Description Usage Arguments Details Value Author(s) Examples

This function finds the best possible value of turnover time from a soil radiocarbon sample assuming a one pool model and annual litter inputs.

1 2 | ```
turnoverFit(obsC14, obsyr, In, C0 = 0, yr0 = 1900, Zone = "NHZone2",
plot = TRUE)
``` |

`obsC14` |
a scalar with the observed radiocarbon value in Delta14C of the soil sample. |

`obsyr` |
a scalar with the year in which the soil sample was taken. |

`In` |
a scalar or data.frame with the annual amount of litter inputs to the soil. |

`C0` |
a scalar with the initial amount of carbon stored at the begning of the simulation. |

`yr0` |
The year at which simulations will start. |

`Zone` |
the hemispheric zone of atmospheric radiocarbon. Possible values are NHZone1: northern hemisphere zone 1, NHZone2: northern hemisphere zone 2, NHZone3: northern hemisphere zone 3, SHZone12: southern hemisphere zones 1 and 2, SHZone3: southern hemisphere zone 3. See |

`plot` |
logical. Should the function produce a plot? |

This algorithm takes the observed values and a given amount of litter inputs, runs `OnepModel14`

, calculates the squared difference between predictions and observations, and uses `optimize`

to find the minimum difference.
If the turnover time is relatively short (< 50 yrs), it is safe to assume C0=0 because the soil will reach steady state within the simulation time. However, for longer turnover times it is recommended to use a value of C0 close to the steady state value.

A scalar with the value of the turnover time that minimizes the difference between the prediction of a one pool model and the observed radiocarbon value.

Carlos A. Sierra <csierra@bgc-jena.mpg.de>, Markus Mueller <mamueller@bgc-jena.mpg.de>

1 2 3 4 5 6 7 | ```
## Not run:
# Calculate the turnover time for a sample from a temperate forest soil
turnoverFit(obsC14=115.22, obsyr=2004.5, C0=2800, yr0=1900,
In=473, Zone="NHZone2")
## End(Not run)
``` |

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