The wildlifeDI package facilitates the calculation of indices of dynamic interaction for wildlife telemetry data. There are also functions for more advanced contact analysis. There are two main streams of analysis that it facilitates: 1) the calculation of a number of ‘dynamic interaction’ or ‘spatial-temporal association’ indices betwewn dyads (i.e., pairs of individuals), and 2) the identification and analysis of contacts within large tracking datasets. There are currently two vignettes, one for each of these streams of analysis:
For more information on the methods used within see the documentation which references the methods cited within. The two papers that can be cited when using the package are:
Long, J.A., Nelson, T.A., Webb, S.L., Gee, K.L. (2014) A critical examination of indices of dynamic interaction for wildlife telemetry studies. Journal of Animal Ecology. 83(5):1216-1233. Link
Long, J.A., Webb, S.L., Harju, S.M., Gee, K.L. (2022) Analyzing contacts and behavior from high frequency tracking data using the wildlifeDI R package. Geographical Analysis. 54(3):648-663. Link
You can install the latest (under development version) of wildlifeDI from github:
To download the latest version from CRAN:
In wildlifeDI version 1.0, I have moved from the adehabitat ltraj objects to the newer move2 class of objects. The rationale here is that the move2 objects extend the sf class of spatial objects and therefore easily integrate common data processing tools such as the tidyverse and are easily mapped and integrated with other spatial analysis workflows. This means all wildlifeDI functions now expect a move2 object as input. There is a new helper function ltraj_move2 that can help you to convert an ltraj to a move2 tracking object.
All the analytical functions now accept tracking data in an identical manner. This is a change to promote consistency across the methods in wildlifeDI. The user can specify a single tracking dataset with multiple individuals (2 or more) and the functions will calculate the chosen metric for all dyad pairs in the dataset with a non-zero temporal overlap (Carefully read the documentation for the function checkTO to understand how this works). Alternatively, analytical functions can accept two tracking datasets which allows one to study interactions from the first tracking dataset to the second. This can be very useful in multi-species study areas (e.g., comparing interactions of predators and prey) or in scenarios where there are two groupings within a dataset that you wish to compare between only (e.g., male and female).
The format of move2 objects provides numerous efficiencies for quickly mapping and summarizing tracking data over the ltraj object type. For that reason a number of the helper functions in wildlifeDI have been removed. These are summarized below:
| Deleted Function | Alternative Functions or Examples |
|---|---|
| sf2ltraj | move2_ltraj |
| ltraj2sf | ltraj_move2 |
| filterTraj | move2::mt_filter_per_interval |
| conSpatial | move2::mt_segments, move2::mt_track_lines |
| conTemporal | see contact analysis vignette |
| conSummary | see contact analysis vignette |
| conPairs | conProcess(return=‘contacts’) |
| conMatrix | see contact analysis vignette |
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