An empirically validated method for characterizing pelagic habitats in the Gulf of Mexico using ocean model data

Limnology and Oceanography: Methods - Tập 17 Số 6 - Trang 362-375 - 2019
Matthew W. Johnston1, Rosanna Milligan1, Cole Easson2,1, Sergio deRada3, David English4, Bradley Penta3, Tracey Sutton1
1Halmos College of Natural Sciences and Oceanography, Nova Southeastern University, Dania Beach, Florida
2Department of Biology, Middle Tennessee State University, Murfreesboro, Tennessee
3U.S. Naval Research Laboratory, Stennis Space Center, Mississippi
4College of Marine Science, University of South Florida, St. Petersburg, Florida

Tóm tắt

AbstractMesoscale oceanic features such as eddies generate considerable environmental heterogeneity within the pelagic oceans, but their transient nature makes it difficult to identify both their spatial and temporal extent and their effects on the distribution of pelagic fauna. Simplifying these complex features using a biologically meaningful classification system will likely be a useful first step in understanding the extent of their influence in structuring open‐ocean ecosystems. In this study, we present a tool to classify the pelagic environment in the Gulf of Mexico using sea‐surface height and temperature‐at‐depth data from the 1/25° GOM HYbrid Coordinate Ocean Model (HYCOM). Three “water types” were identified: Loop Current‐origin water (LCOW), Gulf common water (CW), and mixed (MIX) water, where the latter represents an intermediate state during the degradation of LCOW to CW. The HYCOM‐derived classifications were validated against in situ CTD data and microbial samples collected through 2015–2016 by the Deep Pelagic Nekton Dynamics of the Gulf of Mexico (DEEPEND) consortium. The validation data comprised classifications derived from both temperature‐depth (TD) and temperature‐salinity (TS) profiles and from microbial community analyses from the surface to mesopelagic depths. The HYCOM classifications produced an overall agreement rate of 77% with the TS/TD classifications, and 79% with the microbial classifications. With applicability across a wide range of spatial and temporal scales, we believe that the system provides a useful, complementary tool for biological oceanographers and resource managers interested in better understanding the effects of major mesoscale features on the pelagic biota.

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Tài liệu tham khảo

10.3989/scimar.2006.70s2105

10.1029/90JC02020

10.1029/93JC02153

Biggs D. C., 2001, Distribution and abundance of phytoplankton, zooplankton, ichthyoplankton, and micronekton in the deepwater Gulf of Mexico, Gulf Mex. Sci., 19, 2

10.1038/nmeth.f.303

10.1038/ismej.2012.8

10.1016/j.dsr2.2014.01.008

10.1175/2010JPO4479.1

10.1175/1520-0485(2003)033<2504:NASWTH>2.0.CO;2

10.1016/j.jmarsys.2005.09.016

10.3354/meps063253

10.1007/s10750-017-3330-0

10.1007/s00227-004-1381-z

10.1098/rsos.170033

10.1038/352055a0

10.1038/nature08058

10.4319/lo.1997.42.6.1353

10.4319/lo.2003.48.3.1176

10.1038/nature16942

10.1038/srep33824

Herring H. J.2010.Gulf of Mexico hydrographic climatology and method of synthesizing subsurface profiles from the satellite sea surface height anomaly p. 63. ICES document report 122.

10.4319/lo.2006.51.3.1274

10.1016/S0079-6611(97)00003-7

10.1111/gcb.12874

10.1093/biosci/biu121

10.1146/annurev-marine-010213-135046

10.1007/s10236-008-0160-7

10.1146/annurev-marine-120709-142814

10.1021/es301570w

10.1029/91JC02450

10.1080/00785236.1995.10422042

Liaw A., 2002, Classification and regression by randomForest, R News, 2, 18

10.3354/meps09860

10.3389/fmicb.2016.01048

10.1038/28367

10.1111/fog.12214

10.3354/meps10397

10.1016/j.pocean.2014.12.007

NASA Goddard Space Flight Center Ocean Ecology Laboratory Ocean Biology Processing Group.2014.Coastal zone color scanner experiment (CZCS) chlorophyll data 2014. Reprocessing. NASA OB.DAAC Greenbelt MD USA.

10.1146/annurev.ea.19.050191.001435

10.1357/002224085788437325

10.1029/2006JC003695

10.1093/nar/gks1219

R Core Team.2017.R: A language and environment for statistical computing. R Foundation for Statistical Computing.

10.2134/jeq2001.302320x

10.1175/JPO2786.1

10.1371/journal.pone.0076080

Team R.2015. RStudio: integrated development for R. RStudio Inc. Boston MA.42:14. Available fromhttp://www.rstudio.com

10.1175/JPO-D-14-0138.1

10.1098/rsbl.2014.0746

10.3389/fmars.2016.00031

10.1175/2007JPO3802.1

10.1126/science.1261359

10.1175/JPO2989.1

10.1007/s00227-017-3122-0

10.1073/pnas.95.12.6578

10.1029/1998JC900072

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Limnology and Oceanography: Methods

Tập 17 Số 6

362-375

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