Wildfires are among the most significant natural disaster threats facing the planet, and the threat is only increasing as the climate change crisis worsens. One tool to combat them is prescribed fire, or a controlled fire designed to burn away any existing fuel so wildfires cannot burn in that area. However, prescribed fires can grow too large and become destructive rather than restorative. Thus, we wanted to create a model to minimize the impact of prescribed fires. Current tools do exist for this, but they are technical and require obscure data, so it can be difficult for land managers to use them.
To accomplish this, we ran over 100 simulations and synthesized existing research to create an easy-to-use model requiring easily obtained data to return not only an approximate cost of burning, but also what steps to take to ensure a low-intensity and restorative burn. Then we created a python script of the model that puts it into a digestible and easy-to-use format.
Student Major(s): Undecided
Advisor: Dr. Matt Dean
As rising sea levels impact Virginia’s shorelines, native plants are in high demand to create nature-based solutions for wetland and shoreline erosion. This project asks how a native plant nursery operated by the Chickahominy Tribe can support Virginia’s shorelines and the Tribe’s goals of fostering ecological, cultural, and economic resilience. A business plan that addresses this question was developed using a supply chain perspective, showing how each aspect of the business can align with the Tribe’s vision and provide a meaningful market offering. Research methods included consulting nonprofit organizations, field researchers, and existing literature. The outcome provides market opportunities, material sourcing strategies, potential production processes, financial considerations, and engagement pathways. Findings indicate the nursery is feasible if it is launched in a pilot phase targeting nonprofit clients, supported with grant funding, and scaled gradually. The business plan will act as guidance as the Tribe pursues this opportunity.
Student Major(s): Business Analytics, Environment and Sustainability
Advisor: Dr. Tonya Boone
This project investigates how Kenyan conservation NGOs use community-led livelihood initiatives to achieve both conservation and economic outcomes. Focusing on two organizations- SORALO and the Amboseli Ecosystem Trust- this research explores how initiatives such as beekeeping, beadwork, kitchen gardens, and grass seed banks are designed and implemented in partnership with women from pastoralist communities. Through fieldwork, including interviews, participant observation, and site visits, the study documents the experiences of local participants and identifies factors that influence success, such as climate, market access, and infrastructure. A key goal is to create a decision-support tool to help conservation organizations design sustainable and impactful livelihood programs. Preliminary findings suggest that when communities are deeply involved in these initiatives, they are more effective and culturally appropriate, while also supporting conservation. This work highlights the importance of integrating local knowledge and priorities into conservation strategies and offers insights into scaling similar models in other regions.
Student Major(s)/Minor: Sharanya: Undecided; Skylar: History/Environmental Policy Majors, Global Business Minor; Emma: Biology Major, Innovation and Entrepreneurship Minor
Advisor: Professor Graham Henshaw (Business); Dr. Troy Wiipongwii (Entrepreneurship and Conservation)
This research project examines the impact of artificial intelligence (AI) tools on the legal industry, with a focus on law firm operations. As AI becomes more embedded in functions such as legal research, contract analysis, due diligence, and litigation support, firms are realizing improvements in efficiency and accuracy. To contextualize AI’s role, the study begins with a historical review of technological innovation in law, including the development of legal research databases and e-discovery tools, highlighting how AI represents a shift in legal practice. A multi-method approach is employed, beginning with an in-depth review of academic literature and consultant publications to identify patterns in AI adoption and performance. In addition, original qualitative data was collected through two survey sessions and assessed against current market trends to evaluate alignment and perceived effectiveness in the legal marketplace. Lastly, surveys were conducted with practicing lawyers to collect professional insights on legal AI tools.
Student Major(s): Finance
Advisor: Dr. Vladimir Atanasov