Effectiveness of spawning substrate enhancement for adfluvial fish in a regulated sub‐ <scp>Arctic</scp> river
Bibliographic record
Abstract
Abstract Initial observations of egg mortality downstream of a hydroelectric facility on the Yellowknife River in the Northwest Territories prompted the investigation of habitat use by adfluvial lake trout ( Salvelinus namaycush ), lake whitefish ( Coregonus clupeaformis ), and cisco ( Coregonus artedi ). It was conducted to meet regulatory requirements under the Fisheries Act (1985) for the facility and was focused on results from annual snorkel surveys completed from 2016 to 2019. The design principles of the installed habitat were based on habitat rehabilitation projects for anadromous salmonids in rivers, artificial spawning reefs constructed in lakes for lacustrine populations of lake trout, and lake whitefish and the 2016 study results. The evaluation of the installed habitat was based on results from snorkel surveys that collected data on egg density and survival using 1 m 2 plots on both natural and artificially enhanced substrates. Three years of postenhancement monitoring indicated higher egg densities and a greater proportion of live eggs in the artificially enhanced habitat compared to the natural habitat, with more pronounced trends observed for coregonids (lake whitefish and cisco) compared to lake trout. These findings suggest that habitat enhancement has the potential to enhance juvenile recruitment for adfluvial fish. A critical factor in the design was ensuring the substrate composition provided adequate interstitial spaces for egg development and protection. This study represents the first documented attempt at habitat improvement in a regulated sub‐Arctic river in Canada. The results and design principles for the installed habitat offer a valuable framework for new or existing development projects in Northern Canada that require conservation actions to maintain fisheries productivity.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".