Quantifying biological carbon pump pathways with a data-constrained mechanistic model ensemble approach

Abstract

Abstract. The ability to constrain the mechanisms that transport organic carbon into the deep ocean is complicated by the multiple physical, chemical, and ecological processes that intersect to create, transform, and transport particles in the ocean. In this paper we develop and parameterize a data-assimilative model of the multiple pathways of the biological carbon pump (NEMUROBCP). The mechanistic model is designed to represent sinking particle flux, active transport by vertically migrating zooplankton, and passive transport by subduction and vertical mixing, while also explicitly representing multiple biological and chemical properties measured directly in the field (including nutrients, phytoplankton and zooplankton taxa, carbon dioxide and oxygen, nitrogen isotopes, and 234Thorium). Using 30 different data types (including standing stock and rate measurements related to nutrients, phytoplankton, zooplankton, and non-living organic matter) from Lagrangian experiments conducted on 11 cruises from four ocean regions, we conduct an objective statistical parameterization of the model and generate 1 million different potential parameter sets that are used for ensemble model simulations. The model simulates in situ parameters that were assimilated (net primary production and gravitational particle flux) and parameters that were withheld (234Thorium and nitrogen isotopes) with reasonable accuracy. Model results show that gravitational flux of sinking particles and vertical mixing of organic matter from the euphotic zone are more important biological pump pathways than active transport by vertically migrating zooplankton. However, these processes are regionally variable, with sinking particles most important in oligotrophic areas of the Gulf of Mexico and California Current, sinking particles and vertical mixing roughly equivalent in productive coastal upwelling regions and the subtropical front in the Southern Ocean, and active transport an important contributor in the eastern tropical Pacific. We further find that mortality at depth is an important component of active transport when mesozooplankton biomass is high, but it is negligible in regions with low mesozooplankton biomass. Our results also highlight the high degree of uncertainty, particularly amongst mesozooplankton functional groups, that is derived from uncertainty in model parameters. Indeed, variability in BCP pathways between simulations for a specific location using different parameter sets (all with approximately equal misfit relative to observations) is comparable to variability in BCP pathways between regions. We discuss the implications of these results for other data-assimilation approaches and for studies that rely on non-ensemble model outputs.

Carbon sequestration by multiple biological pump pathways in a coastal upwelling biome

“…b Triangle diagram showing the proportion of export due to each biological carbon pump (BCP) pathway at different depth horizons following ref. 80 . Symbols near the top vertex indicate sinking dominated export; symbols near the bottom left are dominated by active transport; bottom right are mixing.…”

The ZooScan and the ZooCAM zooplankton imaging systems are intercomparable: A benchmark on the Bay of Biscay zooplankton

“…Because of their short generation time, they are sensitive to environmental changes and therefore can be used as good climate change indicators (Hays et al 2005; Beaugrand et al 2015). In addition, zooplankton play important roles in global biogeochemical cycles (Banse 1995), participate in the oceanic mitigation of atmospheric CO 2 build up through active processes, e.g., grazing and vertical diel migration, and passive processes, e.g., repackaging of fast sinking fecal pellets (Ariza et al 2015; Turner 2015; Stukel et al 2022). Given these key functions, abundance, biomass, and diversity of zooplankton are now considered as essential ocean variables and essential biodiversity variables (Chiba et al 2018; Batten et al 2019; Lombard et al 2019).…”