Detecting Vegetation Stress in Mixed Forest Ecosystems Through the Joint Use of Tree‐Water Monitoring and Land Surface Modeling

Author:

Jiménez‐Rodríguez C. D.1ORCID,Fabiani G.1,Schoppach R.1,Mallick K.1,Schymanski S. J.1ORCID,Sulis M.1ORCID

Affiliation:

1. Environmental Research and Innovation (ERIN) Department Luxembourg Institute of Science and Technology (LIST) Belvaux Luxembourg

Abstract

AbstractRecent European heatwaves have significantly impacted forest ecosystems, leading to increased plant water stress. Advances in land surface models aim to improve the representation of vegetation drought responses by incorporating plant hydraulics into the plant functional type (PFT) classification system. However, reliance on PFTs may inadequately capture the diverse plant hydraulic traits (PHTs), potentially biasing transpiration and vegetation water stress representations. The detection of vegetation drought stress is further complicated by the mixing of different tree species and forest patches. This study uses the Community Land Model version 5.0 to simulate an experimental mixed‐forest catchment with configurations representing standalone, patched mixed, and fully‐mixed forests. Biome‐generic, PFT‐specific, or species‐specific PHTs are employed. Results emphasize the crucial role of accurately representing mixed forests in reproducing observed vegetation water stress and transpiration fluxes for both broadleaf and needleleaf tree species. The dominant vegetation fraction is a key determinant, influencing aggregated vegetation response patterns. Segregation level in PHT parameterizations shapes differences between observed and simulated transpiration fluxes. Simulated root water potential emerges as a potential metric for detecting vegetation stress periods. However, the model's plant hydraulic system has limitations in reproducing the long‐term effects of extreme weather events on needleleaf tree species. These findings highlight the complexity of modeling mixed forests and underscore the need for improved representation of plant diversity in land surface models to enhance the understanding of vegetation water stress under changing climate conditions.

Publisher

American Geophysical Union (AGU)

Reference182 articles.

1. LiDAR 2019—Relevé 3D du Territoire Luxembourgeois;ACT;Administration du Cadastre et de la Topographie (ACT). Le Gouvernement du Grand‐Duché de Luxembourg,2020

2. Implementing a New Rubber Plant Functional Type in the Community Land Model (CLM5) Improves Accuracy of Carbon and Water Flux Estimation

3. Rapid hydraulic collapse as cause of drought-induced mortality in conifers

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3