Multi‐Year Nutrient and Organic Carbon Mass Balance of a Young Boreal Hydroelectric Reservoir Complex
Bibliographic record
Abstract
Abstract Reservoir construction can alter the transport and export of nutrients and organic matter by rivers to coastal areas. However, influences from construction within the first years after flooding are not well understood. Here we present a 9‐year study of La Romaine Hydroelectric Complex, composed of four cascading boreal reservoirs sequentially commissioned along La Romaine River in Northeastern Québec, Canada. We followed longitudinal and temporal patterns in concentrations of total nitrogen (TN), total phosphorus (TP), dissolved organic carbon (DOC), dissolved inorganic carbon (DIC), and particulate organic matter (POM) in the river above, within each reservoir, and downriver into the estuary, during and after reservoir construction. TN concentrations varied greatly within and between successive reservoirs, suggesting that reservoir habitats can be sources and sinks of N, but concentrations below the Complex remained on average like those upriver. In contrast, TP consistently increased longitudinally and were greater below the reservoirs than upriver, suggesting that these young boreal reservoirs are net sources of phosphorous. DOC and DIC concentrations were relatively constant through the reservoir continuum, suggesting no net change despite evidence of variable but intense C processing seasonally and annually. POM was highly dynamic but consistently declined through the reservoirs. Although reservoirs were influenced by upstream conditions, each had their own distinct nutrient and carbon dynamics, likely influenced by morphometry, residence time, and pre‐flood landscape. As reservoirs and the Complex age, they can individually or collectively shift from becoming less of an enhanced source of materials relative to pre‐flooding, to sinks of transported material.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".