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Are correlations among foliar traits in ferns consistent with those in the seed plants?

2006· article· en· W1976126390 on OpenAlexafffund
Amanda L. Karst, Martin J. Lechowicz

Bibliographic record

VenueNew Phytologist · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFern and Epiphyte Biology
Canadian institutionsMcGill UniversityUniversity of Regina
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyFrondUnderstoryFernBotanySpecific leaf areaPhotosynthesisDeciduousTwigPhotosynthetic capacityCanopy

Abstract

fetched live from OpenAlex

Broad-based studies of gymnosperms and angiosperms reveal consistent and functionally significant correlations among foliar traits such as leaf mass per area (LMA), maximum photosynthetic rate (A(area)), foliar nitrogen (N(area)), foliar chlorophyll (Chl) and leaf longevity. To assess the generality of these relationships, we studied 20 fern species growing in the understorey of a temperate deciduous forest. We found that foliar N(area) increases with LMA, and that foliar N(area) and A(area) are positively correlated with one another, as are foliar N(area) and Chl. The ferns in general have very low LMA compared with most seed plants; A(area), N(area) and Chl are below median values for seed plants but are not extreme. Species with overwintering fronds have significantly higher LMA than species with fronds that senesce at the end of the growing season, as well as a significantly higher C : N ratio in frond tissue and relatively high foliar N on an areal basis. Correlations among foliar traits associated with gas exchange in these forest understorey ferns are in accordance with patterns reported for seed plants, suggesting a high degree of functional constraint on the interrelationships among key elements in foliar design.

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 score0.251
Threshold uncertainty score1.000

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 studies0.0000.000
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 head0.034
GPT teacher head0.231
Teacher spread0.198 · 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

Citations85
Published2006
Admission routes2
Has abstractyes

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