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Climate change can alter marine ecosystems through changes in ocean temperature, acidification, circulation, and productivity. Over the last decade, the United States northeast continental shelf (U.S. NES) has warmed faster than any other marine ecosystem in the country and is among the fastest warming regions of the global ocean. Many living marine resources in the U.S. NES ranging from recreational and commercial fish stocks to protected species have shifted their distribution in response to ocean warming. The National Oceanic and Atmospheric Administration’s National Marine Fisheries Service (NOAA Fisheries) is responsible for the assessment, protection, and sustainable use of the nation’s living marine resources. In the U.S. NES, NOAA Fisheries has made substantial progress on climate research related to fish, fisheries, and protected species. However, more research is needed to help inform tactical management decisions with the goal of climate-ready living marine resource management. This is a major challenge because the observed physical and biological changes are unprecedented, and the majority of marine species assessments and management decisions do not utilize environmental data. Here we review the research accomplishments and key needs for NOAA Fisheries in the U.S. NES in the context of climate change and living marine resource management. Key research needs and products are: 1) Infrastructure with continued and enhanced ocean surveys that includes cooperative research with the fishing industry and other NOAA line offices and partners; 2) Tracking and projecting change, and understanding mechanisms including state of the ecosystem reporting, improved regional ocean and ecosystem hindcasts, forecasts, and projections, and continued process-based laboratory and field studies, 3) climate-informed management, including stock assessments that account for climate where possible, translation of changing species distributions into spatial management, climate vulnerability assessment and scenario planning, ecosystem-based management, management strategy evaluations, and increased multidisciplinary science that includes economic and social indicators.
Eutrophication and hypoxia represent an ever-growing stressor to estuaries and coastal ecosystems due to population growth and climate change. Understanding water quality dynamics in shallow water systems is particularly challenging due to the complex physical and biogeochemical dynamics and interactions among them. Within shallow waters, benthic microalgae can significantly contribute to autotrophic primary production, generate organic matter, increase dissolved oxygen consumption, and alter nutrient fluxes at the sediment–water interface, yet they have received little attention in modeling applications. A state-of-the-art modeling system, the Semi-Implicit Cross-Scale Hydroscience Integrated System Model (SCHISM), coupled with the Integrated Compartment Model (ICM) of water quality and benthic microalgae, has been implemented in the Corsica River estuary, a tributary to Chesapeake Bay, to study benthic microalgal impact on water quality in shallow water systems. The model simulation has revealed a broad impact of benthic microalgae, ranging from sediment–water interface fluxes to water column dynamics, and the effects are observed from near-field to far-field monitoring stations. High-frequency variability and non-linearity dominate benthic microalgal dynamics, sediment oxygen demand, and nutrient fluxes at the sediment–water interface. Resource competition and supply determine the spatial scope of benthic microalgal impacts on far-field stations and the whole estuary system. Our study shows that benthic microalgae are a significant factor in shallow water dynamics that needs adequate attention in future observation and modeling applications.
The 2010 Chesapeake Bay Total Maximum Daily Load was established for the water quality and ecological restoration of the Chesapeake Bay. In 2017, the latest science, data, and modeling tools were used to develop revised Watershed Implementation Plans (WIPs). In this article, we examine the vulnerability of the Chesapeake Bay watershed to the combined pressures of climate change and growth in population, agricultural intensity, and economic activity for the 60‐year period 1995–2055. The results will be used to revise WIPs, as needed, to account for expected increases in loads. Assessing changes relative to 1995 for the years 2025, 2035, 2045, and 2055, mean annual precipitation increases of 3.11%, 4.21%, 5.34%, and 6.91%, respectively, air temperature increases of 1.12, 1.45, 1.84, and 2.12°C, respectively, and potential evapotranspiration increases of 3.36%, 4.43%, 5.54%, and 6.35%, respectively, are projected. Population in the watershed is expected to grow by 3.5 million between 2025 and 2055. Watershed model results show incremental increases in streamflow (2.3%–6.2%), nitrogen (2.6%–10.8%), phosphorus (4.5%–26.7%), and sediment (3.8%–18.8%) loads to the tidal Bay due to climate change. Growth in population, agricultural intensity, development, and economic activity resulted in relatively smaller increases in loads compared to climate change.
Innovization is a task for analyzing multiple Pareto-optimal solutions obtained by an evolutionary multi-objective optimization (EMO) algorithm to extract common features in the decision variables, leading to design rules or solution principles. The principles derived from innovized principles can provide valuable insights to the users about “how to create an optimal solution?”. Manual or automated machine learning-based innovization methods were proposed in the literature to extract innovized principles in a problem. Although different problems may demand different structures of the rules, the innovized rules can also be utilized to improve the performance of the subsequent iterations of the optimization algorithm or help in executing an efficient re-optimization of the same problem. In this paper, we consider a large-scale and multi-objective complex optimization task of minimizing cost and nitrogen loading in certain counties within the Chesapeake Bay Watershed (CBW) and find multiple trade-off solutions using the NSGA-III approach applied to the CBW's real evaluator tool (The Chesapeake Assessment Scenario Tool–CAST). 205 Best Management Practices (BMPs) are considered to be implemented at each land-river segment within a county, leading to as many as 65,260 variables for the resulting multi-objective optimization procedure. First, hundreds of trade-off solutions found by the CAST-NSGA-III procedure are analyzed manually to find the top-most BMPs used in them. After that, a re-optimization of CAST-NSGA-III is run with a few critical BMPs (resulting in a decrease of the variable to a range between 3% and 33%) found to commonly appear in the trade-off solution set of the previous runs. Interestingly, the resulting trade-off front with reduced BMPs is similar to the original run achieved with tens of thousands of variables. The findings are intriguing and demonstrate the efficacy of innovation in addressing intricate, real-world issues at a significant scale.
Understanding shallow water biogeochemical dynamics is a challenge in coastal regions, due to the presence of highly variable land-water interface fluxes, tight coupling with sediment processes, tidal dynamics, and diurnal variability in biogeochemical processes. While the deployment of continuous monitoring devices has improved our understanding of high-frequency (12 - 24 hours) variability and spatial heterogeneity in shallow regions, mechanistic modeling of these dynamics has lagged behind conceptual and empirical models. The inherent complexity of shallow water systems is represented in the Corsica River estuary, a small basin within the Chesapeake Bay ecosystem, where abundant monitoring data have been collected from long-term monitoring stations, continuous monitoring sensors, synoptic sensor surveys, and measurements of sediment-water fluxes. A state-of-the-art modeling system, the Semi-implicit Cross-scale Hydroscience Integrated System Model (SCHISM), was applied to the Corsica domain with a high-resolution grid and nutrient loads from the most recent version of the Chesapeake Bay watershed model. The Corsica SCHISM model reproduced observed high-frequency variability in dissolved oxygen, as well as seasonal variability in chlorophyll-a and sediment-water fluxes. Time-series signal analyses using Empirical Model Decomposition and spectral analysis revealed that the diurnal and M2 tide frequencies are the dominant high-frequency modes and physical transport contributes a larger share to dissolved oxygen budgets than biogeochemical processes on an hourly time scale. Heterogeneity and patchiness in dissolved oxygen resulting from phytoplankton distributions and geometry-driven eddies amplify the physical transport effect, and on longer time scales oxygen is controlled more by photosynthesis and respiration. Our simulation demonstrates that interactions among physical and biological dynamics generate complex high-frequency variability in water quality and non-linear reposes to nutrient loading and environmental forcing in shallow water systems.
