Abstract
Regional scale habitat suitability models provide finer scale resolution and more focused predictions of where organisms may occur. Previous modelling approaches have focused primarily on local and/or global scales, while regional scale models have been relatively few. In this study, regional scale predictive habitat models are presented for deep-sea corals for the U.S. West Coast (California, Oregon and Washington). Model results are intended to aid in future research or mapping efforts and to assess potential coral habitat suitability both within and outside existing bottom trawl closures (i.e. Essential Fish Habitat (EFH)) and identify suitable habitat within U.S. National Marine Sanctuaries (NMS). Deep-sea coral habitat suitability was modelled at 500 m×500 m spatial resolution using a range of physical, chemical and environmental variables known or thought to influence the distribution of deep-sea corals. Using a spatial partitioning cross-validation approach, maximum entropy models identified slope, temperature, salinity and depth as important predictors for most deep-sea coral taxa. Large areas of highly suitable deep-sea coral habitat were predicted both within and outside of existing bottom trawl closures and NMS boundaries. Predicted habitat suitability over regional scales are not currently able to identify coral areas with pin point accuracy and probably overpredict actual coral distribution due to model limitations and unincorporated variables (i.e. data on distribution of hard substrate) that are known to limit their distribution. Predicted habitat results should be used in conjunction with multibeam bathymetry, geological mapping and other tools to guide future research efforts to areas with the highest probability of harboring deep-sea corals. Field validation of predicted habitat is needed to quantify model accuracy, particularly in areas that have not been sampled.
Highlights
Predictive habitat suitability modelling is a cost effective approach to assist scientific research, conservation and management of vulnerable marine ecosystems (VMEs) in the deep sea
Species’ niche From the available environmental data, an a priori variable selection process that took into account closely related and highly correlated variables, identified seven variables that were likely to influence the probability of species presence (Tables 3, 4 and S1–S10 in File S1)
Unincorporated model variables and model accuracy There are several variables that are important for coral settlement, growth and survival that were not included in the model because they do not exist at sufficient resolutions, a problem shared with all habitat suitability efforts [43]
Summary
Predictive habitat suitability modelling is a cost effective approach to assist scientific research, conservation and management of vulnerable marine ecosystems (VMEs) in the deep sea. Whitmire and Clarke [8] reviewed the state of deep coral ecosystems in the waters of California, Oregon, and Washington and reported 101 species of corals from six cnidarian orders have been identified in the region. These included 18 species of stony corals (Class Anthozoa, Order Scleractinia) from seven families, seven species of black corals (Order Antipatharia) from three families, 36 species of gorgonians (Order Gorgonacea) from 10 families, eight species of true soft corals (Order Alcyonacea) from three families, 27 species of pennatulaceans (Order Pennatulacea) from eleven families, and five species of stylasterid corals (Class Hydrozoa, Order Anthoathecatae, Family Stylasteridae). The U.S West Coast has been relatively well sampled for deep-sea corals in comparison to many other regions of the world’s oceans, but the spatial distribution of deep-sea corals in unsurveyed areas within the EEZ remains largely unknown
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
