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Invasion rate of deer ked depends on spatiotemporal variation in host density

Published online by Cambridge University Press:  13 February 2014

C. M. Meier*
Affiliation:
Swiss Ornithological Institute, Seerose 1, CH-6204 Sempach, Switzerland
D. Bonte
Affiliation:
Terrestrial Ecology Unit, Department of Biology, Ghent University, K.L. Ledeganckstraat 35, 9000 Gent, Belgium
A. Kaitala
Affiliation:
Animal Ecology, Department of Biology, University of Oulu, P.O. Box 3000, 90014, Finland
O. Ovaskainen
Affiliation:
Metapopulation Research Group, Department of Biosciences, University of Helsinki, PO Box 65, 00014, Finland
*
*Author for correspondence Phone: +41(0)414629710 Fax: +41(0)414629710 E-mail: [email protected]

Abstract

Invasive parasites are of great global concern. Understanding the factors influencing the spread of invading pest species is a first step in developing effective countermeasures. Growing empirical evidence suggests that spread rates are essentially influenced by spatiotemporal dynamics of host–parasite interactions, yet approaches modelling spread rate have typically assumed static environmental conditions. We analysed invasion history of the deer ked (Lipoptena cervi) in Finland with a diffusion–reaction model, which assumed either the movement rate, the population growth rate, or both rates may depend on spatial and temporal distribution of moose (Alces alces), the main host of deer ked. We fitted the model to the data in a Bayesian framework, and used the Bayesian information criterion to show that accounting for the variation in local moose density improved the model's ability to describe the pattern of the invasion. The highest ranked model predicted higher movement rate and growth rate of deer ked with increasing moose density. Our results suggest that the historic increase in host density has facilitated the spread of the deer ked. Our approach illustrates how information about the ecology of an invasive species can be extracted from the spatial pattern of spread even with rather limited data.

Type
Research Paper
Copyright
Copyright © Cambridge University Press 2014 

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