Path-dependent speciation in dynamic fitness landscapes

Species is a fundamental concept in evolutionary biology and biodiversity. However, existing species definitions are often influenced by artificial factors or are challenging in practical application, leading to confusion in species classification. Due to uncertain environmental changes and random genetic drift, the fitness expectations of a population may shift, causing species to evolve to a new evolutionary state based on their current instantaneous fitness within a dynamic fitness landscape. This contrasts with the classic static fitness landscape, where fitness expectations are constant. In a dynamic fitness landscape, speciation may exhibit path dependence, where the evolution of traits follows a probabilistic path, creating feedback that shapes evolutionary trajectories. The path-dependent evolutionary mechanism suggests that species survival within an ecosystem is not directly determined by their fitness but by the probability of their evolutionary pathways. This model also indicates that species can coexist with varying probabilities under limited environmental pressures. Consequently, new species, cryptic species, or sympatric species may emerge via path-dependent evolutionary processes. Within this framework, we developed a mathematical species concept, which may guide future species classification methodologies.