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Layer: Chapter 4 - Fishes (ID: 36)

Sub Layers: Name: Chapter 4 - Fishes

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Description: NOTE: The layers presented here only represent a small sample of the spatial information compiled during this assessment. The entire data package is publicly avaialble for download on NOAA's NCEI's website: https://www.nodc.noaa.gov/access/index.html. For more information, please see: Siceloff, L., M.S. Kendall, R. Kokubun, J. Drazen, and V. Moriwake. 2016. Chapter 4: Fishes - Bottom Fish. pp. 137-155. In: B.M. Costa and M.S. Kendall (eds.). Marine Biogeographic Assessment of the Main Hawaiian Islands. Bureau of Ocean Energy Management and National Oceanic and Atmospheric Administration. OCS Study BOEM 2016-035 and NOAA Technical Memorandum NOS NCCOS 214. 359 pp.; Stamoulis, K.A., M. Poti, J.M.S. Delevaux, M.K. Donovan, A. Friedlander, and M.S. Kendall. 2016. Chapter 4: Fishes - Reef Fish. pp. 156-196. In: B.M. Costa and M.S. Kendall (eds.). Marine Biogeographic Assessment of the Main Hawaiian Islands. Bureau of Ocean Energy Management and National Oceanic and Atmospheric Administration. OCS Study BOEM 2016-035 and NOAA Technical Memorandum NOS NCCOS 214. 359 pp. Understanding distributions of Hawaiian fish communities will be an important component of minimizing impacts from developing offshore wind power. Reef-, bottom-, and pelagic-fishes may each be affected by the construction and ongoing presence of mooring systems, floating platforms, and transmission cables. Pelagic fishes will likely utilize new offshore structures as they do the existing network of Fish Aggregating Devices. Bottom fish distributions were evaluated spatially using recent fisheries-dependent (Hawaiʻi's Division of Aquatic Resources catch reports) and fisheries-independent (bottom camera) data. Focused on the 'Deep 7' species of commercial importance, data were summarized around each island using the State’s catch reporting framework and Bureau of Ocean Energy Management's (BOEM) lease-block system. The fisheries-dependent dataset indicates that the winter months and specific areas are most important to the fishery such as Penguin Bank, Maui Nui channels, west Hawaiʻi, southern Maui, and northern Moloka‘i. The fishery independent dataset also highlights the importance of Penguin Bank and Maui Nui, and offers an effective approach for site-specific assessments. Analysis of reef fish distributions was based on a compilation of visual survey datasets and was focused on total species richness and biomass, endemic species richness and biomass, and biomass of commercial fishes. Spatial predictions of these variables were generated for each island on a 60 m grid to help plan for the narrow right of- way needed for power transmission cables. Predictions were created using boosted regression tree models relating the survey data to predictor variables representing seafloor topography, habitat, geography, and oceanography. Reef fish variables showed highest values in areas least accessible to humans such as the Hamakua and Puna districts on the island of Hawaiʻi, northern Molokai, eastern Maui and northeastern Oʻahu. Conversely, areas more accessible to humans had overall lower richness and biomass values and included Kailua Kona, west Maui and southern Oʻahu. Findings were limited by data gaps in several areas including a lack of bottom fish catch data around Kauaʻi and Ni‘ihau, as well as less bottom-camera samples around Kauaʻi, Ni‘ihau, Moloka‘i, western Hawaiʻi and Maui Nui apart from Penguin Bank and the channels. Data gaps that limited analyses for reef fish included a lack of samples in northwest and eastern Molokaʻi, northern and southeast Maui, southwest Oʻahu, northern exposures of the island of Hawaiʻi, Kauaʻi and Lāna‘i, and all of Ni‘ihau and Kaho‘olawe. In addition, a lack of high-resolution bathymetry prevented predictive modelling in several areas.

Copyright Text: For web service: NOAA NOS NCCOS CCMA Biogeography Branch

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