The Afrotropical breeding grounds of the Palearctic-African migratory painted lady butterflies (Vanessa cardui).

Migratory insects are key players in ecosystem functioning and services, but their spatiotemporal distributions are typically poorly known. Ecological niche modeling (ENM) may be used to predict species seasonal distributions, but the resulting hypotheses should eventually be validated by field data. The painted lady butterfly (Vanessa cardui) performs multigenerational migrations between Europe and Africa and has become a model species for insect movement ecology. While the annual migration cycle of this species is well understood for Europe and northernmost Africa, it is still unknown where most individuals spend the winter. Through ENM, we previously predicted suitable breeding grounds in the subhumid regions near the tropics between November and February. In this work, we assess the suitability of these predictions through i) extensive field surveys and ii) two-year monitoring in six countries: a large-scale monitoring scheme to study butterfly migration in Africa. We document new breeding locations, year-round phenological information, and hostplant use. Field observations were nearly always predicted with high probability by the previous ENM, and monitoring demonstrated the influence of the precipitation seasonality regime on migratory phenology. Using the updated dataset, we built a refined ENM for the Palearctic-African range of V. cardui. We confirm the relevance of the Afrotropical region and document the missing natural history pieces of the longest migratory cycle described in butterflies.

Climate change could fuel urinary schistosomiasis transmission in Africa and Europe.

The freshwater snail Bulinus truncatus is an important intermediate host for trematode parasites causing urogenital schistosomiasis, a tropical disease affecting over 150 million people. Despite its medical importance, uncertainty remains about its global distribution and the potential impacts of climate change on its future spread. Here, we investigate the distribution of B. truncatus, combining the outputs of correlative and mechanistic modelling methods to fully capitalize on both experimental and occurrence data of the species and to create a more reliable distribution forecast than ever constructed. We constructed ensemble correlative species distribution models using 273 occurrence points collected from different sources and a combination of climatic and (bio)physical environmental variables. Additionally, a mechanistic thermal suitability model was constructed, parameterized by recent life-history data obtained through extensive lab-based snail-temperature experiments and supplemented with an extensive literature review. Our findings reveal that the current suitable habitat for B. truncatus encompasses the Sahel region, the Middle East, and the Mediterranean segment of Africa, stretching from Southern Europe to Mozambique. Regions identified as suitable by both methods generally coincide with areas exhibiting high urogenital schistosomiasis prevalence. Model projections into the future suggest an overall net increase in suitable area of up to 17%. New suitable habitat is in Southern Europe, the Middle East, and large parts of Central Africa, while suitable habitat will be lost in the Sahel region. The change in snail habitat suitability may substantially increase the risk of urogenital schistosomiasis transmission in parts of Africa and Southern Europe while reducing it in the Sahel region.

Climate correlates of bluetongue incidence in southern Portugal.

Model forecasts of the spatiotemporal occurrence dynamics of diseases are necessary and can help understand and thus manage future disease outbreaks. In our study, we used ecological niche modelling to assess the impact of climate on the vector suitability for bluetongue disease, a disease affecting livestock production with important economic consequences. Specifically, we investigated the relationship between the occurrence of bluetongue outbreaks and the environmental suitability of each of the four vector species studied. We found that the main vector for bluetongue disease, Culicoides imicola, a typically tropical and subtropical species, was a strong predictor for disease outbreak occurrence in a region of southern Portugal from 2004 to 2021. The results highlight the importance of understanding the climatic factors that might influence vector presence to help manage infectious disease impacts. When diseases impact economically relevant species, the impacts go beyond mortality and have important economic consequences.

Microclimate reveals the true thermal niche of forest plant species.

Species distributions are conventionally modelled using coarse-grained macroclimate data measured in open areas, potentially leading to biased predictions since most terrestrial species reside in the shade of trees. For forest plant species across Europe, we compared conventional macroclimate-based species distribution models (SDMs) with models corrected for forest microclimate buffering. We show that microclimate-based SDMs at high spatial resolution outperformed models using macroclimate and microclimate data at coarser resolution. Additionally, macroclimate-based models introduced a systematic bias in modelled species response curves, which could result in erroneous range shift predictions. Critically important for conservation science, these models were unable to identify warm and cold refugia at the range edges of species distributions. Our study emphasizes the crucial role of microclimate data when SDMs are used to gain insights into biodiversity conservation in the face of climate change, particularly given the growing policy and management focus on the conservation of refugia worldwide.

Genomic divergence between two sister Medicago species triggered by the quaternary climatic oscillations on the Qinghai-Tibet plateau and northern China.

Speciation is a central topic in evolutionary biology. However, how genomic divergence originates and accumulates in the face of gene flow during ecological adaptation remains poorly understood. Closely related species that have adapted to distinct environments but inhabit some overlapping ranges provide an ideal system to evaluate this issue. Here, we combine population genomics and species distribution models (SDMs) to examine genomic divergences between two sister plant species, Medicago ruthenica and M. archiducis-nicolai, that occur in northern China and the northeast Qinghai-Tibet Plateau, respectively, with overlapping distributions in the border of the two regions. M. ruthenica and M. archiducis-nicolai are well-delimited based on population genomic data, although hybrids exist in sympatric sampling locations. Coalescent simulations and SDMs suggest that the two species diverged from each other in the Quaternary but have been in continuous contact with gene flow occurring between the two species since then. We also discovered positive selection signatures associated with genes both outside and within genomic islands in both species that are probably involved in adaptations to arid and high-altitude environments. Our findings provide insights into how natural selection and climatic changes in the Quaternary initiated and maintained interspecific divergence of these two sister species.

Climate genomics-Geoscientists, ecologists, and geneticists must reinforce their collaborations to confront climate change.

Geoscientists and ecologists alike must confront the impact of climate change on ecosystems and the services they provide. In the marine realm, major changes are projected in net primary and export production, with significant repercussions on food security, carbon storage, and climate system feedbacks. However, these projections do not include the potential for rapid linear evolution to facilitate adaptation to environmental change. Climate genomics confronts this challenge by assessing the vulnerability of ecosystem services to climate change. Because DNA is the primary biological repository of detectable environmentally selected mutations (showing evidence of change before impacts arise in morphological or metabolic patterns), genomics provides a window into selection in response to climate change, while also recording neutral processes deriving from stochastic mechanisms (Lowe et al., Trends in Ecology & Evolution, 2017; 32:141-152). Due to the revolution afforded by sequencing technology developments, genomics can now meet ecologists and climate scientists in a cross-disciplinary space fertile for collaborations. Collaboration between geoscientists, ecologists, and geneticists must be reinforced in order to combine modeling and genomics approaches at every scale to improve our understanding and the management of ecosystems under climate change. To this end, we present advances in climate genomics from plankton to larger vertebrates, stressing the interactions between modeling and genomics, and identifying future work needed to develop and expand the field of climate genomics.

Climate change affects the distribution of diversity across marine food webs.

Many studies predict shifts in species distributions and community size composition in response to climate change, yet few have demonstrated how these changes will be distributed across marine food webs. We use Bayesian Additive Regression Trees to model how climate change will affect the habitat suitability of marine fish species across a range of body sizes and belonging to different feeding guilds, each with different habitat and feeding requirements in the northeast Atlantic shelf seas. Contrasting effects of climate change are predicted for feeding guilds, with spatially extensive decreases in the species richness of consumers lower in the food web (planktivores) but increases for those higher up (piscivores). Changing spatial patterns in predator-prey mass ratios and fish species size composition are also predicted for feeding guilds and across the fish assemblage. In combination, these changes could influence nutrient uptake and transformation, transfer efficiency and food web stability, and thus profoundly alter ecosystem structure and functioning.

Current and future distribution of a parasite with complex life cycle under global change scenarios: Echinococcus multilocularis in Europe.

Global change is expected to have complex effects on the distribution and transmission patterns of zoonotic parasites. Modelling habitat suitability for parasites with complex life cycles is essential to further our understanding of how disease systems respond to environmental changes, and to make spatial predictions of their future distributions. However, the limited availability of high quality occurrence data with high spatial resolution often constrains these investigations. Using 449 reliable occurrence records for Echinococcus multilocularis from across Europe published over the last 35 years, we modelled habitat suitability for this parasite, the aetiological agent of alveolar echinococcosis, in order to describe its environmental niche, predict its current and future distribution under three global change scenarios, and quantify the probability of occurrence for each European country. Using a machine learning approach, we developed large-scale (25 × 25 km) species distribution models based on seven sets of predictors, each set representing a distinct biological hypothesis supported by current knowledge of the autecology of the parasite. The best-supported hypothesis included climatic, orographic and land-use/land-cover variables such as the temperature of the coldest quarter, forest cover, urban cover and the precipitation seasonality. Future projections suggested the appearance of highly suitable areas for E. multilocularis towards northern latitudes and in the whole Alpine region under all scenarios, while decreases in habitat suitability were predicted for central Europe. Our spatially explicit predictions of habitat suitability shed light on the complex responses of parasites to ongoing global changes.

Applying landscape metrics to species distribution model predictions to characterize internal range structure and associated changes.

Distributional shifts in species ranges provide critical evidence of ecological responses to climate change. Assessments of climate-driven changes typically focus on broad-scale range shifts (e.g. poleward or upward), with ecological consequences at regional and local scales commonly overlooked. While these changes are informative for species presenting continuous geographic ranges, many species have discontinuous distributions-both natural (e.g. mountain or coastal species) or human-induced (e.g. species inhabiting fragmented landscapes)-where within-range changes can be significant. Here, we use an ecosystem engineer species (Sabellaria alveolata) with a naturally fragmented distribution as a case study to assess climate-driven changes in within-range occupancy across its entire global distribution. To this end, we applied landscape ecology metrics to outputs from species distribution modelling (SDM) in a novel unified framework. SDM predicted a 27.5% overall increase in the area of potentially suitable habitat under RCP 4.5 by 2050, which taken in isolation would have led to the classification of the species as a climate change winner. SDM further revealed that the latitudinal range is predicted to shrink because of decreased habitat suitability in the equatorward part of the range, not compensated by a poleward expansion. The use of landscape ecology metrics provided additional insights by identifying regions that are predicted to become increasingly fragmented in the future, potentially increasing extirpation risk by jeopardising metapopulation dynamics. This increased range fragmentation could have dramatic consequences for ecosystem structure and functioning. Importantly, the proposed framework-which brings together SDM and landscape metrics-can be widely used to study currently overlooked climate-driven changes in species internal range structure, without requiring detailed empirical knowledge of the modelled species. This approach represents an important advancement beyond predictive envelope approaches and could reveal itself as paramount for managers whose spatial scale of action usually ranges from local to regional.

Epiphytic CAM bromeliads indicate vulnerability of tropical forest communities to climate change.

BACKGROUND AND SCOPE: Vascular epiphytes have a variety of mechanisms to trap and retain water, including crassulacean acid metabolism (CAM). Niche segregation was investigated for epiphytic bromeliads on the tropical Caribbean island of Trinidad, where habitats range from lowland deciduous forests to high-rainfall montane tropical forests, ~1000 m in elevation. METHODS: Four tank-impounding bromeliad epiphytes in the genus Aechmea (Ae. aquilega, Ae. fendleri, Ae. nudicaulis and Ae. dichlamydea) with CAM were mapped across their distinct geographical and elevational zonations in northern Trinidad and Tobago. Species distribution modelling was used to determine environmental limitations for each species. Anatomical and physiological measurements included leaf succulence traits, gas exchange and CAM activity; hydraulic conductance and vulnerability; stomatal sensitivity and quantum yield responses to nocturnal temperature and long-term water deficits. KEY RESULTS: A total of 2876 field observations identified the transitions between the lowland Ae. aquilega and montane Ae. fendleri, occurring >500 m a.s.l. at the drier western end of the Northern Mountain Range and at progressively lower elevations towards the wetter, eastern region. Anatomical and physiological sensitivities of gas exchange, CAM activity and water use, and responses to elevated nocturnal temperatures and drought, were markedly different for Ae. fendleri compared with Ae. aquilega or the ubiquitous Ae. nudicaulis. CONCLUSIONS: The species distribution model highlighted the susceptibility of Ae. fendleri to a changing climate. For each species, physiological and anatomical traits were tailored to environmental tolerances, consistent with specialist or generalist niche preferences. Using Intergovernmental Panel on Climate Change scenarios, we predict that rapid rainfall and temperature changes will lead to the loss of Ae. fendleri and associated lower (and upper) montane forest communities from Trinidad, seriously impacting both biodiversity and critical ecosystem functions here and in other tropical island habitats. Epiphytic bromeliads act as markers for threatened communities, and their physiological tolerances represent key indicators of climate change impacts.

Macrosystem community change in lake phytoplankton and its implications for diversity and function.

Aim: We use lake phytoplankton community data to quantify the spatio-temporal and scale-dependent impacts of eutrophication, land-use and climate change on species niches and community assembly processes while accounting for species traits and phylogenetic constraints. Location: Finland. Time period: 1977-2017. Major taxa: Phytoplankton. Methods: We use hierarchical modelling of species communities (HMSC) to model metacommunity trajectories at 853 lakes over four decades of environmental change, including a hierarchical spatial structure to account for scale-dependent processes. Using a "region of common profile" approach, we evaluate compositional changes of species communities and trait profiles and investigate their temporal development. Results: We demonstrate the emergence of novel and widespread community composition clusters in previously more compositionally homogeneous communities, with cluster-specific community trait profiles, indicating functional differences. A strong phylogenetic signal of species responses to the environment implies similar responses among closely related taxa. Community cluster-specific species prevalence indicates lower taxonomic dispersion within the current dominant clusters compared with the historically dominant cluster and an overall higher prevalence of smaller species sizes within communities. Our findings denote profound spatio-temporal structuring of species co-occurrence patterns and highlight functional differences of lake phytoplankton communities. Main conclusions: Diverging community trajectories have led to a nationwide reshuffling of lake phytoplankton communities. At regional and national scales, lakes are not single entities but metacommunity hubs in an interconnected waterscape. The assembly mechanisms of phytoplankton communities are strongly structured by spatio-temporal dynamics, which have led to novel community types, but only a minor part of this reshuffling could be linked to temporal environmental change.

An integrated high-resolution mapping shows congruent biodiversity patterns of Fagales and Pinales.

The documentation of biodiversity distribution through species range identification is crucial for macroecology, biogeography, conservation, and restoration. However, for plants, species range maps remain scarce and often inaccurate. We present a novel approach to map species ranges at a global scale, integrating polygon mapping and species distribution modelling (SDM). We develop a polygon mapping algorithm by considering distances and nestedness of occurrences. We further apply an SDM approach considering multiple modelling algorithms, complexity levels, and pseudo-absence selections to map the species at a high spatial resolution and intersect it with the generated polygons. We use this approach to construct range maps for all 1957 species of Fagales and Pinales with data compilated from multiple sources. We construct high-resolution global species richness maps of these important plant clades, and document diversity hotspots for both clades in southern and south-western China, Central America, and Borneo. We validate the approach with two representative genera, Quercus and Pinus, using previously published coarser range maps, and find good agreement. By efficiently producing high-resolution range maps, our mapping approach offers a new tool in the field of macroecology for studying global species distribution patterns and supporting ongoing conservation efforts.

A snapshot of progenitor-derivative speciation in Iberodes (Boraginaceae).

Traditional classification of speciation modes has focused on physical barriers to gene flow. Allopatric speciation with complete reproductive isolation is viewed as the most common mechanism of speciation. Parapatry and sympatry, by contrast, entail speciation in the face of ongoing gene flow, making them more difficult to detect. The genus Iberodes (Boraginaceae, NW Europe) comprises five species with contrasting morphological traits, habitats and species distributions. Based on the predominance of narrow and geographically distant endemic species, we hypothesized that geographical barriers were responsible for most speciation events in Iberodes. We undertook an integrative study including: (i) phylogenomics through restriction-site-associated DNA sequencing (RAD-seq), (ii) genetic structure analyses, (iii) demographic modelling, (iv) morphometrics, and (v) climatic niche modelling and niche overlap analysis. The results revealed a history of recurrent progenitor-derivative speciation manifested by a paraphyletic pattern of nested species differentiation. Budding speciation mediated by ecological differentiation is suggested for the coastal lineage, deriving from the inland widespread Iberodes linifolia during the Late Pliocene. Meanwhile, geographical isolation followed by niche shifts are suggested for the more recent differentiation of the coastland taxa. Our work provides a model for distinguishing speciation via ecological differentiation of peripheral, narrowly endemic I. kuzinskyanae and I. littoralis from a widespread extant ancestor, I. linifolia. Ultimately, our results illustrate a case of Pliocene speciation in the probable absence of geographical barriers and get away from the traditional cladistic perspective of speciation as producing two species from an extinct ancestor, thus reminding us that phylogenetic trees tell only part of the story.

History or demography? Determining the drivers of genetic variation in North American plants.

Understanding the impact of historical and demographic processes on genetic variation is essential for devising conservation strategies and predicting responses to climate change. Recolonization after Pleistocene glaciations is expected to leave distinct genetic signatures, characterised by lower genetic diversity in previously glaciated regions. Populations' positions within species ranges also shape genetic variation, following the central-marginal paradigm dictating that peripheral populations are depauperate, sparse and isolated. However, the general applicability of these patterns and relative importance of historical and demographic factors remains unknown. Here, we analysed the distribution of genetic variation in 91 native species of North American plants by coupling microsatellite data and species distribution modelling. We tested the contributions of historical climatic shifts and the central-marginal hypothesis on genetic diversity and structure on the whole data set and across subsets based on taxonomic groups and growth forms. Decreased diversity was found with increased distance from potential glacial refugia, coinciding with the expected make-up of postglacially colonised localities. At the range periphery, lower genetic diversity, higher inbreeding levels and genetic differentiation were reported, following the assumptions of the central-marginal hypothesis. History and demography were found to have approximately equal importance in shaping genetic variation.

Unexpected post-glacial colonisation route explains the white colour of barn owls (Tyto alba) from the British Isles.

The climate fluctuations of the Quaternary shaped the movement of species in and out of glacial refugia. In Europe, the majority of species followed one of the described traditional postglacial recolonization routes from the southern peninsulas towards the north. Like most organisms, barn owls are assumed to have colonized the British Isles by crossing over Doggerland, a land bridge that connected Britain to northern Europe. However, while they are dark rufous in northern Europe, barn owls in the British Isles are conspicuously white, a contrast that could suggest selective forces are at play on the islands. Yet, our analysis of known candidate genes involved in coloration found no signature of selection. Instead, using whole genome sequences and species distribution modelling, we found that owls colonised the British Isles soon after the last glaciation, directly from a white coloured refugium in the Iberian Peninsula, before colonising northern Europe. They would have followed a hitherto unknown post-glacial colonization route to the Isles over a westwards path of suitable habitat in now submerged land in the Bay of Biscay, thus not crossing Doggerland. As such, they inherited the white colour of their Iberian founders and maintained it through low gene flow with the mainland that prevents the import of rufous alleles. Thus, we contend that neutral processes probably explain this contrasting white colour compared to continental owls. With the barn owl being a top predator, we expect future research will show this unanticipated route was used by other species from its paleo community.

Sampling and modelling rare species: Conceptual guidelines for the neglected majority.

Biodiversity conservation faces a methodological conundrum: Biodiversity measurement often relies on species, most of which are rare at various scales, especially prone to extinction under global change, but also the most challenging to sample and model. Predicting the distribution change of rare species using conventional species distribution models is challenging because rare species are hardly captured by most survey systems. When enough data are available, predictions are usually spatially biased towards locations where the species is most likely to occur, violating the assumptions of many modelling frameworks. Workflows to predict and eventually map rare species distributions imply important trade-offs between data quantity, quality, representativeness and model complexity that need to be considered prior to survey and analysis. Our opinion is that study designs need to carefully integrate the different steps, from species sampling to modelling, in accordance with the different types of rarity and available data in order to improve our capacity for sound assessment and prediction of rare species distribution. In this article, we summarize and comment on how different categories of species rarity lead to different types of occurrence and distribution data depending on choices made during the survey process, namely the spatial distribution of samples (where to sample) and the sampling protocol in each selected location (how to sample). We then clarify which species distribution models are suitable depending on the different types of distribution data (how to model). Among others, for most rarity forms, we highlight the insights from systematic species-targeted sampling coupled with hierarchical models that allow correcting for overdispersion and spatial and sampling sources of bias. Our article provides scientists and practitioners with a much-needed guide through the ever-increasing diversity of methodological developments to improve the prediction of rare species distribution depending on rarity type and available data.

Current breeding distributions and predicted range shifts under climate change in two subspecies of Black-tailed Godwits in Asia.

Habitat loss and shifts associated with climate change threaten global biodiversity, with impacts likely to be most pronounced at high latitudes. With the disappearance of the tundra breeding habitats, migratory shorebirds that breed at these high latitudes are likely to be even more vulnerable to climate change than those in temperate regions. We examined this idea using new distributional information on two subspecies of Black-tailed Godwits Limosa limosa in Asia: the northerly, bog-breeding L. l. bohaii and the more southerly, steppe-breeding L. l. melanuroides. Based on breeding locations of tagged and molecularly assayed birds, we modelled the current breeding distributions of the two subspecies with species distribution models, tested those models for robustness and then used them to predict climatically suitable breeding ranges in 2070 according to bioclimatic variables and different climate change scenarios. Our models were robust and showed that climate change is expected to push bohaii into the northern rim of the Eurasian continent. Melanuroides is also expected to shift northward, stopping in the Yablonovyy and Stanovoy Ranges, and breeding elevation is expected to increase. Climatically suitable breeding habitat ranges would shrink to 16% and 11% of the currently estimated ranges of bohaii and melanuroides, respectively. Overall, this study provides the first predictions for the future distributions of two little-known Black-tailed Godwit subspecies and highlights the importance of factoring in shifts in bird distribution when designing climate-proof conservation strategies.

Hyb-Seq provides new insights into the phylogeny and evolution of the Chrysanthemum zawadskii species complex in China.

A species complex is an assemblage of closely related species with blurred boundaries, and from which species could arise from different speciation processes and/or a speciation continuum. Such a complex can provide an opportunity to investigate evolutionary mechanisms acting on speciation. The Chrysanthemum zawadskii species complex in China, a monophyletic group of Chrysanthemum, consists of seven species with considerable morphological variation, diverse habitats and different distribution patterns. Here, we used Hyb-Seq data to construct a well-resolved phylogeny of the C. zawadskii complex. Then, we performed comparative analyses of variation patterns in morphology, ecology and distribution to investigate the roles of geography and ecology in this complex's diversification. Lastly, we implemented divergence time estimation, species distribution modelling and ancestral area reconstruction to trace the evolutionary history of this complex. We concluded that the C. zawadskii complex originated in the Qinling-Daba mountains during the early Pliocene and then spread west and northward along the mountain ranges to northern China. During this process, geographical and ecological factors imposing different influences resulted in the current diversification and distribution patterns of this species complex, which is composed of both well-diverged species and diverging lineages on the path of speciation.

Selection of predictor variables for species distribution models: a case study with an invasive marine bryozoan.

Species distribution models (SDMs) are important tools for predicting the occurrence and abundance of organisms in space and time, with numerous applications in ecology. However, the accuracy and utility of SDMs can be compromised when predictor variables are selected without careful consideration of their ecophysiological relevance to the focal organism. We conducted an in-depth examination of the variable selection process by evaluating predictors to be used in SDMs for Membranipora membranacea, an ecologically significant marine invasive species with a complex lifecycle, as a case study. Using an information-theoretic and multi-model inference approach based on generalized linear mixed models, we assessed multiple environmental variables (depth, kelp density, kelp substrate, temperature, and wave exposure) as predictors of the abundance of multiple life stages of M. membranacea, investigating species-environment relationships and relative and absolute variable importance. We found that the relative importance of a predictor, the metric calculated to represent a predictor, and whether a predictor was proximal or distal were important considerations in the variable selection process. Data constraints (e.g. sample size, characteristics of available predictor data) may inhibit accurate assessment of predictor variables during variable selection. Importantly, our results suggest that species-environment relationships derived from small-scale studies can inform variable selection for SDMs at larger spatiotemporal scales. We developed a conceptual framework for variable selection for SDMs which can be applied to most contexts of species distribution modelling, but particularly those with several candidate predictors and a large dataset.

Ticks on the move-climate change-induced range shifts of three tick species in Europe: current and future habitat suitability for Ixodes ricinus in comparison with Dermacentor reticulatus and Dermacentor marginatus.

Tick-borne diseases are a major health problem worldwide and could become even more important in Europe in the future. Due to changing climatic conditions, ticks are assumed to be able to expand their ranges in Europe towards higher latitudes and altitudes, which could result in an increased occurrence of tick-borne diseases.There is a great interest to identify potential (new) areas of distribution of vector species in order to assess the future infection risk with vector-borne diseases, improve surveillance, to develop more targeted monitoring program, and, if required, control measures.Based on an ecological niche modelling approach we project the climatic suitability for the three tick species Ixodes ricinus, Dermacentor reticulatus and Dermacentor marginatus under current and future climatic conditions in Europe. These common tick species also feed on humans and livestock and are vector competent for a number of pathogens.For niche modelling, we used a comprehensive occurrence data set based on several databases and publications and six bioclimatic variables in a maximum entropy approach. For projections, we used the most recent IPCC data on current and future climatic conditions including four different scenarios of socio-economic developments.Our models clearly support the assumption that the three tick species will benefit from climate change with projected range expansions towards north-eastern Europe and wide areas in central Europe with projected potential co-occurrence.A higher tick biodiversity and locally higher abundances might increase the risk of tick-borne diseases, although other factors such as pathogen prevalence and host abundances are also important.