Hypoxia conditions are increasing throughout the world, influencing biogeochemical cycles of elements and marine life. Hypoxia results from complex interactions between physical and biogeochemical processes, which can not be understood by observations alone. Models are invaluable tools at studying system dynamics, generalizing discrete observations and predicting future states. They are also useful as management tools for evaluating site-specific responses to management scenarios. Here we review oxygen dynamics models that have significantly contributed to a better understanding of the effects of natural processes and human perturbations on the development of hypoxia, factors controlling the extent and temporal variability of coastal hypoxia, and the effects of oxygen depletion on biogeochemical cycles. Because hypoxia occurs in a variety of environments and can be persistent, periodic or episodic, models differ significantly in their complexity and temporal and spatial resolution. We discuss the progress in developing hypoxia models for benthic and pelagic systems that range from simple box models to three dimensional circulation models. Applications of these models in five major hypoxia regions are presented. In the last decades, substantial progress has been made towards the parameterization of biogeochemical processes in both hypoxic water columns and sediments. In coastal regions, semi-empirical models have been used more frequently than mechanistic models to study nutrient enrichment and hypoxia relationships. Recent advances in three-dimensional coupled physical-ecological-biogeochemical models have allowed a better representation of physical-biological interactions in these systems. We discuss the remaining gaps in process descriptions and suggest directions for improvement. Better process representations in models will help us answer several important questions, such as those about the causes of the observed worldwide increase in hypoxic conditions, and future changes in the intensity and spread of coastal hypoxia. At the same time, quantitative model intercomparison studies suggest that the predictive ability of our models may be adversely affected by their increasing complexity, unless the models are properly constrained by observations.

Significant changes in the abundance and composition of phytoplankton were observed along Line P in the northeast subarctic Pacific as a result of a rapid warming of surface waters in 2014–2015. This feature, labeled “the blob,” reached ~ 4°C above normal and restricted winter ocean–surface nutrient renewal due to increased stratification. As a result, surface nutrients were the lowest observed and nitrate depletion in summer extended farther offshore than in the last three decades. Within this nitrate‐depleted region, there was unusually low phytoplankton biomass and a dramatic increase in the dominance of cyanobacteria, including Prochlorococcus, which had not been previously observed in this region. Farther offshore, in the iron‐limited region, phytoplankton biomass and the abundance of haptophytes and chlorophytes increased during “the blob.” By 2016, surface nutrient and phytoplankton concentrations were still low, but at most of the stations, phytoplankton composition was similar to that observed before the warming occurred, except for an increase in diatoms farther offshore. These changes at the base of the food web could have ecosystem‐wide implications.

A large anomalously warm water patch (the Blob) appeared in the NE Pacific Ocean in the winter of 2013–2014 and persisted through 2016 causing strong positive upper ocean temperature anomalies at Ocean Station Papa (OSP, 50° N, 145° W). The effect of the temperature anomalies on annual net community production (ANCP) was determined by upper ocean chemical mass balances of O₂ and dissolved inorganic carbon (DIC) using data from a profiling float and a surface mooring. Year-round oxygen mass balance in the upper ocean (0 to 91–111 m) indicates that ANCP decreased after the first year when warmer water invaded this area and then returned to the pre-Blob value (2.4, 0.8, 2.1, and 1.6 mol C m⁻² yr⁻¹ from 2012 to 2016, with a mean value of 1.7±0.7 mol C m⁻² yr⁻¹). ANCP determined from the DIC mass balance has a mean value that is similar within the errors as that from the O₂ mass balance but without a significant trend (2.0, 2.1, 2.6, and 3.0 mol C m⁻² yr⁻¹ with a mean value of 2.4±0.6 mol C m⁻² yr⁻¹). This is likely due to differences in the air–sea gas exchange, which is a major term for both mass balances. Oxygen has a residence time with respect to gas exchange of about 1 month while the CO₂ gas exchange response time is more like a year. Therefore the biologically induced oxygen saturation anomaly responds fast enough to record annual changes, whereas that for CO₂ does not. Phytoplankton pigment analysis from the upper ocean shows lower chlorophyll a concentrations and changes in plankton community composition (greater relative abundance of picoplankton) in the year after the warm water patch entered the area than in previous and subsequent years. Our analysis of multiple physical and biological processes that may have caused the ANCP decrease after warm water entered the area suggests that it was most likely due to the temperature-induced changes in biological processes.

Remote-sensing reflectance data collected by ocean colour satellites are processed using bio-optical algorithms to retrieve biogeochemical properties of the ocean. One such important property is the concentration of chlorophyll-a, an indicator of phytoplankton biomass that serves a multitude of purposes in various ocean science studies. Here, the performance of two generic chlorophyll-a algorithms (i.e., a band ratio one, Ocean Colour X (OCx), and a semi-analytical one, Garver–Siegel Maritorena (GSM)) was assessed against two large in situ datasets of chlorophyll-a concentration collected between 1999 and 2016 in the Northeast Pacific (NEP) and Northwest Atlantic (NWA) for three ocean colour sensors: Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS). In addition, new regionally-tuned versions of these two algorithms are presented, which reduced the mean error (mg m⁻³) of chlorophyll-a concentration modelled by OCx in the NWA from −0.40, −0.58 and −0.45 to 0.037, −0.087 and −0.018 for MODIS, SeaWiFS, and VIIRS respectively, and −0.34 and −0.36 to −0.0055 and −0.17 for SeaWiFS and VIIRS in the NEP. An analysis of the uncertainties in chlorophyll-a concentration retrieval showed a strong seasonal pattern in the NWA, which could be attributed to changes in phytoplankton community composition, but no long-term trends were found for all sensors and regions. It was also found that removing the 443 nm waveband for the OCx algorithms significantly improved the results in the NWA. Overall, GSM performed better than the OCx algorithms in both regions for all three sensors but generated fewer chlorophyll-a retrievals than the OCx algorithms.

Recent studies on marine heat waves describe water temperature anomalies causing changes in food web structure, bloom dynamics, biodiversity loss, and increased plant and animal mortality. However, little information is available on how water temperature anomalies impact prokaryotes (bacteria and archaea) inhabiting ocean waters. This is a nontrivial omission given their integral roles in driving major biogeochemical fluxes that influence ocean productivity and the climate system. Here we present a time-resolved study on the impact of a large-scale warm water surface anomaly in the northeast subarctic Pacific Ocean, colloquially known as the Blob, on prokaryotic community compositions. Multivariate statistical analyses identified significant depth- and season-dependent trends that were accentuated during the Blob. Moreover, network and indicator analyses identified shifts in specific prokaryotic assemblages from typically particle-associated before the Blob to taxa considered free-living and chemoautotrophic during the Blob, with potential implications for primary production and organic carbon conversion and export.

Quantification and mapping of surficial seabed sediment organic carbon have wide-scale relevance for marine ecology, geology and environmental resource management, with carbon densities and accumulation rates being a major indicator of geological history, ecological function and ecosystem service provisioning, including the potential to contribute to nature-based climate change mitigation. While global analyses can appear to provide a definitive understanding of the spatial distribution of sediment carbon, regional maps may be constructed at finer resolutions and can utilise targeted data syntheses and refined spatial data products and therefore have the potential to improve these estimates. Here, we report a national systematic review of data on organic carbon content in seabed sediments across Canada and combine this with a synthesis and unification of the best available data on sediment composition, seafloor morphology, hydrology, chemistry and geographic settings within a machine learning mapping framework. Predictive quantitative maps of mud content, dry bulk density, organic carbon content and organic carbon density were produced along with cell-specific estimates of their uncertainty at 200 m resolution across 4 489 235 km² of the Canadian continental margin (92.6 % of the seafloor area above 2500 m) (https://doi.org/10.5683/SP3/ICHVVA, Epstein et al., 2024). Fine-scale variation in carbon stocks was identified across the Canadian continental margin, particularly in the Pacific Ocean and Atlantic Ocean regions. Overall, we estimate the standing stock of organic carbon in the top 30 cm of surficial seabed sediments across the Canadian shelf and slope to be 10.9 Gt (7.0–16.0 Gt). Increased empirical sediment data collection and higher precision in spatial environmental data layers could significantly reduce uncertainty and increase accuracy in these products over time.