Geography Theses and Dissertations

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    (2022) Cui, Diyang; Wang, Dongdong; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Climate change is driving biodiversity redistribution on Earth, undermining the effectiveness of protected areas (PAs) in conserving global biodiversity. Managing the consequences of biodiversity redistribution and promoting effective conservation necessitates a better understanding of climate shift patterns and species’ ability to track changing climates. Recent studies assessing the effects of climate change on biodiversity have increasingly used velocity metrics to represent climate shifts over space and time. Velocity based on a single climate variable or climate space identified using statistically combined multivariate indices may not be related to biomes or ecosystems and lacks the potential to conduct risk evaluation for biodiversity. The widely used Köppen–Geiger classification scheme provides an effective way to characterize bioclimatic conditions by incorporating multiple climatic indicators and biological information, thus can be a new direction for developing velocity metrics and supporting the development of species distribution models (SDMs). To identify research gaps, this dissertation research first reviews recent detection and assessment studies on past and future projected climate zone changes. Previous studies have shown that accelerated global warming since the 1980s has resulted in changes in climate zones that have been observed over 5% of the global land area. Tropical and arid climate zones are expected to expand into mid and high latitudes, while polar climates are shifting poleward and upward, leading to significant area shrinkage. Given the need for improved historical and future global climate maps with long-term temporal coverage and accurate depiction of fine-grained bioclimatic conditions in climate change studies, the study creates a set of 1 km Köppen-Geiger climate classification maps (KGClim) for six historical periods in 1979–2013 and four future periods in 2020–2099 under RCP2.6, 4.5, 6.0, and 8.5. The new maps offer higher classification accuracy than existing datasets and demonstrate the ability to capture recent and future projected changes in distribution of climate zones. Using the new KGClim dataset, this dissertation calculates the velocity of climate zone shifts to assess exposure risks of global PAs and examines the spatial patterns of near-, mid- and long-term climate shifts projected based on different emission pathways. Based on the findings, under RCP8.5, 38% of global protected land could undergo climate zone shifts at accelerating rates for the remainder of this century. Furthermore, global protected lands are experiencing novel (8% of global protected land) and disappearing (7%) climates, shifts of climates outside current PA networks (8%), and transition to human-dominated land use (6%). The fine-scale velocity metrics reveal spatiotemporal patterns of climate shifts and biodiversity redistribution, which can inform adaptive conservation planning to address the ongoing biodiversity crisis and achieve future conservation goals.
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    Tracking the dynamics of the opioid crisis in the United States over space and time
    (2022) Xia, Zhiyue; Stewart, Kathleen; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Millions of adolescents and adults in the United States suffer from drug problems such as substance use disorder, referring to clinical impairments including mental illnesses and disabilities caused by drugs. The Substance Abuse and Mental Health Services Administration reported the estimated number of illicit drug users increased to 59.3 million in 2020, or 21.4% of the U.S. population, which made drug misuse one of the most concerning public health issues. Opioids are a category of drugs that can be highly addictive, including heroin and synthetic drugs such as fentanyl. Centers for Disease Control and Prevention (CDC) indicated that about 74.8% of drug overdose deaths involved opioids in 2020. The opioid crisis has hit American cities hard, spreading across the U.S. beginning with the west coast, and then expanding to heavily impact the central, mid-Atlantic, and east coast of the U.S. as well as states in the southeast. In this dissertation, I work on three studies to track the dynamics of the opioid crisis in the U.S. over space and time from a geographic perspective using spatiotemporal data science methods including clustering analysis, time-series models and machine learning approaches. The first study focused on the geospatial patterns of illicit drug-related activities (e.g., possession, delivery, and manufacture of opioids) in a typical U.S. city (Chicago as a case study area). By analyzing more than 52,000 reported drug activities, I built a data-driven machine learning model for predicting opioid hot zones and identifying correlated built environment and sociodemographic factors that drove the opioid crisis in an urban setting. The second study of my dissertation is to analyze the opioid crisis in the context of the global pandemic of SARS-CoV-2 (COVID-19). In 2020, COVID-19 outbroke and affected hundreds of millions of people across the globe. The COVID-19 pandemic is also impacting the community of opioid misusers in the U.S. The major research objective of Study 2 is to understand how the opioid crisis is impacted by the COVID-19 pandemic and to find neighborhood characteristics and economic factors that have driven the variations before and during the pandemic. Study 3 focuses on analyzing the crisis risen by synthetic opioids (including fentanyl) that are more potent and dangerous than other drugs. This study analyzed the geographic patterns of synthetic opioids spreading across the U.S. between 2013 and 2020, a period when synthetic opioids rose to be a major risk factor for public health. The significance of this dissertation is that the three studies investigate the opioid crisis in the U.S. in a comprehensive manner and these studies can facilitate public health stakeholders with effective decision making on healthcare planning relating to drug problems. Tracking the dynamics of the opioid crisis by drug type, including modeling and predicting the geographic patterns of opioid misuse involving particular opioids (e.g, heroin and synthetic opioids), can provide an important basis for applying further treatment services and mitigation efforts, and also be useful for assessing current services and efforts.
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    Forest Loss Trajectories and Palm Oil Extent in Indonesia
    (2022) Parker, Diana; Hansen, Matthew; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Tropical forests provide critically important ecosystem services, and they are particularly important for their levels of biodiversity and for the carbon that they store. Yet despite global efforts to slow or halt deforestation, natural forests in the tropics continue to be cleared, primarily for agricultural expansion. Indonesia contains the world’s third largest humid tropical forest area, and for much of the past several decades has experienced alarmingly high rates of deforestation. This began to change in 2017, when deforestation rates dropped precipitously and have since remained low. To better understand how this recent trend compares to historical deforestation patterns, this study used a sample-based approach to estimate annual primary forest loss in Indonesia over a 30-year period, from 1991-2020. Since 1990, Indonesia has lost 28.4 (standard error of +/-0.7) Mha of primary forest – roughly one quarter of its total primary forest area in 1990. One fifth of this area (19.7% +/-1) was cleared during a single two-year period, 1997 and 1998, when millions of hectares of primary forest were burned during a severe El Niño event. I also tracked land use after forest clearing to better understand what drives deforestation in Indonesia and found that more than half of all forests were left idle after clearing, often for years at a time. While some of this was caused by forest fires, like those that occurred during the 1997/98 El Niño event, the majority, 8.5 (+/-0.4) Mha, was actively cleared. Large areas of actively and fire-cleared land remained unused at the end of the study period (4 +/-0.3 and 4.8 +/-0.3 Mha, respectively). However, by 2020, an estimated 40.7% (+/-1.7) of initially unproductive land had also been converted to productive land uses, primarily palm oil production, which covered 16 (+/-0.5) Mha of land in Indonesia in 2020. This included 2.5 (+/- 0.2) Mha of land used to cultivate oil palms that directly replaced primary forests and another 5.3 (+/-0.3) Mha that expanded into previously forested areas one or more years after forest conversion. In the last few years of the study, my sample-derived estimates also confirmed a decline in deforestation after 2016, which had previously been seen in forest loss estimates derived from map pixel counting. From 2017-2020 Indonesia experienced the lowest rates of primary forest clearing observed during the study period. This drop in deforestation occurred after years of increasingly tight restrictions related to primary forest conversion, peatland use, and palm oil expansion, and during a period of heightened public concern about deforestation and land fires following the 2015 El Niño event. It also occurred during a time when palm oil prices were relatively low, and after millions of hectares of idle land had been intentionally created, a phenomenon that is likely closely tied to speculation and land banking. This study provides the most detailed information currently available about historic deforestation trends and land use trajectories after forest clearing in Indonesia, shedding new light on forest change patterns and providing a dataset that could potentially be used in future studies, including for econometric research to quantify the extent to which political and economic factors may have influenced land cover change.
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    Socioeconomic Impacts of Policy Interventions in the Food-Energy-water Nexus
    (2022) Kumar, Ipsita; Sun, Laixiang; Feng, Kuishuang; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    The food-energy-water (FEW) nexus is considered essential for human survival and critical for the achievement of the Sustainable Development Goals. However, pressures on each component of the nexus are growing as a result of population and economic growth. The FEW nexus can also be affected by competition for limited land, climate change, and demand and supply changes. Although government policies targeting one of the components of the nexus will directly affect the others, they are still not accounting for the interconnectedness of all three. The dissertation, through three essays seeks to understand how government policies would affect the FEW nexus, focusing on Thailand or Brazil. The first essay assesses challenges with crop residue burning in Thailand. Additionally, the essay highlights policies implemented that target residue burning or its use and the potential solutions through crop residue use. The second essay examines specific policies on crop residue burning and renewable energy (RE) production to understand their impacts on sustainability. An extended input-output model is run to using policy scenarios for the future to gauge its impacts on total output, gross value added, employment, labor income, key input use, land use, water use and CO2 emissions on Thailand and Northeast Thailand. The final essay explores food and energy security given water supply limitations as water availability greatly impacts availability of food and energy. It uses a region in Sao Paulo, Brazil, where RE policies and other interventions have helped make ethanol production and use cost effective. A model is developed to maximize profits while optimally allocating water to food, energy and municipal water. The study looks at a normal rainfall year, and also runs a future demand change scenario. The dissertation concludes by detailing the challenges that exist, future potential for the FEW nexus policies, limitations and uncertainties. The dissertation establishes that given the interlinked nature of the FEW nexus, policies need to be implemented to account for all three components. The first essay shows that over time, an increasing number of policies in Thailand target crop residue burning through controlling burning or its use in RE production. Although these policies have been implemented, there are still shortcomings in the policy targets for biomass use, and in the large water use by the sector, as highlighted in essay 1 and 2. Essay 2 also demonstrates social, economic and environmental benefits of using crop residue for RE through employment generated, labor income increases, and CO2 emission reduction in Thailand and Northeast Thailand. We also see increasing competition for land for energy, with sugarcane potentially overtaking rice in Northeast Thailand. In essay 3, we see that while Brazil has implemented sound policies on RE, there are water security challenges, and competition between food, energy and municipal water supply. We see that the current infrastructure cannot satisfy future demand, leading to competing demands and equity challenges. Finally, in the conclusion, the research highlights uncertainties about future demand, water supply, technology, price, etc. along with potential policies.
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    Multispectral satellite remote sensing approaches for estimating cover crop performance in Maryland and Delaware
    (2022) THIEME, ALISON; Justice, Chris; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Winter cover crops encompass a range of species planted in late summer and fall for a variety of reasons relating to soil health, nutrient retention, soil compaction, biotic diversity, and erosion prevention. As agricultural intensification continues, the practice of winter cover cropping remains a crucial practice to reduce leaching from agricultural fields. Maryland and Delaware both incentivize cover cropping to meet water quality objectives in the Chesapeake Bay Watershed. These large-scale programs necessitate methods to evaluate cover crop performance over the landscape. Cover crop quantity and quality was measured at 2,700 locations between 2006-2021 with a focus on fields planted to four cereal species: wheat, rye, barley, and triticale. Samples were GPS located and timed with satellite remote sensing observations from SPOT 4, SPOT 5, Landsat 5, Landsat 7, Landsat 8, or Sentinel-2. When paired imagery at 10-30 m spatial resolution , there is a strong relationship between the normalized difference vegetation index (NDVI) and percent ground cover (R2=0.72) as well as NDVI and biomass (as high as R2=0.77). There is also a strong relationship between Δ Red Edge (a combination of 740 nm and 783 nm bands) and nitrogen content (R2=0.75). These equations were applied to Harmonized Landsat Sentinel-2 products and used to estimate cover crop aboveground biomass in ~300,000 ha of Maryland Department of Agricultures and ~60,000 ha of Delaware Association of Conservation Districts enrolled fields from 2019-2021 and grouped by agronomic method. Wintertime and springtime cover crop biomass varied based on planting date, planting method, species, termination date, and termination method. Early planted fields had higher wintertime biomass while fields that delayed termination had higher springtime biomass. Triticale had consistently higher biomass while wheat had the lowest biomass. Fields planted using a drill followed by light tillage or no-till drill had higher biomass, likely due to the better seed-to-soil contact. Fields that were taken to harvest or terminated for on farm use (roller crimped, green chopped) also had higher springtime biomass than other termination methods. Incentives can be used to encourage specific agronomic methods and these findings can be used to inform adaptive management in the Mid-Atlantic Region.