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ABSTRACT Aim To describe and explain geographical patterns of false absence and false presence prediction errors that occur when describing current plant species ranges with species distribution models. Location Europe. Methods We calibrated species distribution models (generalized linear models) using a set of climatic variables and gridded distribution data for 1065 vascular plant species from the Atlas Florae Europaeae. We used randomly selected subsets for each species with a constant prevalence of 0.5, modelled the distribution 1000 times, calculated weighted averages of the model parameters and used these to predict the current distribution in Europe. Using a threshold of 0.5, we derived presence/absence maps. Comparing observed and modelled species distribution, we calculated the false absence rates, i.e. species wrongly modelled as absent, and the false presence rates, i.e. species wrongly modelled as present, on a 50 × 50 km grid. Subsequently, we related both error rates to species range properties, land use and topographic variability within grid cells by means of simultaneous autoregressive models to correct for spatial autocorrelation. Results Grid-cell-specific error rates were not evenly distributed across Europe. The mean false absence rate was 0.16 ± 0.12 (standard deviation) and the mean false presence rate was 0.22 ± 0.13. False absence rates were highest in central Spain, the Alps and parts of south-eastern Europe, while false presence rates were highest in northern Spain, France, Italy and south-eastern Europe. False absence rates were high when range edges of species accumulated within a grid cell and when the intensity of human land use was high. False presence rates were positively associated with relative occurrence area and accumulation of range edges. Main conclusions Predictions for various species are not only accompanied by species-specific but also by grid-cell-specific errors. The latter are associated with characteristics of the grid cells but also with range characteristics of occurring species. Uncertainties of predictive species distribution models are not equally distributed in space, and we would recommend accompanying maps of predicted distributions with a graphical representation of predictive performance. [ABSTRACT FROM AUTHOR]

The application of niche-based modelling techniques to plant species has not been explored for the majority of taxa in Europe, primarily due to the lack of adequate distributional data. However, it is of crucial importance for conservation adaptation decisions to assess and quantify the likely pool of species capable of colonising a particular region under altered future climate conditions. We here present a novel method that combines the species pool concept and information about shifts in analogous multidimensional climate space. This allows us to identify regions in Europe with a current climate which is similar to that projected for future time periods in Germany. We compared the extent and spatial location of climatically analogous European regions for three projected greenhouse gas emission scenarios in Germany for the time period 2071–2080 (+2.4°C, +3.3°C, +4.5°C average increase in mean annual temperature) to those of the recent past in Europe (1961–90). Across all three scenarios, European land areas which are characterised by climatic conditions analogue to those found in Germany decreased from 14% in 1961–1990 to ca. 10% in 2071–2080. All scenarios show disappearing current climate types in Germany, which can mainly be explained with a general northwards shift of climatically analogous regions. We estimated the size of the potential species pool of these analogous regions using floristic inventory data for the Iberian Peninsula as 2,354 plant species. The identified species pool in Germany indicates a change towards warmth and drought adapted southern species. About one-third of the species from the Iberian analogous regions are currently already present in Germany. Depending on the scenario used, 1,372 (+2.4°C average change of mean annual temperature), 1,399 (+3.3°C) and 1,444 (+4.5°C) species currently not found in Germany, occur in Iberian regions which are climatically analogous to German 2071–80 climate types. We believe that our study presents a useful approach to illustrate and quantify the potential size and spatial distribution of a pool of species potentially colonising new areas under changing climatic conditions. [ABSTRACT FROM AUTHOR]

Abstract: Predictive species distribution models are standard tools in ecological research and are used to address a variety of applied and conservation related issues. When making temporal or spatial predictions, uncertainty is inevitable and prediction errors may depend not only on data quality and the modelling algorithm used, but on species characteristics. Here, we applied a standard distribution modelling technique (generalized linear models) using European plant species distribution data and climatic parameters. Predictive performance was calculated using AUC, (Cohen’s) Kappa and true skill statistic (TSS), that were subsequently correlated with biological and life-history traits. After accounting for phylogenetic dependence among species, model performance was poorest for species having a short life span and occurring in human disturbed habitats. Our results clearly indicate that the performance of distribution models can be dependent on functional traits and provide further evidence that a species’ ecology is likely to affect the ability of models to predict its distribution. Biased and less reliable predictions could misguide policy decisions and the management and conservation of our natural heritage. [Copyright &y& Elsevier]