Spatial variability and driving factors of soil multifunctionality in drylands of China

Q1 Social Sciences
Shihang Zhang , Yusen Chen , Yongxing Lu , Hao Guo , Xing Guo , Chaohong Liu , Xiaobing Zhou , Yuanming Zhang
{"title":"Spatial variability and driving factors of soil multifunctionality in drylands of China","authors":"Shihang Zhang ,&nbsp;Yusen Chen ,&nbsp;Yongxing Lu ,&nbsp;Hao Guo ,&nbsp;Xing Guo ,&nbsp;Chaohong Liu ,&nbsp;Xiaobing Zhou ,&nbsp;Yuanming Zhang","doi":"10.1016/j.regsus.2022.10.001","DOIUrl":null,"url":null,"abstract":"<div><p>Drylands are highly vulnerable to climate change and human activities. The drylands of China account for approximately 10.8% of global drylands, and China is the country most severely affected by aridity in Asia. Therefore, studying the spatial variation characteristics in soil multifunctionality (SMF) and investigating the driving factors are critical for elucidating and managing the functions of dryland ecosystems in China. Based on the environmental factors (mean annual precipitation (MAP), mean annual temperature (MAT), solar radiation (Srad), soil acidity (pH), enhanced vegetation index (EVI), and cation exchange capacity (CEC)) and aridity from the Dataset of soil properties for land surface modeling over China, we used non-linear regression, ordinary least square (OLS) regression, structural equation model (SEM), and other analytical methods to investigate the relationships of SMF with environmental factors across different aridity levels in China. SMF in different dryland regions varied significantly and showed a patchy distribution, with SMF index values ranging from −1.21 to 2.42. Regions with SMF index values from −0.20 to 0.51 accounting for 63.0% of dryland area in China. OLS regression results revealed that environmental factors like MAP, MAT, Srad, pH, EVI, and CEC were significantly related to SMF (<em>P</em> ​&lt; ​0.05). MAP and MAT were correlated to SMF at the whole aridity level (<em>P</em> ​&lt; ​0.05). SEM results showed that the driving factors of SMF differed depending on the aridity level. Soil pH was the strongest driving factor of SMF when the aridity was less than 0.80 (<em>P</em> ​&lt; ​0.001). Both soil CEC and EVI had a positive effect on SMF when aridity was greater than 0.80 (<em>P</em> ​&lt; ​0.01), with soil CEC being the strongest driving factor. The importance ranking revealed that the relative importance contribution of soil pH to SMF was greatest when aridity was less than 0.80 (66.9%). When aridity was set to greater than 0.80, the relative importance contributions of CEC and EVI to SMF increased (45.1% and 31.9%, respectively). Our findings indicated that SMF had high spatial heterogeneity in drylands of China. The aridity threshold controlled the impact of environmental factors on SMF.</p></div>","PeriodicalId":34395,"journal":{"name":"Regional Sustainability","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666660X22000500/pdfft?md5=a84a403709303fcedf45e055fb7e5c6d&pid=1-s2.0-S2666660X22000500-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Regional Sustainability","FirstCategoryId":"95","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666660X22000500","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0

Abstract

Drylands are highly vulnerable to climate change and human activities. The drylands of China account for approximately 10.8% of global drylands, and China is the country most severely affected by aridity in Asia. Therefore, studying the spatial variation characteristics in soil multifunctionality (SMF) and investigating the driving factors are critical for elucidating and managing the functions of dryland ecosystems in China. Based on the environmental factors (mean annual precipitation (MAP), mean annual temperature (MAT), solar radiation (Srad), soil acidity (pH), enhanced vegetation index (EVI), and cation exchange capacity (CEC)) and aridity from the Dataset of soil properties for land surface modeling over China, we used non-linear regression, ordinary least square (OLS) regression, structural equation model (SEM), and other analytical methods to investigate the relationships of SMF with environmental factors across different aridity levels in China. SMF in different dryland regions varied significantly and showed a patchy distribution, with SMF index values ranging from −1.21 to 2.42. Regions with SMF index values from −0.20 to 0.51 accounting for 63.0% of dryland area in China. OLS regression results revealed that environmental factors like MAP, MAT, Srad, pH, EVI, and CEC were significantly related to SMF (P ​< ​0.05). MAP and MAT were correlated to SMF at the whole aridity level (P ​< ​0.05). SEM results showed that the driving factors of SMF differed depending on the aridity level. Soil pH was the strongest driving factor of SMF when the aridity was less than 0.80 (P ​< ​0.001). Both soil CEC and EVI had a positive effect on SMF when aridity was greater than 0.80 (P ​< ​0.01), with soil CEC being the strongest driving factor. The importance ranking revealed that the relative importance contribution of soil pH to SMF was greatest when aridity was less than 0.80 (66.9%). When aridity was set to greater than 0.80, the relative importance contributions of CEC and EVI to SMF increased (45.1% and 31.9%, respectively). Our findings indicated that SMF had high spatial heterogeneity in drylands of China. The aridity threshold controlled the impact of environmental factors on SMF.

中国旱地土壤多功能性空间变异及其驱动因素
旱地极易受到气候变化和人类活动的影响。中国旱地约占全球旱地的10.8%,是亚洲受干旱影响最严重的国家。因此,研究土壤多功能性的空间变化特征及其驱动因素对阐明和管理中国旱地生态系统的功能具有重要意义。基于中国大陆土壤特性数据集的环境因子(年平均降水量(MAP)、年平均气温(MAT)、太阳辐射(Srad)、土壤酸度(pH)、增强植被指数(EVI)和阳离子交换容量(CEC))和干旱,采用非线性回归、普通最小二乘(OLS)回归、结构方程模型(SEM)、等分析方法探讨中国不同干旱水平的SMF与环境因子的关系。不同干旱区SMF变化显著,呈斑块状分布,指数范围为- 1.21 ~ 2.42。SMF指数在- 0.20 ~ 0.51之间的区域占中国旱地面积的63.0%。OLS回归结果显示,MAP、MAT、Srad、pH、EVI和CEC等环境因子与SMF (P <0.05)。MAP和MAT在整个干旱水平上与SMF相关(P <0.05)。SEM结果表明,不同干旱程度下,SMF的驱动因素不同。当干旱度小于0.80时,土壤pH值是SMF的最大驱动因子(P <0.001)。当干旱度大于0.80时,土壤CEC和EVI对SMF均有正向影响(P <0.01),土壤CEC是最强驱动因子。重要性排序结果表明,土壤pH值对SMF的相对重要性贡献在干旱度< 0.80时最大(66.9%)。当干旱度大于0.80时,CEC和EVI对SMF的相对重要性贡献增加(分别为45.1%和31.9%)。研究结果表明,中国干旱区草地植被具有高度的空间异质性。干旱阈值控制了环境因子对SMF的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Regional Sustainability
Regional Sustainability Social Sciences-Urban Studies
CiteScore
3.70
自引率
0.00%
发文量
20
审稿时长
21 weeks
文献相关原料
公司名称 产品信息 采购帮参考价格
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信