calculate regeneration parameters by plot, species and year — calc_reg_plot

This function calculates for each plot, species and year the number of seedlings and established regeneration per ha (or interval with mean and confidence interval using a log transformation), and the approximate rubbing damage percentage for seedlings and established regeneration. For core area plots, these variables are calculated for each subplot.

calc_reg_plot_species(data_regeneration)

Arguments

data_regeneration: dataframe on tree regeneration with variables plot_id, plottype, subplot_id, height_class, species, nr_of_regeneration, rubbing_damage_number, period, year, subcircle, plotarea_ha, min_number_of_regeneration and max_number_of_regeneration.

Value

dataframe with columns plot, subplot, species, year, period, mean_number_established_ha, lci_number_established_ha, uci_number_established_ha, mean_number_seedlings_ha, lci_number_seedlings_ha, uci_number_seedlings_ha, mean_rubbing_damage_perc_established, lci_rubbing_damage_perc_established, uci_rubbing_damage_perc_established, mean_rubbing_damage_perc_seedlings, lci_rubbing_damage_perc_seedlings, uci_rubbing_damage_perc_seedlings, approx_nr_established_ha, approx_nr_seedlings_ha, approx_rubbing_damage_perc_established, approx_rubbing_damage_perc_seedlings.

Examples

library(forrescalc)
# (add path to your own fieldmap database here)
path_to_fieldmapdb <-
  system.file("example/database/mdb_bosres.sqlite", package = "forrescalc")
data_regeneration <- load_data_regeneration(path_to_fieldmapdb)
calc_reg_plot_species(data_regeneration)
#> # A tibble: 99 × 24
#>    plottype plot_id subplot_id period  year species approx_nr_established_ha
#>    <chr>      <int>      <int>  <int> <int>   <int>                    <dbl>
#>  1 CA         11000     155511      1  2000      NA                        0
#>  2 CA         11000     155511      2  2011       7                      200
#>  3 CA         11000     155511      3  2021       7                     1000
#>  4 CA         11000     155512      1  2000      NA                        0
#>  5 CA         11000     155513      1  2000      NA                        0
#>  6 CA         11000     155521      2  2011       7                        0
#>  7 CA         11000     155521      2  2011      87                        0
#>  8 CA         11000     155521      3  2021       7                     1700
#>  9 CA         11000     155531      2  2011       7                        0
#> 10 CA         11000     155531      2  2011      87                        0
#> # ℹ 89 more rows
#> # ℹ 17 more variables: approx_nr_seedlings_ha <dbl>,
#> #   approx_rubbing_damage_perc_established <dbl>,
#> #   approx_rubbing_damage_perc_seedlings <dbl>,
#> #   rubbing_damage_nr_established_ha <dbl>,
#> #   rubbing_damage_nr_seedlings_ha <dbl>, mean_number_established_ha <dbl>,
#> #   lci_number_established_ha <dbl>, uci_number_established_ha <dbl>, …