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Record W2021073050 · doi:10.1139/x05-024

Seedling recruitment in a northern temperate forest: the relative importance of supply and establishment limitation

2005· article· en· W2021073050 on OpenAlexfundvenueaboutno aff
John P. Caspersen, Megan Saprunoff

Bibliographic record

VenueCanadian Journal of Forest Research · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAbies balsameaSeedlingBiologyTsugaTemperate forestEcologyTemperate rainforestBalsamTemperate climateSeed dispersalBiological dispersalBotanyPopulation

Abstract

fetched live from OpenAlex

We quantified supply and establishment limitation as components of seedling recruitment for five species common to the temperate forests of central Ontario. Establishment limitation was the primary cause of recruitment failure for the three most common species: Acer saccharum Marsh., Betula alleghaniensis Britt., and Tsuga canadensis (L.) Carrière. The main barrier to establishment (including germination and seedling emergence) was a lack of suitable substrates, rather than a lack of light. Supply limitation, on the other hand, was the primary cause of recruitment failure for two less common species, Abies balsamea (L.) Mill. and Fagus grandifolia Ehrh. The cause of supply limitation was a lack of parent trees, in the case of A. balsamea, and low fecundity, in the case of F. grandifolia. Our results suggest that niche differences (i.e., germination requirements) are more important than dispersal in structuring temperate forest communities. Our results also suggest that availability of suitable substrates is the primary factor limiting seedling recruitment following logging.

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)0.002
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 score0.945
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0000.000

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 head0.054
GPT teacher head0.311
Teacher spread0.257 · 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

Citations121
Published2005
Admission routes3
Has abstractyes

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