Steven W. Kembel

Picante: R tools for integrating phylogenies and ecology

SUMMARY Picante is a software package that provides a comprehensive set of tools for analyzing the phylogenetic and trait diversity of ecological communities. The package calculates phylogenetic diversity metrics, performs trait comparative analyses, manipulates phenotypic and phylogenetic data, and performs tests for phylogenetic signal in trait distributions, community structure and species interactions. AVAILABILITY Picante is a package for the R statistical language and environment written in R and C, released under a GPL v2 open-source license, and freely available on the web (http://picante.r-forge.r-project.org) and from CRAN (http://cran.r-project.org).

The merging of community ecology and phylogenetic biology

The increasing availability of phylogenetic data, computing power and informatics tools has facilitated a rapid expansion of studies that apply phylogenetic data and methods to community ecology. Several key areas are reviewed in which phylogenetic information helps to resolve long-standing controversies in community ecology, challenges previous assumptions, and opens new areas of investigation. In particular, studies in phylogenetic community ecology have helped to reveal the multitude of processes driving community assembly and have demonstrated the importance of evolution in the assembly process. Phylogenetic approaches have also increased understanding of the consequences of community interactions for speciation, adaptation and extinction. Finally, phylogenetic community structure and composition holds promise for predicting ecosystem processes and impacts of global change. Major challenges to advancing these areas remain. In particular, determining the extent to which ecologically relevant traits are phylogenetically conserved or convergent, and over what temporal scale, is critical to understanding the causes of community phylogenetic structure and its evolutionary and ecosystem consequences. Harnessing phylogenetic information to understand and forecast changes in diversity and dynamics of communities is a critical step in managing and restoring the Earths biota in a time of rapid global change.

Phylocom: software for the analysis of phylogenetic community structure and trait evolution.

MOTIVATION The increasing availability of phylogenetic and trait data for communities of co-occurring species has created a need for software that integrates ecological and evolutionary analyses. Capabilities: Phylocom calculates numerous metrics of phylogenetic community structure and trait similarity within communities. Hypothesis testing is implemented using several null models. Within the same framework, it measures phylogenetic signal and correlated evolution for species traits. A range of utility functions allow community and phylogenetic data manipulation, tree and trait generation, and integration into scientific workflows. AVAILABILITY Open source at: http://phylodiversity.net/phylocom/.

THE PHYLOGENETIC STRUCTURE OF A NEOTROPICAL FOREST TREE COMMUNITY

Numerous ecological and evolutionary processes are thought to play a role in maintaining the high plant species diversity of tropical forests. An understanding of the phylogenetic structure of an ecological community can provide insights into the relative importance of different processes structuring that community. The objectives of this study were to measure the phylogenetic structure of Neotropical forest tree communities in the Forest Dynamics Plot (FDP) on Barro Colorado Island, Panama, to determine how the phylogenetic structure of tree communities varied among spatial scales and habitats within the FDP, and to study the effects of null-model choice on estimates of community phylogenetic structure. We measured community phylogenetic structure for tree species occurring together in quadrats ranging in size from 10 x 10 m to 100 X 100 m in the FDP. We estimated phylogenetic structure by comparing observed phylogenetic distances among species to the distribution of phylogenetic distances for null communities generated using two different null models. A null model that did not maintain observed species occurrence frequencies tended to find nonrandom community phylogenetic structure, even for random data. Using a null model that maintained observed species frequencies in null communities, the average phylogenetic structure of tree communities in the FDP was close to random at all spatial scales examined, but more quadrats than expected contained species that were phylogenetically clustered or overdispersed, and phylogenetic structure varied among habitats. In young forests and plateau habitats, communities were phylogenetically clustered, meaning that trees were more closely related to their neighbors than expected, while communities in swamp and slope habitats were phylogenetically overdispersed, meaning that trees were more distantly related to their neighbors than expected. Phylogenetic clustering suggests the importance of environmental filtering of phylogenetically conserved traits in young forests and plateau habitats, but the phylogenetic overdispersion observed in other habitats has several possible explanations, including variation in the strength of ecological processes among habitats or the phylogenetic history of niches, traits, and habitat associations. Future studies will need to include information on species traits in order to explain the variation in phylogenetic structure among habitats in tropical forests.

Disentangling niche and neutral influences on community assembly: assessing the performance of community phylogenetic structure tests

Patterns of phylogenetic relatedness within communities have been widely used to infer the importance of different ecological and evolutionary processes during community assembly, but little is known about the relative ability of community phylogenetics methods and null models to detect the signature of processes such as dispersal, competition and filtering under different models of trait evolution. Using a metacommunity simulation incorporating quantitative models of trait evolution and community assembly, I assessed the performance of different tests that have been used to measure community phylogenetic structure. All tests were sensitive to the relative phylogenetic signal in species metacommunity abundances and traits; methods that were most sensitive to the effects of niche-based processes on community structure were also more likely to find non-random patterns of community phylogenetic structure under dispersal assembly. When used with a null model that maintained species occurrence frequency in random communities, several metrics could detect niche-based assembly when there was strong phylogenetic signal in species traits, when multiple traits were involved in community assembly, and in the presence of environmental heterogeneity. Interpretations of the causes of community phylogenetic structure should be modified to account for the influence of dispersal.

Architectural design influences the diversity and structure of the built environment microbiome

Buildings are complex ecosystems that house trillions of microorganisms interacting with each other, with humans and with their environment. Understanding the ecological and evolutionary processes that determine the diversity and composition of the built environment microbiome—the community of microorganisms that live indoors—is important for understanding the relationship between building design, biodiversity and human health. In this study, we used high-throughput sequencing of the bacterial 16S rRNA gene to quantify relationships between building attributes and airborne bacterial communities at a health-care facility. We quantified airborne bacterial community structure and environmental conditions in patient rooms exposed to mechanical or window ventilation and in outdoor air. The phylogenetic diversity of airborne bacterial communities was lower indoors than outdoors, and mechanically ventilated rooms contained less diverse microbial communities than did window-ventilated rooms. Bacterial communities in indoor environments contained many taxa that are absent or rare outdoors, including taxa closely related to potential human pathogens. Building attributes, specifically the source of ventilation air, airflow rates, relative humidity and temperature, were correlated with the diversity and composition of indoor bacterial communities. The relative abundance of bacteria closely related to human pathogens was higher indoors than outdoors, and higher in rooms with lower airflow rates and lower relative humidity. The observed relationship between building design and airborne bacterial diversity suggests that we can manage indoor environments, altering through building design and operation the community of microbial species that potentially colonize the human microbiome during our time indoors.

Incorporating 16S Gene Copy Number Information Improves Estimates of Microbial Diversity and Abundance

The abundance of different SSU rRNA (“16S”) gene sequences in environmental samples is widely used in studies of microbial ecology as a measure of microbial community structure and diversity. However, the genomic copy number of the 16S gene varies greatly – from one in many species to up to 15 in some bacteria and to hundreds in some microbial eukaryotes. As a result of this variation the relative abundance of 16S genes in environmental samples can be attributed both to variation in the relative abundance of different organisms, and to variation in genomic 16S copy number among those organisms. Despite this fact, many studies assume that the abundance of 16S gene sequences is a surrogate measure of the relative abundance of the organisms containing those sequences. Here we present a method that uses data on sequences and genomic copy number of 16S genes along with phylogenetic placement and ancestral state estimation to estimate organismal abundances from environmental DNA sequence data. We use theory and simulations to demonstrate that 16S genomic copy number can be accurately estimated from the short reads typically obtained from high-throughput environmental sequencing of the 16S gene, and that organismal abundances in microbial communities are more strongly correlated with estimated abundances obtained from our method than with gene abundances. We re-analyze several published empirical data sets and demonstrate that the use of gene abundance versus estimated organismal abundance can lead to different inferences about community diversity and structure and the identity of the dominant taxa in microbial communities. Our approach will allow microbial ecologists to make more accurate inferences about microbial diversity and abundance based on 16S sequence data.

Phylogenetic diversity metrics for ecological communities: integrating species richness, abundance and evolutionary history

Phylogenetic information is increasingly being used to understand the assembly of biological communities and ecological processes. However, commonly used metrics of phylogenetic diversity (PD) do not incorporate information on the relative abundances of individuals within a community. In this study, we develop three indices of PD that explicitly consider species abundances. First, we present a metric of phylogenetic-abundance evenness that evaluates the relationship between the abundance and the distribution of terminal branch lengths. Second, we calculate an index of hierarchical imbalance of abundances at the clade level encapsulating the distribution of individuals across the nodes in the phylogeny. Third, we develop an index of abundance-weighted evolutionary distinctiveness and generate an entropic index of phylogenetic diversity that captures both information on evolutionary distances and phylogenetic tree topology, and also serves as a basis to evaluate species conservation value. These metrics offer measures of phylogenetic diversity incorporating different community attributes. We compare these new metrics to existing ones, and use them to explore diversity patterns in a typical California annual grassland plant community at the Jasper Ridge biological preserve.

A global meta‐analysis of the relative extent of intraspecific trait variation in plant communities

Recent studies have shown that accounting for intraspecific trait variation (ITV) may better address major questions in community ecology. However, a general picture of the relative extent of ITV compared to interspecific trait variation in plant communities is still missing. Here, we conducted a meta-analysis of the relative extent of ITV within and among plant communities worldwide, using a data set encompassing 629 communities (plots) and 36 functional traits. Overall, ITV accounted for 25% of the total trait variation within communities and 32% of the total trait variation among communities on average. The relative extent of ITV tended to be greater for whole-plant (e.g. plant height) vs. organ-level traits and for leaf chemical (e.g. leaf N and P concentration) vs. leaf morphological (e.g. leaf area and thickness) traits. The relative amount of ITV decreased with increasing species richness and spatial extent, but did not vary with plant growth form or climate. These results highlight global patterns in the relative importance of ITV in plant communities, providing practical guidelines for when researchers should include ITV in trait-based community and ecosystem studies.

Relationship between cystic fibrosis respiratory tract bacterial communities and age, genotype, antibiotics and Pseudomonas aeruginosa

Polymicrobial bronchopulmonary infections in cystic fibrosis (CF) cause progressive lung damage and death. Although the arrival of Pseudomonas aeruginosa often heralds a more rapid rate of pulmonary decline, there is significant inter-individual variation in the rate of decline, the causes of which remain poorly understood. By coupling culture-independent methods with ecological analyses, we discovered correlations between bacterial community profiles and clinical disease markers in respiratory tracts of 45 children with CF. Bacterial community complexity was inversely correlated with patient age, presence of P. aeruginosa and antibiotic exposure, and was related to CF genotype. Strikingly, bacterial communities lacking P. aeruginosa were much more similar to each other than were those containing P. aeruginosa, regardless of antibiotic exposure. This suggests that community composition might be a better predictor of disease progression than the presence of P. aeruginosa alone and deserves further study.