Spatiotemporal patterns of carbon storage in forest ecosystems in Hunan Province, China

固碳 森林生态学 生态系统 环境科学 生物量(生态学) 碳汇 常绿森林 常绿 森林资源清查 水槽(地理) 森林经营 农林复合经营 林业 生态学 地理 二氧化碳 生物 地图学
作者
Longchi Chen,Xin Guan,Haimei Li,Qingkui Wang,Weidong Zhang,Qingpeng Yang,Silong Wang
出处
期刊:Forest Ecology and Management [Elsevier BV]
卷期号:432: 656-666 被引量:61
标识
DOI:10.1016/j.foreco.2018.09.059
摘要

Forest ecosystems act as a carbon sink and contribute to climate change mitigation. Research on the spatiotemporal patterns of C storage and density in forest ecosystems is essential to understand the role of forest ecosystems in the C sink and is helpful to select the efficient forest management practice to maximize the C sequestration potential. We quantified the C storage in forest ecosystems in Hunan Province in southern China over two decades by combining forest inventory data with field survey. The C storage in forest ecosystems in Hunan Province increased from 820.2 Tg to 1277.8 Tg over the two decades, with 457.6 Tg (134.4 Tg in vegetation and 323.2 Tg in soil) of C sequestration in the forest ecosystems. Forest C storage increased sharply from 1996 to 2007, but slowly from 2007 to 2015. The mean annual C sequestration was 25.8 Tg yr−1, with 19.0 Tg yr−1 in soil and 6.8 Tg yr−1 in vegetation. The C density in forest ecosystems increased from 110.3 Mg ha−1 in 1996 to 130.8 Mg ha−1 in 2013. C densities varied in forest types, with the highest value in evergreen broadleaved forest ecosystems. The uneven spatial distributions of forest C storage, density, and sequestration in Hunan Province exhibited similar pattern with the highest in the western Hunan and the lowest in the central Hunan. The forest ecosystems in Hunan Province present a significant C sequestration potential (1321.5 Tg, including 1029.2 Tg in biomass C and 292.3 Tg in soil C), given the proportion of the area of young and middle-aged forests (71.3%). To maximize the C sequestration potential of forest ecosystems in Hunan Province, future forest management should focus on the conversion of forest type, the selection of tree species in reforestation, and the prevention of adverse human disturbances in young and middle-aged forests.

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
hsn发布了新的文献求助10
刚刚
小鲨鱼发布了新的文献求助10
1秒前
Jasper应助生动初南采纳,获得10
1秒前
1秒前
1秒前
2秒前
2秒前
yudu完成签到,获得积分20
2秒前
3秒前
3秒前
4秒前
x菜鸡博士应助专注的灵薇采纳,获得10
5秒前
乐乐应助alaska采纳,获得10
5秒前
5秒前
无花果应助kamisama采纳,获得10
5秒前
一一发布了新的文献求助10
6秒前
小二郎应助Billy采纳,获得20
6秒前
sanvva应助arniu2008采纳,获得200
7秒前
泡芙完成签到,获得积分10
7秒前
pluto应助AMLYB666采纳,获得10
8秒前
奈莫123发布了新的文献求助10
9秒前
小鲨鱼完成签到,获得积分10
9秒前
四月发布了新的文献求助10
10秒前
LX发布了新的文献求助10
10秒前
核桃发布了新的文献求助10
10秒前
万能图书馆应助chenying采纳,获得10
11秒前
11秒前
Akim应助药007采纳,获得10
11秒前
lin完成签到,获得积分10
12秒前
泡芙发布了新的文献求助20
13秒前
央央发布了新的文献求助10
13秒前
田様应助SIMONLIANG采纳,获得10
13秒前
辣辣发布了新的文献求助10
13秒前
kiyo完成签到,获得积分20
14秒前
wanci应助火星上的寒安采纳,获得10
14秒前
15秒前
15秒前
FashionBoy应助咔咔采纳,获得10
15秒前
15秒前
NexusExplorer应助科研通管家采纳,获得30
16秒前
高分求助中
Cronologia da história de Macau 5000
Matrix Methods in Data Mining and Pattern Recognition 510
C语言程序设计(微课版) 500
Interactions of Vowel Quality and Prosody in East Slavic 500
Vander's Renal Physiology第10版 500
Forensic Science An Introduction to Scientific and Investigative Techniques 6th Edition 400
Reaction of 3-Methylenedihydro-(3H)furan-2-one with Diazoalkanes. Syntheses and Crystal Structures of Spiranic Cyclopropyl Compounds 400
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 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7095943
求助须知:如何正确求助?哪些是违规求助? 8752421
关于积分的说明 18512229
捐赠科研通 6649671
什么是DOI,文献DOI怎么找? 3137816
关于科研通互助平台的介绍 2246163
邀请新用户注册赠送积分活动 2112652