Leaf area and leaf biomass have an important influence on the exchange of energy, light interception, carbon cycling, plant growth, and forest productivity. This study showed development and comparison of models for predicting leaf area and leaf biomass of Lagerstroemia speciosa on the basis of diameter at breast height and tree height as predictors. Data on tree parameters were collected randomly from 312 healthy, well-formed tree species that were considered specifically for full tree crowns. Twenty-four different forms of linear and power models were compared in this study to select the best model. Two models (M10 and M22) for the estimation of leaf area and leaf biomass were selected based on , adjusted , root mean squared error, corrected akaike information criterion, Bayesian information criterion and Furnival’s index, and the three assumptions of linear regression. The models were validated with a test data set having the same range of DBH and tree height of the sampled data set on the basis of linear regression Morisita’s similarity index. So, the robustness of the models suggests their further application for leaf area and biomass estimation of L. speciosa in West Vanugach reserve forest of Bangladesh. 1. Introduction Leaf area (A1) and leaf biomass (B1) estimation are significant basics of studying gas-exchange processes and modeling ecosystems. It is key traits in ecophysiological studies that determine assessing photosynthetic efficiency, evapotranspiration, atmospheric deposition, biogenic volatile organic emissions, light interception, and other ecosystem processes. Leaf area is valuable for the evaluation and understanding of individual tree growth models [1], biogeochemical models [2], and gap models [3]. It is defined as the one-sided projected surface area which is an important consequence for the interception of radiant energy, the absorption of carbon dioxide, and the circulation of water between the foliage and the atmosphere [4]. Leaf biomass constitutes one of the most important pools of essential nutrients, which is vital for forest nutrient cycling [5], including carbon cycling in a forest ecosystem. Leaf biomass estimates were considerably improved when additional biometric information relating to crown structure was added, whereas canopy B1 is the product of leaf dry matter content and leaf area index [6]. Interspecific variation in A1 and B1 has been connected with climatic variation, geology, altitude, or latitude, where heat stress, cold stress, drought stress, and high-radiation stress all tend to select relatively small
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