In inbo/forrescalc: Calculation of Aggregated Values on Dendrometry, Regeneration and Vegetation of Forests, Starting from Individual Tree Measures from Fieldmap

knitr::opts_chunk$set(echo = FALSE)
library(forrescalc)
library(dplyr)
library(tidyr)
library(knitr)
library(kableExtra)
library(readr)
library(ggplot2)
path_to_fieldmap <-
  "C:/3BR/2_VisualisatieDataBR/3MDB_BOSRES_selectieEls/FieldMapData_MDB_BOSRES_selectieEls.accdb" #nolint: line_length_linter

Selection of forest reserves and plots

Following the method of Bosch & Partner (2014), selection of forest reserves based on the 3 criteria should be done in 2 steps:

• select the forest reserves that meet these criteria
• select the plots in the reserves that meet these criteria

But is it necessary to do this in 2 steps? Is there any difference in selected between doing 2 steps and doing only the last step?

The 2-step method:

data_dendro <- load_data_dendrometry(path_to_fieldmap) %>%
  filter(alive_dead == 11)
selection_2steps <- data_dendro %>%
  select_for_das_indicator(
    grouping_vars = c("forest_reserve", "year", "period")
  ) %>%
  inner_join(data_dendro, by = c("forest_reserve", "year", "period")) %>%
  select_for_das_indicator(grouping_vars = c("plot_id", "year", "period")) %>%
  inner_join(
    data_dendro %>%
      select(plot_id, year, period, forest_reserve) %>%
      distinct(),
    by = c("plot_id", "year", "period")
  )

selection_2steps %>%
  group_by(forest_reserve, period) %>%
  summarise(n_plots = n()) %>%
  ungroup() %>%
  pivot_wider(names_from = period,
              names_prefix = "period",
              values_from = n_plots) %>%
  kable() %>%
  kable_styling(full_width = FALSE)

selection_2steps %>%
  pivot_wider(names_from = period,
              names_prefix = "period",
              values_from = year) %>%
  group_by(forest_reserve) %>%
  summarise(
    n_plots_period1 = sum(!is.na(period1) & is.na(period2)),
    n_plots_period2 = sum(is.na(period1) & !is.na(period2)),
    n_plots_period12 = sum(!is.na(period1) & !is.na(period2))
  ) %>%
  ungroup() %>%
  kable() %>%
  kable_styling(full_width = FALSE)

Only the last step:

selection_1step <- data_dendro %>%
  select_for_das_indicator(grouping_vars = c("plot_id", "year", "period")) %>%
  inner_join(
    data_dendro %>%
      select(plot_id, year, period, forest_reserve) %>%
      distinct(),
    by = c("plot_id", "year", "period")
  )

selection_1step %>%
  group_by(forest_reserve, period) %>%
  summarise(n_plots = n()) %>%
  ungroup() %>%
  pivot_wider(names_from = period,
              names_prefix = "period",
              values_from = n_plots) %>%
  kable() %>%
  kable_styling(full_width = FALSE)

selection_1step %>%
  pivot_wider(names_from = period,
              names_prefix = "period",
              values_from = year) %>%
  group_by(forest_reserve) %>%
  summarise(
    n_plots_period1 = sum(!is.na(period1) & is.na(period2)),
    n_plots_period2 = sum(is.na(period1) & !is.na(period2)),
    n_plots_period12 = sum(!is.na(period1) & !is.na(period2))
  ) %>%
  ungroup() %>%
  kable() %>%
  kable_styling(full_width = FALSE)

Calculation of criteria on reserve level (for omitted reserves)

data_dendro %>%
  group_by(forest_reserve, year, period) %>%
  summarise(
    dbh_mm_average = mean(.data$dbh_mm)
  ) %>%
  ungroup() %>%
  left_join(data_dendro, by = c("forest_reserve", "year", "period")) %>%
  left_join(
    read_csv2(system.file("./extdata/das_tree_groups.csv",
                          package = "forrescalc")),
    by = "species"
  ) %>%
  group_by(forest_reserve, year, period, dbh_mm_average, group) %>%
  summarise(
    basal_area_m2_ha = sum(.data$basal_area_alive_m2_ha)
  ) %>%
  ungroup() %>%
  group_by(forest_reserve, year, period, dbh_mm_average) %>%
  mutate(
    basal_area_proportion =
      .data$basal_area_m2_ha / sum(.data$basal_area_m2_ha)
  ) %>%
  ungroup() %>%
  kable()

Conclusie

Heirnisse valt weg doordat de gemiddelde diameter van de bomen te laag is.

Ander aandachtspunt voor dit reservaat (moest het wel meegenomen kunnen worden): de plots zijn niet allemaal in dezelfde winter opgemeten. Zijn er nog reservaten waarbij dit het geval is? Hoe gaan we de berekening in dit geval uitvoeren?

Preliminary results on reserve level

Yearly change of basal area for the studied forest reserves

calc_das_indicator(data_dendro) %>%
  ggplot(aes(x = forest_reserve, y = d_res)) + geom_bar(stat = "identity")

Yearly proportional change of the basal area for each species group.

calc_das_indicator(data_dendro) %>%
  ggplot(aes(x = forest_reserve, y = d_group, fill = group)) +
  geom_bar(stat = "identity", position = "dodge")

inbo/forrescalc documentation built on Sept. 28, 2024, 11:45 a.m.