hysiological and Behavioural Responses of Lake Trout to Catch-And-Release Angling
Bibliographic record
Abstract
Lake trout (Salvelinus namaycush), like many other native fishes in North America are a popular species typically targeted for recreational angling. Catch-and-release angling (C&R) relies on the assumption of high fish survival following release and is considered an effective way to preserve wild stocks of fish. Salmonids and other related species are susceptible to recreational angling, which can induce stress during different parts of the process (e.g., line fighting and air exposure). Other factors can impact fish health (e.g., water temperature and hooking location) and potentially lead to delayed mortality. In this thesis, I present empirical research where I used reflex impairment, physiology, and overall activity to assess the robustness of lake trout to C&R across seasons and time scales. During ice angling, lake trout experienced signs of reflex and physiological impairment up to 6 h and a high mortality rate. A key finding was that lake trout may exhibit pressure-related injuries in cooler water temperatures despite being physostomous. During open water angling, lake trout experienced barotrauma, reflex impairment, and physiological impairment immediately upon capture and 0.5 h post-angling. The addition of post-release activity monitoring via tri-axial accelerometry showed that lake trout rapidly swim to depth and exhibit reduced activity for the first 14 min after release. Collectively, I demonstrate that using multiple metrics of assessing angling-related impairment (i.e., both external and internal metrics) is necessary and future studies should not rely on one or few indices. The work presented here provides new information regarding context-specific aspects of C&R and is useful for recreational fisheries management.
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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".