Upward expansion and acceleration of forest clearance in the mountains of Southeast Asia

生物多样性 地理 气候变化 碳储量 雨林 森林覆盖 自然地理学 环境科学 农林复合经营 林业 生态学 生物
作者
Yu Feng,Alan D. Ziegler,Paul R. Elsen,Yang Liu,Xinyue He,Dominick V. Spracklen,Joseph Holden,Xin Jiang,Chunmiao Zheng,Zhenzhong Zeng
出处
期刊:Nature sustainability [Nature Portfolio]
卷期号:4 (10): 892-899 被引量:112
标识
DOI:10.1038/s41893-021-00738-y
摘要

Southeast Asia contains about half of all tropical mountain forests, which are rich in biodiversity and carbon stocks, yet there is debate as to whether regional mountain forest cover has increased or decreased in recent decades. Here, our analysis of high-resolution satellite datasets reveals increasing mountain forest loss across Southeast Asia. Total mean annual forest loss was 3.22 Mha yr−1 during 2001–2019, with 31% occurring on the mountains. In the 2010s, the frontier of forest loss moved to higher elevations (15.1 ± 3.8 m yr−1 during 2011–2019, P < 0.01) and steeper slopes (0.22 ± 0.05° yr−1 during 2009–2019, P < 0.01) that have high forest carbon density relative to the lowlands. These shifts led to unprecedented annual forest carbon loss of 424 Tg C yr−1, accelerating at a rate of 18 ± 4 Tg C yr−2 (P < 0.01) from 2001 to 2019. Our results underscore the immediate threat of carbon stock losses associated with accelerating forest clearance in Southeast Asian mountains, which jeopardizes international climate agreements and biodiversity conservation. Southeast Asia contains half the world’s tropical mountain forests. This study finds increasing mountain forest loss there, with the clearing frontier moving higher in the 2010s and causing unprecedented carbon loss.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
drsaidu完成签到,获得积分10
1秒前
激动的访文完成签到,获得积分0
2秒前
欢欢完成签到,获得积分10
3秒前
suyaaaaa发布了新的文献求助10
4秒前
joleisalau发布了新的文献求助10
4秒前
Owen应助sht采纳,获得10
8秒前
科研通AI6.1应助龚佳豪采纳,获得30
9秒前
小张呢好完成签到,获得积分10
10秒前
10秒前
image完成签到,获得积分10
12秒前
12秒前
应樱完成签到 ,获得积分10
12秒前
牛牛发布了新的文献求助10
13秒前
思柔完成签到,获得积分10
13秒前
无极微光应助joleisalau采纳,获得20
14秒前
OK完成签到,获得积分10
16秒前
17秒前
17秒前
20秒前
LIUJIE完成签到,获得积分10
21秒前
顺顺利利毕业关注了科研通微信公众号
22秒前
joleisalau完成签到,获得积分10
23秒前
xy发布了新的文献求助10
24秒前
zyw完成签到,获得积分10
26秒前
寒月完成签到,获得积分10
27秒前
橙橙发布了新的文献求助30
27秒前
无机完成签到,获得积分10
27秒前
27秒前
所所应助AHA采纳,获得10
28秒前
帅气绝施完成签到,获得积分10
30秒前
30秒前
小二郎应助小锦采纳,获得10
32秒前
HJK发布了新的文献求助10
32秒前
allezallez完成签到,获得积分10
34秒前
科研girl应助朱佳慧采纳,获得10
38秒前
蓝莓橘子酱应助Athena采纳,获得30
41秒前
苗条白枫完成签到 ,获得积分10
43秒前
丘比特应助xy采纳,获得10
43秒前
lazyyangyang完成签到,获得积分10
44秒前
44秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Photodetectors: From Ultraviolet to Infrared 500
On the Dragon Seas, a sailor's adventures in the far east 500
Yangtze Reminiscences. Some Notes And Recollections Of Service With The China Navigation Company Ltd., 1925-1939 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6356387
求助须知:如何正确求助?哪些是违规求助? 8171252
关于积分的说明 17203615
捐赠科研通 5412291
什么是DOI,文献DOI怎么找? 2864564
邀请新用户注册赠送积分活动 1842098
关于科研通互助平台的介绍 1690360