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Habitat-based species distribution modelling of the Hawaiian deepwater snapper-grouper complex

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dc.contributor University Of Hawaii Manoa
dc.contributor Sch Ocean & Earth Sci & Technol
dc.contributor Univ Hawaii Manoa
dc.contributor Curtin Univ
dc.contributor University Of Hawaii System
dc.contributor Hawaii Inst Marine Biol
dc.contributor Dept Oceanog
dc.contributor Dept Environm & Agr
dc.contributor Curtin University
dc.contributor Australian Inst Marine Sci
dc.contributor Univ Hawaii
dc.contributor Uwa Oceans Inst
dc.contributor Australian Institute Of Marine Science FRANKLIN, ERIK C. OYAFUSO, ZACK. S. DRAZEN, JEFFREY C. MOORE, CORDELIA H. 2017-10-22T19:04:33Z 2017-10-22T19:04:33Z 2018-11-01T03:23:25Z 2017-10-22T19:04:33Z 2017-10-22T19:04:33Z 2018-11-01T03:23:25Z 2017-11-01
dc.identifier.citation Oyafuso ZS, Drazen JC, Moore CH, Franklin EC (2017) Habitat-based species distribution modelling of the Hawaiian deepwater snapper-grouper complex. Fisheries Research 195: 19-27
dc.identifier.issn 0165-7836
dc.description.abstract Deepwater snappers and groupers are valuable components of many subtropical and tropical fisheries globally and understanding the habitat associations of these species is important for spatial fisheries management. Habitat-based species distribution models were developed for the deepwater snapper-grouper complex in the main Hawaiian Islands (MHI). Six eteline snappers (Pristipomoides spp., Aphareus rutilans, and Etelis spp.) and one endemic grouper (Hyporthodus quernus) comprise the species complex known as the Hawaiian Deep Seven Bottomfishes. Species occurrence was recorded using baited remote underwater video stations deployed between 30 and 365 m (n = 2381) and was modeled with 12 geomorphological covariates using GLMs, GAMs, and BRTs. Depth was the most important predictor across species, along with ridge-like features, rugosity, and slope. In particular, ridge-like features were important habitat predictors for E. coruscans and P. filamentosus. Bottom hardness was an important predictor especially for the two Etelis species. Along with depth, rugosity and slope were the most important habitat predictors for A. rutilans and P. zonatus, respectively. Models built using GAMs and BRTs generally had the highest predictive performance. Finally, using the BRT model output, we created species-specific distribution maps and demonstrated that areas with high predicted probabilities of occurrence were positively related to fishery catch rates.
dc.description.sponsorship Project funding was provided by the Colonel Willys E. Lord, DVM and Sandina L. Lord Endowed Scholarship (to ZSO), the Carol Ann and Myron K. Hayashida Scholarship (to ZSO), and the NMFS-Sea Grant Population Dynamics Fellowship (to ZSO). The BotCam data were collected, processed, organized, and provided by: V. Moriwake, C. Demarke, B. Alexander, C. Kelley, W. Misa, J. Friedman, D. Tokishi, B. Richards, D. Kobayashi, and A. Rollo. Funding for the BotCam work was provided by the State of Hawaii Division of Aquatic Resources and the Federal Aid in Sport Fish Restoration program (F17R35-study IX), NOAA Pacific Islands Regional Office, Kahoolawe Island Reserve Commission, NOAA Pacific Island Fisheries Science Center, the Joint Institute for Marine and Atmospheric Research at the University of Hawaii at Manoa, the NOAA Fisheries Office of Science and Technology, and the NOAA Fisheries Advanced Science at Technology Working Group. All funding sources had no involvement in the study design, collection, analysis, and interpretation of the data nor in the writing of this manuscript. This manuscript is SOEST contribution #10019 and HIMB contribution #1686.
dc.language English
dc.subject Demersal Fish
dc.subject Boosted Regression Trees
dc.subject Fisheries
dc.subject Snapper-grouper Complex
dc.subject Species Distribution Models
dc.subject Reef Fishes
dc.subject Fisheries Management
dc.subject Abundance
dc.subject Baited Remote Underwater Video (bruv)
dc.subject Fish Habitat
dc.subject Camera System
dc.subject Marine Protected Areas
dc.subject Essential Fish Habitat
dc.subject Incorporating Spatial Autocorrelation
dc.subject Islands
dc.title Habitat-based species distribution modelling of the Hawaiian deepwater snapper-grouper complex
dc.type journal article
dc.identifier.doi 10.1016/j.fishres.2017.06.011
dc.identifier.wos WOS:000412254900003

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