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Record W2166460914 · doi:10.1139/cjfr-2014-0177

Determinants of survival over 7 years for a natural cohort of sugar maple seedlings in a northern hardwood forest

2014· article· en· W2166460914 on OpenAlexvenueno aff
Natalie L. Cleavitt, John J. Battles, Timothy J. Fahey, Joel D. Blum

Bibliographic record

VenueCanadian Journal of Forest Research · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
FundersDivision of Environmental Biology
KeywordsYellow birchMapleAceraceaeBiologySeedlingSugarHardwoodEcologyAgronomy

Abstract

fetched live from OpenAlex

The regeneration ecology of sugar maple (Acer saccharum Marsh.) has been impacted by acid rain leaching of base cations from the soils throughout much of its range. We tracked the survival and causes of death for a natural cohort of sugar maple seedlings across 22 sites in the Hubbard Brook Valley in New Hampshire, USA, where soil acidification has been documented. Survival over 7 years averaged 3.4%; however, significant differences in survival were observed among sites, which were classified into three main groups based on the shape of their survival curves. These site groups differed in position on the landscape, seedling nutrition and leaf size, and the prevalence of damage agents, but not in soil Ca. First-season mortality was high (71%), and the main damage agents were fungal infection (Rhizoctonia spp.) and caterpillar herbivory (Geometridae). Other principal causes of mortality in order of importance were winter injury, mechanical damage, and rodent (Myodes gapperi Vigors, 1830) tunneling, and all damage agents varied significantly in severity between years. This study highlights the importance of landscape-level variation in biotic factors for predicting sugar maple regeneration success. Predictions of sugar maple regeneration will require a better understanding of controls on initial seedling growth and the suite of biotic agents that damages seedlings.

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)0.001
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 score0.964
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.017
GPT teacher head0.279
Teacher spread0.262 · 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

Citations28
Published2014
Admission routes1
Has abstractyes

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