Wang et al. (2025) Seasonal divergence in the sensitivity of carbon and water fluxes to climate variability in terrestrial ecosystems

Identification

• Journal: Agricultural and Forest Meteorology
• Year: 2025
• Date: 2025-11-01
• Authors: Ting Wang, Zheng Fu, David Makowski, Guopeng Liang, Hongxiao Jin, Fangyue Zhang
• DOI: 10.1016/j.agrformet.2025.110916

Research Groups

• Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
• College of Agriculture and Biology, Liaocheng University, Liaocheng, China
• Unit Applied Mathematics and Computer Science (UMR MIA-PS) INRAE AgroParisTech Universit´e Paris-Saclay, Palaiseau, France
• Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA
• Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
• College of Water Sciences, Beijing Normal University, Beijing, China

Short Summary

This study quantifies the seasonal sensitivity of daily carbon and water fluxes (GPP, RE, NEP, ET) to hydroclimate factors across diverse biomes globally using eddy covariance observations and Earth System Models (ESMs). It reveals significant seasonal variations in these sensitivities, identifying dominant climate drivers for different fluxes in different seasons and an increasing water limitation for summer GPP.

Objective

• To quantify the seasonal sensitivity of daily gross primary productivity (GPP), ecosystem respiration (RE), net ecosystem productivity (NEP), and evapotranspiration (ET) to various hydroclimate factors (air temperature, radiation, soil water content, and vapor pressure deficit) across diverse biomes and climates globally.

Study Configuration

• Spatial Scale: Global, utilizing 196 eddy covariance flux sites distributed across diverse biomes and climates.
• Temporal Scale: Daily estimates, analyzed for seasonal variations and long-term trends in sensitivity.

Methodology and Data

• Models used: Earth System Models (ESMs)
• Data sources: 196 eddy covariance observations from global sensor networks.

Main Results

• Carbon and water fluxes exhibit significant seasonal variations in sensitivity to hydroclimate factors across global flux sites.
• Gross Primary Productivity (GPP) and Net Ecosystem Productivity (NEP) are most sensitive to air temperature (TA) in spring, but to radiation (RAD) in summer, autumn, and winter.
• Ecosystem Respiration (RE) consistently shows positive sensitivity to TA across all seasons.
• Evapotranspiration (ET) demonstrates the highest sensitivity to RAD throughout the year.
• While energy-related factors (TA, RAD) dominate at sub-seasonal scales, soil water content (SWC) and vapor pressure deficit (VPD) become increasingly important during summer, especially in drylands.
• Long-term measurements reveal a significant upward trend in the sensitivity of summer GPP to SWC, increasing by 0.005 ± 0.002 per year, indicating growing water stress on terrestrial ecosystems during summer.
• Compared to observations, ESMs generally overestimate the sensitivity of GPP to SWC and VPD, while underestimating its sensitivity to RAD and TA during summer.

Contributions

• Enhanced the understanding of the seasonal response of ecosystem carbon and water cycles to hydroclimate factors across diverse biomes globally.
• Identified specific seasonal shifts in the dominant hydroclimate drivers for GPP, NEP, RE, and ET.
• Provided evidence for an increasing constraint of water stress on summer GPP in terrestrial ecosystems over time.
• Offered a critical comparison of Earth System Model performance against observational data regarding the seasonal sensitivity of carbon and water fluxes.

Funding

Not specified in the provided text.

Citation

@article{Wang2025Seasonal,
  author = {Wang, Ting and Fu, Zheng and Makowski, David and Liang, Guopeng and Jin, Hongxiao and Zhang, Fangyue},
  title = {Seasonal divergence in the sensitivity of carbon and water fluxes to climate variability in terrestrial ecosystems},
  journal = {Agricultural and Forest Meteorology},
  year = {2025},
  doi = {10.1016/j.agrformet.2025.110916},
  url = {https://doi.org/10.1016/j.agrformet.2025.110916}
}