Package 'fluxible' reference manual

Title:	Ecosystem Gas Fluxes Calculations for Closed Loop Chamber Setup
Description:	Processes the raw data from closed loop flux chamber (or tent) setups into ecosystem gas fluxes usable for analysis. It goes from a data frame of gas concentration over time (which can contain several measurements) and a meta data file indicating which measurement was done when, to a data frame of ecosystem gas fluxes including quality diagnostics. Functions provided include different models (exponential as described in Zhao et al (2018) <doi:10.1016/j.agrformet.2018.08.022>, quadratic and linear) to estimate the fluxes from the raw data, quality assessment, plotting for visual check and calculation of fluxes based on the setup specific parameters (chamber size, plot area, ...).
Authors:	Joseph Gaudard [aut, cre] , Paul Efren Santos-Andrade [aut], Richard James Telford [aut]
Maintainer:	Joseph Gaudard <[email protected]>
License:	GPL (>= 3)
Version:	1.0.1
Built:	2025-03-03 17:29:12 UTC
Source:	https://github.com/plant-functional-trait-course/fluxible

CO2 concentration

Description

CO2 concentration with measurements meta data

Usage

co2_conc
co2_conc

Format

A tibble with 1251 rows and 13 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.
turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
f_start: Datetime at which the measurement was started.
f_end: Datetime at which the measurement ended.
f_fluxid: Unique ID for each flux.
f_n_conc: Number of data point per flux.
f_ratio: Ratio of n_conc over length of the measurement (in seconds).
f_flag_match: Data quality flags.

Examples

co2_conc
co2_conc

CO2 concentration

Description

CO2 concentration with measurements meta data, with missing data.

Usage

co2_conc_missing
co2_conc_missing

Format

A tibble with 668 rows and 13 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.
turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
f_start: Datetime at which the measurement was started.
f_end: Datetime at which the measurement ended.
f_fluxid: Unique ID for each flux.
f_n_conc: Number of data point per flux.
f_ratio: Ratio of n_conc over length of the measurement (in seconds).
f_flag_match: Data quality flags.

Examples

co2_conc_missing
co2_conc_missing

CO2 concentration with missing data

Description

Continuous CO2 concentration as measured on the field, with missing data.

Usage

co2_df_missing
co2_df_missing

Format

A tibble with 1148 rows and 5 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.

Examples

co2_df_missing
co2_df_missing

CO2 concentration

Description

Continuous CO2 concentration as measured on the field

Usage

co2_df_short
co2_df_short

Format

A tibble with 1801 rows and 5 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.

Examples

co2_df_short
co2_df_short

CO2 fluxes

Description

Calculated CO2 fluxes

Usage

co2_fluxes
co2_fluxes

Format

A tibble with 6 rows and 11 variables

f_fluxid: Unique ID for each flux.
f_slope_tz: Slope of C(t) at t zero.
f_temp_air_ave: Air temperature inside the flux chamber in Celsius averaged over the flux measurement.
f_flux: CO2 flux in mmol/sqm/hour.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm averaged over the flux measurement.
temp_soil: Ground temperature inside the flux chamber in Celsius averaged over the flux measurement.
turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
f_start: Datetime at which the measurement started.
temp_fahr: Air temperature inside the flux chamber in Fahrenheit averaged over the flux measurement.
temp_kelvin: Air temperature inside the flux chamber in Kelvin averaged over the flux measurement.

Examples

co2_fluxes
co2_fluxes

CO2 concentration at Liahovden

Description

CO2 concentration at Liahovden site, used in example in readme file

Usage

co2_liahovden
co2_liahovden

Format

A tibble with 89692 rows and 5 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.

Examples

co2_liahovden
co2_liahovden

CO2 concentration

Description

CO2 concentration used to make the plot in the poster

Usage

conc_poster
conc_poster

Format

A tibble with 530 rows and 11 variables

datetime: Datetime at which CO2 concentration was recorded.
conc: CO2 concentration in ppm.
f_fluxid: Unique ID for each flux.
f_quality_flag: quality flag advising if the slope has to be replaced by 0 or NA
f_start: Datetime at which the measurement was started.
f_RMSE: RMSE of the exponential fit and the measured data
f_cor_coef: coefficient of correlation between gas concentration and time
f_b: b parameter of the C(t) function, calculated by optim() with b_est as starting point.
f_cut: Indicating if the measurement should be kept (keep) or discarded (cut).
f_fit: C(t), modeled CO2 concentration as a function of time.
fit_slope: Output of linear model of CO2 concentration passing by C(tz) and a slope of slope_tz.

Examples

conc_poster
conc_poster

calculates ecosystem gas fluxes

Description

calculates a flux based on the rate of change of gas concentration over time

Usage

flux_calc(
  slopes_df,
  slope_col,
  datetime_col,
  temp_air_col,
  chamber_volume,
  atm_pressure,
  plot_area,
  f_fluxid = f_fluxid,
  conc_unit,
  flux_unit,
  cols_keep = c(),
  cols_ave = c(),
  tube_volume,
  temp_air_unit = "celsius",
  f_cut = f_cut,
  keep_arg = "keep",
  cut = TRUE,
  fit_type = c()
)
flux_calc(
  slopes_df,
  slope_col,
  datetime_col,
  temp_air_col,
  chamber_volume,
  atm_pressure,
  plot_area,
  f_fluxid = f_fluxid,
  conc_unit,
  flux_unit,
  cols_keep = c(),
  cols_ave = c(),
  tube_volume,
  temp_air_unit = "celsius",
  f_cut = f_cut,
  keep_arg = "keep",
  cut = TRUE,
  fit_type = c()
)

Arguments

`slopes_df`	dataframe of flux slopes
`slope_col`	column containing the slope to calculate the flux (in ppms^(-1) or ppbs^(-1))
`datetime_col`	column containing the datetime of each gas concentration measurements in slopes_df. The first one after cutting will be kept as datetime of each flux in the output.
`temp_air_col`	column containing the air temperature used to calculate fluxes. Will be averaged with NA removed.
`chamber_volume`	volume of the flux chamber in L, can also be a column in case it is a variable
`atm_pressure`	atmospheric pressure, can be a constant (numerical) or a variable (column name)
`plot_area`	area of the plot in m^2, can also be a column in case it is a variable
`f_fluxid`	column containing the flux IDs
`conc_unit`	unit in which the concentration of gas was measured `ppm` or `ppb`
`flux_unit`	unit in which the calculated flux will be `mmol` outputs fluxes in mmol * m^(-2)h^(-1); `micromol` outputs fluxes in micromol m^(-2)*h^(-1)
`cols_keep`	columns to keep from the input to the output. Those columns need to have unique values for each flux, as distinct() is applied.
`cols_ave`	columns with values that should be averaged for each flux in the output. Note that NA are removed in mean calculation.
`tube_volume`	volume of the tubing in L, can also be a column in case it is a variable
`temp_air_unit`	units in which air temperature was measured. Has to be either `celsius` (default), `fahrenheit` or `kelvin.`
`f_cut`	column containing cutting information
`keep_arg`	name in `f_cut` of data to keep
`cut`	if 'TRUE' (default), the measurements will be cut according to 'f_cut' before calculating fluxes. This has no influence on the flux itself since the slope is provided from flux_fitting, but it will influence the values of the columns in `cols_ave`.
`fit_type`	(optional) model used in flux_fitting, exponential, quadratic or linear. Will be automatically filled if slopes_df was produced using flux_quality.

Value

a dataframe containing flux IDs, datetime of measurements' starts, fluxes in mmol*m^(-2)h^(-1) or micromolm^(-2)*h^(-1) (f_flux) according to flux_unit, temperature average for each flux in Kelvin (f_temp_ave), the total volume of the setup for each measurement (f_volume_setup), the model used in flux_fitting, any column specified in cols_keep, any column specified in cols_ave with their value averaged over the measurement after cuts and discarding NA.

Examples

data(slopes0)
flux_calc(slopes0,
f_slope,
datetime,
temp_air,
conc_unit = "ppm",
flux_unit = "mmol",
chamber_volume = 24.5,
tube_volume = 0.075,
atm_pressure = 1,
plot_area = 0.0625)
data(slopes0)
flux_calc(slopes0,
f_slope,
datetime,
temp_air,
conc_unit = "ppm",
flux_unit = "mmol",
chamber_volume = 24.5,
tube_volume = 0.075,
atm_pressure = 1,
plot_area = 0.0625)

check the items inside `flux_fun_check`

Description

check the items inside flux_fun_check

Usage

flux_check_item(arg, fn, msg, narg, df_name = NA)
flux_check_item(arg, fn, msg, narg, df_name = NA)

Arguments

`arg`	argument to be checked by `fn`
`fn`	function to check `arg`
`msg`	message to display in case `arg` is the wrong class
`narg`	name of `arg`
`df_name`	name of `arg` in case it is a data frame

Author(s)

Adam Klimes

filter cut data before calculating fluxes

Description

filter cut data before calculating fluxes

Usage

flux_cut(slopes_df, cut_col, keep_arg)
flux_cut(slopes_df, cut_col, keep_arg)

Arguments

`slopes_df`	dataset containing slopes and cut column
`cut_col`	column containing cutting information
`keep_arg`	name in cut_col of data to keep

to check the type of fit

Description

extracts the type of fit that was applied in flux_fitting or checks that the fit_type provided by the user is compatible with Fluxible

Usage

flux_fit_type(
  df,
  fit_type = c(),
  fit_type_list = c("exponential", "linear", "quadratic")
)
flux_fit_type(
  df,
  fit_type = c(),
  fit_type_list = c("exponential", "linear", "quadratic")
)

Arguments

`df`	any dataframe
`fit_type`	type of fit that was applied in flux_fitting. Needs to be filled only if the df was produced outside of the Fluxible workflow.
`fit_type_list`	list of fit types in use with Fluxible.

Fitting a model to concentration data and estimating the slope

Description

fits gas concentration over time data with a model (exponential, quadratic or linear) and provides the slope later used to calculate gas fluxes with flux_calc

Usage

flux_fitting(
  conc_df,
  conc_col,
  datetime_col,
  f_start = f_start,
  f_end = f_end,
  f_fluxid = f_fluxid,
  start_cut = 0,
  end_cut = 0,
  t_window = 20,
  cz_window = 15,
  b_window = 10,
  a_window = 10,
  roll_width = 15,
  t_zero = 0,
  fit_type
)
flux_fitting(
  conc_df,
  conc_col,
  datetime_col,
  f_start = f_start,
  f_end = f_end,
  f_fluxid = f_fluxid,
  start_cut = 0,
  end_cut = 0,
  t_window = 20,
  cz_window = 15,
  b_window = 10,
  a_window = 10,
  roll_width = 15,
  t_zero = 0,
  fit_type
)

Arguments

`conc_df`	dataframe of gas concentration over time
`conc_col`	column with gas concentration data
`datetime_col`	column with datetime of each concentration measurement Note that if there are duplicated datetime in the same f_fluxid only the first row will be kept
`f_start`	column with datetime when the measurement started
`f_end`	column with datetime when the measurement ended
`f_fluxid`	column with ID of each flux
`start_cut`	time to discard at the start of the measurements (in seconds)
`end_cut`	time to discard at the end of the measurements (in seconds)
`t_window`	enlarge focus window before and after tmin and tmax (exponential fit)
`cz_window`	window used to calculate Cz, at the beginning of cut window (exponential fit)
`b_window`	window to estimate b. It is an interval after tz where it is assumed that the model fits the data perfectly (exponential fit)
`a_window`	window at the end of the flux to estimate a (exponential fit)
`roll_width`	width of the rolling mean for CO2 when looking for tz, ideally same as cz_window (exponential fit)
`t_zero`	time at which the slope should be calculated (for quadratic fit)
`fit_type`	`exponential`, `quadratic` or `linear.` Exponential is using the exponential model from Zhao et al (2018)

Value

a dataframe with the slope at t zero (f_slope), a datetime column of t zero (f_start_z), a factor column indicating the cuts (f_cut), the time in seconds since the start of the measurement (f_time), the modeled fit (f_fit), the modeled slope (f_fit_slope), the parameters of the fit depending on the model used, and any columns present in the input. The type of fit is added as an attribute for use by the other functions.

References

Zhao, P., Hammerle, A., Zeeman, M., Wohlfahrt, G., 2018. On the calculation of daytime CO2 fluxes measured by automated closed transparent chambers. Agricultural and Forest Meteorology 263, 267–275. https://doi.org/10.1016/j.agrformet.2018.08.022

Examples

data(co2_conc)
flux_fitting(co2_conc, conc, datetime, fit_type = "exp")
flux_fitting(co2_conc, conc, datetime,  fit_type = "quadratic",
t_zero = 10, end_cut = 30)
data(co2_conc)
flux_fitting(co2_conc, conc, datetime, fit_type = "exp")
flux_fitting(co2_conc, conc, datetime,  fit_type = "quadratic",
t_zero = 10, end_cut = 30)

Fitting a model to the gas concentration curve and estimating the slope over time, using the exponential model from Zhao et al (2018)

Description

Fits an exponential expression to the concentration evolution

Usage

flux_fitting_exp(
  conc_df,
  conc_col,
  datetime_col,
  f_start,
  f_end,
  f_fluxid,
  t_window,
  cz_window,
  b_window,
  a_window,
  roll_width,
  start_cut,
  end_cut
)
flux_fitting_exp(
  conc_df,
  conc_col,
  datetime_col,
  f_start,
  f_end,
  f_fluxid,
  t_window,
  cz_window,
  b_window,
  a_window,
  roll_width,
  start_cut,
  end_cut
)

Arguments

`conc_df`	dataframe of gas concentration over time
`conc_col`	column with gas concentration
`datetime_col`	column with datetime of each concentration measurement Note that if there are duplicated datetime in the same f_fluxid only the first row will be kept
`f_start`	column with datetime when the measurement started
`f_end`	column with datetime when the measurement ended
`f_fluxid`	column with ID of each flux
`t_window`	enlarge focus window before and after tmin and tmax
`cz_window`	window used to calculate Cz, at the beginning of cut window
`b_window`	window to estimate b. It is an interval after tz where it is assumed that C fits the data perfectly
`a_window`	window at the end of the flux to estimate a
`roll_width`	width of the rolling mean for CO2 when looking for tz, ideally same as cz_window
`start_cut`	time to discard at the start of the measurements (in seconds)
`end_cut`	time to discard at the end of the measurements (in seconds)

Value

a dataframe with the slope at t zero, modeled concentration over time and exponential expression parameters

References

linear fit to gas concentration over time

Description

fits a linear model to the gas concentration over time

Usage

flux_fitting_lin(
  conc_df,
  conc_col,
  datetime_col,
  f_start,
  f_end,
  f_fluxid,
  start_cut,
  end_cut
)
flux_fitting_lin(
  conc_df,
  conc_col,
  datetime_col,
  f_start,
  f_end,
  f_fluxid,
  start_cut,
  end_cut
)

Arguments

`conc_df`	dataframe of gas concentration over time
`conc_col`	column with gas concentration
`datetime_col`	column with datetime of each concentration measurement Note that if there are duplicated datetime in the same f_fluxid only the first row will be kept
`f_start`	column with datetime when the measurement started
`f_end`	column with datetime when the measurement ended
`f_fluxid`	column with ID of each flux
`start_cut`	time to discard at the start of the measurements (in seconds)
`end_cut`	time to discard at the end of the measurements (in seconds)

Value

a df with the modeled gas concentration, slope, intercept, std error, r square and p value of the linear model

quadratic fit to gas concentration over time

Description

fits a quadratic model to the gas concentration over time

Usage

flux_fitting_quadratic(
  conc_df,
  conc_col,
  datetime_col,
  f_start,
  f_end,
  f_fluxid,
  start_cut,
  end_cut,
  t_zero
)
flux_fitting_quadratic(
  conc_df,
  conc_col,
  datetime_col,
  f_start,
  f_end,
  f_fluxid,
  start_cut,
  end_cut,
  t_zero
)

Arguments

`conc_df`	dataframe of gas concentration over time
`conc_col`	column with gas concentration
`datetime_col`	column with datetime of each concentration measurement Note that if there are duplicated datetime in the same f_fluxid only the first row will be kept
`f_start`	column with datetime when the measurement started
`f_end`	column with datetime when the measurement ended
`f_fluxid`	column with ID of each flux
`start_cut`	time to discard at the start of the measurements (in seconds)
`end_cut`	time to discard at the end of the measurements (in seconds)
`t_zero`	time at which the slope should be calculated

Value

a df with the modeled gas concentration, slope, intercept, std error, r square and p value of the quadratic model

counts quality flags

Description

provides a table of how many fluxes were attributed which quality flag. This function is incorporated in flux_quality (output as a message) but can be used alone to extract a dataframe with the flag count.

Usage

flux_flag_count(
  slopes_df,
  f_fluxid = f_fluxid,
  f_quality_flag = f_quality_flag,
  f_cut = f_cut,
  f_flags = c("ok", "discard", "zero", "force_discard", "start_error", "no_data",
    "force_ok", "force_zero"),
  cut_arg = "cut"
)
flux_flag_count(
  slopes_df,
  f_fluxid = f_fluxid,
  f_quality_flag = f_quality_flag,
  f_cut = f_cut,
  f_flags = c("ok", "discard", "zero", "force_discard", "start_error", "no_data",
    "force_ok", "force_zero"),
  cut_arg = "cut"
)

Arguments

`slopes_df`	dataframe of flux slopes
`f_fluxid`	column containing fluxes unique ID
`f_quality_flag`	column containing the quality flags
`f_cut`	column indicating which part of the flux is being cut
`f_flags`	list of flags used in the dataset (if different from default from flux_quality). If not provided, it will list only the flags that are present in the dataset (no showing 0).
`cut_arg`	argument defining that the data point should be cut out

Value

a dataframe with the number of fluxes for each quality flags and their proportion to the total

Author(s)

Vincent Belde

Examples

data(slopes30qua_flag)
flux_flag_count(slopes30qua_flag)
data(slopes30qua_flag)
flux_flag_count(slopes30qua_flag)

checking that arguments and columns are in the correct class

Description

checking that arguments and columns are in the correct class

Usage

flux_fun_check(args, fn, msg, name_df = NA)
flux_fun_check(args, fn, msg, name_df = NA)

Arguments

`args`	list of arguments or dataframe to check
`fn`	list of functions used to check (`is.numeric`, `is.character`, ...)
`msg`	list of messages to return in case of failed check
`name_df`	in case args is a df with selected columns to check origdf is the original df to take the name from for a more obvious error message

Author(s)

Adam Klimes

Calculates GEP

Description

to calculate gross ecosystem production (GEP) from net ecosystem (NEE) exchange and ecosystem respiration (ER) as GEP = NEE - ER. Datetime and other variables to keep will be taken from the NEE measurement.

Usage

flux_gep(
  fluxes_df,
  type_col,
  datetime_col,
  f_flux = f_flux,
  id_cols,
  nee_arg = "NEE",
  er_arg = "ER",
  cols_keep = "none"
)
flux_gep(
  fluxes_df,
  type_col,
  datetime_col,
  f_flux = f_flux,
  id_cols,
  nee_arg = "NEE",
  er_arg = "ER",
  cols_keep = "none"
)

Arguments

`fluxes_df`	a dataframe containing NEE and ER
`type_col`	column containing type of flux (NEE or ER)
`datetime_col`	column containing start of measurement as datetime
`f_flux`	column containing flux values
`id_cols`	columns used to identify each pair of ER and NEE
`nee_arg`	argument designating NEE fluxes in type column
`er_arg`	argument designating ER fluxes in type column
`cols_keep`	columns to keep from `fluxes_df`. Values from NEE row will be filled in GEP row. `none` (default) keeps only the columns in `id_cols`, flux, type and datetime columns; `all` keeps all the columns; can also be a vector of column names.

Value

a dataframe with GEP as NEE - ER in long format with GEP, NEE, and ER as flux type, datetime, and any column specified in cols_keep. Values of datetime and columns in cols_keep for GEP row are taken from NEE measurements.

Examples

data(co2_fluxes)
flux_gep(co2_fluxes, type, f_start, id_cols = "turfID",
cols_keep = c("temp_soil"))
data(co2_fluxes)
flux_gep(co2_fluxes, type, f_start, id_cols = "turfID",
cols_keep = c("temp_soil"))

Matching continuously measured fluxes with measurement IDs and meta data

Description

Matching a dataframe of continuously measured gas concentration data with measurement metadata from another dataframe. Measurements are paired with their metadata based on datetime. Extra variables in both dataframes are kept in the output.

Usage

flux_match(
  raw_conc,
  field_record,
  datetime_col,
  start_col,
  conc_col,
  startcrop,
  measurement_length,
  ratio_threshold = 0.5,
  time_diff = 0
)
flux_match(
  raw_conc,
  field_record,
  datetime_col,
  start_col,
  conc_col,
  startcrop,
  measurement_length,
  ratio_threshold = 0.5,
  time_diff = 0
)

Arguments

`raw_conc`	dataframe of CO2 concentration measured continuously. Has to contain at least a datetime column in ymd_hms format and a gas concentration column as double.
`field_record`	dataframe recording which measurement happened when. Has to contain at least a column containing the start of each measurement, and any other column identifying the measurements.
`datetime_col`	datetime column in raw_conc (dmy_hms format)
`start_col`	start column in field_record (dmy_hms format)
`conc_col`	concentration column in raw_conc
`startcrop`	how many seconds should be discarded at the beginning of the measurement
`measurement_length`	length of the measurement (in seconds) from the start specified in the field_record
`ratio_threshold`	ratio (number of concentration measurement compared to length of measurement in seconds) below which the data should be flagged as too little
`time_diff`	time difference (in seconds) between the two datasets. Will be added to the datetime column of the raw_conc dataset. For situations where the time was not synchronized correctly.

Value

a dataframe with concentration measurements, corresponding datetime, flux ID (f_fluxid), measurements start (f_start) and end (f_end), flags in case of no data or low number of data (f_flag_match), the number of datapoints per measurement (f_n_conc), the ratio of number of datapoints over the length of each measurement in seconds (f_ratio), and any variables present in one of the inputs.

Examples

data(co2_df_short, record_short)
flux_match(co2_df_short, record_short, datetime, start, conc, startcrop = 10,
measurement_length = 180)
data(co2_df_short, record_short)
flux_match(co2_df_short, record_short, datetime, start, conc, startcrop = 10,
measurement_length = 180)

prepares text to print for flux_plot function

Description

creates a df with quality flags and quality diagnostics to print on the plots produced by flux_plot. flux_param_lm is for fit in the lm family (linear and quadratic) flux_param_exp is for the exponential fit

Usage

flux_param_exp(slopes_df, conc_col)
flux_param_exp(slopes_df, conc_col)

Arguments

`slopes_df`	the slopes_df that is being provided to flux_plot
`conc_col`	column with gas concentration

prepares text to print in flux_plot

Description

Usage

flux_param_lm(slopes_df, conc_col)
flux_param_lm(slopes_df, conc_col)

Arguments

`slopes_df`	the slopes_df that is being provided to flux_plot
`conc_col`	column with gas concentration

plotting fluxes for visual evaluation

Description

plots the fluxes, fit and slope in facets with color code indicating quality flags This function takes time to run and is optional in the workflow, but it is still highly recommended to use it to visually check the measurements. Note that 'flux_plot' is specific to the 'fluxible' package and will work best with datasets produced following a fluxible workflow.

Usage

flux_plot(
  slopes_df,
  conc_col,
  datetime_col,
  color_discard = "#D55E00",
  color_cut = "#D55E00",
  color_ok = "#009E73",
  color_zero = "#CC79A7",
  scale_x_datetime_args = list(date_breaks = "1 min", minor_breaks = "10 sec",
    date_labels = "%e/%m \n %H:%M"),
  f_ylim_upper = 800,
  f_ylim_lower = 400,
  f_plotname = "",
  facet_wrap_args = list(ncol = 4, nrow = 3, scales = "free"),
  y_text_position = 500,
  print_plot = "FALSE",
  output = "print_only",
  ggsave_args = list()
)
flux_plot(
  slopes_df,
  conc_col,
  datetime_col,
  color_discard = "#D55E00",
  color_cut = "#D55E00",
  color_ok = "#009E73",
  color_zero = "#CC79A7",
  scale_x_datetime_args = list(date_breaks = "1 min", minor_breaks = "10 sec",
    date_labels = "%e/%m \n %H:%M"),
  f_ylim_upper = 800,
  f_ylim_lower = 400,
  f_plotname = "",
  facet_wrap_args = list(ncol = 4, nrow = 3, scales = "free"),
  y_text_position = 500,
  print_plot = "FALSE",
  output = "print_only",
  ggsave_args = list()
)

Arguments

`slopes_df`	dataset containing slopes, with flags produced by flux_quality
`conc_col`	column with gas concentration
`datetime_col`	column with datetime of each data point
`color_discard`	color for fits with a discard quality flag
`color_cut`	color for the part of the flux that is cut
`color_ok`	color for fits with an ok quality flag
`color_zero`	color for fits with a zero quality flag
`scale_x_datetime_args`	list of arguments for scale_x_datetime
`f_ylim_upper`	y axis upper limit
`f_ylim_lower`	y axis lower limit
`f_plotname`	filename for the extracted pdf file; if empty, the name of `slopes_df` will be used
`facet_wrap_args`	list of arguments for facet_wrap_paginate
`y_text_position`	position of the text box
`print_plot`	logical, if TRUE it prints the plot as a ggplot object but will take time depending on the size of the dataset
`output`	`pdfpages`, the plots are saved as A4 landscape pdf pages; `ggsave`, the plots can be saved with the ggsave function; `print_only` (default) prints the plot without creating a file (independently from 'print_plot' being TRUE or FALSE)
`ggsave_args`	list of arguments for ggsave (in case `output = "ggsave"`)

Value

plots of fluxes, with raw concentration data points, fit, slope, and color code indicating quality flags and cuts. The plots are organized in facets according to flux ID, and a text box display the quality flag and diagnostics of each measurement. The plots are returned as a ggplot object if print_plot = TRUE; if print_plot = FALSE it will not return anything but will produce a file according to the output argument.

Examples

data(slopes0_flag)
flux_plot(slopes0_flag, conc, datetime)
data(slopes30lin_flag)
flux_plot(slopes30lin_flag, conc, datetime)
data(slopes30qua_flag)
flux_plot(slopes30qua_flag, conc, datetime)
data(slopes0_flag)
flux_plot(slopes0_flag, conc, datetime)
data(slopes30lin_flag)
flux_plot(slopes30lin_flag, conc, datetime)
data(slopes30qua_flag)
flux_plot(slopes30qua_flag, conc, datetime)

plotting fluxes with exponential fit

Description

plots the fluxes that were fitted with an exponential model

Usage

flux_plot_exp(slopes_df, conc_col, datetime_col, y_text_position)
flux_plot_exp(slopes_df, conc_col, datetime_col, y_text_position)

Arguments

`slopes_df`	dataset containing slopes
`conc_col`	column with gas concentration
`datetime_col`	column with datetime of each data point
`y_text_position`	position of the text box

creates the flag column to be used by flux_plot

Description

creates a column with quality flags (from flux_quality) for the part of the rows to be kept, and cut flag for rows to be discarded

Usage

flux_plot_flag(slopes_df, param_df)
flux_plot_flag(slopes_df, param_df)

Arguments

`slopes_df`	as provided in flux_plot
`param_df`	as provided by flux_param

plotting fluxes with linear fit

Description

plots the fluxes that were fitted with a linear model

Usage

flux_plot_lin(slopes_df, conc_col, datetime_col, y_text_position)
flux_plot_lin(slopes_df, conc_col, datetime_col, y_text_position)

Arguments

`slopes_df`	dataset containing slopes
`conc_col`	column with gas concentration
`datetime_col`	column with datetime of each data point
`y_text_position`	position of the text box

plotting fluxes with a quadratic fit

Description

specific part of flux_plot for quadratic fit

Usage

flux_plot_quadratic(slopes_df, conc_col, datetime_col, y_text_position)
flux_plot_quadratic(slopes_df, conc_col, datetime_col, y_text_position)

Arguments

`slopes_df`	dataset containing slopes
`conc_col`	column with gas concentration
`datetime_col`	column with datetime of each data point
`y_text_position`	position of the text box

assessing quality of slopes calculated with flux_fitting

Description

indicates if slopes should be discarded or replaced by 0 according to quality thresholds set by user

Usage

flux_quality(
  slopes_df,
  conc_col,
  f_fluxid = f_fluxid,
  f_slope = f_slope,
  f_time = f_time,
  f_start = f_start,
  f_end = f_end,
  f_fit = f_fit,
  f_cut = f_cut,
  f_pvalue = f_pvalue,
  f_rsquared = f_rsquared,
  f_b = f_b,
  force_discard = c(),
  force_ok = c(),
  force_zero = c(),
  ratio_threshold = 0,
  fit_type = c(),
  ambient_conc = 421,
  error = 100,
  pvalue_threshold = 0.3,
  rsquared_threshold = 0.7,
  rmse_threshold = 25,
  cor_threshold = 0.5,
  b_threshold = 1,
  cut_arg = "cut"
)
flux_quality(
  slopes_df,
  conc_col,
  f_fluxid = f_fluxid,
  f_slope = f_slope,
  f_time = f_time,
  f_start = f_start,
  f_end = f_end,
  f_fit = f_fit,
  f_cut = f_cut,
  f_pvalue = f_pvalue,
  f_rsquared = f_rsquared,
  f_b = f_b,
  force_discard = c(),
  force_ok = c(),
  force_zero = c(),
  ratio_threshold = 0,
  fit_type = c(),
  ambient_conc = 421,
  error = 100,
  pvalue_threshold = 0.3,
  rsquared_threshold = 0.7,
  rmse_threshold = 25,
  cor_threshold = 0.5,
  b_threshold = 1,
  cut_arg = "cut"
)

Arguments

`slopes_df`	dataset containing slopes
`conc_col`	column containing the measured gas concentration (exponential fit)
`f_fluxid`	column containing unique IDs for each flux
`f_slope`	column containing the slope of each flux (as calculated by the flux_fitting function)
`f_time`	column containing the time of each measurement in seconds (exponential fit)
`f_start`	column with datetime of the start of the measurement (after cuts)
`f_end`	column with datetime of the end of the measurement (after cuts)
`f_fit`	column containing the modeled data (exponential fit)
`f_cut`	column containing the cutting information
`f_pvalue`	column containing the p-value of each flux (linear and quadratic fit)
`f_rsquared`	column containing the r squared of each flux (linear and quadratic fit)
`f_b`	column containing the b parameter of the exponential expression (exponential fit)
`force_discard`	vector of fluxIDs that should be discarded by the user's decision
`force_ok`	vector of fluxIDs for which the user wants to keep the calculated slope despite a bad quality flag
`force_zero`	vector of fluxIDs that should be replaced by zero by the user's decision
`ratio_threshold`	ratio of gas concentration data points over length of measurement (in seconds) below which the measurement will be considered as not having enough data points to be considered for calculations
`fit_type`	model fitted to the data, linear, quadratic or exponential. Will be automatically filled if slopes_df was produced using flux_fitting()
`ambient_conc`	ambient gas concentration in ppm at the site of measurement (used to detect measurement that started with a polluted setup)
`error`	error of the setup, defines a window outside of which the starting values indicate a polluted setup
`pvalue_threshold`	threshold of p-value below which the change of gas concentration over time is considered not significant (linear and quadratic fit)
`rsquared_threshold`	threshold of r squared value below which the linear model is considered an unsatisfactory fit (linear and quadratic fit)
`rmse_threshold`	threshold for the RMSE of each flux above which the fit is considered unsatisfactory (exponential fit)
`cor_threshold`	threshold for the correlation coefficient of gas concentration with time below which the correlation is considered not significant (exponential fit)
`b_threshold`	threshold for the b parameter. Defines a window with its opposite inside which the fit is considered good enough (exponential fit)
`cut_arg`	argument defining that the data point should be cut out

Value

a dataframe with added columns of quality flags (f_quality_flag), the slope corrected according to the quality flags (f_slope_corr), some diagnostics depending on the fit, and any columns present in the input.

Examples

data(slopes0lin)
flux_quality(slopes0lin, conc, fit_type = "li")
data(slopes30)
flux_quality(slopes30, conc, fit_type = "expo")
data(slopes0lin)
flux_quality(slopes0lin, conc, fit_type = "li")
data(slopes30)
flux_quality(slopes30, conc, fit_type = "expo")

quality assessment for the slopes estimated by flux_fitting

Description

indicates if fluxes should be discarded or replaced by 0 according to parameters set by user. flux_quality_lm is for the model of the lm family. flux_quality_exp is for the exponential model.

Usage

flux_quality_exp(
  slopes_df,
  conc_col,
  f_fluxid,
  f_slope,
  f_time,
  f_fit,
  f_cut,
  f_b,
  force_discard,
  force_ok,
  force_zero,
  rmse_threshold,
  cor_threshold,
  b_threshold
)
flux_quality_exp(
  slopes_df,
  conc_col,
  f_fluxid,
  f_slope,
  f_time,
  f_fit,
  f_cut,
  f_b,
  force_discard,
  force_ok,
  force_zero,
  rmse_threshold,
  cor_threshold,
  b_threshold
)

Arguments

`slopes_df`	dataset containing slopes, fluxID, and parameters of the exponential expression
`conc_col`	column with gas concentration
`f_fluxid`	column of ID for each measurement
`f_slope`	column containing the slope of each flux (as calculated by the flux_fitting function)
`f_time`	column containing the time of each measurement in seconds
`f_fit`	column containing the modeled data
`f_cut`	column containing the cutting information
`f_b`	column containing the b parameter of the exponential expression
`force_discard`	vector of fluxIDs that should be discarded by the user's decision
`force_ok`	vector of fluxIDs for which the user wants to keep the calculated slope despite a bad quality flag
`force_zero`	vector of fluxIDs that should be replaced by zero by the user's decision
`rmse_threshold`	threshold for the RMSE of each flux above which the fit is considered unsatisfactory
`cor_threshold`	threshold for the correlation coefficient of gas concentration with time below which the correlation is considered non significant
`b_threshold`	threshold for the b parameter. Defines a window with its opposite inside which the fit is considered good enough.

Value

same dataframe with added flag and corrected slopes columns

quality assessment for the slopes estimated by flux_fitting

Description

indicates if fluxes should be discarded or replaced by 0 according to parameters set by user. flux_quality_lm is for the model of the lm family. flux_quality_exp is for the exponential model.

Usage

flux_quality_lm(
  slopes_df,
  conc_col,
  f_fluxid,
  f_slope,
  f_cut,
  f_pvalue,
  f_rsquared,
  force_discard,
  force_ok,
  force_zero,
  pvalue_threshold,
  rsquared_threshold,
  name_df
)
flux_quality_lm(
  slopes_df,
  conc_col,
  f_fluxid,
  f_slope,
  f_cut,
  f_pvalue,
  f_rsquared,
  force_discard,
  force_ok,
  force_zero,
  pvalue_threshold,
  rsquared_threshold,
  name_df
)

Arguments

`slopes_df`	dataset containing slopes, fluxID, p.value and r.squared
`conc_col`	column with gas concentration
`f_fluxid`	column of ID for each measurement
`f_slope`	column containing the slope of each flux (as calculated by the flux_fitting function)
`f_cut`	column containing the cutting information
`f_pvalue`	column containing the p-value of each flux
`f_rsquared`	column containing the r squared to be used for the quality assessment
`force_discard`	vector of fluxIDs that should be discarded by the user's decision
`force_ok`	vector of fluxIDs for which the user wants to keep the calculated slope despite a bad quality flag
`force_zero`	vector of fluxIDs that should be replaced by zero by the user's decision
`pvalue_threshold`	threshold of p-value below which the change of gas concentration over time is considered not significant (user decided)
`rsquared_threshold`	threshold of r squared value below which the linear model is considered an unsatisfactory fit
`name_df`	name of slopes_df (used for error message)

Value

same dataframe with added flag and corrected slopes columns

CO2 and CH4 concentration

Description

CO2 and CH4 measured simultaneously

Usage

raw_twogases
raw_twogases

Format

A tibble with 21681 rows and 4 variables

co2_conc: CO2 concentration in ppm
ch4_conc: CH4 concentration in ppb
datetime: Datetime on the datapoint
temp_air: Air temperature inside the chamber in Celsius

Examples

raw_twogases
raw_twogases

Measurements meta data at Liahovden

Description

Measurements meta data as recorded on the field at site Liahovden

Usage

record_liahovden
record_liahovden

Format

A tibble with 138 rows and 3 variables

turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
round: Round of measurement.
start: Datetime at which the measurement was started.

Examples

record_liahovden
record_liahovden

Measurements meta data

Description

Measurements meta data as recorded on the field

Usage

record_short
record_short

Format

A tibble with 6 rows and 3 variables

turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
start: Datetime at which the measurement was started.

Examples

record_short
record_short

Slopes for each flux

Description

Slopes of C(t) for each flux without cut.

Usage

slopes0
slopes0

Format

A tibble with 1251 rows and 22 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.
turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
f_start: Datetime at which the measurement was started.
f_end: Datetime at which the measurement ended.
f_fluxid: Unique ID for each flux.
f_flag_match: Flags from flux_match.
f_time: Time variable of the flux in seconds.
f_cut: Indicating if the measurement should be kept (keep) or discarded (cut).
f_Cz: Cz parameter of the C(t) function.
f_Cm: Cm parameter of the C(t) function, calculated by optim() with Cm_est as starting point.
f_a: a parameter of the C(t) function, calculated by optim() with a_est as starting point.
f_b: b parameter of the C(t) function, calculated by optim() with b_est as starting point.
f_tz: tz parameter of the C(t) function, calculated by optim() with tz_est as starting point.
f_slope: Slope of C(t) at tz
f_fit: C(t), modeled CO2 concentration as a function of time.
f_fit_slope: Output of linear model of CO2 concentration passing by C(tz) and a slope of slope_tz.
f_start_z: Datetime format of tz

Examples

slopes0
slopes0

Slopes for each flux

Description

Slopes of C(t) for each flux with 0 second cut, with quality flags.

Usage

slopes0_flag
slopes0_flag

Format

A tibble with 1251 rows and 27 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.
turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
f_start: Datetime at which the measurement was started.
f_end: Datetime at which the measurement ended.
f_fluxid: Unique ID for each flux.
f_flag_match: Flags from flux_match.
f_time: Time variable of the flux in seconds.
f_cut: Indicating if the measurement should be kept (keep) or discarded (cut).
f_Cz: Cz parameter of the C(t) function.
f_Cm: Cm parameter of the C(t) function, calculated by optim() with Cm_est as starting point.
f_a: a parameter of the C(t) function, calculated by optim() with a_est as starting point.
f_b: b parameter of the C(t) function, calculated by optim() with b_est as starting point.
f_tz: tz parameter of the C(t) function, calculated by optim() with tz_est as starting point.
f_slope: Slope of C(t) at tz
f_fit: C(t), modeled CO2 concentration as a function of time.
f_fit_slope: Output of linear model of CO2 concentration passing by C(tz) and a slope of slope_tz.
f_start_z: Datetime format of tz
f_ratio: Ratio of number of data points compared to length of measurement in seconds.
f_cor_coef: coefficient of correlation between gas concentration and time
f_RMSE: RMSE of the exponential fit and the measured data
f_quality_flag: quality flag advising if the slope has to be replaced by 0 or NA
f_slope_corr: slope corrected according to quality flag

Examples

slopes0_flag
slopes0_flag

Slopes for each flux

Description

Slopes of C(t) for each flux with air temperature in various units.

Usage

slopes0_temp
slopes0_temp

Format

A tibble with 1251 rows and 24 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.
turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
f_start: Datetime at which the measurement was started.
f_end: Datetime at which the measurement ended.
f_fluxid: Unique ID for each flux.
f_flag_match: Flags from flux_match.
f_time: Time variable of the flux in seconds.
f_cut: Indicating if the measurement should be kept (keep) or discarded (cut).
f_Cz: Cz parameter of the C(t) function.
f_Cm: Cm parameter of the C(t) function, calculated by optim() with Cm_est as starting point.
f_a: a parameter of the C(t) function, calculated by optim() with a_est as starting point.
f_b: b parameter of the C(t) function, calculated by optim() with b_est as starting point.
f_tz: tz parameter of the C(t) function, calculated by optim() with tz_est as starting point.
f_slope: Slope of C(t) at tz
f_fit: C(t), modeled CO2 concentration as a function of time.
f_fit_slope: Output of linear model of CO2 concentration passing by C(tz) and a slope of slope_tz.
f_start_z: Datetime format of tz
temp_fahr: Air temperature inside the flux chamber in Fahrenheit averaged over the flux measurement.
temp_kelvin: Air temperature inside the flux chamber in Kelvin averaged over the flux measurement.

Examples

slopes0_temp
slopes0_temp

Slopes for each flux

Description

Slopes of C(t) for each flux without cut.

Usage

slopes0_vol
slopes0_vol

Format

A tibble with 1251 rows and 23 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.
turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
f_start: Datetime at which the measurement was started.
f_end: Datetime at which the measurement ended.
f_fluxid: Unique ID for each flux.
f_flag_match: Flags from flux_match.
f_time: Time variable of the flux in seconds.
f_cut: Indicating if the measurement should be kept (keep) or discarded (cut).
f_Cz: Cz parameter of the C(t) function.
f_Cm: Cm parameter of the C(t) function, calculated by optim() with Cm_est as starting point.
f_a: a parameter of the C(t) function, calculated by optim() with a_est as starting point.
f_b: b parameter of the C(t) function, calculated by optim() with b_est as starting point.
f_tz: tz parameter of the C(t) function, calculated by optim() with tz_est as starting point.
f_slope: Slope of C(t) at tz
f_fit: C(t), modeled CO2 concentration as a function of time.
f_fit_slope: Output of linear model of CO2 concentration passing by C(tz) and a slope of slope_tz.
f_start_z: Datetime format of tz
volume: volume of chamber in L

Examples

slopes0_vol
slopes0_vol

Slopes for each flux

Description

Slopes of linear fit for each flux without cut.

Usage

slopes0lin
slopes0lin

Format

A tibble with 1251 rows and 19 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.
turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
f_start: Datetime at which the measurement was started.
f_end: Datetime at which the measurement ended.
f_fluxid: Unique ID for each flux.
f_flag_match: Flags from flux_match.
f_time: Time variable of the flux in seconds.
f_cut: Indicating if the measurement should be kept (keep) or discarded (cut).
f_pvalue: P-value of the linear model of CO2 concentration over time.
f_rsquared: R squared of the linear model of CO2 concentration over time.
f_adj_rsquared: Adjusted R squared of the linear model of CO2 concentration over time.
f_intercept: Intercept of the linear model of CO2 concentration over time.
f_slope: Slope of the linear model of CO2 concentration over time.
f_fit: Output of the linear model of CO2 concentration over time.

Examples

slopes0lin
slopes0lin

Slopes for each flux

Description

Slopes of linear fit for each flux without cut, with quality flags.

Usage

slopes0lin_flag
slopes0lin_flag

Format

A tibble with 1251 rows and 22 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.
turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
f_start: Datetime at which the measurement was started.
f_end: Datetime at which the measurement ended.
f_fluxid: Unique ID for each flux.
f_flag_match: Flags from flux_match.
f_time: Time variable of the flux in seconds.
f_cut: Indicating if the measurement should be kept (keep) or discarded (cut).
f_pvalue: P-value of the linear model of CO2 concentration over time.
f_rsquared: R squared of the linear model of CO2 concentration over time.
f_adj_rsquared: Adjusted R squared of the linear model of CO2 concentration over time.
f_intercept: Intercept of the linear model of CO2 concentration over time.
f_slope: Slope of the linear model of CO2 concentration over time.
f_fit: Output of the linear model of CO2 concentration over time.
f_ratio: Ratio of number of data points compared to length of measurement in seconds.
f_quality_flag: quality flag advising if the slope has to be replaced by 0 or NA
f_slope_corr: slope corrected according to quality flag

Examples

slopes0lin_flag
slopes0lin_flag

Slopes for each flux

Description

Slopes of C(t) for each flux with a 30 seconds cut at the end of each flux.

Usage

slopes30
slopes30

Format

A tibble with 1251 rows and 22 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.
turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
f_start: Datetime at which the measurement was started.
f_end: Datetime at which the measurement ended.
f_fluxid: Unique ID for each flux.
f_flag_match: Flags from flux_match.
f_time: Time variable of the flux in seconds.
f_cut: Indicating if the measurement should be kept (keep) or discarded (cut).
f_Cz: Cz parameter of the C(t) function.
f_Cm: Cm parameter of the C(t) function, calculated by optim() with Cm_est as starting point.
f_a: a parameter of the C(t) function, calculated by optim() with a_est as starting point.
f_b: b parameter of the C(t) function, calculated by optim() with b_est as starting point.
f_tz: tz parameter of the C(t) function, calculated by optim() with tz_est as starting point.
f_slope: Slope of C(t) at tz
f_fit: C(t), modeled CO2 concentration as a function of time.
f_fit_slope: Output of linear model of CO2 concentration passing by C(tz) and a slope of slope_tz.
f_start_z: Datetime format of tz

Examples

slopes30
slopes30

Slopes for each flux

Description

Slopes of C(t) for each flux with 30 seconds end cut, with quality flags.

Usage

slopes30_flag
slopes30_flag

Format

A tibble with 1251 rows and 27 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.
turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
f_start: Datetime at which the measurement was started.
f_end: Datetime at which the measurement ended.
f_fluxid: Unique ID for each flux.
f_flag_match: Flags from flux_match.
f_time: Time variable of the flux in seconds.
f_cut: Indicating if the measurement should be kept (keep) or discarded (cut).
f_Cz: Cz parameter of the C(t) function.
f_Cm: Cm parameter of the C(t) function, calculated by optim() with Cm_est as starting point.
f_a: a parameter of the C(t) function, calculated by optim() with a_est as starting point.
f_b: b parameter of the C(t) function, calculated by optim() with b_est as starting point.
f_tz: tz parameter of the C(t) function, calculated by optim() with tz_est as starting point.
f_slope: Slope of C(t) at tz
f_fit: C(t), modeled CO2 concentration as a function of time.
f_fit_slope: Output of linear model of CO2 concentration passing by C(tz) and a slope of slope_tz.
f_start_z: Datetime format of tz
f_ratio: Ratio of number of data points compared to length of measurement in seconds.
f_cor_coef: coefficient of correlation between gas concentration and time
f_RMSE: RMSE of the exponential fit and the measured data
f_quality_flag: quality flag advising if the slope has to be replaced by 0 or NA
f_slope_corr: slope corrected according to quality flag

Examples

slopes30_flag
slopes30_flag

Slopes for each flux

Description

Slopes of linear fit for each flux with a 30 seconds cut at the end of each flux.

Usage

slopes30lin
slopes30lin

Format

A tibble with 1251 rows and 19 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.
turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
f_start: Datetime at which the measurement was started.
f_end: Datetime at which the measurement ended.
f_fluxid: Unique ID for each flux.
f_flag_match: Flags from flux_match.
f_time: Time variable of the flux in seconds.
f_cut: Indicating if the measurement should be kept (keep) or discarded (cut).
f_pvalue: P-value of the linear model of CO2 concentration over time.
f_rsquared: R squared of the linear model of CO2 concentration over time.
f_adj_rsquared: Adjusted R squared of the linear model of CO2 concentration over time.
f_intercept: Intercept of the linear model of CO2 concentration over time.
f_slope: Slope of the linear model of CO2 concentration over time.
f_fit: Output of the linear model of CO2 concentration over time.

Examples

slopes30lin
slopes30lin

Slopes for each flux

Description

Slopes of linear fit for each flux with 30 seconds end cut, with quality flags.

Usage

slopes30lin_flag
slopes30lin_flag

Format

A tibble with 1251 rows and 22 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.
turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
f_start: Datetime at which the measurement was started.
f_end: Datetime at which the measurement ended.
f_fluxid: Unique ID for each flux.
f_flag_match: Flags from flux_match.
f_time: Time variable of the flux in seconds.
f_cut: Indicating if the measurement should be kept (keep) or discarded (cut).
f_pvalue: P-value of the linear model of CO2 concentration over time.
f_rsquared: R squared of the linear model of CO2 concentration over time.
f_adj_rsquared: Adjusted R squared of the linear model of CO2 concentration over time.
f_intercept: Intercept of the linear model of CO2 concentration over time.
f_slope: Slope of the linear model of CO2 concentration over time.
f_fit: Output of the linear model of CO2 concentration over time.
f_ratio: Ratio of number of data points compared to length of measurement in seconds.
f_quality_flag: quality flag advising if the slope has to be replaced by 0 or NA
f_slope_corr: slope corrected according to quality flag

Examples

slopes30lin_flag
slopes30lin_flag

Slopes for each flux

Description

Slopes of quadratic fit for each flux with 30 seconds end cut and t_zero of 10 seconds, without quality flags. C(t) = a + bt + ct^2

Usage

slopes30qua
slopes30qua

Format

A tibble with 1251 rows and 24 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.
turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
f_start: Datetime at which the measurement was started.
f_end: Datetime at which the measurement ended.
f_fluxid: Unique ID for each flux.
f_ratio: Ratio of n_conc over length of the measurement (in seconds).
f_flag_match: Flags from flux_match.
f_time: Time variable of the flux in seconds.
f_cut: Indicating if the measurement should be kept (keep) or discarded (cut).
f_param1: b parameter of C(t)
f_param2: c parameter of C(t)
f_rsquared: R squared of the linear model of CO2 concentration over time.
f_adj_rsquared: Adjusted R squared of the linear model of CO2 concentration over time.
f_intercept: Intercept of the linear model of CO2 concentration over time.
f_pvalue: p-value of the linear model of CO2 concentration over time.
f_slope: Slope of the linear model of CO2 concentration over time.
f_fit: Output of the linear model of CO2 concentration over time.
f_fit_slope: output of linear expression describing the slope at t_zero
f_start_z: Datetime format of tz

Examples

slopes30qua
slopes30qua

Slopes for each flux

Description

Slopes of quadratic fit for each flux with 30 seconds end cut and t_zero of 10 seconds, with quality flags. C(t) = a + bt + ct^2

Usage

slopes30qua_flag
slopes30qua_flag

Format

A tibble with 1251 rows and 26 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.
turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
f_start: Datetime at which the measurement was started.
f_end: Datetime at which the measurement ended.
f_fluxid: Unique ID for each flux.
f_ratio: Ratio of n_conc over length of the measurement (in seconds).
f_flag_match: Flags from flux_match.
f_time: Time variable of the flux in seconds.
f_cut: Indicating if the measurement should be kept (keep) or discarded (cut).
f_param1: b parameter of C(t)
f_param2: c parameter of C(t)
f_rsquared: R squared of the linear model of CO2 concentration over time.
f_adj_rsquared: Adjusted R squared of the linear model of CO2 concentration over time.
f_intercept: Intercept of the linear model of CO2 concentration over time.
f_pvalue: p-value of the linear model of CO2 concentration over time.
f_slope: Slope of the linear model of CO2 concentration over time.
f_fit: Output of the linear model of CO2 concentration over time.
f_fit_slope: output of linear expression describing the slope at t_zero
f_start_z: Datetime format of tz
f_quality_flag: quality flag advising if the slope has to be replaced by 0 or NA
f_slope_corr: slope corrected according to quality flag

Examples

slopes30qua_flag
slopes30qua_flag

Slopes for each flux

Description

Slopes of C(t) for each flux with a cut of 60 seconds at the end of each flux.

Usage

slopes60
slopes60

Format

A tibble with 1251 rows and 22 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.
turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
f_start: Datetime at which the measurement was started.
f_end: Datetime at which the measurement ended.
f_fluxid: Unique ID for each flux.
f_flag_match: Flags from flux_match.
f_time: Time variable of the flux in seconds.
f_cut: Indicating if the measurement should be kept (keep) or discarded (cut).
f_Cz: Cz parameter of the C(t) function.
f_Cm: Cm parameter of the C(t) function, calculated by optim() with Cm_est as starting point.
f_a: a parameter of the C(t) function, calculated by optim() with a_est as starting point.
f_b: b parameter of the C(t) function, calculated by optim() with b_est as starting point.
f_tz: tz parameter of the C(t) function, calculated by optim() with tz_est as starting point.
f_slope: Slope of C(t) at tz
f_fit: C(t), modeled CO2 concentration as a function of time.
f_fit_slope: Output of linear model of CO2 concentration passing by C(tz) and a slope of slope_tz.
f_start_z: Datetime format of tz

Examples

slopes60
slopes60

Slopes for each flux

Description

Slopes of linear fit for each flux with a 60 seconds cut at the end of each flux.

Usage

slopes60lin
slopes60lin

Format

A tibble with 1251 rows and 19 variables

datetime: Datetime at which CO2 concentration was recorded.
temp_air: Air temperature inside the flux chamber in Celsius.
temp_soil: Ground temperature inside the flux chamber in Celsius.
conc: CO2 concentration in ppm.
PAR: Photosynthetically active radiation inside the chamber in micromol/s/sqm.
turfID: Unique ID of the turf in which the measurement took place.
type: Type of measurement: ecosystems respiration (ER) or net ecosystem exchange (NEE).
f_start: Datetime at which the measurement was started.
f_end: Datetime at which the measurement ended.
f_fluxid: Unique ID for each flux.
f_flag_match: Flags from flux_match.
f_time: Time variable of the flux in seconds.
f_cut: Indicating if the measurement should be kept (keep) or discarded (cut).
f_pvalue: P-value of the linear model of CO2 concentration over time.
f_rsquared: R squared of the linear model of CO2 concentration over time.
f_adj_rsquared: Adjusted R squared of the linear model of CO2 concentration over time.
f_intercept: Intercept of the linear model of CO2 concentration over time.
f_slope: Slope of the linear model of CO2 concentration over time.
f_fit: Output of the linear model of CO2 concentration over time.

Examples

slopes60lin
slopes60lin

Field record

Description

Field record

Usage

twogases_record
twogases_record

Format

A tibble with 12 rows and 1 variable

start: Start datetime of each flux measurement

Examples

twogases_record
twogases_record

Package 'fluxible'

Help Index

CO2 concentration

Description

Usage

Format

Examples

CO2 concentration

Description

Usage

Format

Examples

CO2 concentration with missing data

Description

Usage

Format

Examples

CO2 concentration

Description

Usage

Format

Examples

CO2 fluxes

Description

Usage

Format

Examples

CO2 concentration at Liahovden

Description

Usage

Format

Examples

CO2 concentration

Description

Usage

Format

Examples

calculates ecosystem gas fluxes

Description

Usage

Arguments

Value

Examples

check the items inside flux_fun_check

Description

Usage

Arguments

Author(s)

filter cut data before calculating fluxes

Description

Usage

Arguments

to check the type of fit

Description

Usage

Arguments

Fitting a model to concentration data and estimating the slope

Description

Usage

Arguments

Value

References

Examples

Fitting a model to the gas concentration curve and estimating the slope over time, using the exponential model from Zhao et al (2018)

Description

Usage

Arguments

Value

References

linear fit to gas concentration over time

Description

Usage

Arguments

Value

quadratic fit to gas concentration over time

Description

Usage

Arguments

Value

counts quality flags

check the items inside `flux_fun_check`