  Many plankton species undergo daily vertical migration to large depths in the
turbulent ocean. To do this efficiently, the plankton can use a gyrotactic
mechanism, aligning them with gravity to swim downwards, or against gravity to
swim upwards. Many species show passive mechanisms for gyrotactic stability.
For example, bottom-heavy plankton tend to align upwards. This is efficient for
upward migration in quiescent flows, but it is often sensitive to turbulence
which upsets the alignment. Here we suggest a simple, robust active mechanism
for gyrotactic stability, which is only lightly affected by turbulence and
allows alignment both along and against gravity. We use a model for a plankton
that swims with a constant speed and can actively steer in response to
hydrodynamic signals encountered in simulations of a turbulent flow. Using
reinforcement learning, we identify the optimal steering strategy. By using its
setae to sense its settling velocity transversal to its swimming direction, the
swimmer can deduce information about the direction of gravity, allowing it to
actively align upwards. The mechanism leads to a rate of upward migration in a
turbulent flow that is of the same order as in quiescent flows, unless the
turbulence is very vigorous. In contrast, passive swimmers with typical
parameters of copepods show much smaller upward velocity in turbulence.
Settling may even cause them to migrate downwards in vigorous turbulence.
