{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T19:10:14Z","timestamp":1758741014770,"version":"3.44.0"},"reference-count":87,"publisher":"MIT Press","issue":"2","content-domain":{"domain":["direct.mit.edu"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Evolutionary dynamics are shaped by a variety of fundamental, generic drivers, including spatial structure, ecology, and selection pressure. These drivers impact the trajectory of evolution and have been hypothesized to influence phylogenetic structure. For instance, they can help explain natural history, steer behavior of contemporary evolving populations, and influence the efficacy of application-oriented evolutionary optimization. Likewise, in inquiry-oriented Artificial Life systems, these drivers constitute key building blocks for open-ended evolution. Here we set out to assess (a) if spatial structure, ecology, and selection pressure leave detectable signatures in phylogenetic structure; (b) the extent, in particular, to which ecology can be detected and discerned in the presence of spatial structure; and (c) the extent to which these phylogenetic signatures generalize across evolutionary systems. To this end, we analyze phylogenies generated by manipulating spatial structure, ecology, and selection pressure within three computational models of varied scope and sophistication. We find that selection pressure, spatial structure, and ecology have characteristic effects on phylogenetic metrics, although these effects are complex and not always intuitive. Signatures have some consistency across systems when using equivalent taxonomic unit definitions (e.g., individual, genotype, species). Furthermore, we find that sufficiently strong ecology can be detected in the presence of spatial structure. We also find that, while low-resolution phylogenetic reconstructions can bias some phylogenetic metrics, high-resolution reconstructions recapitulate them faithfully. Although our results suggest a potential for evolutionary inference of spatial structure, ecology, and selection pressure through phylogenetic analysis, further methods development is needed to distinguish these drivers\u2019 phylometric signatures from each other and to appropriately normalize phylogenetic metrics. With such work, phylogenetic analysis could provide a versatile tool kit with which to study large-scale, evolving populations.<\/jats:p>","DOI":"10.1162\/artl_a_00470","type":"journal-article","created":{"date-parts":[[2025,4,29]],"date-time":"2025-04-29T09:27:52Z","timestamp":1745918872000},"page":"129-152","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":0,"title":["Ecology, Spatial Structure, and Selection Pressure Induce Strong Signatures in Phylogenetic Structure"],"prefix":"10.1162","volume":"31","author":[{"given":"Matthew Andres","family":"Moreno","sequence":"first","affiliation":[{"name":"University of Michigan, Department of Ecology and Evolutionary Biology, Center for the Study of Complex Systems, Michigan Institute for Data and AI in Society. morenoma@umich.edu"}]},{"given":"Santiago","family":"Rodriguez-Papa","sequence":"additional","affiliation":[{"name":"Michigan State University, Department of Computer Science and Engineering"}]},{"given":"Emily","family":"Dolson","sequence":"additional","affiliation":[{"name":"Michigan State University, Department of Computer Science and Engineering, Program in Ecology, Evolution, and Behavior"}]}],"member":"281","published-online":{"date-parts":[[2025,5,1]]},"reference":[{"key":"2025092414361119500_bib1","first-page":"606","article-title":"Indefinitely scalable computing = Artificial Life engineering","volume-title":"ALIFE 14: The fourteenth international conference on the synthesis and simulation of living systems","author":"Ackley","year":"2014"},{"issue":"2","key":"2025092414361119500_bib2","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1038\/nrg1771","article-title":"Digital genetics: Unravelling the genetic basis of evolution","volume":"7","author":"Adami","year":"2006","journal-title":"Nature Reviews Genetics"},{"issue":"1","key":"2025092414361119500_bib3","doi-asserted-by":"publisher","first-page":"367","DOI":"10.5194\/cp-9-367-2013","article-title":"A new global reconstruction of temperature changes at the Last Glacial Maximum","volume":"9","author":"Annan","year":"2013","journal-title":"Climate of the Past"},{"issue":"1","key":"2025092414361119500_bib4","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1146\/annurev.ecolsys.33.010802.150500","article-title":"Estimating divergence times from molecular data on phylogenetic and population genetic timescales","volume":"33","author":"Arbogast","year":"2002","journal-title":"Annual Review of Ecology and Systematics"},{"issue":"1","key":"2025092414361119500_bib5","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1016\/j.copbio.2010.10.013","article-title":"Measuring growth rate in high-throughput growth phenotyping","volume":"22","author":"Blomberg","year":"2011","journal-title":"Current Opinion in Biotechnology"},{"key":"2025092414361119500_bib6","doi-asserted-by":"publisher","first-page":"1398","DOI":"10.1109\/CEC.2003.1299834","article-title":"Is increased diversity in genetic programming beneficial? 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