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Carbon Management Response Curves: Estimates of Temporal Soil Carbon Dynamics

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Abstract

Measurement of the change in soil carbon that accompanies a change in land use (e.g., forest to agriculture) or management (e.g., conventional tillage to no-till) can be complex and expensive, may require reference plots, and is subject to the variability of statistical sampling and short-term variability in weather. In this paper, we develop Carbon Management Response (CMR) curves that could be used as an alternative to in situ measurements. The CMR curves developed here are based on quantitative reviews of existing global analyses and field observations of changes in soil carbon. The curves show mean annual rates of soil carbon change, estimated time to maximum rates of change, and estimated time to a new soil carbon steady state following the initial change in management. We illustrate how CMR curves could be used in a carbon accounting framework while effectively addressing a number of potential policy issues commonly associated with carbon accounting. We find that CMR curves provide a transparent means to account for changes in soil carbon accumulation and loss rates over time, and also provide empirical relationships that might be used in the development or validation of ecological or Earth systems models.

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Acknowledgements

The research was performed as part of the Consortium for Research on Enhancing Carbon Sequestration in Terrestrial Ecosystems (CSITE) and as part of the Integrated Assessment Program, both sponsored by the U.S. Department of Energy’s Office of Science, Biological and Environmental Research. We are indebted to Siân Mooney, Stephen M. Ogle, and Charles T. Garten for helpful comments on an earlier version of this paper. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the U.S. Dept. of Energy under contract DE-AC05-00OR22725.

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Correspondence to Tristram O. West.

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West, T., Marland, G., King, A. et al. Carbon Management Response Curves: Estimates of Temporal Soil Carbon Dynamics . Environmental Management 33, 507–518 (2004). https://doi.org/10.1007/s00267-003-9108-3

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