Track-a-Forager: a program for the automated analysis of RFID tracking data to reconstruct foraging behaviour

摘要

Behavioural studies make increasingly use of the passive radio-frequency identification (RFID) technology to monitor the foraging behaviour and activity patterns of individual animals over extended periods of time. Central place foragers, such as social insects, birds and many rodents have proved particularly well suited for this technology. As yet, however, there is no standardized methodology to filter and postprocess the data resulting from RFID scanners. Here we present a new user-friendly, publically available Java program named "Track-a-Forager" to analyse and rigorously filter RFID animal tracking data. The program is particularly suited and has special features to analyse social insect behaviour, but it is generic enough to analyse data obtained from any species. The implemented filtering algorithm consists of several well-defined steps to cluster multiple temporally clustered RFID scans of the same individual, determine events of leaving and entering the nest and/or feeder and reconstruct foraging trips for each individual. Track-a-Forager analyses RFID data independent of the used scanner system for eight different types of standard experimental setups that are common in foraging behaviour research. These setups differ with respect to whether or not foraging at an artificial feeder is monitored and the specific placement of the RFID scanners at the nest or feeder. As a real-life example, we show how Track-a-Forager enables one to reconstruct 75 % more foraging trips compared to if one were to use the raw data.