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Equa??es alométricas para estimativa de biomassa e carbono em árvores de reflorestamentos de restaura??o

机译:估计生物质和碳在重新造林树中的大量方程

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The objective of this study was to develop and to fit allometric models to estimate dry biomass and total carbon in trees planted in forest restoration areas. Fit data are from 107 trees of 44 species planted in Médio Paranapanema Vale, SP, Brazil, located in the Atlantic Forest and Cerrado Biomes. Dry biomass and carbon mass were obtained by destructive sampling taken from aerial and underground sections of the trees. For model test and fitting, stratification of the initial data set was made in growth rhythms of the sampled species. Adjust was done by using eight linear models of each dependent variable and two were obtained from Stepwise-Forward method. The best models to estimate dry biomass and carbon stock presented adjusted determination coefficient above 0.95 and standard error below 32%. Models based on growth rate of the species presented the best statistical results, reaching R2= 0.985 and Syx%=16.15 for dry biomass of low growth species. Models created by Stepwise procedure produced the best equations for estimates of dry biomass and total carbon, and data stratification of different growth rates of the sampled species was suitable for improving performance of the models.
机译:本研究的目的是发展和适应各种模型来估计森林恢复区种植的树木中的干生物量和总碳。 Fit Data来自Sp,Sp,Sp,巴西的MédioParanapanemaVale,位于大西洋森林和塞拉多生物群系。通过从树木和地下部分采取的破坏性取样获得干生物质和碳质量。对于模型测试和拟合,初始数据集的分层是在采样物种的生长节奏中进行的。通过使用每个因变量的八个线性模型来进行调整,并且从逐步前进的方法获得两个。估计干生物质和碳股的最佳模型在0.95以上的调整后测定系数和低于32%的标准误差。基于物种的生长速率的模型呈现了最佳统计结果,达到R2 = 0.985和SYX%= 16.15,用于低生长物种。由逐步程序创建的模型为干生物量和总碳估算产生的最佳方程,并且采样物种的不同生长速率的数据分层适用于改善模型的性能。

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