DOI: 10.5061/dryad.wh70rxx08
title: Data from: Running in the rain: Impact of water droplets on tandem running recruitment in a tropical ant

description: Rain hampers essential activities like foraging, guarding and frequently
 cause damage to the dwelling especially for organisms like ants that live
 in subterranean nests. Diacamma indicum, a tropical ant, is known to
 relocate to higher ground by means of tandem running and to build nest
 mounds when they face rain during monsoon. But what happens if they have
 to relocate when water droplets are falling on them? We addressed this
 question by subjecting treatment tandem pairs to water droplets on their
 body (a proxy to low level rainfall) along their journey to the new nest
 and compared it with controls. Treatment tandem runs showed significantly
 higher number of interruptions during the trip and failures to complete
 the tandem run to new nest. The location at which the treatment was given
 (near the old nest, midway or near the new nest) did not influence the
 outcomes. Despite these low levels of water falling on them, tandem
 leaders continued to recruit to the new nest and completed their
 relocation without any significant change in the dynamics. This experiment
 shows the credibility of tandem run as a robust method of transportation
 even under adverse conditions like rain and highlights the need to explore
 how subterranean organisms like ants have adapted to monsoon and manage
 their lives through the months of heavy rainfall.
description: * File name: README_Dataset_Running in rain_Diacamma indicum * Manuscript
 title: Running in the rain: Impact of water droplets on tandem running
 recruitment in a tropical ant * Dataset DOI:
 [[https://doi.org/10.5061/dryad.wh70rxx08](https://doi.org/10.5061/dryad.wh70rxx08) ] ([https://doi.org/10.5061/dryad.wh70rxx08](https://doi.org/10.5061/dryad.wh70rxx08)) * Authors: xxxxxxxx * Other contributors: xxxxxxxxxx * Date created: 2025-03-04 * Date modified: 2025-04-10 Dataset Version and Release History * Current Version: * Number: 1.0.2 * Date: 2025-04-10 * Dataset Title: Data for the article "RUNNING IN THE RAIN RAW DATA." * Date of Issue: 2025-03-04 Data and File Overview File/Folder Details * Description: A folder containing 15 files: 14 csv files named "colony size", "colonywise_failed tandem run percentage", "colonywise_failed tandem run percentage_location specific", "colonywise_percentage of inetrruption per tandem run", "colonywise_percentage of switchover per tandem run", "control_individual tandem run details","discovery time", "latency", "transport time", "treatment_individual tandem run details", "transport", and "individual tandem pairs_analysis", and one R script file containing all th packages, codes and models usd for the manuscript * Format(s): .csv, R * No of files: 13 * Size(s): 30.4 kb * Names of the files: * .csv: colony size * .csv: colonywise_failed tandem run percentage * .csv: colonywise_failed tandem run percentage_location specific * .csv: colonywise_percentage of inetrruption per tandem run * .csv: colonywise_percentage of switchover per tandem run * .csv: control_individual tandem run details * .csv: discovery time * .csv: latency * .csv: transport time * .csv: treatment_individual tandem run details * .csv: transport * .csv: individual tandem pairs_analysis * Rationale of experimennts: We have done the experiment to check the effect of low levels of rainfall on the tandem pairs of a relocating Diacamma indicum colony. The primary mode of relocation in Tnadem running so we have considered each and every tandem pair as an unit while analysing individual level behaviours such as success and failure. 1 ml of water was dropped on each uncique tandem pairs at one of the three different locations (near old nest, at the middle and near the new nest) along the relocation path to check how the relocation process is hampered due to the low level of water stress on the relocating colony. Colony level behaviours such as relocation dynamics (comparison ofthree different phases of relocation: time taken to discover the new nest - discovery time, time taken to start relocation after discovery of new nest - latency, and time taken between first and last tandem run or time taken to transport all the nestmates to the new nest - transport time), colony wise interruptions per tandem pair, and switchover per tandem pair were also analysed. The fate of tandem pairs (success or failure) was impacted by the number of interruptions and the type of teament (water droplets). Details for .csv files * Name: colony size * Size: 1 kb * Organisation: 8 rows X 2 columns: comparison between colony sizes * Variables: control, treatment * Name: discovery time * Size: 1 kb * Organisation: 8 rows X 2 columns: comparison discovery time i.e. time to find the new nest while relocating, across control and treatment colonies * Variable: discovery time Dicovery time Unit - Minutes , No of colonies: Control - 8, Treatment - 8 Control | Treatment | * Name: latency * Size: 1 kb * Organisation: 8 rows X 2 columns: comparison latency i.e. time taken to start relocatig to the new nest after the discovery of the new nest. As this is the time when colonies decide whether or not to relocate to the new nest, this is also called the decision time. Here were compare latency across control and treatment colonies * Variable: cdiscovery time Dicovery time Unit - Minutes , No of colonies: Control - 8, Treatment - 8 Control | Treatment | * Name: transport time * Size: 1 kb * Organisation: 8 rows X 2 columns: comparison discovery time i.e. time from the start to the end of transport, i.e. from first to last tandem run, across control and treatment colonies * Variable: discovery time Dicovery time Unit - Minutes , No of colonies: Control - 8, Treatment - 8 Control | Treatment | * Name: colonywise_failed tandem run percentage * Size: 1 kb * Organisation: 8 rows X 3 columns: colony wise comparison of % of failed tandem runs * Variables: control, treatment Colony ID | Control | Treatment | Unit - NA, Percentage of failed tandem runs were calculated by dividing the the colonywise number of failed tandem runs *100 / Colonywise total number of tandem runs * Name: colonywise_failed tandem run percentage_location specific * Size: 1 kb * Organisation: 8 rows X 4 columns, (3 variables): comparison of failed tandem run percentage (colonywise) with respect to location of water treatment * Variables: ON (near old nest), M (middle of the arena), NN (near new nest) Colony ID | ON | M | NN | Unit - NA, Percentage of failed tandem runs at each position were calculated by dividing the the total number of failed tandem runs at each position *100 / Colonywise total number of tandem runs * Name: colonywise_percentage of inetrruption per tandem run * Size: 1 kb * Organisation:8 rows X 3 columns: comparison of interruption per tandem run (colonywise) across control and treatment colonies * Variables: control, treatment Colony ID | Control | Treatment | Unit: NA, Colony wise interruptions per tandem run was calcualted by: Total number of interruptions for a particular colony relocation / Total number of tandem runs in that particular colony reloation * Name: colonywise_percentage of switchover per tandem run * Size: 1 kb * Organisation:8 rows X 3 columns: comparison of switchovers per tandem run (colonywise) across control and treatment colonies * Variables: control, treatment Colony ID | Control | Treatment | Unit: NA, Colony wise switchovers per tandem run was calcualted by: Total number of switchovers happened during a particular colony relocation / Total number of tandem runs in that particular colony reloation * Name: control_individual tandem run details * Size: 4 kb * Organisation: 114 rows X 7 columns: details of individual tandem runs from control colonies (n = 113): fate, no of interruption, destination * Variables: Tandem pair I'd, treatment given, Treatment type, fate, Destinatons, No of interruptions, Colony I'd * Details of variables: Tandem pair I'd - the individual identities of the lead and follower combination. For e.g. if Blue - Gold is the leader and Orange oragne white is the follower, the variable in the daatasheet will be represented as B-X / OOW Treatment given - Location where the focal tandem pair was subjected to treatment Treatment type - Air Fate - success or failure Desinations - ON or old nest, NN or new nest. In this column there were a few blank cells which are filled with null. Those are the cases where the tandem run failed and the follower was temporarily lost somewhere in the arena. No of interruptions - If the members of a tandem pair breaks apart midway for more than 2 seconds, then it is considered as interruption. Here we present the actual number of interruptions occured during the that particular tandem run. Tandem pair I'd | Treatment given (location) | Treatment type | Fate | Destination | No of interruptions | Colony I'd | * Name: treatment_individual tandem run details * Size: 5 kb * Organisation: 127 rows X 7 columns: details of individual tandem runs from control colonies (n = 126): fate, no of interruptions, destination * Variables: Tandem pair ID, treatment given, Treatment type, fate, Destinations, No of interruptions, Colony ID *Details of variables: Tandem pair I'd - the individual identities of the lead and follower combination. E.g., if Blue-Gold is the leader and Orange or white is the follower, the variable in the datasheet will be represented as B-X / OOW Treatment given - Location where the focal tandem pair was subjected to treatment Treatment type - Water Fate - success or failure Destinations - ON or old nest, NN or new nest. In this column there were a few blank cells which are filled with null. Those are the cases where the tandem run failed and the follower was temporarily lost somewhere in the arena. No of interruptions - If the members of a tandem pair break apart midway for more than 2 seconds, then it is considered an interruption. Here we present the actual number of interruptions that occurred during that particular tandem run Tandem pair I'd | Treatment given (location) | Treatment type | Fate | Destination | No of interruptions | Colony I'd | No of interruptions - actual number of interruptions that occurred during that particular tandem run * Name: individual tandem pairs analysis * Description: A CSV file containing individual-level data of each tandem pair from both the control and treatment sets of colonies * Format(s): .csv * No of files: 1 * Size(s): 8 kb * Sheet 1: Individual tandem pairs analysis. 240 rows X 7 columns * Variables: Tandem pair I'd (tr_id), treatment given (treatment_loc), Treatment type (treatment_type), fate, No of interruptions (interruption), Colony I'd (colonyid), Interruption status (interruption_status). Interruption status - yes/no tr_id | treatment_loc | treatment_type | fate | interruption | colonyid | interruption_status | * A subset of the same file has been used for the R codes while performing models dealing with the fate of tandem pairs and all factors, i.e., type of treatment, location of treatment, and number of interruptions. The names of the files are rain_kb and rain_kb2. We have uploaded those as well as rain_kb.csv and rain_kb2.csv separately. We are not providing the details of those to avoid redundancy. Please refer to those .csv files wherever needed to perform the analysis. The organisation of the data in those files is as such rain_kb.csv treatment_loc treatment_type fate interruption colony_id rain_kb2.csv treatment_loc treatment_type fate interruption colony_id interruption_status * Name: Individual tandem pairs analysis * Description: A .csv file containing colony-wise transport time data concerning treatment type, i.e., if the colony was subjected to water treatment or not (air) * Format(s): .csv * No of files: 1 * Size(s): 1 kb * Sheet 1: transport aka kb_transport: - 17 rows X 2 coloumns * Variables: transport time (transport), treatment type (treatment_type) transport | treatment_type | Details for: Analyses * Description: An R File containing the details of packages, codes and models used to analyse the data (See Manuscript and supplementary files for more details) * Format(s): .R * No of files: 1 * Size(s): 12 kb * Models run: r1_model1 = glmmTMB(fate ~ 1+ treatment_type*treatment_loc + interruption + (1|colony_id), data = r1, family = binomial(link = "logit")) r1_model2 = glmmTMB(fate ~ 1+ interruption*treatment_loc + (1|colony_id), data = r1, family = binomial(link = "logit")) r1_model4 = glmmTMB(fate ~ 1+ interruption*treatment_loc + (1|colony_id), data = r1, family = binomial(link = "logit")) r1_model6 = glmmTMB(fate ~ treatment_type + (1|colony_id), data = r1, family = binomial(link = "logit")) r1_model7 = glmmTMB(fate ~ treatment_type + treatment_loc + interruption + (1|colony_id), data = r1, family = binomial(link = "logit")) r1_model7 = glmmTMB(fate ~  treatment_loc +  (1|colony_id), data = r1, family = binomial(link = "logit")) r1_model7i = glmmTMB(fate ~  interruption +  (1|colony_id), data = r1, family = binomial(link = "logit")) m10= glmmTMB(interruption ~ treatment_type + treatment_loc + (1|colony_id), ziformula=~1, family = poisson(), data=r1)