Modeling biophysical controls on hypoxia in a shallow estuary using a Bayesian mechanistic approach

Katin, Alexey; Giudice, Dario Del; Obenour, Daniel R.

doi:10.1016/j.envsoft.2019.07.016

Cited by 14 publications

(22 citation statements)

References 81 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, SOD and WCOD primarily reflect the effects of N loadings over different time scales, similar to the representation of oxygen demands in Katin et al. (), rather than represent the exact depths at which oxygen consumption occurs. Finally, oxygen is replenished through exchanges with the surface layer, which is approximately saturated.…”

Section: Methodsmentioning

confidence: 89%

See 1 more Smart Citation

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

Giudice

Matli

Obenour

2019

Ecological Applications

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Section: Methodsmentioning

confidence: 89%

“…Interestingly, November–April riverine inputs have been shown to influence SOD in another hypoxic coastal system (Katin et al. ). Overall, considering nutrient loadings before November does not improve model performances further, which is also consistent with the regression results of MFO18.…”

Section: Resultsmentioning

confidence: 99%

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

Giudice

Matli

Obenour

2019

Ecological Applications

Self Cite

View full text Add to dashboard Cite

show abstract

“…Predictability of different HV metrics -Hypoxic extent metrics used for forecasts, scenarios, and reporting across several systems have often been estimates of summer maximum volume or area (e.g., Liu et al 2011;Scavia et al 2003Scavia et al , 2006Scavia et al , 2016Scavia et al , 2017Testa et al 2017a;Obenour et al 2012Obenour et al , 2015Rucinski et al 2016;Bocaniov and Scavia 2016;Zhang et al 2016; but see Katin et al 2019; Accepted Article Giudice et al 2020;Ross et al 2020). However, these maxima are not necessarily representative of year-long conditions.…”

Section: Discussionmentioning

confidence: 99%

“…While few monitoring programs have the resources needed for the intensive monitoring required to accurately capture metrics such as algal and oxygen dynamics, advances in three-dimensional ecological modeling, space-time geostatistical estimation, and their fusion provide sophisticated interpolations of limited survey data. For example, as computational power increased and threedimensional ecological models have become more sophisticated, they have been used to both provide insights into oxygen dynamics and integrate point estimates across time and space to generate continuous time series of hypoxia (Bever et al 2013;Fennel et al 2016;Katin et al 2019).…”

Section: Accepted Articlementioning

confidence: 99%

See 1 more Smart Citation

Advancing estuarine ecological forecasts: seasonal hypoxia in Chesapeake Bay

Scavia

Bertani

Testa

et al. 2021

Ecological Applications

View full text Add to dashboard Cite

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.

show abstract

Searching for Oxygen: Dynamic Movement Responses of Juvenile Spot (Leiostomus xanthurus) in an Intermittently Hypoxic Estuary

Craig

Huebert

Rose

et al. 2023

Estuaries and Coasts

View full text Add to dashboard Cite

Modeling biophysical controls on hypoxia in a shallow estuary using a Bayesian mechanistic approach

Cited by 14 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

Searching for Oxygen: Dynamic Movement Responses of Juvenile Spot (Leiostomus xanthurus) in an Intermittently Hypoxic Estuary

Contact Info

Product

Resources

About