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Turbulence

Do plankton chains swim upward better through turbulent water?

Lovecchio S, Climent E, Stocker R, et al. · Science advances · 2019

Open access · cc by · source: Europe PMC

Although chains of plankton cells are less stable than single cells, their long shape lets them stay pointed upward and ride upward-moving water, so in weak turbulence they migrate much faster.

Study at a glance

Design
Computational / modelling — Individual-based model of gyrotactic swimmers embedded in a direct numerical simulation of isotropic turbulence, varying elongation, stability and swimming speed.
N
No participants; each simulation tracked 100,000 model swimmers (convergence checked with 300,000).
Population
Simulated motile phytoplankton cells and chains in homogeneous isotropic turbulence
Outcome
Mean vertical swimming orientation, vertical fluid velocity sampled by swimmers, and net vertical migration rate

Structured fields used in claim comparison tables when every cited study has a complete layer.

Key findings

Elongation helped weakly stable swimmers keep pointing upward, increasing mean vertical orientation by 38% at one swimming speed and 96% at a roughly three times faster speed. Turbulence sorted swimmers by shape: spheres drifted into downwelling water while elongated chains collected in upwelling water. In weak turbulence, chains of two to eight cells migrated 35 to 130% faster than single cells, and two-cell chains were faster at every turbulence level tested, but in strong turbulence longer chains migrated more slowly than single cells.

Methodology

The authors simulated fully resolved turbulence by solving the Navier-Stokes equations and released 100,000 model swimmers that are turned by flow vorticity, by flow strain (for elongated shapes) and by a stabilising torque that points them upward. They first varied elongation alone, then used literature data on chain swimming speed and stability to predict migration for chains of different lengths across realistic ocean turbulence levels.

Limitations

This is a simulation, not an observation of real plankton, and it treats cells as rigid, point-like, inertia-free particles. Swimming speed and stability as a function of chain length come from literature regressions and simple models, with a range of possible scaling exponents across species. The flow is idealised isotropic turbulence at one Reynolds number, and the suggestion that plankton sense turbulence to regulate chain length is speculative.

How this study connects

Role on claims

Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.

  • Particles in turbulence do not sample the flow randomly; shape decides which structures they end up in.

    Turbulence sorts swimmers by shape: in simulated isotropic turbulence, spherical gyrotactic swimmers drifted into downwelling water while elongated chains collected in upwelling water, so in weak turbulence chains of two to eight cells migrated 35-130% faster than single cells; in strong turbulence longer chains were slower.

    Evidence for the claim as stated.

  • Particles in turbulence do not sample the flow randomly; shape decides which structures they end up in.

    Turbulence sorts swimmers by shape: in simulated isotropic turbulence, spherical gyrotactic swimmers drifted into downwelling water while elongated chains collected in upwelling water, so in weak turbulence chains of two to eight cells migrated 35-130% faster than single cells; in strong turbulence longer chains were slower.

    Scope note — Computational model with rigid point-like swimmers at one Reynolds number, not observations of real plankton.

    Limits the claim's scope: a different population, assay, or outcome.

  • The studies probe very different regimes: marginal wall-bounded turbulence near transition, fully developed magnetised plasma turbulence, buoyancy-driven convection at Prandtl number 10.6, and idealised isotropic turbulence. Intermittency appears in more than one of them, but their scaling laws are not interchangeable.

    Evidence for the claim as stated.

Open questions

Tensions this paper is part of

From concept pages' “where studies disagree.” Disagreement means the same question; scope means different assays, populations, or outcomes.

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Same topic cluster — not a recommendation engine.