Assessing Movement Patterns using Bayesian State-Space Models on Lake Winnipeg Walleye

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dc.contributor.authorMunaweera, Inesh
dc.contributor.authorMuthukumarana, Saman
dc.contributor.authorGillis, D. M
dc.contributor.authorWatkinson, D. A.
dc.contributor.authorCharles, C.
dc.contributor.authorEnders, E.C.
dc.date.accessioned2022-09-23T14:58:33Z
dc.date.available2022-09-23T14:58:33Z
dc.date.issued2021-03-18
dc.date.submitted2022-09-01T07:34:07Zen_US
dc.description.abstractAcoustic telemetry systems technology is useful for studying fish movement patterns and habitat use. However, the data generated from omnidirectional acoustic receivers are prone to large observation errors since the tagged animal can be anywhere in the detection range of the receiver. In this study, we used the Bayesian state-space modeling (SSM) approach and different smoothing methods including kernel smoothing and cross-validated local polynomial regression to reconstruct fish movement paths of Walleye (Sander vitreus) using data obtained from a telemetry receiver grid in Lake Winnipeg. Using SSM approach, we obtained more realistic movement paths, compared to the smoothing methods. In addition, we highlighted the advantages of the SSM approach to estimate undetected movement paths, over simple smoothing techniques, by comparing ecological metrics such as path length and tortuosity between different reconstruction approaches. Reconstructed paths could be useful in making effective fishery management decision on Lake Winnipeg in the future by providing information on how Walleye move and distribute in Lake Winnipeg over space and time.en_US
dc.identifier.doihttps://doi.org/10.1139/cjfas-2020-026
dc.identifier.urihttp://hdl.handle.net/1993/36920
dc.language.isoengen_US
dc.publisherCanadian Journal of Fisheries and Aquatic Sciencesen_US
dc.rightsopen accessen_US
dc.subjectAcoustic Telemetryen_US
dc.subjectWalleyeen_US
dc.subjectBayesian Inferenceen_US
dc.subjectMarkov Chain Monte Carloen_US
dc.subjectState-space Modelsen_US
dc.subjectFish Movementsen_US
dc.titleAssessing Movement Patterns using Bayesian State-Space Models on Lake Winnipeg Walleyeen_US
dc.typepreprinten_US
local.author.affiliationFaculty of Science::Department of Statisticsen_US
oaire.citation.endPage1421en_US
oaire.citation.issue10en_US
oaire.citation.startPage1407en_US
oaire.citation.titleAssessing movement patterns using Bayesian state space models on Lake Winnipeg walleyeen_US
oaire.citation.volume78en_US
project.funder.identifierhttp://dx.doi.org/10.13039/501100000041en_US
project.funder.nameFisheries and Oceans Canadaen_US
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