Integrating the influence of weather into mechanistic models of butterfly movementEvans, L. C. ORCID: https://orcid.org/0000-0001-8649-0589, Sibly, R. M. ORCID: https://orcid.org/0000-0001-6828-3543, Thorbek, P., Sims, I., Oliver, T. H. ORCID: https://orcid.org/0000-0002-4169-7313 and Walters, R. J. (2019) Integrating the influence of weather into mechanistic models of butterfly movement. Movement Ecology, 7 (24). pp. 1-10. ISSN 2051-3933
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: 10.1186/s40462-019-0171-7 Abstract/SummaryUnderstanding the factors influencing movement is essential to forecasting species persistence in a changing environment. Movement is often studied using mechanistic models, extrapolating short-term observations of individuals to longer-term predictions, but the role of weather variables such as air temperature and solar radiation, key determinants of ectotherm activity, are generally neglected. We aim to show how the effects of weather can be incorporated into individual-based models of butterfly movement thus allowing analysis of their effects. Methods: We constructed a mechanistic movement model and calibrated it with high precision movement data on a widely studied species of butterfly, the meadow brown (Maniola jurtina), collected over a 21-week period at four sites in southern England. Day time temperatures during the study ranged from 14.5 to 31.5⁰C and solar radiation from heavy cloud to bright sunshine. The effects of weather are integrated into the individual-based model through weather-dependent scaling of parametric distributions representing key behaviours: the durations of flight and periods of inactivity. Results: Flight speed was unaffected by weather, time between successive flights increased as solar radiation decreased, and flight duration showed a unimodal response to air temperature that peaked between approximately 23⁰C and 26⁰C. After validation, the model demonstrated that weather alone can produce a more than two-fold difference in predicted weekly displacement. Conclusions: Individual Based models provide a useful framework for integrating the effect of weather into movement models. By including weather effects we are able to explain a two-fold difference in movement rate of M. jurtina consistent with inter-annual variation in dispersal measured in population studies. Climate change for the studied populations is expected to decrease activity and dispersal rates since these butterflies already operate close to their thermal optimum.
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