MultiMoveNetCreate

Creates dynamic, directed, multiplex movement networks from capture-mark-recapture datasets using information on the capture locations and times of individuals.

MultiMoveNetCreateHi(
  data,
  intwindow,
  mindate,
  maxdate,
  netwindow,
  overlap,
  nextonly = FALSE,
  index = FALSE
)

Arguments

data	A 6 column dataframe with columns for the ID of the captured individual, the location of its capture (a name or number), the x coordinate of its capture location, the y coordinate of the capture location, the date and time of capture and information to define multiplex network layers. The "Layers" column can consist of any unique identifiers (e.g. if layers representing movements by males and females are used then they could be represented by "M" and "F" or 1 and 2). If the user wants a layer per individual then the "Layers" column can simply be a copy of the individual ID column.
intwindow	The maximum period of time (in minutes) between two co-captures (i.e. if intwindow = 60 then two individuals captured 60 minutes apart could be considered co-captured but two individuals captured 61 days apart couldn't)
mindate	The start date (format = "YYYY-MM-DD hh:mm:ss") of the study (i.e. when you want to build networks from)
maxdate	The end date (format = "YYYY-MM-DD hh:mm:ss") of the study (i.e. when you want to build networks until). Please provide as the day after the last day of the study. Please provide as the day after the last day of the study.
netwindow	The period of time over which each network is built in days (i.e. netwindow=30 would correspond to monthly networks)
overlap	The amount of overlap between netwindows in days (i.e. overlap = 5 would result in a second network window starting 5 days before the end of the first). When overlap=0, there is no overlap between successive network windows
nextonly	(TRUE/FALSE). Determines whether a network edge is only created to the next capture of an individual or all captures within the intwindow. Defaults to FALSE
index	Defaults to FALSE. If FALSE edges are weighted by the number of movements. If TRUE then edges are weighted by the number of movements divided by the number of captures in a group

Value

A list of length 3 containing:

1. A list of edgelists (the same length as the number of network windows) containing the multiplex network for each of the netwindows as an array

2. a list of adjacency matrices (the same length as the number of ntwork windows) containing the multiplex network for each of the netwindows as an array

3. a matrix indicating which individuals occurred in each netwindow

Details

Multiplex networks connect locations that individuals have moved between within a particular interaction window with different layers being defined by the user. The time period for each network, together with the temporal and spatial restrictions on the capture window used to infer a movement can be defined by the user