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Record W2136182215 · doi:10.1139/x06-286

Riparian forest harvesting and its influence on benthic communities of small streams of sub-boreal British Columbia

2007· article· en· W2136182215 on OpenAlexafffundvenueabout
K. Jill Melody, John S. Richardson

Bibliographic record

VenueCanadian Journal of Forest Research · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSTREAMSRiparian zoneEnvironmental scienceBenthic zonePeriphytonRiffleDetritusLoggingHydrology (agriculture)TaigaBiomass (ecology)EcologyPlant litterLitterRiparian forestEcosystemHabitatBiologyGeology

Abstract

fetched live from OpenAlex

Forest harvesting in riparian areas can alter the leaf-litter inputs, shading, and stability of small streams, and many of the details of these impacts are known for coastal streams of the Pacific Northwest. However, little is known about how small streams in the drier, continental areas of western North America respond to logging. We conducted a study of paired stream reaches (comparing one recently harvested (≤3 years) reach and two upstream, forested reaches in each of five streams) in which periphyton, detritus, macroinvertebrate abundance and biomass, and physical features were measured in summer and autumn. In general, recently harvested stream sections tended to be wider and contained more riffle areas than the upstream forested sections. The amounts of leaf litter and algae varied among streams and were not consistently greater or lesser in the forested sections than in the harvested sections. Though the variation in amounts within streams was mainly seasonal, amounts differed more among streams than between pairs of harvested and forested reaches. The communities of benthic invertebrates differed significantly between forested and harvested reaches, but often in opposite directions between streams. The magnitude and direction of differences observed between treatments, streams, or seasons were associated with the specific stream and the method of riparian harvesting used.

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 score0.181
Threshold uncertainty score0.365

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 studies0.0010.001
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 head0.035
GPT teacher head0.268
Teacher spread0.233 · 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

Citations24
Published2007
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Journal of Forest Research→Same topicHydrology and Sediment Transport Processes→French-language works237,207→