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Phylogenetic ecology of leaf surface traits in the milkweeds (<i>Asclepias</i> spp.): chemistry, ecophysiology, and insect behavior

2009· article· en· W2137886260 on OpenAlexafffund
Anurag A. Agrawal, Mark Fishbein, Reinhard Jetter, Juha‐Pekka Salminen, Jessica B. Goldstein, Amy Freitag, Jed P. Sparks

Bibliographic record

VenueNew Phytologist · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Foundation
KeywordsTrichomeBiologyBotanyAbiotic componentPhotosynthesisEcology

Abstract

fetched live from OpenAlex

The leaf surface is the contact point between plants and the environment and plays a crucial role in mediating biotic and abiotic interactions. Here, we took a phylogenetic approach to investigate the function, trade-offs, and evolution of leaf surface traits in the milkweeds (Asclepias). Across 47 species, we found trichome densities of up to 3000 trichomes cm(-2) and epicuticular wax crystals (glaucousness) on 10 species. Glaucous species had a characteristic wax composition dominated by very-long-chain aldehydes. The ancestor of the milkweeds was probably a glaucous species, from which there have been several independent origins of glabrous and pubescent types. Trichomes and wax crystals showed negatively correlated evolution, with both surface types showing an affinity for arid habitats. Pubescent and glaucous milkweeds had a higher maximum photosynthetic rate and lower stomatal density than glabrous species. Pubescent and glaucous leaf surfaces impeded settling behavior of monarch caterpillars and aphids compared with glabrous species, although surface types did not show consistent differentiation in secondary chemistry. We hypothesize that pubescence and glaucousness have evolved as alternative mechanisms with similar functions. The glaucous type, however, appears to be ancestral, lost repeatedly, and never regained; we propose that trichomes are a more evolutionarily titratable strategy.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.908
Threshold uncertainty score0.218

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 head0.042
GPT teacher head0.230
Teacher spread0.189 · 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

Citations149
Published2009
Admission routes2
Has abstractyes

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