Plant functional traits as key regulators of interannual phenological variability in temperate forests
Interannual phenological variability (IPV), a critical indicator of plant phenological sensitivity to climate variations, can determine ecosystem functions and stability. While the influence of climate on IPV has been recognized, the effects of biotic factors such as functional traits and diversity remain underexplored. We selected four temperate forest sites with similar intrasite climate variations to investigate the biotic regulatory mechanisms of IPV. For each site, we utilized IPV from time-series Harmonized Landsat Sentinel-2 data, foliar traits from airborne hyperspectral data, and structural traits from airborne Light Detection and Ranging data for the analysis. Our results reveal considerable IPV variations within and across forests. Functional traits and diversity are important for explaining intrasite IPV variation. Functional traits, particularly those related to resource use and productivity, have more explanatory power than functional diversity. Moreover, functional traits and diversity can regulate ecosystem productivity stability through their effects on IPV, with a strong negative association between IPV and ecosystem productivity stability (r = -0.71 to -0.86). These findings demonstrate significant contributions of functional traits to regulating IPV and ecosystem productivity stability, highlighting their critical role in determining plant phenological sensitivity and ecosystem stability in response to climate changes.
Authors
- Yingyi Zhao (ORCID: https://orcid.org/0009-0001-5392-3402)
- Jin Wu (ORCID: https://orcid.org/0000-0001-8991-3970)
- Minkyu Moon (ORCID: https://orcid.org/0000-0003-0268-1834)
- Zhengbing Yan (ORCID: https://orcid.org/0000-0002-5028-8167)
- Iryna Dronova (ORCID: https://orcid.org/0000-0003-3339-3704)
- Jing Wang (ORCID: https://orcid.org/0000-0003-0116-6179)
- Yanjun Su (ORCID: https://orcid.org/0000-0001-7931-339X)
- Zhengfei Guo (ORCID: https://orcid.org/0000-0001-8806-1307)
- Lin Meng (ORCID: https://orcid.org/0000-0002-1603-4200)
- Zhihui Wang (ORCID: https://orcid.org/0000-0003-1064-7820)
- Lingli Liu (ORCID: https://orcid.org/0000-0002-5696-3151)
- Guangqin Song
Institutions
- Sun Yat-sen University (CN)
- Kangwon National University (KR)
- Chinese University of Hong Kong (HK)
- Shenzhen University (CN)
- Chinese Academy of Sciences (CN)
- Vanderbilt University (US)
- Beijing Botanical Garden (CN)
- Guangdong Academy of Sciences (CN)
- Hong Kong Biotechnology Organization (CN)
- Guangzhou Institute of Geography (CN)
- Institute of Botany (CN)
- China National Botanical Garden
- University of Hong Kong (HK)
- University of California, Berkeley (US)
Publication Details
- Journal
- New Phytologist
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1111/nph.70784
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00