干旱区生态环境知识资源中心(Arid): Predictive modeling of suitable habitat for deep-sea corals offshore the Northeast United States

Arid

DOI	10.1016/j.dsr.2020.103229
	Predictive modeling of suitable habitat for deep-sea corals offshore the Northeast United States
	Kinlan, Brian P.1; Poti, Matthew 1,2; Drohan, Amy F.3,5; Packer, David B.3; Dorfman, Dan S.1,2; Nizinski, Martha S.4
通讯作者	Nizinski, Martha S.
来源期刊	DEEP-SEA RESEARCH PART I-OCEANOGRAPHIC RESEARCH PAPERS
ISSN	0967-0637
EISSN	1879-0119
出版年	2020
卷号	158
英文摘要	Deep-sea corals (DSCs) are important living marine resources, forming both oases of biodiversity and three-dimensional habitat structure for fishes and invertebrates. However, because of logistical difficulties and expense of deep-sea exploration, much less is known about the distribution of DSCs than is known for their shallow-water counterparts. Predictive modeling, therefore, is essential for estimating the extent of DSC habitat in areas that are unexplored in order to support conservation efforts, to provide information for effective management of offshore activities affecting the seafloor, and for future exploration and research. In support of research and management efforts in the U.S. Northeast (Cape Hatteras, NC north to the Canadian border), we developed a comprehensive set of habitat suitability models covering this entire geographic region for nine taxonomic groups of DSCs (Alcyonacea, gorgonian corals, non-gorgonian corals, Scleractinia, Caryophylliidae, Flabellidae, Pennatulacea, Sessiliflorae, and Subselliflorae). Maximum entropy (MaxEnt) models were fit to DSC presence records and spatially-explicit environmental predictors depicting depth and seafloor topography, surficial sediment characteristics, and oceanography. A stepwise model selection procedure was then implemented to identify the set of predictor variables that maximized predictive performance for each taxonomic group. To allow for comparisons across taxonomic groups, the standard MaxEnt logistic predictions were converted into calibrated classes of habitat suitability. Overall, model performance was high for all taxonomic groups. Model fit was best for Caryophylliidae, Sessiliflorae, and Flabellidae, whereas model stability was greatest for the three taxonomic groups of Alcyonacea. Model results reported here corroborate known distributions of corals in the region. For example, large structure-forming taxa are predicted to occur mainly in canyon environments, particularly in areas of steep slope (>30 degrees); sea pens in softer sediments of the continental shelf and slope. Additionally, the models successfully predicted DSC locations during field testing. Despite the limitations of presence-only data, several novel extensions to the traditional MaxEnt analysis workflow improved model selection, accuracy assessment, and comparability of results across taxonomic groups. This approach, when integrated with management processes, could be a powerful tool for science-based conservation, management, and spatial planning for these marine resources.
英文关键词	Cold-water corals Species distribution models Statistical machine learning MaxEnt Marine spatial planning Biogeography
类型	Article
语种	英语
国家	USA
收录类别	SCI-E
WOS记录号	WOS:000523718600005
WOS关键词	WATER GORGONIAN CORALS ; SPECIES DISTRIBUTION MODELS ; CONTINENTAL MARGINS ; LOPHELIA-PERTUSA ; MAXIMUM-ENTROPY ; SAMPLING BIAS ; SUITABILITY ; DISTRIBUTIONS ; PERFORMANCE ; ATLANTIC
WOS类目	Oceanography
WOS研究方向	Oceanography
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/314310
作者单位	1.NOAA, Natl Ocean Serv, Natl Ctr Coastal Ocean Sci, 1305 East West Hwy,N SCI 1, Silver Spring, MD 20910 USA; 2.CSS Inc, 10301 Democracy Lane,Suite 300, Fairfax, VA 22030 USA; 3.NOAA, Fisheries Serv, Northeast Fisheries Sci Ctr, James J Howard Marine Sci Lab, 74 Magruder Rd, Highlands, NJ 07732 USA; 4.NOAA, Fisheries Serv, Off Sci & Technol, Natl Systemat Lab,Smithsonian Inst,NHB, POB 37012,MRC 153, Washington, DC 37012 USA; 5.Brinkerhoff Environm Serv, 1805 Atlantic Ave, Manasquan, NJ 08736 USA
推荐引用方式 GB/T 7714	Kinlan, Brian P.,Poti, Matthew,Drohan, Amy F.,et al. Predictive modeling of suitable habitat for deep-sea corals offshore the Northeast United States[J],2020,158.
APA	Kinlan, Brian P.,Poti, Matthew,Drohan, Amy F.,Packer, David B.,Dorfman, Dan S.,&Nizinski, Martha S..(2020).Predictive modeling of suitable habitat for deep-sea corals offshore the Northeast United States.DEEP-SEA RESEARCH PART I-OCEANOGRAPHIC RESEARCH PAPERS,158.
MLA	Kinlan, Brian P.,et al."Predictive modeling of suitable habitat for deep-sea corals offshore the Northeast United States".DEEP-SEA RESEARCH PART I-OCEANOGRAPHIC RESEARCH PAPERS 158(2020).