  In order to increase their robustness against environmental fluctuations,
many biological populations have developed bet-hedging mechanisms in which the
population `bets' against the presence of prolonged favorable environmental
conditions by having a few individual behaving as if they sensed a threatening
or stressful environment. As a result, the population (as a whole) increases
its chances of surviving environmental fluctuations in the long term, while
sacrificing short-term performance. In this paper, we propose a theoretical
framework, based on Markov jump linear systems, to model and evaluate the
performance of bet-hedging strategies in the presence of stochastic
fluctuations. We illustrate our results using numerical simulations.
