Articles | Volume 14, issue 11
Biogeosciences, 14, 2877–2889, 2017
Biogeosciences, 14, 2877–2889, 2017

Research article 16 Jun 2017

Research article | 16 Jun 2017

Biogeochemical versus ecological consequences of modeled ocean physics

Sophie Clayton1,2, Stephanie Dutkiewicz1, Oliver Jahn1, Christopher Hill1, Patrick Heimbach1,3, and Michael J. Follows1 Sophie Clayton et al.
  • 1Department for Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
  • 2School of Oceanography, University of Washington, Seattle, WA, USA
  • 3Institute for Computational Engineering and Sciences and Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA

Abstract. We present a systematic study of the differences generated by coupling the same ecological–biogeochemical model to a 1°, coarse-resolution, and 1∕6°, eddy-permitting, global ocean circulation model to (a) biogeochemistry (e.g., primary production) and (b) phytoplankton community structure. Surprisingly, we find that the modeled phytoplankton community is largely unchanged, with the same phenotypes dominating in both cases. Conversely, there are large regional and seasonal variations in primary production, phytoplankton and zooplankton biomass. In the subtropics, mixed layer depths (MLDs) are, on average, deeper in the eddy-permitting model, resulting in higher nutrient supply driving increases in primary production and phytoplankton biomass. In the higher latitudes, differences in winter mixed layer depths, the timing of the onset of the spring bloom and vertical nutrient supply result in lower primary production in the eddy-permitting model. Counterintuitively, this does not drive a decrease in phytoplankton biomass but results in lower zooplankton biomass. We explain these similarities and differences in the model using the framework of resource competition theory, and find that they are the consequence of changes in the regional and seasonal nutrient supply and light environment, mediated by differences in the modeled mixed layer depths. Although previous work has suggested that complex models may respond chaotically and unpredictably to changes in forcing, we find that our model responds in a predictable way to different ocean circulation forcing, despite its complexity. The use of frameworks, such as resource competition theory, provides a tractable way to explore the differences and similarities that occur. As this model has many similarities to other widely used biogeochemical models that also resolve multiple phytoplankton phenotypes, this study provides important insights into how the results of running these models under different physical conditions might be more easily understood.

Final-revised paper