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Record W4234736154 · doi:10.2458/azu_jrm_v53i5_bai

Early establishment of Douglas-fir and ponderosa pine in grassland seedbeds

2000· article· en· W4234736154 on OpenAlexaff
Y. Bai, D. Thompson, K. Broersma

Bibliographic record

VenueJournal of Range Management · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicSeedling growth and survival studies
Canadian institutionsKamloops Art Gallery
Fundersnot available
KeywordsSeedlingGerminationLitterGrasslandAgronomyGrowing seasonDouglas firBiologyPinus <genus>ManureEnvironmental scienceBotany

Abstract

fetched live from OpenAlex

Grassland of interior British Columbia are being encroached upon by Douglas-fir (Pseudotsuga menziesii var. glauca (Beissn.) Franco) and ponderosa pine (Pinus ponderosa Dougl.). A pot experiment placed in the field was conducted to determine the effect of forest and grassland seedbeds on seedling emergence and early establishment of the 2 species with 2 seed collections each. For these seedbeds, structural characteristics were evaluated and the effect of seedbeds water extracts on seed germination was determined. Seedling emergence of both species was significantly reduced by Douglas-fir needles and enhanced by fescue litter and cattle manure compared to mineral soil. The rate of emergence was reduced by Douglas-fir needles and sagebrush litter, and for some collections, by ponderosa pine needles, but was always enhanced by manure compared to mineral soil. Seedling survival was generally not affected by seedbeds. Douglas-fir seedlings emerging earlier in the season survived better, and both Douglas-fir and ponderosa pine seedlings emerging earlier lived longer than these emerging later. Seed germination of ponderosa pine was not affected by the water extract while that of Douglas-fir was reduced by the water extract from sagebrush litter. Therefore, differences in seedling emergence of the 2 species among seedbeds were related more to structural than to chemical characteristics of seedbeds. Successful establishment of the 2 species in grasslands within this region likely relies on the ability of seeds to germinate early in the growing season on seedbeds in which soil moisture is conserved, as summer droughts are severe.

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)0.000
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 score0.096
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.007
GPT teacher head0.202
Teacher spread0.195 · 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

Citations0
Published2000
Admission routes1
Has abstractyes

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