Table 4.
Variable loading scores of 17 root traits and the proportion of variation of each principal component.
| PC1 | PC2 | PC3 | |
|---|---|---|---|
| BL | 0.98 | 0.04 | –0.03 |
| RL | 0.98 | 0.03 | –0.02 |
| BN | 0.97 | 0.00 | –0.10 |
| RA | 0.97 | 0.06 | 0.06 |
| RV | 0.93 | 0.09 | 0.13 |
| BD | 0.90 | 0.12 | –0.26 |
| BL_sub | 0.89 | –0.32 | 0.08 |
| BLR_tap | 0.85 | 0.20 | –0.23 |
| BL_top | 0.74 | 0.49 | 0.24 |
| RL_top | 0.74 | 0.49 | 0.24 |
| RL_s3 | 0.71 | –0.46 | 0.03 |
| BLR_top/sub | –0.40 | 0.87 | 0.01 |
| RLR_top/sub | –0.40 | 0.88 | 0.01 |
| SRL | 0.47 | 0.00 | –0.75 |
| RM | 0.59 | 0.08 | 0.71 |
| TRL_z2 | –0.02 | –0.22 | 0.58 |
| RMR | –0.25 | –0.21 | 0.40 |
| Eigenvalue | 9.52 | 2.50 | 1.83 |
| Variability (%) | 56.0 | 14.7 | 10.8 |
| Cumulative variability (%) | 56.0 | 70.7 | 81.5 |
Seventeen root traits with CVs ≥0.3 (see Table 1) were used for factor analysis using the principal component analysis (PCA) extraction method. Rotation converged in 17 iterations using Varimax with Kaiser Normalization. For each trait, the largest variable loading score crossing the three components appears in bold. Principal components with eigenvalues >1 are presented and considered significant (Tabachnik and Fidell, 1996).