title: Retrospective analysis of midsummer hypoxic area and volume in the northern Gulf of Mexico, 1985-2011.
abstract: Robust estimates of hypoxic extent (both area and volume) are important for assessing the impacts of low dissolved oxygen on aquatic ecosystems at large spatial scales. Such estimates are also important for calibrating models linking hypoxia to causal factors, such as nutrient loading and stratification, and for informing management decisions. In this study, we develop a rigorous geostatistical modeling framework to estimate the hypoxic extent in the northern Gulf of Mexico from data collected during midsummer, quasi-synoptic monitoring cruises (1985-2011). Instead of a traditional interpolation-based approach, we use a simulation-based approach that yields more robust extent estimates and quantified uncertainty. The modeling framework also makes use of covariate information (i.e., trend variables such as depth and spatial position), to reduce estimation uncertainty. Furthermore, adjustments are made to account for observational bias resulting from the use of different sampling instruments in different years. Our results suggest an increasing trend in hypoxic layer thickness (p = 0.05) from 1985 to 2011, but less than significant increases in volume (p = 0.12) and area (p = 0.42). The uncertainties in the extent estimates vary with sampling network coverage and instrument type, and generally decrease over the study period.
authors.affiliation: School of Natural Resources & Environment, University of Michigan , Ann Arbor, Michigan 48109-1041, United States. obenour@umich.edu
authors.forename: Daniel R
authors.initials: DR
authors.lastname: Obenour
authors.forename: Donald
authors.initials: D
authors.lastname: Scavia
authors.forename: Nancy N
authors.initials: NN
authors.lastname: Rabalais
authors.forename: R Eugene
authors.initials: RE
authors.lastname: Turner
authors.forename: Anna M
authors.initials: AM
authors.lastname: Michalak
mesh_terms: D000693:Anaerobiosis; D017753:Ecosystem; D060851:Gulf of America; D008962:Models, Theoretical; D009010:Monte Carlo Method; D010100:Oxygen / Q000032:analysis*; D012621:Seasons
chemical_list: D010100:Oxygen
references.citation: Environ Sci Technol. 2013 Jan 15;47(2):899-905
references.pmid: 23237424
references.citation: Mar Pollut Bull. 2006 Feb;52(2):139-48
references.pmid: 16212987
references.citation: Ecol Appl. 2009 Jul;19(5):1161-75
references.pmid: 19688924
references.citation: Mar Environ Res. 2005 Feb;59(1):65-77
references.pmid: 15325136
references.citation: Environ Sci Technol. 2005 Feb 1;39(3):716-23
references.pmid: 15757331
references.citation: Environ Sci Technol. 2008 Apr 1;42(7):2323-7
references.pmid: 18504960
references.citation: Environ Sci Technol. 2012 May 15;46(10):5489-96
references.pmid: 22506901
references.citation: Environ Sci Technol. 2007 Dec 1;41(23):8111-7
references.pmid: 18186345
references.citation: Mar Pollut Bull. 2012 Feb;64(2):319-24
references.pmid: 22153907
references.citation: Environ Sci Technol. 2010 Aug 1;44(15):5836-41
references.pmid: 20608722