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Record W2088451034 · doi:10.1139/x03-070

Effects of streamside logging on stream macroinvertebrate communities and habitat in the sub-boreal forests of British Columbia, Canada

2003· article· en· W2088451034 on OpenAlexvenueaboutno aff
Shirley A. Fuchs, Scott G. Hinch, Eric Mellina

Bibliographic record

VenueCanadian Journal of Forest Research · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicFreshwater macroinvertebrate diversity and ecology
Canadian institutionsnot available
Fundersnot available
KeywordsLoggingEnvironmental scienceTaigaRiparian zoneBiomass (ecology)BorealCoarse woody debrisSTREAMSHabitatEcologyGuildHydrology (agriculture)GeologyBiology

Abstract

fetched live from OpenAlex

Much of the future timber supply in the Northern Hemisphere will come from boreal and sub-boreal forests, yet there has been little investigation of how aquatic communities in these regions would be affected by logging. We conducted an empirical, comparative study to investigate the effects of streamside clear-cut logging on benthic macroinvertebrates, algal standing stock, and in-stream physical and chemical habitats in the sub-boreal central interior region of British Columbia. We found that streams that flowed through old-growth forests (sites termed "not logged") did not differ from streams flowing through older logged forests (where the riparian zones were harvested 20–25 years before our sampling; sites termed "older logged") with respect to macroinvertebrate total density or biomass, feeding guild density or biomass, and chlorophyll a biomass. However, streams flowing through newly logged forests (where the riparian zones were harvested within 5 years of our sampling; sites termed "recently logged") had nearly twice the macroinvertebrate biomass as those in not logged or older logged sites and higher chlorophyll a biomass. There were no differences among the three stream categories in regard to structural aspects of the physical habitat (e.g., substrate composition, large organic debris density, dimensions of pools and riffles). Streamside logging in sub-boreal forests appears to enhance primary and secondary production, but this phenomenon may only be evident for the first two decades following logging.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.019
Threshold uncertainty score0.362

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.212
Teacher spread0.199 · 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.

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

Citations53
Published2003
Admission routes2
Has abstractyes

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