Category: Pop. Genetics

Summary: Testing whether delayed reactivation from dormancy improves lineage survival in persistent Markov environments.

Dormancy can protect a lineage through bad environmental spells, but waking up too early may waste that protection on a one-step improvement that vanishes immediately. This experiment asks whether there is an optimal reactivation delay: short enough to exploit good runs, but long enough to ignore brief false recoveries.

The script simulates branching processes in Markov-switching environments and compares immediate reactivation with thresholded release rules. Instead of searching a spectral threshold, it runs deep single-seed simulations for a set of conditions and records whether moderate delays outperform both immediate wake-up and overly cautious delays.

The scientific interest is in the tradeoff between persistence and responsiveness. The model turns that tradeoff into measurable survival and growth differences across environmental persistence regimes, which is relevant to dormancy strategies in microbes, spores, and other bet-hedging systems.

Method: Deep stochastic branching-process simulations under Markov environmental switching, comparing multiple dormancy-release policies.

What is measured: Moderate-release advantage, long-delay penalty, fast-switch penalty, support fraction, and condition-level performance across persistence regimes.