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Record W2154153710 · doi:10.1073/pnas.0701135104

“Diminishing returns” in the scaling of functional leaf traits across and within species groups

2007· article· en· W2154153710 on OpenAlexaff
Karl J. Niklas, Edward D. Cobb, Ülo Niinemets, Peter B. Reich, Arne Sellin, Bill Shipley, Ian J. Wright

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversité de Sherbrooke
FundersNational Science Foundation
KeywordsScalingAllometryBiologyForbDry weightPlant speciesPaceTaxonEcologySpecific leaf areaBotanyMathematicsGeographyGrassland

Abstract

fetched live from OpenAlex

More than 5,000 measurements from 1,943 plant species were used to explore the scaling relationships among the foliar surface area and the dry, water, and nitrogen/phosphorus mass of mature individual leaves. Although they differed statistically, the exponents for the relationships among these variables were numerically similar among six species groups (ferns, graminoids, forbs, shrubs, trees, and vines) and within 19 individual species. In general, at least one among the many scaling exponents was <1.0, such that increases in one or more features influencing foliar function (e.g., surface area or living leaf mass) failed to keep pace with increases in mature leaf size. Thus, a general set of scaling relationships exists that negatively affects increases in leaf size. We argue that this set reflects a fundamental property of all plants and helps to explain why annual growth fails to keep pace with increases in total body mass across species.

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)0.003
metaresearch head score (Gemma)0.023
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 score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.042
GPT teacher head0.293
Teacher spread0.251 · 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

Citations244
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicEcology and Vegetation Dynamics StudiesFrench-language works237,207