首页> 外文期刊>Environmental Research Letters >Can recent pan-tropical biomass maps be used to derive alternative Tier 1 values for reporting REDD+ activities under UNFCCC?
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Can recent pan-tropical biomass maps be used to derive alternative Tier 1 values for reporting REDD+ activities under UNFCCC?

机译:是否可以使用最新的泛热带生物量图来导出Tier 1值,以报告UNFCCC下的REDD +活动?

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The IPCC Guidelines propose 3 Tier levels for greenhouse gas monitoring within the forest land category with a hierarchical order in terms of accuracy, data requirements and complexity. Due to missing data and/or capacities, many developing countries, potentially interested in the reducing emissions from deforestation and forest degradation scheme, have to rely on Tier 1 default values with highest uncertainties. A possible way to increase the credibility of uncertain estimates is to apply a conservative approach, for which standard statistical information is needed. However, such information is currently not available for the IPCC values. In our study we combine a recent global forest mask, an ecological zoning map and the pan-tropical AGB datasets of Saatchi and Baccini to derive mean forest AGB values per ecological zone and continent as well as their corresponding confidence intervals. Such analysis can be considered transparent as the datasets/methodologies are well documented. Our study leads to alternative Tier 1 values and allows the application of statistically-based conservative approaches. Our AGB estimates derived from Saatchi and Baccini datasets are 35% and 24% lower respectively than the IPCC values. When restricting the analysis to intact forest landscapes resulting ABG estimates derived from Saatchi and Baccini datasets get closer to the IPCC values with 13% and 1% differences respectively (underestimation). This suggests that the IPCC default values are mainly based on plots in mature forest stands. However, as tropical forests generally consist of a mixture of intact and degraded stands, the use of IPCC values may not properly reflect the reality. Finally, we propose to use the average composite of the Saatchi and Baccini datasets to produce improved alternative IPCC Tier 1 values. The values derived from such approach can easily be updated when newer and/or improved pan-tropical AGB maps will be available.
机译:IPCC指南针对林地类别中的温室气体监测提出了3个等级,以准确性,数据要求和复杂性为等级。由于缺少数据和/或能力,许多可能对减少毁林和森林退化计划的排放量感兴趣的发展中国家不得不依赖具有最高不确定性的方法1默认值。提高不确定性估计的可信度的一种可能方法是采用保守的方法,为此需要标准的统计信息。但是,此类信息当前不适用于IPCC值。在我们的研究中,我们结合了最近的全球森林遮罩,生态分区图以及萨奇和巴奇尼的泛热带AGB数据集,以得出每个生态区和每个大陆的平均森林AGB值及其相应的置信区间。这样的分析可以被认为是透明的,因为数据集/方法已被充分记录。我们的研究得出了方法1的替代值,并允许应用基于统计的保守方法。我们从Saatchi和Baccini数据集中获得的AGB估计分别比IPCC值低35%和24%。当将分析限于完整森林景观时,从萨奇和巴奇尼数据集得出的ABG估计值更接近IPCC值,分别相差13%和1%(低估)。这表明IPCC的默认值主要基于成熟林分中的地块。但是,由于热带森林通常由原始林和退化林的混合物组成,因此使用IPCC值可能无法正确反映现实。最后,我们建议使用Saatchi和Baccini数据集的平均组合来产生改进的IPCC Tier 1替代值。当有更新和/或改进的泛热带AGB映射可用时,可以轻松地更新从这种方法得出的值。

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