Add residency patches

Work in progress

This vignette shows how to assign residency patches with WATLAS data.

# Packages
library(tools4watlas)
library(ggplot2)
library(viridis)
library(foreach)

# Path to csv with filtered data
data_path <- system.file(
  "extdata", "watlas_data_filtered.csv",
  package = "tools4watlas"
)

# Load data
data <- fread(data_path, yaml = TRUE)

Median smooth data

To further reduce error in the localization data, a basic smoother such as a median filter can be applied. The resulting table has the smoothed location stored in the x and y column and the original location stored in the x_raw and y_raw column.

# Smooth the data
data <- atl_median_smooth(data, moving_window = 5)

Recalculate speed

After smoothing the data, the speeds need to be recalculated. We now also calculate turning angles. Note: the distance between smoothed positions can be 0 and therefore will produce NAs and a warning

# Recalculate speed
data <- atl_get_speed(data, type = c("in", "out"))

Calculate residency patches by tag

# unique tag ID
id <- unique(data$tag)

# loop by tag ID
rp <- foreach(i = id, .combine = "rbind") %do% {
  atl_res_patch_speed(
    data[tag == i],
    max_speed = 3, lim_spat_indep = 50, lim_time_indep = 180,
    min_fixes = 3, min_duration = 180
  )
}

# extract data from all residency patches
drp <- rp[, rbindlist(lapply(
  patchdata, function(x) cbind(x)
)), by = .(tag, patch)]

# merge back with data
data <- merge(
  data, drp[, .(tag, posID, patch)],
  by = c("tag", "posID"), all.x = TRUE
)

Plot residency patches (Example red knot)

# duration in minutes
rp[, duration := duration / 60]

# subset red knot
data_subset <- data[tag == 3038]
rp_subset <- rp[tag == 3038]

# create basemap
bm <- atl_create_bm(data_subset, buffer = 500)

# track with residency patches coloured
bm +
  geom_path(data = data_subset, aes(x, y), alpha = 0.1) +
  geom_point(
    data = data_subset, aes(x, y), color = "grey",
    show.legend = FALSE
  ) +
  geom_point(
    data = data_subset[!is.na(patch)], aes(x, y, color = as.character(patch)),
    size = 1.5, show.legend = FALSE
  )

# plot x against datetime
ggplot() +
  geom_line(
    data = data_subset, aes(datetime, x), color = "grey",
    show.legend = FALSE
  ) +
  geom_point(
    data = data_subset[!is.na(patch)],
    aes(datetime, x, color = as.character(patch)),
    size = 1.5, show.legend = FALSE
  ) +
  theme_bw()

# plot residency patches itself by duration
bm +
  geom_point(
    data = rp_subset,
    aes(x_median, y_median, color = duration, size = duration),
    show.legend = TRUE, alpha = 0.5
  ) +
  scale_color_viridis()

Plot residency patches (with species colours)