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Record W2525575834 · doi:10.7717/peerj.2874

The fishing and natural mortality of large, piscivorous Bull Trout and Rainbow Trout in Kootenay Lake, British Columbia (2008–2013)

2017· article· en· W2525575834 on OpenAlexafffundabout
Joe Thorley, Greg Andrusak

Bibliographic record

VenuePeerJ · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsMinistry of Forests
FundersHabitat Conservation Trust Foundation
KeywordsRainbow troutFisheryTroutFishingRecreational fishingSalvelinusCatch and releaseFish measurementEnvironmental scienceBiologyCommercial fishingFish <Actinopterygii>

Abstract

fetched live from OpenAlex

BACKGROUND: Estimates of fishing and natural mortality are important for understanding, and ultimately managing, commercial and recreational fisheries. High reward tags with fixed station acoustic telemetry provides a promising approach to monitoring mortality rates in large lake recreational fisheries. Kootenay Lake is a large lake which supports an important recreational fishery for large Bull Trout and Rainbow Trout. METHODS: Between 2008 and 2013, 88 large (≥500 mm) Bull Trout and 149 large (≥500 mm) Rainbow Trout were marked with an acoustic transmitter and/or high reward ($100) anchor tags in Kootenay Lake. The subsequent detections and angler recaptures were analysed using a Bayesian individual state-space Cormack-Jolly-Seber (CJS) survival model with indicator variable selection. RESULTS: The final CJS survival model estimated that the annual interval probability of being recaptured by an angler was 0.17 (95% CRI [0.11-0.23]) for Bull Trout and 0.14 (95% CRI [0.09-0.19]) for Rainbow Trout. The annual interval survival probability for Bull Trout was estimated to have declined from 0.91 (95% CRI [0.76-0.97]) in 2009 to just 0.46 (95% CRI [0.24-0.76]) in 2013. Rainbow Trout survival was most strongly affected by spawning. The annual interval survival probability was 0.77 (95% CRI [0.68-0.85]) for a non-spawning Rainbow Trout compared to 0.41 (95% CRI [0.30-0.53]) for a spawner. The probability of spawning increased with the fork length for both species and decreased over the course of the study for Rainbow Trout. DISCUSSION: Fishing mortality was relatively low and constant while natural mortality was relatively high and variable. The results indicate that angler effort is not the primary driver of short-term population fluctations in the Rainbow Trout abundance. Variation in the probability of Rainbow Trout spawning suggests that the spring escapement at the outflow of Trout Lake may be a less reliable index of abundance than previously assumed. Multi-species stock assessment models need to account for the fact that large Bull Trout are more abundant than large Rainbow Trout in Kootenay Lake.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.910
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.229
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2017
Admission routes3
Has abstractyes

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