Establishing present‐day Sockeye Salmon (<i>Oncorhynchus nerka|sćwin</i>) spawning capacity in the highly impacted sq,awsitkʷ|Okanagan River to guide population conservation and restoration
Bibliographic record
Abstract
Abstract The presence of dams on the Columbia River (CR) has reduced Sockeye Salmon ( Oncorhynchus nerka|sćwin ) numbers to a fraction of their historic numbers. The Syilx Okanagan Nation Alliance (SONA) has led voices of concern regarding the impacts of diminishing Sockeye Salmon numbers on the ecosystem health of the sawsitkʷ|Okanagan River (s|OR), a tributary of the CR. In the early 2000s efforts commenced to rehabilitate the s|OR Sockeye population. These efforts have seen the population rise from a running average of 40,000 to 200,000. However, the contemporary spawning capacity of the s|OR is unknown, and this metric is critical to guide the conservation and restoration of this keystone species. We employed a spawning capacity model relating fish length and gravel size to spawning potential. We collected substrate data at 49 sites throughout our 37‐km study area, and used fish length and egg numbers from n = 269 Sockeye Salmon to establish s|OR specific fecundity metrics. The model estimated the s|OR has the capacity to support 147,687 (±33,346) Sockeye spawners, in its current condition. Whilst our model has limitations, we suggest a minimum escapement of 147,687 Sockeye spawners ought to be passed to the s|OR per annum. These fish will have broad ecosystem benefits and will be culturally beneficial to SONA peoples. Finally, continued restoration of s|OR habitat should enhance opportunities for Sockeye Salmon to continue their remarkable recovery.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".