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  1. National Taiwan Ocean University Research Hub
  2. 海洋科學與資源學院
  3. 環境生物與漁業科學學系
請用此 Handle URI 來引用此文件: http://scholars.ntou.edu.tw/handle/123456789/22045
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dc.contributor.authorMammel, Mubaraken_US
dc.contributor.authorNaimullah, Muhamaden_US
dc.contributor.authorVayghan, Ali Haghien_US
dc.contributor.authorHsu, Jhenen_US
dc.contributor.authorLee, Ming-Anen_US
dc.contributor.authorWu, Jun-Hongen_US
dc.contributor.authorWang, Yi-Chenen_US
dc.contributor.authorLan, Kuo-Weien_US
dc.date.accessioned2022-08-17T02:42:43Z-
dc.date.available2022-08-17T02:42:43Z-
dc.date.issued2022-06-
dc.identifier.issn2072-4292-
dc.identifier.urihttp://scholars.ntou.edu.tw/handle/123456789/22045-
dc.description.abstractThe environmental characteristics of the Taiwan Strait (TS) have been linked to variations in the abundance and distribution of greater amberjack (Seriola dumerili) populations. Greater amberjack is a commercially and ecologically valuable species in ecosystems, and its spatial distribution patterns are pivotal to fisheries management and conservation. However, the relationship between the catch rates of S. dumerili and the environmental changes and their impact on fish communities remains undetermined in the TS. The goal of this study was to determine the spatiotemporal distribution pattern of S. dumerili with environmental characteristics in the TS from south to north (20 degrees N-29 degrees N and 115 degrees E-127 degrees E), applying generalized additive models (GAMs) and spatiotemporal fisheries data from logbooks and voyage data recorders from Taiwanese fishing vessels (2014-2017) as well as satellite-derived remote sensing environmental data. We used the generalized linear model (GLM) and GAM to analyze the effect of environmental factors and catch rates. The predictive performance of the two statistical models was quantitatively assessed by using the root mean square difference. Results reveal that the GAM outperforms the GLM model in terms of the functional relationship of the GAM for generating a reliable predictive tool. The model selection process was based on the significance of model terms, increase in deviance explained, decrease in residual factor, and reduction in Akaike's information criterion. We then developed a species distribution model based on the best GAMs. The deviance explained indicated that sea surface temperature, linked to high catch rates, was the key factor influencing S. dumerili distributions, whereas mixed layer depth was the least relevant factor. The model predicted a relatively high S. dumerili catch rate in the northwestern region of the TS in summer, with the area extending to the East China Sea. The target species is strongly influenced by biophysical environmental conditions, and potential fishing areas are located throughout the waters of the TS. The findings of this study showed how S. dumerili populations respond to environmental variables and predict species distributions. Data on the habitat preferences and distribution patterns of S. dumerili are essential for understanding the environmental conditions of the TS, which can inform future priorities for conservation planning and management.en_US
dc.language.isoen_USen_US
dc.publisherMDPIen_US
dc.relation.ispartofREMOTE SENS-BASELen_US
dc.subjectALBACORE THUNNUS-ALALUNGAen_US
dc.subjectSEA-SURFACE TEMPERATUREen_US
dc.subjectSPECIES DISTRIBUTION MODELSen_US
dc.subjectEAST CHINA SEAen_US
dc.subjectSERIOLA-DUMERILIen_US
dc.subjectPELAGIC FISHen_US
dc.subjectSCOMBER-JAPONICUSen_US
dc.subjectWESTERNen_US
dc.subjectGROWTHen_US
dc.subjectPREDICTIONen_US
dc.titleVariability in the Spatiotemporal Distribution Patterns of Greater Amberjack in Response to Environmental Factors in the Taiwan Strait Using Remote Sensing Dataen_US
dc.typejournal articleen_US
dc.identifier.doi10.3390/rs14122932-
dc.identifier.isiWOS:000818297000001-
dc.relation.journalvolume14en_US
dc.relation.journalissue12en_US
dc.identifier.eissn2072-4292-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
item.languageiso639-1en_US-
item.fulltextno fulltext-
item.grantfulltextnone-
item.openairetypejournal article-
crisitem.author.deptCollege of Ocean Science and Resource-
crisitem.author.deptDepartment of Environmental Biology and Fisheries Science-
crisitem.author.deptNational Taiwan Ocean University,NTOU-
crisitem.author.deptDepartment of Transportation Science-
crisitem.author.deptCollege of Maritime Science and Management-
crisitem.author.deptGeneral Education Center-
crisitem.author.deptLiberal Education Division-
crisitem.author.deptCenter of Excellence for Ocean Engineering-
crisitem.author.deptRiver and Coastal Disaster Prevention-
crisitem.author.deptEcology and Environment Construction-
crisitem.author.deptNational Taiwan Ocean University,NTOU-
crisitem.author.deptDepartment of Environmental Biology and Fisheries Science-
crisitem.author.deptCollege of Ocean Science and Resource-
crisitem.author.orcid0000-0001-6970-7643-
crisitem.author.parentorgNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgCollege of Ocean Science and Resource-
crisitem.author.parentorgCollege of Maritime Science and Management-
crisitem.author.parentorgNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgGeneral Education Center-
crisitem.author.parentorgNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgCenter of Excellence for Ocean Engineering-
crisitem.author.parentorgCenter of Excellence for Ocean Engineering-
crisitem.author.parentorgCollege of Ocean Science and Resource-
crisitem.author.parentorgNational Taiwan Ocean University,NTOU-
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環境生物與漁業科學學系
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