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Record W4214811319 · doi:10.5772/intechopen.101565

Complexity of Regeneration Dynamic at the Ecocline between Mixedwood and Coniferous Domains of the Southernmost Boreal Zone in Eastern North America

2022· book-chapter· en· W4214811319 on OpenAlexaboutno aff
Yassine Messaoud

Bibliographic record

VenueIntechOpen eBooks · 2022
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsBalsamAbies balsameaBlack spruceTaigaBorealRegeneration (biology)ForestrySeedlingEnvironmental scienceAgronomyEcologyBiologyBotanyGeography

Abstract

fetched live from OpenAlex

To explain the ecocline between the southern mixedwood and the northern coniferous bioclimatic domains dominated, respectively, by balsam fir (Abies balsamea (L.) Mill.) and black spruce (Picea mariana (Mill.) B.S.P.), 59 field sites and 7010 sample plots (from the Quebec Ministry of Forests, Wildlife, and Parks), with no major disturbances, were selected throughout the two bioclimatic domains. Regeneration (seedlings and saplings), mortality (difference between seedlings and saplings) of balsam fir, and black spruce (saplings) were examined, accounting for parental trees, main soil type (clay and till), summer growing degree-days above 5°C (GDD_5), and total summer precipitation (May–August; PP_MA). Balsam fir regeneration was more depended on parental trees and soil type than black spruce. Balsam fir mortality was related to seedling competition, species composition of the canopy, and the soil type. GDD_5 and marginally PP_MA were beneficial and detrimental for respectively balsam fir and black spruce regeneration. The ecocline mixedwood/coniferous bioclimatic domains was attributed to a northward gradual decrease of balsam fir regeneration and increase of its mortality, due to cooler temperatures, shorter growing seasons, and decrease of the parental trees. However, balsam fir persists above this ecocline, where parental trees populations and good establishment substrates occur.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.520
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.016
GPT teacher head0.218
Teacher spread0.202 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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