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SummaryClimate change presents a particularly complex challenge in the context of flyway scale conservation of migratory bird species as it requires coordinated action by multiple countries along these species’ migratory routes. Coordinating conservation responses requires understanding the vulnerability of species and their habitats to climate change at the flyway scale throughout each species’ annual cycle. To contribute to such understanding, we used species distribution models to assess the exposure to climate change of waterbird species that are the focus of the Agreement on the Conservation of African-Eurasian Migratory Waterbirds (AEWA). We found that the species with the smallest proportion of their current range projected to be climatically suitable by 2050 (those whose distributions respond to changes in water availability but that do not perform synchronised migration) are dispersive species in the Afrotropical biogeographic realm, and migratory species in their breeding season, particularly Arctic breeding waders. These species also have the most limited availability of newly suitable areas. Projections for most other Palearctic migratory waterbird species suggest that losses of suitable areas in their current passage and wintering ranges may be largely offset by new areas becoming climatically suitable. The majority of migratory Palearctic waterbirds in the breeding season and Afrotropical waterbirds are widely dispersed with only a small proportion of their populations currently supported by ‘Critical Sites’ (i.e. sites that are either important for Globally Threatened Species or support 1% of the bioregional population of any waterbird species). This makes it unlikely that climate change adaptation measures focusing only on key sites will be sufficient to counter the predicted range losses. Therefore, climate change adaptation responses should also be implemented at the landscape scale for Afrotropical waterbirds and for breeding populations of Palearctic migrant waterbirds.

Despite their importance for biodiversity and ecosystem services, wetlands are among the most threatened ecosystems globally. The conservation of many migratory waterbirds depends on the conservation of a network of key sites along their flyways. However, the suitability of these sites is changing under climate change, and it is important that management of individual sites in the network adapts to these changes. Using bioclimatic models that also account for changes in inundation, we found that projected climate change will reduce habitat suitability for waterbirds at 57.5% of existing Critical Sites within Africa-Eurasia, varying from 20.1% in Eastern Europe to 87.0% in Africa. African and Middle East sites are particularly threatened, comprising 71 of the 100 most vulnerable sites. By highlighting priority sites for conservation and classifying Critical Sites into Climate Change Adaptation Strategy (CCAS) classes, our results can be used to support the climate change adaptation of both individual sites and the entire site network.

Our aim is to model rare species (with few occurrences) but modelling the distribution of species with few occurrence data and many predictor variables leads to model overfitting. Thus, we use the recently developed ensemble of small models, which showed high predictive accuracy in modelling the distribution of rare species to estimate the current and future distribution of 56 rare (and endangered) saproxylic beetle species. Thus, we stacked predictions from individual species distribution models to derive rare species richness. We used current and five future general circulation models and three representative concentration pathways to test whether the distribution of hotspots for rare species shifts due to climate change under different future scenarios. Moreover, we verified the representativeness of existing protected area systems under future climate conditions in Italy. Specifically, we identified potential hotspots for rare species richness through a cumulative relative frequency distribution function. The current surface covered by hotspots is 50.4% of the study area corresponding to 151,223 km2 (mainly from central to northern Italy). Currently, only 35,124 km2 of rare saproxylic hotspots are covered by protected areas (PAs) and they will decrease by about 2–72% in 2070 depending on the future scenarios considered. Our results confirmed that the shift of the distribution of hotspots for rare species might occur due to climate change under different future scenarios and that the existing PAs system would be inadequate for assuring the conservation of rare saproxylic beetles in Italy under current and future climate conditions.

The area of occupancy (AOO) is one of the main measures used by IUCN to quantify range size for species. AOO represents the area of suitable habitat currently occupied by the taxon and is usually quantified by counting the number of occupied cells in a uniform grid that covers the entire range of a taxon. However, this methodology adds uncertainty by the location of the origin of the grid frame. In this communication paper, we tested the influence of the origin of the grid frame used to quantify AOO and found for Swiss bryophytes that 14 species (out of 1089) fall into a different Red List category when the origin of the grid frame was shifted. With this and theoretical examples we show that AOO quantified by circles around the occurrences (a circular buffer approach) would reduce uncertainty significantly because they are independent of the origin of a grid frame. A circular buffer approach to quantify AOO contribute thus to more robust and accurate Red Lists and its usage is in accordance with the IUCN criteria.

Globally accelerating trends in societal development and human environmental impacts since the mid-twentieth century 1–7 are known as the Great Acceleration and have been discussed as a key indicator of the onset of the Anthropocene epoch 6 . While reports on ecological responses (for example, changes in species range or local extinctions) to the Great Acceleration are multiplying 8, 9 , it is unknown whether such biotic responses are undergoing a similar acceleration over time. This knowledge gap stems from the limited availability of time series data on biodiversity changes across large temporal and geographical extents. Here we use a dataset of repeated plant surveys from 302 mountain summits across Europe, spanning 145 years of observation, to assess the temporal trajectory of mountain biodiversity changes as a globally coherent imprint of the Anthropocene. We find a continent-wide acceleration in the rate of increase in plant species richness, with five times as much species enrichment between 2007 and 2016 as fifty years ago, between 1957 and 1966. This acceleration is strikingly synchronized with accelerated global warming and is not linked to alternative global change drivers. The accelerating increases in species richness on mountain summits across this broad spatial extent demonstrate that acceleration in climate-induced biotic change is occurring even in remote places on Earth, with potentially far-ranging consequences not only for biodiversity, but also for ecosystem functioning and services.

Recent studies show that light detection and ranging (LiDAR) derived habitat variables significantly increase the performance and accuracy of species distribution models (SDMs). In particular, the structure of complex habitats such as forest can be accurately parametrized by an area-wide, LiDAR-based vegetation profile. However, evidence of specific applications of such models in real-world conservation management still remains sparse. Here, we developed a resource selection SDM for hazel grouse (Bonasa bonasia L.) in a Swiss nature park with the aim to map habitat suitability and to inform the park management about habitat improvement measures. We used remote sensing, particularly LiDAR to derive ecologically relevant forest vegetation characteristics at the local scale and used them as predictors in an ensemble SDM approach. The predicted habitat suitability was mainly affected by local, fine grained vegetation structure. Average vegetation height, shrub density and canopy height variation contributed most to the habitat quality for hazel grouse. This clearly shows how LiDAR provides the means to develop ecologically interpretable predictor variables of forest habitat structure and that these predictors can be used to reliably map local-scale habitat quality, indicated by high model performance scores (median AUC of 0.918). This improves spatial conservation planning, and at the same time, provides meaningful information to derive habitat improvement measures that can be implemented in the field by foresters. Hazel grouse occurrence in the park is restricted to a few highly suitable, disjunct habitat patches. Therefore, conservation management should increase the connectivity of suitable habitat with the aim to stimulate an increase and better exchange of individuals in the regional hazel grouse population. Habitat improvements can be achieved by forestry measures that regularly integrate early successional forest stages into production forests. They should contain stands with a shrub density of around 30% as well as heterogeneous stands in terms of vegetation height. ISSN:2056-3485

Aim Information on change in species’ environmental preferences (i.e., niche) is currently not included in IUCN Red List criteria, although such information is key for assessing whether species not only lose geographic range but also lose part of their realized niche. Here, using niche size quantification and niche-based species distribution models (SDMs), we test whether realized niche size and predicted potential range size provide additional information compared with the standard IUCN scores. Location Switzerland, national scale. Methods We simulated randomly, spatially directed, and ecologically directed local extinction events of varying magnitudes (10%, 30%, and 50% of occurrences). For a set of 148 representative vascular plant species, we tested how accurately the geographic versus niche measures pictured these extinction scenarios respectively. Results We found that changes in niche size often corresponded to changes in geographic space. However, there was considerable variation and, for many species, changes in geographic and in niche space delivered complementary information. IUCN criteria based on spatial projections of SDMs did not capture extinction events in most cases and often increased the modelled range size, even when up to 50% of the occurrences were removed by simulated extinction events. Main conclusion Our findings demonstrate that changes in niche size can provide valuable additional information and could be used more systematically to complement changes in range size for Red List assessments. In turn, change in SDM-predicted range size was not a good surrogate for classical extent of occurrence and area of occupancy criteria and should be used with caution. Further research is needed to assess whether and how spatial predictions of SDMs may be used to appropriately complement current IUCN criteria and to test whether our findings apply to other organisms and other spatial extents.

Assessing the degree to which climate explains the spatial distributions of different taxonomic and functional groups is essential for anticipating the effects of climate change on ecosystems. Most effort so far has focused on above‐ground organisms, which offer only a partial view on the response of biodiversity to environmental gradients. Here including both above‐ and below‐ground organisms, we quantified the degree of topoclimatic control on the occurrence patterns of >1,500 taxa and phylotypes along a c. 3,000 m elevation gradient, by fitting species distribution models. Higher model performances for animals and plants than for soil microbes (fungi, bacteria and protists) suggest that the direct influence of topoclimate is stronger on above‐ground species than on below‐ground microorganisms. Accordingly, direct climate change effects are predicted to be stronger for above‐ground than for below‐ground taxa, whereas factors expressing local soil microclimate and geochemistry are likely more important to explain and forecast the occurrence patterns of soil microbiota. Detailed mapping and future scenarios of soil microclimate and microhabitats, together with comparative studies of interacting and ecologically dependent above‐ and below‐ground biota, are thus needed to understand and realistically forecast the future distribution of ecosystems., The degree to which climate controls the distributions of taxa affects future ecosystems. Including both above‐ and below‐ground organisms, we compare topoclimatic control on >1,500 taxa by fitting SDMs. Differences in model performances suggest that the influence of topoclimate is stronger on above‐ground species than on below‐ground microorganisms. Accordingly, direct climate change effects are predicted to be stronger for above‐ground than for below‐ground taxa, whereas factors expressing local soil conditions are likely more important for soil microbiota. Future scenarios of soil microclimate and microhabitats, together with ecologically dependent biota, are thus needed to understand and realistically forecast the future ecosystems.

Europe is currently being re-colonized by large carnivore species such as brown bear (Ursus arctos), Eurasian lynx (Lynx lynx) and grey wolf (Canis lupus). Approximately one-third of Europe currently hosts at least one of these large carnivore species: they show permanent occurrence in some regions and sporadic occurrence without reproduction in others. We investigated potential future range expansions of these three large carnivores using three different analyses. First, we compared niche overlap between the historical, current permanent and current sporadic occurrences using n-dimensional hypervolumes. Second, we identified the environmental variables that best explain differences between current sporadic and permanent occurrences through multi-model inference. Third, we projected permanent occurrences into the future across a range of land-use change scenarios. We also determined future refuges (i.e. sub-optimal habitat in the environmental model, good habitat in the human disturbance model) and ecological traps (i.e. good habitat in the environmental model, sub-optimal habitat in the human disturbance model). In the three large carnivores species, ecological niche overlap was higher between historical and current permanent occurrences than between historical and current sporadic occurrences, and we also found low ecological niche overlap between current permanent and sporadic occurrences. Between 20 and 24% (corresponding to 86,800 to 173,200 km2) of the current sporadic occurrences could result in permanent settlement of large carnivores in the year 2040, while 17-24% (corresponding to 122,200 to 104,100 km2) and 2.7-4.6% (corresponding to 11,800 to 28,400 km2) of the current sporadic occurrences are likely to become refuges and ecological traps, respectively. Factors affecting range expansion are human activities, which were negatively related to permanent occurrences of all three species. In light of our results, human-dominated European landscapes provide ample space for the future recolonization of large carnivores. This article is protected by copyright. All rights reserved.

Epiphytic lichens are an important component of forest biodiversity. Many of them are threatened and conservation planning therefore requires comprehensive information about their distribution over space and time. However, besides topo-climatic predictors, the spatial pattern of epiphytic lichens is also closely related to the tree characteristics on which they grow. In this paper, we tested the hypothesis that habitat specialist lichens restricted to specific habitat types and common species with a wide range of ecological preferences may respond differently to the topo-climatic and forest-structure predictors. We applied the generalized linear model (GLM) and maximum entropy (Maxent) for 20 epiphytic lichen species in Switzerland at different spatial scales (1 km and 100 m). To evaluate the influence of forest structure on the epiphytic lichen distribution, models with three sets of predictors (topo-climatic, forest-structure and combined predictor sets) were fitted for each species. Canopy height of forest stands and forest type were tested as a proxy of forest structure. Our results showed that both the techniques applied predicted well the occurrences of habitat specialists but the models of common lichens were overall less accurate. Forest-structure predictors significantly improved the models of rare and threatened species with specific microhabitat requirements, i.e. mainly forest lichens (Arthonia byssacea, Bactrospora dryina, Calicium viride, Gyalecta truncigena and Vulpicida pinastri), but they did not contribute considerably to the models of common species that grow equally well on the bark of different trees within or outside of forests (e.g. Caloplaca cerina, Phaeophyscia orbicularis, Physcia stellaris and Xanthoria parietina). We recommend using high-resolution forest-structure data for robust and reliable predictions of the distribution patterns of threatened epiphytic lichens, most of which are habitat specialists. The inclusion of these data will allow a hypothesis-driven sampling strategy, and will thus increase the effectiveness of the field sampling needed for searching large regions thoroughly to discover new sites where rare and threatened species occur.

Summary Species distribution models (SDMs) have become a standard tool in ecology and applied conservation biology. Modelling rare and threatened species is particularly important for conservation purposes. However, modelling rare species is difficult because the combination of few occurrences and many predictor variables easily leads to model overfitting. A new strategy using ensembles of small models was recently developed in an attempt to overcome this limitation of rare species modelling and has been tested successfully for only a single species so far. Here, we aim to test the approach more comprehensively on a large number of species including a transferability assessment. For each species, numerous small (here bivariate) models were calibrated, evaluated and averaged to an ensemble weighted by AUC scores. These ‘ensembles of small models’ (ESMs) were compared to standard SDMs using three commonly used modelling techniques (GLM, GBM and Maxent) and their ensemble prediction. We tested 107 rare and under-sampled plant species of conservation concern in Switzerland. We show that ESMs performed significantly better than standard SDMs. The rarer the species, the more pronounced the effects were. ESMs were also superior to standard SDMs and their ensemble when they were evaluated using a transferability assessment. By averaging simple small models to an ensemble, ESMs avoid overfitting without losing explanatory power through reducing the number of predictor variables. They further improve the reliability of species distribution models, especially for rare species, and thus help to overcome limitations of modelling rare species.

1. Ensembles of Small Models (ESM) represent a novel strategy for species distribution modelling with few observations. ESMs are built by calibrating many small models and then averaging them into an ensemble model where the small models are weighted by their cross-validated scores of predictive performance. In a previous paper (Breiner, Guisan, Bergamini, & Nobis, Methods in Ecology and Evolution, 6, 1210-1218, 2015), we reported two major findings. First, ESMs proved largely superior to standard models in terms of model performance and transferability. Second, ESMs including different modelling techniques did not clearly improve model performance compared to single-technique ESMs. However, ESMs often require a large computation effort, which can become problematic when modelling large numbers of species. Given the appealing new perspectives offered by ESMs, it is especially important to investigate if some techniques yield increased performance while saving computation time and thus could be predominantly used for building ESMs. 2. Here, we present results from a reanalysis of a subset of the data used in Breiner etal. (2015). More specifically, we ran ESMs: (1) fitted with 10 modelling techniques separately (in Breiner etal., 2015 we used only three techniques); and (2) using various parameter options for each modelling technique (i.e., model tuning). 3. We show that ESMs vary in model performance and computation time across techniques, and some techniques are advantageous in terms of optimizing model performance and computation time (i.e., GLM, CTA and ANN). Including one of these modelling techniques could thus optimize computation time compared to using more computing-intensive techniques like GBM. Next, we show that parameter tuning can improve performance and transferability of ESMs, but often at the cost of computation time. Parameter tuning could therefore be used when computing resources are not a limiting factor. 4. These findings help improve the applicability and performance of ESMs when applied to large numbers of species.

The aim of the ecospat package is to make available novel tools and methods to support spatial analyses and modeling of species niches and distributions in a coherent workflow. The package is written in the R language (R Development Core Team 2016) and contains several features, unique in their implementation, that are complementary to other existing R packages. Pre-modeling analyses include species niche quantifications and comparisons between distinct ranges or time periods, measures of phylogenetic diversity, and other data exploration functionalities (e.g. extrapolation detection, ExDet). Core modeling brings together the new approach of Ensemble of Small Models (ESM) and various implementations of the spatially-explicit modeling of species assemblages (SESAM) framework. Post-modeling analyses include evaluation of species predictions based on presence-only data (Boyce index) and of community predictions, phylogenetic diversity and environmentally-constrained species co-occurrences analyses. The ecospat package also provides some functions to supplement the biomod2 package (e.g. data preparation, permutation tests and cross-validation of model predictive power). With this novel package, we intend to stimulate the use of comprehensive approaches in spatial modelling of species and community distributions. This article is protected by copyright. All rights reserved.

International audience; Aim In the alpine life zone, plant diversity is strongly determined by local topography and microclimate. We assessed the extent to which aspect and its relatedness to temperature affect plant species diversity, and the colonization and disappearance of species on alpine summits on a pan-European scale. Location Mountain summits in Europe's alpine life zone. Methods Vascular plant species and their percentage cover were recorded in permanent plots in each cardinal direction on 123 summits in 32 regions across Europe. For a subset from 17 regions, resurvey data and 6-year soil temperature series were available. Differences in temperature sum and Shannon index as well as species richness, colonization and disappearance of species among cardinal directions were analysed using linear mixed-effects and generalised mixed-effects models, respectively. Results Temperature sums were higher in east- and south-facing aspects than in the north-facing ones, while the west-facing ones were intermediate; differences were smallest in northern Europe. The patterns of temperature sums among aspects were consistent among years. In temperate regions, thermal differences were reflected by plant diversity, whereas this relationship was weaker or absent on Mediterranean and boreal mountains. Colonization of species was positively related to temperature on Mediterranean and temperate mountains, whereas disappearance of species was not related to temperature. Main conclusions Thermal differences caused by solar radiation determine plant species diversity on temperate mountains. Advantages for plants on eastern slopes may result from the combined effects of a longer diurnal period of radiation due to convection cloud effects in the afternoon and the sheltered position against the prevailing westerly winds. In northern Europe, long summer days and low sun angles can even out differences among aspects. On Mediterranean summits, summer drought may limit species numbers on the warmer slopes. Warmer aspects support a higher number of colonization events. Hence, aspect can be a principal determinant of the pace of climate-induced migration processes.