Digital Evolution for Ecology Research: A Review

Abstract

In digital evolution, populations of computational organisms evolve via the same principles that govern natural selection in nature. These platforms have been used to great effect as a controlled system in which to conduct evolutionary experiments and develop novel evolutionary theory. In addition to their complex evolutionary dynamics, many digital evolution systems also produce rich ecological communities. As a result, digital evolution is also a powerful tool for research on eco-evolutionary dynamics. Here, we review the research to date in which digital evolution platforms have been used to address eco-evolutionary (and in some cases purely ecological) questions. This work has spanned a wide range of topics, including competition, facilitation, parasitism, predation, and macroecological scaling laws. We argue for the value of further ecological research in digital evolution systems and present some particularly promising directions for further research.

Environmental connectivity influences the origination of adaptive processes

“…Another factor that has yet to be explored but likely plays a critical role in the emergence of adaptive dynamics is the environment's spatial structure, which mediates the range of possible interactions among its occupants. Spatial structure is also known to influence ecological and evolutionary processes both in natural (Kool et al, 2013) and artificial systems (Dolson and Ofria, 2021;Tomassini, 2005;Plum and Baum, 2022). In this work, we use an artificial ecology model to investigate how different patterns of environmental connectivity influence the probability of adaptive dynamics occurring, a property termed "transitionability" (Leither et al, 2023).…”

avidaR: an R library to perform complex queries on an ontology-based database of digital organisms

“…Over the past 30 years, digital evolution research has established itself as a valuable approach in biology, bridging experimental research with computational modelling ( Ray, 1991 ). The contribution of digital evolution to the development of ecology and evolutionary biology comprises diverse topics such as robustness and evolvability ( Edlund & Adami, 2004 ; Lenski, Barrick & Ofria, 2006 ; Elena et al, 2007 ; Elena & Sanjuán, 2008 ; Fortuna et al, 2017 ), complexity ( Ray, 1997 ; Lenski et al, 1999 ; Adami, Ofria & Collier, 2000 ; Gerlee & Lundh, 2008 ; Ofria, Huang & Torng, 2008 ), phenotypic plasticity ( Clune, Ofria & Pennock, 2007 ; Lalejini et al, 2021 ; Fortuna, 2022 ), the role historical contingency in evolution ( Hagstrom et al, 2004 ; Wagenaar & Adami, 2004 ; Clune et al, 2012 ), ecological interactions among species ( Cooper & Ofria, 2003 ; Johnson & Wilke, 2004 ; Zaman, Devangam & Ofria, 2011 ; Fortuna et al, 2013 ; Zaman et al, 2014 ; Dolson & Ofria, 2021 ), gene regulatory networks ( Lenski et al, 2003 ; Edlund & Adami, 2004 ; Covert et al, 2013 ), genomic architecture ( Wilke et al, 2001 ; Knibbe et al, 2005 ; Adami, 2006 ; Knibbe et al, 2007 ; Gerlee & Lundh, 2008 ; Batut et al, 2013 ; Gupta et al, 2016 ), evolution of sex ( Chandler, Ofria & Dworkin, 2012 ), and evolution of cooperation ( Goings et al, 2004 ; Knoester, McKinley & Ofria, 2007 ; Clune et al, 2011 ), among others.…”

Ontology for the Avida digital evolution platform

“…Since the pioneering work by Thomas S. Ray 1 30 years ago, digital evolution research has established itself as a valuable approach in biology, bridging experimental research with computational modelling. The contribution of digital evolution to the development of ecology and evolutionary biology comprises diverse topics such as robustness and evolvability 2 – 6 , complexity 1 , 7 – 10 , phenotypic plasticity 11 , 12 , the role historical contingency in evolution 13 – 15 , ecological interactions among species 16 – 21 , gene regulatory networks 2 , 22 , 23 , genomic architecture 9 , 24 – 26 , evolution of sex 27 , and evolution of cooperation 28 – 30 .…”