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dc.contributor.advisorEnquist, Brian Jen_US
dc.contributor.authorStegen, James
dc.creatorStegen, Jamesen_US
dc.date.accessioned2011-12-06T13:27:36Z
dc.date.available2011-12-06T13:27:36Z
dc.date.issued2009en_US
dc.identifier.urihttp://hdl.handle.net/10150/194843
dc.description.abstractUnderstanding the processes responsible for gradients in biodiversity is a central goal of ecological research. In order to elucidate the processes responsible for community assembly and structure, it is useful to adopt a functional trait approach to community ecology. This is because species names provide little information regarding how constituent species interact. In addition, assembly rules based on species names are likely to become intractably complex with increasing species richness but rules based on traits can provide simple, broadly applicable. In turn, generality is gained by emphasizing functional traits. Here I first build from a previously published model that merged metabolic theory with a model of community evolution and assembly to derive a general assembly rule based on a continuous functional trait and compare this rule with a broad suite of empirical data (Chapter 1). However, linking metabolism to macroevolutionary rates and patterns has thus far been limited to non-ecological, static models. These models are not inconsistent with empirical data, but are relatively limited in their predictive ability (Chapter 2). I thus next develop a fully dynamic `metabolic theory of biodiversity' (MTB) that explicitly implements the qualitative framework proposed in Allen et al. (2007). With this model I examine the influence of temperature dependent mutation rate on speciation rate, extinction rate and species richness (Chapter 2). The model predicts a variable influence of temperature, but the processes responsible for this variation are not immediately clear. I subsequently conduct a detailed analysis elucidating the key processes that allow/constrain a strong influence of temperature dependent mutation rate on species richness (Chapter 3). In addition to mutation rate, temperature-dependent metabolism can influence ecological (feeding and mortality) and ecosystem (e.g. decomposition and in turn nutrient supply) rates. As such, I extend the model developed in chapters 1-3 to incorporate these additional temperature dependencies and derive predictions for the influence of temperature over species richness (Chapter 4).
dc.language.isoENen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectbody sizeen_US
dc.subjectcommunity assemblyen_US
dc.subjectevolutionen_US
dc.subjectmetabolic theoryen_US
dc.subjectspecies richnessen_US
dc.subjecttemperatureen_US
dc.titleAdaptive Diversification of Interaction Networksen_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.identifier.oclc659750931en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.contributor.committeememberFerriere, Regisen_US
dc.contributor.committeememberMcGill, Brian Jen_US
dc.contributor.committeememberSaleska, Scotten_US
dc.identifier.proquest10312en_US
thesis.degree.disciplineEcology & Evolutionary Biologyen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.namePh.D.en_US
refterms.dateFOA2018-08-25T04:07:33Z
html.description.abstractUnderstanding the processes responsible for gradients in biodiversity is a central goal of ecological research. In order to elucidate the processes responsible for community assembly and structure, it is useful to adopt a functional trait approach to community ecology. This is because species names provide little information regarding how constituent species interact. In addition, assembly rules based on species names are likely to become intractably complex with increasing species richness but rules based on traits can provide simple, broadly applicable. In turn, generality is gained by emphasizing functional traits. Here I first build from a previously published model that merged metabolic theory with a model of community evolution and assembly to derive a general assembly rule based on a continuous functional trait and compare this rule with a broad suite of empirical data (Chapter 1). However, linking metabolism to macroevolutionary rates and patterns has thus far been limited to non-ecological, static models. These models are not inconsistent with empirical data, but are relatively limited in their predictive ability (Chapter 2). I thus next develop a fully dynamic `metabolic theory of biodiversity' (MTB) that explicitly implements the qualitative framework proposed in Allen et al. (2007). With this model I examine the influence of temperature dependent mutation rate on speciation rate, extinction rate and species richness (Chapter 2). The model predicts a variable influence of temperature, but the processes responsible for this variation are not immediately clear. I subsequently conduct a detailed analysis elucidating the key processes that allow/constrain a strong influence of temperature dependent mutation rate on species richness (Chapter 3). In addition to mutation rate, temperature-dependent metabolism can influence ecological (feeding and mortality) and ecosystem (e.g. decomposition and in turn nutrient supply) rates. As such, I extend the model developed in chapters 1-3 to incorporate these additional temperature dependencies and derive predictions for the influence of temperature over species richness (Chapter 4).


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