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The aim of this study is to understand how prevalence—the ratio of instances of presence to total sample size—affects the estimation of three discrimination indexes commonly used in distribution modelling: the area under the receiver operating characteristic curve (AUC), the value of sensitivity at the threshold where sensitivity equals specificity (Se*), and the maximum value of the Youden index or true skill statistic (Y). For four sample size levels, samples of suitability scores for the instances of presence and absence with varying prevalences were simulated from known distributions so that the true values of the discrimination indexes were known, and the three indexes were empirically estimated (AUCest, Se*est, Yest). AUCest and Se*est are unbiased estimators, and the greatest precision is achieved with a balanced prevalence. As sample size increases, there is a larger prevalence interval around 0.5 in which precision is more or less stable. As a rule of thumb, in the case of n ≤ 100, at least ten observations of the rare state (either instances of presence or absence) should be considered, whereas the safety prevalence interval [0.01, 0.99] should be used for higher sample sizes. The lower the true discriminative power of the models, the higher the negative effect of prevalence. Yest is positively biased, and bias and precision become worse towards low and high prevalences. Highly unbalanced prevalences increase the imprecision in estimating the discrimination capacity of the models. Y is not recommended as a discrimination measure since it provides overoptimistic results. [ABSTRACT FROM AUTHOR]

Differences between climatic databases have been reported to alter the spatial predictions of species distribution models (SDM). In the present study, the global WorldClim v.2 database (WC) and the regional Iberian Climate Atlas (ICA) were compared in the geographical context of the Iberian Peninsula. Six climatic variables were considered: BIO1, BIO5 and BIO6 (temperature-related variables) and BIO12, BIO13 and BIO14 (precipitation-related variables). We performed regression analyses between values for each pair of homologous variables and generated quantile–quantile plots to compare the distribution of ranges within 10 × 10 grid cells. Pearson correlations were used to determine whether absolute differences between homologue variables were related to elevation. We modelled the occurrence of 48 woody plant species using either WC or ICA variables, and tested for differences in the estimated suitability values, discrimination power and importance of variables. Precipitation values varied considerably between databases, with WC variables reaching lower maximum and less variable values than ICA. Regarding temperature values, BIO1 had the highest correlation value between both datasets, whereas we observed substantial differences in the case of BIO5, which showed consistently lower values in WC than in ICA. Higher discrepancies between datasets, especially for temperature variables, were found in high elevation areas. As regards distribution models, the climate data source affected estimated suitability values, discrimination capacity and estimated variable importance. In addition, the rarer the species, the higher the uncertainty associated with the climate source. Climate data source is another uncertainty factor to add to all those that have already been highlighted in SDM. [ABSTRACT FROM AUTHOR]

An accurate estimation of the expected consequences of climate change requires the proper quantification of the effect of climate on current species distributions. Several interrelated sources of uncertainty may affect the likelihood of species distribution models (SDMs) to determine the relative importance of climate. Our aim was to assess the relationship between the influence of geographical background (GB) delimitation and that of subtracting the non-climate effects from the weight of climatic predictors to estimate the combined influence of these two factors on predictions in climate change scenarios. The distribution of 40 endemic mammals in Western Europe have been modeled by (i) using the whole territory of Western Europe as the GB and also specifically delimiting the GB with a geographical criterion and (ii) considering climatic predictors in addition to other non-climatic variables in order to extract the pure effect of climate. The models were used to quantify species' sensitivity to new climate scenarios. Results showed discrepancies among the analytical approaches. Changes in distribution obtained by considering the pure effect of climate were lower than those obtained by considering the apparent effect, and GB-delimited models yielded higher changes than those trained in Western Europe. We evidence that climate weighting and GB delimitation have dramatic influences on the projections of models when transferred to new scenarios. We emphasize that scientific studies and derived adaptation policies based on SDMs without an explicit consideration of the GB and the weighting of the climate-related variables may be misleading and in need of revision. [ABSTRACT FROM AUTHOR]

In this study, the invertebrate fauna of a colluvial Mesovoid Shallow Substratum (MSS) is Eastern Spain was characterized, and the importance of the MSS as refuge for endemic and rare species was assessed. Ten pitfall traps were buried up to 1 m deep inside multiperforated PVC tubes across a stone debris. Several environmental variables were measured in each sampling point. The completeness of the inventory was assessed, and different diversity patterns-variation in abundance, species richness and species composition-were analyzed. 4150 individuals and 164 species were captured, most of them arthropods. The number of individuals and species varied considerably among traps. Half of the species were represented by one or two individuals, and neither the species accumulation curves nor the curves for the non-parametric estimators showed any sign of stabilizing. Individuals of abundant species aggregated in one or a few traps. No consistent diversity patterns were found, except that distance among traps partially explained the similarity in species composition when considering only the most abundant species. This is a very rich but uneven assemblage that shows a high degree of species turnover between traps. One-sixth of the species can be classified as either troglobionts or troglophiles, but there is a significant presence of edaphic species. Obtaining complete fauna inventories in the MSS has proven to be a challenging task. The study of the MSS reveals important faunistic information, providing new taxa to science as well as interesting records of poorly known species. [ABSTRACT FROM AUTHOR]

Species distribution modelling has become a common approach in ecology in the last decades. As in any modelling exercise, evaluation of the predicted suitability surfaces is a key process, and the area under the receiver operating characteristic (ROC) curve (AUC) has become the most popular statistic for this purpose. A close covariation between the AUC and threshold-dependent discrimination measures (sensitivity Se and specificity Sp) raises into question the advantage of the threshold-independence of the AUC. In this study, the relationship between the AUC and several threshold-dependent discrimination measures is characterized in detail, and the sensitivity of the pattern to variations in the shape of the ROC curve is assessed. Hypothetical suitability values, coming from normal and skew-normal distributions, were simulated for both instances of presence and absence. The flexibility of the skew-normal distribution allowed for the simulation of a wide range of ROC curve configurations. The relationship between the AUC and threshold-dependent measures was graphically assessed; independently of the ROC curve shape, a nonlinear asymptotic relationship between the AUC and Se (and Sp) was obtained after applying the threshold that makes Se = Sp. A nonlinear asymptotic relationship between the AUC and the Youden index was also reported. These results imply that the AUC does not appropriately measure changes in the discrimination of models, and it is especially incapable of distinguishing between models with high discrimination capacity. Se or Sp derived from the application of the threshold that makes them equal is a preferred measure of discrimination power. Together with the rate of false positives and negatives, and with the prevalence of the species, these statistics provide more information about the discrimination capacity of the models than the AUC. [ABSTRACT FROM AUTHOR]

The degree of completeness of the western Palaearctic inventory of the genus Aphthona and the factors that have determined the process of species description in the region were analysed. The historic species accumulation curve shows no asymptotic trend so no accurate estimations could be made of the number of species to be discovered in the future, but the shape of the curve indicates that a significant proportion of the taxa remains yet-to-be-described and thus further taxonomic effort will be needed. In order to optimise this taxonomic work, several morphologic, trophic and geographic variables of Aphthona species were analysed, in a search for the factors that have influenced the probability of discovery of taxa and thus to estimate the characteristics of the yet-to-be-described species. General Regression Models and variation partitioning were used to assess the influence on the process of species description of body size and colour, trophic range, number of host plants, geographic range size, maximum and minimum latitude and longitude. Morphological variables are not statistically significant in explaining the variation in the year of description, whereas trophic and geographic variables are essential determinants. The pure effects of geographic range size, trophic variables and geographic location of taxa are negligible, but the shared effects between the three groups of variables account for important portions of the variation; the whole model explains 64% of the variance. Widely distributed and trophic generalist species living in northern and western areas of the western Palaearctic region were described first. Extrapolation of the observed pattern should yield an estimate of the probable features and location of the yet-to-be-described species. New Aphthona should be searched for southwards and eastwards, distributed in small areas and living on a single, or very few, host plants. [ABSTRACT FROM AUTHOR]