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Record W2729105597 · doi:10.1674/0003-0031-178.1.36

Recruitment Success for Mast Year Cohorts of Sugar Maple (Acer saccharum) Over Three Decades of Heavy Deer Browsing

2017· article· en· W2729105597 on OpenAlexaffabout
Jennifer Macmillan, Lonnie W. Aarssen

Bibliographic record

VenueThe American Midland Naturalist · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsMast (botany)BiologyPopulationCohortWoodlandDemographyGeographyEcologyForestryMast cellMedicine

Abstract

fetched live from OpenAlex

We examined whether particular years of mast seed production in sugar maple (Acer saccharum) are associated with increased likelihood of cohort recruitment success into the sapling stage over three decades of heavy browsing pressure from white-tailed deer in a mature woodland population in southeastern Ontario, Canada. The population was sampled in 2014 for seedling and sapling stages (≤6 cm in stem diameter) to obtain an age frequency distribution spanning about 80 y and including survivors of seed cohorts produced in two known mast years at the study site (2013 and 1984) and in other mast years known to have occurred within the broader region (but not confirmed for the study site). The age frequency distribution is roughly bimodal with zero to very few individuals recorded for ages 9 through 29 y, corresponding with the known time period (early 1980's to late 2000's) of regional overabundance for white-tailed deer in eastern Ontario and at the study site in particular. The 1 y old seedlings (from the 2013 mast year) and the survivors of putative mast year cohorts from 2006 and 2000, however, are especially conspicuous, with less striking recruitment success indicated for the older confirmed mast year cohort from 1984 (which had more years of accumulated impact from mortality risks). Our results suggest seed masting in sugar maple can bolster cohort recruitment success that otherwise would virtually (or completely) fail when severe impact from deer browsing is combined with other typical early life-stage mortality risks, e.g., from drought, neighborhood competition, and persistent overhead canopy shade.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.554

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.047
GPT teacher head0.334
Teacher spread0.287 · 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

Citations5
Published2017
Admission routes2
Has abstractyes

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