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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.

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.

O presente estudo teve por objetivo comparar os resultados de distribuição espacial obtidos entre os métodos clássicos e os métodos que estimam a variância entre parcelas. Foram analisadas duas espécies, Vernonia aurea e Duguetia furfuracea. Foram utilizados a Distribuição de Poisson (padrão aleatório), a Distribuição Binomial Negativa (padrão agregado) e os métodos BQV, TTLQV e PQV (variância entre parcelas), bem como a razão variância:média (I), coeficiente de Green (Ig) e o índice de dispersão de Morisita (Im). Ambas metodologias detectaram padrão de distribuição espacial agregado para as populações analisadas, com resultados similares quanto ao nível de agregação, além de complementação das informações, em diferentes escalas, entre os métodos clássicos e de variância entre parcelas. Desse modo, recomenda-se a utilização desses métodos estatísticos em estudos de estrutura espacial, uma vez que os testes são robustos e complementares e os dados são de fácil coleta em campo.This study aims to compare the results of spatial structure obtained between the classic and quadrat variance methods. Two species were analised, Vernonia aurea and Duguetia furfuracea. The Poisson distribution (random pattern), the Negative Binomial distribution (aggregate pattern), the BQV, TTLQV and PQV methods, the ratiovariance: mean (I), the Green coefficient (Ig) and the Morisita’s index of dispersion (Im) were used to detect the populations spatial pattern. An aggregated spatial pattern distribution was detected through both methodologies, with similar results as for the aggregation level and the complementation of the information in different scales between classic and quadrat variance methods. Thus, the utilization of these statistic methods in studies of the spatialstructure is recommended, given that tests are robust and complementary and field data samples are easy to collect.

O presente estudo teve por objetivo comparar os resultados de distribuição espacial obtidos entre os métodos clássicos e os métodos que estimam a variância entre parcelas. Foram analisadas duas espécies, Vernonia aurea e Duguetia furfuracea. Foram utilizados a Distribuição de Poisson (padrão aleatório), a Distribuição Binomial Negativa (padrão agregado) e os métodos BQV, TTLQV e PQV (variância entre parcelas), bem como a razão variância:média (I), coeficiente de Green (Ig) e o índice de dispersão de Morisita (Im). Ambas metodologias detectaram padrão de distribuição espacial agregado para as populações analisadas, com resultados similares quanto ao nível de agregação, além de complementação das informações, em diferentes escalas, entre os métodos clássicos e de variância entre parcelas. Desse modo, recomenda-se a utilização desses métodos estatísticos em estudos de estrutura espacial, uma vez que os testes são robustos e complementares e os dados são de fácil coleta em campo

O presente estudo teve por objetivo comparar os resultados de distribuição espacial obtidos entre os métodos clássicos e os métodos que estimam a variância entre parcelas. Foram analisadas duas espécies, Vernonia aurea e Duguetia furfuracea . Foram utilizados a Distribuição de Poisson (padrão aleatório), a Distribuição Binomial Negativa (padrão agregado) e os métodos BQV, TTLQV e PQV (variância entre parcelas), bem como a razão variância:média ( I ), coeficiente de Green ( Ig ) e o í­ndice de dispersão de Morisita ( Im ). Ambas metodologias detectaram padrão de distribuição espacial agregado para as populações analisadas, com resultados similares quanto ao ní­vel de agregação, além de complementação das informações, em diferentes escalas, entre os métodos clássicos e de variância entre parcelas. Desse modo, recomenda-se a utilização desses métodos estatí­sticos em estudos de estrutura espacial, uma vez que os testes são robustos e complementares e os dados são de fácil coleta em campo

The purpose of this study was to investigate the importance of present and historical climate as determinants of current species richness pattern of forestry trees in South America. The study predicted the distribution of 217 tree species using Maxent models, and calculated the potential species richness pattern, which was further deconstructed based on range sizes and modeled against current and historical climates predictors using Geographically Weighted Regressions (GWR) analyses. The current climate explains more of the wide-ranging species richness patterns than that of the narrow-ranging species, while the historical climate explained an equally small amount of variance for both narrow-and-wide ranging tree species richness patterns. The richness deconstruction based on range size revealed that the influences of current and historical climate hypotheses underlying patterns in South American tree species richness differ from those found in the Northern Hemisphere. Notably, the historical climate appears to be an important determinant of richness only in regions with marked climate changes and proved Pleistocenic refuges, while the current climate predicts the species richness across those Neotropical regions, with non-evident refuges in the Last Glacial Maximum. Thus, this study's analyses show that these climate hypotheses are complementary to explain the South American tree species richness. Keywords: climate changes, glacial refuges, water-energy availability, GWR analysis, spatial non-stationarity. O objetivo deste estudo foi testar qual dos climas, atual ou historico, e o principal preditor do padrao atual de riqueza de especies arboreas de interesse comercial. Nos modelamos a distribuicao de 217 especies usando Maxent e usamos esses mapas preditivos para obter o padrao de riqueza de especies. A riqueza foi desconstruida em relacao ao tamanho da distribuicao geografica das especies e modelada contra os climas atual e historico utilizando Regressoes Geograficamente Ponderadas. O clima atual explicou melhor o padrao de riqueza das especies com ampla distribuicao geografica do que de especies com distribuicao restrita, enquanto o clima historico explicou a mesma variancia na riqueza dos dois grupos de especies. Nossas analises com plantas sul americanas mostram diferentes relacoes da riqueza de especies ampla e restritamente distribuidas com os climas atual e historico, quando comparado aos resultados encontrados no hemisferio norte. O clima historico se mostra como importante preditor da riqueza somente em regioes com mudancas climaticas acentuadas e onde ocorreram refugios Pleistocenicos, enquanto o clima atual e o melhor da riqueza nas regioes Neotropicais sem evidencias de refugios durante o maximo da ultima glaciacao. Dessa maneira, nossos resultados indicam que essas hipoteses sao complementares para explicar a riqueza predita de especies arboreas da America do Sul. Palavras-chave: mudancas climaticas, refugios gjaciais, disponibilidade hidrico-energetica, analise GWR, nao-estacionaridade espacial.

Despite the widespread use of ecological niche models (ENMs) for predicting the responses of species to climate change, these models do not explicitly incorporate any population‐level mechanism. On the other hand, mechanistic models adding population processes (e.g. biotic interactions, dispersal and adaptive potential to abiotic conditions) are much more complex and difficult to parameterize, especially if the goal is to predict range shifts for many species simultaneously. In particular, the adaptive potential (based on genetic adaptations, phenotypic plasticity and behavioral adjustments for physiological responses) of local populations has been a less studied mechanism affecting species’ responses to climatic change so far. Here, we discuss and apply an alternative macroecological framework to evaluate the potential role of evolutionary rescue under climate change based on ENMs. We begin by reviewing eco‐evolutionary models that evaluate the maximum sustainable evolutionary rate under a scenario of environmental change, showing how they can be used to understand the impact of temperature change on a Neotropical anuran species, the Schneider's toad Rhinella diptycha. Then we show how to evaluate spatial patterns of species’ geographic range shift using such models, by estimating evolutionary rates at the trailing edge of species distribution estimated by ENMs and by recalculating the relative amount of total range loss under climate change. We show how different models can reduce the expected range loss predicted for the studied species by potential ecophysiological adaptations in some regions of the trailing edge predicted by ENMs. For general applications, we believe that parameters for large numbers of species and populations can be obtained from macroecological generalizations (e.g. allometric equations and ecogeographical rules), so our framework coupling ENMs with eco‐evolutionary models can be applied to achieve a more accurate picture of potential impacts from climate change and other threats to biodiversity.

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.