Electronic Thesis or Dissertation

Melaleuca quinquenervia is an Australian tree, an aggressive invader of South Florida ecosystems, and has impacted over 100,000 acres of wetlands with many documented deleterious effects on native ecosystems. Millions of dollars are spent each year on management. The most rapid and cost-effective approach to date is the delivery of broadcast aerial herbicide application via helicopter, though long-term effects of this indiscriminate approach on native vegetation communities is poorly understood. We experimentally examined the effects of broadcast herbicides on uninvaded sawgrass plots in comparison to clip treatments and controls which showed that while clipped plots quickly recovered toward pre-treatment dominance, herbicide plots remained highly dissimilar and showed little to no recruitment even after 36 weeks. We also examined untreated Melaleuca stands to assess relationships between invasion severity and canopy cover using a generalized linear model with a beta distribution. Basal area, number of stems, and the interaction between basal area and number of stems was significantly related to canopy cover. Finally, we surveyed transects through aerially-treated Melaleuca stands (7 years post-treatment) separated into zones of dense infestation, sparse infestation, and untreated marsh. We compared differences in microtopography, invasion severity, and water quality to quantify changes in the physical environment brought about by both invasion and aerial treatment relative to the surrounding marsh. Additionally, we used percent cover abundance of vascular plant species in plots to compare vegetation communities between zones.

My first study proposes that stock price manipulation erodes trust, damages corporate reputation, reorients management towards short-termism, harms entrepreneurial innovation culture, and increases the cost of capital. I tested these ideas by linking stock manipulation data to corporate venture capital data for firms listed on NASDAQ and NYSE. The data indicate CVC investments in entrepreneurial firms are followed by a rise in market manipulation in the short run [-3 months, +3 months], but a decline thereafter. The data further indicates that stock manipulation harms the ability of CVCs to form investment syndicates and reduces the likelihood of successful IPO and acquisition exits. The hazard rate to IPO is 0.54 for CVC-backed firms that face market manipulation. Overall, the theory and evidence provide insights into how firm's manipulation can damage the effectiveness of their venture capital endeavors, ultimately contributing to sustainable growth and innovation.

Policy formation involves an interplay of decision-making processes that shape all policy process stages. A critical aspect of the design process is selecting policy tools to align with policy goals. The First Step Act (FSA) (2018) aims to reduce recidivism and reform sentencing through a robust policy tool portfolio. However, questions persist about how policy tools are selected. This dissertation evaluates the policy design, tool choices, and collaborative networks associated with these choices. Grounded in the social construction framework and using content analysis and discourse network analysis (DNA), this dissertation examines how policymakers select policy tools to achieve functionality.
Research question one explores the complementarity of the FSA’s policy tool portfolio, and results demonstrate alignment between policy goals and corresponding policy tools. Research question two examines how social constructions of target populations and political affiliations influence policy tool choices; hypothesis one reveals that liberal policymakers align with those with similar political affiliations. Results from hypothesis two indicate liberal policymakers adopt a rehabilitation orientation tool approach, viewing target populations as investments and deserving of support structures. The findings also highlight limited interaction with government agency officials, reflecting a need to incorporate more administrative voices into legislative discourse.

South Florida is at the frontlines of climate change impacts. Facing increases in heat waves, flooding, and intensity of storms, climate change has direct detriments on the residents of this region. This research examines the evidence of Climate Change Anxiety (CCA) within Broward, Miami-Dade, Monroe, and Palm Beach counties. Using the CCA instrument developed by Susan Clayton and Bryan Karazsia in 2020, this study replicates analyses of variables conducted in prior research on the national level. This research found South Floridians are experiencing moderate levels of anxiety caused by climate change. Additionally, significant relationships exist between CCA and newly examined variables such as family situations, politics, and sociological perceptions. Sociological perceptions such as identities described in Dan Kahan’s Cultural Cognition Theory help us understand how having different views of society and life may alter how an individual is affected by CCA.

Due to the increased integration of robots into industrial, service, and educational settings it is important to understand how and why individuals interact with robots. The current study aimed to explore the extent to which individuals are receptive to nonverbal communication from a robot compared to a human, and the individual differences and stimuli attributes that are related to trust ratings. A combination of eyetracking and survey measures were used to collect data, and a robot and human both performed the same gesture to allow for direct comparison of gaze patterns. Individuals utilized the offered information equivalently from agents. Survey measures indicated that trust ratings significantly differed between agents, and the perceived likability and intelligence of the agent were the greatest predictors of increased trust.

I assessed the impact of the Merge in Ethereum by analyzing the change in its market capitalization following the event. This study can provide insights into market preferences for proof-of-work versus proof-of-stake protocols. A difference-in-difference analysis was conducted, using Ethereum Classic as the control group and Ethereum as the treatment group to estimate the local average treatment effect following the Merge as the intervention. As a robustness check, the analysis was repeated using the Top 100 cryptocurrencies as the control group. I find no evidence that the Merge improved the market capitalization of Ethereum relative to Ethereum Classic or the Top 100 cryptocurrencies.

In recent years, school counselors and education have faced an increase in mental health challenges, which has had adverse effects on school counseling (Marraccini et al., 2023). Seventy-six percent of state counseling coordinators report insufficient school counselors available to fill positions (American School Counselor Association [ASCA], 2023b). The U.S. Bureau of Labor Statistics (2023) estimates that 26,600 jobs per year will become available for school counselors, career counselors, and advisors over the next 10 years due to attrition and retirement from the profession.
This nonexperimental, correlational design explored the relationships between the volunteer school counselors’ (N= 56) developmental stage and perceived leadership behaviors, wellness, burnout, and turnover intention. The linear regression results revealed that school counselors’ years of experience predicted their leadership related to systemic collaboration and turnover intention. When exploring leadership behaviors, linear regressions found that counselors’ interpersonal skills predicted their perceptions of wellness and burnout, and systemic collaboration and resourceful problem-solving skills predicted a counselor’s level of burnout regarding their feelings of incompetence. Also, the participants’ professional efficacy predicted wellness and incompetence. Finally, social justice had a statistically significant relationship with incompetence and devaluing clients. The results of this study show moderate to strong relationships amongst select variables. The results, implications, and directions for future research are discussed.

It is the purpose of this thesis to analyze the fresh relevance of Shakespeare’s four-hundred-year-old tragedy Macbeth, as manifested in three contemporary films: Macbeth, directed by Rupert Goold, starring Patrick Stewart (2010); Macbeth, directed by Justin Kurzel, starring Michael Fassbender (2015); and The Tragedy of Macbeth, directed by Joel Coen, starring Denzel Washington (2021). The thesis examines the unique thematic ideas in each adaptation. The directors have distinct visions. Goold imagines Macbeth as a Stalinesque authoritarian. Kurzel’s Macbeth battles post-traumatic stress disorder. Coen’s older Macbeth is desperate to attain the status he is adamant he has earned, obsessed with the awareness that his time is limited to act. In these adaptations, underlying themes exploring the danger of the authoritarian personality, the heartbreaking futility of misplaced trust, the ravaging effects war may visit on the warrior’s psyche, and the dark places one may be led in the pursuit of ambition are presented to the audience for contemplation.
The analysis draws from contemporary film criticism found in newspapers, magazines and scholarly journals. It is further supported by interviews with the directors and key actors, as well as autobiographical testimony. The elements used in the artistic craft of cinematography are explored. Recognizable references taken from earlier productions used by Joel Coen in his experimentation with Macbeth as a film noir are identified. Research which supports the relevance of the comparison of Macbeth to the historical Stalin is offered. Physicians’ clarification of the condition of PTSD enlightens the understanding of Kurzel’s interpretation.

Forest ecosystems are critically important to biodiversity and the global carbon budget. Within forest ecosystems, dead wood has several ecological roles, including in carbon and nutrient dynamics and biodiversity conservation. However, surface fuels in forests also influence wildfire behavior and associated risks and hazards. Therefore, appropriate management of dead wood contributes directly to appropriate functioning of the forest ecosystem by conserving forest biodiversity, mitigating extreme wildfire events and pyrogenic emissions, and enhancing carbon sequestration. Using data extracted from peer-reviewed journal articles, geospatial, and field inventory data, and integrating meta-analytic, hierarchical regression, and vegetation simulation modeling approaches, this dissertation project examined the influence of dead wood on biodiversity, carbon, and wildfires in forest ecosystems.
The meta-analysis results suggest that dead wood quantity is an indicator of forest biodiversity, while dead wood types and decay stages had varied relationships with biodiversity. Generalized linear and additive mixed effects modeling of geospatial and human observed data demonstrated the predominant influences of weather conditions and moderate effects of live and dead fuels on exceptionally large wildfires’ behavior in the western United States. Consistently dominant effects of temperature on wildfire behavior highlight and emphasize the pressing need to address climate change's impact on western US forests. Lastly, vegetation and wildfire simulation modeling of forest stand inventory data and post-modeling carbon computations suggested that physical harvesting of dead wood, an approach analogous to traditional practice of firewood collection, when combined with modern mechanical fuel reduction treatments in Sierra Nevada, CA, mixed conifer forests has great potential to mitigate wildfire hazards, reduce fire emissions, and enhance carbon sequestration.

This quantitative research study explored the impact of the COVID-19 pandemic on the utilization of telehealth in mental health services, focusing on the Veterans Health Administration (VHA) of the U.S. Department of Veterans Affairs. The study assessed changes in appointment types across location, modality, gender, age, race, and rurality. Drawing on the Technology Acceptance Model (TAM) and introducing a COVID-19 moderation factor, the study investigates the adoption of telehealth technology and its effects on traditionally underserved groups. The research method involved a quantitative analysis of de-identified patient appointment data from FY 2017 to FY 2022, encompassing 66 million appointments. Empirical research was assessed for any impact of the coronavirus disease 2019 (COVID-19) pandemic on the proliferation of the telehealth modality in mental health. The study incorporated statistical analyses, including time series regression, to test the hypothesis that telehealth positively influenced mental health service delivery, with the COVID-19 pandemic as a moderating factor. Descriptive statistics were used to present the mean and standard deviation scores for the independent and dependent variables. Frequency statistics were used to describe the independent variables for the study further. Three regression models were used to answer the hypotheses. Comprehensive results were presented, showcasing the impact of the pandemic on telehealth adoption, and behavioral intentions. Specifically, the COVID-19 pandemic has fundamentally altered the landscape of doctoral healthcare provider visits, generally decreased in-person visits while substantially increased video and phone visits. The findings highlighted sizable shifts in healthcare dynamics, emphasizing the influence of demographic factors on visit types and the complex interplay with COVID-19. This study contributed valuable insights into the transformative role of telehealth in mental health care, especially during global health crises like the COVID-19 pandemic.