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Record W4407617728 · doi:10.1111/oik.10757

Host specificity of herbivorous insects promotes negative species–genetic diversity relationship

2025· article· en· W4407617728 on OpenAlexaff
Qian‐Ya Li, Linyi Zhang, Xinghua Hu, Rong Wang, Xiaoyong Chen

Bibliographic record

VenueOikos · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHerbivoreBiologyHost (biology)EcologyHost specificityGenetic diversityDiversity (politics)Evolutionary biologyZoologyPopulation

Abstract

fetched live from OpenAlex

Although genetic diversity and species diversity in a community often covary, the direction and strength of the covariation vary. However, this variation in the relationship of these two diversities is poorly understood. Here we investigated the role of host‐specific herbivores in generating species–genetic diversity relationship in plant communities. We quantified host specificity for Fagaceae plants–acorn weevil bipartite networks in a subtropical forest and modeled the effect of weevil herbivory on the relationship. The results showed a consistently negative relationship between Fagaceae species diversity and the genetic diversity of the dominant species, Lithocarpus glaber . Our analysis showed this negative relationship arose from a positive effect of weevil host‐specificity on Fagaceae plant richness on the one hand and the negative effect of weevil host‐specificity on the genetic diversity of L. glaber on the other hand. This latter negative effect was possibly due to differentiated selection of weevils on different genotypes of L. glaber . Our study highlights the importance of considering trophic interactions and herbivore host‐specificity in explaining the species–genetic diversity relationship.

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 score0.058
Threshold uncertainty score0.269

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 head0.060
GPT teacher head0.210
Teacher spread0.150 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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