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
Details
The light response curves are calculated with a quadratic of the form flux(PAR) = a * PAR2 + b * PAR + c
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: 231 × 6
#> PAR_ave type datetime f_flux warming PAR_corrected_flux
#> <dbl> <chr> <dttm> <dbl> <chr> <dbl>
#> 1 1158. NEE 2020-08-08 16:31:00 0.489 control 34.2
#> 2 0.0941 ER 2020-08-22 10:56:45 22.5 control 22.5
#> 3 0.119 ER 2020-08-22 11:00:15 29.9 control 29.9
#> 4 0.131 ER 2020-08-22 11:03:30 26.3 control 26.3
#> 5 81.9 NEE 2020-08-22 11:07:00 13.4 control -1.73
#> 6 87.1 NEE 2020-08-22 11:10:15 13.1 control -1.70
#> 7 88.3 NEE 2020-08-22 11:14:45 23.6 control 8.87
#> 8 0.218 ER 2020-08-22 11:19:45 67.2 warming 67.2
#> 9 0.252 ER 2020-08-22 11:22:45 48.8 warming 48.8
#> 10 0.324 ER 2020-08-22 11:25:45 65.7 warming 65.7
#> # ℹ 221 more rows