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Account for coarse fragments and add survey years
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@heleenderoo
heleenderoo committed Nov 22, 2023
1 parent e2de4d6 commit 6ade3fb
Showing 1 changed file with 54 additions and 30 deletions.
84 changes: 54 additions & 30 deletions src/specific_esb_requests/soil_fertility_data_for_ground_vegetation_plots.R
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Original file line number Diff line number Diff line change
Expand Up @@ -9,12 +9,7 @@

# 1. Prepare required packages ----

stopifnot(require("sf"),
require("tidyverse"),
require("openxlsx"),
require("parsedate"),
require("googlesheets4"),
require("googledrive"),
stopifnot(require("tidyverse"),
require("assertthat"))

# 2. Import "layer 1" data for soil (Level II) ----
Expand All @@ -27,9 +22,25 @@ read_processed(survey_forms = c("si", "so"),

so_som_working <- so_som %>%
# Filter for records starting from 1996
filter(.data$survey_year >= 1996) %>%
# Update 20231123: also include survey years before 1996
# filter(.data$survey_year >= 1996) %>%
# Remove redundant layers
filter(!is.na(.data$layer_number))
filter(!is.na(.data$layer_number)) %>%
# Account for coarse fragments
# Assume they are 0 if NA
mutate(coarse_fragment_vol_frac =
ifelse(is.na(.data$coarse_fragment_vol),
0,
.data$coarse_fragment_vol / 100)) %>%
# Introduce a new variable for bulk density
# which represents the mass (kg) of fine earth per volume (m3) of total soil
# (instead of "per volume of fine earth")
# This is the variable to be used as a weighting factor
mutate(bulk_density_total_soil =
ifelse(!is.na(.data$bulk_density) &
!is.na(.data$coarse_fragment_vol_frac),
.data$bulk_density * (1 - .data$coarse_fragment_vol_frac),
NA))


# 3. Import list of plots with ground vegetation data ----
Expand All @@ -47,7 +58,8 @@ plots_vegetation <-
ph_h2o_0_10 = NA,
c_to_n_forest_floor = NA,
ph_cacl2_forest_floor = NA,
ph_h2o_forest_floor = NA)
ph_h2o_forest_floor = NA,
survey_years = NA)

# Assert: No issue with Polish plot codes

Expand All @@ -72,12 +84,18 @@ for (i in seq_len(nrow(plots_vegetation))) {
if (!identical(which(so_som_working$plot_id == plot_id_i),
integer(0))) {


## 4.1. 0 - 10 cm depth layer ----

# Some of the below-ground fixed-depth layers are not "conform"
# the theoretical depths (e.g. 4_503)
# Therefore, harmonise the layers covering the 0 - 10 cm depth range
# using function "harmonise_layer_to_depths"
# Across each of the layers (partly) within the 0 - 10 cm depth range,
# this function will take a weighted average, using
# - bulk_density_total_soil;
# - the portion of each layer's depth range contributing to the
# 0 - 10 cm depth range;
# as a weighting factor

# Select the layers covering the 0 - 10 cm depth range

Expand All @@ -100,12 +118,12 @@ for (i in seq_len(nrow(plots_vegetation))) {
source("./src/functions/harmonise_layer_to_depths.R")

df_0_10 <- df_sub %>%
group_by(unique_survey_repetition, plot_id) %>%
group_by(unique_survey_repetition, plot_id, survey_year) %>%
reframe(organic_carbon_total_avg =
harmonise_layer_to_depths(limit_sup = 0,
limit_inf = 10,
bulk_density =
.data$bulk_density,
.data$bulk_density_total_soil,
upper_depths =
.data$layer_limit_superior,
lower_depths =
Expand All @@ -118,7 +136,7 @@ for (i in seq_len(nrow(plots_vegetation))) {
harmonise_layer_to_depths(limit_sup = 0,
limit_inf = 10,
bulk_density =
.data$bulk_density,
.data$bulk_density_total_soil,
upper_depths =
.data$layer_limit_superior,
lower_depths =
Expand All @@ -131,7 +149,7 @@ for (i in seq_len(nrow(plots_vegetation))) {
harmonise_layer_to_depths(limit_sup = 0,
limit_inf = 10,
bulk_density =
.data$bulk_density,
.data$bulk_density_total_soil,
upper_depths =
.data$layer_limit_superior,
lower_depths =
Expand All @@ -144,7 +162,7 @@ for (i in seq_len(nrow(plots_vegetation))) {
harmonise_layer_to_depths(limit_sup = 0,
limit_inf = 10,
bulk_density =
.data$bulk_density,
.data$bulk_density_total_soil,
upper_depths =
.data$layer_limit_superior,
lower_depths =
Expand All @@ -158,7 +176,7 @@ for (i in seq_len(nrow(plots_vegetation))) {
harmonise_layer_to_depths(limit_sup = 0,
limit_inf = 10,
bulk_density =
.data$bulk_density,
.data$bulk_density_total_soil,
upper_depths =
.data$layer_limit_superior,
lower_depths =
Expand All @@ -171,7 +189,7 @@ for (i in seq_len(nrow(plots_vegetation))) {
harmonise_layer_to_depths(limit_sup = 0,
limit_inf = 10,
bulk_density =
.data$bulk_density,
.data$bulk_density_total_soil,
upper_depths =
.data$layer_limit_superior,
lower_depths =
Expand All @@ -184,18 +202,21 @@ for (i in seq_len(nrow(plots_vegetation))) {
# Aggregate per plot_id
group_by(plot_id) %>%
reframe(organic_carbon_total_avg =
mean(organic_carbon_total_avg, na.rm = TRUE),
n_total_avg =
mean(n_total_avg, na.rm = TRUE),
ph_cacl2_avg =
mean(ph_cacl2_avg, na.rm = TRUE),
ph_h2o_avg =
mean(ph_h2o_avg, na.rm = TRUE),
# LOQs
organic_carbon_total_loq =
mean(organic_carbon_total_loq, na.rm = TRUE),
n_total_loq =
mean(n_total_loq, na.rm = TRUE))
mean(organic_carbon_total_avg, na.rm = TRUE),
n_total_avg =
mean(n_total_avg, na.rm = TRUE),
ph_cacl2_avg =
mean(ph_cacl2_avg, na.rm = TRUE),
ph_h2o_avg =
mean(ph_h2o_avg, na.rm = TRUE),
# LOQs
organic_carbon_total_loq =
mean(organic_carbon_total_loq, na.rm = TRUE),
n_total_loq =
mean(n_total_loq, na.rm = TRUE),
# Add survey years
survey_years =
paste(sort(unique(.data$survey_year)), collapse = "_"))


# If any 0 - 10 cm layers were reported for the given plot_id
Expand All @@ -218,6 +239,8 @@ for (i in seq_len(nrow(plots_vegetation))) {

plots_vegetation$ph_h2o_0_10[i] <- round(df_0_10$ph_h2o_avg, 2)

plots_vegetation$survey_years[i] <- df_0_10$survey_years

}


Expand Down Expand Up @@ -358,7 +381,8 @@ colSums(!is.na(plots_vegetation))

write.csv2(plots_vegetation,
paste0("./output/specific_esb_requests/",
"plots_vegetation_with_soil_fertility_data.csv"),
as.character(format(Sys.Date(), format = "%Y%m%d")),
"_plots_vegetation_with_soil_fertility_data.csv"),
row.names = FALSE,
na = "")

Expand Down

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