Maxtree Plant Models Vol 15 EXCLUSIVE

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Leaf mass per area. Recruits were measured at 1, 2, 4, 6, and 8 years after planting. The leaf mass per area was predicted using the linear model leaf_mass_area = β0 + β1recruit + β2species + β3origin + β4age + β5pft. (3) The model was fitted for the data from the seedlings that survived at least one year after transplanting to predict the leaf mass per area at each age.

Above ground length. Recruits were measured at 1, 2, 4, 6, and 8 years after planting. The above ground length was predicted using the linear model above_length = β0 + β1recruit + β2species + β3origin + β4age + β5pft. (2) The model was fitted for the data from the seedlings that survived at least one year after transplanting to predict the length at each age. An exponential model was used to fit the seedlings length with four parameters (length = A0exp (β1age + β2). The predicted length of the transplants was calculated as the difference between the average length of the seedlings at each age and the length of the recruits. The predicted length of the transplants was compared with the observed length of the seedlings at each age, and R² values were calculated to estimate the accuracy of the model.

Above ground biomass. Recruits were measured at 1, 2, 4, 6, and 8 years after planting. We predicted above ground biomass (g/m²) of a seedling using the linear model log(biomass) = β0 + β1recruit + β2species + β3origin + β4age + β5pft. (1) The model was fitted for the data from the seedlings that survived at least one year after transplanting to predict biomass at the different ages. An exponential model was used to fit the above ground biomass of the recruits with four parameters (biomass = A0exp (β1age + β2). The predicted biomass of the transplants was calculated as the difference between the average biomass of the seedlings at each age and the biomass of the recruits. The predicted biomass of the transplants was compared with the observed biomass of the seedlings at each age, and R² values were calculated to estimate the accuracy of the model.

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