Correcting for missing and irregular data in home-range estimation.

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dc.contributor.author Fleming, CH en
dc.contributor.author Sheldon, D en
dc.contributor.author Fagan, WF en
dc.contributor.author Leimgruber, P en
dc.contributor.author Mueller, T en
dc.contributor.author Nandintsetseg, D en
dc.contributor.author Noonan, MJ en
dc.contributor.author Olson, KA en
dc.contributor.author Setyawan, Edy en
dc.contributor.author Sianipar, A en
dc.contributor.author Calabrese, JM en
dc.date.accessioned 2019-11-03T21:45:55Z en
dc.date.issued 2018-06 en
dc.identifier.citation Ecological applications : a publication of the Ecological Society of America 28(4):1003-1010 Jun 2018 en
dc.identifier.issn 1051-0761 en
dc.identifier.uri http://hdl.handle.net/2292/48803 en
dc.description.abstract Home-range estimation is an important application of animal tracking data that is frequently complicated by autocorrelation, sampling irregularity, and small effective sample sizes. We introduce a novel, optimal weighting method that accounts for temporal sampling bias in autocorrelated tracking data. This method corrects for irregular and missing data, such that oversampled times are downweighted and undersampled times are upweighted to minimize error in the home-range estimate. We also introduce computationally efficient algorithms that make this method feasible with large data sets. Generally speaking, there are three situations where weight optimization improves the accuracy of home-range estimates: with marine data, where the sampling schedule is highly irregular, with duty cycled data, where the sampling schedule changes during the observation period, and when a small number of home-range crossings are observed, making the beginning and end times more independent and informative than the intermediate times. Using both simulated data and empirical examples including reef manta ray, Mongolian gazelle, and African buffalo, optimal weighting is shown to reduce the error and increase the spatial resolution of home-range estimates. With a conveniently packaged and computationally efficient software implementation, this method broadens the array of data sets with which accurate space-use assessments can be made. en
dc.format.medium Print-Electronic en
dc.language eng en
dc.relation.ispartofseries Ecological applications : a publication of the Ecological Society of America en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.rights.uri https://esajournals.onlinelibrary.wiley.com/hub/journal/19399170/resources/author-guidelines-ecy#Copyright_and_Embargo en
dc.subject Animals en
dc.subject Skates (Fish) en
dc.subject Buffaloes en
dc.subject Ecology en
dc.subject Movement en
dc.subject Algorithms en
dc.subject Female en
dc.subject Animal Distribution en
dc.title Correcting for missing and irregular data in home-range estimation. en
dc.type Journal Article en
dc.identifier.doi 10.1002/eap.1704 en
pubs.issue 4 en
pubs.begin-page 1003 en
pubs.volume 28 en
dc.rights.holder Copyright: Ecological Society of America en
pubs.end-page 1010 en
pubs.publication-status Published en
dc.rights.accessrights http://purl.org/eprint/accessRights/OpenAccess en
pubs.subtype Research Support, Non-U.S. Gov't en
pubs.subtype Evaluation Studies en
pubs.subtype Research Support, U.S. Gov't, Non-P.H.S. en
pubs.subtype Journal Article en
pubs.elements-id 780897 en
pubs.org-id Science en
pubs.org-id Biological Sciences en
pubs.record-created-at-source-date 2018-02-17 en
pubs.dimensions-id 29450936 en


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