Downscaling European species atlas distributions to a finer resolution: implications for conservation planning

Aim One of the limitations to using species’ distribution atlases in conservation planning is their coarse resolution relative to the needs of local planners. In this study, a simple approach to downscale original species atlas distributions to a finer resolution is outlined. If such a procedure yielded accurate downscaled predictions, then it could be an aid to using available distribution atlases in real‐world local conservation decisions. Location Europe. Methods An iterative procedure based on generalized additive modelling is used to downscale original European 50 × 50 km distributions of 2189 plant and terrestrial vertebrate species to c. 10 × 10 km grid resolution. Models are trained on 70% of the original data and evaluated on the remaining 30%, using the receiver operating characteristic (ROC) procedure. Fitted models are then interpolated to a finer resolution. A British dataset comprising distributions of 81 passerine‐bird species in a 10 × 10 km grid is used as a test bed to assess the accuracy of the downscaled predictions. European‐wide, downscaled predictions are further evaluated in terms of their ability to reproduce: (1) spatial patterns of coincidence in species richness scores among different groups; and (2) spatial patterns of coincidence in richness, rarity and complementarity hotspots. Results There was a generally good agreement between downscaled and observed fine‐resolution distributions for passerine species in Britain (median Jaccard similarity = 70%; lower quartile = 36%; upper quartile = 88%). In contrast, the correlation between downscaled and observed passerine species richness was relatively low (rho = 0.31) indicating a pattern of error propagation through the process of overlaying downscaled distributions for many species. It was also found that measures of model accuracy in fitting original data (ROC) were a poor predictor of models’ ability to interpolate distributions at fine resolutions (rho = ?0.10). Although European hotspots were not fully coincident between observed and modelled coarse‐resolution data, or between modelled coarse resolution and modelled downscaled data, there was evidence that downscaled distributions were able to maintain original cross‐taxon coincidence of species‐richness scores, at least for terrestrial vertebrate groups. Downscaled distributions were also able to uncover important environmental gradients otherwise blurred by coarse‐resolution data. Main conclusions Despite uncertainties, downscaling procedures may prove useful to identify reserves that are more meaningfully related to local patterns of environmental variation. Potential errors arising from the presence of false positives may be reduced if downscaled‐distribution records projected to occur outside the range of original coarse‐resolution data are excluded. However, the usefulness of this procedure may be limited to data‐rich regions. If downscaling procedures are applied to data‐poor regions, then there is a need to undertake further research to understand the structure of error in models. In particular, it would be important to investigate which species are poorly modelled, where and why. Without such an assessment it is difficult to support unsupervised use of downscaled data in most real‐world situations.     

Multi-extent analysis of the relationship between pteridophyte species richness and climate

Aim To determine the relationship between the distribution of climate, climatic heterogeneity and pteridophyte species richness gradients in Australia, using an approach that does not assume potential relationships are spatially invariant and allows for scale effects (extent of analysis) to be explicitly examined. Location Australia, extending from 10° S to 43° S and 112° E to 153° E. Method Species richness within 50 × 50 km grid cells was determined using point distribution data. Climatic surfaces representing the distribution and availability of water and energy at 1 km and 5 km cell resolutions were obtained. Climate at the 50 km resolution of analysis was represented by their mean and standard deviation in that area. Relationships were assessed using geographically weighted linear regression at a range of spatial bandwidths to investigate scale effects. Results The parameters and the predictive strength of all models varied across space at all extents of analysis. Overall, climatic variables representing water availability were more highly correlated to pteridophyte richness gradients in Australia than those representing energy. Their variance in cells further increased the strength of the relationships in topographically heterogeneous regions. Relationships with water were strong across all extents of analysis, particularly in the tropical and subtropical parts of the continent. Water availability explained less of the variation in richness at higher latitudes. Main conclusions This study brings into question the ability of aspatial and single‐extent models, searching for a unified explanation of macro‐scaled patterns in gradients of diversity, to adequately represent reality. It showed that, across Australia, there is a positive relationship between pteridophyte species richness and water availability but the strength and nature of the relationship varies spatially with scale in a highly complex manner. The spatial variance, or actual complexity, in these relationships could not have been demonstrated had a traditional aspatial global regression approach been used. Regional scale variation in relationships may be at least as important as more general relationships for a true understanding of the distribution of broad‐scale diversity.     

Modelling the species richness distribution of French dung beetles (Coleoptera, Scarabaeidae) and delimiting the predictive capacity of different groups of explanatory variables

Aim To predict French Scarabaeidae dung beetle species richness distribution, and to determine the possible underlying causal factors. Location The entire French territory has been studied by dividing it into 301 grid cells of 0.72 × 0.36 degrees. Method Species richness distribution was predicted using generalized linear models to relate the number of species with spatial, topographic and climate variables in grid squares previously identified as well sampled (n = 66). The predictive function includes the curvilinear relationship between variables, interaction terms and the significant third‐degree polynomial terms of latitude and longitude. The final model was validated by a jack‐knife procedure. The underlying causal factors were investigated by partial regression analysis, decomposing the variation in species richness among spatial, topographic and climate type variables. Results The final model accounts for 86.2% of total deviance, with a mean jack‐knife predictive error of 17.7%. The species richness map obtained highlights the Mediterranean as the region richest in species, and the less well‐explored south‐western region as also being species‐rich. The largest fraction of variability (38%) in the number of species is accounted for by the combined effect of the three groups of explanatory variables. The spatially structured climate component explains 21% of variation, while the pure climate and pure spatial components explain 14% and 11%, respectively. The effect of topography was negligible. Conclusions Delimiting the adequately inventoried areas and elaborating forecasting models using simple environmental variables can rapidly produce an estimate of the species richness distribution. Scarabaeidae species richness distribution seems to be mainly influenced by temperature. Minimum mean temperature is the most influential variable on a local scale, while maximum and mean temperature are the most important spatially structured variables. We suggest that species richness variation is mainly conditioned by the failure of many species to go beyond determined temperature range limits.     

Biotic interactions improve prediction of boreal bird distributions at macro-scales

Aim The role of biotic interactions in influencing species distributions at macro‐scales remains poorly understood. Here we test whether predictions of distributions for four boreal owl species at two macro‐scales (10 × 10 km and 40 × 40 km grid resolutions) are improved by incorporating interactions with woodpeckers into climate envelope models. Location Finland, northern Europe. Methods Distribution data for four owl and six woodpecker species, along with data for six land cover and three climatic variables, were collated from 2861 10 × 10 km grid cells. Generalized additive models were calibrated using a 50% random sample of the species data from western Finland, and by repeating this procedure 20 times for each of the four owl species. Models were fitted using three sets of explanatory variables: (1) climate only; (2) climate and land cover; and (3) climate, land cover and two woodpecker interaction variables. Models were evaluated using three approaches: (1) examination of explained deviance; (2) four‐fold cross‐validation using the model calibration data; and (3) comparison of predicted and observed values for independent grid cells in eastern Finland. The model accuracy for approaches (2) and (3) was measured using the area under the curve of a receiver operating characteristic plot. Results At 10‐km resolution, inclusion of the distribution of woodpeckers as a predictor variable significantly improved the explanatory power, cross‐validation statistics and the predictive accuracy of the models. Inclusion of land cover led to similar improvements at 10‐km resolution, although these improvements were less apparent at 40‐km resolution for both land cover and biotic interactions. Main conclusions Predictions of species distributions at macro‐scales may be significantly improved by incorporating biotic interactions and land cover variables into models. Our results are important for models used to predict the impacts of climate change, and emphasize the need for comprehensive evaluation of the reliability of species–climate impact models.     

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.     

Species richness patterns of obligate subterranean beetles (Insecta: Coleoptera) in a global biodiversity hotspot – effect of scale and sampling intensity

We studied species richness patterns of obligate subterranean (troglobiotic) beetles in the Dinaric karst of the western Balkans, using five grid sizes with cells of 80 × 80, 40 × 40, 20 × 20, 10 × 10, and 5 × 5 km. The same two hotspots could be recognized at all scales, although details differed. Differences in sampling intensity were not sufficient to explain these patterns. Correlations between number of species and number of sampled localities increased with increasing cell size. Additional species are expected to be found in the region, as indicated by jackknife 1, jackknife 2, Chao2, bootstrap, and incidence‐based coverage (ICE) species richness estimators. All estimates increased with increasing cell size, except Chao2, with the lowest prediction at the intermediate 20 × 20 km cell size. Jackknife 2 and ICE gave highest estimates and jackknife 1 and bootstrap the lowest. Jackknife 1 and bootstrap estimates changed least with cell size, while the number of single cell species increased. In the highly endemic subterranean fauna with many rare species, bootstrap may be most appropriate to consider. Positive autocorrelation of species numbers was highest at 20 × 20 km scale, so we used this cell size for further analyses. At this scale we added 137 localities with less positional accuracy to 1572 previously considered, and increased 254 troglobiotic species considered to 276. Previously discovered hotspots and their positions did not change, except for a new species‐rich cell which appeared in the south‐eastern region. There are two centres of troglobiotic species richness in the Dinaric karst. The one in the north‐west exhibited high species richness of Trechinae (Carabidae), while in the south‐east, the Leptodirinae (Cholevidae) were much more diverse. These centres of species richness should serve as the starting point for establishing a conservation network of important subterranean areas in Dinaric karst.     

The unusual suspect: Land use is a key predictor of biodiversity patterns in the Iberian Peninsula

Although land use change is a key driver of biodiversity change, related variables such as habitat area and habitat heterogeneity are seldom considered in modeling approaches at larger extents. To address this knowledge gap we tested the contribution of land use related variables to models describing richness patterns of amphibians, reptiles and passerines in the Iberian Peninsula. We analyzed the relationship between species richness and habitat heterogeneity at two spatial resolutions (i.e., 10 km × 10 km and 50 km × 50 km). Using both ordinary least square and simultaneous autoregressive models, we assessed the relative importance of land use variables, climate variables and topographic variables. We also compare the species–area relationship with a multi-habitat model, the countryside species–area relationship, to assess the role of the area of different types of habitats on species diversity across scales. The association between habitat heterogeneity and species richness varied with the taxa and spatial resolution. A positive relationship was detected for all taxa at a grain size of 10 km × 10 km, but only passerines responded at a grain size of 50 km × 50 km. Species richness patterns were well described by abiotic predictors, but habitat predictors also explained a considerable portion of the variation. Moreover, species richness patterns were better described by a multi-habitat species-area model, incorporating land use variables, than by the classic power model, which only includes area as the single explanatory variable. Our results suggest that the role of land use in shaping species richness patterns goes beyond the local scale and persists at larger spatial scales. These findings call for the need of integrating land use variables in models designed to assess species richness response to large scale environmental changes.     

Association of Ant Predators and Edaphic Conditions with Termite Diversity in an Amazonian Rain Forest

Predation is a key determinant of prey community structure, but few studies have measured the effect of multiple predators on a highly diverse prey community. In this study, we asked whether the abundance, species richness, and species composition of a species‐rich assemblage of termites in an Amazonian rain forest is more strongly associated with the density of predatory ants or with measures of vegetation, and soil texture and chemistry. We sampled termite assemblages with standardized hand‐collecting in 30 transects arranged in a 5 km × 6 km grid in a terra firme Amazonian rain forest. For each transect, we also measured vegetation structure, soil texture, and soil phosphorus, and estimated the density of predatory ants from baits, pitfall traps, and Winkler samples. Seventy‐nine termite species were recorded, and the total density of predatory ants was the strongest single predictor of local termite abundance (r = ?0.66) and termite species richness (r = ?0.44). In contrast, termite abundance and species richness were not strongly correlated with edaphic conditions (¦r¦ < 0.01), or with the density of non‐predatory ants (r_abund = ?0.27; r_s = ?0.06). Termite species composition was correlated with soil phosphorus content (r = 0.79), clay content (r = ?0.75), and tree density (r = ?0.42). Assemblage patterns were consistent with the hypothesis that ants collectively behaved as generalist predators, reducing total termite abundance, and species richness. There was no evidence that ants behaved as keystone predators, or that any single termite species benefited from the reduction in the abundance of potential competitors.     

Geographical gradients of species richness: a test of the water‐energy conjecture of Hawkins et al. (2003) using European data for five taxa

Aims We present an analysis of grid‐based species‐richness data for European plants, mammals, birds, amphibians and reptiles, designed to test the proposition of Hawkins et al. (2003a ) that the single best factor describing richness variation switches from the water regime to the energy regime in the mid‐latitudes and that the ‘breakpoint’ is related to the physiological character of the taxa. We go on to develop subregional models showing the extent to which regional model fits vary as a function of the extent of the study system, and compare the relative performance of ‘water’, ‘energy’ and ‘water–energy’ models of richness for southern, northern and pan‐European models. Location Western Europe. Methods We use atlas data comprising species range data for 187 species of mammals, 445 species of breeding birds, 58 amphibians, 91 reptiles and 2362 plant species, inserted into a c. 50 × 50 km grid cell system. We used 11 modelled climate variables, averaged for the period 1961–90. Statistical analyses were carried out using generalized additive models (GAMs), with splines simplified to a maximum of four degrees of freedom, and we tested for spatial autocorrelation using Moran's I values obtained at 10 different distance intervals. We selected favoured models on the grounds of deviance explained combined with a simple parsimony criterion, such that we selected either: (1) the best two‐variable energy, water or water–energy model, or (2) a four‐variable water–energy model, where the latter improved on the best two‐variable model by a minimum of 5% deviance explained. Results Threshold energy values, at which richness shows a transition from an increasing to a decreasing function of annual solar radiation, were identified for all taxa apart from reptiles. We found conditional support for the switch from dominance of water variables (southern models) to energy variables (northern models). Our favoured models switched between ‘water’ and ‘energy’ for mammals, and between ‘energy’ and ‘water–energy’ for birds, depending on whether we used data of pan‐European extent, southern or northern subsets. Deviance explained in our favoured models varied from 15% (birds, southern Europe) to 72% (amphibians, northern Europe), i.e. ranging from very poor to good fits with the data. Comparison with previous work indicates that our models are generally consistent with (if sometimes weaker than) previous findings. Main conclusions Our models are incomplete representations of factors influencing macro‐scale richness patterns across Europe, taking no explicit account of, for example, topographic variation, human influences or long‐term climatic variation. However, with the exception of birds, for which only the northern model attains over one‐third deviance explained, the models show that climate can account for meaningful proportions of the deviance. We find general support for considering water and energy regimes together in modelling species richness, and for the proposition that water is more limiting in southern Europe and energy in the north. Our analyses demonstrate the sensitivity of model outcomes to the geographical location and extent of the study system, illustrating that simple curve‐fitting exercises like these, particularly if based on regions with the complex history and geography characteristic of Europe, are unlikely to provide the basis for global, predictive models. However, such exercises may be of value in detecting which aspects of water and energy regimes may be of most importance in refining independently generated global models for regional application.     

Distribution patterns of boreal marshland birds: modelling the relationships to land cover and climate

Aim The aims of this work were (1) to study how well land‐cover and climatic data are capable of explaining distribution patterns of ten bird species breeding and/or feeding primarily on marshes and other wetlands and (2) to compare the differences between red‐listed and common marshland species in explanatory variables, and to study the predictability of their distribution patterns. 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 used in the analyses. Land‐cover data based on CORINE (Coordination of Information on the Environment) classification and climatic variables were compiled using the same 10 × 10 km grid. Generalized additive models (GAM) with a stepwise selection procedure were used to select relevant explanatory variables and to examine the complexity of the response shapes of the different species to each variable. The original data set was randomly divided into model training (70%) and model evaluation (30%) sets. The final models of common and red‐listed bird species richness were validated by fitting them to the model evaluation set, and the correlation between observed and predicted species richness was calculated. We assessed the discrimination ability of the binary models (single species) with the area under the curve (AUC) of a receiver operating characteristic (ROC) plot and the Kappa coefficient. Results Cover of marshland, shoreline length and mean temperature in April–June were significantly (P < 0.01) related to the common marshland species richness. Cover and clumping of marshland and mean temperature and precipitation in April–June were selected in the model of red‐listed marshland species richness. The level of discrimination in our single species models varied in ROC from fair to excellent (AUC values 0.70–0.95). Cover of marshland was included in all GAM models built for the target species, but clumping of marshland, shoreline length and cover of mires also appeared as important predictors in single species models. Seven species had statistically significant relationships with climatic variables in the multivariate GAMs. Cover of marshland was highest in squares in which the red‐listed bittern Botaurus stellaris, marsh harrier Circus aeruginosus and great reed warbler Acrocephalus arundinaceus and the water rail Rallus aquaticus were observed. Main conclusions Cover of marshland was the only variable which was included in all the models, reinforcing the close connection between the studied species and marshlands. Broad‐scale clumping of marshlands was important for the red‐listed species, probably due to the much lower population sizes of red‐listed species than those of common species. Land‐cover data produced in CORINE seems to be well suited for modelling the distribution patterns of marshland birds. Although climatic variables also strongly affect the studied marshland birds, habitat availability plays a crucial role in their occurrence. The distribution patterns of marshland birds at the scale of 10 × 10 km reflect the interplay between habitat availability and direct climatic variables.     

Patterns of woody plant species richness in the Iberian Peninsula: environmental range and spatial scale

Aim Climate‐based models often explain most of the variation in species richness along broad‐scale geographical gradients. We aim to: (1) test predictions of woody plant species richness on a regional spatial extent deduced from macro‐scale models based on water–energy dynamics; (2) test if the length of the climate gradients will determine whether the relationship with woody species richness is monotonic or unimodal; and (3) evaluate the explanatory power of a previously proposed ‘water–energy’ model and regional models at two grain sizes. Location The Iberian Peninsula. Methods We estimated woody plant species richness on grid maps with c. 2500 and 22,500 km² cell size, using geocoded data for the individual species. Generalized additive models were used to explore the relationships between richness and climatic, topographical and substrate variables. Ordinary least squares regression was used to compare regional and more general water–energy models in relation to grain size. Variation partitioning by partial regression was applied to find how much of the variation in richness was related to spatial variables, explanatory variables and the overlap between these two. Results Water–energy dynamics generate important underlying gradients that determine the woody species richness even over a short spatial extent. The relationships between richness and the energy variables were linear to curvilinear, whereas those with precipitation were nonlinear and non‐monotonic. Only a small fraction of the spatially structured variation in woody species richness cannot be accounted for by the fitted variables related to climate, substrate and topography. The regional models accounted for higher variation in species richness than the water–energy models, although the water–energy model including topography performed well at the larger grain size. Elevation range was the most important predictor at all scales, probably because it corrects for ‘climatic error’ due to the unrealistic assumption that mean climate values are evenly distributed in the large grid cells. Minimum monthly potential evapotranspiration was the best climatic predictor at the larger grain size, but actual evapotranspiration was best at the smaller grain size. Energy variables were more important than precipitation individually. Precipitation was not a significant variable at the larger grain size when examined on its own, but was highly significant when an interaction term between itself and substrate was included in the model. Main conclusions The significance of range in elevation is probably because it corresponds to several aspects that may influence species diversity, such as climatic variability within grid cells, enhanced surface area, and location for refugia. The relative explanatory power of energy and water variables was high, and was influenced by the length of the climate gradient, substrate and grain size of the analysis. Energy appeared to have more influence than precipitation, but water availability is also determined by energy, substrate and topographic relief.     

Exploring species attributes and site characteristics to assess plant invasions in Spain

Aim Biological invasions are a major component of global change with increasing effects on natural ecosystems and human societies. Here, we aim to assess the relationship between plant invader species attributes and the extent of their distribution range size, at the same time that we assess the association between environmental factors and plant invader species richness. Location Spain, Mediterranean region. Methods From the species perspective, we calculated the distribution range size of the 106 vascular plant invaders listed in a recently published atlas of alien plant species in Spain. Range size was used as an estimation of the degree of invasion success of the species. To model variation in range size between species as a function of a set of species attributes, we adopted the framework of the generalized linear mixed models because they allow the incorporation of taxonomic categories as nested random factors to control for phylogenetic relationships. From the invaded site perspective, we determined invader plant species richness as the number of species for each 10 × 10 km Universal Transverse Mercator (UTM) grid. For each grid cell, we estimated variables concerning landscape, topography, climate and human settlement. Then, we performed a generalized linear mixed model incorporating a defined spatial correlation structure to assess the relationship between plant invader richness and the environmental predictors. Results From the species perspective, wind dispersal and minimum residence time appeared to favour invasion success. From the invaded site perspective, we identified high anthropogenic disturbance, low altitude, short distance to the coastline and dry, hot weather as the main correlates to UTM grid cell invader richness. Main conclusions According to these results, an increasing importance of man‐modified ecosystems and global warming in the Mediterranean region should facilitate the expansion of plant invaders, especially wind‐dispersed species, leading to the accumulation of invasive species in some sites (i.e. invasion hot spots).     

Plant species richness–environment relationships across the Subantarctic–Patagonian transition zone

Aim To evaluate the relative importance of climate, productivity, environmental heterogeneity, biotic associations and habitat use by cattle to account for the species richness of trees, shrubs and herbs across the Subantarctic–Patagonian transition. Location An area of c. 150 × 150 km, within the transition zone between the Subantarctic and Patagonian subregions on the eastern slope of the Andes (c. 39–42° S, 70–72° W). Methods All vascular plants found at each one of 50 (10 × 10 m) sampling plots were counted to estimate the local tree, shrub and herb species richness. Path analysis was used to evaluate the relationship between the richness of the three life‐forms and plant cover, dried litter biomass, mean annual temperature, annual precipitation, daily temperature range, substrate heterogeneity and number of faecal pats. Principal coordinates of neighbour matrices was used to model the spatial autocorrelation of the data. Results Total plant species richness showed a unimodal pattern of spatial variation across the transition. Richness responded positively to indirect effects of precipitation mediated through plant cover, but there was a negative overall effect of precipitation on richness towards the west of the transition, most strongly for trees. An increase in substrate heterogeneity promoted a local increase in herb and shrub richness; the richness of trees increased in sites with steeper slopes. Canopy closure had a direct negative impact on herb richness; it also increased the local accumulation of litter, which negatively affected shrub and herb richness. The impact of habitat use by cattle negatively affected herb richness in areas to the east of the biogeographical transition. Main conclusions We suggest that the importance of indirect climatic effects mediated by vegetation cover can account for species richness patterns across this transition, most strongly for woody species, which supports the productivity hypothesis. The southern temperate forests towards the west may represent a deviation from the predictions of the water–energy dynamics hypothesis. Dissimilar spatial patterns of variation in the richness of woody and herbaceous species, and their different responses to climatic and heterogeneity variables across the transition, suggest that plant life‐form influences the plant species richness–environment relationships.     

Impact of climate change on risk of incursion of Crimean-Congo haemorrhagic fever virus in livestock in Europe through migratory birds

Aims: To predict the risk of incursion of Crimean‐Congo haemorrhagic fever virus (CCHFV) in livestock in Europe introduced through immature Hyalomma marginatum ticks on migratory birds under current conditions and in the decade 2075–2084 under a climate‐change scenario. Methods and Results: A spatial risk map of Europe comprising 14 282 grid cells (25 × 25 km) was constructed using three data sources: (i) ranges and abundances of four species of bird which migrate from sub‐Saharan Africa to Europe each spring, namely Willow warbler (Phylloscopus trochilus), Northern wheatear (Oenanthe oenanthe), Tree pipit (Anthus trivialis) and Common quail (Coturnix coturnix); (ii) UK Met Office HadRM3 spring temperatures for prediction of moulting success of immature H. marginatum ticks and (iii) livestock densities. On average, the number of grid cells in Europe predicted to have at least one CCHFV incursion in livestock in spring was 1·04 per year for the decade 2005–2014 and 1·03 per year for the decade 2075–2084. In general with the assumed climate‐change scenario, the risk increased in northern Europe but decreased in central and southern Europe, although there is considerable local variation in the trends. Conclusions: The absolute risk of incursion of CCHFV in livestock through ticks introduced by four abundant species of migratory bird (totalling 120 million individual birds) is very low. Climate change has opposing effects, increasing the success of the moult of the nymphal ticks into adults but decreasing the projected abundance of birds by 34% in this model. Significance and Impact of the Study: For Europe, climate change is not predicted to increase the overall risk of incursion of CCHFV in livestock through infected ticks introduced by these four migratory bird species.     

A model for range expansion of an introduced species: the common waxbill Estrilda astrild in Portugal

Abstract. The common waxbill Estrilda astrild was first introduced to Portugal from Africa in 1964, and has spread across much of the country and into Spain. We modelled the expansion of the common waxbill on a 20 × 20 km UTM grid in 4‐year periods from 1964 to 1999. The time variation of the square root of the occupied area shows that this expansion process is stabilizing in Portugal, and reasons for this are discussed. Several methods used to model biological expansions are not appropriate for the present case, because little quantitative data are available on the species ecology and because this expansion has been spatially heterogeneous. Instead, colonization on a grid was modelled as a function of several biophysical and spatio‐temporal variables through the fitting of a multivariate autologistic equation. This approach allows examination of the underlying factors affecting the colonization process. In the case of the common waxbill it was associated positively with its occurrence in adjacent cells, and affected negatively by altitude and higher levels of solar radiation.     

Predicted range expansion of the invasive fire ant, Solenopsis invicta, in the eastern United States based on the VEMAP global warming scenario

The red imported fire ant, Solenopsis invicta Buren, is an invasive pest from South America that currently occupies much of the south‐eastern USA. Global warming is likely to allow range expansion of many invasive species, including S. invicta. We used a dynamic, ecophysiological model of fire ant colony growth coupled with models simulating climate change to predict the potential range expansion of S. invicta in the eastern USA over the next century. The climate change scenario predicted by the Vegetation–Ecosystem Modelling and Analysis Project (VEMAP) was used in our analyses. Our predictions indicate that the habitable area for S. invicta may increase by c. 5% over the next 40–50 years (a northward expansion of 33 ± 35 km). As the pace of global warming is expected to quicken in the latter half of the century, however, the habitable area for S. invicta in 2100 is predicted to be > 21% greater than it currently is (a northward expansion of 133 ± 68 km). Because the black imported fire ant, S. richteri Forel, occupies higher latitudes than S. invicta, the overall area of the eastern USA infested with invasive Solenopsis species could be greater than that estimated here.     

Species richness of woody plants in the landscapes of Central Spain: the role of management disturbances,environment and non‐stationarity

Questions: How important is management disturbance on gamma species richness of woody plants at intermediate landscape scales? How is species richness related to other climatic and biotic factors in the study area? How does the assumption of spatial stationarity affect assessment of relationships among species richness and explanatory variables (e.g. management, biotic and climatic factors) across extensive study areas? Location: Central Spain (regions of Castilla y León, Madrid and Castilla‐La Mancha). Scale: Extent: 150 000 km². Grain: 25 km² (5 × 5‐km cells). Methods: Information from 21 064 plots from the 3SNFI was used to evaluate richness of tree and shrub species at intermediate landscape scales. In addition to variables well known to explain biodiversity, e.g. environmental and biotic factors, effect of management treatments was evaluated by assessing clearcutting, selection cutting, stand improvement treatments and agrosilvopastoral systems (dehesas). Results from GWR techniques were compared with those from OLS regression. Results: Patterns of gamma species richness, although strongly affected by both environmental and biotic variables, were also significantly modified by management factors. Species richness increased with percentage of selection cutting stands and improvement treatments but decreased with percentage of clearcutting stands. Reduced species richness of woody plants was associated with agrosilvopastoral practices. Species richness for trees was closely related to basal area, annual precipitation and topographic complexity; species richness for shrubs was closely related to topographic complexity and agrosilvopastoral systems. Most relationships between species richness and environmental or biotic factors were non‐stationary. Relationships between species richness and management effects tended to be stationary, with a few exceptions. Conclusions: Landscape models of biodiversity in Central Spain were more informative when they accounted for effects of management practices, at least at intermediate scales. In the context of current rural abandonment, silvicultural disturbances of intermediate intensity increased gamma species richness of woody plants. Exclusion of factors such as agrosilvopastoral systems from models could have led to spurious relationships with other spatially co‐varying factors (e.g. summer precipitation). Patterns of spatial variation in relationships, provided by GWR models, allowed formulating hypotheses about potential ecological processes underlying them, beyond generalizations resulting from global (OLS) models.     

What drives elevational patterns of diversity? A test of geometric constraints,climate and species pool effects for pteridophytes on an elevational gradient in Costa Rica

Aim We studied pteridophyte species richness between 100 m and 3400 m along a Neotropical elevational gradient and tested competing hypotheses for patterns of species richness. Location Elevational transects were situated at Volcán Barva in the Braulio Carrillo National Park and La Selva Biological Station (100–2800 m) and Cerro de la Muerte (2700–3400 m), both on the Atlantic slope of Costa Rica, Central America. Method We analysed species richness on 156 plots of 20 × 20 m and measured temperature and humidity at four elevations (40, 650, 1800 and 2800 m). Species richness patterns were regressed against climatic variables (temperature, humidity, precipitation and actual evapotranspiration), regional species pool, area and predicted species number of a geometric null model (the mid‐domain effect, MDE). Results The species richness of the 484 recorded species showed a hump‐shaped pattern with elevation with a richness peak at mid‐elevations (c. 1700 m). The MDE was the single most powerful explanatory variable in linear regression models, but species richness was also associated strongly with climatic variables, especially humidity and temperature. Area and species pool were associated less strongly with observed richness patterns. Main conclusions Geometric models and climatic models exclusive of geometric constraints explained comparable amounts of the elevational variation in species richness. Discrimination between these two factor complexes is not possible based on model fits. While overall fits of geometric models were high, large‐ and small‐ranged species were explained by geometric models to different extents. Species with narrow elevational ranges clustered at both ends of the gradient to a greater extent than predicted by the MDE null models used here. While geometric models explained much of the pattern in species richness, we cannot rule out the role of climatic factors (or vice versa) because the predicted peak in richness from geometric models, the empirical peak in richness and the overlap in favourable environmental conditions all coincide at middle elevations. Mid‐elevations offer highest humidity and moderate temperatures, whereas at high elevations richness is reduced due to low temperatures, and at low elevations by reduced water availability due to high temperatures.     

Latitudinal range shifts in Australian flying‐foxes: A re‐evaluation

Recent range shifts towards higher latitudes have been reported for many animals and plants in the northern hemisphere, and are commonly attributed to changes in climate. Relatively little is known about such changes in the southern hemisphere, although it has been suggested that latitudinal distributions of the fruit‐bats Pteropus alecto and Pteropus poliocephalus changed during the 20th century in response to climate change in eastern Australia. However, historical changes in these species distributions have not been examined systematically. In this study we obtained historical locality records from a wide range of sources (including banding and museum records, government wildlife databases and unpublished records), and filtered them for reliability and spatial accuracy. The latitudinal distribution of each species was compared between eight time‐periods (1843–1920, 1921–1950, five 10‐year intervals between 1950 and 2000, and 2001–2007), using analyses of both the filtered point data (P. alecto 870 records, P. poliocephalus 2506) and presence/absence data within 50 × 50 km grid cells. The results do not support the hypothesis that either species range is shifting in a manner driven by climate change. First, neither the northern or southern range limits of P. poliocephalus (Mackay, Queensland and Melbourne, Victoria respectively) changed over time. Second, P. alecto's range limit extended southward by 1168 km (approximately 10.5 degrees latitude) during the twentieth century (from approximately Rockhampton, Queensland to Sydney, New South Wales). Within this zone of southward expansion (25–29°S), the percentage of total records that were P. alecto increased from 8% prior to 1950 to 49% in the early 2000s, and local count data showed that its abundance increased from several hundred to more than 10 000 individuals at specific roost sites, as range expansion progressed. Pteropus alecto expanded southward at about 100 km/decade, compared with the 10–26 km/decade rate of isotherm change, and analyses of historical weather data show that the species consequently moved into recently‐colder regions than it had previously occupied. Neither climate change nor habitat change could provide simple explanations to explain P. alecto's observed rapid range shift. More generally, climate change should not be uncritically inferred as a primary driver of species range shifts without careful quantitative analyses.     

GIS-based niche models identify environmental correlates sustaining a contact zone between three species of European vipers

The current range of European vipers is mostly parapatric but local‐scale allopatric distribution is common and few cases of sympatry are known. In the High Course of Ebro River, northern Spain, there is a contact zone between Vipera aspis, V. latastei, and V. seoanei. Sympatry was detected between aspis and latastei and also specimens with intermediate morphological traits. Presence‐data at a local scale (1 × 1 km) and ecological niche‐based models manipulated in a GIS were used to (1) identify how environmental factors correlate with the distribution of the three vipers and with the location of the sympatry area, and (2) identify potential areas for viper occurrence and sympatry. Ensemble for casting with 10 Maximum Entropy models identified a mixture of topographical (altitude, slope), climatic (precipitation, evapotranspiration, and minimum and maximum temperature), and habitat factors (land cover) as predictors for viper occurrence. Similar predicted probabilities according to the variation of some environmental factors (indicating probable sympatry) were observed only for aspis‐latastei and aspis‐seoanei. In fact, areas of probable occurrence of vipers were generally allopatric but probable sympatry between vipers was identified for aspis‐latastei in 76 UTM 1 × 1 km squares, for aspis‐seoanei in 23 squares, and latastei‐seoanei in two squares. Environmental factors correlate with the location of this contact zone by shaping the species range: some enhance spatial exclusion and constrain distribution to spatially non‐overlapping ranges, while others allow contact between species. The distribution in the contact zone apparently results from the balance between the pressures exerted by the different environmental factors and in the sympatry area probably by interspecific competition. Further ecological and genetical data are needed to evaluate the dynamics of the probable hybrid zone. GIS and niche‐modelling tools proved to be powerful tools to identify environmental factors sustaining the location of contact zones.