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Developing a Long-Term Monitoring Network for Monitoring Soil Carbon Stocks in the U.S

Spencer, S ; Ogle, S ; Paustian, K ; Breidt, F J

Eos (Washington, D.C.), 2006-12, Vol.87 (52)

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  • Título:
    Developing a Long-Term Monitoring Network for Monitoring Soil Carbon Stocks in the U.S
  • Autor: Spencer, S ; Ogle, S ; Paustian, K ; Breidt, F J
  • É parte de: Eos (Washington, D.C.), 2006-12, Vol.87 (52)
  • Notas: SourceType-Scholarly Journals-2
    ObjectType-Conference Paper-1
    content type line 23
    SourceType-Conference Papers & Proceedings-1
    ObjectType-Feature-2
    ObjectType-Article-3
  • Descrição: Monitoring carbon pools is important for evaluating modeled results, particularly for the slower dynamics of soil C pools. Thus, a national, long-term soil monitoring network is being established on cropland and grazing lands in the U.S. Data from this network will serve as an independent evaluation for model-based estimates of soil carbon stocks. The soil monitoring network will consist of permanently marked sample sites associated with the USDA- NRCS Natural Resource Inventory (NRI), with an anticipated resampling frequency of 5-10 years. Sample stratification has been designed to minimize variance associated with soil carbon stock changes for similar land use and climate-soil combinations, with strata largely based on the USDA's Major Land Resource Areas (MLRA). The national sample has been distributed to minimize the standard error of prediction based on a Neyman Allocation, with goal of detecting soil carbon stock changes at regional and national scales over 5-10 year time periods. A pilot phase is currently underway to establish the network. Site-scale sampling is utilizing a triangular design to minimize within site variance. During the first sample, soils are collected at the corners of the triangle, and then repeated sampling will occur along the sides until reaching the next corner over about a 100 year time horizon. Three triangles are being sampled at each NRI point. A formal uncertainty analysis of modeled results will be conducted using initial carbon data measured at ~35 sites from the Mid-Continent Region of the U.S., comparing modeled data to measurements. In addition, we are incorporating remotely sensed image data into the analysis to further constrain the uncertainty in soil carbon estimates provided by ecosystem models. The soil carbon monitoring network will provide much-needed model evaluation data at a broad scale, which will improve the quantification of carbon sources and sinks.
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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