Session Lead: Bruce Vogt (NOAA Chesapeake Bay Office)

Co-Lead(s): Christina Garvey

Session Format: Oral presentations

Session Description: 

The Chesapeake Bay Program Partnership’s efforts, guided by the revised Chesapeake Bay Watershed Agreement (Beyond 2025), are entering a critical new phase defined by adaptive management and long-term goals extending to 2040. Achieving the Agreement’s commitment to thriving habitat, fisheries and wildlife and addressing recommendations from the Comprehensive Evaluation of System Response Report require a significant evolution in how we monitor, assess, and manage the Bay’s living aquatic resources—including critical habitats (e.g., wetlands, SAV, oyster reefs) and ecologically or commercially important species (e.g., blue crab, striped bass, forage species, invasive blue catfish). As the Bay faces a “dynamic future” characterized by environmental variability, evolving human pressures, and the emergence of new technologies, the established methods for monitoring, assessing, and researching these resources must adapt.


This session invites presentations that showcase next generation tools and transdisciplinary approaches that are reshaping how we understand and manage the Bay’s living resources and the habitats they depend on. We seek contributions that move beyond traditional ecological monitoring to embrace innovative methodologies that enhance the speed, scale, and utility of living resource data for management decisions.

Key topics and areas of interest include:

  • Advanced Monitoring and Data Collection: New applications of high-resolution remote sensing (aerial, satellite, acoustic), autonomous underwater vehicles (AUVs), and in-situ monitoring networks for tracking species movement, habitat change (e.g., SAV or oyster reef growth), and water quality impacts on biota.
  • Machine Learning and AI in Assessment: Novel uses of Artificial Intelligence (AI) and Machine Learning (ML) techniques for processing complex datasets, such as automated species identification from acoustic or image data, forecasting fisheries stock dynamics, modeling habitat suitability under future climate scenarios, or emulating mechanistic ecosystem models.
  • Integrating Social and Ecological Data: Research that successfully merges ecological data (e.g., fish stock surveys, oyster restoration success) with social science data (e.g., human behavior, stakeholder acceptance, economic models).
  • “Team Science” for Management: Case studies and methodologies that demonstrate effective transdisciplinary collaboration between resource managers, modelers, researchers, and stakeholders to translate complex ecological research into timely, actionable management policy for specific species or habitat restoration targets.
  • Addressing Data Challenges: Strategies for managing the high volume of new data, ensuring data quality, and effectively communicating complex or uncertain results (especially those derived from AI/ML) to policymakers and the public in a manner that builds trust.
  • Integrating Diverse Data Streams: Methodologies for synthesizing information from multiple sources—such as citizen science, historical surveys, and novel high-frequency data—to create comprehensive and robust assessments that guide living resource management and restoration targets.

By bringing together scientists and managers focused on aquatic resources, this session aims to articulate a roadmap for leveraging new technologies and “team science” to sustain and accelerate progress toward a healthy Chesapeake Bay in the face of future challenges.