Deep Chlorophyll Maxima (DCMs) are ubiquitous in low-latitude oceans, and of recognized biogeochemical and ecological importance. DCMs have been observed in the Southern Ocean, initially from ships and recently from profiling robotic floats, but with less understanding of their onset, duration, underlying drivers, or whether they are associated with enhanced biomass features. We report the characteristics of a DCM and DBM (Deep Biomass Maximum) in the Inter-Polar-Frontal-Zone (IPFZ) south of Australia from CTD profiles, shipboard-incubated samples, a towbody, and a BGC-ARGO float. The DCM and DBM were ~20 m thick and co-located with the nutricline, in the vicinity of a subsurface ammonium maximum characteristic of the IPFZ, but ~100 m shallower than the ferricline. Towbody transects demonstrated that the co-located DCM/DBM was broadly present across the IPFZ. Large healthy diatoms, with low iron requirements, resided within the DCM/DBM, and fixed up to 20 mmol C m-2 d-1. The BGC-ARGO float revealed the DCM/DBM persisted for >3 months. We propose a dual environmental mechanism to drive DCM/DBM formation and persistence within the IPFZ: sustained supply of both recycled iron within the subsurface ammonium maxima and upward silicate transport from depth. DCM/DBM cell-specific growth rates were considerably slower than those in the overlying mixed layer, implying that phytoplankton losses are also reduced, possibly as a result of heavily silicified diatom frustules. The light-limited seasonal termination of the observed DCM/DBM did not result in a ‘diatom dump’, rather ongoing diatom downward export occurred throughout its multi-month persistence.

We use inverse modelling to infer the distribution and drivers of community-integrated zooplankton grazing dynamics based on the skill with which different grazing formulations recreate the satellite-observed seasonal cycle in phytoplankton biomass. We find that oligotrophic and eutrophic biomes require more and less efficient grazing dynamics, respectively. This is characteristic of micro- and mesozooplankton, respectively, and leads to a strong sigmoidal relationship between observed mean-annual phytoplankton biomass and the optimal grazing parameterization required to simulate its seasonal cycle. Globally, we find Type III rather than Type II functional response curves consistently exhibit higher skill. These new observationally-based distributions can help constrain, validate and develop next-generation biogeochemical models.

Meridional eddy transport across the Antarctic Circumpolar Current is an essential component of the global meridional overturning circulation and the transport of climate relevant tracers. Challenges in comparing model and observational estimates of the transport arise from varying methodologies describing ‘eddy’ processes. We reconcile the approach used in shipboard surveys of eddies, complemented by satellite eddy tracking, with Reynolds decomposition applied to model outputs. This allows us to estimate the fraction of total meridional tracer transport attributed to coherent eddies in a global 0.1$^\circ$ ocean model. The model realistically simulates observed eddy kinetic energy and three-dimensional characteristics, particularly in representing an observed cyclonic eddy near 150 \degrees E, a hotspot for poleward heat flux. Annual meridional transports due to coherent eddies crossing the Subantarctic Front are estimated by vertically and radially integrating the tracer contents of all eddies. Notably, only cyclonic eddies moving equatorward across the Subantarctic Front contribute to the coherent eddy transport, with no anticyclonic eddies found to cross the front poleward in this region. Applying Reynolds decomposition, our study reveals predominantly poleward meridional transports due to all transient processes in a standing meander, particularly between the northern and southern branches of the Subantarctic Front. Coherent, long-lived eddies tracked from satellite data contribute less than 20\% to transient poleward heat transport, and equatorward nitrate transport in the model. Furthermore, we demonstrate that the integrated surface elevation of mesoscale eddies serves as a reliable proxy for inferring subsurface eddy content.

Climate change could irreversibly modify Southern Ocean ecosystems. Marine ecosystem model (MEM) ensembles can assist policy making by projecting future changes and allowing the evaluation and assessment of alternative management approaches. However, projected future changes in total consumer biomass from the Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP) global MEM ensemble highlight an uncertain future for the Southern Ocean, indicating the need for a region-specific ensemble. A large source of model uncertainty originates from the Earth system models (ESMs) used to force FishMIP models, particularly future changes to lower trophic level biomass and sea ice coverage. To build confidence in regional MEMs as ecosystem-based management tools in a changing climate that can better account for uncertainty, we propose the development of a Southern Ocean Marine Ecosystem Model Ensemble (SOMEME) contributing to the FishMIP 2.0 regional model intercomparison initiative. One of the challenges hampering progress of regional MEM ensembles is achieving the balance of global standardised inputs with regional relevance. As a first step, we design a SOMEME simulation protocol, that builds on and extends the existing FishMIP framework, in stages that include: detailed skill assessment of climate forcing variables for Southern Ocean regions, extension of fishing forcing data to include whaling, and new simulations that assess ecological links to sea-ice processes in an ensemble of candidate regional MEMs. These extensions will help advance assessments of urgently needed climate change impacts on Southern Ocean ecosystems.

We examine how zooplankton influence phytoplankton bloom phenology from the top-down, then use inverse modelling to infer the distribution and drivers of mean community zooplankton grazing dynamics based on the skill with which different simulated grazing formulations are able to recreate the observed seasonal cycle in phytoplankton biomass. We find that oligotrophic (eutrophic) biomes require more (less) efficient grazing dynamics, characteristic of micro- (meso-) zooplankton, leading to a strong relationship between the observed mean annual phytoplankton concentration in a region and the optimal grazing parameterization required to simulate it's observed phenology. Across the globe, we found that a type III functional response consistently exhibits more skill than a type II response, suggesting the mean dynamics of a coarse model grid-cell should offer stability and prey refuge at low biomass concentrations. These new observationally-based global distributions will be invaluable to help constrain, validate and develop next generation of biogeochemical models.

The biological carbon pump is a key controller of how much carbon is stored within the global ocean. This pathway is influenced by food web interactions between zooplankton and their prey. In global biogeochemical models, Holling Type functional responses are frequently used to represent grazing interactions. How these responses are parameterised greatly influences biomass and subsequent carbon export estimates. The half-saturation constant, or k value, is central to the Holling functional response. Empirical studies show k can vary over three orders of magnitude, however, this variation is poorly represented in global models. This study derives zooplankton grazing dynamics from remote sensing products of phytoplankton biomass, resulting in global distribution maps of the grazing parameter k. The impact of these spatially varying k values on model skill and carbon export flux estimates is then considered. This study finds large spatial variation in k values across the global ocean, with distinct distributions for micro- and mesozooplankton. High half-saturation constants, which drive slower grazing, are generally associated with areas of high productivity. Grazing rate parameterisation is found to be critical in reproducing satellite-derived distributions of nanophytoplankton biomass, highlighting the importance of top-down drivers for this size class. Spatially varying grazing dynamics decrease mean total carbon export by >17% compared to globally homogeneous dynamics, with increases in faecal pellet export and decreases in export from algal aggregates. This study highlights the importance of grazing dynamics to both community structure and carbon export, with implications for modelling marine carbon sequestration under future climate scenarios.

We examine how zooplankton influence phytoplankton bloom phenology from the top-down, then use inverse modelling to infer the distribution and drivers of mean community zooplankton grazing dynamics based on the skill with which different simulated grazing formulations are able to recreate the observed seasonal cycle in phytoplankton biomass. We find that oligotrophic (eutrophic) biomes require more (less) efficient grazing dynamics, characteristic of micro- (meso-) zooplankton, leading to a strong relationship between the observed mean annual phytoplankton concentration in a region and the optimal grazing parameterization required to simulate it’s observed phenology. Across the globe, we found that a type III functional response consistently exhibits more skill than a type II response, suggesting the mean dynamics of a coarse model grid-cell should offer stability and prey refuge at low biomass concentrations. These new observationally-based global distributions will be invaluable to help constrain, validate and develop next generation of biogeochemical models.

For nearly a century, the functional response curves, which describe how predation rates vary with prey density, have been a mainstay of ecological modelling. While originally derived to describe terrestrial interactions, they have been adopted to characterize aquatic systems in marine biogeochemical, size-spectrum, and population models. However, marine ecological modellers disagree over the qualitative shape of the curve (e.g. Type II vs. III), whether its parameters should be mechanistically or empirically defined (e.g. disk vs. Michaelis-Menten scheme), and the most representative value of those parameters. As a case study, we focus on marine biogeochemical models, providing a comprehensive theoretical, empirical, and numerical road-map for interpreting, formulating, and parameterizing the functional response when used to prescribe zooplankton specific grazing rates on a single prey source. After providing a detailed derivation of each of the canonical functional response types explicitly for aquatic systems, we review the literature describing their parameterization. Empirical estimates of each parameter vary by over three orders of magnitude across 10 orders of magnitude in zooplankton size. However, the strength and direction of the allometric relationship between each parameter and size differs depending on the range of sizes being considered. In models, which must represent the mean state of different functional groups, size spectra or in many cases the entire ocean’s zooplankton population, the range of parameter values is smaller, but still varies by two to three orders of magnitude. Next, we conduct a suite of 0-D NPZ simulations to isolate the sensitivity of phytoplankton population size and stability to the grazing formulation. We find that the disk parameterizations scheme is much less sensitive to it parameterization than the Michaelis-Menten scheme, and quantify the range of parameters over which the Type II response, long known to have destabilizing properties, introduces dynamic instabilities. Finally, we use a simple theoretical model to show how the mean apparent functional response, averaged across sufficient sub-grid scale heterogeneity diverges from the local response. Collectively, we recommend using a type II disk response for models with smaller scales and finer resolutions but suggest that a type III Michaelis-Menten response may do a better job of capturing the complexity of all processes being averaged across in larger scale and coarser resolution modal, not just local consumption and capture rates. While we focus specifically on the grazing formulation in marine biogeochemical models, we believe these recommendations are robust across a much broader range of ecosystem models.