Sportfish population dynamics in an intensively managed river system
Bibliographic record
Abstract
The Elk River valley is intensively utilized by various resource industries including a recreational fishery that predominates in the river section between Sparwood and Elko. Most angling comes from fly-fishers in drift boats who mainly target westslope cutthroat trout (WCT) Onchorhyncus clarkii lewisi in the summer, but also secondarily catch bull trout (BT) Salvelinus confluentus. Non-native rainbow trout (RB) Onchorhyncus mykiss and Eastern brook trout (EB) Salvelinus fontinalis have also been introduced to the system. The river’s trout and char populations have never been directly examined in response to fishing regulations. In 2006 and 2007, I used ecological survey methods to determine WCT growth, mortality, and abundance in a series of catch-and-release and catch-and-keep regulation zones of the lower mainstem Elk River. I assessed the angling effort response to WCT and BT densities in the lower mainstem and systematically determined the relative recruitment capability of the two drainage basins in the tributary system. I estimated 10,050 WCT inhabited the lower mainstem in 2006 with 16,200 WCT in 2007, indicating an annual recruitment of 5,753 fish into the mainstem. Growth was inversely related to fish density, particularly in the first fractal plane of the tributary system. Effects on mortality due to fishing pressure could not be directly determined from effort, but mortality rates were slightly higher in the harvest zones in 2007, especially in the first fractal division of tributaries. Angling effort showed a linear increase with WCT densities. In the tributary system, the highest WCT densities were found in the Michel drainage, whereas BT recruitment appeared largely restricted to the Upper Elk drainage. A strong EB presence in the upper Michel drainage coupled by an absence of BT suggests that EB have displaced BT in warmer streams in this river system, which may even lead to improved WCT densities. This initial investigation indicates that active monitoring of the Elk River sportfish populations can feasibly be integrated into a system-wide adaptive management strategy.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".