Can Simple Adaptive Rules Improve Honeybee Colony Survivability? A Computational Model Inspired by the Work of Thomas Seeley and Gene Robinson

My family has kept honeybees for the past nine years. During that time, I noticed that colonies facing what appeared to be very similar conditions could experience very different outcomes. Some colonies survived difficult periods while others struggled, even when they seemed to begin with similar resources and face the same environment. Those observations made me curious about what separates colonies that survive from those that do not. Environmental conditions clearly matter, but I began to wonder whether a colony's ability to adjust to changing conditions might also influence its chances of survival. While reading the work of Thomas Seeley and Gene Robinson, I became interested in the role that adaptation plays in honeybee colonies. Their research suggested that colonies often respond to changing circumstances through flexible behavior rather than fixed patterns. This led me to a simple question: could a simple adaptive rule improve survivability compared to a strategy that never changes? To explore this question, I developed a simplified computational model to test one adaptive idea by comparing two strategies under identical simulated conditions. The first follows a fixed set of rules regardless of colony condition. The second increases resource-gathering effort when colony reserves become low. Later in the simulation, both strategies enter a shared late-season storage phase representing preparation for winter. During this period, the adaptive strategy continues to adjust its behavior when reserves become low. The model introduces random resource availability and mite pressure to simulate environmental uncertainty. Both strategies experience the same randomly generated conditions, so that the adaptive decision rule is the only meaningful difference between them. Additional stress is introduced through stochastic mite pressure that reduces colony reserves later in the season. The adaptive strategy consistently outperformed the fixed strategy across all four outcome measures, including average survival time, survival rate, final reserve level, and total resources collected. Although the model does not attempt to reproduce the full biology of honeybee colonies, it suggests that even a simple adaptive rule can improve survivability under uncertain conditions. More broadly, the project explores how adaptation may contribute to resilience in complex systems. One of the biggest surprises was discovering that asking a simpler question required building a more carefully controlled experiment.