correct_all.Rdcorrect_all performs corrections for tree life status, overgrown recruits cases, size measurement errors and POM changes, by calling correct_alive, correct_size and correct_recruits in this order.
correct_all( data, id_col = getOption("id_col"), time_col = getOption("time_col"), status_col = getOption("status_col"), plot_col = getOption("plot_col"), byplot = TRUE, dead_confirmation_censuses = 2, use_size = FALSE, invariant_columns = c("Genus", "Species", "binomial_name", "Forest", "Family"), size_col = getOption("size_col"), species_col = "binomial_name", POM_col = getOption("POM_col"), measure_type = getOption("measure_type"), positive_growth_threshold = 5, negative_growth_threshold = -2, default_POM = 1.3, pioneers = c("Cecropia", "Pourouma"), pioneers_treshold = 7.5, dbh_min = 10 )
| data | data.frame, containing forest inventories in the form of a long-format time series - one line corresponds to a measurement for one individual at a given census time. |
|---|---|
| id_col | character, name of the column containing trees unique IDs. |
| time_col | character, name of the column containing census years. |
| status_col | character, name of the column corresponding to tree status: 0/FALSE for dead, 1/TRUE for alive. |
| plot_col | character, name of the column containing plot indices or names. |
| byplot | logical, indicating whether the function has to process the data by plot (TRUE)or for the whole dataset (FALSE). |
| dead_confirmation_censuses | integer, defaults to 2: number of consecutive censuses for which a tree is unseen that are needed to consider the tree as dead. NB: for the trees unseen during the dead_confirmation_censuses -1 last inventories, the status cannot be corrected, thus mortality rates should not be calculated for these censuses. |
| use_size | character, defaults to FALSE. Optional argument specifying whether to use measurement column (circumference or diameter) to create a vital status field in case it does not already exist. See Details. |
| invariant_columns | character vector, containing the name of the columns for which value remain constant for a given tree (for example species name or coordinates). When a row is added by the function correct_alive, values for invariant columns are taken from the value for other censuses. Defaults to null |
| size_col | character, name of the column corresponding to tree size (circumference or diameter) measurements . |
| species_col | character, name of th column containing full species names (or other taxonomic identification) |
| POM_col | character, name of the column corresponding the Point Of Measurement (POM). |
| measure_type | character, partially matching “Circumference” or “Diameter”, indicating what is the type of the measurements. |
| positive_growth_threshold | positive numeric or integer, threshold over which an annual DIAMETER growth is considered abnormal (in cm). Defaults to 5 cm. |
| negative_growth_threshold | negative numeric or integer, threshold under which an absolute DIAMETER difference is considered abnormal. To be given in centimeters. Defaults to -2 cm. Note that this threshold is applied between two consecutive censuses, regardless of the time between them, as it assumes that a tree diameter cannot decrease more than this value, even over a long period. |
| default_POM | scalar numeric, default POM used in the dataset, in the same unit as the POM. When the value in POM_col is different from default_POM, the corrected size is given at default_POM . It defaults to 1.3 meters-according to current practice of measurement of diameter at breast height (DBH). |
| pioneers | character vector containing full species name (or other taxonomic identification)for which a specific positive growth threshold (used for instance for fast growing species for which the threshold to detect an abnormal growth is high). |
| pioneers_treshold | Positive DIAMETER growth limit to apply to pioneer species (specified in 'pioneers'), similar to . Expressed in centimeters. Defaults to 7.5 cm |
| dbh_min | scalar integer or numeric, indicating the minimum DIAMETER (in centimeters) at the default measurement height from which trees are recorded. Defaults to 10 cm. |
A data.frame with additional columns: status_corr and size_corr for corrected tree vital status and size, code_corr for correction tag and types.
data(example_census) # Short version: parameters specified using prepare_forestdata and default values prepare_forestdata(example_census, plot_col="Plot", id_col="idTree", time_col="CensusYear", status_col = "CodeAlive", size_col="Circ", measure_type = "C", POM_col = "POM")#> [1] "plot_col let to its default or previous value" #> [1] "id_col let to its default or previous value" #> [1] "time_col let to its default or previous value" #> [1] "status_col let to its default or previous value" #> [1] "size_col let to its default or previous value" #> [1] "measure_type let to its default or previous value" #> [1] "POM_col let to its default or previous value"all_cors <- suppressWarnings(correct_all(example_census, invariant_columns = c("Genus", "Species", "binomial_name", "Forest", "Family"), species_col = "binomial_name",#tag pioneer measure_type = getOption("measure_type"), pioneers = c("Cecropia","Pourouma"),#tag pioneer pioneers_treshold = 7.5))#> | | | 0% | 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|======================================================================| 100%# Full call: all_cors <- suppressWarnings(correct_all(example_census, id_col = "idTree", time_col = "CensusYear", status_col = "CodeAlive", plot_col = "Plot", byplot = TRUE, dead_confirmation_censuses = 2, use_size = FALSE, invariant_columns = c("Genus", "Species", "binomial_name", "Forest", "Family"), size_col = "Circ", species_col = "binomial_name",#tag pioneer POM_col = "POM", measure_type = "C", positive_growth_threshold = 5, negative_growth_threshold = -2, default_POM = 1.3, pioneers = c("Cecropia","Pourouma"),#tag pioneer pioneers_treshold = 7.5, dbh_min = 10))#> | | | 0% | |=================================== | 50% | |======================================================================| 100% #> | | | 0% | | | 1% | |= | 1% | |= | 2% | |== | 2% | |== | 3% | |== | 4% | |=== | 4% | |=== | 5% | |==== | 5% | |==== | 6% | |===== | 6% | |===== | 7% | |===== | 8% | |====== | 8% | |====== | 9% | |======= | 9% | 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