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Record W2024643470 · doi:10.1098/rspb.2014.0555

Macroecological and macroevolutionary patterns of leaf herbivory across vascular plants

2014· article· en· W2024643470 on OpenAlexaff
Martin M. Turcotte, T. Jonathan Davies, Christina J. M. Thomsen, Marc T. J. Johnson

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of OttawaMcGill UniversityUniversity of Toronto
Fundersnot available
KeywordsHerbivorePlant tolerance to herbivoryCoevolutionBiologyEcologyEcosystemWoody plantArthropodPlant evolution

Abstract

fetched live from OpenAlex

The consumption of plants by animals underlies important evolutionary and ecological processes in nature. Arthropod herbivory evolved approximately 415 Ma and the ensuing coevolution between plants and herbivores is credited with generating much of the macroscopic diversity on the Earth. In contemporary ecosystems, herbivory provides the major conduit of energy from primary producers to consumers. Here, we show that when averaged across all major lineages of vascular plants, herbivores consume 5.3% of the leaf tissue produced annually by plants, whereas previous estimates are up to 3.8× higher. This result suggests that for many plant species, leaf herbivory may play a smaller role in energy and nutrient flow than currently thought. Comparative analyses of a diverse global sample of 1058 species across 2085 populations reveal that models of stabilizing selection best describe rates of leaf consumption, and that rates vary substantially within and among major plant lineages. A key determinant of this variation is plant growth form, where woody plant species experience 64% higher leaf herbivory than non-woody plants. Higher leaf herbivory in woody species supports a key prediction of the plant apparency theory. Our study provides insight into how a long history of coevolution has shaped the ecological and evolutionary relationships between plants and herbivores.

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)0.001
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 score0.089
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.030
GPT teacher head0.218
Teacher spread0.188 · 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

Citations145
Published2014
Admission routes1
Has abstractyes

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