Session Lead: Sairah Malkin, University of Maryland Center for Environmental Science

Co-Lead(s): Isabel Baker

Session Format: Oral presentations

Session Description: 

Molecular biology, genetics, and genomics tools have become indispensable for identifying and understanding ecological processes in aquatic systems, from biogeochemical cycling and pathogen dynamics to species distributions and ecosystem responses to environmental change. The Chesapeake Bay has served as a testbed for foundational studies in biogeochemical cycling including understanding the foundational associations between nutrient loading and deoxygenation in coastal systems. A particularly transformative frontier lies in connecting our rapidly growing molecular datasets with biogeochemical models, arguably representing one of the greatest opportunities to advance our mechanistic and predictive understanding of the Chesapeake Bay. Where molecular patterns show strong relationships with environmental variables, they suggest predictive potential and may help constrain existing models or reveal missing processes. Conversely, models can provide testable hypotheses for molecular ecologists about which genes, taxa, or pathways should respond to specific environmental conditions.

This session aims to bring together researchers employing molecular approaches to study Chesapeake Bay ecosystems. We welcome contributions spanning diverse applications, including but not limited to: microbial community dynamics, biogeochemical transformations, pathogen ecology, harmful algal bloom ecology, species distribution and biodiversity, climate change responses, and pollution impacts. We particularly encourage presentations that explore opportunities for integrating molecular data with other observational or modeling approaches, as well as those highlighting methodological innovations or novel applications of existing tools. We intend for this session to provide a forum to bring together members of the Chesapeake Bay research community using ‘omics tools to foster collaborations and explore new approaches. We especially encourage submission from early career scientists including students.