Jiang et al. (2026) Disentangling the contributions of hydrothermal factors to fractional vegetation cover dynamics on the Qinghai-Tibet plateau

Identification

• Journal: Ecological Indicators
• Year: 2026
• Date: 2026-04-03
• Authors: Chuan Jiang, Yang Pu, Shuping Zhang, Yanbin Lei
• DOI: 10.1016/j.ecolind.2026.114816

Research Groups

• School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
• Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810008, China
• Key Laboratory of Tibetan Environmental Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China

Short Summary

This study quantifies the independent contributions of vapor pressure deficit (VPD) and soil moisture (SM), alongside temperature (Ta) and precipitation (PRE), to fractional vegetation cover (FVC) dynamics on the Qinghai-Tibet Plateau (QTP) from 1982 to 2020, revealing VPD as the dominant driver with spatially heterogeneous effects modulated by soil moisture.

Objective

• Analyze the spatiotemporal variation of annual Fractional Vegetation Cover (FVC) across the Qinghai-Tibet Plateau (QTP) during 1982–2020.
• Apply ridge regression to disentangle the independent contributions of temperature (Ta), precipitation (PRE), soil moisture (SM), and vapor pressure deficit (VPD) to FVC variation across different eco-geographical zones of the QTP.
• Explore how FVC responds to VPD under different hydrothermal regimes.

Study Configuration

• Spatial Scale: Qinghai-Tibet Plateau (QTP), China (26°00′12″N–39°46′50″N, 73°18′52″E–104°46′59″E), with an average elevation exceeding 4000 m. The plateau was stratified into three humidity regimes: humid, transitional, and arid zones.
• Temporal Scale: 1982–2020 (39 years).

Methodology and Data

• Models used:
  • Dimidiate Pixel Model (DPM) for Fractional Vegetation Cover (FVC) derivation from Normalized Difference Vegetation Index (NDVI).
  • Theil-Sen estimator for quantifying long-term trends.
  • Mann-Kendall test for assessing the statistical significance of trends.
  • Ridge regression for quantifying the independent contributions of hydrothermal factors and mitigating multicollinearity.
  • 5-fold cross-validation for determining the optimal regularization parameter (λ) in ridge regression.
• Data sources:
  • Fractional Vegetation Cover (FVC): Derived from Global Inventory Modeling and Mapping Studies-3rd Generation (GIMMS-3G+) AVHRR NDVI (0.0833° spatial resolution, semi-monthly, 1981–2022).
  • Temperature (Ta) and Precipitation (PRE): Downscaled global 0.5° climate data from CRU and high-resolution climate data from WorldClim (1 km spatial resolution, monthly, 1901–2023).
  • Vapor Pressure Deficit (VPD): CHM_Drought dataset (0.1° grid, monthly, 1961–2022).
  • Soil Moisture (SM): ERA5-Land reanalysis dataset (0.1° × 0.1° spatial resolution, hourly, 1982–2020) for three layers: 0–7 cm (SM1), 7–28 cm (SM2), and 28–100 cm (SM3).
  • Aridity Index (AI): Calculated from CRU and WorldClim data (1 km spatial resolution, annual, 1901–2023) for hydrothermal zonation.

Main Results

• FVC exhibited a distinct declining gradient from the southeast to the northwest across the QTP. Over the 1982–2020 period, a significant overall greening trend was observed at a rate of 0.0006 per year (p < 0.05). Spatially, vegetation greening predominantly occurred in the arid and transitional zones (66.07% of the plateau), while localized degradation emerged in the relatively humid zone.
• Among the six hydrothermal factors examined, Vapor Pressure Deficit (VPD) emerged as the primary driver of FVC dynamics, accounting for 31.69% of the total relative contribution and dominating 44.31% of the QTP's total area.
• Temperature (Ta) ranked as the second most influential factor, contributing 24.15% to FVC variation and controlling 27.40% of the region.
• Deep soil moisture (SM3, 28–100 cm) accounted for 14.75% of the FVC trend and dominated 13.76% of the region, exerting a critical influence in the arid zone. Shallow soil moisture (SM1: 9.26%, SM2: 10.77%) and precipitation (PRE: 9.38%) had comparatively weaker influences.
• FVC responses to VPD were highly heterogeneous across hydrothermal regimes:
  • In the arid zone, increased deep soil moisture (SM3) mitigated atmospheric drought stress, sustaining a slow greening trend.
  • In the transitional zone, adequate moisture conditions allowed moderate increases in VPD to promote significant greening.
  • In the humid zone, the synergistic interplay of high VPD and reduced soil moisture intensified vegetation degradation.

Contributions

• This study provides a robust quantification of the independent contributions of key hydrothermal factors to FVC dynamics on the QTP by effectively addressing multicollinearity using ridge regression.
• It identifies Vapor Pressure Deficit (VPD) as the dominant driver of FVC dynamics on the QTP, surpassing the traditionally emphasized temperature and precipitation, thereby advancing the mechanistic understanding of alpine ecosystem responses to climate change.
• The research highlights the spatially heterogeneous sensitivity of alpine vegetation to hydroclimatic shifts, demonstrating how FVC responses to VPD are profoundly modulated by soil moisture availability across different hydrothermal regimes.
• The findings offer essential scientific evidence for developing ecosystem-specific conservation and adaptive management strategies tailored to the distinct hydrological zones of the QTP under global warming.

Funding

• National Natural Science Foundation of China (Grant No. 42171160)
• Chinese Academy of Sciences (Grant No. E2290112)

Citation

@article{Jiang2026Disentangling,
  author = {Jiang, Chuan and Pu, Yang and Zhang, Shuping and Lei, Yanbin},
  title = {Disentangling the contributions of hydrothermal factors to fractional vegetation cover dynamics on the Qinghai-Tibet plateau},
  journal = {Ecological Indicators},
  year = {2026},
  doi = {10.1016/j.ecolind.2026.114816},
  url = {https://doi.org/10.1016/j.ecolind.2026.114816}
}