Infectious marine diseases can drive population sizes of marine organisms, yet these impacts can be hard to quantify due to challenges in data collection, poor understanding of host and/or pathogen life history, and selectivity in sampling methods. Here we explore methods for leveraging marine disease surveillance data with population-data collected for fisheries stock assessments to in order estimate epidemiological parameters. We explore two case studies, ichthyophoniasis in Pacific herring and mycobacteriosis in striped bass. In both cases, long-term datasets are combined with oceanographic data to understand environmental correlates of disease. Employment of multi-state mark recapture methods (in the striped bass example) demonstrates how much more inference is possible when sublethal disease assessments, and recaptures are possible. Finally, we end with a discussion of how these types of studies can be used to inform fisheries management strategies.

Maya Groner is a senior research scientist at the Bigelow Laboratory for Ocean Sciences, where she runs the quantitative marine disease ecology lab. Her research team uses field data, experiments, and models to elucidate the drivers and consequences of marine infectious disease on a variety of taxa, including razor clams, eelgrass, herring, and American lobster. She is also passionate about inclusive mentorship to empower the next generation of scientists.

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