Clean up

R/load_packages.R

@@ -9,4 +9,5 @@ library(writexl)
 #devtools::install_github("Between-the-Fjords/dataDownloader")
 library(dataDownloader)
 library(validate)
+library(janitor)
 

R/vegetation/read_biomass.R

@@ -0,0 +1,138 @@
+#############################################################
+### READ IN FUNCTIONAL REMOVAL BIOMASS DATA - 2015 - 2021 ###
+#############################################################
+
+source("R/load_packages.R")
+
+#Download data from OSF
+# run the code from L10-L13 if you need to download the data from OSF
+
+get_file(node = "4c5v2",
+         file = "FunCaB_raw_biomass_2015_2021.csv",
+         path = "raw_data/biomass",
+         remote_path = "Vegetation data/Functional Group Biomass Removals")
+
+# download 2022 data
+get_file(node = "tx9r2",
+         file = "FUNDER Forbs_Graminoids_Bryophytes.xlsx",
+         path = "raw_data/biomass",
+         remote_path = "1_Vegetation/Raw_data")
+
+
+### 2015 - 2021
+path <- "raw_data/biomass/FunCaB_raw_biomass.xlsx"
+
+biomass_raw <- path %>%
+  excel_sheets() %>%
+  set_names() %>%
+  map_df(read_excel, path = path, col_types = c("numeric", "text", "numeric", "text", "text", "date", "text", "numeric", "text", "text"))
+
+# impute missing rounds
+impute_round = tribble(
+  ~year, ~site, ~block, ~round_new,
+  2016, "ALR", list(5), "2",
+  2016, "ARH", list(1, 2, 3, 4), "1",
+  2016, "FAU", list(1, 2, 4, 5), "1",
+  2016, "RAM", list(4, 5, 6, 8), "1",
+  2016, "VIK", list(2, 3, 4, 5), "1"
+) %>%
+  unchop(block) %>%
+  mutate(block = unlist(block))
+
+
+biomass <- biomass_raw %>%
+  rename(year = Year, date = Date, site = Site, block = Block, treatment = Treatment, removed_fg = "Removed functional group", round = Round, biomass = Biomass, name = Name, remark = Remark) %>%
+  select(year, date, site, block, treatment, removed_fg, round, biomass, name, remark) %>%
+  mutate(site = recode(site, "OVSen" = "OVS"),
+         round = str_sub(round, start = -1)) %>%
+  # impute missing info on round
+  left_join(impute_round, by = c("year", "site", "block")) %>%
+  mutate(round = if_else(is.na(round), round_new, round))
+
+
+# find duplicates
+rule <- validator(is_unique(year, site, block, treatment, removed_fg, round))
+out <- confront(biomass, rule)
+# showing 7 columns of output for readability
+summary(out)
+violating(biomass, out) %>% View()
+# FIX DUPLICATES!!! Needs checking of the raw data!
+
+
+### missing data
+# 2015 round 1 Arh RTC 4
+# 2016 round 1 /2 ALR 5 values missing
+# 2017 round 2 FAU, VIK, ARH missing data, probably not weighed.
+# 2017 missing biomass and other info from ALR 2, GUD 2, HOG 2, LAV 2, ULV 2
+# 2018, 2020 some missing, but already indicated
+# 2019 all data missing
+# 2021 some sites missing
+
+biomass %>% filter(is.na(biomass), !year %in% c(2019, 2021)) %>% View()
+
+biomass %>%
+  mutate(treatment = factor(treatment, levels = c("B", "F", "G", "FB", "GB", "FG", "FGB"))) %>%
+  filter(year != 2019, removed_fg != "C") %>%
+  ggplot(aes(x = treatment, y = biomass, fill = removed_fg)) +
+  geom_col() +
+  facet_grid(year ~ site) +
+  theme_bw()
+
+
+
+
+### 2022
+raw_biomass22 <- read_excel("raw_data/biomass/FUNDER Forbs_Graminoids_Bryophytes.xlsx",
+           sheet = "Dried weight") |>
+  clean_names()
+
+
+biomass <- raw_biomass22 |>
+  filter(!is.na(site)) |>
+  mutate(site = recode(site,
+                         'GUD' = "Gudmedalen",
+                         'LAV' = "Lavisdalen",
+                         'RAM' = "Rambera",
+                         'ULV' = "Ulvehaugen",
+                         'SKJ' = "Skjelingahaugen",
+                         'ALR' = "Alrust",
+                         'ARH' = "Arhelleren",
+                         'FAU' = "Fauske",
+                         'HOG' = "Hogsete",
+                         'OVS' = "Ovstedalen",
+                         'VIK' = "Vikesland",
+                         'VES' = "Veskre")) |>
+  pivot_longer(cols = c(bryophytes_g, forbs_g, graminoids_g, lichen_g), names_to = "removed_fg", values_to = "biomass") |>
+  # remove entries without biomass
+  filter(biomass > 0) |>
+  mutate(removed_fg = case_match(removed_fg,
+                                "bryophytes_g" ~ "B",
+                                "forbs_g" ~ "F",
+                                "graminoids_g" ~ "G",
+                                "lichen_g" ~ "L")) |>
+  # indicate fg not in treatment (= leftover)
+  mutate(no_treatment = case_when(removed_fg == "L" ~ "leftover",
+                                  treatment == "FB" & removed_fg == "G" ~ "leftover",
+                                   treatment == "GF" & removed_fg == "B" ~ "leftover",
+                                   treatment == "GB" & removed_fg == "F" ~ "leftover",
+                                   treatment == "G" & removed_fg %in% c("F", "B") ~ "leftover",
+                                   treatment == "B" & removed_fg %in% c("F", "G") ~ "leftover",
+                                   treatment == "F" & removed_fg %in% c("G", "B") ~ "leftover",
+                                   TRUE ~ NA_character_)) |>
+  select(siteID = site, blockID = block, treatment, removed_fg, biomass, no_treatment, comments)
+
+write_csv(biomass, "clean_data/FUNDER_clean_biomass_2022.csv")
+
+
+biomass %>%
+  mutate(treatment = factor(treatment, levels = c("C", "B", "F", "G", "FB", "GB", "GF", "FGB")),
+         siteID = factor(siteID, levels = c("Skjelingahaugen", "Gudmedalen", "Lavisdalen", "Ulvehaugen",
+                                            "Veskre", "Rambera", "Hogsete", "Alrust",
+                                            "Ovstedalen", "Arhelleren", "Vikesland", "Fauske"))) %>%
+  filter(!no_treatment %in% c("leftover"),
+         treatment != "C") |>
+  ggplot(aes(x = treatment, y = biomass, fill = removed_fg)) +
+  geom_col() +
+  scale_fill_manual(values = c("darkgreen", "violet", "lightblue3")) +
+  facet_wrap(~ siteID) +
+  theme_bw()