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Record W4414330425 · doi:10.3389/fevo.2025.1647436

Caterpillar diet breadth in Área de Conservación Guanacaste, a large and diverse Neotropical wildland in northwestern Costa Rica: toxins, silica, aluminum, and sclerophylly

2025· article· en· W4414330425 on OpenAlexaff
Donаld L. J. Quicke, Allison Brown, Mehrdad Hajibabaei, Ramya Manjunath, Suresh Naik, Sujeevan Ratnasingham, Jayme E Sones, Brianne St. Jacques, M. Alex Smith, Nelson Zamora, John W. Brown, Tanner A. Matson, Scott E. Miller, John M. Burns, Paul Z. Goldstein, Mark A. Metz, Robert K. Robbins, M. Alma Solís, Isidro Chacón, Bernardo Espinoza, Annia Picado, Eugenie Phillips-Rodríguez, Paul D. N. Hebert, Daniel H. Janzen, Winnie Hallwachs, Buntikа А. Butcher

Bibliographic record

VenueFrontiers in Ecology and Evolution · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCaterpillarGeneralist and specialist speciesFaunaLepidoptera genitaliaSpecies richnessBiotaPlant communityBiodiversityFood plant

Abstract

fetched live from OpenAlex

Caterpillar–food plant records collected over approximately 38 years in the Area de Conservación Guanacaste (ACG) in northwestern Costa Rica are described and summarized. The data comprise 431,212 individual rearing records, 197,366 of which represent unique plant–herbivore associations, i.e., same species pair found on separate dates and at different plants of the same species. These represent 29,187 different caterpillar–food plant associations between 2,489 plant and 7,160 Lepidoptera species. We evaluate changes in the taxonomic composition of the food plant flora and Lepidoptera fauna between 1990 and 2020 and across habitat/community types. Food plant and caterpillar community species richness in the rain forest changed considerably over the first 10 years but remained more stable since. Dry forest communities were more consistent than in rain forest. The cloud forest biota was the most consistent between 1995 and 2010, but as in dry forest, the caterpillar fauna changed considerably during 2015–2020. Plant species composition was more constant than caterpillar composition. The taxonomic distributions of diet specialists and generalists are explored. Most of the species-rich Lepidoptera families contain many specialists, variously concentrated throughout each family, though highly polyphagous collectively. The exceptions include Sphingidae, which show preference for Rubiaceae, Hesperiinae for monocotyledons, and non-Hesperiinae skippers for Fabaceae. Among plant families for which there are over 1,000 independent rearings, Acanthaceae, Apocynaceae, Arecaceae, Costaceae, Melastomataceae, Moraceae, Piperaceae, Poaceae, Rubiaceae, Rutaceae, and Solanaceae hosted the greatest proportion of specialists. However, the level at which dietary specialization corresponds to taxonomic rank varies with both caterpillar and plant taxon. Most fern-feeders are polyphagous with respect to fern families but still specialists on Polypodiopsida. A selection of plant families with conspicuous allelochemical and/or structural defenses and a selection of caterpillars and caterpillar families with equally conspicuous counter-defenses were examined. We determined that (1) unpalatable, aposematic herbivores tend to be specialists and (2) families of plants predominantly consumed by highly defended caterpillars host fewer polyphagous herbivores than families with less conspicuously defended plants. Highly toxic plant families with the fewest rearings, such as Aristolochiaceae and Zamiaceae, hosted many monophagous caterpillars. Biochemical and structural plant defenses appear to mediate herbivore diet breadth for many plant families.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.128
Threshold uncertainty score0.255

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.193
Teacher spread0.184 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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