MétaCan
Menu
Back to cohort
Record W3149518527 · doi:10.1093/biolinnean/blab010

Extraordinary diversification of the “bristle flies” (Diptera: Tachinidae) and its underlying causes

2021· article· en· W3149518527 on OpenAlexaff
John O. Stireman, Pierfilippo Cerretti, James E. O’Hara, John K. Moulton

Bibliographic record

VenueBiological Journal of the Linnean Society · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHymenoptera taxonomy and phylogeny
Canadian institutionsAgriculture and Agri-Food Canada
FundersNational Science Foundation
KeywordsBiologyTachinidaeDiversification (marketing strategy)Adaptive radiationTaxonEvolutionary biologyEcologyPhylogeneticsCladeZoologyParasitoidLarvaGenetics

Abstract

fetched live from OpenAlex

Abstract The family Tachinidae (“bristle flies”) is the most diverse and ecologically important group of insect parasitoids outside the parasitic wasps. It is among the most species rich families of flies (Diptera) and has experienced a recent adaptive radiation across the globe. We make use of a molecular phylogeny of the family to examine its rapid radiation and explore the traits of tachinid lineages that may have contributed to variation in their diversification. We apply a range of diversification analyses to assess the consistency and robustness of effects. We find that the Tachinidae are among the most rapidly diversifying families of animals. Six to eight clades of bristle flies, distributed across the phylogeny, exhibit strong evidence of accelerated diversification. Our results suggest that the use of holometabolous insect larvae, and specifically caterpillars (Lepidoptera), as hosts, is associated with increased diversification rates. However, these effects were inconsistent across analyses. We detected little influence of oviposition strategy (egg type) or host feeding habit, and we recovered evidence that unmeasured “hidden” traits may explain greater variance in diversification. We evaluated the strengths and weaknesses of different Maximum Likelihood and Bayesian approaches for analysing diversification and the potential for extrinsic factors, such as geography, to influence patterns of richness and diversification. In general, we conclude that although certain traits may provide opportunities for diversification, whether this is capitalized on may depend on additional traits and/or historical contingency.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.811
Threshold uncertainty score0.252

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 head0.087
GPT teacher head0.247
Teacher spread0.160 · 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

Citations15
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueBiological Journal of the Linnean SocietySame topicHymenoptera taxonomy and phylogenyFrench-language works237,207