The purpose of this work was to determine which structural variables present statistically significant differences between degraded and conserved tropical dry forest through a statistical study of forest survey data. The forest survey was carried out in a tropical dry forest in the watershed of the River Ayuquila, Jalisco state, Mexico between May and June of 2019, when data were collected in 36 plots of 500 m². The sample was designed to include tropical dry forests in two conditions: degraded and conserved. In each plot, data collected included diameter at breast height, tree height, number of trees, number of branches, canopy cover, basal area, and aboveground biomass. Using the Wilcoxon signed-rank test, we show that there are significant differences in canopy cover, tree height, basal area, and aboveground biomass between degraded and conserved tropical dry forest. Among these structural variables, canopy cover and mean height separate conserved and degraded forests with the highest accuracy (both at 80.7%). We also tested which variables best correlate with aboveground biomass, with a view to determining how carbon loss in degraded forest can be quantified at a larger scale using remote sensing. We found that canopy cover, tree height, and density of trees all show good correlation with biomass and these variables could be used to estimate changes in biomass stocks in degraded forests. The results of our analysis will help to increase the accuracy in estimating aboveground biomass, contribute to the ongoing work on REDD+, and help to reduce the great uncertainty in estimation of emissions from forest degradation.

中文翻译：

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识别变量以区分保护林和退化林并量化生物量差异

这项工作的目的是通过对森林调查数据的统计研究，确定哪些结构变量在退化和保护的热带旱林之间存在统计学上的显着差异。该森林调查于2019年5月至6月之间在墨西哥哈利斯科州Ayuquila河分水岭的热带干旱森林中进行，当时在36个500 m ²地块中收集了数据。该样本旨在包括两种条件下的热带干旱森林：退化和保护。在每个图中，收集的数据包括胸高，树高，树木数，树枝数，树冠覆盖率，基底面积和地上生物量的直径。使用Wilcoxon符号秩检验，我们发现，退化和养护的热带旱林在冠层覆盖，树木高度，基础面积和地上生物量方面存在显着差异。在这些结构变量中，冠层覆盖和平均高度以最高的精确度（均为80.7％）将受保护和退化的森林分开。我们还测试了哪些变量与地上生物量最相关，以期确定如何使用遥感技术更大规模地量化退化森林中的碳损失。我们发现树冠覆盖，树高，树木的密度和密度均与生物量具有良好的相关性，这些变量可用于估算退化森林中生物量的变化。我们的分析结果将有助于提高估算地上生物量的准确性，有助于正在进行的有关REDD +的工作，并有助于减少估算森林退化造成的排放中的巨大不确定性。