A novel approach to quantifying mammal locomotor repertoires using scoring and cluster analysis

Describing behaviour using qualitative categories is a staple of studies on tetrapod functional morphology, ecology, and evolution. However, such categorisation has several issues, primarily subjectivity and the loss of important behavioural repertoire information. Here, we propose a novel method for quantifying behaviour, using mammal locomotion as a case study to demonstrate its utility and efficacy. Species are scored from 0-4 on their proficiency in five locomotor modes (swimming, climbing, digging, running and aerial movement), then Ward’s hierarchical clustering is used on the resulting data matrix to group species into biologically informative categories (the number of which can be optimised using clustering validation methods), thus producing a mathematically defined categorical variable. The method is demonstrated on a dataset of 250 mammal species, representing every extant mammal family. We show that this approach successfully quantifies mammal locomotion, producing both a da..., 1. Sample
A total of 250 extant mammal species were included in this study. The species were selected to represent one species per subfamily, or family where such divisions have not been defined. Decisions regarding which particular species within their subfamilies would be scored were largely based on the availability of locomotor information within the literature to avoid introducing missing data into the scoring matrix.
In the case of Chiroptera, not all subspecies are included, regardless of the presence of many subfamilies within the order, because the Chiroptera broadly represent a single behavioural repertoire which would be overrepresented if all subfamilies were included. Similarly, not all rodent subfamilies were included as it would risk overrepresenting this very large order. Note, however, that the reduced coverage still represents the whole locomotor variation within Rodentia.
2. Scoring
Each species was given a score from 0-4 in each of five locomotor modes: swimming, cli..., , # Data from: A novel approach to quantifying mammal locomotor repertoires using scoring and cluster analysis

<br />

Data for:

Sophia C. Anderson, Philip G. Cox, Laura C. Fitton, Karl T. Bates, Eloy Gálvez-López (2025) A novel approach to quantifying mammal locomotor repertoires using scoring and cluster analysis. Royal Society Proceedings B. DOI 10.1098/rspb.2025.2515

This README.md file was generated on 10/12/2025

<br />

## GENERAL INFORMATION

1\. Title of dataset: ‘Data for: A novel approach to quantifying mammal locomotor repertoires using scoring and cluster analysis’

2\. Date of data collection: 2023-2025

3\. Keywords: cluster analysis, Ward's hierarchical clustering, mammal locomotion, behaviour quantification

4\. Language: English (UK)

## DATA AND FILE OVERVIEW

1\. Description of dataset

This is a dataset containing raw data in which 250 extant mammals have been scored from 0-4 on their ability to engage in five types of locomotion (swimming, climbing, digging, runni..., Explicit consent from all human participants was obtained to publish de-identified data. Information regarding career stage and relevant educational background are included in these data, but all participants are referred to across all materials by a number for anonymity. , All participants gave explicit consent for the associated data to be published publicly. This includes information regarding career stage and general academic expertise. Throughout, participants are referred to by a number for anonymity.