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Record W2050431152 · doi:10.1139/x05-272

Factors affecting distribution of wood, detritus, and sediment in headwater streams draining managed young-growth red alder conifer forests in southeast Alaska

2006· article· en· W2050431152 on OpenAlexvenueno aff
Takashi Gomi, A. C. Johnson, Robert L. Deal, Paul E. Hennon, Ewa H. Orlikowska, Mark S. Wipfli

Bibliographic record

VenueCanadian Journal of Forest Research · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Sediment Transport Processes
Canadian institutionsnot available
FundersCore Research for Evolutional Science and TechnologyU.S. Department of Agriculture
KeywordsAlderRiparian zoneDetritusSTREAMSRiparian forestSedimentEnvironmental scienceEcologyChannel (broadcasting)Hydrology (agriculture)ForestryGeologyGeographyBiologyHabitatGeomorphology

Abstract

fetched live from OpenAlex

Factors (riparian stand condition, management regimes, and channel properties) affecting distributions of wood, detritus (leaves and branches), and sediment were examined in headwater streams draining young-growth red alder (Alnus rubra Bong.) – conifer riparian forests (< 40 years old) in southeast Alaska. More riparian red alder were found along streams affected by both timber harvesting and mass movement than in streams affected by timber harvesting alone. Young-growth stands produced little large wood material (diameter ≥10 cm) and had little effect on altering the size distribution of functional large wood in channels, although more alder wood pieces were found in streams with greater numbers of riparian alder trees. Legacy wood pieces (>40 years old) remained in channels and provided sites for sediment and organic matter storage. Despite various alder–conifer mixtures and past harvesting effects, the abundance of large wood, fine wood, and detritus accumulations significantly decreased with increasing channel bank-full width ( 0.5–3.5 m) along relatively short channel distances (up to 700 m). Changes in wood, detritus, and sediment accumulations together with changes in riparian stand characteristics create spatial and temporal variability of in-channel conditions in headwater systems. A component of alder within young-growth riparian forests may benefit both wood production and biological recovery in disturbed headwater stream channels.

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)0.002
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 score0.581
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.021
GPT teacher head0.258
Teacher spread0.237 · 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

Citations20
Published2006
Admission routes1
Has abstractyes

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