Dynamics of rapid evolution on the basis of phenotypic adaptation and ecological opportunities

• Published in: Evolutionary intelligence 2024, Vol.17 (4), p.2843-2863
• Main Authors: Pasti, Rodrigo, Politi, Alexandre A., De Castro, Leandro N.
• Format: Article
• Language: English
• Subjects: Adaptation; Applications of Mathematics; Artificial Intelligence; Bioinformatics; Biological evolution; Computation; Control; Ecosystems; Engineering; Knowledge representation; Mathematical and Computational Engineering; Mechatronics; Problem solving; Research Paper; Robotics; Speciation; Statistical Physics and Dynamical Systems
• ISSN: 1864-5909; 1864-5917
• DOI: 10.1007/s12065-024-00915-w

Recent studies have demonstrated that evolution can be observed in a few dozen generations, especially when species occupy a new ecological opportunity due to environmental changes. There are several factors that induce this rapid evolution and are related to the phenotype and its response to the environment. This response is then determined by phenotypic variation, because if patterns of diversity in a population produce a rapid response to an environmental change, then rapid adaptation to the new environment can occur. This paper aims to investigate patterns of evolution of species in an artificial ecosystem, and to highlight some patterns that promote rapid evolution. Understanding how rapid evolution occurs is not only of fundamental importance in understanding evolutionary processes and species conservation, but also to provide support for improving the resolution of certain types of problems, especially those in which the solution is time-variant. To achieve the objectives of this paper, a computational model of Adaptive Radiation was designed using the concepts of Biogeographic Computing, an area of knowledge that studies ecosystems as information processors, a fundamental principle of Natural Computing. Habitats are represented by adaptive surfaces, which in turn are composed of different ecological opportunities. The results show, for example, that dramatic changes in ecosystems can lead to a rapid response and a rapid adaptation to new ecological opportunities, mainly because of the emergent and self-sustaining behaviour promoted by the continuous speciation, extinction and adaptation of species. This emergent dynamic supports the thesis that rapid environmental changes can lead to rapid evolution. This behaviour, in turn, is highly desired when considering time-varying problem solving. If solutions to a problem are changing over time, sometimes it is necessary to rapidly find new solutions.