The relationship between phylogenetic signal in trait data (x-axis) and the relationship between the phylogenetic and functional beta diversity of communities (y-axis).

<p>Larger <i>K</i> values indicate more phylogenetic signal in trait data and higher y-axis values indicate that the phylogenetic beta diversity of the tree plots is more correlated with the functional beta diversity.</p

A correlation analysis of different metrics of species and phylogenetic community dissimilarity.

<p>The lower triangle cell values are Pearson's <i>r</i> values being calculated from the Phylomatic phylogeny. Values in the upper triangle are 95% confidence intervals of <i>r</i> values calculated from the 100 randomly resolved phylogenies.</p

The results of Mantel tests used to determine the correlation between community beta diversity metrics and geographic, altitudinal or precipitation differences.

<p>The values in the cells are <i>r</i> values and boldface indicates significance with phylogenetic values being calculated from the Phylomatic phylogeny. Values in the parentheses indicate 95% confidence intervals generated from the 100 randomly resolved phylogenies.</p

An example of four pairs of hypothetical communities and types of phylogenetic beta diversity.

<p>The species in a single community have the same color boxes. Species that are in neither community are left blank. All branch lengths are set to one and all species are scored as present or absent in this simplified example. It is important to note that in each of the four scenarios there is a complete turnover of species between the two communities, but the degree of phylogenetic beta diversity varies. Scenario A indicates species in the blue community are closely related to one another, but distantly related to the species in the orange community. This is an example of ‘basal’ phylogenetic turnover. Scenario B also indicates species in the blue community are closely related to one another, but distantly related to the species in the orange community. The main difference in that Scenario B has a much lower level of ‘basal’ phylogenetic beta diversity than that in Scenario A. Scenario C indicates locally phylogenetically overdispersed communities that have little phylogenetic beta diversity. Scenario D also indicates local phylogenetic overdispersion and low phylogenetic beta diversity. In both scenarios phylogenetic beta diversity measured using a nearest neighbor metric will be lower than when measured using a pairwise metric that considers the basal portion of the phylogeny and this effect will be maximized in Scenario C.</p

Calculated values for the four scenarios provided in Figure 1 using the six presence-absence weighted metrics used in the article.

<p>Further the original phylogeny (λ = 1) was lambda transformed <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0021264#pone.0021264-Pagel1" target="_blank">[24]</a> four times to produce phylogenies that were increasingly ‘tippy’ ending with a ‘star’ phylogeny where all species are equally related. This simplified example highlights the similarity or redundancy of some of the phylogenetic beta diversity metrics utilized. It also shows that the metrics converge as the phylogeny becomes more ‘star-like’ at which point very little phylogenetic information is available.</p

Appendix J. The moments of the trait distribution in FIA plots in 1° grid cells weighted by abundance in the five Holdridge life zones in the study area.

The moments of the trait distribution in FIA plots in 1° grid cells weighted by abundance in the five Holdridge life zones in the study area

Appendix B. The results of a regression through the origin where the moments of the trait distribution of plots and grid cells calculated using presence–absence weighting are regressed on the mean trait values calculated using abundance weighting.

The results of a regression through the origin where the moments of the trait distribution of plots and grid cells calculated using presence–absence weighting are regressed on the mean trait values calculated using abundance weighting

Appendix B. The results of the principal components analysis of the six functional traits quantified for all of the species in the LFDP.

The results of the principal components analysis of the six functional traits quantified for all of the species in the LFDP

Appendix A. Literature sources for height data.

Literature sources for height data

Appendix C. The Pearson correlation coefficients for precipitation variables and the moments of the trait distribution in plots and 1° grid cells.

The Pearson correlation coefficients for precipitation variables and the moments of the trait distribution in plots and 1° grid cells