction, and climate change may exacerbate these declines. In this study, we assess how global chelonian species richness will change in the near future. We use species distribution models developed under current climate conditions for 78% of all extant species and project them onto different Intergovernmental Panel on Climate Change (IPCC) scenarios for 2080. We detect a strong dependence of temperature shaping most species ranges, which coincide with their general temperature-related physiological traits (i.e., temperature-dependent sex determination). Furthermore, the extent and distribution of the current bioclimatic niches of most chelonians may change remarkably in the near future, likely leading to a substantial decrease of local species abundance and ultimately a reduction in species richness. Future climatic changes may cause the ranges of 86% of the species to contract, and of these ranges, nearly 12% are predicted to be situated completely outside their currently realized niches. Hence, the interplay of increasing habitat fragmentation and loss due to climatic stress may result in a serious threat for several chelonian species.

Quantifying species distributions using species distribution models (SDMs) has emerged as a central method in modern biogeography. These empirical models link species occurrence data with spatial environmental information. Since their emergence in the 1990s, thousands of scientific papers have used SDMs to study organisms across the entire tree of life, with birds commanding considerable attention. Here, we review the current state of avian SDMs and point to challenges and future opportunities for specific applications, ranging from conservation biology, invasive species and predicting seabird distributions, to more general topics such as modeling avian diversity, niche evolution and seasonal distributions at a biogeographic scale. While SDMs have been criticized for being phenomenological in nature, and for their inability to explicitly account for a variety of processes affecting populations, we conclude that they remain a powerful tool to learn about past, current, and future species distributions -at least when their limitations and assumptions are recognized and addressed. We close our review by providing an outlook on prospects and synergies with other disciplines in which avian SDMs can play an important role.

The climatic cycles of the Quaternary, during which global mean annual temperatures have regularly changed by 5–10°C, provide a special opportunity for studying the rate, magnitude, and effects of geographic responses to changing climates. During the Quaternary, high- and mid-latitude species were extirpated from regions that were covered by ice or otherwise became unsuitable, persisting in refugial retreats where the environment was compatible with their tolerances. In this study we combine modern geographic range data, phylogeny, Pleistocene paleoclimatic models, and isotopic records of changes in global mean annual temperature, to produce a temporally continuous model of geographic changes in potential habitat for 59 species of North American turtles over the past 320 Ka (three full glacial-interglacial cycles). These paleophylogeographic models indicate the areas where past climates were compatible with the modern ranges of the species and serve as hypotheses for how their geographic ranges would have changed in response to Quaternary climate cycles. We test these hypotheses against physiological, genetic, taxonomic and fossil evidence, and we then use them to measure the effects of Quaternary climate cycles on species distributions. Patterns of range expansion, contraction, and fragmentation in the models are strongly congruent with (i) phylogeographic differentiation; (ii) morphological variation; (iii) physiological tolerances; and (iv) intraspecific genetic variability. Modern species with significant interspecific differentiation have geographic ranges that strongly fluctuated and repeatedly fragmented throughout the Quaternary. Modern species with low genetic diversity have geographic distributions that were highly variable and at times exceedingly small in the past. Our results reveal the potential for paleophylogeographic models to (i) reconstruct past geographic range modifications, (ii) identify geographic processes that result in genetic bottlenecks; and (iii) predict threats due to anthropogenic climate change in the future.

Studies of Hordeum vulgare subsp. spontaneum, the wild progenitor of cultivated barley, have mostly relied on materials collected decades ago and maintained since then ex situ in germplasm repositories. We analyzed spatial genetic variation in wild barley populations collected rather recently, exploring sequence variations at seven single-copy nuclear loci, and inferred the relationships among these populations and toward the genepool of the crop. The wild barley collection covers the whole natural distribution area from the Mediterranean to Middle Asia. In contrast to earlier studies, Bayesian assignment analyses revealed three population clusters, in the Levant, Turkey, and east of Turkey, respectively. Genetic diversity was exceptionally high in the Levant, while eastern populations were depleted of private alleles. Species distribution modeling based on climate parameters and extant occurrence points of the taxon inferred suitable habitat conditions during the ice-age, particularly in the Levant and Turkey. Together with the ecologically wide range of habitats, they might contribute to structured but long-term stable populations in this region and their high genetic diversity. For recently collected individuals, Bayesian assignment to geographic clusters was generally unambiguous, but materials from genebanks often showed accessions that were not placed according to their assumed geographic origin or showed traces of introgression from cultivated barley. We assign this to gene flow among accessions during ex situ maintenance. Evolutionary studies based on such materials might therefore result in wrong conclusions regarding the history of the species or the origin and mode of domestication of the crop, depending on the accessions included.

Conservation genetics is a well‐established scientific field. However, limited information transfer between science and practice continues to hamper successful implementation of scientific knowledge in conservation practice and management. To mitigate this challenge, we have established a conservation genetics community, which entails an international exchange‐and‐skills platform related to genetic methods and approaches in conservation management. First, it allows for scientific exchange between researchers during annual conferences. Second, personal contact between conservation professionals and scientists is fostered by organising workshops and by popularising knowledge on conservation genetics methods and approaches in professional journals in national languages. Third, basic information on conservation genetics has been made accessible by publishing an easy‐to‐read handbook on conservation genetics for practitioners. Fourth, joint projects enabled practitioners and scientists to work closely together from the start of a project in order to establish a tight link between applied questions and scientific background. Fifth, standardised workflows simplifying the implementation of genetic tools in conservation management have been developed. By establishing common language and trust between scientists and practitioners, all these measures help conservation genetics to play a more prominent role in future conservation planning and management.

Climate is a major factor delimiting species' distributions. However, biotic interactions may also be prominent in shaping geographical ranges, especially for parapatric species forming hybrid zones. Determining the relative effect of each factor and their interaction of the contact zone location has been difficult due to the lack of broad scale environmental data. Recent developments in species distribution modelling (SDM) now allow disentangling the relative contributions of climate and species' interactions in hybrid zones and their responses to future climate change. We investigated the moving hybrid zone between the breeding ranges of two parapatric passerines in Europe. We conducted SDMs representing the climatic conditions during the breeding season. Our results show a large mismatch between the realized and potential distributions of the two species, suggesting that interspecific interactions, not climate, account for the present location of the contact zone. The SDM scenarios show that the southerly distributed species, Hippolais polyglotta, might lose large parts of its southern distribution under climate change, but a similar gain of novel habitat along the hybrid zone seems unlikely, because interactions with the other species (H. icterina) constrain its range expansion. Thus, whenever biotic interactions limit range expansion, species may become 'trapped' if range loss due to climate change is faster than the movement of the contact zone. An increasing number of moving hybrid zones are being reported, but the proximate causes of movement often remain unclear. In a global context of climate change, we call for more interest in their interactions with climate change.