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AbstractDifferences among hummingbird species in bill length and shape have rightly been viewed as adaptive in relation to the morphology of the flowers they visit for nectar. In this study we examine functional variation in a behaviorally related but neglected feature: hummingbird feet. We gathered records of hummingbirds clinging by their feet to feed legitimately as pollinators or illegitimately as nectar robbers-"unorthodox" feeding behaviors. We measured key features of bills and feet for 220 species of hummingbirds and compared the 66 known "clinger" species (covering virtually the entire scope of hummingbird body size) with the 144 presumed "non-clinger" species. Once the effects of phylogenetic signal, body size, and elevation above sea level are accounted for statistically, hummingbirds display a surprising but functionally interpretable negative correlation. Clingers with short bills and long hallux (hind-toe) claws have evolved-independently-more than 20 times and in every major clade. Their biomechanically enhanced feet allow them to save energy by clinging to feed legitimately on short-corolla flowers and by stealing nectar from long-corolla flowers. In contrast, long-billed species have shorter hallux claws, as plant species with long-corolla flowers enforce hovering to feed, simply by the way they present their flowers.

Climate's effect on global biodiversity is typically viewed through the lens of temperature, humidity and resulting ecosystem productivity 1-6 . However, it is not known whether biodiversity depends solely on these climate conditions, or whether the size and fragmentation of these climates are also crucial. Here we shift the common perspective in global biodiversity studies, transitioning from geographic space to a climate-defined multidimensional space. Our findings suggest that larger and more isolated climate conditions tend to harbour higher diversity and species turnover among terrestrial tetrapods, encompassing more than 30,000 species. By considering both the characteristics of climate itself and its geographic attributes, we can explain almost 90% of the variation in global species richness. Half of the explanatory power (45%) may be attributed either to climate itself or to the geography of climate, suggesting a nuanced interplay between them. Our work evolves the conventional idea that larger climate regions, such as the tropics, host more species primarily because of their size 7,8 . Instead, we underscore the integral roles of both the geographic extent and degree of isolation of climates. This refined understanding presents a more intricate picture of biodiversity distribution, which can guide our approach to biodiversity conservation in an ever-changing world., (© 2023. The Author(s).)

Landscape dynamics are widely thought to govern the tempo and mode of continental radiations, yet the effects of river network rearrangements on dispersal and lineage diversification remain poorly understood. We integrated an unprecedented occurrence dataset of 4,967 species with a newly compiled, time-calibrated phylogeny of South American freshwater fishes-the most species-rich continental vertebrate fauna on Earth-to track the evolutionary processes associated with hydrogeographic events over 100 Ma. Net lineage diversification was heterogeneous through time, across space, and among clades. Five abrupt shifts in net diversification rates occurred during the Paleogene and Miocene (between 30 and 7 Ma) in association with major landscape evolution events. Net diversification accelerated from the Miocene to the Recent (c. 20 to 0 Ma), with Western Amazonia having the highest rates of in situ diversification, which led to it being an important source of species dispersing to other regions. All regional biotic interchanges were associated with documented hydrogeographic events and the formation of biogeographic corridors, including the Early Miocene (c. 23 to 16 Ma) uplift of the Serra do Mar and Serra da Mantiqueira and the Late Miocene (c. 10 Ma) uplift of the Northern Andes and associated formation of the modern transcontinental Amazon River. The combination of high diversification rates and extensive biotic interchange associated with Western Amazonia yielded its extraordinary contemporary richness and phylogenetic endemism. Our results support the hypothesis that landscape dynamics, which shaped the history of drainage basin connections, strongly affected the assembly and diversification of basin-wide fish faunas.

Insular biodiversity is expected to be regulated differently than continental biota, but their determinants remain to be quantified at a global scale. We evaluated the importance of physical, environmental and historical factors on mammal richness and endemism across 5592 islands worldwide. We fitted generalized linear and mixed models to accommodate variation among biogeographic realms and performed analyses separately for bats and non-volants. Richness on islands ranged from one to 234 species, with up to 177 single island endemics. Diversity patterns were most consistently influenced by the islands' physical characteristics. Area positively affected mammal diversity, in particular the number of non-volant endemics. Island isolation, both current and past, was associated with lower richness but greater endemism. Flight capacity modified the relative importance of past versus current isolation, with bats responding more strongly to current and non-volant mammals to past isolation. Biodiversity relationships with environmental factors were idiosyncratic, with a tendency for greater effects sizes with endemism than richness. The historical climatic change was positively associated with endemism. In line with theory, we found that area and isolation were among the strongest drivers of mammalian biodiversity. Our results support the importance of past conditions on current patterns, particularly of non-volant species.

Aim: We aimed to dissect the spatial variation of the direct and indirect effects of climate and productivity on global species richness of terrestrial tetrapods., Location: Global., Time Period: Present., Major Taxa Studied: Terrestrial tetrapods., Methods: We used a geographically weighted path analysis to estimate and map the direct and indirect effects of temperature, precipitation and primary productivity on species richness of terrestrial tetrapods across the globe., Results: We found that all relationships shift in magnitude, and even in direction, among taxonomic groups, geographical regions and connecting paths. Direct effects of temperature and precipitation are generally stronger than both indirect effects mediated by productivity and direct effects of productivity., Main Conclusions: Richness gradients seem to be driven primarily by effects of climate on organismal physiological limits and metabolic rates rather than by the amount of productive energy. Reptiles have the most distinct relationships across tetrapods, with a clear latitudinal pattern in the importance of temperature versus water., (© 2021 The Authors. Global Ecology and Biogeography published by John Wiley & Sons Ltd.)

Understanding the origins of biodiversity has been an aspiration since the days of early naturalists. The immense complexity of ecological, evolutionary, and spatial processes, however, has made this goal elusive to this day. Computer models serve progress in many scientific fields, but in the fields of macroecology and macroevolution, eco-evolutionary models are comparatively less developed. We present a general, spatially explicit, eco-evolutionary engine with a modular implementation that enables the modeling of multiple macroecological and macroevolutionary processes and feedbacks across representative spatiotemporally dynamic landscapes. Modeled processes can include species' abiotic tolerances, biotic interactions, dispersal, speciation, and evolution of ecological traits. Commonly observed biodiversity patterns, such as α, β, and γ diversity, species ranges, ecological traits, and phylogenies, emerge as simulations proceed. As an illustration, we examine alternative hypotheses expected to have shaped the latitudinal diversity gradient (LDG) during the Earth's Cenozoic era. Our exploratory simulations simultaneously produce multiple realistic biodiversity patterns, such as the LDG, current species richness, and range size frequencies, as well as phylogenetic metrics. The model engine is open source and available as an R package, enabling future exploration of various landscapes and biological processes, while outputs can be linked with a variety of empirical biodiversity patterns. This work represents a key toward a numeric, interdisciplinary, and mechanistic understanding of the physical and biological processes that shape Earth's biodiversity., Competing Interests: The authors have declared that no competing interests exist.

This study uses species distribution modeling and physiological and functional traits to predict the impacts of climate change on native freshwater fish in the Murray-Darling Basin, Australia. We modelled future changes in taxonomic and functional diversity in 2050 and 2080 for two scenarios of carbon emissions, identifying areas of great interest for conservation. Climatic-environmental variables were used to model the range of 23 species of native fish under each scenario. The consensus model, followed by the physiological filter of lethal temperature was retained for interpretation. Our study predicts a severe negative impact of climate change on both taxonomic and functional components of ichthyofauna of the Murray-Darling Basin. There was a predicted marked contraction of species ranges under both scenarios. The predictions showed loss of climatically suitable areas, species and functional characters. There was a decrease in areas with high values of functional richness, dispersion and uniqueness. Some traits are predicted to be extirpated, especially in the most pessimistic scenario. The climatic refuges for fish fauna are predicted to be in the southern portion of the basin, in the upper Murray catchment. Incorporating future predictions about the distribution of ichthyofauna in conservation management planning will enhance resilience to climate change., Competing Interests: The authors have declared that no competing interests exist.

According to the island rule, small-bodied vertebrates will tend to evolve larger body size on islands, whereas the opposite happens to large-bodied species. This controversial pattern has been studied at the macroecological and biogeographical scales, but new developments in quantitative evolutionary genetics now allow studying the island rule from a mechanistic perspective. Here, we develop a simulation approach based on an individual-based model to model body size change on islands as a progressive adaptation to a moving optimum, determined by density-dependent population dynamics. We applied the model to evaluate body size differentiation in the pigmy extinct hominin Homo floresiensis, showing that dwarfing may have occurred in only about 360 generations (95% CI ranging from 150 to 675 generations). This result agrees with reports suggesting rapid dwarfing of large mammals on islands, as well as with the recent discovery that small-sized hominins lived in Flores as early as 700 kyr ago. Our simulations illustrate the power of analysing ecological and evolutionary patterns from an explicit quantitative genetics perspective.

Ecological Niche Models (ENMs) have different performances in predicting potential geographic distributions. Here we meta-analyzed the likely effects of climate change on the potential geographic distribution of 1,205 bird species from the Neotropical region, modeled using eight ENMs and three Atmosphere-Ocean General Circulation Models (AOGCM). We considered the variability in ENMs performance to estimate a weighted mean difference between potential geographic distributions for baseline and future climates. On average, potential future ranges were projected to be from 25.7% to 44.5% smaller than current potential ranges across species. However, we found that 0.2% to 18.3% of the total variance in range shifts occurred "within species" (i.e., owing to the use of different modeling techniques and climate models) and 81.7% to 99.8% remained between species (i.e., it could be explained by ecological correlates). Using meta-analytical techniques akin to regression, we also showed that potential range shifts are barely predicted by bird biological traits. We demonstrated that one can combine and reduce species-specific effects with high uncertainty in ENMs and also explore potential causes of climate change effect on species using meta-analytical tools. We also highlight that the search for powerful correlates of climate change-induced range shifts can be a promising line of investigation., Competing Interests: None declared., (© 2019 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Although many hypotheses have been proposed to explain why humans speak so many languages and why languages are unevenly distributed across the globe, the factors that shape geographical patterns of cultural and linguistic diversity remain poorly understood. Prior research has tended to focus on identifying universal predictors of language diversity, without accounting for how local factors and multiple predictors interact. Here, we use a unique combination of path analysis, mechanistic simulation modelling, and geographically weighted regression to investigate the broadly described, but poorly understood, spatial pattern of language diversity in North America. We show that the ecological drivers of language diversity are not universal or entirely direct. The strongest associations imply a role for previously developed hypothesized drivers such as population density, resource diversity, and carrying capacity with group size limits. The predictive power of this web of factors varies over space from regions where our model predicts approximately 86% of the variation in diversity, to areas where less than 40% is explained.

The latitudinal diversity gradient (LDG) is one of the most widely studied patterns in ecology, yet no consensus has been reached about its underlying causes. We argue that the reasons for this are the verbal nature of existing hypotheses, the failure to mechanistically link interacting ecological and evolutionary processes to the LDG, and the fact that empirical patterns are often consistent with multiple explanations. To address this issue, we synthesize current LDG hypotheses, uncovering their eco-evolutionary mechanisms, hidden assumptions, and commonalities. Furthermore, we propose mechanistic eco-evolutionary modeling and an inferential approach that makes use of geographic, phylogenetic, and trait-based patterns to assess the relative importance of different processes for generating the LDG., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Knowledge on the relationships between species functional traits and environmental filters is key to understanding the mechanisms underlying the current patterns of biodiversity loss from a multi-taxa perspective. The aim of this study was to identify the main environmental factors driving the functional structure of a terrestrial vertebrate community (mammals, breeding birds, reptiles and amphibians) in a temperate mountain system (the Cantabrian Mountains; NW Spain). Based on the Spanish Inventory of Terrestrial Vertebrate Species, we selected three functional traits (feeding guild, habitat use type and daily activity) and defined, for each trait, a set of functional groups considering vertebrate species with common functional characteristics. The community functional structure was evaluated by means of two functional indexes indicative of functional redundancy (species richness within each functional group) and functional diversity. Ordinary least squares regression and conditional autoregressive models were applied to determine the response of community functional structure to environmental filters (climate, topography, land cover, physiological state of vegetation, landscape heterogeneity and human influence). The results revealed that both functional redundancy and diversity of terrestrial vertebrates were non-randomly distributed across space; rather, they were driven by environmental filters. Climate, topography and human influence were the best predictors of community functional structure. The influence of land cover, physiological state of vegetation and landscape heterogeneity varied among functional groups. The results of this study are useful to identify the general assembly rules of species functional traits and to illustrate the importance of environmental filters in determining functional structure of terrestrial vertebrate communities in mountain systems., Competing Interests: The authors have declared that no competing interests exist.

Expanding populations may loss genetic diversity because sequential founder events throughout a wave of demographic expansion may cause "allele surfing", as the alleles of founder individuals may propagate rapidly through space. The spatial components of allele surfing have been studied by geneticists, but have never been investigate on dynamic and shifting habitats. Here we used an individual-based-model (IBM) to study how interactions between different habitat restoration scenarios and biological characteristics (dispersal capacity) affect the spatial patterns of the genetic structure of a population during demographic expansion. We found that both habitat dynamics and dispersal capacity, as well as their interaction, were the drivers of emergent pattern of genetic diversity and allele surfing. Specifically, allele surfing is more common when a species with low dispersal capacity colonizes a large geographic area with slow restoration (low carrying capacity). Despite this, we showed that allele surfing can be reduced, or even avoided, by dispersal management through suitable habitat restoration. Thus, investigating how colonization generates a spatial variation in genetic diversity, and which parameters control the emergent genetic pattern, are essential steps to planning assisted gene flow, which is fundamental for an effective planning of habitat restoration.

A reliable description of any spatial pattern in species richness requires accurate knowledge about species geographical distribution. However, sampling bias may generate artefactual absences within species range and compromise our capacity to describe biodiversity patterns. Here, we analysed the spatial distribution of 35,000 marine species (varying from copepods to sharks) to identify missing occurrences (gaps) across their latitudinal range. We find a latitudinal gradient of species absence peaking near the equator, a pattern observed in both shallow and deep waters. The tropical gap in species distribution seems a consequence of reduced sampling effort at low latitudes. Overall, our results suggest that spatial gaps in species distribution are the main cause of the bimodal pattern of marine diversity. Therefore, only increasing sampling effort at low latitudes will reveal if the absence of species in the tropics, and the consequent dip in species richness, are artefacts of sampling bias or a natural phenomenon.

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., (Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

A contemporary goal in ecology is to determine the ecological and evolutionary processes that generate recurring structural patterns in mutualistic networks. One of the great challenges is testing the capacity of neutral processes to replicate observed patterns in ecological networks, since the original formulation of the neutral theory lacks trophic interactions. Here, we develop a stochastic-simulation neutral model adding trophic interactions to the neutral theory of biodiversity. Without invoking ecological differences among individuals of different species, and assuming that ecological interactions emerge randomly, we demonstrate that a spatially explicit multitrophic neutral model is able to capture the recurrent structural patterns of mutualistic networks (i.e., degree distribution, connectance, nestedness, and phylogenetic signal of species interactions). Nonrandom species distribution, caused by probabilistic events of migration and speciation, create nonrandom network patterns. These findings have broad implications for the interpretation of niche-based processes as drivers of ecological networks, as well as for the integration of network structures with demographic stochasticity.

Climate change and species invasions interact in nature, disrupting biological communities. Based on this knowledge, we simultaneously assessed the effects of climate change on the native distribution of the Amazonian fish Colossoma macropomum as well as on its invasiveness across river basins of South America, using ecological niche modeling. We used six niche models within the ensemble forecast context to predict the geographical distribution of C. macropomum for the present time, 2050 and 2080. Given that this species has been continuously introduced into non-native South American basins by fish farming activities, we added the locations of C. macropomum farms into the modeling process to obtain a more realistic scenario of its invasive potential. Based on modelling outputs we mapped climate refuge areas at different times. Our results showed that a plenty of climatically suitable areas for the occurrence of C. macropomum occurrence are located outside the original basins at the present time and that its invasive potential is greatly amplified by fish farms. Simulations of future geographic ranges revealed drastic range contraction in the native region, implying concerns not only with respect to the species conservation but also from a socio-economic perspective since the species is a cornerstone of artisanal and commercial fisheries in the Amazon. Although the invasive potential is projected to decrease in the face of climate change, climate refugia will concentrate in Paraná River, Southeast Atlantic and East Atlantic basins, putting intense, negative pressures on the native fish fauna these regions. Our findings show that short and long-term management actions are required for: i) the conservation of natural stocks of C. macropomum in the Amazon, and ii) protecting native fish fauna in the climate refuges of the invaded regions.

Human disturbance drives the decline of many species, both directly and indirectly. Nonetheless, some species do particularly well around humans. One mechanism that may explain coexistence is the degree to which a species tolerates human disturbance. Here we provide a comprehensive meta-analysis of birds, mammals and lizards to investigate species tolerance of human disturbance and explore the drivers of this tolerance in birds. We find that, overall, disturbed populations of the three major taxa are more tolerant of human disturbance than less disturbed populations. The best predictors of the direction and magnitude of bird tolerance of human disturbance are the type of disturbed area (urbanized birds are more tolerant than rural or suburban populations) and body mass (large birds are more tolerant than small birds). By identifying specific features associated with tolerance, these results guide evidence-based conservation strategies to predict and manage the impacts of increasing human disturbance on birds.

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., (© 2015 The Author(s).)

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.

The comparison of genetic divergence or genetic distances, estimated by pairwise FST and related statistics, with geographical distances by Mantel test is one of the most popular approaches to evaluate spatial processes driving population structure. There have been, however, recent criticisms and discussions on the statistical performance of the Mantel test. Simultaneously, alternative frameworks for data analyses are being proposed. Here, we review the Mantel test and its variations, including Mantel correlograms and partial correlations and regressions. For illustrative purposes, we studied spatial genetic divergence among 25 populations of Dipteryx alata ("Baru"), a tree species endemic to the Cerrado, the Brazilian savannas, based on 8 microsatellite loci. We also applied alternative methods to analyze spatial patterns in this dataset, especially a multivariate generalization of Spatial Eigenfunction Analysis based on redundancy analysis. The different approaches resulted in similar estimates of the magnitude of spatial structure in the genetic data. Furthermore, the results were expected based on previous knowledge of the ecological and evolutionary processes underlying genetic variation in this species. Our review shows that a careful application and interpretation of Mantel tests, especially Mantel correlograms, can overcome some potential statistical problems and provide a simple and useful tool for multivariate analysis of spatial patterns of genetic divergence.

Several methods of spatial analyses have been proposed to infer the relative importance of evolutionary processes on genetic population structure. Here we show how a new eigenfunction spatial analysis can be used to model spatial patterns in genetic data. Considering a sample of n local populations, the method starts by modeling the response variable (allele frequencies or phenotypic variation) against the eigenvectors sequentially extracted from a geographic distance matrix (n × n). The relationship between the coefficient of determination (R(2)) of the models and the cumulative eigenvalues, which we named the spatial signal-representation (SSR) curve, can be more efficient than Moran's I correlograms in describing different patterns. The SSR curve was also applied to simulated data (under distinct scenarios of population differentiation) and to analyze spatial patterns in alleles from microsatellite data for 25 local populations of Dipteryx alata, a tree species endemic to the Brazilian Cerrado. The SSR curves are consistent with previous phylogeographical patterns of the species, revealing combined effects of isolation-by-distance and range expansion. Our analyses demonstrate that the SSR curve is a useful exploratory tool for describing spatial patterns of genetic variability and for selecting spatial eigenvectors for models aiming to explain spatial responses to environmental variables and landscape features.

Background: Phylogenetic comparative analyses usually rely on a single consensus phylogenetic tree in order to study evolutionary processes. However, most phylogenetic trees are incomplete with regard to species sampling, which may critically compromise analyses. Some approaches have been proposed to integrate non-molecular phylogenetic information into incomplete molecular phylogenies. An expanded tree approach consists of adding missing species to random locations within their clade. The information contained in the topology of the resulting expanded trees can be captured by the pairwise phylogenetic distance between species and stored in a matrix for further statistical analysis. Thus, the random expansion and processing of multiple phylogenetic trees can be used to estimate the phylogenetic uncertainty through a simulation procedure. Because of the computational burden required, unless this procedure is efficiently implemented, the analyses are of limited applicability., Results: In this paper, we present efficient algorithms and implementations for randomly expanding and processing phylogenetic trees so that simulations involved in comparative phylogenetic analysis with uncertainty can be conducted in a reasonable time. We propose algorithms for both randomly expanding trees and calculating distance matrices. We made available the source code, which was written in the C++ language. The code may be used as a standalone program or as a shared object in the R system. The software can also be used as a web service through the link: http://purl.oclc.org/NET/sunplin/., Conclusion: We compare our implementations to similar solutions and show that significant performance gains can be obtained. Our results open up the possibility of accounting for phylogenetic uncertainty in evolutionary and ecological analyses of large datasets.

Differential coexistence among species underlies geographical patterns of biodiversity. Understanding such patterns has relied either on ecological or historical approaches applied separately. Recently, macroecology and community phylogenetics have tried to integrate both ecological and historical approaches. However, macroecology is mostly non-phylogenetic, whereas community phylogenetics is largely focused on local scales. Here, we propose a conceptual framework to link macroecology and community phylogenetics by exploring the evolutionary context of large-scale species coexistence, introducing the phylogenetic field concept. This is defined as the phylogenetic structure of species co-occurrence within a focal species' geographical range. We developed concepts and methods for analysing phylogenetic fields and applied them to study coexistence patterns of the bat family Phyllostomidae. Our analyses showed that phyllostomid bats coexist mostly with closely related species, revealing a north-south gradient from overdispersed to clustered phylogenetic fields. Patterns at different phylogenetic levels (i.e. all species versus close relatives only) presented the same gradient. Results support the tropical niche conservatism hypothesis, potentially mediated by higher speciation rates in the region of origin coupled with shared environmental preferences among species. The phylogenetic field approach enables species-based community phylogenetics, instead of those that are site-based, allowing the description of historical processes at more appropriate macroecological and biogeographic scales.

We investigated here the demographical history of Tabebuia impetiginosa (Bignoniaceae) to understand the dynamics of the disjunct geographical distribution of South American seasonally dry forests (SDFs), based on coupling an ensemble approach encompassing hindcasting species distribution modelling and statistical phylogeographical analysis. We sampled 17 populations (280 individuals) in central Brazil and analysed the polymorphisms at chloroplast (trnS-trnG, psbA-trnH, and ycf6-trnC intergenic spacers) and nuclear (ITS nrDNA) genomes. Phylogenetic analyses based on median-joining network showed no haplotype sharing among population but strong evidence of incomplete lineage sorting. Coalescent analyses showed historical constant populations size, negligible gene flow among populations, and an ancient time to most recent common ancestor dated from ~4.7 ± 1.1 Myr BP. Most divergences dated from the Lower Pleistocene, and no signal of important population size reduction was found in coalescent tree and tests of demographical expansion. Demographical scenarios were built based on past geographical range dynamic models, using two a priori biogeographical hypotheses ('Pleistocene Arc' and 'Amazonian SDF expansion') and on two additional hypotheses suggested by the palaeodistribution modelling built with several algorithms for distribution modelling and palaeoclimatic data. The simulation of these demographical scenarios showed that the pattern of diversity found so far for T. impetiginosa is in consonance with a palaeodistribution expansion during the last glacial maximum (LGM, 21 kyr BP), strongly suggesting that the current disjunct distribution of T. impetiginosa in SDFs may represent a climatic relict of a once more wide distribution., (© 2012 Blackwell Publishing Ltd.)

Several metrics have been developed for estimating phylogenetic signal in comparative data. These may be important both in guiding future studies on correlated evolution and for inferring broad-scale evolutionary and ecological processes (e.g., phylogenetic niche conservatism). Notwithstanding, the validity of some of these metrics is under debate, especially after the development of more sophisticated model-based approaches that estimate departure from particular evolutionary models (i.e., Brownian motion). Here, two of these model-based metrics (Blomberg's K-statistics and Pagel's λ) are compared with three statistical approaches [Moran's I autocorrelation coefficient, coefficients of determination from the autoregressive method (ARM), and phylogenetic eigenvector regression (PVR)]. Based on simulations of a trait evolving under Brownian motion for a phylogeny with 209 species, we showed that all metrics are strongly, although non-linearly, correlated to each other. Our analyses revealed that statistical approaches provide valid results and may be still particularly useful when detailed phylogenies are unavailable or when trait variation among species is difficult to describe by more standard Brownian or O-U evolutionary models.

Many species are expected to suffer strong shifts in their geographic ranges due to climate changes in the next 50 years, with severe consequences for biodiversity patterns and population structure. We used here an ensemble forecast approach for obtaining species' range in which multiple species distribution models and climatic models were combined to model loss of genetic variability in Baru, Dipteryx alata (Fabaceae), an economically important Neotropical tree native to the Cerrado of Brazil. We estimated a series of genetic parameters (number of alleles per locus, expected heterozygosity under Hardy-Weinberg equilibrium and mutation-drift equilibrium) for this species based on eight microsatellite loci. We then recalculated these parameters assuming that local populations in areas of low future environmental suitability will go extinct. All genetic parameters remained approximately constant up to a 50% threshold of climatic suitability in the future; after this critical threshold there is an abrupt reduction in all parameters, although the magnitude of shift is only about 10% of current values, on average. Thus, despite the shifts in geographic range and climatically suitable areas towards southeastern Brazil, our analyses do not predict a strong loss of genetic diversity in D. alata because of the broad tolerance of this species, which ensures large future ranges, contrasting with other Cerrado species that have been analyzed in a similar manner.

A number of metrics have been developed for estimating phylogenetic signal in data and to evaluate correlated evolution, inferring broad-scale evolutionary and ecological processes. Here, we proposed an approach called phylogenetic signal-representation (PSR) curve, built upon phylogenetic eigenvector regression (PVR). In PVR, selected eigenvectors extracted from a phylogenetic distance matrix are used to model interspecific variation. In the PSR curve, sequential PVR models are fitted after successively increasing the number of eigenvectors and plotting their R(2) against the accumulated eigenvalues. We used simulations to show that a linear PSR curve is expected under Brownian motion and that its shape changes under alternative evolutionary models. The PSR area, expressing deviations from Brownian motion, is strongly correlated (r= 0.873; P < 0.01) with Blomberg's K-statistics, so nonlinear PSR curves reveal if traits are evolving at a slower or higher rate than expected by Brownian motion. The PSR area is also correlated with phylogenetic half-life under an Ornstein-Uhlenbeck process, suggesting how both methods describe the shape of the relationship between interspecific variation and time since divergence among species. The PSR curve provides an elegant exploratory method to understand deviations from Brownian motion, in terms of acceleration or deceleration of evolutionary rates occurring at large or small phylogenetic distances., (© 2011 The Author(s). Evolution© 2011 The Society for the Study of Evolution.)

A common assumption in bioclimatic envelope modeling is that species distributions are in equilibrium with contemporary climate. A number of studies have measured departures from equilibrium in species distributions in particular regions, but such investigations were never carried out for a complete lineage across its entire distribution. We measure departures of equilibrium with contemporary climate for the distributions of the world amphibian species. Specifically, we fitted bioclimatic envelopes for 5544 species using three presence-only models. We then measured the proportion of the modeled envelope that is currently occupied by the species, as a metric of equilibrium of species distributions with climate. The assumption was that the greater the difference between modeled bioclimatic envelope and the occupied distribution, the greater the likelihood that species distribution would not be at equilibrium with contemporary climate. On average, amphibians occupied 30% to 57% of their potential distributions. Although patterns differed across regions, there were no significant differences among lineages. Species in the Neotropic, Afrotropics, Indo-Malay, and Palaearctic occupied a smaller proportion of their potential distributions than species in the Nearctic, Madagascar, and Australasia. We acknowledge that our models underestimate non equilibrium, and discuss potential reasons for the observed patterns. From a modeling perspective our results support the view that at global scale bioclimatic envelope models might perform similarly across lineages but differently across regions.

Current climate and Pleistocene climatic changes are both known to be associated with geographical patterns of diversity. We assess their associations with the European Scarabaeinae dung beetles, a group with high dispersal ability and well-known adaptations to warm environments. By assessing spatial stationarity in climate variability since the last glacial maximum (LGM), we find that current scarab richness is related to the location of their limits of thermal tolerance during the LGM. These limits mark a strong change in their current species richness-environment relationships. Furthermore, northern scarab assemblages are nested and composed of a phylogenetically clustered subset of large-range sized generalist species, whereas southern ones are diverse and variable in composition. Our results show that species responses to current climate are limited by the evolution of assemblages that occupied relatively climatically stable areas during the Pleistocene, and by post-glacial dispersal in those that were strongly affected by glaciations., (© 2011 Blackwell Publishing Ltd/CNRS.)

Water and energy have emerged as the best contemporary environmental correlates of broad-scale species richness patterns. A corollary hypothesis of water-energy dynamics theory is that the influence of water decreases and the influence of energy increases with absolute latitude. We report the first use of geographically weighted regression for testing this hypothesis on a continuous species richness gradient that is entirely located within the tropics and subtropics. The dataset was divided into northern and southern hemispheric portions to test whether predictor shifts are more pronounced in the less oceanic northern hemisphere. American palms (Arecaceae, n = 547 spp.), whose species richness and distributions are known to respond strongly to water and energy, were used as a model group. The ability of water and energy to explain palm species richness was quantified locally at different spatial scales and regressed on latitude. Clear latitudinal trends in agreement with water-energy dynamics theory were found, but the results did not differ qualitatively between hemispheres. Strong inherent spatial autocorrelation in local modeling results and collinearity of water and energy variables were identified as important methodological challenges. We overcame these problems by using simultaneous autoregressive models and variation partitioning. Our results show that the ability of water and energy to explain species richness changes not only across large climatic gradients spanning tropical to temperate or arctic zones but also within megathermal climates, at least for strictly tropical taxa such as palms. This finding suggests that the predictor shifts are related to gradual latitudinal changes in ambient energy (related to solar flux input) rather than to abrupt transitions at specific latitudes, such as the occurrence of frost.

Quaternary glacial-interglacial cycles repeatedly forced thermal zones up and down the slopes of mountains, at all latitudes. Although no one doubts that these temperature cycles have left their signature on contemporary patterns of geography and phylogeny, the relative roles of ecology and evolution are not well understood, especially for the tropics. To explore key mechanisms and their interactions in the context of chance events, we constructed a geographical range-based, stochastic simulation model that incorporates speciation, anagenetic evolution, niche conservatism, range shifts and extinctions under late Quaternary temperature cycles along tropical elevational gradients. In the model, elevational patterns of species richness arise from the differential survival of founder lineages, consolidated by speciation and the inheritance of thermal niche characteristics. The model yields a surprisingly rich variety of realistic patterns of phylogeny and biogeography, including close matches to a variety of contemporary elevational richness profiles from an elevational transect in Costa Rica. Mountaintop extinctions during interglacials and lowland extinctions at glacial maxima favour mid-elevation lineages, especially under the constraints of niche conservatism. Asymmetry in temperature (greater duration of glacial than of interglacial episodes) and in lateral area (greater land area at low than at high elevations) have opposing effects on lowland extinctions and the elevational pattern of species richness in the model--and perhaps in nature, as well.

The duality between "niche" and "biotope" proposed by G. Evelyn Hutchinson provides a powerful way to conceptualize and analyze biogeographical distributions in relation to spatial environmental patterns. Both Joseph Grinnell and Charles Elton had attributed niches to environments. Attributing niches, instead, to species, allowed Hutchinson's key innovation: the formal severing of physical place from environment that is expressed by the duality. In biogeography, the physical world (a spatial extension of what Hutchinson called the biotope) is conceived as a map, each point (or cell) of which is characterized by its geographical coordinates and the local values of n environmental attributes at a given time. Exactly the same n environmental attributes define the corresponding niche space, as niche axes, allowing reciprocal projections between the geographic distribution of a species, actual or potential, past or future, and its niche. In biogeographical terms, the realized niche has come to express not only the effects of species interactions (as Hutchinson intended), but also constraints of dispersal limitation and the lack of contemporary environments corresponding to parts of the fundamental niche. Hutchinson's duality has been used to classify and map environments; model potential species distributions under past, present, and future climates; study the distributions of invasive species; discover new species; and simulate increasingly more realistic worlds, leading to spatially explicit, stochastic models that encompass speciation, extinction, range expansion, and evolutionary adaptation to changing environments.

Understanding the causes of spatial variation in species richness is a major research focus of biogeography and macroecology. Gridded environmental data and species richness maps have been used in increasingly sophisticated curve-fitting analyses, but these methods have not brought us much closer to a mechanistic understanding of the patterns. During the past two decades, macroecologists have successfully addressed technical problems posed by spatial autocorrelation, intercorrelation of predictor variables and non-linearity. However, curve-fitting approaches are problematic because most theoretical models in macroecology do not make quantitative predictions, and they do not incorporate interactions among multiple forces. As an alternative, we propose a mechanistic modelling approach. We describe computer simulation models of the stochastic origin, spread, and extinction of species' geographical ranges in an environmentally heterogeneous, gridded domain and describe progress to date regarding their implementation. The output from such a general simulation model (GSM) would, at a minimum, consist of the simulated distribution of species ranges on a map, yielding the predicted number of species in each grid cell of the domain. In contrast to curve-fitting analysis, simulation modelling explicitly incorporates the processes believed to be affecting the geographical ranges of species and generates a number of quantitative predictions that can be compared to empirical patterns. We describe three of the 'control knobs' for a GSM that specify simple rules for dispersal, evolutionary origins and environmental gradients. Binary combinations of different knob settings correspond to eight distinct simulation models, five of which are already represented in the literature of macroecology. The output from such a GSM will include the predicted species richness per grid cell, the range size frequency distribution, the simulated phylogeny and simulated geographical ranges of the component species, all of which can be compared to empirical patterns. Challenges to the development of the GSM include the measurement of goodness of fit (GOF) between observed data and model predictions, as well as the estimation, optimization and interpretation of the model parameters. The simulation approach offers new insights into the origin and maintenance of species richness patterns, and may provide a common framework for investigating the effects of contemporary climate, evolutionary history and geometric constraints on global biodiversity gradients. With further development, the GSM has the potential to provide a conceptual bridge between macroecology and historical biogeography.

Most evolutionary processes occur in a spatial context and several spatial analysis techniques have been employed in an exploratory context. However, the existence of autocorrelation can also perturb significance tests when data is analyzed using standard correlation and regression techniques on modeling genetic data as a function of explanatory variables. In this case, more complex models incorporating the effects of autocorrelation must be used. Here we review those models and compared their relative performances in a simple simulation, in which spatial patterns in allele frequencies were generated by a balance between random variation within populations and spatially-structured gene flow. Notwithstanding the somewhat idiosyncratic behavior of the techniques evaluated, it is clear that spatial autocorrelation affects Type I errors and that standard linear regression does not provide minimum variance estimators. Due to its flexibility, we stress that principal coordinate of neighbor matrices (PCNM) and related eigenvector mapping techniques seem to be the best approaches to spatial regression. In general, we hope that our review of commonly used spatial regression techniques in biology and ecology may aid population geneticists towards providing better explanations for population structures dealing with more complex regression problems throughout geographic space.

Spatial autocorrelation is the lack of independence between pairs of observations at given distances within a geographical space, a phenomenon commonly found in ecological data. Taking into account spatial autocorrelation when evaluating problems in geographical ecology, including gradients in species richness, is important to describe both the spatial structure in data and to correct the bias in Type I errors of standard statistical analyses. However, to effectively solve these problems it is necessary to establish the best way to incorporate the spatial structure to be used in the models. In this paper, we applied autoregressive models based on different types of connections and distances between 181 cells covering the Cerrado region of Central Brazil to study the spatial variation in mammal and bird species richness across the biome. Spatial structure was stronger for birds than for mammals, with R(2) values ranging from 0.77 to 0.94 for mammals and from 0.77 to 0.97 for birds, for models based on different definitions of spatial structures. According to the Akaike Information Criterion (AIC), the best autoregressive model was obtained by using the rook connection. In general, these results furnish guidelines for future modelling of species richness patterns in relation to environmental predictors and other variables expressing human occupation in the biome.

Evolutionary processes underlying spatial patterns in species richness remain largely unexplored, and correlative studies lack the theoretical basis to explain these patterns in evolutionary terms. In this study, we develop a spatially explicit simulation model to evaluate, under a pattern-oriented modeling approach, whether evolutionary niche dynamics (the balance between niche conservatism and niche evolution processes) can provide a parsimonious explanation for patterns in species richness. We model the size, shape, and location of species' geographical ranges in a multivariate heterogeneous environmental landscape by simulating an evolutionary process in which environmental fluctuations create geographic range fragmentation, which, in turn, regulates speciation and extinction. We applied the model to the South American domain, adjusting parameters to maximize the correspondence between observed and predicted patterns in richness of about 3,000 bird species. Predicted spatial patterns, which closely resemble observed ones (r2=0.795), proved sensitive to niche dynamics processes. Our simulations allow evaluation of the roles of both evolutionary and ecological processes in explaining spatial patterns in species richness, revealing the enormous potential of the link between ecology and historical biogeography under integrated theoretical and methodological frameworks.

Three main causes to population synchrony are proposed: exogenous factors, dispersal and inter-specific interactions. This paper had as main goal to test the influence of the exogenous factors in the synchrony in spatially isolated (i.e., no dispersal) populations of Sitophilus zeamais (Mots.) (Coleoptera: Curculionidae), in microcosms with different environmental conditions (humidity, temperature and light intensity). Twelve populations of 20 individuals each, were randomly assigned between two treatment conditions: with or without light. Population size and environmental factors (temperature and relative humidity) were weekly assessed for seven months. Temporal trend in populations increase was eliminated adjusting autoregressive models. Population synchrony, detected by means of Pearson's and Spearman's correlation coefficients, was higher within than between treatments, although the populations kept without lamp were more synchronized than populations with lamp. Besides demonstrating the influence of environment on population fluctuations, these results suggest that metabolism and intra-specific interactions are important factors in population dynamic. Organisms exposed to unsuitable environmental conditions may have abnormal metabolic rates, which negatively influences the population grow. Thus, small populations are more likely to suffer from demographic stochasticity, decreasing the probability of the synchrony among populations. On the other hand, in more suitable environments, individuals are expected to have normal metabolic functions, and so, to achieve higher rates of population grow. In this case, the demographic stochasticity has smaller influence, leading populations without lamp to fluctuate synchronously.

The causes of global variation in species richness have been debated for nearly two centuries with no clear resolution in sight. Competing hypotheses have typically been evaluated with correlative models that do not explicitly incorporate the mechanisms responsible for biotic diversity gradients. Here, we employ a fundamentally different approach that uses spatially explicit Monte Carlo models of the placement of cohesive geographical ranges in an environmentally heterogeneous landscape. These models predict species richness of endemic South American birds (2248 species) measured at a continental scale. We demonstrate that the principal single-factor and composite (species-energy, water-energy and temperature-kinetics) models proposed thus far fail to predict (r(2) < or =.05) the richness of species with small to moderately large geographical ranges (first three range-size quartiles). These species constitute the bulk of the avifauna and are primary targets for conservation. Climate-driven models performed reasonably well only for species with the largest geographical ranges (fourth quartile) when range cohesion was enforced. Our analyses suggest that present models inadequately explain the extraordinary diversity of avian species in the montane tropics, the most species-rich region on Earth. Our findings imply that correlative climatic models substantially underestimate the importance of historical factors and small-scale niche-driven assembly processes in shaping contemporary species-richness patterns.

Correlations between species richness and climate suggest non-random occupation of environmental space and niche evolution through time. However, the evolutionary mechanisms involved remain unresolved. Here, we partition the occupation of environmental space into intra- and inter-clade components to differentiate a model based on pure conservation of ancestral niches with higher diversification rates in the tropics, and an adaptive radiation model based on shifts in adaptive peaks at the family level allowing occupation of temperate regions. We examined these mechanisms using within- and among-family skewness components based on centroids of 3560 New World bird species across four environmental variables. We found that the accumulation of species in the tropics is a result of both processes. The components of adaptive radiation have family level skewness of species' distributions strongly structured in space, but not phylogenetically, according to the integrated analyses of spatial filters and phylogenetic eigenvectors. Moreover, stronger radiation components were found for energy variables, which are often used to argue for direct climatic effects on diversity. Thus, the correspondence between diversity and climate may be due to the conservation of ancestral tropical niches coupled with repeated broad shifts in adaptive peaks during birds' evolutionary history more than by higher diversification rates driven by more energy in the tropics.

Termites usually build nests differently shaped and characterized according to each species, to protect and keep society cohesion. Some species build nests in the ground, some prefer tree thunks or branches as support, whereas other dig galleries in the wood. The purpose of this study is to analyze the relationship between the occurrence of arboreal termites Constrictotermes cyphergaster Silvestri and tree species that support the nest of this species, in a Cerrado sensu strictu of the Serra de Caldas Novas, GO. Data suggest a association relationship between C. Cyphergaster and the tree species Qualea grandiflora Mart., Annona crassiflora Mart., Caryocar brasiliense Camb. and Plathymenia reticulata Benth., shown by high Qui-squared values (chi2 = 214.986, gl. = 20, P < 0.001). This relationship may be found among other termites and tree species, including Cerrado biome, and may be due to several factors, such as natural competitors and predators, toxin production by other tree species or benefits between associated species (facultative mutualism or facilitation).

Many mechanisms have been proposed to explain broad scale spatial patterns in species richness. In this paper, we evaluate five explanations for geographic gradients in species richness, using South American owls as a model. We compared the explanatory power of contemporary climate, landcover diversity, spatial climatic heterogeneity, evolutionary history, and area. An important aspect of our analyses is that very different hypotheses, such as history and area, can be quantified at the same observation scale and, consequently can be incorporated into a single analytical framework. Both area effects and owl phylogenetic history were poorly associated with richness, whereas contemporary climate, climatic heterogeneity at the mesoscale and landcover diversity explained ca. 53% of the variation in species richness. We conclude that both climate and environmental heterogeneity should be retained as plausible explanations for the diversity gradient. Turnover rates and scaling effects, on the other hand, although perhaps useful for detecting faunal changes and beta diversity at local and regional scales, are not strong explanations for the owl diversity gradient.

Recently, the hypothesis that the geographic distribution of species could be influenced by the shape of the domain edges, the so-called Mid-Domain Effect (MDE), has been included as one of the five credible hypotheses for explaining spatial gradients in species richness, despite all the unsuccessful current attempts to prove empirically the validity of MDE. We used data on spatial worldwide distributions of Falconiformes to evaluate the validity of MDE assumptions, incorporated into two different sorts of null models at a global level and separately across five domains/landmasses. Species richness values predicted by the null models of the MDE and those values predicted by Net Primary Productivity, a surrogate variable expressing the effect of available energy, were compared in order to evaluate which hypothesis better predicts the observed values. Our tests showed that MDE continues to lack empirical support, regardless of its current acceptability, and so, does not deserve to be classified as one possible explanation of species richness gradients.