Disaggregating the Carbon Exchange of Degrading Permafrost Peatlands Using Bayesian Deep Learning

Disaggregating the Carbon Exchange of Degrading Permafrost Peatlands Using Bayesian Deep Learning

Abstract Extensive regions in the permafrost zone are projected to become climatically unsuitable to sustain permafrost peatlands over the next century, suggesting transformations in these landscapes that can leave large amounts of permafrost carbon vulnerable to post‐thaw decomposition. We present...

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Bibliographic Details
Main Authors: Norbert Pirk, Kristoffer Aalstad, Erik Schytt Mannerfelt, François Clayer, Heleen deWit, Casper T. Christiansen, Inge Althuizen, Hanna Lee, Sebastian Westermann
Format: Article
Language:English
Published: Wiley 2024-05-01
Series:Geophysical Research Letters
Subjects:
carbon fluxes
permafrost degradation
Bayesian neural networks
Online Access:https://doi.org/10.1029/2024GL109283

Internet

https://doi.org/10.1029/2024GL109283

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