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Modeling radiocarbon dynamics in soils: SoilR version 1.1

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Abstract. Radiocarbon is an important tracer of the global carbon cycle that helps to understand carbon dynamics in soils. It is useful to estimate rates of organic matter cycling as well as the mean residence or transit time of carbon in soils. We included a set of functions to model the fate of radiocarbon in soil organic matter within the SoilR package for the R environment for computing. Here we present the main system equations and functions to calculate the transfer and release of radiocarbon from different soil organic matter pools. Similarly, we present functions to calculate the mean transit time for different pools and the entire soil system. This new version of SoilR also includes a group of datasets describing the amount of radiocarbon in the atmosphere over time, data necessary to estimate the incorporation of radiocarbon in soils. Also, we present examples on how to obtain parameters of pool-based models from radiocarbon data using inverse parameter estimation. This implementation is general enough so it can also be used to trace the incorporation of radiocarbon in other natural systems that can be represented as linear dynamical systems.
Title: Modeling radiocarbon dynamics in soils: SoilR version 1.1
Description:
Abstract.
Radiocarbon is an important tracer of the global carbon cycle that helps to understand carbon dynamics in soils.
It is useful to estimate rates of organic matter cycling as well as the mean residence or transit time of carbon in soils.
We included a set of functions to model the fate of radiocarbon in soil organic matter within the SoilR package for the R environment for computing.
Here we present the main system equations and functions to calculate the transfer and release of radiocarbon from different soil organic matter pools.
Similarly, we present functions to calculate the mean transit time for different pools and the entire soil system.
This new version of SoilR also includes a group of datasets describing the amount of radiocarbon in the atmosphere over time, data necessary to estimate the incorporation of radiocarbon in soils.
Also, we present examples on how to obtain parameters of pool-based models from radiocarbon data using inverse parameter estimation.
This implementation is general enough so it can also be used to trace the incorporation of radiocarbon in other natural systems that can be represented as linear dynamical systems.

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