Impacts of ocean acidification (OA) on phytoplankton productivity, survival, community structure, nutritional quality and trophic transfer efficiency to zooplankton

Phytoplankton, the foundation of marine ecosystems, are increasingly subjected to ocean acidification (OA). To understand the impacts of OA on the St. Lawrence Estuary and Gulf (SLEG), this project investigated the physiological responses of phytoplankton to elevated carbon dioxide (CO2) levels.

Specifically, we submitted a natural population of phytoplankton collected in the Estuary to a decreasing gradient of pH (from 8.1 to 7.2) and measured key biogeochemical parameters such as chlorophyll-a (chl-a), nutrients, dissolved inorganic carbon (DIC), total alkalinity (TA), pH, essential fatty acids (EFAs), bacterial abundance, and genetics (RNA transcriptomics). The sampling was conducted during a 14 day laboratory experiment at the Maurice Lamontagne Institute during summer 2024. By combining controlled mesocosm experiments with metatranscriptomics, we aimed to identify critical thresholds for OA impacts on phytoplankton growth, community composition, and nutritional quality.

The dataset includes several inorganic carbon state variables, phytoplankton- and bacterial-associated variables, nutrient concentrations, as well as gene expression analysis data.

To ensure the highest standard of data quality, sample collection and processing procedures adhered to the guidelines set by the Guide to Best Practices for Ocean CO2 Measurements (Dickson et al. 2007) and followed detailed Standard Operating Procedures (SOPs) to maintain consistency (Mitchell et al. 2002). Quality Control (QC) methods included: regular calibration of analytical instruments to ensure accurate measurements; the use of standard reference materials for calibration or control samples to monitor the accuracy and precision of the analysis; running blanks to check for contamination; replicating analyses on certain samples to assess precision.

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Last Updated October 20, 2025, 02:27 (UTC)
Created October 20, 2025, 02:27 (UTC)
Domain / Topic
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Biota, Environment
Title
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Impacts of ocean acidification (OA) on phytoplankton productivity, survival, community structure, nutritional quality and trophic transfer efficiency to zooplankton
Description
A description of the dataset.

Phytoplankton, the foundation of marine ecosystems, are increasingly subjected to ocean acidification (OA). To understand the impacts of OA on the St. Lawrence Estuary and Gulf (SLEG), this project investigated the physiological responses of phytoplankton to elevated carbon dioxide (CO2) levels.

Specifically, we submitted a natural population of phytoplankton collected in the Estuary to a decreasing gradient of pH (from 8.1 to 7.2) and measured key biogeochemical parameters such as chlorophyll-a (chl-a), nutrients, dissolved inorganic carbon (DIC), total alkalinity (TA), pH, essential fatty acids (EFAs), bacterial abundance, and genetics (RNA transcriptomics). The sampling was conducted during a 14 day laboratory experiment at the Maurice Lamontagne Institute during summer 2024. By combining controlled mesocosm experiments with metatranscriptomics, we aimed to identify critical thresholds for OA impacts on phytoplankton growth, community composition, and nutritional quality.

The dataset includes several inorganic carbon state variables, phytoplankton- and bacterial-associated variables, nutrient concentrations, as well as gene expression analysis data.

To ensure the highest standard of data quality, sample collection and processing procedures adhered to the guidelines set by the Guide to Best Practices for Ocean CO2 Measurements (Dickson et al. 2007) and followed detailed Standard Operating Procedures (SOPs) to maintain consistency (Mitchell et al. 2002). Quality Control (QC) methods included: regular calibration of analytical instruments to ensure accurate measurements; the use of standard reference materials for calibration or control samples to monitor the accuracy and precision of the analysis; running blanks to check for contamination; replicating analyses on certain samples to assess precision.
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2025-03-01
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Open Government Licence - Canada
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https://open.canada.ca/data/en/dataset/37e66fc5-4a81-4506-a7fe-637412ac6fbd
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Fisheries and Oceans Canada | Pêches et Océans Canada
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None
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None
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