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Record W4380489022 · doi:10.1002/nafm.10917

Lake Sturgeon population trends in the St. Clair–Detroit River system, 2001–2019

2023· article· en· W4380489022 on OpenAlexaff
Justin A. Chiotti, James C. Boase, Andrew S. Briggs, Chris L. Davis, Richard Drouin, Darryl W. Hondorp, Lloyd C. Mohr, Edward F. Roseman, Michael V. Thomas, Todd C. Wills

Bibliographic record

VenueNorth American Journal of Fisheries Management · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsMinistry of Energy, Northern Development and Mines
FundersU.S. Fish and Wildlife Service
KeywordsLake sturgeonAcipenserSturgeonPopulationEndangered speciesFisheryHabitatThreatened speciesGeographyRange (aeronautics)Abundance (ecology)EcologyEnvironmental scienceBiologyFish <Actinopterygii>Demography

Abstract

fetched live from OpenAlex

Abstract Objective The Lake Sturgeon Acipenser fulvescens is listed as threatened or endangered in 15 states or provinces within the species' native range. Accordingly, investments in habitat and population restoration for this species have increased throughout the Great Lakes. To aid in the evaluation of restoration efficacy, robust population parameters are needed to inform management decisions. The St. Clair–Detroit River system (SCDRS) contains one of the largest self-sustaining Lake Sturgeon populations in the Great Lakes; however, recent estimates of population abundance and growth parameters have not been assessed. Methods Our study used baited setline and mark–recapture data collected between 2001 and 2019 to estimate whether the number of Lake Sturgeon captured varied annually and/or with water temperature and whether population abundance and the population growth rate (λ) varied among three subpopulations located in the SCDRS. Result Trends in the number of Lake Sturgeon captured on setlines varied among subpopulations and by life stage. Annual trends in the number of Lake Sturgeon captured remained consistent over time in the upper St. Clair River, decreased for adults and increased for subadults in the lower St. Clair River, and increased in the Detroit River. With subpopulation abundances of 20,184 (95% confidence interval [CI] = 12,533–27,816) in the upper St. Clair River/southern Lake Huron, 6523 (95% CI = 5720–7327) in the lower St. Clair River, and 6416 (95% CI = 4065–8767) in the Detroit River, our study confirms that the SCDRS contains the largest Lake Sturgeon population with unimpeded access to the Great Lakes. The geometric mean λ for all subpopulations indicated stable populations and ranged from 1.00 to 1.16. Conclusion Our study provides an updated assessment of Lake Sturgeon population parameters that serve as a baseline to evaluate habitat restoration efforts and to inform management of the SCDRS recreational Lake Sturgeon fishery.

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)0.001
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 score0.072
Threshold uncertainty score0.142

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.009
GPT teacher head0.214
Teacher spread0.205 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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