Granularity of model input data impacts estimates of carbon storage in soils

The exchange of carbon between the soil and the atmosphere is an important factor in climate change. Soil organic carbon (SOC) storage is sensitive to land management, soil properties, and climatic conditions, and these data serve as key inputs to computer models projecting SOC change. Farmland has...

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Bibliographic Details
Published in:PLOS climate 2024-10, Vol.3 (10), p.e0000363
Main Authors: Wiltshire, Serge, Clemins, Patrick J., Beckage, Brian
Format: Article
Language:English
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Summary:The exchange of carbon between the soil and the atmosphere is an important factor in climate change. Soil organic carbon (SOC) storage is sensitive to land management, soil properties, and climatic conditions, and these data serve as key inputs to computer models projecting SOC change. Farmland has been identified as a sink for atmospheric carbon, and we have previously estimated the potential for SOC sequestration in agricultural soils in Vermont, USA using the Rothamsted Carbon Model. However, fine spatial-scale (high granularity) input data are not always available, which can limit the skill of SOC projections. For example, climate projections are often only available at scales of 10s to 100s of km 2 . To overcome this, we use a climate projection dataset downscaled to
ISSN:2767-3200
2767-3200
DOI:10.1371/journal.pclm.0000363