Prediction of mesophotic coral distributions in the Au‘au Channel, Hawaii

The primary objective of this study was to predict the distribution of mesophotic hard corals in the Au‘au Channel in the Main Hawaiian Islands (MHI). Mesophotic hard corals are light-dependent corals adapted to the low light conditions at approximately 30 to 150 m in depth. Several physical factors...

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Main Authors: Costa, Bryan M., Kendall, Matthew S., Rooney, John, Chow, Malia, Lecky, Joey, Parrish, Frank A., Montgomery, Anthony, Boland, Raymond C., Spalding, Heather
Format: Book
Language:English
Published: NOAA/National Centers for Coastal Ocean Science 2012
Subjects:
Online Access:http://aquaticcommons.org/14708/
http://aquaticcommons.org/14708/1/NOS%20NCCOS%20149.pdf
id ftaquaticcommons:oai:generic.eprints.org:14708
record_format openpolar
institution Open Polar
collection International Association of Aquatic and Marine Science Libraries and Information Centers (IAMSLIC): Aquatic Commons
op_collection_id ftaquaticcommons
language English
topic Ecology
Fisheries
Management
spellingShingle Ecology
Fisheries
Management
Costa, Bryan M.
Kendall, Matthew S.
Rooney, John
Chow, Malia
Lecky, Joey
Parrish, Frank A.
Montgomery, Anthony
Boland, Raymond C.
Spalding, Heather
Prediction of mesophotic coral distributions in the Au‘au Channel, Hawaii
topic_facet Ecology
Fisheries
Management
description The primary objective of this study was to predict the distribution of mesophotic hard corals in the Au‘au Channel in the Main Hawaiian Islands (MHI). Mesophotic hard corals are light-dependent corals adapted to the low light conditions at approximately 30 to 150 m in depth. Several physical factors potentially influence their spatial distribution, including aragonite saturation, alkalinity, pH, currents, water temperature, hard substrate availability and the availability of light at depth. Mesophotic corals and mesophotic coral ecosystems (MCEs) have increasingly been the subject of scientific study because they are being threatened by a growing number of anthropogenic stressors. They are the focus of this spatial modeling effort because the Hawaiian Islands Humpback Whale National Marine Sanctuary (HIHWNMS) is exploring the expansion of its scope—beyond the protection of the North Pacific Humpback Whale (Megaptera novaeangliae)—to include the conservation and management of these ecosystem components. The present study helps to address this need by examining the distribution of mesophotic corals in the Au‘au Channel region. This area is located between the islands of Maui, Lanai, Molokai and Kahoolawe, and includes parts of the Kealaikahiki, Alalākeiki and Kalohi Channels. It is unique, not only in terms of its geology, but also in terms of its physical oceanography and local weather patterns. Several physical conditions make it an ideal place for mesophotic hard corals, including consistently good water quality and clarity because it is flushed by tidal currents semi-diurnally; it has low amounts of rainfall and sediment run-off from the nearby land; and it is largely protected from seasonally strong wind and wave energy. Combined, these oceanographic and weather conditions create patches of comparatively warm, calm, clear waters that remain relatively stable through time. Freely available Maximum Entropy modeling software (MaxEnt 3.3.3e) was used to create four separate maps of predicted habitat suitability for: (1) all mesophotic hard corals combined, (2) Leptoseris, (3) Montipora and (4) Porites genera. MaxEnt works by analyzing the distribution of environmental variables where species are present, so it can find other areas that meet all of the same environmental constraints. Several steps (Figure 0.1) were required to produce and validate four ensemble predictive models (i.e., models with 10 replicates each). Approximately 2,000 georeferenced records containing information about mesophotic coral occurrence and 34 environmental predictors describing the seafloor’s depth, vertical structure, available light, surface temperature, currents and distance from shoreline at three spatial scales were used to train MaxEnt. Fifty percent of the 1,989 records were randomly chosen and set aside to assess each model replicate’s performance using Receiver Operating Characteristic (ROC), Area Under the Curve (AUC) values. An additional 1,646 records were also randomly chosen and set aside to independently assess the predictive accuracy of the four ensemble models. Suitability thresholds for these models (denoting where corals were predicted to be present/absent) were chosen by finding where the maximum number of correctly predicted presence and absence records intersected on each ROC curve. Permutation importance and jackknife analysis were used to quantify the contribution of each environmental variable to the four ensemble models.
format Book
author Costa, Bryan M.
Kendall, Matthew S.
Rooney, John
Chow, Malia
Lecky, Joey
Parrish, Frank A.
Montgomery, Anthony
Boland, Raymond C.
Spalding, Heather
author_facet Costa, Bryan M.
Kendall, Matthew S.
Rooney, John
Chow, Malia
Lecky, Joey
Parrish, Frank A.
Montgomery, Anthony
Boland, Raymond C.
Spalding, Heather
author_sort Costa, Bryan M.
title Prediction of mesophotic coral distributions in the Au‘au Channel, Hawaii
title_short Prediction of mesophotic coral distributions in the Au‘au Channel, Hawaii
title_full Prediction of mesophotic coral distributions in the Au‘au Channel, Hawaii
title_fullStr Prediction of mesophotic coral distributions in the Au‘au Channel, Hawaii
title_full_unstemmed Prediction of mesophotic coral distributions in the Au‘au Channel, Hawaii
title_sort prediction of mesophotic coral distributions in the au‘au channel, hawaii
publisher NOAA/National Centers for Coastal Ocean Science
publishDate 2012
url http://aquaticcommons.org/14708/
http://aquaticcommons.org/14708/1/NOS%20NCCOS%20149.pdf
geographic Pacific
geographic_facet Pacific
genre Humpback Whale
Megaptera novaeangliae
genre_facet Humpback Whale
Megaptera novaeangliae
op_relation http://aquaticcommons.org/14708/1/NOS%20NCCOS%20149.pdf
Costa, Bryan M. and Kendall, Matthew S. and Rooney, John and Chow, Malia and Lecky, Joey and Parrish, Frank A. and Montgomery, Anthony and Boland, Raymond C. and Spalding, Heather (2012) Prediction of mesophotic coral distributions in the Au‘au Channel, Hawaii. Silver Spring, MD, NOAA/National Centers for Coastal Ocean Science, 44pp. (NOAA Technical Memorandum NOS NCCOS, 149)
_version_ 1766026399073697792
spelling ftaquaticcommons:oai:generic.eprints.org:14708 2023-05-15T16:36:05+02:00 Prediction of mesophotic coral distributions in the Au‘au Channel, Hawaii Costa, Bryan M. Kendall, Matthew S. Rooney, John Chow, Malia Lecky, Joey Parrish, Frank A. Montgomery, Anthony Boland, Raymond C. Spalding, Heather 2012-06 application/pdf http://aquaticcommons.org/14708/ http://aquaticcommons.org/14708/1/NOS%20NCCOS%20149.pdf en eng NOAA/National Centers for Coastal Ocean Science http://aquaticcommons.org/14708/1/NOS%20NCCOS%20149.pdf Costa, Bryan M. and Kendall, Matthew S. and Rooney, John and Chow, Malia and Lecky, Joey and Parrish, Frank A. and Montgomery, Anthony and Boland, Raymond C. and Spalding, Heather (2012) Prediction of mesophotic coral distributions in the Au‘au Channel, Hawaii. Silver Spring, MD, NOAA/National Centers for Coastal Ocean Science, 44pp. (NOAA Technical Memorandum NOS NCCOS, 149) Ecology Fisheries Management Monograph or Serial Issue NonPeerReviewed 2012 ftaquaticcommons 2020-02-27T09:26:33Z The primary objective of this study was to predict the distribution of mesophotic hard corals in the Au‘au Channel in the Main Hawaiian Islands (MHI). Mesophotic hard corals are light-dependent corals adapted to the low light conditions at approximately 30 to 150 m in depth. Several physical factors potentially influence their spatial distribution, including aragonite saturation, alkalinity, pH, currents, water temperature, hard substrate availability and the availability of light at depth. Mesophotic corals and mesophotic coral ecosystems (MCEs) have increasingly been the subject of scientific study because they are being threatened by a growing number of anthropogenic stressors. They are the focus of this spatial modeling effort because the Hawaiian Islands Humpback Whale National Marine Sanctuary (HIHWNMS) is exploring the expansion of its scope—beyond the protection of the North Pacific Humpback Whale (Megaptera novaeangliae)—to include the conservation and management of these ecosystem components. The present study helps to address this need by examining the distribution of mesophotic corals in the Au‘au Channel region. This area is located between the islands of Maui, Lanai, Molokai and Kahoolawe, and includes parts of the Kealaikahiki, Alalākeiki and Kalohi Channels. It is unique, not only in terms of its geology, but also in terms of its physical oceanography and local weather patterns. Several physical conditions make it an ideal place for mesophotic hard corals, including consistently good water quality and clarity because it is flushed by tidal currents semi-diurnally; it has low amounts of rainfall and sediment run-off from the nearby land; and it is largely protected from seasonally strong wind and wave energy. Combined, these oceanographic and weather conditions create patches of comparatively warm, calm, clear waters that remain relatively stable through time. Freely available Maximum Entropy modeling software (MaxEnt 3.3.3e) was used to create four separate maps of predicted habitat suitability for: (1) all mesophotic hard corals combined, (2) Leptoseris, (3) Montipora and (4) Porites genera. MaxEnt works by analyzing the distribution of environmental variables where species are present, so it can find other areas that meet all of the same environmental constraints. Several steps (Figure 0.1) were required to produce and validate four ensemble predictive models (i.e., models with 10 replicates each). Approximately 2,000 georeferenced records containing information about mesophotic coral occurrence and 34 environmental predictors describing the seafloor’s depth, vertical structure, available light, surface temperature, currents and distance from shoreline at three spatial scales were used to train MaxEnt. Fifty percent of the 1,989 records were randomly chosen and set aside to assess each model replicate’s performance using Receiver Operating Characteristic (ROC), Area Under the Curve (AUC) values. An additional 1,646 records were also randomly chosen and set aside to independently assess the predictive accuracy of the four ensemble models. Suitability thresholds for these models (denoting where corals were predicted to be present/absent) were chosen by finding where the maximum number of correctly predicted presence and absence records intersected on each ROC curve. Permutation importance and jackknife analysis were used to quantify the contribution of each environmental variable to the four ensemble models. Book Humpback Whale Megaptera novaeangliae International Association of Aquatic and Marine Science Libraries and Information Centers (IAMSLIC): Aquatic Commons Pacific