FIG. D1. Principal component analysis (PCA) of a plot-trait matrix (8988 relevés × 7 traits). For each plot, a trait mean was calculated for all seven traits. Each plot mean is a dot in the figure (for details see main article).
Appendix D. Results of the PCA, RDA with three environmental drivers and seven traits.
TABLE D1. Results of principal component analysis (PCA) of the site-trait matrix (156 sites × 7 traits). The explained variance is shown as well as the trait scores. Abbreviations of traits: Leaf nitrogen content (LNC), leaf phosphorus content (LPC), specific leaf area (SLA), seed mass of the germinule (SM_g), maximum canopy height (maxCH), relative growth rate (RGR), germination onset (GO).
| PCA 1 | PCA 2 | |
|
Cumulative explained variance |
0.50 | 0.80 |
| Scores | ||
| SLA | -1.15 | -1.4 |
| LNC | -1.76 | -1.02 |
| LPC | -1.48 | -1.42 |
| RGR | 0.80 | -1.62 |
| maxCH | -1.71 | 1.11 |
| SM_g | -1.85 | 0.39 |
| GO | 1.65 | -0.97 |
TABLE D2. Results of the RDA with the relevé-traits (156 sites × 7 traits) constrained by 2 environmental factors (measured TSD and measured Soil C/P and Soil C/N). The cumulative explained variance of the constrained axis, and the scores of the environmental constraints are shown.
| RDA1 | RDA2 | RDA3 | |
|
Cumulative explained variance |
0.29 | 0.37 | 0.38 |
| LogC/N | 0.21 | -0.55 | -0.81 |
| LogC/P | 0.45 | -0.87 | 0.21 |
| TSD | -0.92 | -0.38 | -0.02 |
|
|
FIG. D1. Principal component analysis (PCA) of a plot-trait matrix (8988 relevés × 7 traits). For each plot, a trait mean was calculated for all seven traits. Each plot mean is a dot in the figure (for details see main article). |