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.
Strong relationships between size and other traits have long motivated studies of the size structure and dynamics of planktonic food webs. Size structured ecosystem models (SSEMs) are often used to represent the behavior of these ecosystems, with organism size as a first order approximation of the axis of biological diversity. Previous studies using SSEMs have reported the emergence of localized “peaks” in the size spectrum, a phenomenon that will be referred to in this study as “quantization”. However, SSEMs that are used routinely in Earth System Models (ESMs), they tend to be too coarsely discretized to resolve quantization. Observational studies of plankton biomass have also shown qualitatively similar patterns, with localized peaks along the size spectrum. The conditions under which quantization occurs and the ecosystem parameters that control the locations of the biomass “peaks” along the size spectrum have not been systematically explored. This study serves to simultaneously advance our understanding of the constraints on quantization in size-structured ecosystems, and to suggest an approach to discretizing SSEMs that leverages quantization to select a greatly reduced number of size classes. A size-structured model of the pelagic food web, similar to those implemented in global models, is used to investigate the sensitivity of biomass peaks to predator–prey interactions, and nutrient forcing. This study shows that the location of biomass peaks along the size spectrum is strongly controlled by the size selectivity of predation, and the location of biomass peaks along the size spectrum is less sensitive to variations in nutrient supply, external ecosystem forcing, and vertical heterogeneity. Taking advantage of a robust localization of biomass peaks, the dynamics of a continuous planktonic size spectrum to be represented using a few selected size classes, corresponding to locations of the peaks along the size spectrum. These findings offer an insight on how to approach discretization of size structured ecosystem model in Earth system models.
Climate change can drive shifts in the seasonality of marine productivity, with consequences for the marine food web. However, these alterations in phytoplankton bloom phenology (initiation and peak timing), and the underlying drivers, are not well understood. Here, using a 30-member Large Ensemble of climate change projections, we show earlier bloom initiation in most ocean regions, yet changes in bloom peak timing vary widely by region. Shifts in both initiation and peak timing are induced by a subtle decoupling between altered phytoplankton growth and zooplankton predation, with increased zooplankton predation (top-down control) playing an important role in altered bloom peak timing over much of the global ocean. Only in limited regions is light limitation a primary control for bloom initiation changes. In the extratropics, climate-change-induced phenological shifts will exceed background natural variability by the end of the twenty-first century, which may impact energy flow in the marine food webs.
The abundance and size distribution of marine particles control a range of biogeochemical and ecological processes in the ocean, including carbon sequestration. These quantities are the result of complex physical-biological interactions that are difficult to observe, and their spatial and temporal patterns remain uncertain. Here, we present a novel analysis of particle size distributions (PSDs) from a global compilation of in situ Underwater Vision Profiler 5 (UVP5) optical measurements. Using a machine learning algorithm, we extrapolate sparse UVP5 observations to the global ocean from well-sampled oceanographic variables. We reconstruct global maps of PSD parameters (biovolume [BV] and slope) for particles at the base of the euphotic zone. These reconstructions reveal consistent global patterns, with high chlorophyll regions generally characterized by high particle BV and flatter PSD slope, that is, a high relative abundance of large versus small particles. The resulting negative correlations between particle BV and slope further suggests synergistic effects on size-dependent processes such as sinking particle fluxes. Our approach and estimates provide a baseline for an improved understanding of particle cycles in the ocean, and pave the way to global, three-dimensional reconstructions of PSD and sinking particle fluxes from the growing body of UVP5 observations.
Atmospheric nitrous oxide (N2O) contributes to global warming and stratospheric ozone depletion, so reducing uncertainty in estimates of emissions from different sources is important for climate policy. Here, we simulate atmospheric N2O using an atmospheric chemistry-transport model (ACTM), and the results are first compared with the in situ measurements. Five combinations of known (a priori) N2O emissions due to natural soil, agricultural land, other human activities and sea-air exchange are used. The N2O lifetime is 127.6 ± 4.0 yr in the control ACTM simulation (range indicate interannual variability). Regional N2O emissions are optimised by Bayesian inverse modelling for 84 partitions of the globe at monthly intervals, using measurements at 42 sites around the world covering 1997-2019. The best estimate global land and ocean emissions are 12.99 ± 0.22 and 2.74 ± 0.27 TgN yr−1, respectively, for 2000-2009, and 14.30 ± 0.20 and 2.91 ± 0.27 TgN yr−1, respectively, for 2010-2019. On regional scales, we find that the most recent ocean emission estimation, with lower emissions in the Southern Ocean regions, fits better with that predicted by the inversions. Marginally higher (lower) emissions than the inventory/model for the tropical (extra-tropical) land regions is estimated and validated using independent aircraft observations. Global land and ocean emission variabilities show statistically significant correlation with El Niño Southern Oscillation (ENSO). Analysis of regional land emissions shows increases over America (Temperate North, Central, Tropical), Central Africa, and Asia (South, East and Southeast) between the 2000s and 2010s. Only Europe as a whole recorded a slight decrease in N2O emissions due to chemical industry. Our inversions suggest revisions to seasonal emission variations for 3 of the 15 land regions (East Asia, Temperate North America and Central Africa), and the Southern Ocean region. The terrestrial ecosystem model (VISIT) is able to simulate annual total emissions in agreement with the observed N2O growth rate since 1978, but the lag-time scales of N2O emissions from nitrogen fertiliser application may need to be revised.
Models and observations suggest that particle flux attenuation is lower across the mesopelagic zone of anoxic environments compared to oxic environments. Flux attenuation is controlled by microbial metabolism as well as aggregation and disaggregation by zooplankton, all of which shape the relative abundance of differently sized particles. Observing and modeling particle spectra can provide information about the contributions of these processes. We measured particle size spectrum profiles at one station in the oligotrophic Eastern Tropical North Pacific Oxygen Deficient Zone (ETNP ODZ) using an underwater vision profiler (UVP), a high-resolution camera that counts and sizes particles. Measurements were taken at different times of day, over the course of a week. Comparing these data to particle flux measurements from sediment traps collected over the same time-period allowed us to constrain the particle size to flux relationship, and to generate highly resolved depth and time estimates of particle flux rates. We found that particle flux attenuated very little throughout the anoxic water column, and at some time points appeared to increase. Comparing our observations to model predictions suggested that particles of all sizes remineralize more slowly in the ODZ than in oxic waters, and that large particles disaggregate into smaller particles, primarily between the base of the photic zone and 500 m. Acoustic measurements of multiple size classes of organisms suggested that many organisms migrated, during the day, to the region with high particle disaggregation. Our data suggest that diel-migrating organisms both actively transport biomass and disaggregate particles in the ODZ core.
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.
The biomass and biogeochemical roles of fish in the ocean are ecologically important but poorly known. Here, we use a data-constrained marine ecosystem model to provide a first-order estimate of the historical reduction of fish biomass due to fishing and the associated change in biogeochemical cycling rates. The pre-exploitation global biomass of exploited fish (10 g to 100 kg) was 3.3 ± 0.5 Gt, cycling roughly 2% of global primary production (9.4 ± 1.6 Gt year−1) and producing 10% of surface biological export. Particulate organic matter produced by exploited fish drove roughly 10% of the oxygen consumption and biological carbon storage at depth. By the 1990s, biomass and cycling rates had been reduced by nearly half, suggesting that the biogeochemical impact of fisheries has been comparable to that of anthropogenic climate change. Our results highlight the importance of developing a better mechanistic understanding of how fish alter ocean biogeochemistry.
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.
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. .
The remineralization depth of sinking organic particles controls the efficiency of the biological carbon pump by setting the sequestration timescale of remineralized carbon in the ocean interior. Oxygen minimum zones (OMZs) have been identified as regions of elevated particle transfer and efficient carbon sequestration at depth, but direct measurements remain sparse in these regions and only provide snapshots of the particle flux. Here, we use remineralization tracers to reconstruct time-mean particle flux profiles in the OMZs of the Eastern Tropical Pacific and the Arabian Sea. Compared to the surrounding tropical waters, both OMZs exhibit slow flux attenuation between 100 and 1000 m where suboxic waters reside, and sequester carbon beneath 1000 m more than twice as efficiently. Using a mechanistic model of particle sinking, remineralization, and disaggregation, we show that three different mechanisms might explain the shape of the OMZ flux profiles: (i) a significant slow-down of remineralization when carbon oxidation transitions from aerobic to anaerobic respiration (e.g., denitrification); (ii) the exclusion of zooplankton that mediate disaggregation of large particles from suboxic waters, and (iii) the limitation of remineralization by the diffusive supply of oxidants (oxygen and nitrate) into large particles. We show that each mechanism leaves a unique signature in the size distribution of particles, suggesting that observations with optical instruments such as Underwater Vision Profilers hold great promise for understanding the drivers of efficient carbon transfer though suboxic water columns. In turn, this will allow more accurate prediction of future changes in carbon sequestration as the ocean loses oxygen in a warming climate.
Abstract Coastal winds in the California Current System (CCS) are credited with the high productivity of its planktonic ecosystem and the shallow hypoxic and corrosive waters that structure diverse macrofaunal habitats. These winds thus are considered a leading mediator of climate change impacts in the CCS and other Eastern Boundary Upwelling systems. We use an eddy-permitting regional model to downscale the response of the CCS to three of the major distinct climate changes commonly projected by global Earth System Models: regional winds, ocean warming and stratification, and remote water chemical properties. An increase in alongshore winds intensifies spring upwelling across the CCS, but this response is muted by increased stratification, especially during summer. Despite the seasonal shift in regional wind-driven upwelling, basin-scale changes are the decisive factor in the response of marine ecosystem properties including temperature, nutrients, productivity, and oxygen. Downscaled temperature increases and dissolved oxygen decreases are broadly consistent with coarse resolution Earth System Models, and these projected changes are large and well constrained across the models, whereas nutrient and productivity changes are small compared to the intermodel spread. These results imply that global models with poor resolution of coastal processes nevertheless yield important information about the dominant climate impacts on coastal ecosystems.