How long to rest in unpredictably changing habitats?

Abstract

In the present study, we investigated the optimum length of prolonged dormancy (developmental arrest extending over favourable periods) of organisms under uncertain environmental conditions. We used an artificial life model to simulate the evolution of suspended development in the ontogenesis of organisms inhabiting unpredictably changing habitats. A virtual population of semelparous parthenogenetic individuals that varied in a duration of developmental arrest competed for limited resources. At a constant level of available resources, uninterrupted development was the superior life strategy. Once population fluctuations appeared (generated by the stochastic variability of available resources), temporal developmental arrest became more advantageous than continuous development. We did not observe the selection of the optimum length of dormancy, but rather the evolution of a diversified period of developmental arrest. The fittest organisms employed bet-hedging strategy and produced diversified dormant forms postponing development for a different number of generations (from 0 to several generations, in decreasing or equal proportions). The maximum length of suspended development increased asymptotically with increasing environmental variability and was inversely related to the mortality of dormant forms. The prolonged dormancy may appear beneficial not only in erratic habitats but also in seasonal ones that are exposed to long-term variability of environmental conditions during the growing seasons. In light of our simulations the phenomenon of very long diapause (VLD), lasting tens to thousands of generations, which is occasionally observed in ontogenesis of some living creatures, may not be explained by the benefits of bet-hedging revival strategies. We propose an alternative reasoning for the expression of VLD.

Fig 1. The scheme of a one generation cycle of the virtual population of our simulation.

Fig 2. Mean survivorship of various life strategies competing for limited resources for 5,000 generations at different range of environmental variability when mortality of dormant forms assumed as 5% per generation.

The strategies differ in maximum lifespan of developmental arrest of the diapausing forms. Population fluctuations are presented as relative values of standard deviations of the carrying capacity. The dotted line indicate cross-section presented on the next graph.

Fig 3. The example of a final structure of dormant stages formed at the end of simulation by most successful life strategies at high population fluctuation SD = 5K and 5% mortality of dormant forms per generation, indicated by the dotted line on the Fig 2.

Note that the d_max value—the longest diapause in the tested conditions is 17 generations, but it does not offer the highest advantage. The most successful strategy appeared here the strategy number 10 (indicated by dark grey colour).

Fig 4. Cumulative (added up to 100%) proportion of dormant stages, inactive for various number of generations (0–49) formed by all surviving life strategies at the end of the competition experiments at various ranges of population fluctuations and 5% mortality of dormant forms per generation.

Fig 5. Effect of mortality of dormant forms on mean survivorship of life strategies competing for randomly varying resources for 5,000 generations at considerable population fluctuations (when SD = K).