Zonal patterns and driving factors of soil organic carbon density in Zhejiang Province, China

土壤碳 环境科学 高度(三角形) 土地利用 植被(病理学) 陆地生态系统 经度 自然地理学 降水 生态系统 驱动因素 土地利用、土地利用的变化和林业 中国 全球变化 地理 纬度 气候变化 生态学 土壤科学 土壤水分 气象学 医学 几何学 数学 大地测量学 病理 考古 生物
作者
Xuqing Li,Fĕi Li,Dan Wang,Jianfeng Hou,Zhihui Wang,Rui Cao,Wanqin Yang
出处
期刊:Geoderma Regional [Elsevier BV]
卷期号:34: e00679-e00679
标识
DOI:10.1016/j.geodrs.2023.e00679
摘要

The complex topography and intensive land use and land cover change (LUCC) might shift the spatial pattern of soil organic carbon (SOC) density. However, the effects of LUCC caused by development on the distribution and driving factors of SOC density remain unclear. As one of the most developed regions in China, Zhejiang Province has experienced intensive land use change and has various vegetation types, making it an ideal location to analyse the zonal pattern and driving factors of SOC density in terrestrial ecosystems. To do that, a dataset was built with data collected from existing literature. The average SOC density in Zhejiang Province was 69.75 Mg ha−1, ranging widely from 6.44 to 301.90 Mg ha−1 depending on land and vegetation types. We found that forests had the highest mean SOC density (78.30 Mg ha−1), while cropland had the lowest (45.69 Mg ha−1). Meanwhile, the SOC density of unmanaged land was significantly higher than that of managed land (P < 0.001). Additionally, SOC density varied greatly with longitude and altitude, showing a decreasing zonal pattern from west to east and from high to low altitude. The RF model indicated that vegetation type, stand age, mean annual temperature (MAT), soil pH, and mean annual precipitation (MAP) were the five most important factors affecting SOC density in this area, but the effects differed between managed and unmanaged lands. These results aid with understanding the dynamics of SOC pools in terrestrial ecosystems and inform policy-making to mitigate global climate change. These findings provide valuable insights into the dynamics of SOC pools in terrestrial ecosystems, enabling more effective policymaking to mitigate the impact of global climate change.

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
科研小白发布了新的文献求助10
刚刚
咖啡豆发布了新的文献求助10
刚刚
1秒前
1秒前
1秒前
皮皮发布了新的文献求助10
1秒前
2秒前
Fighter完成签到,获得积分20
2秒前
Ly1完成签到,获得积分10
2秒前
2秒前
2秒前
开朗成风完成签到 ,获得积分10
3秒前
chen发布了新的文献求助10
4秒前
4秒前
4秒前
无极微光应助HH采纳,获得20
4秒前
swallow完成签到,获得积分10
4秒前
儒雅的谷兰完成签到 ,获得积分10
5秒前
米里迷路完成签到,获得积分10
5秒前
pluto应助尔蓝红颜采纳,获得10
5秒前
英吉利25发布了新的文献求助10
5秒前
5秒前
无风风发布了新的文献求助10
6秒前
搜集达人应助Nice采纳,获得10
6秒前
7秒前
人人发布了新的文献求助10
7秒前
Ppxc发布了新的文献求助10
7秒前
阔达黎云发布了新的文献求助10
8秒前
8秒前
8秒前
8秒前
hanshuo4400发布了新的文献求助10
9秒前
Rencal完成签到 ,获得积分10
9秒前
决明完成签到,获得积分10
9秒前
嘉熠完成签到,获得积分10
9秒前
ketaman发布了新的文献求助10
10秒前
10秒前
紧张的幻柏应助小王采纳,获得10
10秒前
hh完成签到,获得积分20
10秒前
一盒苦发布了新的文献求助30
11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
Picture this! Including first nations fiction picture books in school library collections 2000
The Cambridge History of China: Volume 4, Sui and T'ang China, 589–906 AD, Part Two 1500
Cowries - A Guide to the Gastropod Family Cypraeidae 1200
Quality by Design - An Indispensable Approach to Accelerate Biopharmaceutical Product Development 800
ON THE THEORY OF BIRATIONAL BLOWING-UP 666
Signals, Systems, and Signal Processing 610
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 6391646
求助须知:如何正确求助?哪些是违规求助? 8207042
关于积分的说明 17371721
捐赠科研通 5445303
什么是DOI,文献DOI怎么找? 2878864
邀请新用户注册赠送积分活动 1855331
关于科研通互助平台的介绍 1698531