The role of land cover in bioclimatic models depends on spatial resolution

Aim We explored the importance of climate and land cover in bird species distribution models on multiple spatial scales. In particular, we tested whether the integration of land cover data improves the performance of pure bioclimatic models. Location Finland, northern Europe. Methods The data of the bird atlas survey carried out in 1986–89 using a 10 × 10 km uniform grid system in Finland were employed in the analyses. Land cover and climatic variables were compiled using the same grid system. The dependent and explanatory variables were resampled to 20‐km, 40‐km and 80‐km resolutions. Generalized additive models (GAM) were constructed for each of the 88 land bird species studied in order to estimate the probability of occurrence as a function of (1) climate and (2) climate and land cover variables. Model accuracy was measured by a cross‐validation approach using the area under the curve (AUC) of a receiver operating characteristic (ROC) plot. Results In general, the accuracies of the 88 bird–climate models were good at all studied resolutions. However, the inclusion of land cover increased the performance of 79 and 78 of the 88 bioclimatic models at 10‐km and 20‐km resolutions, respectively. There was no significant improvement at the 40‐km resolution. In contrast to the finer resolutions, the inclusion of land cover variables decreased the modelling accuracy at 80km resolution. Main conclusions Our results suggest that the determinants of bird species distributions are hierarchically structured: climatic variables are large‐scale determinants, followed by land cover at finer resolutions. The majority of the land bird species in Finland are rather clearly correlated with climate, and bioclimate envelope models can provide useful tools for identifying the relationships between these species and the environment at resolutions ranging from 10 km to 80 km. However, the notable contribution of land cover to the accuracy of bioclimatic models at 10–20‐km resolutions indicates that the integration of climate and land cover information can improve our understanding and model predictions of biogeographical patterns under global change.     

Inclusion of soil data improves the performance of bioclimatic envelope models for insect species distributions in temperate Europe

Aim To analyse the effect of the inclusion of soil and land‐cover data on the performance of bioclimatic envelope models for the regional‐scale prediction of butterfly (Rhopalocera) and grasshopper (Orthoptera) distributions. Location Temperate Europe (Belgium). Methods Distributional data were extracted from butterfly and grasshopper atlases at a resolution of 5 km for the period 1991–2006 in Belgium. For each group separately, the well‐surveyed squares (n = 366 for butterflies and n = 322 for grasshoppers) were identified using an environmental stratification design and were randomly divided into calibration (70%) and evaluation (30%) datasets. Generalized additive models were applied to the calibration dataset to estimate occurrence probabilities for 63 butterfly and 33 grasshopper species, as a function of: (1) climate, (2) climate and land‐cover, (3) climate and soil, and (4) climate, land‐cover and soil variables. Models were evaluated as: (1) the amount of explained deviance in the calibration dataset, (2) Akaike’s information criterion, and (3) the number of omission and commission errors in the evaluation dataset. Results Information on broad land‐cover classes or predominant soil types led to similar improvements in the performance relative to the climate‐only models for both taxonomic groups. In addition, the joint inclusion of land‐cover and soil variables in the models provided predictions that fitted more closely to the species distributions than the predictions obtained from bioclimatic models incorporating only land‐cover or only soil variables. The combined models exhibited higher discrimination ability between the presence and absence of species in the evaluation dataset. Main conclusions These results draw attention to the importance of soil data for species distribution models at regional scales of analysis. The combined inclusion of land‐cover and soil data in the models makes it possible to identify areas with suitable climatic conditions but unsuitable combinations of vegetation and soil types. While contingent on the species, the results indicate the need to consider soil information in regional‐scale species–climate impact models, particularly when predicting future range shifts of species under climate change.     

Quantifying components of risk for European woody species under climate change

Estimates of species extinction risk under climate change are generally based on differences in present and future climatically suitable areas. However, the locations of potentially suitable future environments (affecting establishment success), and the degree of climatic suitability in already occupied and new locations (affecting population viability) may be equally important determinants of risk. A species considered to be at low risk because its future distribution is predicted to be large, may actually be at high risk if these areas are out of reach, given the species' dispersal and migration rates or if all future suitable locations are only marginally suitable and the species is unlikely to build viable populations in competition with other species. Using bioclimatic models of 17 representative European woody species, we expand on current ways of risk assessment and suggest additional measures based on (a) the distance between presently occupied areas and areas predicted to be climatically suitable in the future and (b) the degree of change in climatic suitability in presently occupied and unoccupied locations. Species of boreal and temperate deciduous forests are predicted to face higher risk from loss of climatically suitable area than species from warmer and drier parts of Europe by 2095 using both the moderate B1 and the severe A1FI emission scenario. However, the average distance from currently occupied locations to areas predicted suitable in the future is generally shorter for boreal species than for southern species. Areas currently occupied will become more suitable for boreal and temperate species than for Mediterranean species whereas new suitable areas outside a species' current range are expected to show greater increases in suitability for Mediterranean species than for boreal and temperate species. Such additional risk measures can be easily derived and should give a more comprehensive picture of the risk species are likely to face under climate change.     

Patterns of beta diversity in Europe: the role of climate,land cover and distance across scales

Aim We test the prediction that beta diversity (species turnover) and the decay of community similarity with distance depend on spatial resolution (grain). We also study whether patterns of beta diversity are related to variability in climate, land cover or geographic distance and how the independent effects of these variables depend on the spatial grain of the data. Location Europe, Great Britain, Finland and Catalonia. Methods We used data on European birds, plants, butterflies, amphibians and reptiles, and data on British plants, Catalonian birds and Finnish butterflies. We fitted two or three nested grids of varying resolutions to each of these datasets. For each grid we calculated differences in climate, differences in land‐cover composition (CORINE) and beta diversity (β_sim, β_Jaccard) between all pairs of grid cells. In a separate analysis we looked specifically at pairs of adjacent grid cells (the first distance class). We then used variation partitioning to identify the magnitude of independent statistical associations (i.e. independent effects in the statistical sense) of climate, land cover and geographic distance with spatial patterns of beta diversity. Results Beta diversity between grid cells at any given distance decreased with increasing grain. Geographic distance was always the most important predictor of beta diversity for all pairwise comparisons at the extent of Europe. Climate and land cover had weaker but distinct and grain‐dependent effects. Climate was more important at relatively coarse grains, whereas land‐cover effects were stronger at finer grains. In the country‐wide analyses, climate and land cover were more important than geographic distance. Climatic and land‐cover models performed poorly and showed no systematic grain dependence for beta diversity between adjacent grid cells. Main conclusions We found that relationships between geographic distance and beta diversity, as well as the environmental correlates of beta diversity, are systematically grain dependent. The strong independent effect of distance indicates that, contrary to the current belief, a substantial fraction of species are missing from areas with a suitable environment. Moreover, the effects of geographic distance (at continental extents) and land cover (at fine grains) indicate that any species distribution modelling should take both environment and dispersal limitation into account.     

Disregarding topographical heterogeneity biases species turnover assessments based on bioclimatic models

We investigated whether the inclusion of topographical heterogeneity in bioclimatic envelope models would significantly alter predictions of climate change – induced broad-scale butterfly species range size changes in Europe. Using generalized additive models, and data on current climate and species distributions and two different climate scenarios (HadCM3A2 and HadCM3B2) for the period 2051–2080, we developed predictions of the currently suitable area and potential range size changes of 100 European butterfly species. The inclusion of elevation range increased the predictive accuracy of climate-only models for 86 of the 100 species. The differences in projected future distributions were most notable in mountainous areas, where the climate–topography models projected only ca. half of the species losses than the climate-only models. By contrast, climate–topography models estimated double the losses of species than climate-only models in the flatlands regions. Our findings suggest that disregarding topographical heterogeneity may cause a significant source of error in broad-scale bioclimatic modelling. Mountainous regions are likely to be even more important for future conservation of species than had until now been predicted, based on bioclimatic envelope models that did not take an explicit account of elevational range of grid squares.     

A phyloclimatic study of Cyclamen

Background

The impact of global climate change on plant distribution, speciation and extinction is of current concern. Examining species climatic preferences via bioclimatic niche modelling is a key tool to study this impact. There is an established link between bioclimatic niche models and phylogenetic diversification. A next step is to examine future distribution predictions from a phylogenetic perspective. We present such a study using Cyclamen (Myrsinaceae), a group which demonstrates morphological and phenological adaptations to its seasonal Mediterranean-type climate. How will the predicted climate change affect future distribution of this popular genus of garden plants?

Results

We demonstrate phylogenetic structure for some climatic characteristics, and show that most Cyclamen have distinct climatic niches, with the exception of several wide-ranging, geographically expansive, species. We reconstruct climate preferences for hypothetical ancestral Cyclamen. The ancestral Cyclamen lineage has a preference for the seasonal Mediterranean climate characteristic of dry summers and wet winters. Future bioclimatic niches, based on BIOCLIM and Maxent models, are examined with reference to a future climate scenario for the 2050s. Over the next 50 years we predict a northward shift in the area of climatic suitability, with many areas of current distribution becoming climatically unsuitable. The area of climatic suitability for every Cyclamen species is predicted to decrease. For many species, there may be no areas with a suitable climate regardless of dispersal ability, these species are considered to be at high risk of extinction. This risk is examined from a phylogenetic perspective.

Conclusion

Examining bioclimatic niches from a phylogenetic perspective permits novel interpretations of these models. In particular, reconstruction of ancestral niches can provide testable hypothesis about the historical development of lineages. In the future we can expect a northwards shift in climatic suitability for the genus Cyclamen. If this proves to be the case then dispersal is the best chance of survival, which seems highly unlikely for ant-dispersed Cyclamen. Human-assisted establishment of Cyclamen species well outside their native ranges offers hope and could provide the only means of dispersal to potentially suitable future environments. Even without human intervention the phylogenetic perspective demonstrates that major lineages could survive climate change even if many species are lost.     

Do we need land‐cover data to model species distributions in Europe?

Aim To assess the influence of land cover and climate on species distributions across Europe. To quantify the importance of land cover to describe and predict species distributions after using climate as the main driver. Location The study area is Europe. Methods (1) A multivariate analysis was applied to describe land‐cover distribution across Europe and assess if the land cover is determined by climate at large spatial scales. (2) To evaluate the importance of land cover to predict species distributions, we implemented a spatially explicit iterative procedure to predict species distributions of plants (2603 species), mammals (186 species), breeding birds (440 species), amphibian and reptiles (143 species). First, we ran bioclimatic models using stepwise generalized additive models using bioclimatic variables. Secondly, we carried out a regression of land cover (LC) variables against residuals from the bioclimatic models to select the most relevant LC variables. Finally, we produced mixed models including climatic variables and those LC variables selected as decreasing the residual of bioclimatic models. Then we compared the explanatory and predictive power of the pure bioclimatic against the mixed model. Results (1) At the European coarse resolution, land cover is mainly driven by climate. Two bioclimatic axes representing a gradient of temperature and a gradient of precipitation explained most variation of land‐cover distribution. (2) The inclusion of land cover improved significantly the explanatory power of bioclimatic models and the most relevant variables across groups were those not explained or poorly explained by climate. However, the predictive power of bioclimatic model was not improved by the inclusion of LC variables in the iterative model selection process. Main conclusion Climate is the major driver of both species and land‐cover distributions over Europe. Yet, LC variables that are not explained or weakly associated with climate (inland water, sea or arable land) are interesting to describe particular mammal, bird and tree distributions. However, the addition of LC variables to pure bioclimatic models does not improve their predictive accuracy.     

Land-cover data improve bioclimatic models for anurans and turtles at a regional scale

Aim We investigated whether accounting for land cover could improve bioclimatic models for eight species of anurans and three species of turtles at a regional scale. We then tested whether accounting for spatial autocorrelation could significantly improve bioclimatic models after statistically controlling for the effects of land cover. Location Nova Scotia, eastern Canada. Methods Species distribution data were taken from a recent (1999–2003) herpetofaunal atlas. Generalized linear models were used to relate the presence or absence of each species to climate and land‐cover variables at a 10‐km resolution. We then accounted for spatial autocorrelation using an autocovariate or third‐order trend surface of the geographical coordinates of each grid square. Finally, variance partitioning was used to explore the independent and joint contributions of climate, land cover and spatial autocorrelation. Results The inclusion of land cover significantly increased the explanatory power of bioclimatic models for 10 of the 11 species. Furthermore, including land cover significantly increased predictive performance for eight of the 11 species. Accounting for spatial autocorrelation improved model fit for rare species but generally did not improve prediction success. Variance partitioning demonstrated that this lack of improvement was a result of the high correlation between climate and trend‐surface variables. Main conclusions The results of this study suggest that accounting for the effects of land cover can significantly improve the explanatory and predictive power of bioclimatic models for anurans and turtles at a regional scale. We argue that the integration of climate and land‐cover data is likely to produce more accurate spatial predictions of contemporary herpetofaunal diversity. However, the use of land‐cover simulations in climate‐induced range‐shift projections introduces additional uncertainty into the predictions of bioclimatic models. Further research is therefore needed to determine whether accounting for the effects of land cover in range‐shift projections is merited.     

Potential impacts of climate change on the distributions and diversity patterns of European mammals

The Intergovernmental Panel on Climate Change (IPCC) predicts an increase in global temperatures of between 1.4°C and 5.8°C during the 21st century, as a result of elevated CO₂ levels. Using bioclimatic envelope models, we evaluate the potential impact of climate change on the distributions and species richness of 120 native terrestrial non-volant European mammals under two of IPCC’s future climatic scenarios. Assuming unlimited and no migration, respectively, our model predicts that 1% or 5–9% of European mammals risk extinction, while 32–46% or 70–78% may be severely threatened (lose > 30% of their current distribution) under the two scenarios. Under the no migration assumption endemic species were predicted to be strongly negatively affected by future climatic changes, while widely distributed species would be more mildly affected. Finally, potential mammalian species richness is predicted to become dramatically reduced in the Mediterranean region but increase towards the northeast and for higher elevations. Bioclimatic envelope models do not account for non-climatic factors such as land-use, biotic interactions, human interference, dispersal or history, and our results should therefore be seen as first approximations of the potential magnitude of future climatic changes.     

Inclusion of local environmental conditions alters high-latitude vegetation change predictions based on bioclimatic models

Current predictions of how species will respond to climate change are typically based on coarse-grained climate surfaces utilizing bioclimate envelope modelling. However, the suitability of environmental conditions for a given species might result from a variety of factors including some unrelated to climate. To address this issue, we investigated whether the inclusion of topographical and soil information in bioclimatic envelope models would significantly alter predictions of climate change—induced fine-scale tree and shrub species range size changes at the tree-limit in subarctic Europe. Using generalized additive models and data on current climate and species distributions and three different climate scenarios for the period 2040–2069, we developed predictions of the currently suitable area and potential range size changes of seven tree and shrub species in an area of 1,100 km² at a resolution of 1-ha. The inclusion of topography and soil information increased the predictive accuracy of climate-only models for all studied species. The predicted changes in species distribution volumes were contradictory, and the predicted occurrences varied greatly depending on the model used. Our results therefore support the arguments that vegetation responses to climate change can be influenced by local environmental conditions and that attention should be paid to the combined effects of these factors. We conclude that disregarding local topography and soil conditions in bioclimatic models may result in biased projections of range expansions and the associated colonization, extinction and turnover assessments.     

Ancient woodland indicators signal the climate change risk for dispersal-limited species

The climate change risk to biodiversity operates alongside a range of anthropogenic pressures. These include habitat loss and fragmentation, which may prevent species from migrating between isolated habitat patches in order to track their suitable climate space. Predictive modelling has advanced in scope and complexity to integrate: (i) projected shifts in climate suitability, with (ii) spatial patterns of landscape habitat quality and rates of dispersal. This improved ecological realism is suited to data-rich model species, though its broader generalisation comes with accumulated uncertainties, e.g. incomplete knowledge of species response to variable habitat quality, parameterisation of dispersal kernels etc. This study adopts ancient woodland indicator species (lichen epiphytes) as a guild that couples relative simplicity with biological rigour. Subjectively-assigned indicator species were statistically tested against a binary habitat map of woodlands of known continuity (>250 yr), and bioclimatic models were used to demonstrate trends in their increased/decreased environmental suitability under conditions of ‘no dispersal’. Given the expectation of rapid climate change on ecological time-scales, no dispersal for ancient woodland indicators becomes a plausible assumption. The risk to ancient woodland indicators is spatially structured (greater in a relative continental compared to an oceanic climatic zone), though regional differences are weakened by significant variation (within regions) in woodland extent. As a corollary, ancient woodland indicators that are sensitive to projected climate change scenarios may be excellent targets for monitoring climate change impacts for biodiversity at a site-scale, including the outcome of strategic habitat management (climate change adaptation) designed to offset risk for dispersal-limited species.     

Combining climatic projections and dispersal ability: a method for estimating the responses of sandfly vector species to climate change

BACKGROUND: In the Old World, sandfly species of the genus Phlebotomus are known vectors of Leishmania, Bartonella and several viruses. Recent sandfly catches and autochthonous cases of leishmaniasis hint on spreading tendencies of the vectors towards Central Europe. However, studies addressing potential future distribution of sandflies in the light of a changing European climate are missing. METHODOLOGY: Here, we modelled bioclimatic envelopes using MaxEnt for five species with proven or assumed vector competence for Leishmania infantum, which are either predominantly located in (south-) western (Phlebotomus ariasi, P. mascittii and P. perniciosus) or south-eastern Europe (P. neglectus and P. perfiliewi). The determined bioclimatic envelopes were transferred to two climate change scenarios (A1B and B1) for Central Europe (Austria, Germany and Switzerland) using data of the regional climate model COSMO-CLM. We detected the most likely way of natural dispersal ("least-cost path") for each species and hence determined the accessibility of potential future climatically suitable habitats by integrating landscape features, projected changes in climatic suitability and wind speed. RESULTS AND RELEVANCE: Results indicate that the Central European climate will become increasingly suitable especially for those vector species with a current south-western focus of distribution. In general, the highest suitability of Central Europe is projected for all species in the second half of the 21st century, except for P. perfiliewi. Nevertheless, we show that sandflies will hardly be able to occupy their climatically suitable habitats entirely, due to their limited natural dispersal ability. A northward spread of species with south-eastern focus of distribution may be constrained but not completely avoided by the Alps. Our results can be used to install specific monitoring systems to the projected risk zones of potential sandfly establishment. This is urgently needed for adaptation and coping strategies against the emerging spread of sandfly-borne diseases.     

Threat spots and environmental determinants of red-listed plant,butterfly and bird species in boreal agricultural environments

The aims of this study were (1) to examine the geographic distribution of red-listed species of agricultural environments and identify their national threat spots (areas with high diversity of threatened species) in Finland and (2) to determine the main environmental variables related to the richness and occurrence patterns of red-listed species. Atlas data of 21 plant, 17 butterfly and 11 bird species recorded using 10 km grid squares were employed in the study. Generalized additive models (GAMs) were constructed separately for species richness and occurrence of individual species of the three species groups using climate and land cover predictor variables. The predictive accuracy of models, as measured using correlation between the observed and predicted values and AUC statistics, was generally good. Temperature-related variables were the most important determinants of species richness and occurrence of all three taxa. In addition, land cover variables had a strong effect on the distribution of species. Plants and butterflies were positively related to the cover of grasslands and birds to small-scale agricultural mosaic as well as to arable land. Spatial coincidence of threat spots of plants, butterflies and birds was limited, which emphasizes the importance of considering the potentially contrasting environmental requirements of different taxa in conservation planning. Further, it is obvious that the maintenance of various non-crop habitats and heterogeneous agricultural landscapes has an essential role in the preservation of red-listed species of boreal rural environments.     

The Definition of British Water Beetle Species Pools (Coleoptera) and their Relationship to Altitude, Temperature, Precipitation and Land Cover Variables

Pooled water beetle species lists from 1826 British national grid 10-km squares were analysed using multivariate ordination and classification methods. The relationships of pool groups to the climate, altitude and land cover variables were assessed using constrained and partial ordinations. Ordination of the species pool data indicated a major trend between squares in the north-west of Scotland and those in southern England, illustrating differences in acid and basic water standing water. Secondary variation was from acid standing water to fast-flowing streams and rivers. Classification generated nine species pool groups. These showed a distinct north-west to south-east trend but there was no obvious coastal or brackish water effect on distribution. The climatic and land cover variables were all significantly related to each other, and to north-south variation in grid square location, but the constrained ordination results indicated that that the most important influence on water beetle species pool distribution was mean summer temperature. Although the amount of variation explained by the environmental variables was low, spatial variation in the environmental predictors was almost as important as the environmental variables themselves in determining species pool composition. Mean annual temperature was also strongly correlated with species pool distribution with two land cover variables slightly less important. Altitude and precipitation had the least influence. The water beetle national recording scheme database appears to be of sufficiently high quality for environmental investigations at the British scale. There is considerable potential for the synthesis of invertebrate species distribution, land cover and climate change predictions in the assessment of environmental change. The results, together with previous work on other invertebrate species, indicate that changing summer temperatures may have a considerable influence on the distribution British invertebrate species.     

Predicting range expansion of the map butterfly in Northern Europe using bioclimatic models

The two main goals of this study are: (i) to examine the range shifts of a currently northwards expanding species, the map butterfly (Araschnia levana), in relation to annual variation in weather, and (ii) to test the capability of a bioclimatic envelope model, based on broad-scale European distribution data, to predict recent distributional changes (2000–2004) of the species in Finland. A significant relationship between annual maximum dispersal distance of the species and late summer temperature was detected. This suggests that the map butterfly has dispersed more actively in warmer rather than cooler summers, the most notable dispersal events being promoted by periods of exceptionally warm weather and southerly winds. The accuracy of the broad-scale bioclimatic model built for the species with European data using Generalized Additive Models (GAM) was good based on split-sample evaluation for a single period. However, the model’s performance was poor when applied to predict range shifts in Finland. Among the many potential explanations for the poor success of the transferred bioclimatic model, is the fact that bioclimatic envelope models do not generally account for species dispersal. This and other uncertainties support the view that bioclimatic models should be applied with caution when they are used to project future range shifts of species.     

Impacts of Land Cover Data Selection and Trait Parameterisation on Dynamic Modelling of Species’ Range Expansion

Dynamic models for range expansion provide a promising tool for assessing species’ capacity to respond to climate change by shifting their ranges to new areas. However, these models include a number of uncertainties which may affect how successfully they can be applied to climate change oriented conservation planning. We used RangeShifter, a novel dynamic and individual-based modelling platform, to study two potential sources of such uncertainties: the selection of land cover data and the parameterization of key life-history traits. As an example, we modelled the range expansion dynamics of two butterfly species, one habitat specialist (Maniola jurtina) and one generalist (Issoria lathonia). Our results show that projections of total population size, number of occupied grid cells and the mean maximal latitudinal range shift were all clearly dependent on the choice made between using CORINE land cover data vs. using more detailed grassland data from three alternative national databases. Range expansion was also sensitive to the parameterization of the four considered life-history traits (magnitude and probability of long-distance dispersal events, population growth rate and carrying capacity), with carrying capacity and magnitude of long-distance dispersal showing the strongest effect. Our results highlight the sensitivity of dynamic species population models to the selection of existing land cover data and to uncertainty in the model parameters and indicate that these need to be carefully evaluated before the models are applied to conservation planning.     

Climatic niche of the Saker Falcon Falco cherrug: predicted new areas to direct population surveys in Central Asia

Accurate species distribution data across remote and extensive geographical areas are difficult to obtain. Here, we use bioclimatic envelope models to determine climatic constraints on the distribution of the migratory Saker Falcon Falco cherrug to identify areas in data-deficient regions that may contain unidentified populations. Sakers live at low densities across large ranges in remote regions, making distribution status difficult to assess. Using presence-background data and eight bioclimatic variables within a species distribution modelling framework, we applied MaxEnt to construct models for both breeding and wintering ranges. Occurrence data were spatially filtered and climatic variables tested for multicollinearity before selecting best fit models using the Akaike information criterion by tuning MaxEnt parameters. Model predictive performance tested using the continuous Boyce index (B) was high for both breeding (B_TEST = 0.921) and wintering models (B_TEST = 0.735), with low omission rates and minimal overfitting. The Saker climatic niche was defined by precipitation in the warmest quarter in the breeding range model, and mean temperature in the wettest quarter in the wintering range model. Our models accurately predicted areas of highest climate suitability and defined the climatic constraints on a wide-ranging rare species, suggesting that climate is a key determinant of Saker distribution across macro-scales. We recommend targeted population surveys for the Saker based on model predictions to areas of highest climatic suitability in key regions with distribution knowledge gaps, in particular the Qinghai-Tibet plateau in western China. Further applications of our models could identify protected areas and reintroduction sites, inform development conflicts, and assess the impact of climate change on distributions.     

An unexpected new record of the Mediterranean orchid, <Emphasis Type="Italic">Ophrys bertolonii</Emphasis> (Orchidaceae) in Central Europe

One flowering specimen of Ophrys bertolonii (s. str.) — a plant with a Circum-Adriatic distribution and hitherto unknown in other regions — was found on 7^th May 2010 in the vicinity of Kunadacs (Central Hungary; N 47°00′ E 19°17′). The nearest known populations of this Mediterranean plant inhabit the Adriatic coast (ca. 450 km away) in Croatia, therefore this new occurrence represents a significant long distance dispersal event. The circumstances of the occurrence argue against introduction, but we can not decide now whether this new appearance is temporary or permanent. The permanent establishment of this strictly entomophilous plant requires the presence of its specific pollinator in the close neighbourhood of the habitat. However, no pollination was observed on the three flowers of the plant until 9^th May, and one day later the stem had disappeared most likely due to grazing. Whatever the long-term fate of the plant is, this discovery represents a significant long distance (jump) dispersal event, and testifies to the dispersal ability of Ophrys species. Additionally, the appearance of a mature Adriatic plant in Central Europe fits well into the currently observed, climate change driven northward expansion of European orchids, therefore this finding most likely reflects a growing Mediterranean-like climatic influence in the region.     

Mountain landscapes offer few opportunities for high‐elevation tree species migration

Climate change is anticipated to alter plant species distributions. Regional context, notably the spatial complexity of climatic gradients, may influence species migration potential. While high‐elevation species may benefit from steep climate gradients in mountain regions, their persistence may be threatened by limited suitable habitat as land area decreases with elevation. To untangle these apparently contradictory predictions for mountainous regions, we evaluated the climatic suitability of four coniferous forest tree species of the western United States based on species distribution modeling (SDM) and examined changes in climatically suitable areas under predicted climate change. We used forest structural information relating to tree species dominance, productivity, and demography from an extensive forest inventory system to assess the strength of inferences made with a SDM approach. We found that tree species dominance, productivity, and recruitment were highest where climatic suitability (i.e., probability of species occurrence under certain climate conditions) was high, supporting the use of predicted climatic suitability in examining species risk to climate change. By predicting changes in climatic suitability over the next century, we found that climatic suitability will likely decline, both in areas currently occupied by each tree species and in nearby unoccupied areas to which species might migrate in the future. These trends were most dramatic for high elevation species. Climatic changes predicted over the next century will dramatically reduce climatically suitable areas for high‐elevation tree species while a lower elevation species, Pinus ponderosa, will be well positioned to shift upslope across the region. Reductions in suitable area for high‐elevation species imply that even unlimited migration would be insufficient to offset predicted habitat loss, underscoring the vulnerability of these high‐elevation species to climatic changes.