The influence of abiotic incubation conditions on the winter mortality of wild salmonid embryos
Bibliographic record
Abstract
Abstract Embryos of many valued salmonid species incubate in the hyporheic zone of boreal streams over winter. Influence of individual winter‐related environmental variables on salmonid embryo success has been previously investigated. However, how multiple variables act together to influence embryo incubation remains poorly understood. Using a naturally spawning population of Atlantic salmon (Salmo salar) in the Miramichi River basin (New Brunswick, Canada), we related variation in the abiotic embryo incubation habitat in different streams (spatial) and over the course of two winters (temporal) to embryo mortality between fertilisation and hatch. Over two years (2013–2014 and 2014–2015), we introduced fertilised eggs to six simulated salmon redds in each of three riffles in each of five active spawning reaches (nredds = 90) with a range of hyporheic conditions. Embryo mortality was quantified at an early sampling event (March; pre‐freshet and during late embryonic development) and a late sampling event (May; post‐freshet and post‐hatch). We extracted 22 abiotic predictor variables for statistical analyses from continuous records of hyporheic environmental conditions, collected for the duration of the incubation period in each study reach. Through partial least squares regression analyses, 37.6% of the total variation in mortality was explained by the predictor variables. Each group of predictor variables explained similar proportions of variation (water temperature: 8.4%, water level: 7.4%, dissolved oxygen: 7.1%, ice conditions: 7.2%, and substrate characteristics: 7.5%), which suggests that mortality is influenced by multiple interacting abiotic conditions, rather than a single variable in isolation, and that the factors contributing to ideal salmonid incubation habitats are complex and interconnected. Our research highlights the value of a multi‐faceted research perspective and provides a baseline from which future changes in threatened salmonid populations can be measured and compared in an effort to identify relevant species‐ or population‐specific differences.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".