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Estimate organic carbon

Source: R/estimate_oc.R
estimate_oc.Rd

Estimate organic carbon from organic matter values

Usage

estimate_oc(
  df = NULL,
  core = "core",
  site = "site",
  ecosystem = "ecosystem",
  species = "species",
  om = "om",
  oc = "oc"
)

Arguments

df

A tibble or data.frame containing all the data. Must have at least five columns (see arguments below).

core

Character Name of the column with the id of the core to which the sample belongs

site

Character Name of the column reporting sample site.

ecosystem

Character Name of the column reporting ecosystem type. To apply published equations for OC estimation, ecosystem names should be either "Salt Marsh", "Seagrass" or "Mangrove".

species

Character Name of the column reporting the main species in the site.

om

Character Name of the column reporting organic matter values.

oc

Character Name of the column reporting organic carbon values.

Value

The initial tibble or data.frame with three new columns:

  • one column with estimated organic carbon values (eOC) in %

  • the standard error of the prediction (eOC_se)

  • the type of model used for estimation (origin) In addition, a plot with the relationship between organic matter and estimated organic carbon

Details

Estimation of organic Carbon is done by means of linear regressions on log(organic carbon) ~ log(organic matter). It gives back a organic carbon value for each organic matter value provided. If there is a organic carbon value for that sample it return the same value, else, generates a model for that site, else, model for specie, else, model for Ecosystem. If a model can not be created due to the low number of samples (<10) or the created model has less than 0.5 r2 value it uses published equations to estimate the organic carbon: Maxwell et al. 2023 for salt marshes, Fourqurean et al. 2012 for seagrasses and Pineiro-Juncal et al. in prep for mangroves.

Examples

bluecarbon_decompact <- decompact(bluecarbon_data)
#> Warning: Setting compaction = 0 for these cores: Sm_03_04, Sm_03_04, Sm_03_04, Sm_03_04, Sm_03_04, Sm_03_04, Sm_03_04, Sg_10_02, Sg_10_02, Sg_10_02, Sg_10_02, Sg_10_02, Sg_11_03, Sg_11_03, Sg_11_03, Sg_11_03, Sg_11_03, Sg_11_03, Sg_11_03, Sg_11_03, Sg_11_03, Sg_11_03, Sg_11_03, Sg_11_03, Sm_05_01, Sm_05_01, Sm_05_01, Sm_05_01, Sm_05_01, Sm_05_01, Sm_06_01, Sm_06_01, Sm_06_01, Sm_06_01, Sm_06_01, Sm_06_01
out <- estimate_oc(bluecarbon_decompact)

#> Warning: The following cores had samples with organic carbon values below the organic carbon range used to built the model: Sg_04_01, Sm_04_03, Sm_04_04, Sm_05_01
#> Warning: The following cores had samples with organic carbon values above the organic carbon range used to built the model: Sg_04_01, Sm_03_01, Sm_04_02, Sm_04_03, Sm_04_04, Sm_05_01