The Response of Carbon Uptake to Soil Moisture Stress: Adaptation to Climatic Aridity

IF 12 1区 环境科学与生态学 Q1 BIODIVERSITY CONSERVATION Global Change Biology Pub Date : 2025-03-10 DOI:10.1111/gcb.70098
Giulia Mengoli, Sandy P. Harrison, I. Colin Prentice
{"title":"The Response of Carbon Uptake to Soil Moisture Stress: Adaptation to Climatic Aridity","authors":"Giulia Mengoli,&nbsp;Sandy P. Harrison,&nbsp;I. Colin Prentice","doi":"10.1111/gcb.70098","DOIUrl":null,"url":null,"abstract":"<p>The coupling between carbon uptake and water loss through stomata implies that gross primary production (GPP) can be limited by soil water availability through reduced leaf area and/or stomatal conductance. Ecosystem and land-surface models commonly assume that GPP is highest under well-watered conditions and apply a stress function to reduce GPP as soil moisture declines. Optimality considerations, however, suggest that the stress function should depend on climatic aridity: ecosystems adapted to more arid climates should use water more conservatively when soil moisture is high, but maintain unchanged GPP down to a lower critical soil-moisture threshold. We use eddy-covariance flux data to test this hypothesis. We investigate how the light-use efficiency (LUE) of GPP depends on soil moisture across ecosystems representing a wide range of climatic aridity. ‘Well-watered’ GPP is estimated using the sub-daily P model, a first-principles LUE model driven by atmospheric data and remotely sensed vegetation cover. Breakpoint regression is used to relate daily β(θ) (the ratio of flux data–derived GPP to modelled well-watered GPP) to soil moisture estimated via a generic water balance model. The resulting piecewise function describing β(θ) varies with aridity, as hypothesised. Unstressed LUE, even when soil moisture is high, declines with increasing aridity index (AI). So does the critical soil-moisture threshold. Moreover, for any AI value, there exists a soil moisture level at which β(θ) is maximised. This level declines as AI increases. This behaviour is captured by universal non-linear functions relating both unstressed LUE and the critical soil-moisture threshold to AI. Applying these aridity-based functions to predict the site-level response of LUE to soil moisture substantially improves GPP simulation under both water-stressed and unstressed conditions, suggesting a route towards a robust, universal model representation of the effects of low soil moisture on leaf-level photosynthesis.</p>","PeriodicalId":175,"journal":{"name":"Global Change Biology","volume":"31 3","pages":""},"PeriodicalIF":12.0000,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcb.70098","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Change Biology","FirstCategoryId":"93","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/gcb.70098","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIODIVERSITY CONSERVATION","Score":null,"Total":0}
引用次数: 0

Abstract

The coupling between carbon uptake and water loss through stomata implies that gross primary production (GPP) can be limited by soil water availability through reduced leaf area and/or stomatal conductance. Ecosystem and land-surface models commonly assume that GPP is highest under well-watered conditions and apply a stress function to reduce GPP as soil moisture declines. Optimality considerations, however, suggest that the stress function should depend on climatic aridity: ecosystems adapted to more arid climates should use water more conservatively when soil moisture is high, but maintain unchanged GPP down to a lower critical soil-moisture threshold. We use eddy-covariance flux data to test this hypothesis. We investigate how the light-use efficiency (LUE) of GPP depends on soil moisture across ecosystems representing a wide range of climatic aridity. ‘Well-watered’ GPP is estimated using the sub-daily P model, a first-principles LUE model driven by atmospheric data and remotely sensed vegetation cover. Breakpoint regression is used to relate daily β(θ) (the ratio of flux data–derived GPP to modelled well-watered GPP) to soil moisture estimated via a generic water balance model. The resulting piecewise function describing β(θ) varies with aridity, as hypothesised. Unstressed LUE, even when soil moisture is high, declines with increasing aridity index (AI). So does the critical soil-moisture threshold. Moreover, for any AI value, there exists a soil moisture level at which β(θ) is maximised. This level declines as AI increases. This behaviour is captured by universal non-linear functions relating both unstressed LUE and the critical soil-moisture threshold to AI. Applying these aridity-based functions to predict the site-level response of LUE to soil moisture substantially improves GPP simulation under both water-stressed and unstressed conditions, suggesting a route towards a robust, universal model representation of the effects of low soil moisture on leaf-level photosynthesis.

Abstract Image

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
土壤水分胁迫对碳吸收的响应:对气候干旱的适应
通过气孔的碳吸收和水分损失之间的耦合表明,总初级生产(GPP)可能受到土壤水分有效性的限制,因为叶片面积和/或气孔导度减少。生态系统和陆地表面模型通常假设GPP在水分充足的条件下最高,并应用应力函数来降低GPP随着土壤湿度的下降。然而,最优性考虑表明,应力函数应取决于气候干旱:适应更干旱气候的生态系统在土壤湿度高时应更保守地用水,但在较低的土壤湿度临界阈值下保持不变的GPP。我们使用涡流协方差通量数据来检验这一假设。我们研究了GPP的光利用效率(LUE)如何依赖于代表广泛气候干旱的生态系统中的土壤湿度。“水分充足”的GPP使用亚日P模式估算,这是一种由大气数据和遥感植被覆盖驱动的第一线LUE模式。断点回归用于将每日β(θ)(通量数据导出的GPP与模拟的水分充足的GPP的比率)与通过一般水平衡模型估计的土壤湿度联系起来。所得到的描述β(θ)的分段函数如假设的那样随干旱而变化。在土壤湿度较高的情况下,随干旱指数(AI)的增加,非胁迫下的LUE也呈下降趋势。土壤湿度临界值也是如此。此外,对于任何AI值,都存在一个使β(θ)最大化的土壤湿度水平。这个等级随着AI的增加而下降。这种行为可以通过与非应力LUE和临界土壤湿度阈值相关的通用非线性函数来捕捉。利用这些基于干旱的函数来预测LUE对土壤水分的响应,大大改善了水分胁迫和非胁迫条件下的GPP模拟,为建立一个反映低土壤水分对叶片光合作用影响的鲁棒、通用模型提供了一条途径。
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 去求助
来源期刊
Global Change Biology
Global Change Biology 环境科学-环境科学
CiteScore
21.50
自引率
5.20%
发文量
497
审稿时长
3.3 months
期刊介绍: Global Change Biology is an environmental change journal committed to shaping the future and addressing the world's most pressing challenges, including sustainability, climate change, environmental protection, food and water safety, and global health. Dedicated to fostering a profound understanding of the impacts of global change on biological systems and offering innovative solutions, the journal publishes a diverse range of content, including primary research articles, technical advances, research reviews, reports, opinions, perspectives, commentaries, and letters. Starting with the 2024 volume, Global Change Biology will transition to an online-only format, enhancing accessibility and contributing to the evolution of scholarly communication.
期刊最新文献
Increased Contributions of Microbial Extracellular Polymeric Substance to Soil Organic Carbon During Grassland Degradation Rising Global Riverine Deoxygenation Rates and GHG Emissions Driven by the Synergistic Effects of Warming and Anthropogenic Land Use Expansion Effect of Heat Stress on Wheat Quality and Its Heterogeneity: A Global Meta‐Analysis Migrating in a Warming World: A Deep Learning Approach to Predict Pan‐American Seasonal Shifts in the Monarch Butterfly Niche Aligning Nitrogen Form With Rice Preference Through Enhanced‐Efficiency Fertilizers Raises Yield and Cuts Emissions
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1