Using an Artificial Ecosystem to Understand Living Ecosystems
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Community ecosystems at very different levels of biological organization often have similar properties. Coexistence of multiple species, cross-feeding, biodiversity and fluctuating population dynamics are just a few of the properties that arise in a range of ecological settings. Here we develop a bottom-up model of consumer-resource interactions, in the form of an artificial ecosystem “number soup”. Our model reflects basic properties of many bacterial and other community ecologies. We demonstrate four key properties of the number soup model: (1) Communities self-organize so that all available resources are fully consumed; (2) Reciprocal cross-feeding is a common evolutionary outcome, which evolves in a number of stages, and many transitional species are involved; (3) The evolved ecosystems are often “robust yet fragile”, with keystone species required to prevent the whole system from collapsing; (4) Nonequilibrium dynamics and chaotic patterns are general properties, readily generating rich biodiversity. These properties have been observed in empirical ecosystems, ranging from bacteria to rainforests. Establishing similar properties in an evolutionary model as simple as the number soup suggests that these four properties are ubiquitous features of all community ecosystems, and raises questions about how we interpret ecosystem structure in the context of natural selection. In Chapter 1, the motivation of the model and other researchers’ works are described. Chapter 2 is the paper about the number soup model, in a journal format. In Chapter 3, I elaborate all the mathematical details of the model, which were not fully discussed in that paper in Chapter 2. In Chapter 4, I list some of the intriguing questions and points related to the number soup model, and give a description of the whole plan for my PhD studies and the future wok that will be done in the remaining PhD study.
Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2016. , 85 p.
U.U.D.M. report / Uppsala University, Department of Mathematics, ISSN 1101-3591 ; 2016:5
Mathematical Biology, Mathematical Modeling, Emergence, Ecosystem Evolution, Community Ecology
Research subject Mathematics with specialization in Applied Mathematics
IdentifiersURN: urn:nbn:se:uu:diva-306639OAI: oai:DiVA.org:uu-306639DiVA: diva2:1043679
2016-11-21, 64119, Ångströmlaboratoriet, Lägerhyddsvägen 1, Uppsala, 13:15 (English)
Gerlee, Philip, Assistant Professor
Sumpter, David, Professor