Accessibility navigation

Behaviour underpins the predictive power of a trait-based model of butterfly movement

Evans, L. C. ORCID:, Sibly, R. M. ORCID:, Thorbek, P., Sims, I., Oliver, T. H. and Walters, R. J. (2020) Behaviour underpins the predictive power of a trait-based model of butterfly movement. Ecology and Evolution, 10 (7). pp. 3200-3208. ISSN 2045-7758

[img] Text (Open Access) - Published Version
· Available under License Creative Commons Attribution.
· Please see our End User Agreement before downloading.


It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1002/ece3.5957


1) Dispersal ability is key to species persistence in times of environmental change. Assessing a species’ vulnerability and response to anthropogenic changes is often performed using one of two methods: correlative approaches that infer dispersal potential based on traits, such as wingspan or an index of mobility derived from expert opinion, or a mechanistic modelling approach that extrapolates displacement rates from empirical data on short-term movements. 2) Here we compare and evaluate the success of the correlative and mechanistic approaches using a mechanistic random-walk model of butterfly movement that incorporates relationships between wingspan and sex-specific movement behaviours. 3) The model was parameterised with new data collected on four species of butterfly in the South of England and we observe how wingspan relates to flight speeds, turning angles, flight durations, and displacement rates. 4) We show that flight speeds and turning angles correlate with wingspan but that to achieve good prediction of displacement even over 10 minutes the model must also include details of sex- and species-specific movement behaviours. 5) We discuss what factors are likely to differentially motivate the sexes and how these could be included in mechanistic models of dispersal to improve their use in ecological forecasting.

Item Type:Article
Divisions:Life Sciences > School of Biological Sciences > Ecology and Evolutionary Biology
ID Code:89408


Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation