DOI: 10.5061/dryad.31zcrjdsm
title: Group phenotypic composition drives task performances in ants

description: Differences in individual behaviour within a group can give rise to
 functional dissimilarities between groups, particularly in social animals.
 However, how individual behavioural phenotypes translate into the group
 phenotype remains unclear. Here we investigate whether individual
 behavioural type affects group performance in an eusocial species, the ant
 Aphaenogaster senilis. We measured individual behavioural traits and
 created groups of workers with similar behavioural type, either
 high-exploratory or low-exploratory. We tested these groups in four
 different, ecologically relevant tasks: reaction to an intruder, prey
 retrieval from a maze, nest relocation and tool use. We show that,
 compared to groups of low-exploratory workers, groups of high-exploratory
 workers were more aggressive towards intruders, more efficient in
 collecting prey, faster in nest relocation and more likely to perform tool
 use. Our results demonstrate a strong link between individual and
 collective behaviour in ants. This supports the ‘behavioural type
 hypothesis’ for group dynamics, which suggests that an individual’s
 behaviour in a social environment reflects its own behavioural type. The
 average behavioural phenotype of a group can therefore be predicted from
 the behavioural types of individual group members.
description: # Group phenotypic composition drives task performances in ants
 The data were collected at
 the Laboratory of Experimental and Comparative Ethology, University
 Sorbonne Paris Nord, using 8 different colonies of the ant species
 *Aphaenogaster senilis* for the repeatability tests and 6 different
 colonies for the group tests. The methodology used for data collection is
 described in the Manuscript entitled “***Group phenotypic composition
 drives task performances in ants***” submitted to Biology Letters.   **1.
 *Repeatability (Boldness)* data sheet:** Contains the variable
 (**Ex_lat**) collected during the Boldness test to assess the
 repeatability of behavioural traits. This variable was collected with a
 chronometer and written down in a spreadsheet (.xls).   Variables
 included: ·      **Ex_lat:** latency to exit the tube (sec) ·      **ID:**
 worker IDs ·      **Nr_of_session:** which one of the two sessions of the
 *Boldness* *test*   **2. *Repeatability (Openfield)* data sheet:**
 Contains the variables (**Int** and **ExtM**) collected during the
 Open-field tests to assess the repeatability of behavioural traits.  
 Variables included: ·      **Int:** percentage of time the individual
 spent inside the central area ·      **ExtM:** percentage of time the
 individual spent moving in the periphery ·      **ID:** worker IDs ·     
 **Nr_of_session:** which one of the two sessions of the *Open-field test*
   Int and & ExtM variables were extracted from the video-recordings
 using a custom-made ant tracking software for open-field test. When the
 ant moves it creates a difference between two consecutives frames of the
 video enabling us to track her movement (more details in supplementary
 material). The software then calculates the percentage of frames the
 individual spent moving in the periphery (directly equivalent to ExtM) and
 the percentage of frames the individual spent in the central area
 (directly equivalent to Int). A csv file with the frame percentages was
 given as the output of the software. The following variables were
 collected during the ***Group behaviour assays*****.** The variables used
 in the analysis of these assays are highlighted in the Manuscript with the
 symbols “**i-xii**”, also shown in the following description of the
 variables in parentheses.   **3. *Tool use* data sheet:** Contains the
 variables (**FirstTool, FirstHoney, UsingTools**) collected during the
 ***Tool Use assay*** to assess the differences in the behaviour between
 the two types of sub-colonies. The experiments were filmed (.mp4), the
 variables were collected by analysing the video recordings by hand and
 written down in a spreadsheet (.xls).   Variables included: ·     
 **FirstTool (i):** latency of  first interaction with a tool (sec) ·     
 **FirstHoney (ii):** latency of first interaction with the honey (sec)
 ·      **UsingTools:** sub-colony performing tool use (1) or not (0)
 ·      **Subcolony:** high- (High) and low–exploratory (Low) sub-colonies
 ·      **Col:** colony IDs   **4. *Reaction to Intruder* data sheet:**
 Contains the variables (**Anten, MandOpen, Bite, Tot**) collected during
 the ***Reaction to Intruder assay*** to assess the differences in the
 behaviour between the two types of sub-colonies. The experiments were
 filmed (.mp4), the variables were collected by analysing the video
 recordings by hand and written down in a spreadsheet (.xls).   Variables
 included: ·      **Anten (iii):** proportion of time spent with intruder
 antennation (sec) ·      **MandOpen (iv):** proportion of time spent with
 mandible opening towards the intruder (sec) ·      **Bite (v):**
 Proportion of time spent with biting the intruder (sec) ·      **Tot:**
 total time of interaction with the intruder (sec) ·      **Subcolony:**
 high- (High) and low–exploratory (Low) sub-colonies ·      **Col:** colony
 IDs   **5. *Prey retrieval from a maze* data sheet:** Contains the
 variables (**FirstEnter, FirstCont, FirsttoNest, NoDroso**) collected
 during the ***Prey retrieval from a maze assay*** to assess the
 differences in the behaviour between the two types of sub-colonies. The
 experiments were filmed (.mp4), the variables were collected by analysing
 the video recordings by hand and written down in a spreadsheet (.xls).  
 Variables included: ·      **FirstEnter (vi):** latency of first entrance
 into maze (sec) ·      **FirstCont (vii):** latency of first contact with
 a Drosophila (sec) ·      **FirsttoNest (viii):** latency to transport the
 first Drosophila to nest (sec) ·      **NoDroso (ix):** number of
 Drosophila corpses transported into nest ·      **Subcolony:** high-
 (High) and low–exploratory (Low) sub-colonies ·      **Col:** colony IDs  
 **6. *Nest relocation* data sheet:** Contains the variables (**DiscNest,
 FirstLarvaToNest, NoWork**) collected during the ***Nest relocation
 assay*** to assess the differences in the behaviour between the two types
 of sub-colonies. The experiments were filmed (.mp4), the variables were
 collected by analysing the video recordings by hand and written down in a
 spreadsheet (.xls).   Variables included: ·      **DiscNest (x):** latency
 to discover new nest site (sec) ·      **FirstLarvaToNest (xi):** latency
 to transport first brood to nest (sec) ·      **NoWork (xii):** number of
 workers involved in nest relocation (carrying brood) ·      **Subcolony:**
 high- (High) and low–exploratory (Low) sub-colonies ·      **Col:** colony
 IDs   The variables were used in the statistical analyses as described in
 the ***Supplemental information*** accompanying the Manuscript entitled
 “***Group phenotypic composition drives task performances in ants***”. All
 statistical analyses were performed in ***R Statistical Environment,
 version 4.2.2***. ### Code/Software **Tracking and data processing** The
 tracking of the individual ants was performed by a program written in
 Python using the OpenCV computer vision package. The source code is
 available on the following GitHub page: 
 . The tracking
 is based on the movement of the ant, by differentiating between two
 consecutive frames. The general principle of the algorithm is based on the
 subtraction of these frames together and then filtered by a threshold.
 Thus, the position of the ant can be accurately determined, although it is
 sensitive to the change of background (a constant background is strongly
 recommended). The ant is considered to be standing if its position between
 two frames remains unchanged.