Precipitation Dominates Forest Net Primary Productivity Variations With Distinct Regional Differences in Yunnan Province, China
Xiaofang Yang, Kun Yang, Shaohua Zhang, Wenxia Zeng, Jing Liu, Yan Rao, Yan Ma, Changyou Bi

TL;DR
This study shows that precipitation is the main driver of forest productivity in Yunnan, China, with regional differences and nonlinear effects.
Contribution
The study introduces a comparative framework for analyzing stable and changing forests using random forest and SHAP methods in Yunnan.
Findings
Changing forests show greater NPP variation and spatial heterogeneity than stable forests.
Precipitation has strong synergistic effects on NPP, especially in changing forests.
Key factors like temperature and elevation show nonlinear threshold responses for NPP.
Abstract
In the topographically and climatically diverse region of Yunnan, clarifying the driving mechanisms and threshold effects of factors influencing forest net primary productivity (NPP) is crucial for managing forest carbon sinks. In this study, we established a comparative analysis framework for the stable forest (SF) and the changing forest (CF). Yunnan was then divided into five subregions based on topography and climate. Using a random forest model and the SHAP method, we systematically analyzed drivers of spatiotemporal NPP variations. The results show that CF exhibits greater NPP variation and spatial heterogeneity than SF and maintains stronger trend persistence. At the provincial scale, elevation and precipitation are the main drivers of NPP in SF and CF, respectively, while at the subregional scale, dominant factors differ and include solar radiation, temperature, and forest age,…
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Taxonomy
TopicsPlant Water Relations and Carbon Dynamics · Remote Sensing in Agriculture · Tree-ring climate responses
