Promoting Instrument Development for New Research Avenues in Ocean Science: Opening the Black Box of Grazing

Heidi Dierssen,Wayne Homer Slade,Susanne Menden-Deuer

doi:10.3389/fmars.2021.695938

Abstract

While recent research has provided increasing insight into ocean ecosystem functions and rapidly improving predictive ability, it has become clear that for some key processes, including grazing by zooplankton, there simply is no currently available instrumentation to quantify relevant stocks and rates, remotely or in situ. When measurement capacity is lacking, collaborative research between instrument manufacturers and researchers can bring us closer to addressing key knowledge gaps. By necessity, this high risk, high rewards research will require iterative steps from best case scenarios under highly controlled and often artificial laboratory conditions to empirical verification in complex in situ conditions with diverse biota. To illustrate our point, we highlight the example of zooplankton grazing in marine planktonic food webs. Grazing by single-celled zooplankton accounts for the majority of organic carbon loss from marine primary production but is still measured with logistically demanding, point-sample incubation methods that result in reproducible results but at insufficient resolution to adequately describe temporal and spatial dynamics of grazer induced impacts on primary production, export production and the annual cycle of marine plankton. We advance a collaborative research and development agenda to eliminate this knowledge gap. Resolving primary production losses through grazing is fundamental to a predictive understanding of the transfer of matter and energy through marine ecosystems, major reservoirs of the global carbon cycle.

Highlights

Grazing remains one of the key unknowns in global predictive models of carbon flux, food web structure and ecosystem characteristics, because empirical grazing measurements are sparse, resulting in poor parameterization of grazing functions (e.g., Stock and Dunne, 2010; Bisson et al, 2020). To overcome this critical knowledge gap, we suggest focused effort be placed on the development of instrumentation that can link changes in phytoplankton biomass or optical properties with grazing
Several largescale analyses have concluded that phytoplankton losses, which are dominated by grazing are the putative explanation for annual cycles in phytoplankton biomass, accumulation rates and export production (Behrenfeld, 2010; Mignot et al, 2018; Bisson et al, 2020)
Model analyses suggest that the majority of C export due to grazing may be due to microzooplankton (Bisson et al, 2020)

Summary

INTRODUCTION

Grazing remains one of the key unknowns in global predictive models of carbon flux, food web structure and ecosystem characteristics, because empirical grazing measurements are sparse, resulting in poor parameterization of grazing functions (e.g., Stock and Dunne, 2010; Bisson et al, 2020) To overcome this critical knowledge gap, we suggest focused effort be placed on the development of instrumentation that can link changes in phytoplankton biomass or optical properties with grazing. Several largescale analyses have concluded that phytoplankton losses, which are dominated by grazing are the putative explanation for annual cycles in phytoplankton biomass, accumulation rates and export production (Behrenfeld, 2010; Mignot et al, 2018; Bisson et al, 2020) While these analyses were based on in situ or remote observations, none quantified grazing empirically. We conclude by highlighting some of the benefits and challenges of these collaborative relationships

Background

Findings

DISCUSSION