Insights into coastal phytoplankton variations from 1979 to 2018 derived from Ba/Ca records in scallop shells (Chlamys islandica) from a fishing ground in the northern Gulf of St. Lawrence
Bibliographic record
Abstract
Bivalve growth is affected by phytoplankton quality and availability, but long-term, coastal environmental time series related to these parameters are often lacking. Therefore, it is crucial to develop methods to accurately quantify trends in phytoplankton dynamics over time. This would be especially important for the fished scallop beds in the northern Gulf of St. Lawrence, where landings sharply declined since the early-2000s. Over the past decade, many studies have highlighted the potential of Ba/Ca ratios in bivalve shells as an environmental proxy for phytoplankton dynamics. This study presents records of Ba/Ca ratios in 31 young Chlamys islandica shells sampled in the Mingan Archipelago from 1979 to 2018. The Ba/Ca master chronology showed a decreasing trend since 2002, which could reflect changes in local phytoplankton bloom taxonomic composition, and coincides with the aforementioned decline in scallop landings. Investigations of environmental controls on barium incorporation into the shells highlight the importance of bottom, nutrient-rich waters to support diatom production or export in this fishing area. The use of such high-resolution seasonal records extracted from bio-archives may identify essential environmental mechanisms that will then assist with the development of an ecosystem-based fishery management strategy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".