Appendix B. Regeneration niche of Ambrosia deltoidea.

Regeneration niche of Ambrosia deltoidea

Appendix A. Correlation matrix and standard deviations.

Correlation matrix and standard deviations

Results for linking functional diversity with light capture.

<p>Summary of linear mixed-effects models for diversity metrics on light incident on the soil surface in the BioCON experiment. R² are shown for observed versus predicted values. Comparisons are based on Akaike weights, with larger weights indicating greater relative strength of evidence for that predictor. Slopes are standardized and associated P-values are for significance of diversity metrics on light not captured by the canopy.</p

Summary of diversity metrics used in this study.

<p>Abundances of species <i>i</i> and <i>j</i> abbreviated <i>p_i</i> and <i>p_j</i>. Also shown are average correlations with the 18 other indices, and correlation with planned richness (significance denoted as: *, ns, P>0.05; *, P<0.05; **, P<0.01; ***, P<0.001).</p>1<p>Petchey OL, Gaston KJ. 2002. Functional diversity (FD), species richness and community composition. Ecology Letters 5∶402–411.</p>2<p>This study.</p>3<p>Cornwell WK, Schwilk DW, Ackerly DD. 2006. A trait-based test for habitat filtering: Convex hull volume. Ecology 87∶1465–1471.</p>4<p>Rao CR. 1982. Diversity and Dissimilarity Coefficients – A unified approach. Theoretical Population Biology 21∶24–43.</p>5<p>Villéger S, Mason NWH, Mouillot D. 2008. New multidimensional functional diversity indices for a multifaceted framework in functional ecology. Ecology 89∶2290–2301.</p>6<p>Laliberté E, Legendre P. 2010. A distance-based framework for measuring functional diversity from multiple traits. Ecology 91∶299–305.</p

Illustrative bivariate plots for select functional diversity metrics and ecosystem function.

<p>Relationships between aboveground biomass (top row) or light (bottom row) with functional diversity metrics. Leftmost panels show the strongest predictors based on AIC, and selected representative metrics are shown to the right for comparison. Reproduced from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0052821#pone-0052821-t001" target="_blank">Tables 1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0052821#pone-0052821-t002" target="_blank">2</a> are Akaike weights (w_i), with larger weights indicating greater relative strength of evidence for that predictor.</p

Results for linking functional diversity with aboveground biomass.

<p>Summary of linear mixed-effects models for diversity metrics on aboveground biomass in the BioCON experiment. R² are shown for observed versus predicted values. Comparisons are based on Akaike weights, with larger weights indicating greater relative strength of evidence for that predictor. Slopes are standardized and associated P-values are for significance of diversity metrics on aboveground biomass.</p

Associations between FD’ and species abundances.

<p>Shown are associations between FD’ and three example species: <i>Lupinus perennis</i> (N-fixer), <i>Bromus inermis</i> (C3 grass) and <i>Schizachyrium scoparium</i> (C4 grass).</p

Results for linking functional diversity with belowground biomass.

<p>Summary of linear mixed-effects models for diversity metrics on belowground biomass in the BioCON experiment. R² are shown for observed versus predicted values. Comparisons are based on Akaike weights, with larger weights indicating greater relative strength of evidence for that predictor. Slopes are standardized and associated P-values are for significance of diversity metrics on belowground biomass.</p

Association between <i>Lupinus perennis</i> and aboveground biomass.

<p>Linear association between the relative abundance of <i>Lupinus perennis</i> and aboveground biomass.</p

Illustration of abundance weighting procedure for FD and Hulls.

<p>Calculations are shown for a simplified community of three species with unequal abundances (abundance represented by the size of circles). Subscripts are for species i and trait j. Trait values for species are standardized to a mean of zero and standard deviation of one (Z-scores). Trait values for species are then multiplied by the proportional relative abundance (bound between zero and one), which results in a translation towards the origin, more so for rare species and less so for abundant species (see Appendix 1 for calculation). This modified distribution is then used for subsequent metric calculation. Weighing by the CV involves multiplying each standardized trait value by the CV (a positive value). This “stretches” trait axes with CV>1, effectively spreading species further apart along that axis, and “compresses” trait axes with CV<1, effectively crowding species closer together along that axis. We performed CV weighting prior to abundance weighting.</p