cleaning_code/1_seed_data/clean_seed_predation_data.R

In Between-the-Fjords/seedclim-data: Code for Cleaning SeedClim data

###################################
#### CLEAN SEED PREDATION DATA ####
###################################

# load libraries
library("tidyverse")
library("lubridate")
library("dataDownloader")

## DOWNLOAD DATA
# Use this code to download the data directly from OSF and unzip the file.
# Alternatively you can find the raw data here: https://osf.io/npfa9/

# get_file(node = "npfa9",
#          file = "SeedPredation_2018_SG_18.csv",
#          path = "seed_predation/data",
#          remote_path = "Seed_predation_data/Raw_data")


## CLEAN DATA

predation_raw <- read_delim(file = "cleaning_code/1_seed_data/data/SeedPredation_2018_SG_18.csv", delim = ",")

predation <- predation_raw %>% 
  rename(siteID = site, 
         biogeographic_zone = temp, 
         annual_precipitation_gridded = precipitation, 
         predation_treatment = treat) %>% 
  mutate(siteID = recode(siteID, "ulv" = "Ulvehaugen",
                         "lav" = "Lavisdalen",
                         "gud" = "Gudmedalen",
                         "skj" = "Skjelingahaugen",
                         "alr" = "Alrust",
                         "hog" = "Hogsete",
                         "ram" = "Rambera",
                         "ves" = "Veskre",
                         "fau" = "Fauske",
                         "vik" = "Vikesland",
                         "arn" = "Arhelleren",
                         "ovs" = "Ovstedalen"),
         biogeographic_zone = recode(biogeographic_zone, "Low-alpine" = "alpine",
                                     "Sub-alpine" = "sub.alpine",
                                     "North-boreal" = "boreal"),
         unit = "percentage",
         year = 2018) |> 
  select(year, siteID, predation_treatment, value = predated, unit, biogeographic_zone, annual_precipitation_gridded, weather)
        

write_csv(predation, file = "cleaning_code/1_seed_data/data/VCG_clean_seed_predation_2018.csv")