Xu et al. (2025) Vegetation Phenological Responses to Multi-Factor Climate Forcing on the Tibetan Plateau: Nonlinear and Spatially Heterogeneous Mechanisms

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Land
• Year: 2025
• Date: 2025-11-12
• Authors: Liuxing Xu, Ruicheng Xu, Wenfu Peng
• DOI: 10.3390/land14112238

Research Groups

[Information not provided in the paper text.]

Short Summary

This study quantifies the independent and interactive effects of multiple climate factors on vegetation phenology on the Tibetan Plateau, revealing a significant increase in growing season length (0.24 days per year) primarily due to earlier spring onset, with spatially heterogeneous and ecosystem-specific responses.

Objective

• To systematically assess and quantify the independent effects and spatial heterogeneity of temperature, precipitation, solar radiation, and evapotranspiration on the growing season length (GSL) on the Tibetan Plateau from 2001 to 2023.

Study Configuration

• Spatial Scale: Tibetan Plateau (large-scale, pixel-level analysis).
• Temporal Scale: 2001 to 2023 (23 years).

Methodology and Data

• Models used: Sen’s slope estimation, Mann–Kendall trend tests, and partial correlation analyses.
• Data sources:
  • Remote sensing data: MODIS MCD12Q2 (for phenological metrics: Start of Season (SOS), End of Season (EOS), Growing Season Length (GSL)).
  • Meteorological data: ERA5-Land (for temperature, precipitation, solar radiation, and evapotranspiration (ET)).
  • Cloud platform: Google Earth Engine (GEE).

Main Results

• The Growing Season Length (GSL) on the Tibetan Plateau significantly increased by an average of 0.24 days per year (Sen’s slope +0.183 days/yr; linear regression +0.253 days/yr, decadal trend 2.53 days).
• This GSL extension is primarily driven by an earlier spring onset (SOS: −0.183 days/yr), while autumn dormancy (EOS) showed limited delay (+0.051 days/yr).
• GSL changes exhibit pronounced spatial heterogeneity and ecosystem-specific responses:
  • Southeastern warm–wet regions show the strongest responses, with temperature as the dominant driver (mean partial correlation coefficient 0.62).
  • In high–cold arid regions, warming substantially extends GSL, whereas in warm–wet regions, growth may be constrained by water stress.
  • Grasslands and urban areas show the largest GSL extension, while evergreen forests and wetlands remain relatively stable.
• Multi-factor interactions among temperature, precipitation, radiation, and ET are complex and nonlinear, potentially involving lagged effects and clear thresholds with spatial dependence.
• The use of GEE enabled large-scale, multi-year, pixel-level GSL analysis, providing high-precision evidence for phenological quantification.

Contributions

• Systematically reveals the lengthening and asymmetric patterns of GSL on the Tibetan Plateau.
• Elucidates diverse land cover and climate responses to phenological changes in a globally critical and climate-sensitive region.
• Advances understanding of high-altitude ecosystem adaptability and climate resilience under multi-factor climate change.
• Provides high-precision evidence for phenological quantification and critical parameters for carbon cycle modeling, ecosystem service assessment, and adaptive management.
• Offers scientific guidance for regional ecological protection, sustainable management, and future phenology prediction.

Funding

[Information not provided in the paper text.]

Citation

@article{Xu2025Vegetation,
  author = {Xu, Liuxing and Xu, Ruicheng and Peng, Wenfu},
  title = {Vegetation Phenological Responses to Multi-Factor Climate Forcing on the Tibetan Plateau: Nonlinear and Spatially Heterogeneous Mechanisms},
  journal = {Land},
  year = {2025},
  doi = {10.3390/land14112238},
  url = {https://doi.org/10.3390/land14112238}
}