Fabricio Villalobos

letsR: a new R package for data handling and analysis in macroecology

Summary 1. The current availability of large ecological data sets and the computational capacity to handle them have fostered the testing and development of theory at broad spatial and temporal scales. Macroecology has particularly benefited from this era of big data, but tools are still required to help transforming this data into information and knowledge. 2. Here, we present ‘letsR’, a package for the R statistical computing environment, designed to handle and analyse macroecological data such as species’ geographic distributions (polygons in shapefile format and point occurrences) and environmental variables (in raster format). The package also includes functions to obtain data on species’ habitat use, description year and current as well as temporal trends in conservation status as provided by the IUCN RedList online data base. 3. ‘letsR’ main functionalities are based on the presence–absence matrices that can be created with the package’s functions and from which other functions can be applied to generate, for example species richness rasters, geographic mid-points of species and species- and site-based attributes. 4. We exemplify the package’s functionality by describing and evaluating the geographic pattern of species’ description year in tailless amphibians. All data preparation and most analyses were made using the ‘letsR ’f unctions. Our example illustrates the package’s capability for conducting macroecological analyses under a single computer platform, potentially helping researchers to save time and effort in this endeavour.

Forest structure drives global diversity of primates

Geographic gradients in the species richness of non-human primates have traditionally been attributed to the variation in forest productivity (related to precipitation levels), although an all-inclusive, global-scale analysis has never been conducted. We perform a more comprehensive test on the role of precipitation and biomass production and propose an alternative hypothesis - the variation in vertical structure of forest habitats as measured by forest canopy height - in determining primate species richness on a global scale. Considering the potential causal relationships among precipitation, productivity and forest structure, we arranged these variables within a path framework to assess their direct and indirect associations with the pattern of primate species richness using structural equation modelling. The analysis also accounted for the influence of spatial autocorrelation in the relationships and assessed possible historical differences among biogeographical regions. The path coefficients indicate that forest canopy height (used as a proxy for vertical forest structure) is a better predictor of primate species richness than either precipitation or productivity on both global and continental scales. The only exception was Asia, where precipitation prevailed, albeit independently from productivity or forest structure. The influence of spatially structured processes varied markedly among biogeographical regions. Our results challenge the traditional rainfall-based viewpoint in favour of forest distribution and structure as primary drivers of primate species richness, which aggregate potential effects from both climatic factors and habitat complexity. These findings may support predictions of the impact of forest removal on primate species richness.

Is rich and rare the common share? Describing biodiversity patterns to inform conservation practices for South American anurans.

Species richness and range size are key features of biogeographic and macroecological analyses, which can yield a first assessment tool to define conservation priorities. Here we combined both features in a simultaneous analysis, based on range-diversity plots, to identify sets of rich-rare (high species richness with restricted ranges) and poor-rare cells (low species richness with restricted ranges). We applied this analysis to the anurans of South America and evaluated the representation of those sets of cells within the protected area system. South American anurans showed high species richness in the Brazilian Atlantic Forest and East Tropical Andes, while regions harboring most of the rare species were concentrated in the Andes and Atlantic Coast from North-Eastern Brazil to River Plate. Based on such patterns, we identified as rich-rare cells the Brazilian Atlantic Forest and Tropical Andes and as poor-rare cells the southern part of Andes and Uruguay. A low fraction of both sets of cells was represented within the protected area system. We show that a simultaneous consideration of species richness and rarity provides a rapid assessment of large-scale biodiversity patterns and may contribute to the definition of conservation priorities.

Disentangling the Role of Climate, Topography and Vegetation in Species Richness Gradients.

Environmental gradients (EG) related to climate, topography and vegetation are among the most important drivers of broad scale patterns of species richness. However, these different EG do not necessarily drive species richness in similar ways, potentially presenting synergistic associations when driving species richness. Understanding the synergism among EG allows us to address key questions arising from the effects of global climate and land use changes on biodiversity. Herein, we use variation partitioning (also know as commonality analysis) to disentangle unique and shared contributions of different EG in explaining species richness of Neotropical vertebrates. We use three broad sets of predictors to represent the environmental variability in (i) climate (annual mean temperature, temperature annual range, annual precipitation and precipitation range), (ii) topography (mean elevation, range and coefficient of variation of elevation), and (iii) vegetation (land cover diversity, standard deviation and range of forest canopy height). The shared contribution between two types of EG is used to quantify synergistic processes operating among EG, offering new perspectives on the causal relationships driving species richness. To account for spatially structured processes, we use Spatial EigenVector Mapping models. We perform analyses across groups with distinct dispersal abilities (amphibians, non-volant mammals, bats and birds) and discuss the influence of vagility on the partitioning results. Our findings indicate that broad scale patterns of vertebrate richness are mainly affected by the synergism between climate and vegetation, followed by the unique contribution of climate. Climatic factors were relatively more important in explaining species richness of good dispersers. Most of the variation in vegetation that explains vertebrate richness is climatically structured, supporting the productivity hypothesis. Further, the weak synergism between topography and vegetation urges caution when using topographic complexity as a surrogate of habitat (vegetation) heterogeneity.

Phylogenetic eigenvectors and nonstationarity in the evolution of theropod dinosaur skulls.

Despite the long‐standing interest in nonstationarity of both phenotypic evolution and diversification rates, only recently have methods been developed to study this property. Here, we propose a methodological expansion of the phylogenetic signal‐representation (PSR) curve based on phylogenetic eigenvectors to test for nonstationarity. The PSR curve is built by plotting the coefficients of determination R2 from phylogenetic eigenvector regression (PVR) models increasing the number of phylogenetic eigenvectors against the accumulated eigenvalues. The PSR curve is linear under a stationary model of trait evolution (i.e. the Brownian motion model). Here we describe the distribution of shifts in the models R2 and used a randomization procedure to compare observed and simulated shifts along the PSR curve, which allowed detecting nonstationarity in trait evolution. As an applied example, we show that the main evolutionary pattern of variation in the theropod dinosaur skull was nonstationary, with a significant shift in evolutionary rates in derived oviraptorosaurs, an aberrant group of mostly toothless, crested, birdlike theropods. This result is also supported by a recently proposed Bayesian‐based method (AUTEUR). A significant deviation between Ceratosaurus and Limusaurus terminal branches was also detected. We purport that our new approach is a valuable tool for evolutionary biologists, owing to its simplicity, flexibility and comprehensiveness.

Body size, extinction risk and knowledge bias in New World snakes.

Extinction risk and body size have been found to be related in various vertebrate groups, with larger species being more at risk than smaller ones. We checked whether this was also the case for snakes by investigating extinction risk–body size relationships in the New Worlds Colubroidea species. We used the IUCN Red List risk categories to assign each species to one of two broad levels of threat (Threatened and Non-Threatened) or to identify it as either Data Deficient or Not-Evaluated by the IUCN. We also included the year of description of each species in our analysis as this could affect the level of threat assigned to it (earlier described species had more time to gather information about them, which might have facilitated their evaluation). Also, species detectability could be a function of body size, with larger species tending to be described earlier, which could have an impact in extinction risk–body size relationships. We found a negative relationship between body size and description year, with large-bodied species being described earlier. Description year also varied among risk categories, with Non-Threatened species being described earlier than Threatened species and both species groups earlier than Data Deficient species. On average, Data Deficient species also presented smaller body sizes, while no size differences were detected between Threatened and Non-Threatened species. So it seems that smaller body sizes are related with species detectability, thus potentially affecting both when a species is described (smaller species tend to be described more recently) as well as the amount of information gathered about it (Data Deficient species tend to be smaller). Our data also indicated that if Data Deficient species were to be categorized as Threatened in the future, snake body size and extinction risk would be negatively related, contrasting with the opposite pattern commonly observed in other vertebrate groups.

Explorando patrones en rasgos macroecológicos utilizando regresión secuencial de autovectores filogenéticos

Bini, L.M., Villalobos, F., Diniz-Filho, J.A.F. 2014. Exploring patterns in macroecological traits using sequential phylogenetic eigenvector regression . Ecosistemas 23(1):21-26. Doi.: 10.7818/ECOS.2014.23-1.04 A number of methods have been proposed to estimate the level of phylogenetic signal (autocorrelation) in macroecological traits. These methods are useful to devise alternative ways to circumvent the problem of lack of independence among species and, recently, they have also proved valuable to infer how fast a trait has evolved in comparison with alternative evolutionary models, such as a Brownian motion or Ornstein-Uhlenbeck process. Recently, we developed a method called phylogenetic signal-representation (PSR) curve, an expansion of the phylogenetic eigenvector regression (PVR) proposed in 1998, which consists in estimating different coefficients of determination by regressing a trait of interest on the eigenvectors extracted from a phylogenetic distance matrix. The first model uses only the first of these eigenvectors as an explanatory variable; the second model uses both the first and the second and so on. After, the resultant coefficients of determination are plotted against the cumulative eigenvalues, and the shape of this curve is related to evolutionary models driving trait variation (i.e., a linear pattern is expected under Brownian evolution). Here, we used the PSR curve to study patterns of interspecific variation in Carnivora body size and geographical range size, and compared them with simulated curves under distinct evolutionary processes. Our results unequivocally support our expectations based on previous studies that body size has a strong phylogenetic signal, approximated by an OU pattern with low restraining force, whereas geographic range size is more labile and better fits the null expectations (i.e., absence of phylogenetic signal)

GlobTherm, a global database on thermal tolerances for aquatic and terrestrial organisms

How climate affects species distributions is a longstanding question receiving renewed interest owing to the need to predict the impacts of global warming on biodiversity. Is climate change forcing species to live near their critical thermal limits? Are these limits likely to change through natural selection? These and other important questions can be addressed with models relating geographical distributions of species with climate data, but inferences made with these models are highly contingent on non-climatic factors such as biotic interactions. Improved understanding of climate change effects on species will require extensive analysis of thermal physiological traits, but such data are both scarce and scattered. To overcome current limitations, we created the GlobTherm database. The database contains experimentally derived species’ thermal tolerance data currently comprising over 2,000 species of terrestrial, freshwater, intertidal and marine multicellular algae, plants, fungi, and animals. The GlobTherm database will be maintained and curated by iDiv with the aim to keep expanding it, and enable further investigations on the effects of climate on the distribution of life on Earth.

The best of both worlds: Phylogenetic eigenvector regression and mapping

Eigenfunction analyses have been widely used to model patterns of autocorrelation in time, space and phylogeny. In a phylogenetic context, Diniz-Filho et al. (1998) proposed what they called Phylogenetic Eigenvector Regression (PVR), in which pairwise phylogenetic distances among species are submitted to a Principal Coordinate Analysis, and eigenvectors are then used as explanatory variables in regression, correlation or ANOVAs. More recently, a new approach called Phylogenetic Eigenvector Mapping (PEM) was proposed, with the main advantage of explicitly incorporating a model-based warping in phylogenetic distance in which an Ornstein-Uhlenbeck (O-U) process is fitted to data before eigenvector extraction. Here we compared PVR and PEM in respect to estimated phylogenetic signal, correlated evolution under alternative evolutionary models and phylogenetic imputation, using simulated data. Despite similarity between the two approaches, PEM has a slightly higher prediction ability and is more general than the original PVR. Even so, in a conceptual sense, PEM may provide a technique in the best of both worlds, combining the flexibility of data-driven and empirical eigenfunction analyses and the sounding insights provided by evolutionary models well known in comparative analyses.

Integrating selection, niche, and diversification into a hierarchical conceptual framework

Recently, new phylogenetic comparative methods have been proposed to test for the association of biological traits with diversification patterns, with species ecological “niche” being one of the most studied traits. In general, these methods implicitly assume natural selection acting at the species level, thus implying the mechanism of species selection. However, natural selection acting at the organismal level could also influence diversification patterns (i.e., effect macroevolution). Owing to our scarce knowledge on multi-level selection regarding niche as a trait, we propose a conceptual model to discuss and guide the test between species selection and effect macroevolution within a hierarchical framework. We first assume niche as an organismal as well as a species’ trait that interacts with the environment and results in species-level differential fitness. Then, we argue that niche heritability, a requirement for natural selection, can be assessed by its phylogenetic signal. Finally, we propose several predictions that can be tested in the future by disentangling both types of evolutionary processes (species selection or effect macroevolution). Our framework can have important implications for guiding analyses that aim to understand the hierarchical perspective of evolution.