DOI: 10.5061/dryad.xksn02vn0
title: Foraging behavior of tagged rock ants (Temnothorax rugatulus)

description: Technological advances continue to push the boundaries of scientific
 inquiry in animal behavior. One such development is the emergence of
 automated tracking systems, which enable the collection of high-resolution
 spatio-temporal information for animals. Although tag-based tracking
 systems provide valuable insights into animal movement and collective
 behavior, the attachment of devices can have detrimental effects in some
 cases. Here, we investigated the effects of recently developed miniature
 tracking tags using the rock ant, Temnothorax rugatulus, as a
 model system. To do so, we compared the foraging activities of tagged ants
 and untagged ants (who lost their tags) within initially fully-tagged
 colonies. Additionally, we compared the foraging activities of these
 initially fully-tagged colonies with those of no-tag control colonies (no
 one was tagged). We found that tags did not significantly reduce
 individual activity, with tagged ants visiting the food source as
 frequently as untagged ants within initially fully-tagged colonies.
 However, our analysis revealed a marked difference in recruitment
 behavior—tagged ants were less likely to participate in tandem runs than
 untagged ants. Furthermore, the number of tandem runs was higher for the
 no-tag control colonies than the initially fully-tagged colonies, in which
 69–95% of colony members had tags. Our data suggest, for the first time,
 that tracking tags can negatively impact ant behavior. Although tracking
 devices are powerful tools for understanding complex behavioral patterns,
 it is crucial to carefully consider their potential impact on animal
 behavior to ensure accurate conclusions.
description: Three colonies
 of ants were tagged prior to foraging experiments
 (<strong>Initially
 Fully-Tagged</strong>: 'R2119',
 'R2111', and 'R2100'). However, the final proportion
 of tagged individuals varied since tags were frequently detached during
 grooming and handling. Three colonies were never tagged and served as
 control groups (<strong>Not-tagged</strong>: 'FR2217', 'FR2218', and 'FR2220'). For 5 hours and 30 minutes, we annotated videos (S1 Video Repository), recording the status (column: "tag_status") of each ant ("tagged" or "untagged") and time of occurrence for three foraging events: Feeding at food source ("Feeder visit") Leading a tandem run ("Tandem-running leader") Following a tandem run ("Tandem-running follower")
description: All statistical analyses were
 performed in Python with the SciPy and Statsmodels. A complete list of our Python environment and all
 dependencies is included:
 "env-specs.yml."
description: # Foraging behavior of tagged ants dataset *** Authors: [Ben
 Taylor](mailto:benjaminztaylor@gmail.com), Supraja Rajagopal, and Takao
 Sasaki *** Three colonies of ants were tagged prior to foraging
 experiments (**Initially Fully-Tagged**: 'R2119',
 'R2111', and 'R2100'). However, the final proportion
 of tagged individuals varied since tags were frequently detached during
 grooming and handling. Three colonies were never tagged and served as
 control groups (**Not-tagged**: 'FR2217', 'FR2218',
 and 'FR2220'). For 5 hours and 30 minutes, we annotated videos
 ([S1 Video
 Repository](https://kaltura.uga.edu/playlist/dedicated/1_dsklo3z0/1_4yj44wyy)), recording the status ("tag\_status") of each ant ("tagged" or "untagged") and time of occurrence for three foraging events: 1. Feeding at food source ("Feeder visit") 2. Leading a tandem run ("Tandem-running leader") 3. Following a tandem run ("Tandem-running follower") ## **Description of the data and file structure** ### File: `colony_information.csv` **Description**: This file contains basic details details regarding the count of tagged and untagged ants in each colony. #### Details * `Colony`: Colony identity (*str*) * `Whole colony_Tagged`: the number of ants with tags in the colony (*int*) * `Whole colony_Untagged`: the number of ants within a colony that do not have tags (*int*). **Note**: For "Initially fully-tagged" colonies "untagged" describes ants that were formerly tagged. *** ### File: `foraging_behavior_data.csv` **Description**: This file contains annotations of foraging events for all colonies. Each row represents a unique feeder visit, detailing the following attributes: #### Details * `colony`: Colony identity (*str*) * `colony_treatment`: Treatment type applied to the colony ("Not-tagged" *or* "Initially fully-tagged") * `behavior`: Specifies the behavior observed during the event. It designates whether the ant is a "Feeder visit", "Tandem-running leader" or a "Tandem-running follower." (*str*) * `time`: Video timestamp indicating the time of the event.(*datetime64*) * `tag_status`: Tag status of the ant involved in the foraging event. (*str*) **Note**: This dataset only includes records of successful tandem runs. For information on both successful and unsuccessful tandem runs, refer to the `all_tandem_run_behavior.csv` data. *** ### File: `all_tandem_run_behavior.csv` **Description**: This dataset contains records of all tandem running behaviors, encompassing both successful and unsuccessful runs. An unsuccessful tandem run occurs when recruitment is initiated but the pair fails/breaks to reach the target food source. #### Details * `colony`: Colony identity (*str*) * `colony_treatment`: Treatment type applied to the colony ("Not-tagged" *or* "Initially fully-tagged") (*str*) * `successful`: Indicates if the tandem run was successful (1) or unsuccessful (0) (*int*) * `tr_start`: Timestamp of tandem behavior start (*datetime64*) * `tr_end`: Timestamp of tandem behavior end (*datetime64*) * `tr_leader_tag_status`: Tag status of the tandem run leader (*str*) * `tr_follower_tag_status`: Tag status of the tandem run follower (*str*) ## **Sharing/Access information** **S1 Video Repository**: Videos of foraging experiments for each colony can be accessed via Kaltura video repository: [Access Here](https://kaltura.uga.edu/playlist/dedicated/1_dsklo3z0/1_4yj44wyy). ## **Code/Software** All statistical analyses were conducted in Python. `Tag_attachment_reduces_initiation_stats.ipynb`: Python notebook contain statistical analysis. * Fisher's Exact and T-tests (SciPy) * OLS Regression and S1 Table 1 (Statsmodels) * Fig 3 creation (Plotly) A complete list of our Python environment and dependencies is included in `env-specs.yml.` Replicate our environment with Conda (MacOS): `conda env create -f env-specs.yml`