The educational quality of Erie County and Buffalo, New York, as represented by school district performance was examined and the relationship between school district performance and the social environment was analyzed. Socioeconomic status, social stability and race were all found to be strongly correlated to school district performance. Within Erie County, Buffalo has the poorest school performance levels while Snyder and Williamsville, two high status suburban districts, have the highest school performance levels. The overall spatial pattern of school district performance based on the PEP test results for 1974 reveal a strong correspondence between school district performance and the social structure of Erie County. The distribution of Regents Scholarship winners within Erie County also straws the strong relationship between social status and school performance. The performance of the Buffalo schools schools a strong relationship to the social structure of the city. The performance of third, sixth and ninth grade pupils on reading and math PEP tests reveals an inner city-periphery contrast in school performance, especially for the elementary schools. The low-achieving schools are located in the inner city, especially the black ghetto, and the high-achieving schools are located on the periphery of the city. Elementary school performance is strongly correlated to income (SES), minority enrollment (race) and the percentage of broken hares (family stability).

Throughout the Spanish poetic production of the 20th century, cities have developed a relevant role as a recurring space at the same time as society urbanized and an exodus took place from agricultural areas to the work centers offered by the cities. Since the second half of the 19th century the city has been the meeting place for people from different backgrounds where the poet found, from his exclusive point of view, a new universe to develop in his work. However, the evolution of capitalist society sponsored the poet's transition from an artist to a worker in the service sector, now able to describe the everyday life through that "other voice" that Octavio Paz so well exhibited in his work (Paz 1990). This way, I argue that with the passage of time and the disappearance of the romanticized figure of the poet, writers who describe the daily commute of the inhabitants of the cities emerged among the working classes through a simple style that has come to be related with other transcultural artistic movements such as Minimalism or Dirty Realism. My dissertation studies the representation of the urban working class in three contemporary Spanish poets: Karmelo C. Iribarren, Itziar Mínguez Arnáiz, and Fernando del Val. I analyze their shared poetics of the city with a focus on the omnipresent common objects that seem to represent the urban everyday life. In Chapter One, I develop a conceptual “trialectic” lens through which to approach all three poets based on the convergence of urban studies, the analysis of poetic form in relation to the artistic current of Minimalism, and the imprint that U.S. author Raymond Carver-as both literary persona and style-left on Spain since his publication in translation in the late 1980s. In Chapter Two, I analyze how the processes of gentrification and privatization of public spaces reflect an experience of suffering by the working class in Iribarren's poetry. In Chapter Three, I study gender-space relations as I analyze what it means for working class women to walk the city and occupy public spaces traditionally reserved for men in Mínguez Arnáiz’ poetry. In Chapter Four, I follow Spanish expatriates across the Atlantic Ocean in the wake of the 2008 financial crisis to explore resistance movements against spatial exploitation that force working classes into geographical oblivion in Del Val's “New York trilogy.” To carry out this project, I propose to analyze the works of these three authors emphasizing not only the common characteristics that each one of them presents but also those that make them unique. With this, I intend to find out the paths Spanish poetry is taking and how this realist-style poetry differs from the realistic trends of "the poetry of experience" and the "dirty realism" so popular in the 80s and 90s. I argue that with the entry of the new millennium and especially with the extensive implementation of neoliberal policies that led to the economic crisis of 2008, there is a boom in the poetry of resistance that seeks to prove that an egalitarian right to the city is more urgent than ever.

Several studies in hydrology have reported differences in outcomes between models in which spatial autocorrelation (SAC) is accounted for and those in which SAC is not. However, the capacity to predict the magnitude of such differences is still ambiguous. In this thesis, I hypothesized that SAC, inherently possessed by a response variable, influences spatial modeling outcomes. I selected ten watersheds in the USA and analyzed them to determine whether water quality variables with higher Moran’s I values undergo greater increases in the coefficient of determination (R²) and greater decreases in residual SAC (rSAC) after spatial modeling. I compared non-spatial ordinary least squares to two spatial regression approaches, namely, spatial lag and error models. The predictors were the principal components of topographic, land cover, and soil group variables. The results revealed that water quality variables with higher inherent SAC showed more substantial increases in R² and decreases in rSAC after performing spatial regressions. In this study, I found a generally linear relationship between the spatial model outcomes (R² and rSAC) and the degree of SAC in each water quality variable. I suggest that the inherent level of SAC in response variables can predict improvements in models before spatial regression is performed. The benefits of this study go beyond modeling selection and performance, it has the potential to uncover hydrologic connectivity patterns that can serve as insights to water quality managers and policy makers.

Wetlands are one of the most productive ecosystems in the world, providing a range of services, including: water quality improvement, flood mitigation, erosion control, habitat, and carbon storage. It is estimated that Tennessee has lost 60% of its original 2 million acres of pre-European settlement wetlands. Recently, increased funding has been made available for wetland restoration and expansion. In response, the Cherokee National Forest has proposed a range of wetland restoration actions within the Paint Creek Watershed to expand and restore some of the existing bogs and fens, including the Cutshaw Bog, a 163,864 m2 wetland located 32 km south of Greeneville, TN. The U.S. Forest Service has proposed a new expanded wetland boundary to result from restoration efforts. However, to assess the potential for success, current wetland indicators based on soil color, texture, depth, drainage, sulfide materials, and iron concentrations were examined. Sampling locations were identified by overlaying a grid, composed of 64 cells, each 40.5 meter by 40.5 meter in size. Soil cores were extracted up to a depth of 0.6 meters from each sampling cell and evaluated in situ for hydric soil properties using the Eastern Mountains and Piedmont Army Corps of Engineers Wetlands Delineation Manual. Soil physical (texture, bulk density, moisture content) and chemical (pH, cation exchange capacity, % base saturation, Nitrogen, Bray II Phosphorus, Iron, Zinc, and Total Carbon Content) properties were evaluated in the laboratory. Results indicated 47% of samples taken within the proposed wetland expansion area currently have hydric soil characteristics and were located along drainage lines. Presence of hydric soils was correlated with soil physicochemical properties including bulk density, moisture content, sulfur and phosphorus concentrations, iron, and other metals. Statistical analyses for the northern section and southern section of the bog were completed separately, as they were physically divided by a French drain structure. Logistic regression models were developed using properties most strongly correlated with the presence of hydric soil. For the northern section, bulk density and iron were retained in the model, while for the southern section, iron was retained. A spatial model for the presence of hydric soil was developed by spatially interpolating the covariates through kriging. Next, a probability map was created from the logistic regression equation with raster math in ArcGIS Pro. Results indicate that Cutshaw Bog’s area cannot be expanded to the original proposed boundary provided by the US Forest Service and a new recommended boundary was delineated from the probability map. The results of this data driven approach will assist the Forest Service in targeted wetland restoration efforts at the Cutshaw Bog.

Use of satellite imagery makes environmental monitoring easy and convenient with little of the logistics involved in planning sampling campaigns. Colored dissolved organic matter (CDOM) is an important component to track as a proxy for the large pool of dissolved organic carbon (DOC). In a world contending with the looming issue of global climate change, the ability to investigate the carbon cycle of inland to coastal environments allows for examination of the magnitude of carbon flowing through the system and potential changes over years. The Arctic region is a critical area for climate change impacts but is a difficult landscape for sampling implementation and is thus an excellent target for satellite monitoring. This thesis focuses on the North Slopes region of Alaska to take advantage of the Toolik Lake monitoring site. Landsat 8 imagery has the appropriate spatial, spectral, and temporal resolutions for use in inland water and coastal environments. There are numerous developed algorithms for CDOM estimations, but many algorithms are designed for specific regions. A special challenge in inland environments is the bottom reflectance contribution to the outgoing light signal. An algorithm designed specifically for optically-shallow water environments (SBOP) was tested against two algorithms designed for optically-deep water environments (QAA-CDOM, K05). The relationship between CDOM and DOC was also investigated and used as further validation for algorithm performance. The SBOP algorithm shows promise iv alongside QAA-CDOM at estimating CDOM absorption, but the number of validation point makes pinpointing one algorithm difficult. All algorithms performed well at estimating DOC concentrations.

Beaver Creek is an impaired streams that is not supporting its designated use for recreation due to Escherichia coli (E.coli), and sediment. To address this problem, this thesis was divided into two studies. The first study explored changes in Land Use Land Cover (LULC), and its impact on surface water quality. Changes in E.coli load between 1997-2001 and 2014-2018 were analyzed. Also, Landsat data of 2001, and 2018 were examined in Terrset 18.31. Mann-Whitney test only showed a significant reduction in E.coli for one site. Negative correlation was established between E.coli load, and Developed LULC, Forest LULC, and Cultivated LULC. The second study modelled discharge for Beaver Creek watershed using HEC-HMS. This study simulated discharge in an upstream sub-watershed of Beaver Creek, and the full Beaver Creek with a Nash-Sutcliffe of 0.007, and R2 0.20. Sub-basins with high discharge were identified for further examination for possible high sediment load.

Ecological niche models (ENMs) were created for White-tailed and Black-tailed prairie dogs and projected into the Last Interglacial (LI), the Last Glacial Maximum (LGM), and mid-Holocene (mid-H) to discern possible past suitable habitat for both species. Additionally, ENMs were projected into the future year 2070 representative concentration pathways (RCPs) 2.6 and 8.5 to discern how climate change may affect future habitat suitability. Kernel density estimations, minimum convex polygons, and median distribution centers of White-tailed and Black-tailed occurrence records were examined between time-periods to discern the effects of anthropogenic westward expansion on both species’ distributions. Current ENMs were constructed from commonly used bioclimatic variables and non-traditional variables (including EPA level III Ecoregions) for White-tailed and Black-tailed prairie dogs for variable comparison performance in ENMs. Results indicate that both species respond to climate change and each occupy distinct ecological niches. Biogeographical changes coincident with westward expansion remain unknown.

The 21st century experienced several health crises, especially in the form of infectious disease outbreaks such as the SARS outbreak in 2003, the H1N1 in 2009, and Ebola outbreaks in 2013. However, none has produced a worldwide socio-economic and health impact compared to the recent pandemic, known as COVID-19. As of October 4, 2022, more than 614 million cases with 6 million deaths have been reported worldwide. The United States is currently in the leading position with more than 98 million cases and 1 million deaths. The pandemic, however, did not impact the entire region similarly, and the infections and intensity varied with geographical and socio-economic characteristics. In this project, I used a multi-method approach to analyze the relationship between health disparities and COVID-19-related health outcomes in the USA and examine the influence of health disparities reporting on newspaper coverage of COVID-19. This assessment was performed in three ways. First, I have explored the relationship between Mississippi’s county-level COVID-19-related cases and deaths with the Center for Disease Control and Preventions’s Social Vulnerability Index (CDC SVI). Second, I have investigated the spatial pattern of COVID-19 in the USA and its associations with Social Determinants of Health (SDoH) by utilizing the County Health Rankings & Roadmaps (CHRR) dataset.Finally, I analyzed how news media reporting of key health determinants (i.e., age, race, income and gender) is framed, including the role of different stakeholders in the context of COVID-19. Findings revealed a statistical relationship between CDC’s Social Vulnerability Index (SVI) and Mississippi’s county-level COVID-19 cases and deaths. I also found that COVID-19 infections showed considerable spatial heterogeneity as the distribution of COVID-19 cases and deaths varies across the US counties and among the three largest waves. The multiple regression results also exhibited a temporal association between social determinants of health (SDH) indicators and COVID-19-related health outcomes across the USA. Finally, I found that the NYT coverage of COVID-19 dealt more with human interest, responsibility, and conflict than economic and morality frames. The findings revealed the vital role social determinants of health play during a health crisis, such as the COVID-19 pandemic.

While it is true that historic cemeteries are places that contain a wealth of knowledge about the history of a community they are sometimes not well maintained. The information within can be lost as grave-markers are damaged either by natural causes or human interaction. In larger cemeteries preserving these significant places can sometimes be difficult due to a number of different factors. Therefore focusing preservation efforts on specific locations where damage is more likely to occur is crucial to ensure that the monuments that are the most at risk are preserved. One possible way of accomplishing this is through the utilization of a geographic information system (GIS) to determine the shortest distance path an individual may take to reach a specific grave-marker. This can be accomplished by conducting a near analysis between an origin point and every grave-marker. These paths would also show each grave-marker that an individual passes indicating the potential for purposeful or accidental interaction. With this information efforts such as photogrammetry can be applied effectively for digital heritage preservation. Such methods would permit individuals to manipulate three-dimensional representations of grave-markers in order to preserve a large portion of the information it contains.

Public bureaucracy finds itself in a strange place at the intersection of political science and public administration. Political science finds that, within representative democracy, discretion granted to bureaucrats threatens the nature of democracy by subverting politicians who represent the will of the people – bureaucracy vs democracy. At the same time, public administration holds that, in the interest of promoting democracy, bureaucracy should be objective in its implementation of policy in a way that eliminates the influence of politics from decision-making – politics vs bureaucracy. Those positions are seemingly contradictory in nature. From one perspective, bureaucracy is undemocratic because it is outside of politics, yet an overreach of politics into the bureaucracy yields undemocratic outcomes. Bureaucracy can facilitate democracy outside of politics. This study looks to empirically test whether local bureaucrats, who should be willing to act in-line with influential co-partisans, might still promote democratic outcomes for their constituents with their discretionary decision-making. Florida provides an empirical backdrop for testing bureaucracy’s impact on democracy with a natural experimental scenario created with the passing of new early voting limitations in 2011. Florida’s Republican (R) lawmakers passed House Bill 1355 (HB 1355), which was signed into law by Governor Scott (R), that dramatically limited the early voting days allowed for federal elections. HB 1355 changed the early voting (EV) period from fourteen (14) days to eight (8) days and eliminated the last Sunday before Election Day as well. The move was widely seen as a political calculation aimed at stifling the participation of Democrats in the 2012 General Election. In seeming lockstep, local Supervisors of Elections (SOEs) from both parties utilized their statutory discretion over the location of early voting sites to alter the distribution of sites before the 2012 General Election. I find that Republican SOEs did not distribute early voting locations in a way that negatively impacted early voting participation rates (EVPR) for their local precincts. Furthermore, I find that, all else equal, their decisions did not statistically impact EVPR differently than the EVPR in communities managed by Democrats. Republican SOEs did not add new costs to voters in their communities. I provide new evidence that demonstrates that bureaucrats can indeed limit the impact of undue politics from their influential co-partisans to promote more democratic outcomes.