Amazonian forest degradation must be incorporated into the COP26 agenda
Amazonian forest degradation must be incorporated into the COP26 agenda
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亚马逊森林退化必须纳入COP26议程
作者：
C. H. L. Silva Junior;N. Carvalho;A. Pessôa;J. Reis;Aline Pontes;J. Doblas;Viola H. A. Heinrich;W. Campanharo;A. Alencar;Camila Silva;D. Lapola;D. Armenteras;E. Matricardi;E. Berenguer;H. Cassol;Izaya Numata;J. House;J. Ferreira;Jos Barlow;L. Gatti;P. Brando;P. Fearnside;Sassan Saatchi;S. Silva;S. Sitch;A. Aguiar;Carlos A. Silva;C. Vancutsem;F. Achard;R. Beuchle;Y. Shimabukuro;L. Anderson;L. Aragão
各国将于2021年11月在苏格兰格拉斯哥举行的第26届联合国气候变化大会（COP 26; www.ukcop26.org）上重申其减少温室气体（GHG）排放的承诺。修订国家承诺将在确定地球气候的未来方面发挥关键作用。在过去的会议上，亚马逊国家的主要目标是通过承诺降低森林砍伐率来减少土地使用变化和土地管理造成的排放，这是一项众所周知的有效战略。然而，火灾、选择性砍伐和边缘效应造成的人为森林退化也可能导致大量二氧化碳排放，1 -5亚马逊国家尚未明确报告。森林退化尽管影响巨大，但在以往的政策讨论中基本上被忽视了。至关重要的是，在即将举行的COP 26讨论中考虑森林退化问题，并将其纳入未来减少温室气体排放的承诺。人为森林退化是亚马逊河流域社会环境退化的主要驱动力6、7，其程度正在增加8。退化的森林目前所占的面积大于被砍伐的森林面积8、9。在2003-2015年期间，巴西亚马逊地区森林火灾1（5，904 Tg）和边缘效应2（2，068 Tg）产生的二氧化碳承诺排放量占森林砍伐总排放量1（9，108 Tg）的88%（图1）。使这种情况更加严重的是，退化造成的CO2排放并非都是即时的。退化的森林多年来继续排放比吸收更多的二氧化碳，成为重要的碳源2，10。所有亚马逊国家都必须停止这些排放。这就要求向《联合国气候变化框架公约》（《气候公约》）报告所有二氧化碳排放量，包括森林退化。如果忽略或低估任何排放源，那么计算出的所需减缓量将不足以防止全球变暖。量化降解过程造成的碳损失是一项艰巨的任务。退化森林面积估计数以及每种干扰如何影响碳通量，都存在相当大的不确定性。这些不确定性，但是，可以减少相结合的实地测量7，10与不断增加的遥感数据集和方法，自20055年以来，提高了我们的能力，执行大规模监测退化过程在空间和时间维度1 - 4，8，9。改进对森林退化的时空估计可以提供宝贵的信息，以更好地查明和量化与退化有关的碳排放。更准确和更现实的模型将使受益0 500 1，000 1，500 2，000 2，500 3，000 a
To the Editor — Nations will reaffirm their commitment to reducing greenhouse gas (GHG) emissions during the 26th United Nations Climate Change Conference (COP26; www.ukcop26.org), in Glasgow, Scotland, in November 2021. Revision of the national commitments will play a key role in defining the future of Earth’s climate. In past conferences, the main target of Amazonian nations was to reduce emissions resulting from land-use change and land management by committing to decrease deforestation rates, a well-known and efficient strategy1,2. However, human-induced forest degradation caused by fires, selective logging, and edge effects can also result in large carbon dioxide (CO2) emissions1–5, which are not yet explicitly reported by Amazonian countries. Despite its considerable impact, forest degradation has been largely overlooked in previous policy discussions5. It is vital that forest degradation is considered in the upcoming COP26 discussions and incorporated into future commitments to reduce GHG emissions. Human-induced forest degradation is the main driver of socio-environmental impoverishment6,7 in Amazonia, and its extent is increasing8. Degraded forests currently occupy an area larger than that which has been deforested8,9. During the 2003–2015 period in the Brazilian Amazon, CO2 committed emissions from forest fires1 (5,904 Tg) and edge effects2 (2,068 Tg) reached 88% of the gross deforestation emissions1 (9,108 Tg) (Fig. 1). Aggravating this scenario, the CO2 emissions resulting from degradation are not all immediate. Degraded forests continue to emit more CO2 than they absorb for many years, becoming significant carbon sources2,10. It is critically important for all Amazonian countries to halt these emissions. This requires reporting the whole range of CO2 emissions to the United Nations Framework Convention on Climate Change (UNFCCC), including forest degradation. If any emission source is ignored or underestimated, then the calculated amount of mitigation needed will be insufficient to prevent global warming. Quantifying the carbon losses attributable to degradation processes is a difficult task. There are considerable uncertainties associated with degraded-forest area estimates and how each type of disturbance affects carbon fluxes. These uncertainties, however, can be reduced by combining field measurements7,10 with an ever-increasing array of remote-sensing datasets and methods that since 20055 have enhanced our capacity to perform large-scale monitoring of degradation processes across both space and time dimensions1–4,8,9. Improved spatio-temporal estimates of forest degradation can provide valuable information to better identify and quantify degradation-related carbon emissions. More accurate and realistic models would benefit 0 500 1,000 1,500 2,000 2,500 3,000 a
影响因子：
13.6
作者：
Silva Junior CHL;Aragão LEOC;Anderson LO;Fonseca MG;Shimabukuro YE;Vancutsem C;Achard F;Beuchle R;Numata I;Silva CA;Maeda EE;Longo M;Saatchi SS
通讯作者：
Saatchi SS
估计被烧毁的亚马逊森林的数十年碳赤字
影响因子：
6.7
作者：
Silva, Camila V;Aragão, Luiz E;Young, Paul J;Espirito-Santo, Fernando;Berenguer, Erika;Anderson, Liana O;Brasil, Izaias;Pontes-Lopes, Aline;Ferreira, Joice;Withey, Kieran
通讯作者：
Withey, Kieran