A predictive model of avian natal dispersal distance provides prior information for investigating response to landscape change Garrard, Georgia E., Mccarthy, Michael A., Vesk, Peter A., Radford, James Q. and Bennett, Andrew F. 2012, A predictive model of avian natal dispersal distance provides prior information for investigating response to landscape change, Journal of animal ecology, vol. 81, no. 1, pp. 14-23. Attached Files Name Description MIMEType Size Downloads Title A predictive model of avian natal dispersal distance provides prior information for investigating response to landscape change Author(s) Garrard, Georgia E. Mccarthy, Michael A. Vesk, Peter A. Radford, James Q. Bennett, Andrew F. Journal name Journal of animal ecology Volume number 81 Issue number 1 Start page 14 End page 23 Total pages 10 Publisher Wiley-Blackwell Publishing Ltd Place of publication Oxford, U. K. Publication date 2012 ISSN 0021-8790 1365-2656 Keyword(s) bayesian statistics habitat fragmentation informative priors precision Summary 1. Informative Bayesian priors can improve the precision of estimates in ecological studies or estimate parameters for which little or no information is available. While Bayesian analyses are becoming more popular in ecology, the use of strongly informative priors remains rare, perhaps because examples of informative priors are not readily available in the published literature. 2. Dispersal distance is an important ecological parameter, but is difficult to measure and estimates are scarce. General models that provide informative prior estimates of dispersal distances will therefore be valuable. 3. Using a world-wide data set on birds, we develop a predictive model of median natal dispersal distance that includes body mass, wingspan, sex and feeding guild. This model predicts median dispersal distance well when using the fitted data and an independent test data set, explaining up to 53% of the variation. 4. Using this model, we predict a priori estimates of median dispersal distance for 57 woodland-dependent bird species in northern Victoria, Australia. These estimates are then used to investigate the relationship between dispersal ability and vulnerability to landscape-scale changes in habitat cover and fragmentation. 5. We find evidence that woodland bird species with poor predicted dispersal ability are more vulnerable to habitat fragmentation than those species with longer predicted dispersal distances, thus improving the understanding of this important phenomenon. 6. The value of constructing informative priors from existing information is also demonstrated. When used as informative priors for four example species, predicted dispersal distances reduced the 95% credible intervals of posterior estimates of dispersal distance by 8-19%. Further, should we have wished to collect information on avian dispersal distances and relate it to species' responses to habitat loss and fragmentation, data from 221 individuals across 57 species would have been required to obtain estimates with the same precision as those provided by the general model. Language eng Field of Research 050104 Landscape Ecology Socio Economic Objective 960805 Flora, Fauna and Biodiversity at Regional or Larger Scales HERDC Research category C1 Refereed article in a scholarly journal Copyright notice ©2011, Wiley-Blackwell Publishing Persistent URL http://hdl.handle.net/10536/DRO/DU:30040418 Document type: Journal Article Collections: School of Life and Environmental Sciences Higher Education Research Group Centre for Integrative Ecology Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Mon, 05 Dec 2011, 12:36:50 EST Tue, 06 Dec 2011, 14:43:57 EST Tue, 06 Dec 2011, 14:48:47 EST Thu, 15 Dec 2011, 09:43:44 EST Mon, 06 Feb 2012, 09:34:03 EST Mon, 06 Feb 2012, 11:06:56 EST Mon, 06 Feb 2012, 11:08:15 EST Mon, 06 Feb 2012, 11:09:36 EST Mon, 06 Feb 2012, 11:11:13 EST Mon, 22 Jul 2013, 11:42:16 EST Tue, 05 Aug 2014, 11:13:35 EST Fri, 17 Oct 2014, 11:07:04 EST Tue, 27 Jan 2015, 11:18:32 EST Filtered Full Citation counts:   Cited 18 times in TR Web of Science Cited 21 times in Scopus Search Google Scholar Access Statistics: 130 Abstract Views, 21 File Downloads  -  Detailed Statistics Created: Mon, 05 Dec 2011, 12:36:50 EST

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