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The dynamics of urban water use are characterized by spatial and temporal variability that is influenced by associated factors at different scales. Thus it is important to capture the relationship between urban water use and its determinants in a spatio-temporal framework in order to enhance understanding and management of urban

The dynamics of urban water use are characterized by spatial and temporal variability that is influenced by associated factors at different scales. Thus it is important to capture the relationship between urban water use and its determinants in a spatio-temporal framework in order to enhance understanding and management of urban water demand. This dissertation aims to contribute to understanding the spatio-temporal relationships between single-family residential (SFR) water use and its determinants in a desert city. The dissertation has three distinct papers to support this goal. In the first paper, I demonstrate that aggregated scale data can be reliably used to study the relationship between SFR water use and its determinants without leading to significant ecological fallacy. The usability of aggregated scale data facilitates scientific inquiry about SFR water use with more available aggregated scale data. The second paper advances understanding of the relationship between SFR water use and its associated factors by accounting for the spatial and temporal dependence in a panel data setting. The third paper of this dissertation studies the historical contingency, spatial heterogeneity, and spatial connectivity in the relationship of SFR water use and its determinants by comparing three different regression models. This dissertation demonstrates the importance and necessity of incorporating spatio-temporal components, such as scale, dependence, and heterogeneity, into SFR water use research. Spatial statistical models should be used to understand the effects of associated factors on water use and test the effectiveness of certain management policies since spatial effects probably will significantly influence the estimates if only non-spatial statistical models are used. Urban water demand management should pay attention to the spatial heterogeneity in predicting the future water demand to achieve more accurate estimates, and spatial statistical models provide a promising method to do this job.
ContributorsOuyang, Yun (Author) / Wentz, Elizabeth (Thesis advisor) / Ruddell, Benjamin (Thesis advisor) / Harlan, Sharon (Committee member) / Janssen, Marcus (Committee member) / Arizona State University (Publisher)
Created2013
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Drawing from the fields of coastal geography, political ecology, and institutions, this dissertation uses Cape Cod, MA, as a case study, to investigate how chronic and acute climate-related coastal hazards, socio-economic characteristics, and governance and decision-making interact to produce more resilient or at-risk coastal communities. GIS was used to model

Drawing from the fields of coastal geography, political ecology, and institutions, this dissertation uses Cape Cod, MA, as a case study, to investigate how chronic and acute climate-related coastal hazards, socio-economic characteristics, and governance and decision-making interact to produce more resilient or at-risk coastal communities. GIS was used to model the impacts of sea level rise (SLR) and hurricane storm surge scenarios on natural and built infrastructure. Social, gentrification, and tourism indices were used to identify communities differentially vulnerable to coastal hazards. Semi-structured interviews with planners and decision-makers were analyzed to examine hazard mitigation planning.

The results of these assessments demonstrate there is considerable variation in coastal hazard impacts across Cape Cod towns. First, biophysical vulnerability is highly variable with the Outer Cape (e.g., Provincetown) at risk for being temporarily and/or permanently isolated from the rest of the county. In most towns, a Category 1 accounts for the majority of inundation with impacts that will be intensified by SLR. Second, gentrification in coastal communities can create new social vulnerabilities by changing economic bases and disrupting communities’ social networks making it harder to cope. Moreover, higher economic dependence on tourism can amplify towns’ vulnerability with reduced capacities to recover. Lastly, low political will is an important barrier to effective coastal hazard mitigation planning and implementation particularly given the power and independence of town government on Cape Cod. Despite this independence, collaboration will be essential for addressing the trans-boundary effects of coastal hazards and provide an opportunity for communities to leverage their limited resources for long-term hazard mitigation planning.

This research contributes to the political ecology of hazards and vulnerability research by drawing from the field of institutions, by examining how decision-making processes shape vulnerabilities and capacities to plan and implement mitigation strategies. While results from this research are specific to Cape Cod, it demonstrates a broader applicability of the “Hazards, Vulnerabilities, and Governance” framework for assessing other hazards (e.g., floods, fires, etc.). Since there is no “one-size-fits-all” approach to mitigating coastal hazards, examining vulnerabilities and decision-making at local scales is necessary to make resiliency and mitigation efforts specific to communities’ needs.
ContributorsGentile, Lauren Elyse (Author) / Bolin, Bob (Thesis advisor) / Wentz, Elizabeth (Committee member) / White, Dave (Committee member) / York, Abigail (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Food production and consumption directly impacts the environment and human health. Protein in particular has significant cultural and health implications, and how people make decisions about what type of protein they eat has not been studied directly. Many decision tools exist to offer recommendations for seafood, but neglect livestock or

Food production and consumption directly impacts the environment and human health. Protein in particular has significant cultural and health implications, and how people make decisions about what type of protein they eat has not been studied directly. Many decision tools exist to offer recommendations for seafood, but neglect livestock or plant protein. This study attempts to address these shortcomings in food decision science and tools by asking the questions: 1) What qualities of a dietary protein-based decision tool make it effective? 2) What do people consider when making decisions about what type of protein to consume? Using literature review, meta-analysis, and surveys, this study attempts to determine how the knowledge gained from answering these questions can be used to develop an electronic tool to engage consumers in making sustainable and healthy decisions about protein consumption. The data show that, given environmental and health information about the protein types, people in the sample of farmers market shoppers are more likely to purchase wild salmon and organically grown soybeans, and less likely to purchase grain-fed beef. However, the order of preference among the six types of protein did not change. Additional results suggest that there is a disconnect between consumers and sources of dietary protein, indicating a need for improved education. Inconsistency in labeling and information regarding protein types is a large source of confusion for consumers who participated in the survey, highlighting the need for transparency. Results of this study suggest that decisions tools may help improve decision making, but new ways of using them need to be considered to achieve this.
ContributorsGeren, Sarah (Author) / Gerber, Leah (Thesis advisor) / Minteer, Ben (Committee member) / Wentz, Elizabeth (Committee member) / Arvai, Joseph (Committee member) / Arizona State University (Publisher)
Created2015