Detecting vegetation stress in mixed forest ecosystems through the joint
use of tree-water monitoring and land surface modeling
Abstract
Recent 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.