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dc.contributor.authorFair, Kathyrn
dc.date.accessioned2020-06-01 16:14:37 (GMT)
dc.date.available2020-06-01 16:14:37 (GMT)
dc.date.issued2020-06-01
dc.date.submitted2020-05-27
dc.identifier.urihttp://hdl.handle.net/10012/15966
dc.description.abstractAs we move further into the Anthropocene, numerous challenges to sustainable development present themselves. Questions abound: How do we feed a growing population? What steps must we take to conserve ecologically valuable ecosystems? How can we create the greatest improvements in global food security and equality? The increasing impacts of climate change on Earth’s systems only serve to heighten the importance of, and difficulty in, answering these questions. Given the complexity of the systems -- trade networks, ecosystems, etc. -- to which these questions pertain, it is crucial that we gain a comprehensive understanding of their dynamics before taking action. Without this, any changes to these complex human-environment systems could have unintended and potentially calamitous effects. As such, the value of modelling techniques for exploring the dynamics and potential futures of these complex systems is high. This thesis uses models to examine the behaviour and possible future trajectories of 3 such systems. We begin by delving into the temporal evolution of the global wheat trade network using a dynamic network model. A preferential attachment mechanism is found to provide a good fit to the empirical network, based on several key metrics. Our modelled trade network is quite fragile to shocks. However, as it grows towards 2050, its resilience to attacks will increase. Next, we implement a spatially-explicit agent-based model for the forest-grassland mosaics of Southern Brazil. These ecologically valuable systems are fragile, with simulated mosaics persisting only over a narrow range of conditions. Mosaics may cease to exist in scenarios where climate change impacts greatly reduce fire-mediated recruitment thresholds. When climate change effects are less severe mosaics that do not disappear exhibit substantial alterations to their spatial structure. Finally, we explore the dynamics of a human metapopulation linked through a trade network. Centrality to the network is key to obtaining high food per capita, and differences in centrality may result in inequalities between patches. Inequalities and issues of food security can also arise when patch-level behaviours differ. Larger and more regular network structures facilitate more equal patch-level outcomes and higher levels of food security. However, when patch-level import behaviours are heterogeneous, the best course of action is to first modify these behaviours before adjusting the network topology. Across all 3 projects, modelled systems display complex behaviours. This emphasizes the necessity of further development of models for complex human-environment systems that can provide a more complete understanding of system dynamics and potential futures. The insights gained from these models can be used to inform policies for facilitating positive outcomes in real-world complex systems.en
dc.language.isoenen
dc.publisherUniversity of Waterlooen
dc.subjectecological modellingen
dc.subjectcoupled human-environment systemsen
dc.subjectsustainabilityen
dc.subjectresilienceen
dc.subjectmetapopulation modellingen
dc.subjecttrade networksen
dc.subjectclimate changeen
dc.subjectagent-based modellingen
dc.subjectdynamic network modellingen
dc.subjectfood securityen
dc.subjectland useen
dc.titleModelling resilience and sustainability of complex human-environment systems in agriculture and ecologyen
dc.typeDoctoral Thesisen
dc.pendingfalse
uws-etd.degree.departmentApplied Mathematicsen
uws-etd.degree.disciplineApplied Mathematicsen
uws-etd.degree.grantorUniversity of Waterlooen
uws-etd.degreeDoctor of Philosophyen
uws.contributor.advisorBauch, Chris
uws.contributor.advisorAnand, Madhur
uws.contributor.affiliation1Faculty of Mathematicsen
uws.published.cityWaterlooen
uws.published.countryCanadaen
uws.published.provinceOntarioen
uws.typeOfResourceTexten
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen


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