Advancing estuarine ecological forecasts: seasonal hypoxia in Chesapeake Bay.

Ecological forecasts are quantitative tools that can guide ecosystem management. The coemergence 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 data set 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.

The Chesapeake Bay Program Modeling System: Overview and Recommendations for Future Development.

The Chesapeake Bay is the largest, most productive, and most biologically diverse estuary in the continental United States providing crucial habitat and natural resources for culturally and economically important species. Pressures from human population growth and associated development and agricultural intensification have led to excessive nutrient and sediment inputs entering the Bay, negatively affecting the health of the Bay ecosystem and the economic services it provides. The Chesapeake Bay Program (CBP) is a unique program formally created in 1983 as a multi-stakeholder partnership to guide and foster restoration of the Chesapeake Bay and its watershed. Since its inception, the CBP Partnership has been developing, updating, and applying a complex linked modeling system of watershed, airshed, and estuary models as a planning tool to inform strategic management decisions and Bay restoration efforts. This paper provides a description of the 2017 CBP Modeling System and the higher trophic level models developed by the NOAA Chesapeake Bay Office, along with specific recommendations that emerged from a 2018 workshop designed to inform future model development. Recommendations highlight the need for simulation of watershed inputs, conditions, processes, and practices at higher resolution to provide improved information to guide local nutrient and sediment management plans. More explicit and extensive modeling of connectivity between watershed landforms and estuary sub-areas, estuarine hydrodynamics, watershed and estuarine water quality, the estuarine-watershed socioecological system, and living resources will be important to broaden and improve characterization of responses to targeted nutrient and sediment load reductions. Finally, the value and importance of maintaining effective collaborations among jurisdictional managers, scientists, modelers, support staff, and stakeholder communities is emphasized. An open collaborative and transparent process has been a key element of successes to date and is vitally important as the CBP Partnership moves forward with modeling system improvements that help stakeholders evolve new knowledge, improve management strategies, and better communicate outcomes.

Nitrogen reductions have decreased hypoxia in the Chesapeake Bay: Evidence from empirical and numerical modeling.

Seasonal hypoxia is a characteristic feature of the Chesapeake Bay due to anthropogenic nutrient input from agriculture and urbanization throughout the watershed. Although coordinated management efforts since 1985 have reduced nutrient inputs to the Bay, oxygen concentrations at depth in the summer still frequently fail to meet water quality standards that have been set to protect critical estuarine living resources. To quantify the impact of watershed nitrogen reductions on Bay hypoxia during a recent period including both average discharge and extremely wet years (2016-2019), this study employed both statistical and three-dimensional (3-D) numerical modeling analyses. Numerical model results suggest that if the nitrogen reductions since 1985 had not occurred, annual hypoxic volumes (O2 < 3 mg L-1) would have been ~50-120% greater during the average discharge years of 2016-2017 and ~20-50% greater during the wet years of 2018-2019. The effect was even greater for O2 < 1 mg L-1, where annual volumes would have been ~80-280% greater in 2016-2017 and ~30-100% greater in 2018-2019. These results were supported by statistical analysis of empirical data, though the magnitude of improvement due to nitrogen reductions was greater in the numerical modeling results than in the statistical analysis. This discrepancy is largely accounted for by warming in the Bay that has exacerbated hypoxia and offset roughly 6-34% of the improvement from nitrogen reductions. Although these results may reassure policymakers and stakeholders that their efforts to reduce hypoxia have improved ecosystem health in the Bay, they also indicate that greater reductions are needed to counteract the ever-increasing impacts of climate change.

Seabed Resuspension in the Chesapeake Bay: Implications for Biogeochemical Cycling and Hypoxia.

Sediment processes, including resuspension and transport, affect water quality in estuaries by altering light attenuation, primary productivity, and organic matter remineralization, which then influence oxygen and nitrogen dynamics. The relative importance of these processes on oxygen and nitrogen dynamics varies in space and time due to multiple factors and is difficult to measure, however, motivating a modeling approach to quantify how sediment resuspension and transport affect estuarine biogeochemistry. Results from a coupled hydrodynamic-sediment transport-biogeochemical model of the Chesapeake Bay for the summers of 2002 and 2003 showed that resuspension increased light attenuation, especially in the northernmost portion of the Bay, shifting primary production downstream. Resuspension also increased remineralization in the central Bay, which experienced larger organic matter concentrations due to the downstream shift in primary productivity and estuarine circulation. As a result, oxygen decreased and ammonium increased throughout the Bay in the bottom portion of the water column, due to reduced photosynthesis in the northernmost portion of the Bay and increased remineralization in the central Bay. Averaged over the channel, resuspension decreased oxygen by ~ 25% and increased ammonium by ~ 50% for the bottom water column. Changes due to resuspension were of the same order of magnitude as, and generally exceeded, short-term variations within individual summers, as well as interannual variability between 2002 and 2003, which were wet and dry years, respectively. Our results quantify the degree to which sediment resuspension and transport affect biogeochemistry, and provide insight into how coastal systems may respond to management efforts and environmental changes.

Effects of reduced shoreline erosion on Chesapeake Bay water clarity.

Shoreline erosion supplies sediments to estuaries and coastal waters, influencing water clarity and primary production. Globally, shoreline erosion sediment inputs are changing with anthropogenic alteration of coastlines in populated regions. Chesapeake Bay, a prime example of such a system where shoreline erosion accounts for a large proportion of sediments entering the estuary, serves here as a case study for investigating the effects of changing sediment inputs on water clarity. Long-term increases in shoreline armoring have contributed to decreased erosional sediment inputs to the estuary, changing the composition of suspended particles in surface waters. This study examined the impact of shoreline erosion on water clarity using a coupled hydrodynamic-biogeochemical model. Experiments were conducted to simulate realistic shoreline conditions representative of the early 2000s, increased shoreline erosion, and highly armored shorelines. Together, reduced shoreline erosion and the corresponding reduced rates of resuspension result in decreased concentrations of inorganic particles, improving water clarity particularly in the lower Bay and in dry years where and when riverine sediment influence is low. This clarity improvement relaxed light limitation, which increased organic matter production. Differences between the two extreme experiments revealed that in the mid-estuary in February to April, surface inorganic suspended sediment concentrations decreased 3-7 mg L-1, while organic suspended solids increased 1-3 mg L-1. The resulting increase in the organic-to-inorganic ratio often had opposite effects on clarity according to different metrics, improving clarity in mid-Bay central channel waters in terms of light attenuation depth, but simultaneously degrading clarity in terms of Secchi depth because the resulting increase in organic suspended solids decreased the water's transparency. This incongruous water clarity effect, the spatial extent of which is defined here as an Organic Fog Zone, was present in February to April in all years studied, but occurred farther south in wet years.

Challenges in Quantifying Air-Water Carbon Dioxide Flux Using Estuarine Water Quality Data: Case Study for Chesapeake Bay.

Estuaries play an uncertain but potentially important role in the global carbon cycle via CO2 outgassing. The uncertainty mainly stems from the paucity of studies that document the full spatial and temporal variability of estuarine surface water partial pressure of carbon dioxide ( pCO2). Here, we explore the potential of utilizing the abundance of pH data from historical water quality monitoring programs to fill the data void via a case study of the mainstem Chesapeake Bay (eastern United States). We calculate pCO2 and the air-water CO2 flux at monthly resolution from 1998 to 2018 from tidal fresh to polyhaline waters, paying special attention to the error estimation. The biggest error is due to the pH measurement error, and errors due to the gas transfer velocity, temporal sampling, the alkalinity mixing model, and the organic alkalinity estimation are 72%, 27%, 15%, and 5%, respectively, of the error due to pH. Seasonal, interannual, and spatial variability in the air-water flux and surface pCO2 is high, and a correlation analysis with oxygen reveals that this variability is driven largely by biological processes. Averaged over 1998-2018, the mainstem bay is a weak net source of CO2 to the atmosphere of 1.2 (1.1, 1.4) mol m-2 yr-1 (best estimate and 95% confidence interval). Our findings suggest that the abundance of historical pH measurements in estuaries around the globe should be mined in order to constrain the large spatial and temporal variability of the CO2 exchange between estuaries and the atmosphere.

Skill Assessment for Coupled Biological/Physical Models of Marine Systems.

Coupled biological/physical models of marine systems serve many purposes including the synthesis of information, hypothesis generation, and as a tool for numerical experimentation. However, marine system models are increasingly used for prediction to support high-stakes decision-making. In such applications it is imperative that a rigorous model skill assessment is conducted so that the model's capabilities are tested and understood. Herein, we review several metrics and approaches useful to evaluate model skill. The definition of skill and the determination of the skill level necessary for a given application is context specific and no single metric is likely to reveal all aspects of model skill. Thus, we recommend the use of several metrics, in concert, to provide a more thorough appraisal. The routine application and presentation of rigorous skill assessment metrics will also serve the broader interests of the modeling community, ultimately resulting in improved forecasting abilities as well as helping us recognize our limitations.

Dermal mycobacteriosis and warming sea surface temperatures are associated with elevated mortality of striped bass in Chesapeake Bay.

Temperature is hypothesized to alter disease dynamics, particularly when species are living at or near their thermal limits. When disease occurs in marine systems, this can go undetected, particularly if the disease is chronic and progresses slowly. As a result, population-level impacts of diseases can be grossly underestimated. Complex migratory patterns, stochasticity in recruitment, and data and knowledge gaps can hinder collection and analysis of data on marine diseases. New tools enabling quantification of disease impacts in marine environments include coupled biogeochemical hydrodynamic models (to hindcast key environmental data), and multievent, multistate mark-recapture (MMSMR) (to quantify the effects of environmental conditions on disease processes and assess population-level impacts). We used MMSMR to quantify disease processes and population impacts in an estuarine population of striped bass (Morone saxatilis) in Chesapeake Bay from 2005 to 2013. Our results supported the hypothesis that mycobacteriosis is chronic, progressive, and, frequently, lethal. Yearly disease incidence in fish age three and above was 89%, suggesting that this disease impacts nearly every adult striped bass. Mortality of diseased fish was high, particularly in severe cases, where it approached 80% in typical years. Severely diseased fish also had a 10-fold higher catchability than healthy fish, which could bias estimates of disease prevalence. For both healthy and diseased fish, mortality increased with the modeled average summer sea surface temperature (SST) at the mouth of the Rappahannock River; in warmer summers (average SST ≥ 29°C), a cohort is predicted to experience >90% mortality in 1 year. Regression of disease signs in mildly and moderately diseased fish was <2%. These results suggest that these fish are living at their maximum thermal tolerance and that this is driving increased disease and mortality. Management of this fishery should account for the effects of temperature and disease on impacted populations.

Dissolved organic carbon fluxes in the Middle Atlantic Bight: An integrated approach based on satellite data and ocean model products.

Continental margins play an important role in global carbon cycle, accounting for 15-21% of the global marine primary production. Since carbon fluxes across continental margins from land to the open ocean are not well constrained, we undertook a study to develop satellite algorithms to retrieve dissolved organic carbon (DOC) and combined these satellite data with physical circulation model products to quantify the shelf boundary fluxes of DOC for the U.S. Middle Atlantic Bight (MAB). Satellite DOC was computed through seasonal relationships of DOC with colored dissolved organic matter absorption coefficients, which were derived from an extensive set of in situ measurements. The multiyear time series of satellite-derived DOC stocks (4.9 Teragrams C; Tg) shows that freshwater discharge influences the magnitude and seasonal variability of DOC on the continental shelf. For the 2010-2012 period studied, the average total estuarine export of DOC into the MAB shelf is 0.77 Tg C yr-1 (year). The integrated DOC tracer fluxes across the shelf boundaries are 12.1 Tg C yr-1 entering the MAB from the southwest alongshore boundary, 18.5 Tg C yr-1 entering the MAB from the northeast alongshore boundary, and 29.0 Tg C yr-1 flowing out of the MAB across the entire length of the 100 m isobath. The magnitude of the cross-shelf DOC flux is quite variable in time (monthly) and space (north to south). The highly dynamic exchange of water along the shelf boundaries regulates the DOC budget of the MAB at subseasonal time scales.

Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models.

The relative skill of 21 regional and global biogeochemical models was assessed in terms of how well the models reproduced observed net primary productivity (NPP) and environmental variables such as nitrate concentration (NO3), mixed layer depth (MLD), euphotic layer depth (Zeu), and sea ice concentration, by comparing results against a newly updated, quality-controlled in situ NPP database for the Arctic Ocean (1959-2011). The models broadly captured the spatial features of integrated NPP (iNPP) on a pan-Arctic scale. Most models underestimated iNPP by varying degrees in spite of overestimating surface NO3, MLD, and Zeu throughout the regions. Among the models, iNPP exhibited little difference over sea ice condition (ice-free versus ice-influenced) and bottom depth (shelf versus deep ocean). The models performed relatively well for the most recent decade and toward the end of Arctic summer. In the Barents and Greenland Seas, regional model skill of surface NO3 was best associated with how well MLD was reproduced. Regionally, iNPP was relatively well simulated in the Beaufort Sea and the central Arctic Basin, where in situ NPP is low and nutrients are mostly depleted. Models performed less well at simulating iNPP in the Greenland and Chukchi Seas, despite the higher model skill in MLD and sea ice concentration, respectively. iNPP model skill was constrained by different factors in different Arctic Ocean regions. Our study suggests that better parameterization of biological and ecological microbial rates (phytoplankton growth and zooplankton grazing) are needed for improved Arctic Ocean biogeochemical modeling.

Chesapeake Bay nitrogen fluxes derived from a land-estuarine ocean biogeochemical modeling system: Model description, evaluation, and nitrogen budgets.

The Chesapeake Bay plays an important role in transforming riverine nutrients before they are exported to the adjacent continental shelf. Although the mean nitrogen budget of the Chesapeake Bay has been previously estimated from observations, uncertainties associated with interannually varying hydrological conditions remain. In this study, a land-estuarine-ocean biogeochemical modeling system is developed to quantify Chesapeake riverine nitrogen inputs, within-estuary nitrogen transformation processes and the ultimate export of nitrogen to the coastal ocean. Model skill was evaluated using extensive in situ and satellite-derived data, and a simulation using environmental conditions for 2001-2005 was conducted to quantify the Chesapeake Bay nitrogen budget. The 5 year simulation was characterized by large riverine inputs of nitrogen (154 × 109 g N yr-1) split roughly 60:40 between inorganic:organic components. Much of this was denitrified (34 × 109 g N yr-1) and buried (46 × 109 g N yr-1) within the estuarine system. A positive net annual ecosystem production for the bay further contributed to a large advective export of organic nitrogen to the shelf (91 × 109 g N yr-1) and negligible inorganic nitrogen export. Interannual variability was strong, particularly for the riverine nitrogen fluxes. In years with higher than average riverine nitrogen inputs, most of this excess nitrogen (50-60%) was exported from the bay as organic nitrogen, with the remaining split between burial, denitrification, and inorganic export to the coastal ocean. In comparison to previous simulations using generic shelf biogeochemical model formulations inside the estuary, the estuarine biogeochemical model described here produced more realistic and significantly greater exports of organic nitrogen and lower exports of inorganic nitrogen to the shelf.

An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models.

We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters.

Modeling the dynamics of continental shelf carbon.

Continental margin systems are important contributors to global nutrient and carbon budgets. Effort is needed to quantify this contribution and how it will be modified under changing patterns of climate and land use. Coupled models will be used to provide projections of future states of continental margin systems. Thus, it is appropriate to consider the limitations that impede the development of realistic models. Here, we provide an overview of the current state of modeling carbon cycling on continental margins as well as the processes and issues that provide the next challenges to such models. Our overview is done within the context of a coupled circulation-biogeochemical model developed for the northeastern North American continental shelf region. Particular choices of forcing and initial fields and process parameterizations are used to illustrate the consequences for simulated distributions, as revealed by comparisons to observations using quantitative statistical metrics.