Quantifying animal social behaviour with ecological field methods

Field studies of social behaviour are challenging due to the need to record or infer interactions between multiple individuals, often under suboptimal environmental conditions or with potential disturbance by observers. Due to the limited field techniques available, we present a novel method to quantify social behaviours in the field by comparing the counts of individuals caught in traps across multiple locations sampled simultaneously. The distribution of individuals between traps gives the extent of aggregation, and phenotypic data allow for inference of non-random assortment. As a case study, we applied this method to populations of three-spined sticklebacks (Gasterosteus aculeatus) in freshwater ponds, using minnow traps. As expected, we observed a strong trend for aggregation. We were able to describe the ecological drivers of aggregation, comparing environmental and phenotypic conditions across sites. Aggregation was not related to environmental parameters, but was negatively asso..., , , # Quantifying animal social behaviour with ecological field methods

[https://doi.org/10.5061/dryad.g79cnp5zw](https://doi.org/10.5061/dryad.g79cnp5zw)

## Description of the data and file structure

### Overview

This project introduces a novel method to quantify animal social behaviour by comparing counts of individuals caught in traps across multiple locations sampled simultaneously. The method was applied to three-spined sticklebacks (*Gasterosteus aculeatus*) in freshwater ponds using minnow traps.

### Dataset

The dataset includes the number of fish caught per trap location including the number of males in breeding condition (red males), aggregation scores calculated using the index of dispersion, measurements of fish body length, and various environmental parameters. Data was collected from 4 pond sites over 13 weeks from May to November 2021. The associated script performs statistical analyses to explore the relationships between these variables.

### Key Analyses

1. **Aggrega...