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Record W2093091744 · doi:10.1086/677296

Metabolism and the Rise of Fungus Cultivation by Ants

2014· article· en· W2093091744 on OpenAlexafffund
Jonathan Z. Shik, Juan C. Santos, Jon N. Seal, Adam D. Kay, Ulrich G. Mueller, Michael Kaspari

Bibliographic record

VenueThe American Naturalist · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsUniversity of British Columbia
FundersUniversity of British ColumbiaNational Evolutionary Synthesis CenterNational Science Foundation
KeywordsBiologyFungusAnt colonyEcologyContext (archaeology)HymenopteraBotanyAnt colony optimization algorithms

Abstract

fetched live from OpenAlex

Most ant colonies are comprised of workers that cooperate to harvest resources and feed developing larvae. Around 50 million years ago (MYA), ants of the attine lineage adopted an alternative strategy, harvesting resources used as compost to produce fungal gardens. While fungus cultivation is considered a major breakthrough in ant evolution, the associated ecological consequences remain poorly understood. Here, we compare the energetics of attine colony-farms and ancestral hunter-gatherer colonies using metabolic scaling principles within a phylogenetic context. We find two major energetic transitions. First, the earliest lower-attine farmers transitioned to lower mass-specific metabolic rates while shifting significant fractions of biomass from ant tissue to fungus gardens. Second, a transition 20 MYA to specialized cultivars in the higher-attine clade was associated with increased colony metabolism (without changes in garden fungal content) and with metabolic scaling nearly identical to hypometry observed in hunter-gatherer ants, although only the hunter-gatherer slope was distinguishable from isometry. Based on these evolutionary transitions, we propose that shifting living-tissue storage from ants to fungal mutualists provided energetic storage advantages contributing to attine diversification and outline critical assumptions that, when tested, will help link metabolism, farming efficiency, and colony fitness.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.241
Threshold uncertainty score0.293

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 studies0.0000.001
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 head0.004
GPT teacher head0.236
Teacher spread0.233 · 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 designBench or experimental
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

Citations34
Published2014
Admission routes2
Has abstractyes

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