Qin et al. (2026) Dynamic responses of gross primary productivity to compound hot extremes and drought across different geographical regions of China

Identification

• Journal: Frontiers in Plant Science
• Year: 2026
• Date: 2026-01-12
• Authors: Yu Qin, Qiuxiang Jiang, Youzhu Zhao, Zilong Wang, Meiyun Tao, Baohan Li
• DOI: 10.3389/fpls.2025.1715432

Research Groups

• School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin, China
• International Cooperation Joint Laboratory of Health in Cold Region Black Soil Habitat of the Ministry of Education, Harbin, China

Short Summary

This study quantifies the synergistic impact of compound hot extremes and drought events on vegetation gross primary productivity (GPP) across China using an integrated framework. It reveals that compound events have a significantly amplified negative effect on GPP compared to single factors, with notable regional heterogeneity, particularly in North China.

Objective

• To systematically reveal the impact mechanism of compound hot and drought events on vegetation GPP at the regional scale in China, specifically quantifying the independent and interactive effects of key driving factors.

Study Configuration

• Spatial Scale: China, encompassing six major geographical regions (Northeast China, North China, East China, Central and South China, Northwest China, and Southwest China).
• Temporal Scale: 2001 to 2020 (20 years).

Methodology and Data

• Models used: Spatiotemporal trend analysis (Theil-Sen Median technique, Mann-Kendall test), Pearson correlation analysis, and an improved optimal parameter-based Geographical Detector model.
• Data sources:
  • MODIS GPP data (MOD17A2 product, 0.5° spatial resolution, 8-day temporal resolution synthesized to monthly).
  • Standardized Precipitation Evapotranspiration Index (SPEI) data (SPEIbase v.2.8 dataset, monthly temporal resolution).
  • Monthly average temperature data (National Tibetan Plateau Data Center, 0.5° spatial resolution).

Main Results

• From 2001 to 2020, the mean GPP in China showed an overall upward trend, with the Central and South region exhibiting the highest growth rate of 9.88 gC·m⁻²·a⁻¹.
• The Standardized Temperature Index (STI) showed a significant increasing trend in 90.77% of China's regions, while the SPEI indicated no significant changes in drought severity across 83.76% of the territory.
• The frequency of compound hot extremes and drought events ranged from 5% to 23% across China, with North China experiencing the highest average frequency (14.4%) and Northwest China the lowest (13.1%).
• Correlation analysis revealed that 72.4% of regions showed a negative correlation between STI and GPP, and 64.1% showed a positive correlation between SPEI and GPP.
• A significant negative correlation was observed between the frequency of compound hot extremes and drought events and GPP in 71.69% of China's land area, with North China showing the strongest negative response (r = -0.32).
• The Geographical Detector model demonstrated that the impact of compound hot extremes and drought events on GPP significantly exceeded that of either factor alone, exhibiting a synergistic amplification. North China showed the most pronounced effect, with a q-value of 0.51 for compound events, compared to 0.14 for STI and 0.25 for SPEI.

Contributions

• Introduces a novel, integrated framework combining spatiotemporal trend analysis, correlation methods, and the geographical detector model to quantitatively assess the non-linear interactions of compound hot extremes and drought with GPP.
• Systematically elucidates the complex interaction mechanisms among STI, SPEI, and GPP across different geographical regions of China.
• Provides crucial data support for evaluating ecosystem resilience and developing informed adaptive management strategies in the context of climate change.
• Establishes a connection between localized correlations and broader impact patterns, offering new methodological insights for understanding climate-vegetation interactions.

Funding

• National Natural Science Foundation of China [grant number 52479006, 52409011].

Citation

@article{Qin2026Dynamic,
  author = {Qin, Yu and Jiang, Qiuxiang and Zhao, Youzhu and Wang, Zilong and Tao, Meiyun and Li, Baohan},
  title = {Dynamic responses of gross primary productivity to compound hot extremes and drought across different geographical regions of China},
  journal = {Frontiers in Plant Science},
  year = {2026},
  doi = {10.3389/fpls.2025.1715432},
  url = {https://doi.org/10.3389/fpls.2025.1715432}
}