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Record W2026403610 · doi:10.1525/auk.2008.125.1.51

PRESENCE OF SALMON INCREASES PASSERINE DENSITY ON PACIFIC NORTHWEST STREAMS

2008· article· en· W2026403610 on OpenAlexafffund
Katie S. Christie, T. E. Reimchen

Bibliographic record

VenueThe Auk · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGeographyRiparian zoneFisheryEcologySTREAMSSongbirdOncorhynchusAbundance (ecology)HabitatBiologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The annual migration of Pacific salmon (Oncorhynchus spp.) to freshwater streams and lakes provides an important nutrient subsidy to terrestrial systems in North America. We investigated the effects of salmon and other habitat variables on abundance of Winter Wren (Troglodytes troglodytes), Swainson's Thrush (Catharus ustulatus), Varied Thrush (Ixoreus naevius), Pacific-slope Flycatcher (Empidonax difficilis), Golden-crowned Kinglet (Regulus satrapa), and Chestnut-backed Chickadee (Poecile rufescens) on the central coast of British Columbia. In our comparisons of salmon-bearing and non-salmon-bearing reaches of two rivers that had waterfall barriers to salmon partway upstream, we found that position above or below the falls and proximity to the stream were the major predictors of songbird abundance. Each species, except for Chestnut-backed Chickadee, had higher densities below the falls at both rivers. Our results suggest that salmon-derived nutrients influence songbird density, and thus benefit multiple trophic levels within riparian ecosystems. La présence du saumon augmente la densité de passereaux près des cours d'eau du nord-ouest du Pacifique

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 score0.052
Threshold uncertainty score0.103

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.199
Teacher spread0.188 · 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

Citations42
Published2008
Admission routes2
Has abstractyes

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