Remote Sensing of Seasonal Climatic Constraints on Leaf Phenology Across Pantropical Evergreen Forest Biome

• Main Authors: Qian Li, Xiuzhi Chen, Wenping Yuan, Haibo Lu, Ruoque Shen, Shengbiao Wu, Fanxi Gong, Yuhang Dai, Liyang Liu, Qingling Sun, Chaoqun Zhang, Yongxian Su
• Format: Article
• Language: English
• Published: American Geophysical Union (AGU) 2021-09-01
• Series: Earth's Future
• Subjects: remote sensing; soil and atmospheric water stresses; sunlight availability; tropical evergreen forests; tropical leaf phenology; unimodal and bimodal phenology
• Online Access: https://doi.org/10.1029/2021EF002160

Abstract Climatic drivers for canopy leaf shedding and flush of evergreen broadleaved forest biome are still unclear at the continental scale across tropical and subtropical region. This imposes a challenge for modeling pantropical photosynthesis seasonality in Earth system models. Here, we examined three potential climatic triggers, vapor pressure deficit–a proxy of atmospheric water deficit, downward shortwave incoming solar radiation–a proxy of sunlight availability, and terrestrial water storage–a proxy of soil water availability observed by the Gravity Recovery and Climate Experiment, by comparing with two satellite phenological proxies–the Enhanced Vegetation Index and Continuous Solar‐induced chlorophyll fluorescence. Results show that tropical leaf phenology varies greatly from equatorial bimodal seasonality to higher‐latitude unimodal seasonality. Sunlight availability dominantly controls the whole seasonal leaf phenology across the pantropical region. Atmospheric dryness is one main type of water stress for leaf phenology during the first half year. However, soil water stress strongly inhibits the first‐half of leaf phenology in tropical Asia and the second‐half of leaf phenology in Congo, but shows rare constraint on the leaf phenology in Amazon. Ignoring these various roles of soil moisture availability and atmospheric dryness in influencing tropical leaf phenology might lead to unexpected uncertainty for predicting the water and carbon cycles of tropical forest ecosystem in Earth system models.