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Record W3018624093 · doi:10.1016/j.jglr.2020.03.014

Seasonal habitat-use differences among Lake Erie’s walleye stocks

2020· article· en· W3018624093 on OpenAlexafffundvenueabout
Jordan K. Matley, Matthew D. Faust, Graham D. Raby, Yingying Zhao, Jake M. Robinson, Tom MacDougall, Todd A. Hayden, Aaron T. Fisk, Christopher S. Vandergoot, Charles C. Krueger

Bibliographic record

VenueJournal of Great Lakes Research · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsTrent UniversityMinistry of Natural Resources and ForestryUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of WindsorGreat Lakes Fishery CommissionAdam Taliaferro Foundation
KeywordsHabitatFisheryStock (firearms)Structural basinStock assessmentTemporal scalesGeographyEcologySpatial ecologyPopulationEnvironmental scienceBiologyFishing

Abstract

fetched live from OpenAlex

Understanding the spatial ecology and habitat-use of Lake Erie’s commercially important walleye (Sander vitreus) population is imperative due to their large-scale seasonal migrations (>400 km) exposing them to five different jurisdictions in the USA and Canada. The objective of this study was to determine the habitat selected by walleye throughout the year and across Lake Erie. Here, we used acoustic telemetry to estimate walleye occurrence at three lake depth categories that were pertinent to biology (e.g., spawning) and management (e.g., quota allocation). Detection data from 851 adults during five continuous years identified consistent seasonal fluctuations in habitat selection across western (WB) and eastern (EB) basin walleye stocks. Sex-specific differences were also found during spawning periods (March-May) when males showed a stronger affinity to shallow waters <6 m than females. Also, EB stocks selected these shallow waters longer than WB stocks, likely due to differences in thermal patterns between basins. Deep water (>13 m) was readily selected between spring and winter (>6 months/year) for most WB and EB walleye despite stock-specific migration patterns. This study provides novel information about the space use patterns of one of the most economically important fish in North America at spatial and temporal scales relevant to management.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.064
GPT teacher head0.302
Teacher spread0.238 · 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.

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

Citations65
Published2020
Admission routes4
Has abstractyes

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