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Record W2608284382 · doi:10.1080/00028487.2017.1317663

Trends in Rainbow Trout Recruitment, Abundance, Survival, and Growth during a Boom‐and‐Bust Cycle in a Tailwater Fishery

2017· article· en· W2608284382 on OpenAlexaff
Josh Korman, Michael D. Yard, Theodore A. Kennedy

Bibliographic record

VenueTransactions of the American Fisheries Society · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsEcoMetrix
FundersU.S. Geological SurveyArizona Game and Fish Department
KeywordsRainbow troutPopulationBiologyFisheryTailwaterTroutJuvenileAbundance (ecology)CanyonPredationEcologyAnimal scienceDemographyFish <Actinopterygii>GeographyOceanography

Abstract

fetched live from OpenAlex

Abstract Data from a large‐scale mark–recapture study were used in an open‐population model to determine the cause for long‐term trends in growth and abundance of a Rainbow TroutOncorhynchus mykisspopulation in the tailwater of Glen Canyon Dam, Arizona. Reduced growth affected multiple life stages and processes, causing negative feedbacks that regulated the abundance of the population, including higher mortality of larger fish; lower rates of recruitment (young of the year) during years when growth was reduced; and lower rates of sexual maturation in the following year. High and steady flows during spring and summer 2011 resulted in a very large recruitment event. The population had declined tenfold by 2016 due to a combination of lower recruitment and reduced survival of larger trout. Survival rates for 225‐mm and larger Rainbow Trout in 2014, 2015, and 2016 were 11, 21, and 22% lower, respectively, than average survival rates between 2012 and 2013. Abundance at the end of the study would have been threefold to fivefold higher if survival rates for larger individuals had remained at the elevated levels estimated for 2012 and 2013. Growth declined between 2012 and 2014 owing to reduced prey availability, which led to very poor fish condition (~0.90–0.95) by fall 2014. Poor condition in turn resulted in low survival rates of larger fish during fall 2014 and winter 2015, which contributed to the population collapse. In Glen Canyon, large recruitment events driven by high flows can lead to population increases that cannot be sustained due to limitations in prey supply. When the ability to regulate prey supply is lacking, flows that reduce the probability of large recruitment events can be used to avoid boom‐and‐bust population cycles. Our study demonstrates that mark–recapture is a very informative approach for understanding the dynamics of tailwater trout populations. Received December 6, 2016; accepted March 31, 2017 Published online August 2, 2017

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.085
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.246
Teacher spread0.224 · 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 source (direct Gemma or distilled Codex), 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

Citations19
Published2017
Admission routes1
Has abstractyes

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