Construct residence patches from position data — atl_res_patch

A cleaned movement track of one individual at a time can be classified into residence patches using the function atl_res_patch_speed. The function expects a specific organisation of the data: there should be at least the following columns, X, Y, and time, corresponding to the coordinates, and the time as POSIXct. atl_res_patch_speed requires only three parameters: (1) the maximum speed threshold between localizations (called max_speed), (2) the distance threshold between clusters of positions (called lim_spat_indep), and (3) the time interval between clusters (called lim_time_indep).Clusters formed of fewer than a minimum number of positions can be excluded.The exclusion of clusters with few positions can help in removing bias due to short stops, but if such short stops are also of interest, they can be included by reducing the min_fixes argument. Position covariates such as speed may also be summarised patch-wise by passing covariate names and summary functions as character vectors to the summary_variables and summary_functions arguments, respectively.

Usage

atl_res_patch_speed(
  data,
  max_speed = 3,
  lim_spat_indep = 75,
  lim_time_indep = 180,
  min_fixes = 3,
  min_duration = 120,
  summary_variables = c(),
  summary_functions = c()
)

Arguments

data: A dataframe of any class that is or extends data.frame of one individual only. The dataframe must contain at least two spatial coordinates, X and Y, and a temporal coordinate, time.
max_speed: A numeric value specifying the maximum speed (m/s) between two coordinates that would be considered non-transitory
lim_spat_indep: A numeric value of distance in metres of the spatial distance between two patches for them to the considered independent.
lim_time_indep: A numeric value of time in minutes of the time difference between two patches for them to be considered independent.
min_fixes: The minimum number of fixes for a group of spatially-proximate number of ponts to be considered a preliminary residence patch.
min_duration: The minimum duration (in seconds) for classifying residence patches.
summary_variables: Optional variables for which patch-wise summary values are required. To be passed as a character vector.
summary_functions: The functions with which to summarise the summary variables; must return only a single value, such as median, mean etc. To be passed as a character vector.

Value

A data.frame extension object. This dataframe has the added column patch, patchdata, and polygons, indicating the patch identity, the localization data used to construct the patch, and the polygons of residence patches based on the lim_spat_indep. In addition, there are columns with patch summaries: nfixes, dist_in_patch, dist_bw_patch and statistics based on the summary_variables and summary_functions provided. summary variables.

Author

Pratik R. Gupte, Christine E. Beardsworth & Allert I. Bijleveld