ABSTRACT

The carbon storage capacity and allometry for bamboo in forest ecosystems has been neglected in the Congo Basin. This study evaluated the above ground carbon stocks and develop allometry for Bambusa vulgaris Schrad. ex J.C.Wendl. in the tropical evergreen forest of Cameroon. Data was collected destructively. Culm density and aboveground carbon were extrapolated; and log transformed models were regressed for best fit allometries. Age of bamboo appeared to be the best predictor of biomass, followed by height and diameter respectively. Height of culm was the best predictor of leaf biomass. The best fit allometric model was obtained when all three predictive variables (diameter, height and age) were inputted in the model. The culm density was 2296 bamboo per hectare (ha); the average aboveground biomass of bamboo was 29 kg; the total aboveground carbon of bamboo per hectare (AGC_bamboo per ha) was 29.70 t C per ha and the total aboveground carbon dioxide emission of bamboo per hectare (AGC_bamboo emissions per ha) was 108.7 t CO₂ equivalence. The more predictive variables were added in a model, the more the model’s quality improved and thereby reducing the uncertainty. Thus, the destruction of one ha of bamboo releases enormous CO₂ into the atmosphere. These findings are especially timely given the urgent need to quantify carbon stocks in the tropics and formulate good policies to fight against climate change in Cameroon.

摘要

刚果盆地一直忽视森林生态系统中竹子的碳储存能力和异速生长。本研究评估了地上碳储量并开发了 Bambusa vulgaris Schrad 的异速生长。前 JCWendl。在喀麦隆热带常绿森林中。数据是破坏性收集的。外推秆密度和地上碳；对数转换模型进行回归以获得最佳拟合异变。竹子的年龄似乎是生物量的最佳预测因子，其次是高度和直径。秆高是叶片生物量的最佳预测因子。当所有三个预测变量（直径、身高和年龄）都输入模型时，就得到了最适合的异速生长模型。秆密度为每公顷（ha）2296根竹子；竹子的平均地上生物量为29 kg；每公顷_竹子）为每公顷 29.70 吨 C，每公顷竹子的地上二氧化碳总排放量（每公顷 AGC_竹子排放量）为 108.7 吨 CO ₂当量。模型中添加的预测变量越多，模型的质量提高得越多，从而降低不确定性。因此，破坏一公顷的竹子会向大气中释放大量的 CO ₂。鉴于迫切需要量化热带地区的碳储量并制定良好的政策以应对喀麦隆的气候变化，这些发现尤其及时。