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Most species data display spatial autocorrelation that can affect ecological niche models (ENMs) accuracy‐statistics, affecting its ability to infer geographic distributions. Here we evaluate whether the spatial autocorrelation underlying species data affects accuracy‐statistics and map the uncertainties due to spatial autocorrelation effects on species range predictions under past and future climate models. As an example, ENMs were fitted to Qualea grandiflora (Vochysiaceae), a widely distributed plant from Brazilian Cerrado. We corrected for spatial autocorrelation in ENMs by selecting sampling sites equidistant in geographical (GEO) and environmental (ENV) spaces. Distributions were modelled using 13 ENMs evaluated by two accuracy‐statistics (TSS and AUC), which were compared with uncorrected ENMs. Null models and the similarity statistics I were used to evaluate the effects of spatial autocorrelation. Moreover, we applied a hierarchical ANOVA to partition and map the uncertainties from the time (across last glacial maximum, pre‐insustrial, and 2080 time periods) and methodological components (ENMs and autocorrelation corrections). The GEO and ENV models had the highest accuracy‐statistics values, although only the ENV model had values higher than expected by chance alone for most of the 13 ENMs. Uncertainties from time component were higher in the core region of the Brazilian Cerrado where Q. grandiflora occurs, whereas methodological components presented higher uncertainties in the extreme northern and southern regions of South America (i.e. outside of Brazilian Cerrado). Our findings show that accounting for autocorrelation in environmental space is more efficient than doing so in geographical space. Methodological uncertainties were concentrated in outside the core region of Q. grandiflora's habitat. Conversely, uncertainty due to time component in the Brazilian Cerrado reveals that ENMs were able to capture climate change effects on Q. grandiflora distributions.

Climate change is amongst the main threats to biodiversity. Considering extant mammals endured Quaternary climate change, we analyzed the extent to which this past change predicts current mammals' extinction risk at global and biogeographical scales. We accessed range dynamics by modeling the potential distribution of all extant terrestrial mammals in the Last Glacial Maximum (LGM, 21,000 years ago) and in current climate conditions and used extinction risk from IUCN red list. We built General Linear Mixed-Effects Models to test the magnitude with which the variation in geographic range (ΔRange) and a proxy for abundance (ΔSuitability) between the LGM and present-day predicts current mammal's extinction risk. We found past climate change most strongly reduced the geographical range and climatic suitability of threatened rather than non-threatened mammals. Quaternary range contractions and reduced suitability explain around 40% of species extinction risk, particularly for small-bodied mammals. At global and biogeographical scales, all groups that suffered significant Quaternary range contractions now contain a greater proportion of threatened species when compared to groups whose ranges did not significantly contract. This reinforces the importance of using historical range contractions as a key predictor of extinction risk for species in the present and future climate change scenarios and supports current efforts to fight climate change for biodiversity conservation.

Species distributions are determined by abiotic and biotic factors as well as dispersal, but most studies focus exclusively on abiotic (mainly climatic) components. In this study, we evaluated the influence of dispersal as a predictor for species distribution models (SDMs) using the turtle Mesoclemmys tuberculata as an example. We specifically tested whether dispersal is a better predictor of the distribution of M. tuberculata than climatic predictors. We sampled occurrence records of M. tuberculata to build SDMs and used the distance of each cell to the nearest river (river distance) as a predictor for dispersal. In addition, three bioclimatic predictors that quantify temperature and precipitation were used. We applied five different algorithms (BioClim, Domain, Maxent, SVM, and Random Forest) to model the distribution of M. tuberculata and evaluate the relative influence of each predictor variable. Although models including dispersal as a predictor performed slightly better than models omitting it, climatic predictors were found to be more important to describe species distribution across all SDMs. Our results suggest that although dispersal limits the potential geographic areas that the species may reach, abiotic parameters determine where M. tuberculata actually lives. Finally, we used consensus maps to prioritize areas for future field surveys.

Biological invasions are important drivers of biodiversity loss. Hence, predicting invasion risks considering the invasion history of a species might help drive meaningful conservation strategies. We investigated the niche dynamics occurring during the invasion of Hydrilla verticillata in North and South America. Because of founder effects, we hypothesised that occupied invaded area niches across North and South American are a subset of the occupied niche in the native range. Moreover, according to the invasion history, we expected that the South American niche is more similar to the North American one than the native niche. We built ecological niche models to predict the potential distribution of hydrilla from native and invaded occurrence records, as well as analysing niche overlap, equivalency, and similarity between the native and two invaded areas. Although the models predicted spatially congruent suitable sites, the ones based on native occurrence records predicted larger geographical ranges for hydrilla across South America than those based on the records of its North American invasions. The environmental conditions the species occupied in both invaded areas are modestly overlapped with the native area (Schoener’s D < 0.6), with native and South American niches showing the highest overlap and significant equivalency. Contrary to our prediction, the invaded North and South American niches presented the smallest niche overlap. Our findings suggest that founder effects triggered deep shifts in hydrilla’s occupation abilities across invaded areas, but do not support successive invasion events. Hydrilla’s Grinnellian niche was maintained throughout the invaded areas, and its potential invasion across South America is massive, regardless of its origin.

• Premise of the study: Wild edible plants (WEPs) have an important cultural and economic role in human population worldwide. Human impacts are quickly converting natural habitats in agricultural, cattle ranch, and urbanized lands, putting native species on peril of risk of extinction, including some WEPs. Moreover, global climate changes also can pose another threat to species persistency. Here, we established conservation priorities for the Cerrado, a neotropical region in South America with high levels of plant endemism and vulnerability, aiming to assure long-term persistency of 16 most important WEPs. We evaluated these conservation priorities using a conservation biogeography framework using ecological patterns and process at a biogeographical scale to deal with species conservation features. • Methods: We built ecological niche models for 16 WEPs from Cerrado in the neotropics using climate models for preindustrial, past (Last Glacial Maximum) and future (year 2080) time periods to establish climatically stable areas through time, finding refugias for these WEPs. We used a spatial prioritization algorithm based on the spatial pattern of irreplaceability across the neotropics, aiming to ensure the persistence of at least 25% of range size in climatically stable areas for each WEP, using agricultural models as constraints. • Key results: The Southeast Cerrado was the most biotically stable and irreplaceable region for the WEPs compared with other areas across the neotropics. • Conclusions: Our findings strongly suggest that the Southeast Cerrado should be considered a conservation priority, with new protected areas to be sustainably managed and restored, to guarantee the supply of cultural and ecosystem services provided from the Cerrado's WEPs.

Understanding the dispersal routes of Neotropical savanna tree species is an essential step to unravel the effects of past climate change on genetic patterns, species distribution and population demography. Here we reconstruct the demographic history and dispersal dynamics of the Neotropical savanna tree species Tabebuia aurea to understand the effects of Quaternary climate change on its current spatial patterns of genetic diversity. We sampled 285 individuals from 21 populations throughout Brazilian savannas and sequenced all individuals for three chloroplast intergenic spacers and ITS nrDNA. We analyzed data using a multi-model inference framework by coupling the relaxed random walk model (RRW), ecological niche modeling (ENM) and statistical phylogeography. The most recent common ancestor of T. aurea lineages dated from ~4.0 ± 2.5 Ma. T. aurea lineages cyclically dispersed from the West toward the Central-West Brazil, and from the Southeast toward the East and Northeast Brazil, following the paleodistribution dynamics shown by the ENMs through the last glacial cycle. A historical refugium through time may have allowed dispersal of lineages among populations of Central Brazil, overlapping with population expansion during interglacial periods and the diversification of new lineages. Range and population expansion through the Quaternary were, respectively, the most frequent prediction from ENMs and the most likely demographic scenario from coalescent simulations. Consistent phylogeographic patterns among multiple modeling inferences indicate a promising approach, allowing us to understand how cyclical climate changes through the Quaternary drove complex population dynamics and the current patterns of species distribution and genetic diversity.

Purpose: Ecological Niche Modeling (ENM) and Species Distribution Modeling (SDM) have become powerful tools in biology, biogeography, paleoecology and biodiversity conservation. ENM and SDM are evaluated using metrics that take into account the errors and successes of the models in predicting the presence or absence of species in certain locations. Here, we evaluate the effects of sampling bias on the relationship between evaluative metrics and the predictive capacity of models.   Theoretical framework: ENM and SDM are powerful tools with extensive potential for use, but in order for them to produce useful results, they need to be constructed and validated appropriately. The occurrence data used in both processes may not have been collected randomly, which can lead to issues. An investigation into potential problems arising from the use of non-randomly collected occurrence data is necessary, as new issues may arise from simply filtering the data and reducing the number of occurrence records.   Material and Methods: We use Virtual Species (VS) to evaluate the effect of sampling bias. Using VS is the most robust approach for this type of testing, as we know the entire VS distribution.   Results and conclusion: Our results showed that sampling bias reduces the predictive capacity of the ENM and SDM models. We did not find a consistent pattern of the effect of sampling bias on the relationship between evaluation metrics and the predictive capacity of models. The effect size varied between different bias intensities. We emphasize that reducing the strength of the bias is one of the most efficient ways to minimize this problem.

Conservation strategies aiming to safeguard species genetic diversity in the Cerrado are urgent. The biome is an agriculture frontier and lost at least 50% of its natural capital since the early 1950s, with the highest rate of vegetation clearing among all Brazilian biomes. Here we match information on geographic range shifts in response to climate changes and habitat loss to define conservation priorities for species genetic diversity using Eugenia dysenterica, a widely distributed tree across the Brazilian Cerrado. We found a set of 27 optimal solutions in which a minimum of 12 out of 23 populations are necessary to represent all 208 alleles of the species. Environmental suitability predicted for 2050 was higher for populations in the southern region of the Cerrado, whereas the proportion of natural remnants around populations expected for 2030 was lower in this same region. Thus, it seems to be more conservative to adopt “in situ” strategies in the northwestern part of the species range to hold more genetic diversity in areas harboring high numbers of natural remnants, despite the likely reduction in climatic suitability. On the other hand, in the southern and southeastern region of the range, despite more stability from a climatic point of view, there was a serious constraint given the high levels of human occupation; in this case, “ex situ” strategies might be a better option for the species. Our results and proposed priorities enable different strategies for making an operational approach for conservation of genetic diversity. Adopting different prioritization strategies for stable and unstable regions (both in climatic suitability and natural remnants) in the future would allow, in principle, to avoid “the worst of both worlds” to achieve an efficient conservation program for the species.

Climate change is currently considered one key threat to biodiversity. Species with a restricted distribution possibly will be more affected than those with wide ranges. Climate change can potentially affect both herbivores and their host plants and reduce their geographical ranges. The nature and intensity of their responses, however, may not necessarily match. We investigated the synergistic effects of climate change on two Neotropical butterfly species and their respective host plants at the end of twenty-first century. The species selected contrast in distribution extent, feeding habits and conservation status: Battus polystictus is widespread, oligophagous and common and Parides ascanius has a restricted distribution, is monophagous and is listed as vulnerable in the IUCN red list. Maps of the potential distribution of the butterflies and their host plants, as well as maps showing the changes in the ranges, in overlap area and direction of shifts were produced. Under forecasted climate change, all ranges and interaction areas decreased and the impacts were proportional to the intensity of change in future scenarios, either when compared all together or pairwise (p < 0.001). Based in our results estimation of climatically suitability, the monophagous butterfly with restricted distribution did suffer more severely these effects than the widespread generalist species. We did not anticipate, however, the possible strength of the predicted effects. Under the conditions modelled, P. ascanius would probably find no suitable conditions for occurrence, irrespectively of its host plant, and might go extinct. B. polystictus, on the other hand, suffered marked decreases in suitable area (46% for RCP4.5 and 91% for RCP8.5) and dramatic southward shifts (> 1439 km for RCP4.5 and > 1956 km for RCP8.5) on its range. This effect is further worsening because although most host plants are also much affected by the changes, the shift in their ranges is on average much smaller and each species responded in subtly different ways to the changing conditions, so that most of their future range may be spatially incompatible with the B. polystictus. We propose that the extinction risk of P. ascanius should be adjusted to critically endangered and point that species interactions and climate change must be accounted for in conservation planning.Implications for insect conservationThe assessment carried out in this study contributes to the knowledge of climate change scenarios of butterfly species correlated with their host plants until the end of this century. These results can propose priority sites for conservation efforts like contribute to change status of P. ascanius to critically endangered, actually listed as vulnerable on the IUCN red list.