Dynamics of Rapid Evolution on the Basis of Phenotypic Adaptation and Ecological Opportunities

Dynamics of Rapid Evolution on the Basis of Phenotypic Adaptation and Ecological Opportunities | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Dynamics of Rapid Evolution on the Basis of Phenotypic Adaptation and Ecological Opportunities Rodrigo Pasti, Alexandre Politi, Leandro Nunes de Castro This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3659536/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Mar, 2024 Read the published version in Evolutionary Intelligence → Version 1 posted 7 You are reading this latest preprint version Abstract 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. rapid evolution biogeography biogeographic computing adaptive radiation natural computing Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 02 Mar, 2024 Read the published version in Evolutionary Intelligence → Version 1 posted Editorial decision: Revision requested 20 Dec, 2023 Reviews received at journal 13 Dec, 2023 Reviewers agreed at journal 04 Dec, 2023 Reviewers invited by journal 30 Nov, 2023 Editor assigned by journal 29 Nov, 2023 Submission checks completed at journal 29 Nov, 2023 First submitted to journal 24 Nov, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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