Landscape mapping at sub-Antarctic South Georgia provides a protocol for underpinning large-scale marine protected areas

被引:40
作者
Hogg, Oliver T. [1 ,2 ,3 ]
Huvenne, Veerle A. I. [2 ]
Griffiths, Huw J. [1 ]
Dorschel, Boris [4 ]
Linse, Katrin [1 ]
机构
[1] British Antarctic Survey, Nat Environm Res Council, Madingley Rd, Cambridge CB3 0ET, England
[2] Univ Southampton, Natl Oceanog Ctr, Waterfront Campus,European Way, Southampton SO14 3ZH, Hants, England
[3] Univ Southampton, Waterfront Campus,European Way, Southampton SO14 3ZH, Hants, England
[4] Helmholtz Ctr Polar & Marine Res, Alfred Wegener Inst, Alten Hafen 26, D-27568 Bremerhaven, Germany
基金
欧洲研究理事会; 美国国家科学基金会;
关键词
BIODIVERSITY LOSS; DEEP-SEA; CLASSIFICATION; HABITAT; CLUSTERS; ISLANDS; NUMBER; IMPACT; OCEAN; REEFS;
D O I
10.1038/srep33163
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Global biodiversity is in decline, with the marine environment experiencing significant and increasing anthropogenic pressures. In response marine protected areas (MPAs) have increasingly been adopted as the flagship approach to marine conservation, many covering enormous areas. At present, however, the lack of biological sampling makes prioritising which regions of the ocean to protect, especially over large spatial scales, particularly problematic. Here we present an interdisciplinary approach to marine landscape mapping at the sub-Antarctic island of South Georgia as an effective protocol for underpinning large-scale (10(5)-10(6) km(2)) MPA designations. We have developed a new high-resolution (100 m) digital elevation model (DEM) of the region and integrated this DEM with bathymetry-derived parameters, modelled oceanographic data, and satellite primary productivity data. These interdisciplinary datasets were used to apply an objective statistical approach to hierarchically partition and map the benthic environment into physical habitats types. We assess the potential application of physical habitat classifications as proxies for biological structuring and the application of the landscape mapping for informing on marine spatial planning.
引用
收藏
页数:15
相关论文
共 56 条
[31]   Highly Diverse, Poorly Studied and Uniquely Threatened by Climate Change: An Assessment of Marine Biodiversity on South Georgia's Continental Shelf [J].
Hogg, Oliver T. ;
Barnes, David K. A. ;
Griffiths, Huw J. .
PLOS ONE, 2011, 6 (05)
[32]   A global synthesis reveals biodiversity loss as a major driver of ecosystem change [J].
Hooper, David U. ;
Adair, E. Carol ;
Cardinale, Bradley J. ;
Byrnes, Jarrett E. K. ;
Hungate, Bruce A. ;
Matulich, Kristin L. ;
Gonzalez, Andrew ;
Duffy, J. Emmett ;
Gamfeldt, Lars ;
O'Connor, Mary I. .
NATURE, 2012, 486 (7401) :105-U129
[33]  
Hutchinson M., 2011, ESRI GEOMORPHOLOGY 2, P19
[34]   A NEW PROCEDURE FOR GRIDDING ELEVATION AND STREAM LINE DATA WITH AUTOMATIC REMOVAL OF SPURIOUS PITS [J].
HUTCHINSON, MF .
JOURNAL OF HYDROLOGY, 1989, 106 (3-4) :211-232
[35]   Comparison of automated classification techniques for predicting benthic biological communities using hydroacoustics and video observations [J].
Ierodiaconou, D. ;
Monk, J. ;
Rattray, A. ;
Laurenson, L. ;
Versace, V. L. .
CONTINENTAL SHELF RESEARCH, 2011, 31 (02) :S28-S38
[36]   Objective automated classification technique for marine landscape mapping in submarine canyons [J].
Ismail, Khaira ;
Huvenne, Veerle A. I. ;
Masson, Douglas G. .
MARINE GEOLOGY, 2015, 362 :17-32
[37]  
Kabacoff R. I., 2013, MANNING PUBLICATION
[38]   Acoustic seabed classification: improved statistical method [J].
Legendre, P ;
Ellingsen, KE ;
Bjornbom, E ;
Casgrain, P .
CANADIAN JOURNAL OF FISHERIES AND AQUATIC SCIENCES, 2002, 59 (07) :1085-1089
[39]  
Legendre P., 1998, NUMERICAL ECOLOGY
[40]   Fuzzy clustering for seafloor classification [J].
Lucieer, V. ;
Lucieer, A. .
MARINE GEOLOGY, 2009, 264 (3-4) :230-241