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The toxic diatom genus Pseudo-nitzschia is a growing presence in the Gulf of Maine (GOM), where regionally unprecedented levels of domoic acid (DA) in 2016 led to the first Amnesic Shellfish Poisoning closures in the region. However, factors driving GOM Pseudo-nitzschia dynamics, DA concentrations, and the 2016 event are unclear. Water samples were collected at the surface and at depth in offshore transects in summer 2012, 2014, and 2015, and fall 2016, and a weekly time series of surface water samples was collected in 2013. Temperature and salinity data were obtained from NERACOOS buoys and measurements during sample collection. Samples were processed for particulate DA (pDA), dissolved nutrients (nitrate, ammonium, silicic acid, and phosphate), and cellular abundance. Species composition was estimated via Automated Ribosomal Intergenic Spacer Analysis (ARISA), a semi-quantitative DNA finger-printing tool. Pseudo-nitzschia biogeography was consistent in the years 2012, 2014, and 2015, with greater Pseudo-nitzschia cell abundance and P. plurisecta dominance in low-salinity inshore samples, and lower Pseudo-nitzschia cell abundance and P. delicatissima and P. seriata dominance in high-salinity offshore samples. During the 2016 event, pDA concentrations were an order of magnitude higher than in previous years, and inshore-offshore contrasts in biogeography were weak, with P. australis present in every sample. Patterns in temporal and spatial variability confirm that pDA increases with the abundance and the cellular DA of Pseudo-nitzschia species, but was not correlated with any one environmental factor. The greater pDA in 2016 was caused by P. australis – the observation of which is unprecedented in the region – and may have been exacerbated by low residual silicic acid. The novel presence of P. australis may be due to local growth conditions, the introduction of a population with an anomalous water mass, or both factors. A definitive cause of the 2016 bloom remains unknown, and continued DA monitoring in the GOM is warranted. 

Abstract. Internally consistent, quality-controlled (QC) data products play animportant role in promoting regional-to-global research efforts tounderstand societal vulnerabilities to ocean acidification (OA). However,there are currently no such data products for the coastal ocean, where mostof the OA-susceptible commercial and recreational fisheries and aquacultureindustries are located. In this collaborative effort, we compiled, quality-controlled, and synthesized 2 decades of discrete measurements ofinorganic carbon system parameters, oxygen, and nutrient chemistry data fromthe North American continental shelves to generate a data product calledthe Coastal Ocean Data Analysis Product in North America (CODAP-NA). Thereare few deep-water (> 1500 m) sampling locations in the currentdata product. As a result, crossover analyses, which rely on comparisonsbetween measurements on different cruises in the stable deep ocean, couldnot form the basis for cruise-to-cruise adjustments. For this reason, carewas taken in the selection of data sets to include in this initial releaseof CODAP-NA, and only data sets from laboratories with known qualityassurance practices were included. New consistency checks and outlierdetections were used to QC the data. Future releases of this CODAP-NAproduct will use this core data product as the basis for cruise-to-cruisecomparisons. We worked closely with the investigators who collected andmeasured these data during the QC process. This version (v2021) of theCODAP-NA is comprised of 3391 oceanographic profiles from 61 researchcruises covering all continental shelves of North America, from Alaska toMexico in the west and from Canada to the Caribbean in the east. Data for 14variables (temperature; salinity; dissolved oxygen content; dissolvedinorganic carbon content; total alkalinity; pH on total scale; carbonateion content; fugacity of carbon dioxide; and substance contents of silicate,phosphate, nitrate, nitrite, nitrate plus nitrite, and ammonium) have beensubjected to extensive QC. CODAP-NA is available as a merged data product(Excel, CSV, MATLAB, and NetCDF; https://doi.org/10.25921/531n-c230,https://www.ncei.noaa.gov/data/oceans/ncei/ocads/metadata/0219960.html, last access: 15 May 2021)(Jiang et al., 2021a). The original cruise data have also been updated withdata providers' consent and summarized in a table with links to NOAA'sNational Centers for Environmental Information (NCEI) archives(https://www.ncei.noaa.gov/access/ocean-acidification-data-stewardship-oads/synthesis/NAcruises.html). 

This study uses the Maine Department of Marine Resources Lobster Sea Sampling data (2000–2016) and logistic models to develop the first time series for the timing and suddenness of onset of the initial intra‐annual molt of American lobster in the Gulf of Maine (GoM), an annual fishery recruitment event crucial to fishermen. Data from three GoM regions (eastern, central, and western coastal Maine) were further divided by sex and estimated maturity of sampled lobsters for analysis. We found differences in the patterns of initial molt timing and suddenness between the regions, sexes, and stages of maturity. Using the Northeast Coastal Ocean Forecasting System hindcast temperatures, seasonal accumulated degrees above 5°C were used to describe the thermal history for each region at ocean depths of about 5 and 110 m. These temperature metrics were used in generalized linear models to investigate the potential effects of seasonal temperatures on the initial molt season. Results showed that initial intra‐annual molting of lobsters was variable from 2000 to 2016, with periods of both earlier and more sudden molts and later and more protracted molts. Warmer temperatures, specifically inshore temperatures, were generally associated with an earlier molt, but without complete uniformity in the direction and magnitude across seasons, regions, and lobster demographics. We also discuss why developing molt time series and quantifying the connection to the bottom temperatures are necessary and emphasized why existing monitoring programs and the applied quantification techniques herein make this relationship difficult to quantify.