Simulating vertical distribution of normalized leaf biomass for individual Moso bamboos under intensive management

Abstract

Leaf biomass is a crucial parameter that influences forest growth and carbon exchange between ecosystems and the atmosphere. A clear understanding of the vertical distribution of leaf biomass is essential for accurate carbon sequestration estimations in Moso bamboo. We collected data on leaf biomass from each crown layer and the structural characteristics of 54 individual Moso bamboo plants. We then simulated the vertical distribution of normalized upward cumulative leaf biomass (CLBn) using three power functions. The first model (Model 1) estimates CLBn using unique and unadjustable parameters (a and b) of the power function. In the second model (Model 2), parameter ‘a’ was fixed at 1, and parameter ‘b’ was fitted for all samples. In the third model (Model 3), parameter b was adjusted based on the structural characteristics of each bamboo. Model 3 demonstrated the highest accuracy in estimating CLBn and normalized leaf biomass (LBn) in each layer, with RMSEr values of 20.34 % and 36.85 % for CLBn and LBn, respectively. When compared with Model 1 and Model 2, Model 3 reduced RMSEr by 12.27 % and 6.88 % for CLBn and 21.13 % and 10.49 % for LBn, respectively. However, uncertainty remained significant in low LBn estimates from Model 3. Variations in the vertical distribution of CLBn in individual bamboo plants were primarily explained by crown length, height to the lowest living branch, and age. This study proposes a viable method for elucidating the variation in CLBn among individual bamboo plants.