Table 4. Allocation coefficients to leaf biomass, structural biomass, and root biomass for the studied species according to the shading treatment at date 9.
Species | Biomass compartment | shading |
Final model r2 | |
---|---|---|---|---|
L | S | |||
Bridelia ferruginea | leaf | 0.359 | 0.283 | 0.995 |
stem | 0.308 | 0.258 | 0.986 | |
root | 0.330 | 0.432 | 0.993 | |
sum | 0.997 | 0.973 | ||
Ceiba pentandra | leaf | 0.177 | 0.177 | 0.942 |
stem | 0.575 | 0.575 | 0.989 | |
root | 0.263 | 0.236 | 0.994 | |
sum | 1.015 | 0.988 | ||
Cynometra megalophylla | leaf | 0.249 | 0.249 | 0.987 |
stem | 0.386 | 0.386 | 0.995 | |
root | 0.349 | 0.349 | 0.990 | |
sum | 0.984 | 0.984 | ||
Piliostigma thonningii | leaf | 0.396 | 0.275 | 0.989 |
stem | 0.266 | 0.219 | 0.993 | |
root | 0.437 | 0.356 | 0.994 | |
sum | 1.099 | 0.850 |
Shading, L (light) and S (shade). Coefficients computed as slopes of regressions (forced through the origin) between increase in biomass compartments and increase in total biomass between dates 3 and 9. All coefficients are significant at the 5% level. Regression models were simplified until all remaining effects were significantly different from each other (equal coefficients were merged into a single coefficient). The sum of the three coefficients should be equal to 1, however since they were estimated as regression coefficients there was no such constraint put on their estimation: we provide the sum as an assessment of the estimate quality.