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dc.date.accessioned2020-06-23T17:46:56Z
dc.date.available2020-06-23T17:46:56Z
dc.date.created2019-12-19T17:53:10Z
dc.date.issued2019
dc.identifier.citationLuo, Tian-Tong Heier, Lise Khan, Zaki Ahmad Hasan, Faraz Reitan, Trond Yasseen, Abdool S Xie, Zi-Xuan Zhu, Jian-Long Yedid, Gabriel . Examining Community Stability in the Face of Mass Extinction in Communities of Digital Organisms. Artificial Life. 2019, 24(4), 250-276
dc.identifier.urihttp://hdl.handle.net/10852/77136
dc.description.abstractDigital evolution is a computer-based instantiation of Darwinian evolution in which short self-replicating computer programs compete, mutate, and evolve. It is an excellent platform for addressing topics in long-term evolution and paleobiology, such as mass extinction and recovery, with experimental evolutionary approaches. We evolved model communities with ecological interdependence among community members, which were subjected to two principal types of mass extinction: a pulse extinction that killed randomly, and a selective press extinction involving an alteration of the abiotic environment to which the communities had to adapt. These treatments were applied at two different strengths, along with unperturbed control experiments. We examined how stability in the digital communities was affected from the perspectives of division of labor, relative shift in rank abundance, and genealogical connectedness of the community's component ecotypes. Mass extinction that was due to a Strong Press treatment was most effective in producing reshaped communities that differed from the pre-treatment ones in all of the measured perspectives; weaker versions of the treatments did not generally produce significant departures from a Control treatment; and results for the Strong Pulse treatment generally fell between those extremes. The Strong Pulse treatment differed from others in that it produced a slight but detectable shift towards more generalized communities. Compared to Press treatments, Pulse treatments also showed a greater contribution from re-evolved ecological doppelgangers rather than new ecotypes. However, relatively few Control communities showed stability in any of these metrics over the whole course of the experiment, and most did not represent stable states (by some measure of stability) that were disrupted by the extinction treatments. Our results have interesting, broad qualitative parallels with findings from the paleontological record, and show the potential of digital evolution studies to illuminate many aspects of mass extinction and recovery by addressing them in a truly experimental manner.
dc.languageEN
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleExamining Community Stability in the Face of Mass Extinction in Communities of Digital Organisms
dc.typeJournal article
dc.creator.authorLuo, Tian-Tong
dc.creator.authorHeier, Lise
dc.creator.authorKhan, Zaki Ahmad
dc.creator.authorHasan, Faraz
dc.creator.authorReitan, Trond
dc.creator.authorYasseen, Abdool S
dc.creator.authorXie, Zi-Xuan
dc.creator.authorZhu, Jian-Long
dc.creator.authorYedid, Gabriel
cristin.unitcode185,15,29,50
cristin.unitnameCentre for Ecological and Evolutionary Synthesis
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2
dc.identifier.cristin1763147
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Artificial Life&rft.volume=24&rft.spage=250&rft.date=2019
dc.identifier.jtitleArtificial Life
dc.identifier.volume24
dc.identifier.issue4
dc.identifier.startpage250
dc.identifier.endpage276
dc.identifier.doihttps://doi.org/10.1162/artl_a_00272
dc.identifier.urnURN:NBN:no-80245
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn1064-5462
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/77136/1/Examining%2BCommunity%2BStability-artl_a_00272.pdf
dc.type.versionPublishedVersion


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