Influence of the vegetation restoration age on the soil detachment of root–soil composites on the Loess Plateau of China

黄土高原 植被(病理学) 中国 黄土 高原(数学) 地质学 土壤科学 环境科学 地貌学 地理 考古 医学 数学分析 数学 病理
作者
Jianye Ma,Sijing Zhang,Fangtao She,Xiaofeng Zhao,Bo Ma,Haibo Li,Chenguang Wang,Yongze Shang,Zhanbin Li
出处
期刊:European Journal of Soil Science [Wiley]
卷期号:75 (6)
标识
DOI:10.1111/ejss.70011
摘要

Abstract Vegetation restoration processes significantly affect near‐surface characteristics, thus affecting soil detachment. Existing research has primarily focused on analysing soil detachment via root morphological parameters and soil physical and chemical properties. However, few studies have focused on analysing the variation in soil detachment with restoration age from a mechanical parameter perspective. Natural, undisturbed soil samples were collected from five grasslands restored for 1–22 years and from one bare plot (0 years of restoration, employed as the control). The collected samples were subjected to flow scouring in hydraulic flume experiments under six stream powers. The relationship between the soil detachment rate (SDR) and the mechanical parameters of the root–soil composites, namely root cohesion and soil shear strength ( τ 200 ), were quantified to reveal the mechanical mechanism underlying soil detachment during vegetation restoration. The results indicated that the SDR decreased, whereas root cohesion increased with increasing vegetation restoration age. The dominant factors influencing the SDR changed from hydrodynamics at the early restoration stage to the mechanical properties of the root–soil composites at the late stage. An SDR model with a high prediction accuracy (Nash–Sutcliffe efficiency = 0.96 and R 2 = 0.96) was developed based on mechanical parameters, and the fitting effect was greater than that of the SDR prediction model developed based on root morphological parameters and soil physical and chemical properties. This study aimed to analyse the SDR variation mechanism from the perspective of mechanics and could provide reference for the study of the erosion reduction effect of roots.
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
kb发布了新的文献求助10
刚刚
dafwfwaf完成签到,获得积分20
刚刚
Snow完成签到 ,获得积分10
1秒前
1秒前
CC发布了新的文献求助10
1秒前
小苏打完成签到,获得积分10
2秒前
Xiaoxiao应助程琳采纳,获得10
2秒前
ycc完成签到 ,获得积分10
2秒前
畏寒的北完成签到,获得积分10
3秒前
爆米花应助单纯的雅香采纳,获得10
3秒前
俭朴的玉兰完成签到 ,获得积分10
3秒前
4秒前
4秒前
5秒前
5秒前
5秒前
adazbd发布了新的文献求助10
5秒前
Jenny应助木头人采纳,获得10
5秒前
ATAYA完成签到,获得积分10
6秒前
6秒前
畏寒的北发布了新的文献求助10
6秒前
6秒前
7秒前
地下室没有鬼完成签到 ,获得积分10
7秒前
whh123完成签到 ,获得积分10
7秒前
天天快乐应助空禅yew采纳,获得10
8秒前
在水一方应助开心采纳,获得10
9秒前
Akim应助王w采纳,获得10
9秒前
towerman发布了新的文献求助10
9秒前
畅快平蓝完成签到,获得积分10
9秒前
大棒槌发布了新的文献求助10
10秒前
10秒前
Ann完成签到,获得积分10
10秒前
今今发布了新的文献求助10
11秒前
123123完成签到 ,获得积分10
11秒前
SciGPT应助伊酒采纳,获得10
12秒前
何糖发布了新的文献求助10
13秒前
ding应助SEV采纳,获得10
13秒前
田様应助csq采纳,获得10
13秒前
dafwfwaf发布了新的文献求助10
13秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527961
求助须知:如何正确求助?哪些是违规求助? 3108159
关于积分的说明 9287825
捐赠科研通 2805882
什么是DOI,文献DOI怎么找? 1540070
邀请新用户注册赠送积分活动 716926
科研通“疑难数据库(出版商)”最低求助积分说明 709808