Ding et al. (2026) Long-term increases in tree water-use efficiency across China are associated with CO2 and hydroclimatic variation

Identification

• Journal: Journal of Hydrology
• Year: 2026
• Date: 2026-07-26
• Authors: Yali Ding, Li Wen, Jingzhi Zhang, Wei Zhang, Hongsong Chen, Shanshan Song, Zongrui Lai, Jinxing Zhou, Guanghui Lin
• DOI: 10.1016/j.jhydrol.2026.136114

Research Groups

• School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
• Science and Insights Division, Department of Climate Change, Energy, the Environment and Water, Parramatta, NSW 2150, Australia
• Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
• Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China
• Huanjiang Observation and Research Station for Karst Ecosystems, Chinese Academy of Sciences, Huanjiang 547100, Guangxi, China
• Guangxi Key Laboratory of Forest Ecology and Conservation, School of Forestry, Guangxi University, Nanning 530004, China

Short Summary

This study investigated long-term intrinsic tree water-use efficiency (iWUE) trajectories across China during the 20th century, quantifying the interactive effects of atmospheric CO2 and hydroclimatic variability using tree-ring δ13C data and a novel statistical approach to address CO2-time collinearity. It found significant iWUE increases and strong hydroclimate-dependent responses of iWUE to non-trend CO2 deviations.

Objective

• To examine long-term intrinsic tree water-use efficiency (iWUE) trajectories across China's major biogeographic zones during the 20th century.
• To test whether non-trend CO2 deviations were associated with iWUE after accounting for zone-specific temporal trends and hydroclimatic variation, specifically addressing the collinearity between atmospheric CO2 and calendar year.

Study Configuration

• Spatial Scale: Nationwide across China's major biogeographic zones.
• Temporal Scale: The 20th century (approximately 100 years).

Methodology and Data

• Models used: Generalized additive mixed models (GAMMs) with zone-specific year smooths, tree-level random effects, and AR(1) temporal correlation. Atmospheric CO2 was decomposed into a long-term trend and residual deviations (CO2_resid).
• Data sources: Nationwide tree-ring δ13C dataset.

Main Results

• Intrinsic water-use efficiency (iWUE) increased markedly across all biogeographic zones in China over the 20th century.
• The developed statistical framework effectively reduced collinearity between CO2 and time, allowing more stable inference about non-trend CO2 associations.
• Positive non-trend CO2 deviations were associated with higher iWUE under lower annual precipitation contexts.
• The effects of non-trend CO2 deviations on iWUE were weak under intermediate precipitation and attenuated or slightly reversed under the highest annual precipitation contexts.
• Temperature exerted weaker moderating effects on iWUE responses to CO2 deviations compared to precipitation.
• CO2-related iWUE responses are strongly hydroclimate-dependent.

Contributions

• Provides a robust statistical framework for separating long-term temporal trends from short-term CO2 variability in tree-ring studies, effectively addressing the collinearity issue between CO2 and calendar year.
• Highlights the critical importance of moisture context (precipitation) in modulating forest carbon–water coupling responses to CO2 variability.
• Offers novel insights into the interactive effects of rising atmospheric CO2 and hydroclimatic variability on long-term iWUE across China.

Funding

• The provided paper text does not explicitly list funding projects, programs, or reference codes.

Citation

@article{Ding2026Longterm,
  author = {Ding, Yali and Wen, Li and Zhang, Jingzhi and Zhang, Wei and Chen, Hongsong and Song, Shanshan and Lai, Zongrui and Zhou, Jinxing and Lin, Guanghui},
  title = {Long-term increases in tree water-use efficiency across China are associated with CO2 and hydroclimatic variation},
  journal = {Journal of Hydrology},
  year = {2026},
  doi = {10.1016/j.jhydrol.2026.136114},
  url = {https://doi.org/10.1016/j.jhydrol.2026.136114}
}