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Record W3036901022 · doi:10.7717/peerj.9249

Behavioral, morphological, and ecological trait evolution in two clades of New World Sparrows ( <i>Aimophila</i> and <i>Peucaea</i> , Passerellidae)

2020· article· en· W3036901022 on OpenAlexaff
Carla Cicero, Nicholas A. Mason, Lauryn Benedict, James D. Rising

Bibliographic record

VenuePeerJ · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiologyPlumageCladeTraitEcologyPhylogenetic treeHabitatPhylogenetic comparative methodsPhylogeneticsEvolutionary biologyZoology

Abstract

fetched live from OpenAlex

The New World sparrows (Passerellidae) are a large, diverse group of songbirds that vary in morphology, behavior, and ecology. Thus, they are excellent for studying trait evolution in a phylogenetic framework. We examined lability versus conservatism in morphological and behavioral traits in two related clades of sparrows ( Aimophila, Peucaea ), and assessed whether habitat has played an important role in trait evolution. We first inferred a multi-locus phylogeny which we used to reconstruct ancestral states, and then quantified phylogenetic signal among morphological and behavioral traits in these clades and in New World sparrows more broadly. Behavioral traits have a stronger phylogenetic signal than morphological traits. Specifically, vocal duets and song structure are the most highly conserved traits, and nesting behavior appears to be maintained within clades. Furthermore, we found a strong correlation between open habitat and unpatterned plumage, complex song, and ground nesting. However, even within lineages that share the same habitat type, species vary in nesting, plumage pattern, song complexity, and duetting. Our findings highlight trade-offs between behavior, morphology, and ecology in sparrow diversification.

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 score0.805
Threshold uncertainty score0.458

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 head0.055
GPT teacher head0.322
Teacher spread0.267 · 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

Citations21
Published2020
Admission routes1
Has abstractyes

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