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Record W4403091768 · doi:10.1126/science.adn7179

The coevolution of fungus-ant agriculture

2024· article· en· W4403091768 on OpenAlexaff
Ted R. Schultz, Jeffrey Sosa‐Calvo, Matthew Kweskin, Michael W. Lloyd, Bryn T. M. Dentinger, Pepijn W. Kooij, Else C. Vellinga, Stephen A. Rehner, André Rodrigues, Quimi Vidaurre Montoya, Hermógenes Fernández‐Marín, Ana Ješovnik, Tuula Niskanen, Kare Liimatainen, Caio A. Leal-Dutra, Scott E. Solomon, Nicole M. Gerardo, Cameron R. Currie, Maurício Bacci, Heraldo L. Vasconcelos, Christian Rabeling, Brant C. Faircloth, Vinson P. Doyle

Bibliographic record

VenueScience · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCoevolutionBiologyFungusDomesticationPopulationEcologyAgricultureHabitatBotany

Abstract

fetched live from OpenAlex

Fungus-farming ants cultivate multiple lineages of fungi for food, but, because fungal cultivar relationships are largely unresolved, the history of fungus-ant coevolution remains poorly known. We designed probes targeting >2000 gene regions to generate a dated evolutionary tree for 475 fungi and combined it with a similarly generated tree for 276 ants. We found that fungus-ant agriculture originated ~66 million years ago when the end-of-Cretaceous asteroid impact temporarily interrupted photosynthesis, causing global mass extinctions but favoring the proliferation of fungi. Subsequently, ~27 million years ago, one ancestral fungal cultivar population became domesticated, i.e., obligately mutualistic, when seasonally dry habitats expanded in South America, likely isolating the cultivar population from its free-living, wet forest-dwelling conspecifics. By revealing these and other major transitions in fungus-ant coevolution, our results clarify the historical processes that shaped a model system for nonhuman agriculture.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.005
GPT teacher head0.252
Teacher spread0.247 · 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

Citations37
Published2024
Admission routes1
Has abstractyes

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