The Role of Ocean Currents in the Temperature Selection of Plankton: Insights from an Individual-Based Model

Abstract

Biogeography studies that correlate the observed distribution of organisms to environmental variables are typically based on local conditions. However, in cases with substantial translocation, like planktonic organisms carried by ocean currents, selection may happen upstream and local environmental factors may not be representative of those that shaped the local population. Here we use an individual-based model of microbes in the global surface ocean to explore this effect for temperature. We simulate up to 25 million individual cells belonging to up to 50 species with different temperature optima. Microbes are moved around the globe based on a hydrodynamic model, and grow and die based on local temperature. We quantify the role of currents using the “advective temperature differential” metric, which is the optimum temperature of the most abundant species from the model with advection minus that from the model without advection. This differential depends on the location and can be up to 4°C. Poleward-flowing currents, like the Gulf Stream, generally experience cooling and the differential is positive. We apply our results to three global datasets. For observations of optimum growth temperature of phytoplankton, accounting for the effect of currents leads to a slightly better agreement with observations, but there is large variability and the improvement is not statistically significant. For observed Prochlorococcus ecotype ratios and metagenome nucleotide divergence, accounting for advection improves the correlation significantly, especially in areas with relatively strong poleward or equatorward currents.

Surface-circulation change in the Southern Ocean across the Middle Eocene Climatic Optimum: inferences from dinoflagellate cysts and biomarker paleothermometry

“…Bijl et al, 2011). In the modern ocean, phytoplankton distribution patterns are driven by the interplay of passive transport by surface currents and temperature selection (Hellweger et al, 2016;Thomas et al, 2012). A similar dual selection mechanism seems to have affected the middle Eocene dinocyst assemblages in the region.…”

“…in Mediterranean sapropels (e.g., Sangiorgi et al, 2006;van Helmond et al, 2015;Zwiep et al, 2018), Cretaceous Oceanic Anoxic Event 2 shelf sediments (van Helmond et al, 2014) and the Holocene Adélie drift underlying a highly productive polynya system (Hartman et al, 2018). The average dinocyst concentrations at Site 1170 may be converted to average accumulation rates in the order of 10,000-80,000 cysts per cm 2 per yr.…”

“…The relatively low diversity of the dinocyst assemblages in combination with the high dominance of a single taxon (Enneadocysta dictyostila in the MECO interval) suggests a generally eutrophic setting that could have been characterised by seasonal plankton blooms. Notably, in several records from the Paleocene-Eocene Thermal Maximum (Harding et al, 2011;Sluijs et al, 2011;Frieling et al, 2018b), and a record from Oceanic Anoxic Event 2 at Bass River (van Helmond et al, 2014), highest concentrations of dinocysts reach into the 10,000-100,000 cysts per gram sediment, and also correspond to low diversity -high dominance assemblages, suggestive of dinoflagellate blooms. Dinocysts deriving from heterotrophic dinoflagellates are present at Site 1170, but not in high abundance (Supplementary data).…”

Recent mixing of Vibrio parahaemolyticus populations

“…There are many studies of distribution of marine microbes e.g. [1][2][3][4], but these typically survey patterns of macro-scale diversity. Differences in species level or genus level composition between locations are as likely to reflect environmental heterogeneity as dispersal, making the patterns difficult to interpret.…”

Recent mixing of Vibrio parahaemolyticus populations

“…There are many studies of distribution of marine microbes e.g. [1-4], but these typically survey patterns of macro-scale diversity. Differences in species level or genus level composition between locations are as likely to reflect environmental heterogeneity as dispersal, making the patterns difficult to interpret.…”