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Questions: Rhododendron ponticum subsp. baeticum is an invasive shrub of growing concern in continental Europe, but little is known about its impact on native plant communities. Here we ask: do environmental conditions differ between forest stands invaded by it and uninvaded stands? Do these differences correlate with R. ponticum's cover? Are these differences associated with differences in taxonomic and functional diversity of vascular plant species of the herb layer? Can these vegetation changes be explained by the sorting of certain life‐history traits by R. ponticum‐induced environmental changes? Location: Several forests invaded by R. ponticum in the French Atlantic domain. Methods: We recorded vegetation composition and a number of environmental variables in 400‐m2 plots that were established in 64 paired forest stands (32 invaded vs 32 uninvaded). We compiled traits from existing databases. We computed several metrics of taxonomic and functional diversity. We compared environmental variables and diversity metrics between invaded and uninvaded stands. We used correlation and regression analyses to relate them with R. ponticum's cover. We ran RLQ and fourth‐corner analyses to explore the relationships between R. ponticum invasion, environmental variables, species traits, and vegetation composition. Results: Independent of its abundance, R. ponticum invasion was associated with lower light arrival at the forest floor and increased litter thickness. Concomitantly, species richness and diversity and trait diversity were reduced. The major driver of species assemblages was soil pH, which strongly interacted with the invasion gradient. R. ponticum did not sort species according to traits associated with shade tolerance and thick‐litter tolerance. However, tree and shrub saplings were more abundant in invaded than uninvaded stands, at the expense of graminoid and fern species. Conclusions: As R. ponticum becomes the dominant shrub, it exerts new selection forces on life‐history traits of extant species, mostly via reduced light availability, increased litter thickness, and physical competition, thereby reducing taxonomic and functional diversity of the herb layer, without impeding tree and shrub self‐regeneration, at least in the short term. [ABSTRACT FROM AUTHOR]

In Europe, since 1990, a survey on environmental monitoring has been taking place every 5 years, using moss samples to study the distribution of heavy metal concentration and assess contamination sources, resulting on the identification of statistical association of several heavy metal concentrations in mosses. With this work, we propose an extension of an existing spatio-temporal model, introduced in Høst et al. (JASA 90(431):853-861, ), allowing for prediction at unsampled locations of pollution data in the presence of covariates related to each country specificities, when separately modelling the spatial mean field, the spatial variance field and the space-time residual field. Moreover, this model allows to estimate an interpolation error, as an accuracy measure, derived dependently on the case study. For a validation purpose, a simulation study is conducted, showing that the use of the proposed model leads to more accurate prediction values. Results obtained by the proposed methodology for the most recent available survey, are compared with results obtained with no temporal information, namely when Ordinary Kriging, according to the definition in Cressie (Statistics for spatial data, Wiley, New York, ), is used to derive illustrative prediction maps based only on the most recent data. An exercise of cross-validation is performed relative to each of the scenarios considered and the average interpolation errors are presented. While assessing interpolation errors, we conclude that the monitoring specificities of each country and the information of preceding surveys allow for more accurate prediction results. [ABSTRACT FROM AUTHOR]

Whilst biological traits of river macroinvertebrates show unimodal responses to geographic changes in habitat conditions in Europe, we still do not know whether spatial turnover of species result in distinct combinations of biological traits for pond macroinvertebrates. Here, we used data on the occurrence of 204 macroinvertebrate taxa in 120 ponds from four biogeographic regions of Europe, to compare their biological traits. The Mediterranean, Atlantic, Alpine, and Continental regions have specific climate, vegetation and geology. Only two taxa were exclusively found in the Alpine and Continental regions, while 28 and 34 taxa were exclusively recorded in the Atlantic and Mediterranean regions, respectively. Invertebrates in the Mediterranean region allocated much energy to reproduction and resistance forms. Most Mediterranean invertebrate species had narrow thermal ranges. In Continental areas, invertebrates allocated lesser energy to reproduction and dispersal, and organisms were short lived with high diversity of feeding groups. These characteristics suggest higher resilience. The main difference between ponds in the Alpine and Atlantic regions was their elevation. Alpine conditions necessitate specific adaptations related to rapid temperature fluctuations, and low nutrient concentrations. Even if our samples did not cover the full range of pond conditions across Europe, our analyses suggest that changes in community composition have important impacts on pond ecosystem functions. Consistent information on a larger set of ponds across Europe would be much needed, but their low accessibility (unpublished data and/or not disclosed by authors) remains problematic. There is still, therefore, a pressing need for the incorporation of high quality data sets into a standardized database so that they can be further analyzed in an integrated European-wide manner. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Aim We explored the relative contributions of climatic and land-cover factors in explaining the distribution patterns of butterflies in a boreal region. Location Finland, northern Europe. Methods Data from a national butterfly atlas survey carried out during 1991-2003, with a 10-km grain grid system, were used in these analyses. We used generalized additive models (GAM) and hierarchical partitioning (HP) to explore the main environmental correlates (climate and land-cover) of the realized niches of 98 butterfly species. The accuracy of the distribution models (GAMs) was validated by resubstitution and cross-validation approaches, using the area under the curve (AUC) derived from the receiver operating characteristic (ROC) plots. Results Predictive accuracies of the 98 individual environment—butterfly models varied from low to very high (cross-validated AUC values 0.48-0.99), with a mean of 0.79. The results of both the GAM and HP analyses were broadly concordant. Most of the variation in butterfly distributions is associated with growing degree-days, mean temperature of the coldest month and cover of built-up area in all six phylogenetic groups (butterfly families). There were no statistically significant differences in predictive accuracy among the different butterfly families. Main conclusions About three-quarters of the distributions of butterfly species in Finland appear to be governed principally by climatic, predominantly temperature-related, factors. This indicates that many butterfly species may respond rapidly to the projected climate change in boreal regions. By determining the ecological niches of multiple species, we can project their range shifts in response to changes in climate and land-cover, and identify species that are particularly sensitive to forecasted global changes. [ABSTRACT FROM AUTHOR]

Ranunculus communities have been identified by the European Community Directive on Conservation of Natural and Semi-Natural Habitats as a key habitat in need of protection. The ecological requirements and floristic composition of three Ranunculus communities were investigated in North-Eastern France. We also aimed to determine the relationships between environmental parameters, Ranunculus abundance and species richness. R. Fluitans communities clearly differed from the other communities by a higher evenness and species richness and by the occurrence of specific species. In contrast, R. Penicillatus and R. Peltatus communities displayed similar floristic content. Three different sub-associations were however identified within these communities. If alkalinity was determinant in isolating R. Fluitans communities from the other stretches, the ecological ranges of the three communities strongly overlapped while considering parameters linked with other resources or with physical constraints. Further, no significant correlations were highlighted between environmental parameters, Ranunculus abundance and species richness. With respect to conservation, these observations may indicate the particular difficulty in defining each Ranunculus habitat on a European scale, and identify several key points which need to be taken into account when evaluating their status. [ABSTRACT FROM AUTHOR]

1. Multiple biological invertebrate traits (e.g. body size, body form, dispersal potential) each described through multiple categories (e.g. small, intermediate or large body size) could serve as indicators of particular types of human impacts on large rivers. The trait composition of natural invertebrate communities is scarcely constrained by taxonomic differences among them, i.e. individual trait categories could be used to discriminate various types of human impacts across large geographic areas, which would require the definition of trait patterns for conditions of relatively low human impact. 2. Using large databases to link 14 biological traits (described through 66 categories) of invertebrate genera to their occurrence in running water reaches with known environmental conditions, we examined the accuracy of various approaches to predict expected trait variation across least impacted river reaches (LIRRs) of Europe in a stepwise analytical procedure. This procedure included Monte Carlo simulations and ultimately the assignment of test-LIRRs (reaches not used in previous analyses) to the previously defined LIRR conditions. 3. Distance from the source was an integrative variable capturing some (but not all) landscape features (e.g. altitude) or habitat variables (e.g. reach shear stress). Correspondingly, the relative abundance of many trait categories changed along 13 European running waters, although particularly the intensity of these changes differed among these 13 running waters. 4. ‘Downstream models’ (using only distance from the source as predictor) provided the least accurate predictions of expected invertebrate trait patterns when compared with ‘landscape models’ (using distance from the source in combination with altitude and/or latitude) or ‘habitat models’ (using reach shear stress, mean annual air temperature and/or pH of the water). Landscape models provided more accurate predictions than habitat models, but the improvement of predictions of expected invertebrate traits patterns obtained using landscape models was negligible in comparison with a simpler ‘mean-model’ approach, suggesting that defining LIRR conditions through simple descriptions of frequency distributions would be sufficient for the future biomonitoring of large European rivers. 5. To define these LIRR conditions, we used the average of the relative abundance of each trait category from 68 LIRRs (≥40 m wide) as expected LIRR values, and computed LIRR frequency distributions that described the deviations of the 68 individual LIRRs from these expected values. Computing such deviations from the expected LIRR values for 57 test-LIRRs (also ≥40 m wide), 57 trait categories correctly assigned >90% of the test-LIRRs to LIRR conditions if the latter were defined through the entire range of the LIRR frequency distributions. To the 90%-range enveloped by the LIRR frequency distributions, 42 trait categories correctly assigned >80% and 12 categories >90% of the test-LIRRs. 6. Using a framework that required no regionalisation of a large geographic area, no modelling of expected values using environmental information and no standardised invertebrate sampling, the performance of our trait approach to assign test-LIRRs to LIRR conditions encourages future assessments of deviations from these defined LIRR conditions in large European river reaches with different types of human impacts. [ABSTRACT FROM AUTHOR]

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. The study area is Europe. (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. (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. 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. [ABSTRACT FROM AUTHOR]

An original species-selection method for the building of test batteries is presented. This method is based on the statistical analysis of the biological and ecological trait patterns of species. It has been applied to build a macroinvertebrate test battery for the assessment of sediment toxicity, which efficiently describes the diversity of benthic macroinvertebrate biological responses to toxicants in a large European lowland river. First, 109 potential representatives of benthic communities of European lowland rivers were selected from a list of 479 taxa, considering 11 biological traits accounting for the main routes of exposure to a sediment-bound toxicant and eight ecological traits providing an adequate description of habitat characteristics used by the taxa. Second, their biological and ecological trait patterns were compared using coinertia analysis. This comparison allowed the clustering of taxa into groups of organisms that exhibited similar life-history characteristics, physiological and behavioral features, and similar habitat use. Groups exhibited various sizes (7-35 taxa), taxonomic compositions, and biological and ecological features. Main differences among group characteristics concerned morphology, substrate preferendum and habitat utilization, nutritional features, maximal size, and life-history strategy. Third, the best representatives of the mean biological and ecological characteristics of each group were included in the test battery. The final selection was composed of Chironomus riparius (Insecta: Diptera), Branchiura sowerbyi (Oligochaeta: Tubificidae), Lumbriculus variegatus (Oligochaeta: Lumbriculidae), Valvata piscinalis (Gastropoda: Valvatidae), and Sericostoma personatum (Trichoptera: Sericostomatidae). This approach permitted the biological and ecological variety of the battery to be maximized. Because biological and ecological traits of taxa determine species sensitivity, such maximization should permit the battery to better account for the sensitivity range within a community. [ABSTRACT FROM AUTHOR]