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dc.contributor.authorKuhn Córdova, Angela M.
dc.date.accessioned2017-10-03T17:42:45Z
dc.date.available2017-10-03T17:42:45Z
dc.identifier.urihttp://hdl.handle.net/10222/73354
dc.description.abstractWhile both observational and modelling approaches can improve our understanding of ocean ecology, each type of approach has intrinsic limitations. Direct observations have limited temporal/spatial coverage and many quantities are not easily measured. Models rely on assumptions and parameters that are not always based on direct observation. My thesis research systematically combines observations and models through the use of parameter optimization, and further investigates model behavior with the help of sensitivity analyses and hypothesis-oriented experiments. I apply the optimization formalism in three case studies that revisit paradigms in biological oceanography including drivers of the phytoplankton spring bloom, the importance of trophic interactions in determining rates of primary production, and the biogeochemical role of nitrogen-fixing organisms. The first case study juxtaposes bottom-up and top-down hypotheses to explain the initiation of the phytoplankton spring bloom. Realistic and idealized model simulations reveal that the conceptual bases of both hypotheses are ecological truisms. A spring bloom can develop in the absence of mixed layer fluctuations, and both its magnitude and timing are strongly dependent on nutrient and light availability. Changes in zooplankton grazing modulate phytoplankton biomass but do not produce significant shifts to explain bloom initiation. In the second case study, I compare ecosystem models of different trophic complexity. I found that models of low complexity can accurately respond to bottom-up drivers of phytoplankton phenology; however, aspects like the spring bloom termination, accurate simulation of primary production, and partitioning of nitrogen cycling pathways require a higher degree of complexity that is insufficiently constrained by presently available observations. In the third case study, I demonstrate that the inclusion of specific planktonic traits, such as heterotrophic diazotrophy, is necessary to explain biogeochemical characteristics at certain geographical locations. Despite the regional scope of these study cases, my conclusions provide insights that can be extrapolated to large-scale applications.en_US
dc.language.isoenen_US
dc.subjectmarine ecosystem modelsen_US
dc.subjectparameter optimizationen_US
dc.subjectNorth Atlantic Regionen_US
dc.subjectPhytoplanktonen_US
dc.subjectmodel complexityen_US
dc.subjectRed Seaen_US
dc.subjectNitrogen--Fixationen_US
dc.titleIntegration of Observations and Models for an Improved Understanding of Marine Ecosystem Dynamicsen_US
dc.date.defence2017-09-27
dc.contributor.departmentDepartment of Oceanographyen_US
dc.contributor.degreeDoctor of Philosophyen_US
dc.contributor.external-examinerDr. Marion Gehlenen_US
dc.contributor.graduate-coordinatorDr. Christopher Taggarten_US
dc.contributor.thesis-readerDr. Michael Dowden_US
dc.contributor.thesis-readerDr. Hugh MacIntyreen_US
dc.contributor.thesis-readerDr. Marlon Lewisen_US
dc.contributor.thesis-supervisorDr. Katja Fennelen_US
dc.contributor.ethics-approvalNot Applicableen_US
dc.contributor.manuscriptsYesen_US
dc.contributor.copyright-releaseYesen_US
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