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Aim: We tested whether the geographic variation in the proportion of beta diversity attributed to nestedness or turnover components was explained by the effect of past glaciation events. Specifically, we tested the hypothesis that most of the beta diversity in regions retaining ice until recent periods was due to nestedness. Additionally, we tested whether the variation was influenced by thermal tolerance and the dispersal ability of species. Location: This study analysed data from the New World. Methods: We used presence/absence data for amphibians, birds and mammals of the New World. We calculated beta diversity among each 1° x 1° cell and the adjacent cells using the Sorensen dissimilarity index that expresses the total beta diversity. Furthermore, we partitioned it into turnover and nestedness components. The relative importance of the two latter components was expressed as the proportion of total beta diversity explained by nestedness (ß ratio ). We calculated the correlation between p rat io and the time each cell was free of ice since the last glaciation (cell age). To control the effects of spatial autocorrelation, we calculated geographically effective degrees of freedom. Results: The proportion of beta diversity attributed to nestedness was negatively correlated with cell age. Moreover, this effect was stronger for amphibians than mammals, and stronger for mammals than birds. Main conclusions: Our results are in accordance with the hypothesis that the nestedness component of beta diversity is more important in areas affected by glaciations until recent time. The beta diversity in high latitudes is the result of past extinctions and recent recolonization, which result in higher levels of nestedness. This process is more evident for vertebrates with lower dispersal ability and lower temperature tolerance.

Because most macroecological and biodiversity data are spatially autocorrelated, special tools for describing spatial structures and dealing with hypothesis testing are usually required. Unfortunately, most of these methods have not been available in a single statistical package. Consequently, using these tools is still a challenge for most ecologists and biogeographers. In this paper, we present SAM (Spatial Analysis in Macroecology), a new, easy-to-use, freeware package for spatial analysis in macroecology and biogeography. Through an intuitive, fully graphical interface, this package allows the user to describe spatial patterns in variables and provides an explicit spatial framework for standard techniques of regression and correlation. Moran's I autocorrelation coefficient can be calculated based on a range of matrices describing spatial relationships, for original variables as well as for residuals of regression models, which can also include filtering components (obtained by standard trend surface analysis or by principal coordinates of neighbour matrices). SAM also offers tools for correcting the number of degrees of freedom when calculating the significance of correlation coefficients. Explicit spatial modelling using several forms of autoregression and generalized least-squares models are also available. We believe this new tool will provide researchers with the basic statistical tools to resolve autocorrelation problems and, simultaneously, to explore spatial components in macroecological and biogeographical data. Although the program was designed primarily for the applications in macroecology and biogeography, most of SAM's statistical tools will be useful for all kinds of surface pattern spatial analysis. The program is freely available at www.ecoevol.ufg.br/sam (permanent URL at http://purl.oclc.org/sam/).

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.

We tested the proposition that there are more species in the tropics because basal clades adapted to warm paleoclimates have been lost in regions now experiencing cool climates. Molecular phylogenies were used to classify species as “basal” and “derived” based on their family, and their richness patterns were contrasted. Path models also evaluated environmental predictors of richness patterns. As predicted, basal clades are more diverse in the lowland tropics, whereas derived clades are more diverse in the extratropics and high‐altitude tropics. Seventy‐four percent of the variation in bird richness was explained by environmental variables, but models differed for basal and derived groups. The overall gradient is described by the spatial pattern of basal clades, although there are differences in the Old and New Worlds. We conclude that in ecological time, the global richness gradient reflects birds’ responses to climatic gradients, partially operating via plants. Over evolutionary time, the gradient primarily reflects the extirpation of species in older clades from parts of the world that have become cooler in the present. A strong secondary effect arises from dispersal of clades from centers of origin and subsequent radiations. Overall, the diversity gradient is well explained by niche conservatism and the “time‐for‐speciation” hypothesis.

1. Many factors shape plant reproductive patterns including climate, competition or attraction of pollinators and seed dispersers, flower and fruit morphologies and phylogenetic relationships. South American Myrtaceae (Myrteae) were chosen to evaluate hypotheses on how abiotic and biotic factors, morphology and phylogeny influence plant reproductive phenology. 2. We examined whether Myrteae reproductive patterns are seasonal and related to climate; whether aggregated or segregated flowering and fruiting occur among species sharing pollinators or seed dispersers; the relationship between phenological and morphological traits, time of reproduction and Myrteae phylogenetic history; and the shared influence of ecological (environmental) and phylogenetic factors on Myrteae reproductive patterns. 3. We observed flowering and fruiting of 34 Myrteae species during 30 months in an Atlantic rain forest (south-eastern Brazil). We employed circular statistics to test for seasonality and multiple regressions to relate climate and phenology. Competition and facilitation hypotheses were tested using null models. We quantified the phylogenetic signal on phenology and morphology of Myrteae species using phylogenetic eigenvector regression (PVR) analyses, and used PVR and partial regressions to quantify the influences of ecology and phylogeny on phenology. 4. Myrteae flowered seasonally, whereas fruiting was not seasonal. Environmental factors (day-length and temperature) and associations with biotic vectors through facilitation hypothesis explained the aggregated blossom. Fruit maturation time affected the species' flowering sequence. Plants with longer fruit maturation times flowered at the end of the appropriate season, explaining the continuous fruit availability despite the seasonal flowering. The random fruiting pattern explained the regular presence of seed dispersers. Myrteae phenology was phylogenetically structured, even when phenophases were not seasonal, i.e., closer related species fruited under more similar environmental conditions, suggesting that the reproductive phenological niche was inherited along the course of evolution. We detected a shared influence of ecology and phylogeny on Myrteae phenological responses, and the ecological component explained better phenological variation than phylogeny. 5. Synthesis. We provided a new perspective on plant phenology based on phylogeny and ecology and demonstrated the importance of considering their shared influence in phenological studies. Our analyses can be employed for the most representative families of highly diverse ecosystems to improve our understanding of evolutionary patterns and general trends in phenology.

Although parameter estimates are not as affected by spatial autocorrelation as Type I errors, the change from classical null hypothesis significance testing to model selection under an information theoretic approach does not completely avoid problems caused by spatial autocorrelation. Here we briefly review the model selection approach based on the Akaike information criterion (AIC) and present a new routine for Spatial Analysis in Macroecology (SAM) software that helps establishing minimum adequate models in the presence of spatial autocorrelation. We illustrate how a model selection approach based on the AIC can be used in geographical data by modelling patterns of mammal species in South America represented in a grid system (n = 383) with 2° of resolution, as a function of five environmental explanatory variables, performing an exhaustive search of minimum adequate models considering three regression methods: non-spatial ordinary least squares (OLS), spatial eigenvector mapping and the autoregressive (lagged-response) model. The models selected by spatial methods included a smaller number of explanatory variables than the one selected by OLS, and minimum adequate models contain different explanatory variables, although model averaging revealed a similar rank of explanatory variables. We stress that the AIC is sensitive to the presence of spatial autocorrelation, generating unstable and overfitted minimum adequate models to describe macroecological data based on non-spatial OLS regression. Alternative regression techniques provided different minimum adequate models and have different uncertainty levels. Despite this, the averaged model based on Akaike weights generates consistent and robust results across different methods and may be the best approach for understanding of macroecological patterns.

Aim  The aim of this study was to test a variant of the evolutionary time hypothesis for the bird latitudinal diversity gradient derived from the effects of niche conservatism in the face of global climate change over evolutionary time. Location  The Western Hemisphere. Methods  We used digitized range maps of breeding birds to estimate the species richness at two grain sizes, 756 and 12,100 km2. We then used molecular phylogenies resolved to family to quantify the root distance (RD) of each species as a measure of its level of evolutionary development. Birds were classified as ‘basal’ or ‘derived’ based on the RD of their family, and richness patterns were contrasted for the most basal and most derived 30% of species. We also generated temperature estimates for the Palaeogene across the Western Hemisphere to examine how spatial covariation between past and present climates might make it difficult to distinguish between ecological and evolutionary hypotheses for the current richness gradient. Results  The warm, wet tropics support many species from basal bird clades, whereas the northern temperate zone and cool or dry tropics are dominated by species from more recent, evolutionarily derived clades. Furthermore, crucial to evaluating how niche conservatism among birds may drive the hemispherical richness gradient, the spatial structure of the richness gradient for basal groups is statistically indistinguishable from the overall gradient, whereas the richness gradient for derived groups is much shallower than the overall gradient. Finally, modern temperatures and the pattern of climate cooling since the Eocene are indistinguishable as predictors of bird species richness. Main conclusions  Differences in the richness gradients of basal vs. derived clades suggest that the hemispherical gradient has been strongly influenced by the differential extirpation of species in older, warm‐adapted clades from parts of the world that have become cooler in the present. We propose that niche conservatism and global‐scale climate change over evolutionary time provide a parsimonious explanation for the contemporary bird latitudinal diversity gradient in the New World, although dispersal limitation of some highly derived clades probably plays a secondary role.

Non-governmental organizations have proposed nine different global prioritization schemes, some of them focusing on areas with low vulnerability (a proactive reasoning) and some others targeting areas with high vulnerability (a reactive reasoning). The main threat to the remaining natural habitats of these areas is the expansion of agriculture. We evaluated the spatial congruence between agricultural land cover and global conservation priority areas in the present and in the future using a spatial model of land use cover change from 2000 to 2100. We showed that by the year 2000, the extent of agriculture was larger in reactive priority areas than in the rest of the world, while it was smaller in areas highlighted as important under proactive approaches. During the twenty-first century, we found a general increase in agriculture area and the difference between the approaches of conservation schemes is expected to hold true, although we found that high-biodiversity wilderness areas (HBWA), a proactive scheme, may be specially affected in certain scenarios of future change. These results suggest an increase in conservation conflicts over this century. In face of agricultural expansion, both kinds of prioritization approaches are important, but different strategies of protection are necessary (e.g., reactive approaches need the urgent protection of remnant habitats, while proactive ones have space to create megareserves). Further, conservation organizations must include agriculture expansion data and their uncertainty in conservation planning in order to be more successful in biological conservation.

Colonization of islands often activate a complex chain of adaptive events that, over a relatively short evolutionary time, may drive strong shifts in body size, a pattern known as the Island Rule. It is arguably difficult to perform a direct analysis of the natural selection forces behind such a change in body size. Here, we used quantitative evolutionary genetic models, coupled with simulations and pattern-oriented modelling, to analyse the evolution of brain and body size in Homo floresiensis, a diminutive hominin species that appeared around 700 kya and survived up to relatively recent times (60–90 kya) on Flores Island, Indonesia. The hypothesis of neutral evolution was rejected in 97% of the simulations, and estimated selection gradients are within the range found in living natural populations. We showed that insularity may have triggered slightly different evolutionary trajectories for body and brain size, which means explaining the exceedingly small cranial volume of H. floresiensis requires additional selective forces acting on brain size alone. Our analyses also support previous conclusions that H. floresiensis may be most likely derived from an early Indonesian H. erectus, which is coherent with currently accepted biogeographical scenario for Homo expansion out of Africa.

Aim: Despite the importance of the niche concept in ecological and evolutionary theory, there are still many discussions about its definition and operational evaluation, especially when dealing with niche divergence and conservatism in an explicit phylogenetic context. Here we evaluate patterns of niche evolution in 67 New World Carnivora species, measured using Hellinger distances based on MAXENT models of species distribution. We show how inferences on niche conservatism or divergence depend on the way phylogenetic patterns are analysed using matrix comparison techniques. Innovation: Initially we used the simplest approach of Mantel tests to compare Hellinger distances (N) derived from MAXENT and phylogenetic distances (P) among species. Then we extended the Mantel test to generate a multivariate correlogram, in which phylogenetic patterns are analysed at multiple levels in the phylogeny and can reveal nonlinearity in the relationship between divergence and time. Finally, we proposed a new approach to generate c locaP (or 'specific') leverages of components for Mantel correlation, evaluating the non-stationarity in the relationship between N and P for each species. This new approach was used to show if some lineages are more prone to niche shift or conservatism than others. Main conclusions: Standard Mantel tests indicated a poor correspondence between N and P matrices, discarding the idea of niche conservatism for Carnivora, but the correlogram supports that closely related species tend to be more similar than expected by chance. Moreover, the variance among Hellinger distances between pairs of closely phylogenetically related species is much larger than for the entire clade. Phylogenetic non-stationarity analysis shows that in some Carnivora families the niche tends to divergence (Mustelidae and Canidae), whereas in others it tends to conservatism (Procyonidae and Mustelidae) at short phylogenetic distances. Our analyses clearly show that misleading results may appear if niche divergence is analysed only by simple matrix correlations not taking into account complex patterns of phylogenetic nonlinearity and non-stationarity.