Seasonal reproductive patterns and recommended sampling times for sentinel fish species used in environmental effects monitoring programs in Canada
Bibliographic record
Abstract
Canada’s environmental effects monitoring (EEM) program is currently in its fifth cycle of monitoring for the pulp and paper industry and second cycle of monitoring for the metal mining industry. More than 60 different sentinel fish species have been used in the EEM fish population surveys and reproductive impacts have been identified as an issue of concern in the pulp and paper program. A review of the literature was conducted to obtain details of the reproductive biology of each fish species that has been used in EEM studies in Canada. Using available data on seasonal changes in gonadosomatic indices, the seasonal reproductive patterns of Canadian fish species were divided into categories based on reproductive strategy and the timing of initiation of gonadal recrudescence. Recommended sampling times were developed for each reproductive pattern based on periods of temporal stability, minimum variability, and maximum value in gonadosomatic indices within a reproductive cycle. The reproductive strategy, spawning time, spawning temperature, and recommended sampling time were provided for the each sentinel fish species as well as life history characteristics including longevity, age and size at maturity, and mobility. Examination of the fish surveys using small bodied forage species from the EEM pulp and paper program revealed that approximately 72% of these studies were not conducted at the developed recommended sampling times and the magnitude of impacts may be underestimated by failing to sample at the recommended time.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".