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The emergence, distribution, and extinction of species are driven by interacting factors—spatial, temporal, physical, and biotic. Rangel et al. simulated the past 800,000 years of evolution in South America, incorporating these factors into a spatially explicit dynamic model to explore the geographical generation of diversity. Their simulations, based on a paleoclimate model on a 5° latitude-longitude scale, result in shifting maps of speciation, persistence, and extinction (or cradles, museums, and graves). The simulations culminate in a striking resemblance to contemporary distribution patterns across the continent for birds, mammals, and plants—despite having no target patterns and no empirical data parameterizing them. Science , this issue p. eaar5452 Mechanistic simulations of climate dynamics, speciation, and adaptive evolution yield realistic geographical patterns of biodiversity. Individual processes shaping geographical patterns of biodiversity are increasingly understood, but their complex interactions on broad spatial and temporal scales remain beyond the reach of analytical models and traditional experiments. To meet this challenge, we built a spatially explicit, mechanistic simulation model implementing adaptation, range shifts, fragmentation, speciation, dispersal, competition, and extinction, driven by modeled climates of the past 800,000 years in South America. Experimental topographic smoothing confirmed the impact of climate heterogeneity on diversification. The simulations identified regions and episodes of speciation (cradles), persistence (museums), and extinction (graves). Although the simulations had no target pattern and were not parameterized with empirical data, emerging richness maps closely resembled contemporary maps for major taxa, confirming powerful roles for evolution and diversification driven by topography and climate.

It is thought that species abundance is correlated with environmental suitability and that environmental variables, scale, and type of model fitting can confound this relationship. We performed a meta-analysis to 1) test whether species abundance is positively correlated with environmental suitability derived from correlative ecological niche models (ENM), 2) test whether studies encompassing large areas within a species range (> 50%) exhibited higher AS correlations than studies encompassing small areas within a species range (< 50%), 3) assess which modelling method provided higher AS correlation, and 4) compare strength of the AS relationship between studies using only climatic variables and those that used both climatic and other environmental variables to derive suitability. We used correlation coefficients to measure the relationship between abundance and environmental suitability derived from ENM. Each correlation coefficient was considered an effect size in a random-effects multivariate meta-analysis. In all cases we found a significantly positive relationship between abundance and suitability. This relationship was consistent regardless of scale of study, ENM method, or set of variables used to derive suitability. There was no difference in strength of correlation between studies focusing on large or small areas within a species’ range or among ENM methods. Studies using other variables in combination with climate exhibited higher AS correlations than studies using only climatic variables. We conclude that occurrence data can be a reasonable proxy for abundance, especially for vertebrates, and the use of local variables increases the strength of the AS relationship. Use of ENMs can significantly decrease survey costs and allow the study of large-scale abundance patterns using less information. Including only climatic variables in ENM may confound the relationship between abundance and suitability when compared to studies including variables taken locally. However, modelers and conservationists must be aware that high environmental suitability does not always indicate high abundance.

Documenting and exploring the patterns of diversity of life on Earth has always been a central theme in biology. Species richness despite being the most commonly used measure of diversity in macroecological studies suffers from not considering the evolutionary and ecological differences among species. Phylogenetic diversity (PD) and functional diversity (FD) have been proposed as alternative measures to overcome this limitation. Although species richness, PD and FD are closely related, their relationships have never been investigated on a global scale. Comparing PD and FD with species richness corroborated the general assumptions of surrogacy of the different diversity measures. However, the analysis of the residual variance suggested that the mismatches between the diversity measures are influenced by environmental conditions. PD increased relative to species richness with increasing mean annual temperature, whereas FD decreased with decreasing seasonality relative to PD. We also show that the tropical areas are characterized by a FD deficit, a phenomenon, that suggests that in tropical areas more species can be packed into the ecological space. We discuss potential mechanisms that could have resulted in the gradient of spatial mismatch observed in the different biodiversity measures and draw parallels to local scale studies. We conclude that the use of multiple diversity measures on a global scale can help to elucidate the relative importance of historical and ecological processes shaping the present gradients in mammalian diversity.

Aim The fossil record has led to a historical explanation for forest diversity gradients within the cool parts of the Northern Hemisphere, founded on a limited ability of woody angiosperm clades to adapt to mid-Tertiary cooling. We tested four predictions of how this should be manifested in the phylogenetic structure of 91,340 communities: (1) forests to the north should comprise species from younger clades (families) than forests to the south; (2) average cold tolerance at a local site should be associated with the mean family age (MFA) of species; (3) minimum temperature should account for MFA better than alternative environmental variables; and (4) traits associated with survival in cold climates should evolve under a niche conservatism constraint. Location The contiguous United States. Methods We extracted angiosperms from the US Forest Service's Forest Inventory and Analysis database. MFA was calculated by assigning age of the family to which each species belongs and averaging across the species in each community. We developed a phylogeny to identify phylogenetic signal in five traits: realized cold tolerance, seed size, seed dispersal mode, leaf phenology and height. Phylogenetic signal representation curves and phylogenetic generalized least squares were used to compare patterns of trait evolution against Brownian motion. Eleven predictors structured at broad or local scales were generated to explore relationships between environment and MFA using random forest and general linear models. Results Consistent with predictions, (1) southern communities comprise angiosperm species from older families than northern communities, (2) cold tolerance is the trait most strongly associated with local MFA, (3) minimum temperature in the coldest month is the environmental variable that best describes MFA, broad-scale variables being much stronger correlates than local-scale variables, and (4) the phylogenetic structures of cold tolerance and at least one other trait associated with survivorship in cold climates indicate niche conservatism. Main conclusions Tropical niche conservatism in the face of long-term climate change, probably initiated in the Late Cretaceous associated with the rise of the Rocky Mountains, is a strong driver of the phylogenetic structure of the angiosperm component of forest communities across the USA. However, local deterministic and/or stochastic processes account for perhaps a quarter of the variation in the MFA of local communities.

Ecologists and biogeographers usually rely on a single phylogenetic tree to study evolutionary processes that affect macroecological patterns. This approach ignores the fact that each phylogenetic tree is a hypothesis about the evolutionary history of a clade, and cannot be directly observed in nature. Also, trees often leave out many extant species, or include missing species as polytomies because of a lack of information on the relationship among taxa. Still, researchers usually do not quantify the effects of phylogenetic uncertainty in ecological analyses. We propose here a novel analytical strategy to maximize the use of incomplete phylogenetic information, while simultaneously accounting for several sources of phylogenetic uncertainty that may distort statistical inferences about evolutionary processes. We illustrate the approach using a clade-wide analysis of the hummingbirds, evaluating how different sources of uncertainty affect several phylogenetic comparative analyses of trait evolution and biogeographic patterns. Although no statistical approximation can fully substitute for a complete and robust phylogeny, the method we describe and illustrate enables researchers to broaden the number of clades for which studies informed by evolutionary relationships are possible, while allowing the estimation and control of statistical error that arises from phylogenetic uncertainty. Software tools to carry out the necessary computations are offered.

Forecasts of species range shifts under climate change are fraught with uncertainties and ensemble forecasting may provide a framework to deal with such uncertainties. Here, a novel approach to partition the variance among modeled attributes, such as richness or turnover, and map sources of uncertainty in ensembles of forecasts is presented. We model the distributions of 3837 New World birds and project them into 2080. We then quantify and map the relative contribution of different sources of uncertainty from alternative methods for niche modeling, general circulation models (AOGCM), and emission scenarios. The greatest source of uncertainty in forecasts of species range shifts arises from using alternative methods for niche modeling, followed by AOGCM, and their interaction. Our results concur with previous studies that discovered that projections from alternative models can be extremely varied, but we provide a new analytical framework to examine uncertainties in models by quantifying their importance and mapping their patterns.

AIM: Under the Hutchinsonian concept of the realized niche, biotic interactions and dispersal limitation may prevent species from fully occupying areas that they could tolerate physiologically. This can hamper the translation of physiological limits into climatically defined range limits and distorts inferences of evolutionary changes of the adaptive limits (i.e. niche conservatism). In contrast, heritable physiological limits should conform more closely to the position of the niche in the climatic hyperspace. Here, we hypothesize that a measure of niche position in the climatic hyperspace is more reliable than niche boundaries to capture the variability and evolutionary pattern of physiological tolerance. LOCATION: Neotropics and Palaeartic. METHODS: We used phylogenetic and non‐phylogenetic regressions to test the relationships between physiological requirements and macroecological niche features (i.e. based on known species distributions) among anurans. We use larval critical thermal maximum (CTₘₐₓ) as a measure of physiological response and maximum temperature (Tₘₐₓ), temperature variability (Tᵥₐᵣ) and the position and breadth of niche in climatic hyperspace as measures of the realized niche in geographical space. We also compare evolutionary rates among these parameters using the phylogenetic signal representation curve. RESULTS: CTₘₐₓ is better correlated with niche position (r² = 0.414) than with Tᵥₐᵣ, and CTₘₐₓ is unrelated to either Tₘₐₓ or niche breadth. CTₘₐₓ and macroecological niche position also show similar and rapid evolutionary rates, i.e. faster than Brownian motion, whereas Tₘₐₓ and Tᵥₐᵣ evolve more slowly and niche breadth evolves at random. MAIN CONCLUSIONS: The transferability between thermal tolerance and realized climatic niche limits is weak. Only macroecological niche position in the multivariate climatic hyperspace correlates with physiological tolerance. It thus appears to be more suitable for describing the variability and evolutionary pattern of the species' adaptive limits. We link these results to ‘niche dimensionality’, in that multiple interacting factors outweigh single factors in demarcating the species' realized climatic niche, thereby determining the conserved upper thermal limits of the species.

Current macroecological research places great emphasis on patterns of species richness (alpha diversity) and the underlying ecological and evolutionary processes involved in their origin and maintenance. However, few studies dealing with continental scales have addressed dissimilarities in species composition among areas (beta diversity). Using data for the occurrence of 3836 bird and 1641 mammal species in 4220 cells covering the New World, we assessed whether broad-scale macroecological patterns in beta diversity are related to dissimilarities in environmental variables and biotic units. We employed spatial regression and tree regression to model beta diversity. Difference in altitude was the best predictor of beta diversity. Accordingly, the highest beta diversity values were found in mountainous areas, particularly in the Andes, Central America and western North America. Explanatory variables related to transitions between biotic units (biome, ecoregion) were relatively unimportant. Areas that differ in altitude from their surroundings harbor different sets of species, and this may reflect either species adaptation to particular environmental conditions by range shifts, or species divergence by vicariance, or both.

More than two million species have been described so far, but our knowledge on most taxa remains scarce or inexistent, and the available biodiversity data is often taxonomically, phylogenetically and spatially biased. Unevenness in research effort across species or regions can interact with data biases and compromise our ability to properly study and conserve biodiversity. Herein, we assess the influence of biological, conservation, geographic and socioeconomic correlates of reptile research effort globally and across six biogeographic realms. We combine bibliometric data from the Scopus database with trait‐based approaches and provide research effort information for 10 531 reptile species, modelling it as a function of 10 putative correlates of species‐level variation in research effort through negative binomial generalised mixed effect models. We show that reptile research effort is highly skewed toward certain taxa and regions, such as turtles, crocodiles, tuatara, viperids, pythons and some anguimorph lizards, as well as for temperate compared to tropical regions. Our findings indicate that greater research attention is directed towards large‐sized and early described reptile species, particularly those whose geographic range overlap with biodiversity institutions. Although we demonstrate that biological and socioeconomic factors more strongly affect reptile research effort variation, geography and conservation‐related factors also matter. Global patterns are mostly consistent, but variation across realms were observed and likely reflects differences in socioeconomic attributes as well as in the amount of species to be studied in each realm. Directing researchers and citizen scientists' attention toward understudied taxa will contribute to alleviate this biased biodiversity knowledge, although the sheer amount of species in tropical regions inevitably makes it a long‐term solution. Performing comparative studies across species with similar levels of research attention could represent a more immediate and feasible alternative.

One of the most popular approaches for investigating the roles of niche and neutral processes driving metacommunity patterns consists of partitioning variation in species data into environmental and spatial components. The logic is that the distance decay of similarity in communities is expected under neutral models. However, because environmental variation is often spatially structured, the decay could also be attributed to environmental factors that are missing from the analysis. Here, we use a spatial autocorrelation analysis protocol, previously developed to detect isolation-by-distance in alíele frequencies, to evaluate patterns of species abundances under neutral dynamics. We show that this protocol can be linked with variation partitioning analyses. Moreover, in an attempt to test the neutral model, we derive three predictions to be applied both to original species abundances and to abundances predicted by a pure spatial model species abundances will be uncorrelated; Moran's I correlograms will reveal similar short-distance autocorrelation patterns; an increasing degree of non-neutrality will tend to generate patterns of correlation among abundances within groups of species with similar correlograms (i.e. within species with neutral and non-neutral dynamics). We illustrate our protocol by analyzing spatial patterns in abundance of 28 terrestrially breeding anuran species from Central Amazonia. We recommend that researchers should investigate spatial autocorrelation patterns of abundances predicted by pure spatial models to identify similar patterns of spatial autocorrelation at short distances and lack of correlation between species abundances. Therefore, the hypothesis that spatial patterns in abundances are primarily due to pure neutral dynamics (rather than to missing spatiallystructured environmental factors) can be confirmed after taking environmental variables into account.