20 research outputs found
Assessing the Causes and Severity of Gulf of Mexico Hypoxia Using Geostatistical and Mechanistic Modeling.
Hypoxia, typically defined by dissolved oxygen levels below 2 mg L-1, is an environmental problem common to many coastal systems. One particularly severe example of hypoxia is the large ‘dead zone’ that forms nearly every summer on the Louisiana-Texas shelf of the northern Gulf of Mexico. While there is considerable agreement about the primary causes of hypoxia, there remains substantial uncertainty regarding its spatial and temporal variability, such that it is difficult to predict how hypoxia will respond to management actions and other environmental changes. This research focuses on improving our understanding of Gulf hypoxia through three types of quantitative modeling. First, a geostatistical regression is developed to empirically model how water column stratification (a primary driver of hypoxia) affects bottom water dissolved oxygen (BWDO) concentrations, and to also infer the importance of other primary drivers, such as nutrient loading. Second, a geostatistical spatial estimation model is developed to simulate BWDO and hypoxic layer thickness across the Gulf shelf, providing estimates of hypoxic zone area and volume for a 27-year study period. Third, a mechanistic model, driven by nutrient loading, flow, and weather conditions is developed to predict hypoxic severity, as determined from the geostatistical model. As with all environmental models, the models developed in this dissertation are approximations of reality, tuned to limited observational and experimental information, such that they contain significant uncertainty. Because of this, all models are developed within statistical frameworks that quantify uncertainty and allow results to be presented as ranges of likely values. Overall, this works suggests there has been considerable variability in the mid-summer hypoxic extent over the last few decades, and this variability is explained, in large part, by both nutrient loading and oceanographic conditions (i.e., stratification). Relatively parsimonious models that account for these two main drivers explain at least 70% of the year-to-year variability in hypoxic area and mean BWDO. Also, this work indicates that over the past few decades, the Gulf has not become increasingly susceptible to hypoxia formation (independent of the biophysical drivers considered), at least in terms of hypoxic area and mean BWDO.PHDNatural Resources and Environment and Environmental EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/100085/1/obenour_1.pd
Assessing biophysical controls on Gulf of Mexico hypoxia through probabilistic modeling
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/116353/1/eap2015252492.pd
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Satellite-based Empirical Models Linking River Plume Dynamics with Hypoxic Area and Volume
Satellite-based empirical models explaining hypoxic area and volume variation were developed for the seasonally hypoxic (O2 \u3c 2 mg L−1) northern Gulf of Mexico adjacent to the Mississippi River. Annual variations in midsummer hypoxic area and volume were related to Moderate Resolution Imaging Spectroradiometer-derived monthly estimates of river plume area (km2) and average, inner shelf chlorophyll a concentration (Chl a, mg m−3). River plume area in June was negatively related with midsummer hypoxic area (km2) and volume (km3), while July inner shelf Chl a was positively related to hypoxic area and volume. Multiple regression models using river plume area and Chl a as independent variables accounted for most of the variability in hypoxic area (R2 = 0.92) or volume (R2 = 0.89). These models explain more variation in hypoxic area than models using Mississippi River nutrient loads as independent variables. The results here also support a hypothesis that confinement of the river plume to the inner shelf is an important mechanism controlling hypoxia area and volume in this region
Satellite-based Empirical Models Linking River Plume Dynamics with Hypoxic Area and Volume
Satellite-based empirical models explaining hypoxic area and volume variation were developed for the seasonally hypoxic (O2 \u3c 2 mg L−1) northern Gulf of Mexico adjacent to the Mississippi River. Annual variations in midsummer hypoxic area and volume were related to Moderate Resolution Imaging Spectroradiometer-derived monthly estimates of river plume area (km2) and average, inner shelf chlorophyll a concentration (Chl a, mg m−3). River plume area in June was negatively related with midsummer hypoxic area (km2) and volume (km3), while July inner shelf Chl a was positively related to hypoxic area and volume. Multiple regression models using river plume area and Chl a as independent variables accounted for most of the variability in hypoxic area (R2 = 0.92) or volume (R2 = 0.89). These models explain more variation in hypoxic area than models using Mississippi River nutrient loads as independent variables. The results here also support a hypothesis that confinement of the river plume to the inner shelf is an important mechanism controlling hypoxia area and volume in this region
Hypoxic volume is more responsive than hypoxic area to nutrient load reductions in the northern Gulf of Mexico—and it matters to fish and fisheries
While impacts of low oxygen on marine organisms have been reviewed from physiological and ecological perspectives, relating broad population- and ecosystem-level effects to the areal extent of hypoxia (dissolved oxygen concentration below 64 μ M, or 2 mg l ^−1 ) has proven difficult. We suggest that hypoxic volume is a more appropriate metric compared to hypoxic area because volume better integrates the effects of hypoxia on ecological processes relevant to many marine taxa. In this paper, we compare the volume-based load responses from a simple biophysical model with results from an independent three-dimensional hydrodynamic-biogeochemical model, and discuss the implications with respect to potentially more ecologically-relevant hypoxia management goals. We also show that hypoxic volume appears more sensitive than hypoxic area to nutrient load reductions. Model simulations indicate that even under a modest 25% nitrogen load reduction, the thickness of the hypoxic layer in the northern Gulf of Mexico decreases markedly, and hypoxia remains localized to a relatively thin layer near the bottom that most fish and other mobile organisms can more effectively avoid. This finding should be considered when reviewing and potentially setting hypoxia management goals
Quantifying the Impacts of Stratification and Nutrient Loading on Hypoxia in the Northern Gulf of Mexico
Stratification and nutrient loading are two primary factors
leading
to hypoxia in coastal systems. However, where these factors are temporally
correlated, it can be difficult to isolate and quantify their individual
impacts. This study provides a novel solution to this problem by determining
the effect of stratification based on its spatial relationship with
bottom-water dissolved oxygen (BWDO) concentration using a geostatistical
regression. Ten years (1998–2007) of midsummer Gulf of Mexico
BWDO measurements are modeled using stratification metrics along with
trends based on spatial coordinates and bathymetry, which together
explain 27–61% of the spatial variability in BWDO for individual
years. Because stratification effects explain only a portion of the
year-to-year variability in mean BWDO; the remaining variability is
explained by other factors, with May nitrate plus nitrite river concentration
the most important. Overall, 82% of the year-to-year variability in
mean BWDO is explained. The results suggest that while both stratification
and nutrients play important roles in determining the annual extent
of midsummer hypoxia, reducing nutrient inputs alone will substantially
reduce the average extent
Ensemble modeling informs hypoxia management in the northern Gulf of Mexico
A large region of low-dissolved-oxygen bottom waters (hypoxia) forms nearly every summer in the northern Gulf of Mexico because of nutrient inputs from theMississippi River Basin andwater column stratification. Policymakers developed goals to reduce the area of hypoxic extent because of its ecological, economic, and commercial fisheries impacts. However, the goals remain elusive after 30 y of research and monitoring and 15 y of goal-setting and assessment because there has been little change in river nitrogen concentrations. An intergovernmental Task Force recently extended to 2035 the deadline for achieving the goal of a 5,000-km(2) 5-y average hypoxic zone and set an interim load target of a 20% reduction of the spring nitrogen loading from the Mississippi River by 2025 as part of their adaptive management process. The Task Force has asked modelers to reassess the loading reduction required to achieve the 2035 goal and to determine the effect of the 20% interim load reduction. Here, we address both questions using a probabilistic ensemble of four substantially different hypoxia models. Our results indicate that, under typical weather conditions, a 59% reduction in Mississippi River nitrogen load is required to reduce hypoxic area to 5,000 km(2). The interim goal of a 20% load reduction is expected to produce an 18% reduction in hypoxic area over the long term. However, due to substantial interannual variability, a 25% load reduction is required before there is 95% certainty of observing any hypoxic area reduction between consecutive 5-y assessment periods
Retrospective Analysis of Midsummer Hypoxic Area and Volume in the Northern Gulf of Mexico, 1985–2011
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
(<i>p</i> = 0.05) from 1985 to 2011, but less than significant
increases in volume (<i>p</i> = 0.12) and area (<i>p</i> = 0.42). The uncertainties in the extent estimates vary
with sampling network coverage and instrument type, and generally
decrease over the study period
Spatial and Temporal Trends in Lake Erie Hypoxia, 1987–2007
Hypoxic conditions, defined as dissolved oxygen (DO)
concentrations
below 2 mg/L, are a regular summertime occurrence in Lake Erie, but
the spatial extent has been poorly understood due to sparse sampling.
We use geostatistical kriging and conditional realizations to provide
quantitative estimates of the extent of hypoxia in the central basin
of Lake Erie for August and September of 1987 to 2007, along with
their associated uncertainties. The applied geostatistical approach
combines the limited in situ DO measurements with auxiliary data selected
using the Bayesian Information Criterion. Bathymetry and longitude
are found to be highly significant in explaining the spatial distribution
of DO, while satellite observations of sea surface temperature and
satellite chlorophyll are not. The hypoxic extent was generally lowest
in the mid-1990s, with the late 1980s (1987, 1988) and the 2000s (2003,
2005) experiencing the largest hypoxic zones. A simple exponential
relationship based on the squared average measured bottom DO explains
97% of the estimated variability in the hypoxic extent. The change
in the observed maximum extent between August and September is found
to be sensitive to the corresponding variability in the hypolimnion
thickness