MétaCan
Menu
Back to cohort
Record W2790319840 · doi:10.1080/02723646.2018.1434926

Influences of fine-scale disturbance on germinant success in a treeline ecotone

2018· article· en· W2790319840 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePhysical Geography · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaArctic Institute of North America
KeywordsQuadratEcotoneTundraSeedlingDisturbance (geology)Environmental scienceEcologyGerminationEcosystemBiologyAgronomyShrub

Abstract

fetched live from OpenAlex

Fine-scale disturbance can increase seed access to suitable substrates, facilitating germinant emergence and survival, which are necessary elements for treeline advance. We conducted an experiment to test this hypothesis in a white spruce (Picea glauca) treeline ecotone in southwest Yukon, Canada. Sixty seed germination quadrats were established at two elevations (treeline and alpine tundra) and subjected to three levels of simulated disturbance. We sowed 125 seeds in half of the quadrats (30) and measured their emergence and survival over 3 years. Soil temperature, moisture, and organic depth were recorded in all treatments. Treeline quadrats had significantly greater seedling emergence and survival than alpine tundra quadrats. Mean soil temperature, moisture, and organic layer depth were all greater in treeline quadrats. Partially scarified quadrats had the highest germinant emergence compared to unscarified and completely scarified quadrats. Completely scarified quadrats had the highest temperature range and the lowest soil moisture. The results indicate that moderate levels of disturbance can positively influence seedling emergence, while more severe disturbance can lead to high temperature ranges and moisture loss that negate the benefits of lower interspecific competition. Collectively, our findings suggest that fine-scale disturbance can play a significant role in influencing seedling presence in treeline ecotones.

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.

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 score0.034
Threshold uncertainty score0.462

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.255
Teacher spread0.244 · 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