Nutrient inputs from subarctic rivers into Hudson Bay
Bibliographic record
Abstract
Hudson Bay (HB), a large subarctic inland sea, is impacted by rapid climate change and anthropogenic disturbance. HB plays crucial roles in supporting resident and migratory species of birds and marine mammals, providing subsistence to coastal communities, and exporting nutrients into the western Labrador Sea. To better constrain the impact of river nutrients on the HB ecosystem and to obtain a contemporary reference point by which future change can be evaluated, we estimated fluxes of nitrate plus nitrite (N), phosphate (P), and silicate using contemporary and historical nutrient data in conjunction with discharge estimates produced by three global climate models. Concentrations and molar ratios of the different nutrients exhibited large contrasts between different sectors of HB, which is attributed to the diversity of geological settings across distinct watersheds. With respect to the needs of primary producers, river waters were characterized by a shortage of P during winter and spring (N:P molar ratios in dissolved nutrients >16), nearly balanced N:P ratios in summer, and a shortage of N during fall (N:P < 16). Southwestern rivers made the largest regional contribution to the total annual delivery of all nutrients, followed by modest contributions from southern and eastern rivers, and minor ones from northwestern rivers. While the regulation of river flow in the Nelson and La Grande rivers had no discernible impact on nutrient concentrations and ratios, it clearly shifted nutrient transports toward the winter when biological activity in the estuaries is reduced. Finally, the potential amount of new production supported by riverine N inputs was nearly two orders of magnitude (1.8 × 1011 g C yr−1) lower than the new production supported by marine nutrients (7.3 × 1012 g C yr−1). Although the potential contribution of river nutrients to new primary production is small (2.4%) at the bay-wide scale, it can be significant locally.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".