This paper addresses two challenges in higher education that increased with the shift to online learning due to COVID-19: translating experiential learning online and supporting student engagement. While virtual reality can be mobilized to address both of these challenges, finding or creating virtual reality that fits a course’s learning objective is a common barrier. This paper illustrates how instructors can integrate anthropological readings with freely available 360° videos or Google Earth to create their own virtual reality-like experiences and class activities. Such immersive experiences can support students in applying anthropology to real-world issues from any location with a smart device and internet connection and lead to a more holistic understanding of social issues. They also present an alternative to narrated PowerPoints or videos in online and in-person learning that can foster student engagement with the content.

Previous empirical studies have suggested that climate change induces human migration in Mexico by damaging agricultural livelihood and worsening habitability. However, these studies present different opinions on how water availability affects migration. Also, a high-spatial-resolution climate migration analysis that covers a long-time period is lacking. This study employs two water availability data sets and two migration data sets with high spatial resolution and extended temporal coverage. Firstly, I look at two hydroclimate data sets, ground-station-based and satellite-based, to examine the surface water dynamics in Mexico. Secondly, two migration data sets, modeled gridded data and census data, are analyzed to identify the internal and international migration patterns at the municipality-level in Mexico. Lastly, migration rate is regressed on various climate metrics, including temperature trend and variability, precipitation trend and variability, and surface water trend. In addition, climate metrics' impacts on rural-urban migration flow are examined separately. The investigation of two hydroclimate data reveals the limitation to capture surface water dynamics at fine-scale, the municipality-level, in Mexico. Also, the comparison of two migration data sets displays a huge international migration flow in Mexico. Lastly, the regression results suggest a closer climate's relationship with international migration than internal migration. They also show a consistent delay response of migration after environmental stressors.

Improved understanding of the physical impacts to the climate caused by anthropogenic emissions has led to an increased focus on the role of policy on limiting mitigating the cause and the impacts of climate change. The emissions trajectory that society takes will play a major role in determining a wide variety of climate impacts from health to economic growth. This dissertation explores how idealized modeling can be used to inform the potential outcomes of the policies meant to mitigate the negative impacts of climate change and optimize the benefits of emission reduction. Chapter 1 explores the potential trade-offs between increased temperatures and reduced health impacts of considering aerosol emissions in international climate policy. Using an idealized model, it is possible to demonstrate that both health and temperature benefits can result from considering either health or temperature separately. Chapter 2 interrogates whether climate policy in the United States can be used to reduce existing racial inequities in air pollution exposure. The modeling shows that prioritizing by exclusively income or cost in national policy would result in worsening inequities, but that prioritizing by race explicitly has the opposite effect. Using a set of more realistic air quality simulations with randomized emission reduction, it appears that the transportation has a unique potential for air quality equity improvements. Lastly, Chapter 3 focuses on statistical models that use natural variation in annual weather to predict how climate will influence human outcomes. Using an idealized outcome variable and real data of global gross domestic product, it is possible to demonstrate that imperfect measurement networks and the mean shift in climate both work to underestimate future climate impacts.

Since the discovery of citrus Huanglongbing (HLB) in Florida in 2005, research efforts to develop and identify germplasm resistant to HLB have intensified greatly.  Many research groups in Florida and elsewhere are screening existing citrus varieties and members of the Rutaceae in an attempt to identify useful sources of resistance that can be used in traditional breeding programs to produce commercial scions and rootstocks resistant to HLB.  Although progress has been made, it is generally accepted that although some level of tolerance and resistance have been identified, it is not likely that these will be sufficient to confer commercially acceptable levels of resistance in the short term.  Similarly, it is widely accepted that genetic modification using a biotechnology approach is likely to be the only way to achieve acceptable levels of resistance in commercial varieties in the near term.  Progress has been made by many groups to produce and screen plants with a wide variety of genes and approaches, and more than one group is starting the process to collect the data necessary for deregulation.  However, the deregulation process is daunting and full of hurdles and the science may actually be the easiest and the cheapest part of the project.  The process as it applies to one project will be presented to demonstrate what is involved as the industry moves forward with this technology.