Biodiversity Policy and Policy for Biodiversity: Establishing Impactful Natural Capital Markets
Matthew Potts, Professor
Environmental Science, Policy and Management
Applications for Fall 2024 are closed for this project.
Overview: Public debates and policies are increasingly shifting to include nature and nature-related risks and mitigations in climate discourse. Chief among nature-related risks are issues centered on biodiversity. These frameshifts are evidenced by multilateral agreements such as the Global Biodiversity Framework and a suite of regulations coming out of the European Union (EU), such as the Nature Restoration Law. National policies and commitments are simultaneously spurring and requiring private commitments and disclosures. The EU’s European Commission Sustainability Reporting Standards (ESRS) requires companies to disclose nature-related risks and footprints, while the Taskforce on Nature-related Financial Disclosures (TNFD) provides a framework for voluntary reporting. How these risks are characterized at both individual and national scales will have significant and cascading consequences for where, when, and how mitigation measures will be prioritized, and therefore the scale of potential impact.
Project Focus: This project will focus on exploring the emerging science, policy, and entrepreneurial activity to better understand how to best guide the development of policy and the deployment of public and private market capital to meet existing and emerging commitments to restore nature.
Role: The expected learning outcomes are broad and will be reflective of the student's interest. Students will improve their skills in data management, data analytics, biodiversity science, literature review, and interdisciplinary analysis.
Qualifications: We are looking for motivated and independent undergraduate students with a broad background in the environmental sciences, biodiversity science, or business. All students should have excellent reading, writing, and organizational skills and those interested in quantitative analyses ideally have a background in programming (e.g. R) and/or geospatial skills (e.g. Google Earth Engine).
Hours: to be negotiated
Social Sciences Environmental Issues Biological & Health Sciences