Global patterns and drivers of soil dissolved organic carbon concentrations

土壤碳 溶解有机碳 环境科学 环境化学 总有机碳 碳纤维 碳循环 土壤科学 地球科学 土壤水分 化学 地质学 生态系统 生态学 材料科学 生物 复合数 复合材料
作者
Tianjing Ren,Andong Cai
标识
DOI:10.5194/essd-2024-343
摘要

Abstract. Dissolved organic carbon (DOC) is the most active carbon pool in soils, which plays critical roles in soil carbon cycling, plant productivity, and global climate change. An accurate assessment of the quantity of DOC in the soil is essential for the detailed elucidation of ecosystem functions and services. Nevertheless, the global driving factors and distribution of soil DOC remain inadequately quantified due to the scarcity of large-scale data. Here, a comprehensive global database of 12807 soil DOC concentrations derived from 975 target papers in the literature was compiled. Detailed geographic locations, climate, and soil properties were also recorded as predictors of soil DOC. Machine learning techniques were employed to assess the relative importance of various predictors in the determination of soil DOC concentrations, which were subsequently extended for their prediction on a global scale. The worldwide soil DOC concentration spanned a wide range (0.04 to 7859 mg kg-1), averaging 222.78 mg kg-1. The 12 selected variables (including soil properties, month, climate, and ecosystem) explained 65 % of the variance in soil DOC concentrations. Elevation, soil clay, and soil organic carbon were three of the most important predictors. Global soil DOC concentration increased from the equator to the poles. The soil DOC stocks in the topsoil layer (0–30 cm) amounted to 12.17 Pg, with significant variations observed across different continents. These results are instrumental for informing strategies on soil management practices, ecosystem services, and the mitigation of climate change. Furthermore, our database can be combined with other carbon pools to explore the total soil carbon turnover and constrain Earth carbon models. The dataset is publicly available at https://doi.org/10.6084/m9.figshare.26379898 (Ren and Cai, 2024).

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
NCU-Xzzzz发布了新的文献求助10
1秒前
孟寐以求发布了新的文献求助10
4秒前
5秒前
啊凡发布了新的文献求助10
6秒前
彭于晏应助依霏采纳,获得10
6秒前
胡萝卜须发布了新的文献求助10
9秒前
lq1024424发布了新的文献求助10
9秒前
科研通AI2S应助poki采纳,获得10
10秒前
11秒前
11秒前
烟花应助萧羽采纳,获得10
13秒前
16秒前
舒心的诗云完成签到,获得积分10
16秒前
我是老大应助啊凡采纳,获得10
16秒前
依霏完成签到,获得积分10
17秒前
小鱼不干发布了新的文献求助10
17秒前
17秒前
zl给zl的求助进行了留言
18秒前
20秒前
SHAM发布了新的文献求助10
21秒前
23秒前
义气鞋子完成签到,获得积分10
25秒前
深情安青应助后会无期采纳,获得10
26秒前
26秒前
erniu发布了新的文献求助10
26秒前
水瑟完成签到,获得积分10
27秒前
跳跃的浩阑完成签到,获得积分10
28秒前
义气鞋子发布了新的文献求助10
29秒前
南陌发布了新的文献求助10
29秒前
32秒前
三千世界完成签到,获得积分10
33秒前
33秒前
魔幻的雁风完成签到,获得积分10
33秒前
36秒前
C·麦塔芬完成签到,获得积分10
36秒前
情怀应助1234采纳,获得10
36秒前
子车烙发布了新的文献求助10
36秒前
wahaha发布了新的文献求助10
37秒前
38秒前
41秒前
高分求助中
求助这个网站里的问题集 1000
Floxuridine; Third Edition 1000
Models of Teaching(The 10th Edition,第10版!)《教学模式》(第10版!) 800
La décision juridictionnelle 800
Rechtsphilosophie und Rechtstheorie 800
Nonlocal Integral Equation Continuum Models: Nonstandard Symmetric Interaction Neighborhoods and Finite Element Discretizations 500
Academic entitlement: Adapting the equity preference questionnaire for a university setting 500
热门求助领域 (近24小时)
化学 医学 材料科学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 免疫学 细胞生物学 电极
热门帖子
关注 科研通微信公众号,转发送积分 2871220
求助须知:如何正确求助?哪些是违规求助? 2479040
关于积分的说明 6718308
捐赠科研通 2165843
什么是DOI,文献DOI怎么找? 1150668
版权声明 585640
科研通“疑难数据库(出版商)”最低求助积分说明 564989