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Pseudoryzomys simplex (Winge 1887) is a small to medium sized terrestrial oryzomyine rodent (Cricetidae, Sigmodontinae) widely distributed in humid environments of tropical and subtropical lowlands of South America with a marked rainy season. The occurrence of this species in the south-central Pampean region between 4700 and 200 ka cal BP was originally associated with some warm climatic episodes. A later hypothesis points out that P. simplex was a typical element of the Humid Pampa subregion during this period, whose distribution was retracted to the north due to the strong anthropic modifications in the area. To corroborate these hypotheses, the niche of occurrence of P. simplex was calculated to analyse the preferred climatic conditions of contemporaneous and fossil record of the species since 4700 ka cal BP. The derived climatic niche of P. simplex shows a marked preference for areas with seasonality precipitation patterns and tropical/subtropical conditions. Geographical estimations and climatic niches derived revealed a moderate overlapping between contemporaneous and Pampean late-Holocene projection, which in no case includes the localities where fossil data were found. Although a better comprehension of the ecological requirements of the species is necessary to discard a shift in its realized climatic niche, it is probable that P. simplex is able to maintain stable populations under similar conditions to the ones represented by fossil occurrences. The distribution of the species in the Humid Pampa subregion is probably affected by non-climatic factors today which are reducing its contemporaneous realized climatic niche and distorting the derived climatic niches obtained. These results support that this species cannot be considered a reliable palaeoclimatic indicator of more Brazilian conditions in the Humid Pampean subregion during the past. [ABSTRACT FROM AUTHOR]

Aim: Adequate responses of species to climate changes require that thermal changes remain compatible across different key biological aspects (e.g. reproduction, feeding and development). However, limits of thermal compatibility to such biological aspects are largely unknown in extant ectotherm groups. To fill this gap, we studied the in-traspecific congruence of thermal responses across biological aspects. Location: Iberian Peninsula. Taxon: Scarabaeidae Dung beetles. Methods: We studied the role of temperature in determining the diel, seasonal and geographical occurrences of 16 dung beetle species. We fitted polynomial GLMs of the abundance/occurrence of each species as a function of temperature and alternative predictors for each spatiotemporal scale, using deviance partitioning to explore the relative contribution of temperature. We used the fitted models to estimate realized thermal niche attributes at these three spatiotemporal scales, and assessed their intraspecific congruence through the correlation of niche attributes from different scales. Results: We found that temperature has relatively low--but not negligible--explanatory capacity at the three spatiotemporal scales, once alternative predictors are taken into account. More importantly, the estimated thermal responses were largely incongruent across scales, indicating that these species have multidimensional thermal niches. Main conclusions: The multidimensionality of thermal niches entails that species' adjustments to fulfil temperature requirements for one biological aspect (such as seasonal ontogenetic cycles) may result in detrimental effects on other elements (e.g. diel activity). These trade-offs could expose individuals to inadequate temperatures at certain moments, reducing populations' performance. Paradoxically, the weak effects of temperature we found may have severe consequences for species responses to warming if temperature regulates essential aspects of their biology in divergent ways. [ABSTRACT FROM AUTHOR]

The description of how biological information is compiled over time is essential to detect temporal biases in biodiversity data that could directly influence the utility, comparability, and reliability of ecological and biogeographical studies.We explore trends in species recording over time using one of the most spatially and temporally comprehensive country‐level databases for any group of insects in the world – the database of butterfly occurrences from Great Britain.Firstly, we used two crucial milestones (the year in which the taxonomic inventory is complete, i.e., when the last species was recorded, the year in which all species are recorded together for the first time) to delimit three main phases in the process of biodiversity recording (taxonomic, faunistic and exhaustive phases). Secondly, we aimed to quantify how far species features (attractiveness and detectability) influence the process of recording through time.During the first stage of biodiversity compilation, when the main aim is to complete the taxonomic inventory (taxonomic period), entomologists tend to record attractive species more frequently. However, once the inventory is complete, particularly in the period during which more spatially and temporally comprehensive information about species distribution is amassed (the exhaustive period), the recording pattern clearly changes to more detectable species.Common, highly detectable species are undersampled in the first phase of biodiversity data compilation and oversampled in the final stages. Awareness of such temporal patterns in recording is necessary in order to correctly interpret and address bias in insect biodiversity trends. [ABSTRACT FROM AUTHOR]

Estimating the realized and potential distribution of species has become a very active field of research with capacity to propose likely speciation mechanisms. Here, environmental variables and point locality data derived from several sources were used to examine the concordance between geographical distributions and environmental niches derived from occurrences for eleven species of the genus Uromastyx (Reptilia, Agamidae). Our results indicate that the degree of geographical overlap is definitively and statistically lower than the degree of environmental similarity. This reinforces the hypothesis that speciation process within the genus Uromastyx will be mainly based on geographical isolation. However, the environmental divergence among some groups of species cannot be excluded; high environmental distances can be obtained for some related species and the environmental gradient represented by two unique climatic variables allows discriminating some species among which an ecological or environmental segregation would be a plausible explanation. [ABSTRACT FROM AUTHOR]

Historic processes are expected to influence present diversity patterns in combination with contemporary environmental factors. We hypothesise that the joint use of beta diversity partitioning methods and a threshold-based approach may help reveal the effect of large-scale historic processes on present biodiversity. We partitioned intra-regional beta diversity into its turnover (differences in composition caused by species replacements) and nestedness-resultant (differences in species composition caused by species losses) components. We used piecewise regressions to show that, for amphibian beta diversity, two different world regions can be distinguished. Below parallel 37, beta diversity is dominated by turnover, while above parallel 37, beta diversity is dominated by nestedness. Notably, these regions are revealed when the piecewise regression method is applied to the relationship between latitude and the difference between the Last Glacial Maximum (LGM) and the present temperature but not when present energy-water factors are analysed. When this threshold effect of historic climatic change is partialled out, current energy-water variables become more relevant to the nestedness-resultant dissimilarity patterns, while mountainous areas are associated with higher spatial turnover. This result suggests that nested patterns are caused by species losses that are determined by physiological constraints, whereas turnover is associated with speciation and/or Pleistocene refugia. Thus, the new threshold-based view may help reveal the role of historic factors in shaping present amphibian beta diversity patterns. [ABSTRACT FROM AUTHOR]

Aim Still poorly understood, the main migratory pathways for most trans-Saharan species pass through the Iberian Peninsula, which acts as a gateway to the European–African migratory system. Arrival patterns in this region for the common swift ( Apus apus) and barn swallow ( Hirundo rustica), of similar morphology and flight capabilities, were described, and the environmental and geographical factors best explaining them were examined, in a search for common ecological constraints on these two migratory species. Location Latitude ranged from 36.02 to 43.68°N, longitude from 9.05°W to 3.17°E, and altitude from 0 to 1595 m a.s.l. for 482 common swift and 812 barn swallow Spanish localities spread widely over the Iberian breeding grounds of the two species. Methods Our data set, covering the years 1960–1990, consisted of 3206 first-arrival dates for common swifts and 6036 for barn swallows. Forty topographical, climatic, river basin, geographical and spatial variables were used as explanatory variables in general regression models (GRMs). GRMs included polynomial terms up to cubic functions in all variables when they were significant. A backward stepwise selection procedure was applied in all models until only significant terms remained. GRMs were applied in two steps. First, we searched for the best model in each one of the five types of variables (topographical, climatic, river basin, geographical and spatial). To cope with the unavoidable correlation between explanatory variables, the relative importance of each type of variable was assessed by hierarchical variance partitioning. Secondly, we searched for that model able to explain the maximum amount of the observed variability in arrival date. To obtain this model all significant explanatory variables were subjected jointly to a GRM. Spatial variables were then added to this model to take any remaining spatial structure in the data into account. Moran's I autocorrelation coefficient was used to check for spatial autocorrelation. Results Both species arrived earlier in the south-western Iberian Peninsula, where summers are warmer and drier. From there, both species followed the main southern Iberian river basins towards the north-east; however, several mountainous regions impede the colonization of eastern Iberia. The best models for each type of variable explained 19–47% of the variability in common swift arrival dates and 14–44% in barn swallow arrival dates. Variance partitioning indicated that climatic and geographical variables best explained variability. The best predictive models built with all variables accounted for 52% of the variability in common swift arrival dates and 50% for the barn swallow. Residuals from both models were not spatially autocorrelated, an indication that all major spatially structured variation had been accounted for. Main conclusions Spring arrival patterns are highly dependent on the geographical configuration of the Iberian Peninsula. This spatial constraint forces both species to converge very closely in their spring migration, because common swifts and barn swallows are subject to a trade-off between optimum migratory pathways and territories ecologically suitable for breeding. [ABSTRACT FROM AUTHOR]

ABSTRACT: For many applications the continuous prediction afforded by species distribution modeling must be converted to a map of presence or absence, so a threshold probability indicative of species presence must be fixed. Because of the bias in probability outputs due to frequency of presences (prevalence), a fixed threshold value, such as 0.5, does not usually correspond to the threshold above which the species is more likely to be present. In this paper four threshold criteria are compared for a wide range of sample sizes and prevalences, modeling a virtual species in order to avoid the omnipresent error sources that the use of real species data implies. In general, sensitivity–specificity difference minimizer and sensitivity–specificity sum maximizer criteria produced the most accurate predictions. The widely-used 0.5 fixed threshold and Kappa-maximizer criteria are the worst ones in almost all situations. Nevertheless, whatever the criteria used, the threshold value chosen and the research goals that determined its choice must be stated. [Copyright &y& Elsevier]