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Record W2137154620 · doi:10.22230/jem.2007v8n1a363

Natural regeneration of lodgepole pine following partial harvesting on northern caribou winter range in west-central British Columbia

2007· article· en· W2137154620 on OpenAlexaffabout
O. A. Steen, M. J. Waterhouse, Harold M. Armleder, Nola M. Daintith

Bibliographic record

VenueJournal of Ecosystems and Management · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsGovernment of British Columbia
Fundersnot available
KeywordsStockingPinus contortaHectareLoggingAbies lasiocarpaRange (aeronautics)Natural regenerationBorealSeedlingForestryEnvironmental scienceBiologyEcologyGeographyAgronomy

Abstract

fetched live from OpenAlex

This study compares pine natural regeneration density and height growth in small harvested openings (0.01–0.07 ha) within two biogeoclimatic subzones (Sub-Boreal Pine–Spruce [SBPS] xc and Montane Spruce [MS] xv) and three partial harvesting treatments on northern caribou (Rangifer tarandus caribou Gmelin) winter range in the western Chilcotin region of British Columbia, Canada. Regeneration density was assessed annually for 7 years (1996–2002). In year 7, post-logging ingress stems > 1 year old had a significantly greater density on SBPSxc blocks (5898 stems per hectare) than on the higher-elevation MSxv blocks (1829 stems per hectare). The percentage of 2-m2 plots with a natural post-logging seedling > 1 year old averaged 52% in the SBPSxc and 31% in the MSxv. Advance regeneration added substantially to density and stocking in the SBPSxc but not in the MSxv. These results indicate that small (0.01–0.07 ha) harvested openings in the SBPSxc can be naturally restocked by lodgepole pine without post-logging site preparation, but higher-elevation blocks in the MSxv will need to be planted to ensure full stocking by lodgepole pine within 7 years. However, the long period between harvest entries on caribou winter range may still allow sufficient time to naturally regenerate openings in the MSxv.

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 score0.548
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.005
GPT teacher head0.197
Teacher spread0.192 · 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

Citations10
Published2007
Admission routes2
Has abstractyes

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