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Fluxible

The Fluxible R package is made to transform any dataset of gas concentration over time into a gas flux dataset. It was originally made to be used with a closed loop chamber system connected to a gas analyzer.

The goal of fluxible is to provide a workflow that removes individual evaluation of each flux, reduces risk of bias, and makes it reproducible. Users set specific data quality standards and selection parameters as function arguments that are applied to the entire dataset. The package runs the calculations automatically, without prompting the user to take decisions mid-way, and provides quality flags and plots at the end of the process for a visual check. This makes it easy to use with large flux datasets and to integrate into a reproducible workflow. Using the Fluxible R package makes the workflow reproducible, increases compatibility across studies, and is more time efficient.

Installation

Fluxible can be installed from CRAN.

install.packages("fluxible")

You can install the development version of fluxible from the GitHub repo with:

# install.packages("devtools")
devtools::install_github("plant-functional-trait-course/fluxible")

Short example 

library(fluxible)

conc_df <- flux_match(
  co2_df_short,
  record_short,
  datetime,
  start,
  conc,
  startcrop = 10,
  measurement_length = 220
)

slopes_df <- flux_fitting(
  conc_df,
  conc,
  datetime,
  fit_type = "exp",
  end_cut = 30
)
#> Cutting measurements...
#> Estimating starting parameters for optimization...
#> Optimizing fitting parameters...
#> Calculating fits and slopes...
#> Done.

slopes_flag_df <- flux_quality(
  slopes_df,
  conc
)
#> 
#>  Total number of measurements: 6
#> 
#>  ok   6   100 %
#>  discard      0   0 %
#>  zero     0   0 %
#>  force_discard    0   0 %
#>  start_error      0   0 %
#>  no_data      0   0 %
#>  force_ok     0   0 %

flux_plot(
  slopes_flag_df,
  conc,
  datetime,
  f_ylim_lower = 390,
  f_ylim_upper = 650,
  facet_wrap_args = list(
    ncol = 3,
    nrow = 2,
    scales = "free"
  )
)
#> Plotting in progress


fluxes_df <- flux_calc(
  slopes_flag_df,
  f_slope_corr,
  datetime,
  temp_air,
  conc_unit = "ppm",
  flux_unit = "mmol",
  cols_keep = c("turfID", "type"),
  cols_ave = c("temp_soil", "PAR"),
  chamber_volume = 24.5,
  tube_volume = 0.075,
  atm_pressure = 1,
  plot_area = 0.0625
)
#> Cutting data according to 'keep_arg'...
#> Averaging air temperature for each flux...
#> Creating a df with the columns from 'cols_keep' argument...
#> Creating a df with the columns from 'cols_ave' argument...
#> Calculating fluxes...
#> R constant set to 0.082057
#> Concentration was measured in ppm
#> Fluxes are in mmol/m2/h

fluxes_gep <- flux_gep(
  fluxes_df,
  type,
  datetime,
  id_cols = "turfID",
  cols_keep = c("temp_soil")
)
#> Warning in flux_gep(fluxes_df, type, datetime, id_cols = "turfID", cols_keep = c("temp_soil")): 
#>  NEE missing for measurement turfID: 156 AN2C 156

fluxes_gep
#> # A tibble: 9 × 5
#>   datetime            type  f_flux temp_soil turfID      
#>   <dttm>              <chr>  <dbl>     <dbl> <chr>       
#> 1 2022-07-28 23:43:35 ER      47.7      10.8 156 AN2C 156
#> 2 2022-07-28 23:47:22 GEP     10.3      10.7 74 WN2C 155 
#> 3 2022-07-28 23:47:22 NEE     31.0      10.7 74 WN2C 155 
#> 4 2022-07-28 23:52:10 ER      20.7      10.7 74 WN2C 155 
#> 5 2022-07-28 23:59:32 GEP    -27.2      10.8 109 AN3C 109
#> 6 2022-07-28 23:59:32 NEE     41.5      10.8 109 AN3C 109
#> 7 2022-07-29 00:03:10 ER      68.7      10.5 109 AN3C 109
#> 8 2022-07-29 00:06:35 GEP     NA        12.2 29 WN3C 106 
#> 9 2022-07-29 00:06:35 NEE     26.1      12.2 29 WN3C 106

Further developments

Segmentation tool

We are working on a tool to automatically select the window of the measurement on which to fit a model. This selection will be based on environmental variable, such as photosynthetically active radiation (PAR), measured simultaneously.

More fits

As we want fluxible to fit the use of as many projects as possible, more fitting expressions will be included in the flux_fitting function. Feel welcome to get in touch if you wish to include yours in fluxible.

Contact

Joseph Gaudard, University of Bergen, Norway

GitHub profile

Dissemination

Gaudard, J., Telford, R., Vandvik, V., and Halbritter, A. H.: Fluxible: an R package to calculate ecosystem gas fluxes in a reproducible and automated workflow., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-956, https://doi.org/10.5194/egusphere-egu24-956, 2024.