Among the other substitute variables crown surface area seems to

Among the other substitute variables crown surface area seems to be the best, even better than sapwood area INCB018424 datasheet at breast height. Basal area and crown projection area are the poorest proxy for leaf area. However, it has to be noted that the figures in Table 3 concern regressions with different intercepts and slopes in each stand, and thus cannot be generalized. Next, the relationships according to Eq. (11) were investigated for common slopes (Table 4). For all sapwood areas the hypothesis that the slopes do not differ between the stands had to be rejected. The same is true for the basal area as a proxy for the leaf area. Only for crown projection area and for crown surface

area, a common slope could be assumed. Among those, the adjusted R2 indicates that the estimations from the crown surface area are better than those from the crown projection area. Interestingly the crown surface area with a common slope seems to be a better estimator for leaf area than the sapwood area at breast height. Furthermore, the test for the hypothesis that the slope does not deviate from 1, indicates that leaf area can be assumed proportional to all substitute variables, except for the sapwood area at breast height. Selleck Regorafenib The test, if the intercepts differ is only applicable if the slopes do not differ

between stands, thus only for the crown projection area and for the crown surface area. This test is the same as the test for differences of the adjusted means. These adjusted means differed significantly by stands for both independent

variables ln CPA and ln CSA, with F = 3.227 and 4.086 and p > F of 0.0033 and 0.0004 respectively. Hence, LA/CSA and LA/CPA are proportional in all stands but the ratios differ significantly between the stands. This is, why later on we will investigate the relationship between the intercepts and stand variables (Eq. (12)). Deciding that among those substitute variables, which can be assessed in a non-destructive way, crown surface area is the best choice to predict leaf Inositol monophosphatase 1 area, we furthermore investigated if these estimations can be improved by adding additional variables. Since crown length and crown width are both parameters from which the crown surface area is calculated, the main additional information for leaf area has been expected to come from the dbh, which is not part of Pretzsch’s (2001) crown model. However, the analysis of covariance for the model: equation(13) ln LA=a+b⋅ln CSA+c⋅ln dbhln LA=a+b⋅ln CSA+c⋅ln dbhexhibited first that in no stand both variables, crown surface area and dbh, were significant. Only in one stand, crown surface area was significant, and in three stands, dbh was significant. Second, assuming common coefficients b and c for all stands, both coefficients were significant. However, the hypothesis for equal coefficients had to be rejected (p = 0.00012).

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