Space-Time Geostatistical Assessment of Hypoxia in the Northern Gulf of Mexico

Matli, Venkata Rohith Reddy; Fang, Shiqi; Guinness, Joseph; Rabalais, Nancy N.; Craig, J. Kevin; Obenour, Daniel R.

doi:10.1021/acs.est.8b03474

Cited by 22 publications

(69 citation statements)

References 81 publications

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“…Instead, we find that, from 1968 to 1979, summertime HA ranged from 5,900 (lowest HA) to 17,400 km 2 (88th percentile of HA, 1985HA, -2016, which is comparable to the estimates of Scavia and Donnelly (2007) and Greene et al (2009). When compared to all previous hindcasting studies, the model applied here benefits from a longer and more accurate calibration data set (Matli et al 2018). Longer calibration spanning a variety of conditions is likely to generate more representative model parameters (Del Giudice et al 2018a).…”

Section: Oxygen Demand Apportionment and Multi-annual Trendsmentioning

confidence: 47%

“…When compared to all previous hindcasting studies, the model applied here benefits from a longer and more accurate calibration data set (Matli et al. ). Longer calibration spanning a variety of conditions is likely to generate more representative model parameters (Del Giudice et al.…”

Section: Resultsmentioning

confidence: 99%

“…, Matli et al. ). The shelf is divided into east and west sections relative to the Atchafalaya River outflow (), as these regions can have different bottom‐water dissolved oxygen (BWDO) dynamics (Obenour et al.…”

Section: Methodsmentioning

confidence: 99%

“…Parsimonious models fall within the modeling spectrum ranging from simple regressions (Greene et al 2009, Le et al 2016, Del Giudice et al 2018b) to high-resolution hydrodynamic-biogeochemical models (Meier et al 2011, Fennel et al 2016, and have been successfully employed to understand and predict eutrophicationrelated phenomena in the Gulf (Justi c et al 1996, Scavia and Donnelly 2007, Obenour et al 2015 and other aquatic systems (Rucinski et al 2010, Chapra et al 2016. Also, we leverage new, geostatistically derived estimates of Gulf dissolved oxygen from Matli et al (2018) hereafter referred to as MFO18. Compared to previous Gulf studies focusing only on mid-summer hypoxic conditions (Greene et al 2009, Forrest et al 2011, Obenour et al 2015, these new estimates allow for calibration and prediction of hypoxia over the entire summer.…”

Section: Models Of Intermediatementioning

confidence: 99%

“…Finally, pðy e jO b ð0Þ; r e ð0ÞÞpðy w jO b ð0Þ; r w ð0ÞÞ is the likelihood function, which represents the probability that the measured BWDO is generated by the biophysical-Bayesian model. Here, r e ð0Þ and r w ð0Þ are standard deviations for the two shelf sections, which combine r m,e and r m,w , model structural uncertainty from 2 ð0Þ, and measurement uncertainty specified by the geostatistical model (Matli et al 2018).…”

Section: Inference and Predictionsmentioning

confidence: 99%

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Bayesian mechanistic modeling characterizes Gulf of Mexico hypoxia: 1968–2016 and future scenarios

Giudice

Matli

Obenour

2019

Ecological Applications

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The hypoxic zone in the northern Gulf of Mexico is among the most dramatic examples of impairments to aquatic ecosystems. Despite having attracted substantial attention, management of this environmental crisis remains challenging, partially due to limited monitoring to support model development and long‐term assessments. Here, we leverage new geostatistical estimates of hypoxia derived from nearly 150 monitoring cruises and a process‐based model to improve characterization of controlling mechanisms, historic trends, and future responses of hypoxia while rigorously quantifying uncertainty in a Bayesian framework. We find that November–March nitrogen loads are important controls of sediment oxygen demand, which appears to be the major oxygen sink. In comparison, only ~23% of oxygen in the near‐bottom region appears to be consumed by net water column respiration, which is driven by spring and summer loads. Hypoxia typically exceeds 15,600 km2 in June, peaks in July, and declines below 10,000 km2 in September. In contrast to some previous Gulf hindcasting studies, our simulations demonstrate that hypoxia was both severe and worsening prior to 1985, and has remained relatively stable since that time. Scenario analysis shows that halving nutrient loadings will reduce hypoxia by 37% with respect to 13,900 km2 (1985–2016 median), while a +2°C change in water temperature will cause a 26% hypoxic area increase due to enhanced sediment respiration and reduced oxygen solubility. These new results highlight the challenges of achieving hypoxia reduction targets, particularly under warming conditions, and should be considered in ecosystem management.

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Section: Oxygen Demand Apportionment and Multi-annual Trendsmentioning

confidence: 47%

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Models Of Intermediatementioning

confidence: 99%

Section: Inference and Predictionsmentioning

confidence: 99%

See 3 more Smart Citations

Bayesian mechanistic modeling characterizes Gulf of Mexico hypoxia: 1968–2016 and future scenarios

Giudice

Matli

Obenour

2019

Ecological Applications

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Advancing estuarine ecological forecasts: seasonal hypoxia in Chesapeake Bay

Scavia

Bertani

Testa

et al. 2021

Ecological Applications

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Ecological forecasts are quantitative tools that can guide ecosystem management. The co-emergence of extensive environmental monitoring and quantitative frameworks allows for widespread development and continued improvement of ecological forecasting systems. We use a relatively simple estuarine hypoxia model to demonstrate advances in addressing some of the most critical challenges and opportunities of contemporary ecological forecasting, including predictive accuracy, uncertainty characterization, and management relevance. We explore the impacts of different combinations of forecast metrics, drivers, and driver time windows on predictive performance. We also incorporate multiple sets of state-variable observations from different sources and separately quantify model prediction error and measurement uncertainty through a flexible Bayesian hierarchical framework. Results illustrate the benefits of 1) adopting forecast metrics and drivers that strike an optimal balance between predictability and relevance to management, 2) incorporating multiple data sources in the calibration dataset to separate and propagate different sources of uncertainty, and 3) using the model in scenario mode to probabilistically evaluate the effects of alternative management decisions on future ecosystem state. In the Chesapeake Bay, the subject of this case study, we find that average summer or total annual hypoxia metrics are more predictable than monthly metrics and that measurement error represents an important source of uncertainty. Application of the model in scenario mode suggests that absent watershed management actions over the past decades, long-term average hypoxia would have increased by 7% compared to 1985. Conversely, the model projects that if management goals currently in place to restore the Bay are met, long-term average hypoxia would eventually decrease by 32% with respect to the mid-1980s.

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Stoichiometry of nitrogen, phosphorus, and silica loads in the Mississippi‐Atchafalaya River basin reveals spatial and temporal patterns in risk for cyanobacterial blooms

Royer

2019

Limnology & Oceanography

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Ratios of nitrogen (N), phosphorus (P), and dissolved silica (DSi) influence how algal communities respond to nutrient loading, and DSi limitation can facilitate cyanobacterial dominance. The indicator of coastal eutrophication potential (ICEP), described previously by other researchers, predicts production by diatoms vs. nonsiliceous taxa based on deviation of nutrient loads from the Redfield ratio of 106C:16 N:20Si (N‐ICEP) or 106C:1P:20Si (P‐ICEP). The ICEP was calculated for the Mississippi‐Atchafalaya River basin, and four subbasins: the Ohio‐Tennessee, Missouri, Upper Mississippi, and Arkansas‐Red basins from 1979 to 2015. The P‐ICEP indicated a stoichiometric imbalance that favored cyanobacteria for all but the Arkansas‐Red subbasin. The N‐ICEP indicated conditions favorable for cyanobacteria in the Upper Mississippi, Ohio‐Tennessee, and the northern Gulf of Mexico. Agriculture is the predominant land use in the Upper Mississippi and Ohio‐Tennessee subbasins and these subbasins controlled the stoichiometry of the nutrients delivered to the northern Gulf of Mexico. The imbalance in N, P, and DSi inputs to the Gulf was greatest during spring and early summer, and in most years transitioned to favoring diatoms by August or September. Comparing the 1980–1994 and 2001–2015 periods, there was a significant increase in the P‐ICEP for the Upper Mississippi, Ohio‐Tennessee, and Missouri subbasins that appeared to arise mainly from increased P loading to surface waters in the those basins. The ICEP revealed patterns in stoichiometry of N, P, and DSi loads among the major tributaries to the Mississippi River, and an increasing risk of cyanobacterial blooms for inland waters in much of the Mississippi‐Atchafalaya River basin.

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Space-Time Geostatistical Assessment of Hypoxia in the Northern Gulf of Mexico

Cited by 22 publications

References 81 publications

Bayesian mechanistic modeling characterizes Gulf of Mexico hypoxia: 1968–2016 and future scenarios

Bayesian mechanistic modeling characterizes Gulf of Mexico hypoxia: 1968–2016 and future scenarios

Advancing estuarine ecological forecasts: seasonal hypoxia in Chesapeake Bay

Stoichiometry of nitrogen, phosphorus, and silica loads in the Mississippi‐Atchafalaya River basin reveals spatial and temporal patterns in risk for cyanobacterial blooms

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