Interpretable machine learning unveils threshold responses and spatial patterns of global soil respiration

Soil respiration (Rs) represents the largest carbon flux from land to the atmosphere and is important for assessing the terrestrial carbon cycle and studying climate change. In this study, we propose an interpretable machine learning prediction of global Rs (IMPGRs) based on explainable artificial i...

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Bibliographic Details
Main Authors: Junjie Jiang, Lingxia Feng, Junguo Hu, Chao Zhu
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:Ecological Indicators
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Online Access:http://www.sciencedirect.com/science/article/pii/S1470160X25006806
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