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Record W4306168983 · doi:10.1139/cjfas-2021-0339

Sensitivity analysis of a lake sturgeon population with early life stage density-dependent effects

2022· article· en· W4306168983 on OpenAlexafffundvenueabout
James D. Burchfield, Brian McLaren, Darryl T. McLeod

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsMinistry of Natural Resources and ForestryLakehead University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of LethbridgeSouth Dakota State UniversityMinistry of Natural ResourcesOntario Ministry of Natural Resources and ForestryMinnesota Department of Natural Resources
KeywordsLake sturgeonJuvenileAcipenserVital ratesPopulationHabitatBiologyPopulation modelEcologySturgeonStage (stratigraphy)Density dependencePopulation growthFisheryDemographyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Lake sturgeon ( Acipenser fulvescens) exhibit a complex life-history strategy where behaviour, including habitat selection, depends on ontogenetic stage. Protection or recovery efforts for one stage may not impact other stages. Stage-structured models have been used to explore the sensitivity of the population to changes in vital rates of individual stages. Recent research demonstrates that juvenile mortality may be lower than estimated in prior modelling efforts and density-dependent. We constructed a Lefkovitch matrix model to reflect an updated understanding of the prerecruitment stages of the lake sturgeon. We then compared the model to a population of lake sturgeon on the Ontario−Minnesota border. Our model predicts that population growth rate, time to equilibrium, and final population size were most sensitive to changes to the survival of early adults, followed by subadults and juveniles. Sensitivity to changes in age-0 survival was very low in contrast to earlier modelling efforts, while sensitivities to juvenile (ages 1–7 years) and subadult (ages 8–23 years) were higher than previously reported values.

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)0.007
metaresearch head score (Gemma)0.022
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.192
Teacher spread0.184 · 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

Citations2
Published2022
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic Sciences→Same topicFish Ecology and Management Studies→French-language works237,207→