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Forecasting deforestation and carbon emissions in tropical developing countries facing demographic expansion: A case study in Madagascar

机译:预测面临人口增长的热带发展中国家的森林砍伐和碳排放:以马达加斯加为例

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摘要

Anthropogenic deforestation in tropical countries is responsible for a significant part of global carbon dioxide emissions in the atmosphere. To plan efficient climate change mitigation programs (such as REDD+, Reducing Emissions from Deforestation and forest Degradation), reliable forecasts of deforestation and carbon dioxide emissions are necessary. Although population density has been recognized as a key factor in tropical deforestation, current methods of prediction do not allow the population explosion that is occurring in many tropical developing countries to be taken into account. Here, we propose an innovative approach using novel computational and statistical tools, including R/GRASS scripts and the new phcfM R package, to model the intensity and location of deforestation including the effect of population density. We used the model to forecast anthropogenic deforestation and carbon dioxide emissions in five large study areas in the humid and spiny-dry forests of Madagascar. Using our approach, we were able to demonstrate that the current rapid population growth in Madagascar (+3.39% per year) will significantly increase the intensity of deforestation by 2030 (up to +1.17% per year in densely populated areas). We estimated the carbon dioxide emissions associated with the loss of aboveground biomass to be of 2.24 and 0.26 tons per hectare and per year in the humid and spiny-dry forest, respectively. Our models showed better predictive ability than previous deforestation models (the figure of merit ranged from 10 to 23). We recommend this approach to reduce the uncertainty associated with deforestation forecasts. We also underline the risk of an increase in the speed of deforestation in the short term in tropical developing countries undergoing rapid population expansion. (Résumé d'auteur)
机译:热带国家的人为砍伐森林是全球大气中二氧化碳排放量的很大一部分。为了规划有效的减缓气候变化计划(如REDD +,减少森林砍伐和森林退化造成的排放),需要可靠的森林砍伐和二氧化碳排放预测。尽管人口密度已被认为是热带森林砍伐的关键因素,但目前的预测方法并未考虑到许多热带发展中国家正在发生的人口爆炸。在这里,我们提出了一种使用新颖的计算和统计工具(包括R / GRASS脚本和新的phcfM R软件包)的创新方法,以模拟包括人口密度影响在内的森林砍伐的强度和位置。我们使用该模型预测了马达加斯加湿润和多刺干旱森林中五个大型研究区的人为砍伐森林和二氧化碳排放量。使用我们的方法,我们能够证明,马达加斯加目前的人口快速增长(每年+ 3.39%)将在2030年之前显着增加森林砍伐的强度(在人口稠密地区每年高达+ 1.17%)。我们估计,在湿润和多刺的干旱森林中,与地上生物量损失相关的二氧化碳排放量分别为每公顷和每年2.24和0.26吨。我们的模型显示出比以前的森林砍伐模型更好的预测能力(价值因数从10到23)。我们建议使用这种方法来减少与毁林预测相关的不确定性。我们还强调了在人口迅速膨胀的热带发展中国家,短期内毁林速度加快的风险。 (Résuméd'auteur)

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