The Role of Angler Behaviour on the Post-Release Locomotor Activity and Depth Selection of Angled Fish Revealed by Biologgers
Bibliographic record
Abstract
Catch-and-release (C&R) angling is a growing practice worldwide with the number of fish released each year by anglers in the billions.Research has demonstrated that C&R can result in significant physiological stress for fish, however few studies have been able to observe fine-scale behaviour in the wild after they are released from angling events.Recent advancements in technology have led to the development of smaller biologging devices that are able to be attached to fish externally or surgically implanted in order to gather behavioural data of fish in the wild.The goal of my thesis was to assess fish behaviour in the wild following various angling scenarios using externally attached biologgers.Chapter 2 focused on assessing the impacts of air exposure on the post-release behaviour of three gamefish species.My data suggested that Northern Pike that were air-exposed exhibited decreased swimming activity immediately after release, however the same trends were not observed for Smallmouth Bass or Walleye.In chapter 3, I evaluated the efficacy of assisted recovery methods at reducing postrelease behavioural impairments in Rainbow Trout.I determined that assisted recovery was effective at reducing equilibrium impairments, especially if the water temperature in the recovery devices was significantly cooler than ambient surface water temperatures.In both chapters, behavioural data was gathered using externally attached biologgers equipped with tri-axial accelerometers and pressure/temperature sensors.Collectively, these results suggest that the impacts of a C&R event on the swimming activity of released fish can vary greatly with the species targeted, angler behaviour, and environmental factors.My thesis also introduces a novel, minimally invasive method for the external attachment of biologgers on fish for monitoring postrelease behaviour in a natural setting.II Dedication To Steve, thank you for your constant support and positivity throughout my time in the lab.Over the past 3 years I've learnt things that I never would have imagined, such as how to drive a trailer, how to write code, and how to set the hook.I will forever be grateful for all the opportunities that this lab has given me.To Andy, Gabe, and Michael, thank you for your guidance.Advising a student remotely was not an easy task and I am grateful for the mentorship that I received from you all.To my field partners and closest friends: Danny, Alley, Jess, Ben, Pete, Jen and Brooke, thank you for sticking
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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".