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Exploring spatial nonstationary environmental effects on Yellow Perch distribution in Lake Erie

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dc.contributor.authorLiu, Changdongen
dc.contributor.authorLiu, Junchaoen
dc.contributor.authorJiao, Yanen
dc.contributor.authorTang, Yanlien
dc.contributor.authorReid, Kevin B.en
dc.contributor.departmentFish and Wildlife Conservationen
dc.date.accessioned2021-05-01T04:38:35Zen
dc.date.available2021-05-01T04:38:35Zen
dc.date.issued2019-07-25en
dc.date.updated2021-05-01T04:38:27Zen
dc.description.abstractBackground: Global regression models under an implicit assumption of spatial stationarity were commonly applied to estimate the environmental effects on aquatic species distribution. However, the relationships between species distribution and environmental variables may change among spatial locations, especially at large spatial scales with complicated habitat. Local regression models are appropriate supplementary tools to explore species-environment relationships at finer scales. Method: We applied geographically weighted regression (GWR) models on Yellow Perch in Lake Erie to estimate spatially-varying environmental effects on the presence probabilities of this species. Outputs from GWR were compared with those from generalized additive models (GAMs) in exploring the Yellow Perch distribution. Local regression coefficients from the GWR were mapped to visualize spatially-varying species-environment relationships. K-means cluster analyses based on the t-values of GWR local regression coefficients were used to characterize the distinct zones of ecological relationships. Results: Geographically weighted regression resulted in a significant improvement over the GAM in goodness-of-fit and accuracy of model prediction. Results from the GWR revealed the magnitude and direction of environmental effects on Yellow Perch distribution changed among spatial locations. Consistent species-environment relationships were found in the west and east basins for adults. The different kinds of species-environment relationships found in the central management unit (MU) implied the variation of relationships at a scale finer than the MU. Conclusions: This study draws attention to the importance of accounting for spatial nonstationarity in exploring species-environment relationships. The GWR results can provide support for identification of unique stocks and potential refinement of the current jurisdictional MU structure toward more ecologically relevant MUs for the sustainable management of Yellow Perch in Lake Erie.en
dc.description.versionPublished (Publication status)en
dc.format.extent20 page(s)en
dc.format.mediumElectronic-eCollectionen
dc.format.mimetypeapplication/pdfen
dc.identifierARTN e7350 (Article number)en
dc.identifier.doihttps://doi.org/10.7717/peerj.7350en
dc.identifier.eissn2167-8359en
dc.identifier.issn2167-8359en
dc.identifier.issue7en
dc.identifier.orcidJiao, Yan [0000-0002-8804-5005]en
dc.identifier.other7350 (PII)en
dc.identifier.pmid31380148 (pubmed)en
dc.identifier.urihttp://hdl.handle.net/10919/103173en
dc.identifier.volume7en
dc.language.isoenen
dc.publisherPeerJen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectSpatial nonstationarityen
dc.subjectSpecies-environment relationshipsen
dc.subjectGeographically weighted regressionen
dc.subjectGeneralized additive modelsen
dc.subjectYellow Perchen
dc.subjectLake Erieen
dc.subjectGEOGRAPHICALLY WEIGHTED REGRESSIONen
dc.subjectGENERALIZED LINEAR-MODELen
dc.subjectWALLEYE SANDER-VITREUSen
dc.subjectFLAVESCENSen
dc.subjectABUNDANCEen
dc.subjectFISHERYen
dc.subjectGROWTHen
dc.subjectSHELFen
dc.subjectEXPLORATIONen
dc.subjectVARIABLESen
dc.subject06 Biological Sciencesen
dc.subject11 Medical and Health Sciencesen
dc.titleExploring spatial nonstationary environmental effects on Yellow Perch distribution in Lake Erieen
dc.title.serialPeerJen
dc.typeArticle - Refereeden
dc.type.otherArticleen
dc.type.otherJournalen
dcterms.dateAccepted2019-06-25en
pubs.organisational-group/Virginia Tech/Natural Resources & Environmenten
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Natural Resources & Environment/Fish and Wildlife Conservationen
pubs.organisational-group/Virginia Tech/Natural Resources & Environment/CNRE T&R Facultyen
pubs.organisational-group/Virginia Techen

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