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Aim: To assess the relative relevance of dispersal limitation and species sorting as drivers of spatial turnover between spider faunas of European territories. Location: Continental Europe. Time period: Present. Major taxa studied: Spiders (Order Araneae). Methods: We analysed how distance‐decay patterns differ between northern and southern Europe (broadly, territories covered vs. not covered by ice sheets during the last glacial maximum, respectively) in 15 spider families, using standardized distances to allow a direct comparison between parameters (i.e. slope and intercept) of climatic and spatial distance‐decay models. Thus, we assessed North–South differences in parameters of spatial and, independently, climatic distance‐decay models, and whether those differences are explained by family‐specific traits related to dispersal ability. Results: Climatic and spatial distance‐decay patterns are very similar in northern Europe, where climatic and spatial distances are highly correlated. In contrast, slopes are steeper in spatial than in climatic distance‐decay curves in southern Europe, where climatic and spatial distances are decoupled. Moreover, family traits related to dispersal ability explained the North–South difference in spatial distance‐decay slopes, as well as the amount of nestedness‐resultant dissimilarity between southern and northern spider faunas. Main conclusions: Our results suggest that differences in beta diversity patterns between northern and southern Europe reflect the strength of dispersal limitation in spiders, which varies across families and leads to different degrees of disequilibrium with current climatic conditions depending on the taxon. Moreover, in the South of Europe, where spatial and climatic distances are uncorrelated, spatial distance‐decay models are steeper and have larger explanatory power than climatic distance‐decay models, which suggests that dispersal limitation is the main factor shaping current beta diversity patterns of European spiders at the continental scale. [ABSTRACT FROM AUTHOR]

Diplura is the sister group to insects and one of the three basal hexapod groups with unique entognathan mouthparts. The order is divided into 10 families, which include 1008 species in 141 genera, with a high proportion of monotypic genera. They are ubiquitous in soils and subsurface terrestrial habitats, as well as have an important role in overall biogeochemical cycles.We present the first comprehensive review of the global biodiversity and ecology of Diplura. We highlight four aspects of this basal hexapod group: diversity in morphological body plans and sizes; ecology in terrestrial environments from soil to caves; food preference and trophic levels, and their biogeographical and paleobiogeographical significance.Diplura depends on high humidity and moderate temperatures. They are presumably very sensitive to anthropogenic pressures and climate change, and therefore are a suitable model for ecophysiological studies and evident priority targets for conservation.We conclude that the future efforts should focus on establishing a molecular phylogeny to clarify the relationships between and within families, as well as to reveal global biogeographical patterns. This will require an increase in sampling effort in several regions of the globe, especially in tropical regions. [ABSTRACT FROM AUTHOR]

Diplurans (Hexapoda) are considered the 'ideal cavernicolous animal' having one of the highest ratios of cave-adapted vs. non-cave-adapted species. They are successful colonizers of subterranean habitats, thriving in all cryptic, dark, terrestrial environments. Diplurans play an important role in the decomposition of organic matter below the ground and are sensitive to anthropogenic pressures. We present the first comprehensive review about cave Diplura diversity, ecology, evolution, distribution and biogeography. We provide a roadmap for research questions regarding the ecology, aimed at stimulating the pursuit of new studies on this fascinating group. Filling these current knowledge gaps will contribute to conservation efforts for cave ecosystems. [ABSTRACT FROM AUTHOR]

Aim: Local suitability estimated with species distribution models (SDMs) could indicate the maximum abundance attainable by species. Often the abundance–suitability relationship is wedge‐shaped because species do not reach their maximum potential in every suitable location. We explore how SDM performance, the amount of information lost when converting continuous abundance into presence–absence data and species prevalence influence the abundance–suitability relationship. Location: Undefined. Time period: Undefined. Major taxa: Virtual species. Methods: Different abundance scenarios were simulated and converted into presence–absence maps. SDMs were parameterized using simulated predictors with different explanatory capacities. Quantile regressions were performed to characterize the abundance–suitability relationship. The strength of the wedge‐shaped pattern was estimated using the difference in slopes between the 90th and 50th quantile lines, the goodness‐of‐fit of the 90th quantile regressions was calculated, and variation of both parameters was analysed as a function of SDM performance, prevalence and maximum abundance. Results: The degree of wedge shape was directly related to maximum abundance. It also depended on SDM quality; the higher the discrimination capacity, the less wedge‐shaped the abundance–suitability relationship and higher the goodness‐of‐fit of the 90th quantile regressions. Prevalence exerted a significant effect on the shape of the relationship by influencing—together with maximum abundance—the extent of information loss. Main conclusions: SDMs cannot predict actual abundance even when the true determinants of abundance are included as predictors. Because presence–absence and abundance data are related but are different variables, wedge‐shaped patterns are unavoidable. Discrimination capacity and prevalence affect the strength of the wedge‐shaped pattern, so understanding their effects is necessary before any biological explanation is provided for the abundance–suitability relationship. Suitability maps derived from SDMs may transmit a false sense of precision at a local scale and should not be used as a perfect surrogate when abundance information is required. [ABSTRACT FROM AUTHOR]

Aim: It is still debated whether allometry, the relationship between body size and body parts, entails merely an evolutionary constraint or can itself evolve. Recently, a hypothesis has been proposed that states that static allometry (allometry measured across individuals at the same developmental stage) can evolve from differences in the developmental pathways between pairs of traits under different nutritional environments. A macroecological prediction stemming from this hypothesis is that allometric coefficients (scaling and allometric factors) should covary with ecosystem productivity. Here, we tested this prediction using a worldwide database of mass–length allometric equations. Location: Worldwide, data distributed across the entire globe. Time period: 1967–2017. Major taxa studied: Soil arthropods. Methods: We fitted general linear models with the allometric coefficients (the scaling a and allometric b factors) as the dependent variables. The target independent variable was the normalized difference vegetation index, as a proxy of ecosystem productivity. Longitude, absolute latitude and altitude, as well as mean annual temperature and mean annual precipitation were included as both covariates and additional variables of interest. We also included body bauplan (obtained from geometric morphometrics), taxonomic affiliation (a proxy of phylogenetic relationships) and the reciprocal allometric coefficient as covariates in the model. Results: We found a strong negative association between both allometric factors and the productivity of the ecosystems, and the effect for the allometric factor b was stronger at lower trophic levels. We also detected strikingly similar effects of geographic and climatic predictors on both allometric factors, suggesting the occurrence of similar selective regimes. Main conclusions: The fact that productivity, geography and climate affect the value of mass–length allometric coefficients has important consequences not only to understand the evolution of allometries, but also for how energy is processed in soil ecosystems across the globe. [ABSTRACT FROM AUTHOR]

The continuing advancement of new technologies is making available novel sources of occurrence data, such as photo‐sharing platforms. Using three Iberian Argiope spider species as models, this study aimed to compare the quality of three data sources – existing scientific literature, a biodiversity‐focused photo‐sharing citizen science project, and a photo‐sharing social network – and the results derived from niche and distribution analyses.Data sources were compared in terms of sample size, spatial clustering, and coverage, degree of climatic niche completeness, and in their consistency in the characterisation of response curves. Possible biases towards big cities and protected natural areas were identified, and species distribution models were parameterised and compared.Photo records provided the largest number of occurrences, whereas data from scientific literature showed the worst spatial coverage. Records from the citizen science project yielded the highest degree of niche completeness. All data sources showed some bias towards big cities and protected areas. Data from existing scientific literature yielded the worst range representations and, accordingly, the most different distribution models, whereas the models based on two photo‐vouchered sources were very similar.Range and niche analyses using records from different sources may yield disparate results. Occurrence data from existing scientific literature may not be enough to develop robust niche analyses nor to characterise recent range changes of poorly studied taxa. Photo‐sharing platforms provide updated chorological information and have the potential to increase sample sizes dramatically, which is an important data property in distribution and niche modelling. [ABSTRACT FROM AUTHOR]

The scarce and biased knowledge about the diversity and distribution of Araneae species in the Iberian Peninsula is accentuated in poorly known habitats such as the Mesovoid Shallow Substratum (MSS). The aim of this study was to characterize the spiders inventory of the colluvial MSS of the Sierra de Guadarrama National Park, and to assess the importance of this habitat for the conservation of the taxon. Thirty-three localities were selected across the high peaks of the Guadarrama mountain range and they were sampled for a year using subterranean traps specially designed to capture arthropods in the MSS. Species accumulation curves were built both for the observed species richness and for the non-parametric richness estimators. The literature was reviewed in order to update the distributional maps of the rarest species. Forty-two species were collected, of which four were species new to science. More than half were represented by one or two individuals which caused the accumulation curves to rise slowly and to end without reaching an asymptote. Almost half of the species showed significant increases in their Iberian distribution ranges. Two species were recorded for the first time in the Iberian Peninsula and 32 species were new additions to the spider checklist of the Sierra de Guadarrama National Park. [ABSTRACT FROM AUTHOR]

The aim of this study was to unravel the relative role played by speleogenesis (i.e., the process in which a cave is formed), landscape-scale variables, and geophysical factors in the determination of species richness in caves. Biological inventories from 21 caves located in the southeastern Iberian Peninsula along with partial least square ( PLS) regression analysis were used to assess the relative importance of the different explanatory variables. The caves were grouped according to the similarity in their species composition; the effect that spatial distance could have on similarity was also studied using correlation between matrices. The energy and speleogenesis of caves accounted for 44.3% of the variation in species richness. The trophic level of each cave was the most significant factor in PLS regression analysis, and epigenic caves (i.e., those formed by the action of percolating water) had significantly more species than hypogenic ones (i.e., those formed by the action of upward flows in confined aquifers). Dissimilarity among the caves was very high (multiple-site βsim = 0.92). Two main groups of caves were revealed through the cluster analysis, one formed by the western caves and the other by the eastern ones. The significant-but low-correlation found between faunistic dissimilarity and geographical distance ( r = .16) disappeared once the caves were split into the two groups. The extreme beta-diversity suggests a very low connection among the caves and/or a very low dispersal capacity of the species. In the region under study, two main factors are intimately related to the richness of terrestrial subterranean species in caves: the amount of organic material (trophic level) and the formation process (genesis). This is the first time that the history of a cave genesis has been quantitatively considered to assess its importance in explaining richness patterns in comparison with other factors more widely recognized. [ABSTRACT FROM AUTHOR]

Aim Niche-based species distribution models (SDMs) are commonly used to predict impacts of global change on biodiversity, but the reliability of these predictions in space and time depends on their transferability. We tested how the strategy used to choose predictors impacts the transferability of SDMs at a cross-continental scale. Location North America, Eurasia and Australia. Method We used a systematic approach including 50 Holarctic plant invaders and 27 initial predictor variables, considering 10 different strategies for variable selection, accounting for the proximality, multicollinearity and climate analogy of predictors. We compared the average performance of each strategy, some of which used a large number of predictor combinations. Next, we looked for the single best model for each species across all the predictor combinations retained in the analysis. Transferability was considered as the predictive success of SDMs calibrated in the native range and projected onto the invaded range. Results Two strategies showed better SDM transferability on average: a set of predictors known for their ecologically meaningful effects on plant distribution, and the two first axes of a principal component analysis calibrated on all predictor variables (Spc2). From the more than 2000 combinations of predictors per species across strategies, the best set of predictors yielded SDMs with good transferability for 45 species (90%). These best combinations consisted of eight randomly assembled (39 species) or uncorrelated predictors (6 species) and Spc2 (5 species). We also found that internal cross-validation was not sufficient to give full information about the transferability of a SDM to a distinct range. Main conclusion Transferring SDMs at the macroclimatic scale, and thus anticipating invasions, is possible for the large majority of invasive plants considered in this study, but the accuracy of the predictions relies strongly on the choice of predictors. From our results, we recommend including either proximal and state-of-the-art variables or a reduced and orthogonalized set to obtain robust SDM projections. [ABSTRACT FROM AUTHOR]

Aim Statistical and ecological mechanisms shape species abundance distributions (SADs). A lack of correlation between ecological gradients and SAD shape would suggest that SADs are caused by purely statistical reasons. We evaluated the variation in the shape of SADs for communities in landscapes of differing variable connectivity, environmental heterogeneity, species niches overlap and productivity. Location Rainforests in the Madidi region (Bolivia). Methods We compiled biological and environmental information on 65 sites (a site being a group of two to six 0.1-ha plots where woody plants of a diameter at breast height ≥ 2.5 cm were inventoried). We built unveiled (complete) SADs for each site and fitted Gambin models to those SADs. The Gambin α parameter served as a metric of SAD shape. Low α values characterize logseries-like SADs, while high α values characterize lognormal-like SADs. For each site, we estimated landscape roughness, environmental heterogeneity, species niche overlap and productivity. These variables were related to SAD shape by means of variation partitioning. Results SADs changed from logseries-like to lognormal-like along the elevational gradient. Many of our predictor variables were correlated: 40.4% of the variation in SAD shape could not be attributed to specific factors. However, 50.62% of the variation in the SAD shape could be assigned to individual predictor matrices: 28.4% was explained exclusively by niche overlap, 15.41% exclusively by environmental heterogeneity, 5.20% exclusively by landscape roughness and 1.6% exclusively by productivity. Main conclusions Ecological processes related to the topographical/environmental complexities that vary across the elevational gradient are correlated with the SAD shape. Purely statistical mechanisms are apparently not sufficient to explain the changes in SAD shape. The most important factor is the mean overlap of the niches of the species of an assemblage: avoiding competition with co-occurring species could be the most important mechanism driving species relative success at the ≤100 km2 scale. [ABSTRACT FROM AUTHOR]