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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).)

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.

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.)

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.