Constructing random matrices to represent real ecosystems

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dc.contributor.authorJames, Alex
dc.contributor.authorPlank, Michael
dc.contributor.authorRossberg AG
dc.contributor.authorBeecham J
dc.contributor.authorEmmerson M
dc.contributor.authorPitchford JW
dc.date.accessioned2024-07-18T01:49:44Z
dc.date.available2024-07-18T01:49:44Z
dc.date.issued2015
dc.date.updated2023-04-17T20:54:37Z
dc.description.abstractModels of complex systems with n components typically have order n2 parameters because each component can potentially interact with every other. When it is impractical to measure these parameters, one may choose random parameter values and study the emergent statistical properties at the system level. Many influential results in theoretical ecology have been derived from two key assumptions: that species interact with random partners at random intensities and that intraspecific competition is comparable between species. Under these assumptions, community dynamics can be described by a community matrix that is often amenable to mathematical analysis. We combine empirical data with mathematical theory to show that both of these assumptions lead to results that must be interpreted with caution. We examine 21 empirically derived community matrices constructed using three established, independent methods. The empirically derived systems are more stable by orders of magnitude than results from random matrices. This consistent disparity is not explained by existing results on predator-prey interactions. We investigate the key properties of empirical community matrices that distinguish them from random matrices. We show that network topology is less important than the relationship between a species’ trophic position within the food web and its interaction strengths. We identify key features of empirical networks that must be preserved if random matrix models are to capture the features of real ecosystems.
dc.identifier.citationJames A, Plank MJ, Rossberg AG, Beecham J, Emmerson M, Pitchford JW (2015). Constructing random matrices to represent real ecosystems. American Naturalist. 185(5). 680-692.
dc.identifier.doihttp://doi.org/10.1086/680496
dc.identifier.issn0003-0147
dc.identifier.issn1537-5323
dc.identifier.urihttps://hdl.handle.net/10092/107329
dc.languageEnglish
dc.publisherUNIV CHICAGO PRESS
dc.rightsAll rights reserved unless otherwise stated
dc.rights.urihttp://hdl.handle.net/10092/17651
dc.subjectScience & Technology
dc.subjectLife Sciences & Biomedicine
dc.subjectEcology
dc.subjectEvolutionary Biology
dc.subjectEnvironmental Sciences & Ecology
dc.subjectcommunity matrix
dc.subjectcomplexity
dc.subjectfood web
dc.subjectinteraction strength
dc.subjectstability
dc.subjectpredator-prey interaction
dc.subjectASSEMBLING FOOD WEBS
dc.subjectINTERACTION STRENGTHS
dc.subjectBODY-SIZE
dc.subjectECOLOGICAL NETWORKS
dc.subjectMODEL-ECOSYSTEMS
dc.subjectTRIVARIATE PATTERNS
dc.subjectSTABILITY
dc.subjectCOMPLEX
dc.subjectCONSEQUENCES
dc.subjectARCHITECTURE
dc.subject.anzsrc06 Biological Sciences
dc.subject.anzsrc49 - Mathematical sciences
dc.titleConstructing random matrices to represent real ecosystems
dc.typeJournal Article
uc.collegeFaculty of Engineering
uc.departmentMathematics and Statistics
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