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A key control on the magnitude of coastal eutrophication is the degree to which currents quickly transport nitrogen derived from human sources away from the coast to the open ocean before eutrophication develops. In the Southern California Bight (SCB), an upwelling-dominated eastern boundary current ecosystem, anthropogenic nitrogen inputs increase algal productivity and cause subsurface acidification and oxygen (O 2 ) loss along the coast. However, the extent of anthropogenic influence on eutrophication beyond the coastal band, and the physical transport mechanisms and biogeochemical processes responsible for these effects are still poorly understood. Here, we use a submesoscale-resolving numerical model to document the detailed biogeochemical mass balance of nitrogen, carbon and oxygen, their physical transport, and effects on offshore habitats. Despite management of terrestrial nutrients that has occurred in the region over the last 20 years, coastal eutrophication continues to persist. The input of anthropogenic nutrients promote an increase in productivity, remineralization and respiration offshore, with recurrent O 2 loss and pH decline in a region located 30-90 km from the mainland. During 2013 to 2017, the spatially averaged 5-year loss rate across the Bight was 1.3 mmol m -3 O 2 , with some locations losing on average up to 14.2 mmol m -3 O 2 . The magnitude of loss is greater than model uncertainty assessed from data-model comparisons and from quantification of intrinsic variability. This phenomenon persists for 4 to 6 months of the year over an area of 278,40 km 2 ( ∼ 30% of SCB area). These recurrent features of acidification and oxygen loss are associated with cross-shore transport of nutrients by eddies and plankton biomass and their accumulation and retention within persistent eddies offshore within the SCB.

Climate change is increasing drought severity worldwide. Ocean discharges of municipal wastewater are a target for potable water recycling. Potable water recycling would reduce wastewater volume; however, the effect on mass nitrogen loading is dependent on treatment. In cases where nitrogen mass loading is not altered or altered minimally, this practice has the potential to influence spatial patterns in coastal eutrophication. We apply a physical-biogeochemical numerical ocean model to understand the influence of nitrogen management and potable wastewater recycling on net primary productivity (NPP), pH, and oxygen. We model several theoretical management scenarios by combining dissolved inorganic nitrogen (DIN) reductions from 50 to 85% and recycling from 0 to 90%, applied to 19 generalized wastewater outfalls in the Southern California Bight. Under no recycling, NPP, acidification, and oxygen loss decline with DIN reductions, which simulated habitat volume expansion for pelagic calcifiers and aerobic taxa. Recycling scenarios under intermediate DIN reduction show patchier areas of pH and oxygen loss with steeper vertical declines relative to a no recycling scenario. These patches are diminished under 85% DIN reduction across all recycling levels, suggesting nitrogen management lowers eutrophication risk even with concentrated discharges. These findings represent a novel application of ocean numerical models to investigate the regional effects of idealized outfall management on eutrophication. Additional work is needed to investigate more realistic outfall-specific water recycling and nutrient management scenarios and to contextualize the benefit of these management actions, given accelerating acidification and hypoxia from climate change.

Pseudo-nitzschia species with the ability to produce the neurotoxin domoic acid (DA) are the main cause of harmful algal blooms (HABs) along the U.S. West Coast, with major impacts on ecosystems, fisheries, and human health. While most Pseudo-nitzschia (PN) HAB studies to date have focused on their characteristics at specific sites, few cross-regional comparisons exist, and mechanistic understanding of large-scale HAB drivers remains incomplete. To close these gaps, we compiled a nearly 20-year time series of in situ particulate DA and environmental observations to characterize similarities and differences in PN HAB drivers along the California coast. We focus on three DA hotspots with the greatest data density: Monterey Bay, the Santa Barbara Channel, and the San Pedro Channel. Coastwise, DA outbreaks are strongly correlated with upwelling, chlorophyll-a, and silicic acid limitation relative to other nutrients. Clear differences also exist across the three regions, with contrasting responses to climate regimes across a north to south gradient. In Monterey Bay, PN HAB frequency and intensity increase under relatively nutrient-poor conditions during anomalously low upwelling intensities. In contrast, in the Santa Barbara and San Pedro Channels, PN HABs are favored under cold, nitrogen-rich conditions during more intense upwelling. These emerging patterns provide insights on ecological drivers of PN HABs that are consistent across regions and support the development of predictive capabilities for DA outbreaks along the California coast and beyond.

Abstract: The Santa Barbara Channel is one of the most productive regions of the California Current System. Yet, the physical processes that sustain this high productivity remain unclear. We use a high‐resolution physical‐biogeochemical model to show that submesoscale eddies generated by islands are energized by orographic effects on the wind, with significant impacts on nutrient, carbon, and oxygen cycles. These eddies are modulated by two co‐occurring air‐sea‐land interactions: transfer of wind energy to ocean currents that intensifies ocean eddies, and a wind‐current feedback that tends to dampen them. Here we show that the dampening is overwhelmed by fine scale wind patterns induced by the presence of surrounding capes and islands. The fine‐scale winds cause an additional transfer of momentum from the atmosphere to the ocean that energizes submesoscale eddies. This drives upward doming of isopycnals in the center of the channel, allowing a more efficient injection of nutrients to the surface, and triggering intense phytoplankton blooms that nearly double productivity relative to the case without fine‐scale winds. The intensification of the doming effect by the wind‐curl and submesoscale eddies pumps deep low oxygen, acidic waters to the center of the cyclonic eddies. These eddies are then transported away from the Channel into the California Current, where they impact a wider area along the central coast, with potential ecological consequences. Our study highlights the important role of air‐sea‐land interactions in modulating coastal processes, and suggests that submesoscale resolving models are required to correctly represent coastal processes and their ecological impacts.

Pseudo-nitzschia species are one of the leading causes of harmful algal blooms (HABs) along the western coast of the United States. Approximately half of known Pseudo-nitzschia strains can produce domoic acid (DA), a neurotoxin that can negatively impact wildlife and fisheries and put human life at risk through amnesic shellfish poisoning. Production and accumulation of DA, a secondary metabolite synthesized during periods of low primary metabolism, is triggered by environmental stressors such as nutrient limitation. To quantify and estimate the feedbacks between DA production and environmental conditions, we designed a simple mechanistic model of Pseudo-nitzschia and domoic acid dynamics, which we validate against batch and chemostat experiments. Our results suggest that, as nutrients other than nitrogen (i.e., silicon, phosphorus, and potentially iron) become limiting, DA production increases. Under Si limitation, we found an approximate doubling in DA production relative to N limitation. Additionally, our model indicates a positive relationship between light and DA production. These results support the idea that the relationship with nutrient limitation and light is based on direct impacts on Pseudo-nitzschia biosynthesis and biomass accumulation. Because it can easily be embedded within existing coupled physical-ecosystem models, our model represents a step forward toward modeling the occurrence of Pseudo-nitzschia HABs and DA across the U.S. West Coast.

Pelagic fish communities are shaped by bottom-up and top-down processes, transport by currents, and active swimming. However, the interaction of these processes remains poorly understood. Here, we use a regional implementation of the APex ECOSystem Model (APECOSM), a mechanistic model of the pelagic food web, to investigate these processes in the California Current, a highly productive upwelling system characterized by vigorous mesoscale circulation. The model is coupled with an eddy-resolving representation of ocean currents and lower trophic levels, and is tuned to reproduce observed fish biomass from fisheries independent trawls. Several emergent properties of the model compare realistically with observations. First, the epipelagic community accounts for one order of magnitude less biomass than the vertically migratory community, and is composed by smaller species. Second, the abundance of small fish decreases from the coast to the open ocean, while the abundance of large fish remains relatively uniform. This in turn leads to flattening of biomass size-spectra away from the coast for both communities. Third, the model reproduces a cross-shore succession of small to large sizes moving offshore, consistent with observations of species occurrence. These cross-shore variations emerge in the model from a combination of: (1) passive offshore advection by the mean current, (2) active swimming toward coastal productive regions to counterbalance this transport, and (3) mesoscale heterogeneity that reduces the ability of organisms to return to coastal waters. Our results highlight the importance of passive and active movement in structuring the pelagic food web, and suggest that a representation of these processes can help to improve the realism in simulations with marine ecosystem models.

[Figure: see text].

Global change is leading to warming, acidification, and oxygen loss in the ocean. In the Southern California Bight, an eastern boundary upwelling system, these stressors are exacerbated by the localized discharge of anthropogenically enhanced nutrients from a coastal population of 23 million people. Here, we use simulations with a high-resolution, physical-biogeochemical model to quantify the link between terrestrial and atmospheric nutrients, organic matter, and carbon inputs and biogeochemical change in the coastal waters of the Southern California Bight. The model is forced by large-scale climatic drivers and a reconstruction of local inputs via rivers, wastewater outfalls, and atmospheric deposition; it captures the fine scales of ocean circulation along the shelf; and it is validated against a large collection of physical and biogeochemical observations. Local land-based and atmospheric inputs, enhanced by anthropogenic sources, drive a 79% increase in phytoplankton biomass, a 23% increase in primary production, and a nearly 44% increase in subsurface respiration rates along the coast in summer, reshaping the biogeochemistry of the Southern California Bight. Seasonal reductions in subsurface oxygen, pH, and aragonite saturation state, by up to 50 mmol m-3, 0.09, and 0.47, respectively, rival or exceed the global open-ocean oxygen loss and acidification since the preindustrial period. The biological effects of these changes on local fisheries, proliferation of harmful algal blooms, water clarity, and submerged aquatic vegetation have yet to be fully explored.

The Southern California Bight (SCB) is an upwelling-dominated, open embayment on the U.S. West Coast and receives discharges of anthropogenically-enhanced freshwater, nutrients, carbon, and other materials. These inputs include direct point sources discharged from wastewater treatment (WWT) plants via ocean outfalls and point, non-point, and natural sources discharged via coastal rivers. We assembled a daily time series over 1971-2017 of discharges from large WWT plants ≥ 50 million gallon per day (MGD) and 1997-2017 from small WWT plants and coastal rivers. Constituents include nitrogen, phosphorus, organic carbon, alkalinity, iron, and silica. Data from research studies, several government and non-government agency databases containing discharge monitoring reports, river flow gauges, and other collateral information were compiled to produce this dataset. Predictive models and expert analysis addressed unmonitored sources and data gaps. The time series of terrestrial discharge and fluxes are provided with location of coastal discharge point or tributary. The data are deposited in a repository found in Sutula et al. [1].

Projections of climate change impacts on marine ecosystems have revealed long-term declines in global marine animal biomass and unevenly distributed impacts on fisheries. Here we apply an enhanced suite of global marine ecosystem models from the Fisheries and Marine Ecosystem Model Intercomparison Project (Fish-MIP), forced by new-generation Earth system model outputs from Phase 6 of the Coupled Model Intercomparison Project (CMIP6), to provide insights into how projected climate change will affect future ocean ecosystems. Compared with the previous generation CMIP5-forced Fish-MIP ensemble, the new ensemble ecosystem simulations show a greater decline in mean global ocean animal biomass under both strong-mitigation and high-emissions scenarios due to elevated warming, despite greater uncertainty in net primary production in the high-emissions scenario. Regional shifts in the direction of biomass changes highlight the continued and urgent need to reduce uncertainty in the projected responses of marine ecosystems to climate change to help support adaptation planning.

In the current era of rapid climate change, accurate characterization of climate-relevant gas dynamics-namely production, consumption, and net emissions-is required for all biomes, especially those ecosystems most susceptible to the impact of change. Marine environments include regions that act as net sources or sinks for numerous climateactive trace gases including methane (CH4) and nitrous oxide (N2O). The temporal and spatial distributions of CH4 and N2O are controlled by the interaction of complex biogeochemical and physical processes. To evaluate and quantify how these mechanisms affect marine CH4 and N2O cycling requires a combination of traditional scientific disciplines including oceanography, microbiology, and numerical modeling. Fundamental to these efforts is ensuring that the datasets produced by independent scientists are comparable and interoperable. Equally critical is transparent communication within the research community about the technical improvements required to increase our collective understanding of marine CH4 and N2O. A workshop sponsored by Ocean Carbon and Biogeochemistry (OCB) was organized to enhance dialogue and collaborations pertaining to marine CH4 and N2O. Here, we summarize the outcomes from the workshop to describe the challenges and opportunities for near-future CH4 and N2O research in the marine environment.

Assessment of the global budget of the greenhouse gas nitrous oxide ([Formula: see text]O) is limited by poor knowledge of the oceanic [Formula: see text]O flux to the atmosphere, of which the magnitude, spatial distribution, and temporal variability remain highly uncertain. Here, we reconstruct climatological [Formula: see text]O emissions from the ocean by training a supervised learning algorithm with over 158,000 [Formula: see text]O measurements from the surface ocean-the largest synthesis to date. The reconstruction captures observed latitudinal gradients and coastal hot spots of [Formula: see text]O flux and reveals a vigorous global seasonal cycle. We estimate an annual mean [Formula: see text]O flux of 4.2 ± 1.0 Tg N[Formula: see text], 64% of which occurs in the tropics, and 20% in coastal upwelling systems that occupy less than 3% of the ocean area. This [Formula: see text]O flux ranges from a low of 3.3 ± 1.3 Tg N[Formula: see text] in the boreal spring to a high of 5.5 ± 2.0 Tg N[Formula: see text] in the boreal summer. Much of the seasonal variations in global [Formula: see text]O emissions can be traced to seasonal upwelling in the tropical ocean and winter mixing in the Southern Ocean. The dominant contribution to seasonality by productive, low-oxygen tropical upwelling systems (>75%) suggests a sensitivity of the global [Formula: see text]O flux to El Niño-Southern Oscillation and anthropogenic stratification of the low latitude ocean. This ocean flux estimate is consistent with the range adopted by the Intergovernmental Panel on Climate Change, but reduces its uncertainty by more than fivefold, enabling more precise determination of other terms in the atmospheric [Formula: see text]O budget.

Climate warming is expected to intensify hypoxia in the California Current System (CCS), threatening its diverse and productive marine ecosystem. We analyzed past regional variability and future changes in the Metabolic Index (Φ), a species-specific measure of the environment's capacity to meet temperature-dependent organismal oxygen demand. Across the traits of diverse animals, Φ exhibits strong seasonal to interdecadal variations throughout the CCS, implying that resident species already experience large fluctuations in available aerobic habitat. For a key CCS species, northern anchovy, the long-term biogeographic distribution and decadal fluctuations in abundance are both highly coherent with aerobic habitat volume. Ocean warming and oxygen loss by 2100 are projected to decrease Φ below critical levels in 30 to 50% of anchovies' present range, including complete loss of aerobic habitat-and thus likely extirpation-from the southern CCS. Aerobic habitat loss will vary widely across the traits of CCS taxa, disrupting ecological interactions throughout the region.

While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends.

Global observations show that the ocean lost approximately 2% of its oxygen inventory over the last five decades 1-3, with important implications for marine ecosystems 4, 5. The rate of change varies with northwest Atlantic coastal waters showing a long-term drop 6, 7 that vastly outpaces the global and North Atlantic basin mean deoxygenation rates 5, 8. However, past work has been unable to resolve mechanisms of large-scale climate forcing from local processes. Here, we use hydrographic evidence to show a Labrador Current retreat is playing a key role in the deoxygenation on the northwest Atlantic shelf. A high-resolution global coupled climate-biogeochemistry model 9 reproduces the observed decline of saturation oxygen concentrations in the region, driven by a retreat of the equatorward-flowing Labrador Current and an associated shift toward more oxygen-poor subtropical waters on the shelf. The dynamical changes underlying the shift in shelf water properties are correlated with a slowdown in the simulated Atlantic Meridional Overturning Circulation 10. Our results provide strong evidence that a major, centennial-scale change of the Labrador Current is underway, and highlight the potential for ocean dynamics to impact coastal deoxygenation over the coming century.

Eastern boundary upwelling systems (EBUSs) are among the most productive regions in the ocean because deep, nutrient‐rich waters are brought up to the surface. Previous studies have identified winds, mesoscale eddies and offshore nutrient distributions as key influences on the net primary production in EBUSs. However uncertainties remain regarding their roles in setting cross‐shore primary productivity and ecosystem diversity. Here, we use a quasi‐two‐dimensional (2D) model that combines ocean circulation with a spectrum of planktonic sizes to investigate the impact of winds, eddies, and offshore nutrient distributions in shaping EBUS ecosystems. A key finding is that variations in the strength of the wind stress and the nutrient concentration in the upwelled waters control the distribution and characteristics of the planktonic ecosystem. Specifically, a strengthening of the wind stress maximum, driving upwelling, increases the average planktonic size in the coastal upwelling zone, whereas the planktonic ecosystem is relatively insensitive to variations in the wind stress curl. Likewise, a deepening nutricline shifts the location of phytoplankton blooms shore‐ward, shoals the deep chlorophyll maximum offshore, and supports larger phytoplankton across the entire domain. Additionally, increased eddy stirring of nutrients suppresses coastal primary productivity via "eddy quenching," whereas increased eddy restratification has relatively little impact on the coastal nutrient supply. These findings identify the wind stress maximum, isopycnal eddy diffusion, and nutricline depth as particularly influential on the coastal ecosystem, suggesting that variations in these quantities could help explain the observed differences between EBUSs, and influence the responses of EBUS ecosystems to climate shifts. Plain Language Summary: Ecosystems in eastern boundary upwelling systems (EBUSs) are supported by the movement of nutrient‐rich water from the deep ocean to the coastal surface waters through a wind‐driven process called "upwelling." Many factors can impact the across‐shore (zonal) distribution of size in EBUSs, with abundant large phytoplankton near shore, and sparse small phytoplankton offshore. For example, the strength of the wind controls upwelling, the subsurface nutrient distribution determines surface nutrient supply, and large‐scale ocean vortices ("eddies") remove nutrients from the surface. However, there remains uncertainty as to the relative importance of these different factors in determining the sizes and abundance of phytoplankton upwelling ecosystems. This study utilizes a physical ocean model coupled to an ecosystem model to investigate the impact of various physical and biological influences on planktonic ecosystems in EBUSs. We find that the strength of the wind, the mixing of nutrients by eddies, and the concentration of nutrients in the upwelled waters are most important in determining the ecosystem structure. In contrast, cross‐shore variations in the wind and the tendency of eddies to push waters downward near the coast are less influential. Our findings provide clarity on how physical and biochemical aspects of the EBUS environment influence its ecosystem. Key Points: An idealized quasi‐2D model (meridionally averaged model of eastern boundary upwelling systems) of eastern boundary upwelling systems and coupled size structured ecosystem model is presentedControls on the across‐shore phytoplankton size structure are identified by a set of model experimentsIdealized simulations motivated by the California Current System show wind stress max and subsurface nutrients set plankton size structure [ABSTRACT FROM AUTHOR]

Hybrid rockets have very interesting characteristics like simplicity, reliability, safety, thrust modulation, environmental friendliness and lower costs, which make them very attractive for several applications like sounding rockets, small launch vehicles, upper stages, hypersonic test-beds and planetary landers. In recent years, advancements have been made to increase hybrid motor performance, and two of the most promising solutions are vortex injection and paraffin-based fuels. Moreover, both technologies can be also used to tailor the fuel regression rate, in the first case varying the swirl intensity, and in the second case with the amount and type of additives. In this way, it is possible not only to design high-performing hybrid motors, but also to adjust their grain and chamber geometries to different mission requirements, particularly regarding thrust and burning time. In this paper, the knowledge about these two technical solutions and their coupling is extended. Three sets of experimental campaigns were performed in the frame of the Italian Space Agency-sponsored PHAEDRA program. The first one investigated a reference paraffin fuel with axial and standard vortex injection. The second campaign tested vortex injection with low values of swirl numbers down to 0.5 with a conventional plastic fuel, namely polyethylene. Finally, the last campaign tested another, lower regressing, paraffin-based fuel with the same low swirl numbers as the second campaign. [ABSTRACT FROM AUTHOR]

We propose a novel variational Bayes approach to estimate high-dimensional Vector Autoregressive (VAR) models with hierarchical shrinkage priors. Our approach does not rely on a conventional structural representation of the parameter space for posterior inference. Instead, we elicit hierarchical shrinkage priors directly on the matrix of regression coefficients so that (a) the prior structure maps into posterior inference on the reduced-form transition matrix and (b) posterior estimates are more robust to variables permutation. An extensive simulation study provides evidence that our approach compares favorably against existing linear and nonlinear Markov chain Monte Carlo and variational Bayes methods. We investigate the statistical and economic value of the forecasts from our variational inference approach for a mean-variance investor allocating her wealth to different industry portfolios. The results show that more accurate estimates translate into substantial out-of-sample gains across hierarchical shrinkage priors and model dimensions. [ABSTRACT FROM AUTHOR]