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Notebook for "Fluxes vs. Pools: Connecting Temperature Dependence and Sensitivity of Soil Carbon Dynamics Across Timescales""
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Type: | Resource | |
Storage: | The size of this resource is 595.2 KB | |
Created: | Aug 13, 2025 at 2:28 p.m. (UTC) | |
Last updated: | Aug 13, 2025 at 3:35 p.m. (UTC) | |
Citation: | See how to cite this resource | |
Content types: | Single File Content |
Sharing Status: | Public |
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Abstract
This Data Resource includes the Mathematica notebook developed to generate the Figures for the manuscript titled "Fluxes vs. Pools: Connecting Temperature Dependence and Sensitivity of Soil Carbon Dynamics Across Timescales". The Notebook can be run using Mathematica or through a Wolfram Engine. The abstract of the manuscript:
As global temperature (T) regimes shift, there is growing interest in understanding the biotic and abiotic mechanisms driving short- and long-term changes in soil organic carbon (SOC) dynamics. Inconsistent terminology—particularly the use of T sensitivity and dependence—and varying methodological emphases on SOC pools versus fluxes can hinder the integration of experimental results with process-based models aimed at mechanistic insights into SOC-T responses. Here, we clarify the distinction between T dependence (e.g., Q10 formulations of fluxes) and T sensitivity (i.e., T the derivative of SOC fluxes or pools), and demonstrate how T responses of SOC fluxes are related to that of SOC pools. We apply this framework to analyze SOC dynamics using experimental data and a SOC model, examining both steady-state (quasi-static) and transient responses, including the change in heterotrophic respiration following a step-change in T. Our analysis reveals that the T dependence of SOC pools emerges from the T dependence of individual fluxes and is determined, at steady state, by ratios of Q10 values. This underscores the need to measure multiple SOC pools and fluxes, and to use process-based models, in order to estimate the Q10s accurately. Recognizing heterotrophic respiration as an emergent process, we showed that its short-term T response is influenced by the Q10 ratio of microbial uptake and maintenance processes, while the long-term decline arises from mass-balance constraints. Our results offer a mechanistic basis for integrating flux- and pool-based studies and emphasize the importance of combining data and models to quantify SOC-T responses across temporal scales.
Subject Keywords
Coverage
Spatial
Temporal
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Additional Metadata
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Figure generation | Running the Notebook as is will automatically generate the Figures and export them to the working folder. For Figure 4, legends will also be exported automatically as separate image files. |
Credits
Funding Agencies
This resource was created using funding from the following sources:
Agency Name | Award Title | Award Number |
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National Science Foundation | DEB-2241389 |
Contributors
People or Organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.
Name | Organization | Address | Phone | Author Identifiers |
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Aaron Thompson | University of Georgia | |||
Jennifer Pett-Ridge | Lawrence Livermore National Laboratory | |||
Sherlynette Pérez Castro | University of North Carolina | |||
Shibli Sadik Tulip | Texas A&M University | |||
ZIvko Nikolov | Texas A&M University |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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