aggregate regeneration parameters by plot, species and year

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), the number and percentage of subplots in which the species is regenerating and the approximate rubbing damage percentage per hectare. This calculation is designed for core areas,that consist of different subplots.

calc_reg_core_area_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, species, year, nr_of_subplots_with_regeneration, perc_subplots_with_regeneration, 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_CA <-
  load_data_regeneration(path_to_fieldmapdb, plottype = "CA")
calc_reg_core_area_species(data_regeneration_CA)
#> # A tibble: 32 × 25
#>    plottype plot_id period  year species nr_of_subplots_with_regeneration
#>    <chr>      <int>  <int> <int>   <int>                            <int>
#>  1 CA         11000      1  2000      NA                                3
#>  2 CA         11000      2  2011       7                                3
#>  3 CA         11000      2  2011      87                                2
#>  4 CA         11000      3  2021       7                                3
#>  5 CA         11000      3  2021      16                                1
#>  6 CA         11000      3  2021      87                                1
#>  7 CA         21000      1  2009       7                                3
#>  8 CA         21000      1  2009      16                                3
#>  9 CA         21000      1  2009      27                                3
#> 10 CA         21000      1  2009      87                                3
#> # ℹ 22 more rows
#> # ℹ 19 more variables: perc_subplots_with_regeneration <dbl>,
#> #   approx_nr_established_ha <dbl>, 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>, …