Heat-Stress Dormancy and the Muted Advance of Spring Phenology Under Extreme Warming in a Subtropical Transitional Zone: A Correlative Analysis
Anthropogenic warming has intensified extreme climate events, yet whether vegetation phenology in subtropical transitional zones follows the canonical warming-advance relationship or deviates under extreme conditions remains unresolved. Here, we analyze MODIS NDVI and ETCCDI extreme climate data across the northern slope of the Nanling Mountains, a critical subtropical transitional zone in southern China. At the spatial and interannual scale, SOS correlates negatively with extreme warm indices across 65.97% of the study area, i.e., warmer conditions coincide with earlier (canonical warming-advance) SOS, yet the regional SOS trend is non-significant despite coherent warming. We propose that heat-stress dormancy, extreme spring warmth triggering a reversible quiescent response that overrides thermal-time accumulation, is the most plausible explanation, although the present correlative, remote-sensing design cannot yet establish the underlying physiological mechanism. Growing season lengthening is driven by EOS delay (6.4 d per four years, p < 0.05) rather than SOS advance. Extreme precipitation is also predominantly associated with earlier SOS, with 75%–80% of pixels showing significant negative correlations, indicating that both thermal and moisture extremes shape spring phenology. Vegetation types follow a sensitivity hierarchy: cultivated land and grassland show the strongest phenological shifts, while natural forests remain buffered. These findings qualify the universal applicability of the warming-advance framework and call for incorporating heat-stress dormancy into phenological projections for subtropical transitional zones under continued extreme warming.
Authors
- Zhiwei Wan (ORCID: https://orcid.org/0000-0002-8520-2191)
- Yuandong Wang (ORCID: https://orcid.org/0009-0005-9122-9744)
- Guangxu Liu (ORCID: https://orcid.org/0000-0002-3596-2205)
- Aicun Xiang
- Liujian Liao
- Wei Luo
- Hangna Ke
Institutions
- Chinese Academy of Sciences (CN)
- Northwest Institute of Eco-Environment and Resources (CN)
- Gannan Normal University (CN)
Publication Details
- Journal
- Forests
- Published
- 2026-10-16
- DOI
- https://doi.org/10.3390/f17101233
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China