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dc.contributor.advisorSutherland, William
dc.contributor.authorLin, Yangchen
dc.date.accessioned2016-04-13T14:31:19Z
dc.date.available2016-04-13T14:31:19Z
dc.date.issued2015-11-10
dc.identifier.otherPhD.39173
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/254976
dc.description.abstractComplexity science has come into the limelight in recent years as the scientific community begins to grapple with higher-order natural phenomena that cannot be fully explained via the behaviour of components at lower levels of organization. Network modeling and analysis, being a powerful tool that can capture the interconnections that embody complex behaviour, has therefore been at the forefront of complexity science. In ecology, the network paradigm is relatively young and there remain limitations in many ecological network studies, such as modeling only one type of species interaction at a time, lack of realistic network structure, or non-inclusion of community dynamics and environmental stochasticity. I introduce bioenergetic network models that bring together for the first time many of the fundamental structures and mechanisms of species interactions present in real ecological communities. I then use these models to address some outstanding questions that are relevant to understanding ecological networks at the systems level rather than at the level of subsets of interactions. Firstly, I find that realistic red-shifted environmental noise, and synchrony of species responses to noise, are associated with increased variability in ecosystem properties, with implications for predictive ecological modeling which usually assumes white noise. Next, I look at simultaneous species extinction and invasion, finding that as their individual impacts increase, their combined impact becomes decreasingly additive. In addition, the greater the impact of extinction or invasion, the lesser their reversibility via reintroduction or eradication of the species in question. For modifications of pairwise species interactions by third-party species, a phenomenon that has so far been studied one interaction at a time, I find that the many interaction modifications that occur concurrently in a community can collectively have systematic effects on total biomass and species evenness. Finally, examining a higher level of organization in the form of compartmentalized networks, I find that the relationship between intercompartment connectivity and the impacts of species decline depends considerably on network topology and whether the consumer-resource functional response is prey- or ratio-dependent. Overall, the results vary considerably across model communities with different parameterizations, underscoring the contingency and context dependence of nature that scientists and policy makers alike should no longer ignore. This work hopes to contribute to a growing multidisciplinary understanding, appreciation and management of complex systems that is fundamentally transforming the modern world and giving us insights on how to live more harmoniously within our environment.en
dc.language.isoenen
dc.subjectecological networken
dc.subjectcomplexityen
dc.subjectbioenergetic modelen
dc.subjectfood weben
dc.subjectecologyen
dc.subjectspecies interactionen
dc.subjectnature conservationen
dc.subjectenvironmental stochasticityen
dc.subjectpink noiseen
dc.subjectratio dependenceen
dc.subjecttrophic functional responseen
dc.titleMacroscopic insights from mechanistic ecological network models in a data voiden
dc.typeThesisen
dc.type.qualificationlevelDoctoral
dc.type.qualificationnameDoctor of Philosophy (PhD)
dc.publisher.institutionUniversity of Cambridgeen
dc.publisher.departmentDepartment of Zoologyen
dc.identifier.doi10.17863/CAM.16419


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