Changes in sediment regimes and mass accumulation rates in Eeyou Istchee eelgrass habitat, James Bay, Canada
Bibliographic record
Abstract
Fourteen sediment cores collected from shallow subtidal waters in 2017–2021 in northeastern James Bay, Canada (known as Eeyou Istchee) were analyzed for excess 210 Pb ( 210 Pb ex ), 137 Cs and fine particle content (% <63 μm) to characterize sediment deposition within an eelgrass ( Zostera marina) ecosystem recovering from a massive decline in the 1990s. A strong signature of surface soil input from nearby La Grande Rivière watershed is evident from high 137 Cs inventories and low 210 Pb ex / 137 Cs ratios. Mass accumulation rates (MARs) were established in five cores using a 210 Pb ex model that accounts for bio-mixing and subsequently validated by 137 Cs. MARs are higher in this area (0.14–0.48 g cm −2 yr −1 ) than in nearby offshore Hudson Bay. Low inventories of 210 Pb ex and 137 Cs and disturbances in particle size distribution (coarsening upwards) in the remaining cores indicate non-steady-state behaviour, most likely surficial erosion. Using well-preserved 137 Cs peaks and other core-specific methods, pre-disturbance MARs were estimated at between <0.05 and 0.39 g cm −2 yr −1 , indicating an environmental transition from net accumulation to erosion. Recent deposition of sediment is largely controlled by sediment focusing, resulting in high variability of inventories and MARs at small spatial scales. The loss of eelgrass has likely increased sediment resuspension and redistribution to deeper areas, contributing to decreased light availability for subtidal eelgrass and increased export of material to greater James Bay. The findings of this study show the foundational importance of small-scale assessment of MARs in river-dominated eelgrass ecosystems like those in Eeyou Istchee. • Sediment sources are highly influenced by the nearby La Grande Riviere. • Disturbances in accumulation ( i.e. erosion) is seen in over half the sediment cores. • Surface erosion is linked to areas that have experienced eelgrass loss.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".