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Record W2037445916 · doi:10.4296/cwrj3004331

Camp Creek Revisited: Streamflow Changes Following Salvage Harvesting in a Medium-Sized, Snowmelt-Dominated Catchment

2005· article· en· W2037445916 on OpenAlexfundvenueaboutno aff
R. D. Moore, David F. Scott

Bibliographic record

VenueCanadian Water Resources Journal / Revue canadienne des ressources hydriques · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSnowmeltDrainage basinStreamflowHydrology (agriculture)Environmental scienceSTREAMSWater yearDrainageSnowElevation (ballistics)GeologyGeographyEcologyGeomorphologyBiology

Abstract

fetched live from OpenAlex

This study used a paired-catchment approach to investigate the effects of harvesting on streamflow for Camp Creek, a snowmelt-dominated stream in the southern interior of British Columbia. The drainage area for Camp Creek is 33.9 km2, and 27 percent of the area was harvested in response to a pine beetle infestation. Adjacent Greata Creek, with a drainage area of 40.7 km2, served as a control. Harvesting resulted in a significant increase in April flows, which persisted with no evidence of recovery through the 18-year post-treatment period, as well as a significant advance in the timing of peak flows relative to those for the control stream. No significant nor apparent changes in seven-day low flows were detected. Peak flows appeared to increase for smaller events, but not for larger events, although this result was not statistically significant. Detection of significant harvesting effects on low flows, peak flows and annual water yield may have been hampered by inherent differences between the two catchments, particularly in relation to aspect and elevation distribution, as well as by the effects of a climate shift that coincided with the harvesting treatment, and which was associated with low snow accumulation throughout the post-treatment period. Problems with finding well-matched catchment pairs likely represent a fundamental limitation in applying the paired-catchment approach to estimate the effects of forest harvesting in medium to large catchments.

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)0.001
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 score0.816
Threshold uncertainty score0.366

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.011
GPT teacher head0.206
Teacher spread0.196 · 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

Citations50
Published2005
Admission routes3
Has abstractyes

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