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Record W2102402140 · doi:10.1139/x04-202

Stream habitat and rainbow trout (<i>Oncorhynchus mykiss</i>) physiological stress responses to streamside clear-cut logging in British Columbia

2005· article· en· W2102402140 on OpenAlexvenueaboutno aff
Eric Mellina, Scott G. Hinch, Edward M. Donaldson, Greg Pearson

Bibliographic record

VenueCanadian Journal of Forest Research · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRainbow troutTroutLoggingHabitatEnvironmental scienceFisheryEcologyBiologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The impacts associated with streamside clear-cut logging (e.g., increased temperatures and sedimentation, loss of habitat complexity) are potentially stressful to stream-dwelling fish. We examined stream habitat and rainbow trout physiological stress responses to clear-cut logging in north-central British Columbia using 15 streams divided into three categories: old growth (reference), recently logged (clear-cut to both banks 1–9 years prior to the study), and second growth (clear-cut 25–28 years prior to the study). We used plasma cortisol and chloride concentrations as indicators of acute stress, and interrenal nuclear diameters, impairment of the plasma cortisol response, and trout condition and length-at-age estimates as indicators of chronic stress. No statistically significant acute or chronic stress responses to streamside logging were found, despite increases in summertime stream temperatures (daily maxima and diurnal fluctuations) and a reduction in the average overall availability of pool habitat. Our observed stress responses were approximately an order of magnitude lower than what has previously been reported in the literature for a variety of different stressors, and trout interrenal nuclear diameters responses to the onset of winter were approximately five times greater than those to logging. The overall consistency of our results suggests that the impacts of streamside clear-cut logging are not acutely or chronically stressful to rainbow trout in our study area.

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 score0.190
Threshold uncertainty score0.382

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.025
GPT teacher head0.279
Teacher spread0.254 · 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
Published2005
Admission routes2
Has abstractyes

Explore more

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