Calculates light response curves (LRC) for CO2 fluxes and standardizes CO2 fluxes according to the LRC
Usage
flux_lrc(
fluxes_df,
type_col,
par_ave = par_ave,
f_flux = f_flux,
lrc_arg = "LRC",
nee_arg = "NEE",
er_arg = "ER",
lrc_group = c(),
par_nee = 300,
par_er = 0
)Arguments
- fluxes_df
a dataframe containing NEE, ER and LRC measurements
- type_col
column containing type of flux (NEE, ER, LRC)
- par_ave
column containing the PAR value for each flux
- f_flux
column containing flux values
- lrc_arg
argument designating LRC fluxes in type column
- nee_arg
argument designating NEE fluxes in type column
- er_arg
argument designating ER fluxes in type column
- lrc_group
character vector of columns to use to group the LRC (campaign, site, treatment), if applicable
- par_nee
PAR value to correct the NEE fluxes to
- par_er
PAR value to correct the ER fluxes to
Value
the same dataframe with the additional column par_correction = TRUE
for correct fluxes. Corrected fluxes
are in the same f_flux column. Non corrected fluxes and other fluxes are
kept, with NA in par_correction.
Details
The light response curves are calculated with a quadratic of the form flux(PAR) = a * PAR2 + b * PAR + c
The long format of the output with both uncorrected and corrected
fluxes in the same flux column allows for easier gross primary production
(GPP) fluxes with flux_gpp (par_correction will
have to be added to the arguemnt id_cols).
Examples
data(co2_fluxes_lrc)
flux_lrc(
fluxes_df = co2_fluxes_lrc,
type_col = type,
par_ave = PAR_ave,
f_flux = f_flux,
lrc_arg = "LRC",
nee_arg = "NEE",
er_arg = "ER",
lrc_group = c("warming"),
par_nee = 300,
par_er = 0
)
#> Joining with `by = join_by(warming)`
#> # A tibble: 488 × 6
#> PAR_ave type datetime f_flux warming par_correction
#> <dbl> <chr> <dttm> <dbl> <chr> <lgl>
#> 1 1158. NEE 2020-08-08 16:31:00 34.2 control TRUE
#> 2 1158. NEE 2020-08-08 16:31:00 0.489 control NA
#> 3 0.0941 ER 2020-08-22 10:56:45 22.5 control TRUE
#> 4 0.0941 ER 2020-08-22 10:56:45 22.5 control NA
#> 5 0.119 ER 2020-08-22 11:00:15 29.9 control TRUE
#> 6 0.119 ER 2020-08-22 11:00:15 29.9 control NA
#> 7 0.131 ER 2020-08-22 11:03:30 26.3 control TRUE
#> 8 0.131 ER 2020-08-22 11:03:30 26.3 control NA
#> 9 81.9 NEE 2020-08-22 11:07:00 -1.73 control TRUE
#> 10 81.9 NEE 2020-08-22 11:07:00 13.4 control NA
#> # ℹ 478 more rows