Leveraging Artificial Intelligence and Machine Learning to Advance Chesapeake Bay Research and Management: A Review of Status, Challenges, and Opportunities
STAC Workshop Report
The STAC Workshop, "Leveraging Artificial Intelligence and Machine Learning to Advance Chesapeake Bay Research and Management: A Review of Status, Challenges, and Opportunities," convened February 2025 to delve into the opportunities artificial intelligence (AI) and machine learning (ML) offer for analyzing large-scale environmental data, identifying research needs, and improving coordination within the Chesapeake Bay Program partnership. The aim of this collaborative workshop was to enhance data-driven approaches to support Chesapeake Bay restoration goals, ensuring more effective and informed management practices.
Description
The Chesapeake Bay Program (CBP) partnership, guided by the 2014 Watershed Agreement, has long invested in monitoring, modeling, implementation, and research across the Bay and its watershed. As artificial intelligence and machine-learning (AI/ML) gain traction in ecology and water management, STAC convened a workshop, “Leveraging AI/ML to Advance Chesapeake Bay Research and Management,” on February 24–25 in Edgewater, Maryland, bringing together 50+ federal, state, academic, and NGO partners. The workshop reviewed current AI/ML applications in tidal and non-tidal systems, identified key challenges (e.g., data gaps and harmonization, communicating insights, and coordination across institutions), and developed practical recommendations to advance Bay restoration. The resulting report synthesizes lessons learned and outlines opportunities to deliver clear, actionable, data-driven insights for managers in supporting the CBP’s goals and measurable outcomes.