Improved dryland carbon flux predictions with explicit consideration of water-carbon coupling
Upscaling in situ carbon flux measurements using remotely sensed and meteorological observations in a machine learning algorithm leads to improved estimates of average uptake, and interannual variability in global drylands.
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Autores principales: | , , , , , , , , |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/cc09b7906fa14313a1c796d37d5d2281 |
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