MétaCan
Menu
← Back to cohort
Record W4238268571 · doi:10.1139/f00-129

Effects of forestry roads on reproductive habitat and exploitation of lake trout (<i>Salvelinus namaycush</i>) in three experimental lakes

2000· article· en· W4238268571 on OpenAlexvenueno aff
John M. Gunn, Rod Sein

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSalvelinusTroutFisherySiltationHabitatFontinalisFishingEnvironmental sciencePopulationEcologyGeographyFish <Actinopterygii>BiologySediment

Abstract

fetched live from OpenAlex

This study was designed to test the effects of two potential impacts of forest access roads on lake trout (Salvelinus namaycush) lakes in the Boreal Shield ecozone: (i) loss of reproductive habitat through siltation and (ii) increased access and exploitation. During an 9-year study (1991-1999) in Whitepine Lake, access to seven original spawning sites and over 250 alternate spawning sites was progressively removed by covering the substrate with opaque plastic sheeting to simulate siltation. No effects on recruitment of lake trout have yet been detected. Mark-recapture estimates of juvenile (<370 mm fork length) abundance remained high, mean body size did not increase, and emergent alevins continued to be produced from the alternate spawning sites each year. Similar results occurred in a short-term study in Helen Lake. The lack of obvious effects of reproductive habitat loss was in sharp contrast with the rapid and severe effects that fishing pressure exerted on the lake trout population in Michaud Lake where access was improved by construction of a 12-km forest access road. These findings suggest that lake trout can tolerate substantial losses in spawning habitat, but natural populations, particularly in small lakes, must be protected from excessive exploitation.

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 score0.987
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.010
GPT teacher head0.207
Teacher spread0.198 · 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

Citations38
Published2000
Admission routes1
Has abstractyes

Explore more

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