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Record W2029027498 · doi:10.1139/f00-002

Stream channel configuration, landform, and riparian forest structure in the Cascade Mountains, Washington

2000· article· en· W2029027498 on OpenAlexvenueno aff
Byron Rot, Robert J. Naiman, Robert E. Bilby

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsnot available
FundersU.S. Forest Service
KeywordsRiparian zoneLarge woody debrisRiparian forestLandformRiffleSinuosityBasal areaGeologyChannel (broadcasting)FloodplainHydrology (agriculture)DeciduousGeomorphologyEcologyHabitatGeographyForestryBiology

Abstract

fetched live from OpenAlex

The hierarchical relationship of five key elements, valley constraint, riparian landform, riparian plant community, channel type, and channel configuration, are described for 21 sites in mature to old-growth riparian forests of the western Cascades Mountains, Washington, U.S.A. Channel type (bedrock, plane-bed, and forced pool-riffle) was closely related to channel configuration (especially large woody debris (LWD) volume, density, and LWD-formed pools) at the smallest spatial scale and valley constraint at the largest. Valley constraint significantly influenced off-channel habitat (r 2 = 0.71) and LWD volume within forced pool-riffle channels (r 2 = 0.58). Riparian plant community composition was differentiated by four landform classes: three alluvial landforms based on height above the channel and one based on hillslope. Just above the active channel, floodplain landforms contained more deciduous stems than conifer and greater conifer basal area than deciduous. Conifers dominated other landforms. The diameter of in-channel LWD increased with the age of the riparian forest (r 2 = 0.34). In old-growth forests, LWD diameter was equivalent to or greater than the average riparian tree diameter for all sites. In younger forests, the mixed relationship between LWD and riparian tree diameter may reflect a combination of LWD input from the previous old-growth stand and LWD input from the existing stand.

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)0.000
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 score0.269
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.009
GPT teacher head0.196
Teacher spread0.187 · 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

Citations71
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicHydrology and Sediment Transport ProcessesFrench-language works237,207