Identifying Variables to Discriminate between Conserved and Degraded Forest and to Quantify the Differences in Biomass
2020
Yan Gao | Margaret Skutsch | Diana Laura Jiménez Rodríguez | Jonathan V. Solórzano
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.
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