Community Phylogenetic structure with R Central question in

Community Phylogenetic structure with R

• Central question in community ecology • What processes are responsible for the identity and relative abundances of co-occurring species in local assemblages? • What is the relative importance of different ecological processes in structuring communities • Search for patterns in community structure that may reflect underlying processes

Community assembly processes Niche and trait evolution Patterns of phylogenetic community structure Phylogenetic data

Patterns of phylogenetic community structure • Phylogenetic clustering – Co-occurring species are more closely related than expected by chance • Phylogenetic overdispersion/evenness – Co-occurring species are more distantly related than expected by chance • Random patterns

Community assembly processes • Many processes could influence phylogenetic community structure – Facilitation – Negative density dependent processes (e. g. herbivory, predation) – Indirect interactions mediated by herbivores, parasites, pathogens – Disturbance e. g. fire – Speciation • Two main processes are usually considered

Habitat filtering • Adaptation of species to abiotic conditions – Communities composed of ecologically similar species – Environment imposes a filter via abiotic conditions favoring species with similar adaptations Emerson & Gillepsie, 2008

Competitive exclusion – The principle of competitive exclusion: similar species cannot coexist indefinitely. – Related species are ecologically similar • Prediction: closely related species should co-occur less than would be expected • Early efforts tested this hypothesis using – species : genus ratios – Taxonomic community structure Emerson & Gillepsie, 2008

Phylogenetic signal Kembel, 2009

Community phylogenetic structure (Competitive exclusion) Kembel, 2009 (or clustering)

Clustering: Co-occurring species are more closely related than expected by chance Over-dispersion: Co-occurring species are more distantly related than expected Clustering due to environmental filtering Over-dispersion due to competitive exclusion Clustering due to competitive exclusion Over-dispersion due to environmental filtering Trait conservatism Trait convergence h

Emerging patterns • Communities structured by several processes acting in concert – Mediated by different sets of traits • Scale is important – Taxonomic scale (Cavender-Barres et al. , 2004; 2006) • Oaks: phylogenetic over dispersion • Angiosperms: phylogenetic clustering – Spatial scales • Similar shift from smaller (overdispersion) to larger spatial scales (clustering)

Steps • Quantify the degree of relatedness among cooccurring species using a phylogeny • Define a broader pool of species from which communities have been assembled • Construct a null model which generates random communities from the broader species pool • Determine phylogenetic signal for functional traits that influence community assembly

Data • Phylogenetic tree for regional/broader species pool – Entire species in all the communities • Species list and presence/absence or abundance data for the different communities, plots or specific habitats within a community.

Getting a phylogenetic tree • Can use either sequence data or species list • Different formats: Newick, Nexus • Online tools available e. g. – Genbank (http: //www. ncbi. nlm. nih. gov/): can obtain raw sequence data – ARB/Silva (http: //www. arb-silva. de/): provides aligned sequence data free for academic use – RDP (http: //rdp. cme. msu. edu/ ): provides sequence data and builds phylogenetic tree – Beast (http: //beast. bio. ed. ac. uk/Main_Page): contains programs to create phylogenies with sequence data – Phylomatic (http: //www. phylodiversity. net/phylomatic/): assembles phylogenies using species lists.

Quantifying degree of relatedness Vamosi et al. , 2009

Within community measures • Faith’s phylogenetic diversity (PD) – Total branch length spanned by the tree including all species in a local community. • A lower value indicates that – Taxa are clumped on the phylogeny – Capture only a small part of the total phylogenetic diversity present in the entire phylogeny – Co-ocurring species are more closely related

• MPD: Mean pair-wise distance between all species in a community – Measures whether species in a community are more closely related than expected by chance (using a null model and the regional species pool) – MPD is more sensitive to tree-wide phylogenetic patterns • MNTD: Mean distance to nearest taxon for each species in the community – Measures whether closely related species tend to co-occur or not (using a null model and the regional species pool). – MNTD is more sensitive to patterns of evenness and clustering closer to the tips of the phylogeny

Distance matrix Kembel, 2009

Null models • Randomize the phylogeny – Phylogeny shuffle: randomizes phylogenetic relationships among species by shuffling the taxa on the tips. – Randomize tree structure • Randomize community structure – Randomize draws from species pool • Species in each sample are random draws from the – Sample pool: maintains species richness of each sample but species are drawn without replacement from the list of all species actually occurring in the sample. – Regional species pool: maintains species richness, but species are drawn without replacement from a broader phylogeny pool. – Randomize community matrix • Independent swap: creates swapped versions of the sample/species matrix; only applicable with presence/absence data.

Randomization • Using null model – Generate a random community – Recalculate metrics i. e. MPD/MNTD – Repeat many times • Result: distribution of metric values for random communities

Standardized effect sizes (SES) • SES=(Observed value – Mean (random values))/SD(random values) • Net relatedness index (NRI): standardized metric obtained by comparing MPDobs and MPDexp – + NRI = phylogenetic clustering – - NRI = phylogenetic evenness – Calculated as standardized effect size (SES) in picante • SES = -1 x NRI

SES continued • Nearest taxon index (NTI): obtained by comparing MNTDobs and MNTDexp – + NTI = phylogenetic clustering – - NTI = phylogenetic evenness – Computed as standardized effect size (SES) in picante • SES = -1 x NTI

Phylogenetic Beta Diversity • Measures patterns of phylogenetic relatedness among communities – Among communities equivalent of MPD and MNTD using pairs of species drawn from different communities – can be used with any method based on among-community distances • e. g. cluster analysis, phyloordination, Mantel tests with spatial/environmental distances separating communities.

Today’s Data • Bird communities along 3 highways: 64, 44, and 55 – Gradient from urban (1) to rural (5) along those highways, with each community separated by 16 km – Ex. Communities: RD 441, RD 442, RD 443, RD 641, RD 642, etc… RD 64 1 2 3 ? ? ? 4 5

• Genetic data from Genbank using 2 mitochondrial genes – Cytochrome b (Cytb) and Cytochrome c oxidase subunit I (COI) – Made a phylogeny using Beast and Beauti (free online, easy to use, and comes with a short tutorial and good manual) • Question: What is the phylogenetic structure of communities as you go from rural to urban environments? RD 64 1 2 3 ? ? ? 4 5