Liang et al. (2026) Vegetation in Central Asia is more sensitive to soil moisture stress than to precipitation and vapor pressure deficit stresses

Identification

• Journal: Agricultural and Forest Meteorology
• Year: 2026
• Date: 2026-03-26
• Authors: Hongwu Liang, Guli Jiapaer, Cun Chang, Tao Yu, Liancheng Zhang, Pingping Feng, Kaixiong Lin, Tongwei Ju, Xiapeng Jiang, Philippe De Maeyer, Tim Van de Voorde
• DOI: 10.1016/j.agrformet.2026.111140

Research Groups

• State Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China
• University of Chinese Academy of Sciences, Beijing, China
• Xinjiang Key Laboratory of RS & GIS Application, Urumqi, China
• Department of Geography, Ghent University, Ghent, Belgium
• CAS Research Center for Ecology and Environment of Central Asia, Urumqi, China
• Sino-Belgian Joint Laboratory for Geo-Information, Ghent, Belgium
• Sino-Belgian Joint Laboratory for Geo-Information, Urumqi, China

Short Summary

This study investigated vegetation sensitivity to precipitation, soil moisture, and vapor pressure deficit stresses across Central Asia from 1982 to 2020, revealing that vegetation is most sensitive to soil moisture stress, a trend projected to continue increasing in the future.

Objective

• To investigate vegetation sensitivity to precipitation (Pre), soil moisture (SM), and vapor pressure deficit (VPD) stresses across Central Asia (CA) during 1982–2020.
• To project future vegetation sensitivity and its trends using data from the Coupled Model Intercomparison Project Phase 6 (CMIP6).

Study Configuration

• Spatial Scale: Central Asia (CA)
• Temporal Scale: 1982–2020 (historical analysis); Future projections (using CMIP6 data)

Methodology and Data

• Models used: Coupled Model Intercomparison Project Phase 6 (CMIP6) for future projections.
• Data sources: Multiple remote sensing vegetation indices; Meteorological reanalysis data.

Main Results

• Vegetation in Central Asia was most sensitive to soil moisture (SM) stress.
• Mean sensitivities were 0.40 for precipitation (Pre), 0.69 for soil moisture (SM), and 0.44 for vapor pressure deficit (VPD) stresses.
• Vegetation in forests, wetlands, and relatively cold and wet climate zones exhibited slightly lower sensitivity to SM stress but slightly higher sensitivity to VPD stress, yet still showed the highest average sensitivity to SM stress.
• Irrigation significantly reduced crop sensitivity to SM stress, with sensitivity decreasing as irrigation water use increased.
• Vegetation sensitivity to SM stress showed an obvious increasing trend during 1982–2020, while sensitivity trends to Pre and VPD stress were not obvious.
• Trend-shift analysis revealed that 9.27 % of vegetation areas experienced significant shifts in sensitivity trends for Pre, 18.28 % for SM, and 7.10 % for VPD stress, with dominant shift types being decreasing to increasing (D-I) and increasing to increasing (I-I).
• Future projections suggest that vegetation sensitivity to SM stress will remain the highest and continue to increase overall.

Contributions

• Enhances understanding of vegetation responses to different water stresses in Central Asia.
• Provides insights applicable to other arid regions worldwide regarding vegetation sensitivity to water stress.
• Quantifies the relative importance of precipitation, soil moisture, and vapor pressure deficit stresses on vegetation in Central Asia.

Funding

Not explicitly mentioned in the provided text.

Citation

@article{Liang2026Vegetation,
  author = {Liang, Hongwu and Jiapaer, Guli and Chang, Cun and Yu, Tao and Zhang, Liancheng and Feng, Pingping and Lin, Kaixiong and Ju, Tongwei and Jiang, Xiapeng and Maeyer, Philippe De and Voorde, Tim Van de},
  title = {Vegetation in Central Asia is more sensitive to soil moisture stress than to precipitation and vapor pressure deficit stresses},
  journal = {Agricultural and Forest Meteorology},
  year = {2026},
  doi = {10.1016/j.agrformet.2026.111140},
  url = {https://doi.org/10.1016/j.agrformet.2026.111140}
}