Peaks and transient dynamics of ecological and biogeochemical variables following impoundment in boreal reservoirs
Bibliographic record
Abstract
Across the globe, reservoirs represent nearly 10 % of the world's freshwater. River impoundment strongly alters the hydrological regime of aquatic ecosystems which subsequently affect the ecological (e.g., primary production, fish biomass) and biogeochemical variables (e.g., nutrient, mercury, and carbon cycles which includes Green House Gas emissions; GHG). We examined the transient dynamics and co-variation of biogeochemical and ecological variables from unique long-term time series (40 years of data) from Hydro-Québec boreal reservoirs, with data before and after impoundment. To do so, we applied curve fitting analysis on the data from eight plausible scenarios and model selection. Following impoundment, most variables increased, peaked, and then decreased over time (clear hump-shaped patterns; six over eight variables). Model predictions peaked between three- and 11-years post-impoundment and returned to pre-impoundment levels after about nine- to 40-years. Variables also followed a clear sequence where GHG emissions (CO2, CH4) peaked first, immediately after impoundment, followed by an increase in phosphorus and Chl-a. Total mercury in fish peaked a few years later for non-piscivorous fish and was followed closely by piscivorous fish. This work provides the first comprehensive and holistic description of the transitory nature and co-variation of ecological and biogeochemical variables following reservoir impoundment.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".