Dispersal kernels for predicting animal movement patterns

Miss Laura Merritt1,2, Professor Justin Travis3, Miss Isabel Schödl5, Professor Tom Oliver2, Dr Rob Salguero-Gomez4, Dr Steven White1, Professor James Bullock1

1Centre For Ecology And Hydrology, Wallingford, United Kingdom, 2University of Reading, Reading, United Kingdom, 3University of Aberdeen, Aberdeen, United Kingdom, 4University of Oxford, Oxford, United Kingdom, 5University of Greifswald, Greifswald, Germany

One response of species to climate change is to shift their ranges. Using models to predict these range shifts will help conservation planning. However, current approaches based on simulations using individual based models are generally slow and computationally intensive. Population level models called integrodifference equations have been developed, however they require the fitting of functions called dispersal kernels. The previous focus of dispersal kernel studies has been predominantly plants, which show passive or directed dispersal. Integrodifference equations have, however, been used for predicting mammals’ extinction risks under climate change. This active dispersal shows different patterns, arising from different behavioural responses to the environment among animal species. Using virtual movement data developed through RangeShifter simulations, we tested the performance of different dispersal kernels for animal movement. Many widely used dispersal kernels show consistently poor fit to animal dispersal data. It is therefore important that both animal behaviour and landscape structure is considered in deciding the most appropriate dispersal kernel to use. Additionally, alternative fitting techniques are required to account for the small frequency but high importance of long distance dispersal events that are often poorly predicted.


Laura Merritt is a second year PhD student between the School of Biosciences at the University of Reading and the Centre for Ecology and Hydrology. Her work focuses on the ecology of range shifts. In particular, the application of integrodifference equations for predicting animal dispersal.

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