Investigating microscale patchiness of motile microbes under turbulence in a simulated convective mixed layer

PLoS Comput Biol. 2022 Jul 27;18(7):e1010291. doi: 10.1371/journal.pcbi.1010291. eCollection 2022 Jul.

Abstract

Microbes play a primary role in aquatic ecosystems and biogeochemical cycles. Spatial patchiness is a critical factor underlying these activities, influencing biological productivity, nutrient cycling and dynamics across trophic levels. Incorporating spatial dynamics into microbial models is a long-standing challenge, particularly where small-scale turbulence is involved. Here, we combine a fully 3D direct numerical simulation of convective mixed layer turbulence, with an individual-based microbial model to test the key hypothesis that the coupling of gyrotactic motility and turbulence drives intense microscale patchiness. The fluid model simulates turbulent convection caused by heat loss through the fluid surface, for example during the night, during autumnal or winter cooling or during a cold-air outbreak. We find that under such conditions, turbulence-driven patchiness is depth-structured and requires high motility: Near the fluid surface, intense convective turbulence overpowers motility, homogenising motile and non-motile microbes approximately equally. At greater depth, in conditions analogous to a thermocline, highly motile microbes can be over twice as patch-concentrated as non-motile microbes, and can substantially amplify their swimming velocity by efficiently exploiting fast-moving packets of fluid. Our results substantiate the predictions of earlier studies, and demonstrate that turbulence-driven patchiness is not a ubiquitous consequence of motility but rather a delicate balance of motility and turbulent intensity.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Ecosystem*
  • Swimming*

Grants and funding

AKC was supported by the UK Natural Environment Research Council (NERC) through the Quantitative Methods in Ecology and Evolution (QMEE) CDT, under grant NE/P012345/1. SP was supported by Leverhulme Research Fellowship (RF-2020-653\2). MP acknowledges support from the UK Engineering and Physical Sciences Research Council (EPSRC) under grant EP/R029423/1. MvR acknowledges support from the UK turbulence consortium for computational resources (EPSRC grant EP/R029326/1). EvS was supported by the Dutch Research Council (NWO) through the ENW-Klein research programme with project number OCENW.KLEIN.085 The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.