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State monitoring programs in the region rely on weekly shellfish sampling and toxin analysis, requiring extensive effort with limited temporal resolution. With the development of autonomous in situ detection devices such as the Environmental Sample Processor (ESP), this study aimed to model shellfish toxicity using ESP\u2010derived\n                    <jats:italic>A<\/jats:italic>\n                    .\n                    <jats:italic>catenella<\/jats:italic>\n                    counts to complement traditional monitoring programs using mussels (\n                    <jats:italic>Mytilus edulis<\/jats:italic>\n                    ). We developed a one\u2010compartment model of PST accumulation using\n                    <jats:italic>A. catenella<\/jats:italic>\n                    concentrations from nearshore ESP deployments. Multi\u2010year and multi\u2010site data were used to test four approaches for estimating mussel toxin uptake and depuration parameters, that is, local, global, or fixed literature values. When compared with direct PST measurements in nearby shellfish, the models achieved high correlations (\n                    <jats:italic>R<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    \u2009=\u20090.69\u20130.90), with no false negatives. Model fit varied mainly with toxin uptake parameters and was influenced by\n                    <jats:italic>Alexandrium<\/jats:italic>\n                    concentrations. The impact of other environmental and biological factors on uptake and depuration parameters remained elusive, likely due to the mussels' physiological plasticity, spatial or hydrographic separation between ESP and toxicity measurements, and microhabitat conditions. This ESP\u2010based model offers a simple, effective tool for translating offshore, automated cell counts into daily shellfish toxicity estimates and is promising for improvement of monitoring capacity in remote or under\u2010sampled areas. Incorporation of this approach into physical\u2013biological models and application in early warning systems with other biosensors remain to be tested.\n                  <\/jats:p>","DOI":"10.1002\/lno.70502","type":"journal-article","created":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T15:30:50Z","timestamp":1789399850000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Model predicts coastal paralytic shellfish toxicity in mussels from in situ phytoplankton concentrations"],"prefix":"10.1002","volume":"71","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5592-4460","authenticated-orcid":false,"given":"Sylvain","family":"Gaillard","sequence":"first","affiliation":[{"name":"Woods Hole Oceanographic Institution  Woods Hole Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David K.","family":"Ralston","sequence":"additional","affiliation":[{"name":"Woods Hole Oceanographic Institution  Woods Hole Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"V. Monica","family":"Bricelj","sequence":"additional","affiliation":[{"name":"TechMar Research Inc.  Brooklyn New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"suffix":"III","given":"Roman","family":"Marin","sequence":"additional","affiliation":[{"name":"Monterey Bay Aquarium Research Institute  Moss Landing California USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bruce","family":"Keafer","sequence":"additional","affiliation":[{"name":"Woods Hole Oceanographic Institution  Woods Hole Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"suffix":"Jr.","given":"Dennis J.","family":"McGillicuddy","sequence":"additional","affiliation":[{"name":"Woods Hole Oceanographic Institution  Woods Hole Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Donald M.","family":"Anderson","sequence":"additional","affiliation":[{"name":"Woods Hole Oceanographic Institution  Woods Hole Massachusetts 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