Leveraging explainable AI to predict soil respiration sensitivity and its drivers for climate change mitigation

Leveraging explainable AI to predict soil respiration sensitivity and its drivers for climate change mitigation

Abstract Global warming is one of the most pressing and critical problems facing the world today. It is mainly caused by the increase in greenhouse gases in the atmosphere, such as carbon dioxide (CO2). Understanding how soils respond to rising temperatures is critical for predicting carbon release...

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Bibliographic Details
Main Authors: Pierfrancesco Novielli, Michele Magarelli, Donato Romano, Pierpaolo Di Bitonto, Anna Maria Stellacci, Alfonso Monaco, Nicola Amoroso, Roberto Bellotti, Sabina Tangaro
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Soil Respiration Sensitivity
Machine Learning
Explainable Artificial Intelligence (XAI)
Q10
Climate Change
Online Access:https://doi.org/10.1038/s41598-025-96216-y
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https://doi.org/10.1038/s41598-025-96216-y

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