Conserved role of juvenile hormone in regulating behavioural maturation and division of labour in a highly eusocial wasp
Description
This dataset contains the behavioural observations, mortality data and R analysis code associated with the study: Ferreira, H. M., Di Pietro, V., Wenseleers, T., & Oi, C. A. (2023). Conserved role of juvenile hormone in regulating behavioural maturation and division of labour in a highly eusocial wasp. Animal Behaviour, 200, 59–69. DOI: 10.1016/j.anbehav.2023.03.013. The study investigated whether juvenile hormone regulates behavioural maturation and age-related division of labour in workers of the common wasp, Vespula vulgaris. Workers from nine colonies were assigned to one of three topical treatments: the juvenile hormone analogue methoprene, the anti-juvenile-hormone compound precocene, or an acetone solvent control. Untreated older workers already present in the colonies were included as an additional comparison group. Behavioural observations were conducted over 10 days. Each colony was observed for 30 minutes per day, comprising 15 minutes in the nest compartment and 15 minutes in the foraging compartment. The recorded behaviours were larval care, cell inspection, nest building and foraging. The behavioural dataset contains the number of times each task was observed for every colony, experimental day and treatment group. The mortality dataset contains the initial and final numbers of marked workers in each treatment group and was used to estimate worker mortality over the experimental period. Colony-level variables, including original, initial and final colony sizes, are also included. The accompanying R script performs data preparation, model selection, statistical analyses, post hoc comparisons and figure generation. Task allocation is analysed using multinomial regression, while worker mortality is analysed using a binomial generalized linear mixed model.
Files
Steps to reproduce
1. Download the two CSV data files and the R script and save them in the same folder. 2. Open Sript_AB.V2.1.R in R or RStudio. 3. Set the working directory to the folder containing the files, either by editing the setwd() line in the script or by opening the folder as an RStudio project. 4. Install any required R packages that are not already installed. The main packages used are lme4, nnet, emmeans, MuMIn, car, effects, tidyr, dplyr, ggplot2, ggthemes, export and writexl. 5. Run the script from beginning to end. The script imports the mortality and behavioural datasets, prepares the data, compares candidate statistical models, fits the selected models, performs post hoc comparisons and produces the tables and figures reported in the paper. The mortality analysis uses a binomial generalized linear mixed model, while the behavioural task data are analysed using multinomial regression.
Institutions
- KU LeuvenFlanders, Leuven