We present a representation of nitrogen and phosphorus cycling in the vegetation demography model the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), within the Energy Exascale Earth System (E3SM) land model. This representation is modular, and designed to allow testing of multiple hypothetical approaches for carbon-nutrient coupling in plants. The model tracks nutrient uptake, losses via turnover from both live plants and mortality into soil decomposition, and allocation during tissue growth for a large number of size- and functional-type-resolved plant cohorts within a time-since-disturbance-resolved ecosystem. Root uptake is governed by fine root biomass, and plants vary in their fine root carbon allocation in order to balance carbon and nutrient limitations to growth. We test the sensitivity of the model to a wide range of parameter variations and structural representations, and in the context of observations at Barro Colorado Island, Panama. A key model prediction is that plants in the high-light-availability canopy positions allocate more carbon to fine roots than plants in low-light understory environments, given the widely different carbon versus nutrient constraints of these two niches within a given ecosystem. This model provides a basis for exploring carbon-nutrient coupling with vegetation demography within Earth System Models (ESMs).
The Southern Ocean (SO) is the worlds largest high nutrient low chlorophyll region and has a plentiful supply of underutilised macronutrients due to light and iron limitation. These macronutrients supply the rest of the neighboring ocean basins, and are hugely important for global productivity and ocean carbon sequestration. Vertical mixing rates in the SO are known to vary by an order of magnitude temporally and spatially, however there is great uncertainty in the parameterization of this mixing, including in the specification of a background mixing value in coarse resolutation Earth System Models. Using a biogeochemical-ocean model we show that SO biomass is highly sensitive to altering the background diapycnal mixing over short timescales. Increasing mixing enhances biomass by altering key biogeochemical and physical parameters. An increased surface supply of iron is responsible for biomass increases in most areas, demonstrating the importance of year round diapycnal fluxes of iron to SO surface waters. These changes to SO biomass could potentially alter atmospheric CO2 concentration over longer timescales, demonstrating the importance of accurate representation of diapycnal mixing in climate models.
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.