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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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-08-01
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| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X25006806 |
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