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巴西马托格罗索州毁林和森林退化所致历史排放量:1) 源数据不确定性。

Historic emissions from deforestation and forest degradation in Mato Grosso, Brazil: 1) source data uncertainties.

机构信息

NASA Goddard Space Flight Center, Greenbelt MD USA.

出版信息

Carbon Balance Manag. 2011 Dec 30;6:18. doi: 10.1186/1750-0680-6-18.

Abstract

BACKGROUND

Historic carbon emissions are an important foundation for proposed efforts to Reduce Emissions from Deforestation and forest Degradation and enhance forest carbon stocks through conservation and sustainable forest management (REDD+). The level of uncertainty in historic carbon emissions estimates is also critical for REDD+, since high uncertainties could limit climate benefits from credited mitigation actions. Here, we analyzed source data uncertainties based on the range of available deforestation, forest degradation, and forest carbon stock estimates for the Brazilian state of Mato Grosso during 1990-2008.

RESULTS

Deforestation estimates showed good agreement for multi-year periods of increasing and decreasing deforestation during the study period. However, annual deforestation rates differed by > 20% in more than half of the years between 1997-2008, even for products based on similar input data. Tier 2 estimates of average forest carbon stocks varied between 99-192 Mg C ha-1, with greatest differences in northwest Mato Grosso. Carbon stocks in deforested areas increased over the study period, yet this increasing trend in deforested biomass was smaller than the difference among carbon stock datasets for these areas.

CONCLUSIONS

Estimates of source data uncertainties are essential for REDD+. Patterns of spatial and temporal disagreement among available data products provide a roadmap for future efforts to reduce source data uncertainties for estimates of historic forest carbon emissions. Specifically, regions with large discrepancies in available estimates of both deforestation and forest carbon stocks are priority areas for evaluating and improving existing estimates. Full carbon accounting for REDD+ will also require filling data gaps, including forest degradation and secondary forest, with annual data on all forest transitions.

摘要

背景

历史碳排放是减少毁林和森林退化所致排放并通过保护和可持续森林管理来提高森林碳储量(REDD+)的提议努力的重要基础。历史碳排放估算中的不确定性水平对于 REDD+也很关键,因为高不确定性可能会限制碳信用减排行动的气候效益。在此,我们根据巴西马托格罗索州 1990-2008 年期间可用的森林砍伐、森林退化和森林碳储量估算的范围分析了来源数据不确定性。

结果

在研究期间,森林砍伐估算在多年的森林砍伐增加和减少期间显示出良好的一致性。然而,在 1997-2008 年期间,超过一半的年份中,每年的森林砍伐率差异超过 20%,即使是基于类似输入数据的产品也是如此。平均森林碳储量的 Tier 2 估算值在 99-192 Mg C ha-1 之间变化,在马托格罗索州西北部差异最大。在研究期间,已砍伐地区的碳储量增加,但这些地区的森林生物量碳储量增加趋势小于这些数据集之间的差异。

结论

来源数据不确定性的估算对于 REDD+至关重要。现有数据产品之间的时空不一致模式为减少历史森林碳排放估算中来源数据不确定性的未来努力提供了路线图。具体而言,在森林砍伐和森林碳储量的现有估算中存在较大差异的区域是评估和改进现有估算的优先区域。REDD+的全面碳核算还需要填补数据空白,包括森林退化和次生林,以及所有森林转化的年度数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/43b5/3269366/7385b234f3ae/1750-0680-6-18-1.jpg

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