Influence of altered freshwater discharge on the seasonality of nutrient distributions near La Grande River, northeastern James Bay, Québec
Bibliographic record
Abstract
In subarctic marine environments, nutrient stocks are replenished through physical and biogeochemical processes in winter, largely setting an upper limit on new primary production for the next growing season. In spring, marine nutrient stocks are modified by freshwater-associated additions, especially in coastal areas. Hydroelectric development of the La Grande River (LGR) in northern Québec has shifted the timing of peak freshwater discharge from spring into winter, producing 10 times the natural winter discharge. Here, we considered salinity, oxygen isotope ratio (δ18O), and nutrient (nitrate, phosphate) data from coastal waters of northeast James Bay in different seasons of 2016 and 2017. We quantified two main freshwater sources, LGR and sea-ice melt, established by freshwater tracers, and their influence on coastal nutrient distributions. Our results show that LGR is the dominant source of freshwater to coastal waters throughout the year, especially during winter, and an important source of nitrate to nitrogen-limited coastal waters (winter concentrations of 4.53 μM versus 3.18 μM in ambient seawater). Despite being a poor phosphate source (0.11 μM versus 0.66 μM in ambient seawater), LGR provides the largest portion of the phosphate stock in surface waters near its mouth. LGR regulation has changed the pattern of natural fluvial nitrate inputs: what was observed in spring (pre-development) is now observed in winter (post-development). Thus, high winter surface nitrate stocks (22.5 mmol m−2) are available to support primary production, but are dispersed to offshore areas prior to the onset of the growing season, which begins only after the return of light. In northeast James Bay, the timing and magnitude of primary production, dependent on nutrients in the water column, is expected to have been impacted by altered freshwater input, reducing overall production in local areas and potentially increasing production further downstream with cascading effects on the marine ecosystem.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".