Nevermann Daniel Henrik, Gros Claudius, Lennon Jay T
Institute for Theoretical Physics, Goethe-Universitat Frankfurt, Frankfurt, Germany.
Department of Biology, Indiana University, Bloomington, IN 47405, USA.
Proc Biol Sci. 2025 Jan;292(2039):20242543. doi: 10.1098/rspb.2024.2543. Epub 2025 Jan 29.
The factors contributing to the persistence and stability of life are fundamental for understanding complex living systems. Organisms are commonly challenged by harsh and fluctuating environments that are suboptimal for growth and reproduction, which can lead to extinction. Many species contend with unfavourable and noisy conditions by entering a reversible state of reduced metabolic activity, a phenomenon known as dormancy. Here, we develop Spore Life, a model to investigate the effects of dormancy on population dynamics. It is based on Conway's Game of Life (GoL), a deterministic cellular automaton where simple rules govern the metabolic state of an individual based on the metabolic state of its neighbours. For individuals that would otherwise die, Spore Life provides a refuge in the form of an inactive state. These dormant individuals (spores) can resuscitate when local conditions improve. The model includes a parameter [Formula: see text] that controls the survival probability of spores, interpolating between GoL ([Formula: see text]) and Spore Life ([Formula: see text]), while capturing stochastic dynamics in the intermediate regime ([Formula: see text]). In addition to identifying the emergence of unique periodic configurations, we find that spore survival increases the average number of active individuals and buffers populations from extinction. Contrary to expectations, stabilization of the population is not the result of a large and long-lived seed bank. Instead, the demographic patterns in Spore Life only require a small number of resuscitation events. Our approach yields novel insight into what is minimally required for the origins of complex behaviours associated with dormancy and the seed banks that they generate.
促成生命持久性和稳定性的因素是理解复杂生命系统的基础。生物体通常面临着恶劣且多变的环境,这些环境对于生长和繁殖而言并非最优,可能导致物种灭绝。许多物种通过进入代谢活动降低的可逆状态(即休眠现象)来应对不利和嘈杂的条件。在此,我们开发了“孢子生命”模型,以研究休眠对种群动态的影响。它基于康威生命游戏(GoL),这是一种确定性细胞自动机,其中简单规则根据个体邻居的代谢状态来控制个体的代谢状态。对于那些否则就会死亡的个体,“孢子生命”模型以非活动状态的形式提供了一个避难所。这些休眠个体(孢子)在局部条件改善时可以复苏。该模型包含一个参数[公式:见原文],它控制孢子的存活概率,在GoL([公式:见原文])和“孢子生命”模型([公式:见原文])之间进行插值,同时在中间状态([公式:见原文])捕捉随机动态。除了识别独特周期构型的出现,我们发现孢子存活增加了活跃个体的平均数量,并使种群免于灭绝。与预期相反,种群的稳定并非源于大量且长寿的种子库。相反,“孢子生命”模型中的人口统计学模式仅需要少量的复苏事件。我们的方法为与休眠及其产生的种子库相关的复杂行为起源所需的最低条件提供了新的见解。