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Record W2157979807 · doi:10.1139/x00-042

Establishment of tree seedlings and water-soluble nutrients in coarse woody debris in an old-growth <i>Picea</i>-<i>Abies</i> forest in Hokkaido, northern Japan

2000· article· en· W2157979807 on OpenAlexvenueno aff
Masamichi Takahashi, Yoshimi Sakai, Reiko Ootomo, Masao Shiozaki

Bibliographic record

VenueCanadian Journal of Forest Research · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCoarse woody debrisMicrositePicea abiesForest floorSeedlingSeedbedForestryPinaceaeBotanyEnvironmental scienceBiologyAgronomyEcologySoil waterHabitatGeographyPinus <genus>

Abstract

fetched live from OpenAlex

Forest floor microsite conditions and tree seedling establishment were studied at an old-growth Picea-Abies forest in Hokkaido Island, northern Japan. Tree seedlings were established abundantly on coarse woody debris (CWD) from decay class III, a class indicating moderate decay, to class V, the most advanced decay class. The height-class distribution of tree seedlings indicates that the recruitment of Picea glehnii (Fr. Schm.) Masters and Picea jezoensis (Sieb. et Zucc.) Carr. seedlings on CWD started on decay class II and was mostly restricted to CWD decay class III. Seedlings of Abies sachalinensis (Fr. Schm.) Masters also favored establishment on CWD but had a wide adaptability to most of the microsites. Although CWD functioned as a suitable seedbed, water extracts from CWD were acidic and had quite low mineral nutrient concentrations. Tree seedling establishment did not necessarily require high levels of nutrient content in microsites. Although the forest floor was largely covered by CWD, with 2056 m 2 ·ha -1 of the total projected area covered by CWD, CWD decay class III covered only 366 m 2 ·ha -1 of the forest floor, indicating that CWD as a functioning seedbed is limited by time and space on the forest floor.

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)0.001
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 score0.829
Threshold uncertainty score0.852

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.026
GPT teacher head0.235
Teacher spread0.210 · 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

Citations119
Published2000
Admission routes1
Has abstractyes

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