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Enregistrement W2033804168 · doi:10.1080/10635150290102528

Using Tree Shape

2002· review· en· W2033804168 sur OpenAlexaff
Arne Ø. Mooers, Stephen B. Heard

Notice bibliographique

RevueSystematic Biology · 2002
Typereview
Langueen
DomaineEarth and Planetary Sciences
ThématiqueEvolution and Paleontology Studies
Établissements canadiensUniversity of New BrunswickSimon Fraser University
Organismes subventionnairesnon disponible
Mots-clésPhylogenetic treeTaxonTree (set theory)CladeBiologyEvolutionary biologyDiversification (marketing strategy)Tree of life (biology)Variation (astronomy)GenealogyPhylogeneticsEcologyHistoryMathematicsCombinatorics

Résumé

récupéré en direct d'OpenAlex

Although the primary purpose of phylogenies is to depict evolutionary relationships among taxa, they have other interesting properties. One of the most interesting is their shape, some quantifiable measure of how they look. Such measures come in two general flavors: diversity variation among contemporaneous clades (e.g., when averaged over the whole tree, this is tree balance) and distribution of splitting times (e.g., lineages-through-time plots). These measures represent variation in diversification rates among taxa at a given time and within a taxon through time, respectively. As such, tree shape is the signature of the forces that produce biodiversity, and its study informs one of the major areas in evolutionary biology. It has been over a decade since Craig Guyer and Joseph Slowinski (Slowinski and Guyer, 1989; Guyer and Slowinski, 1991, 1993) began the current era of tree shape work (for a history and general review, see Mooers and Heard, 1997). The concept was elegant: compare shapes of published trees with expectations from reasonable null models, deal with uninteresting technical confounds, and interpret what remains with an eye to explaining past and (perhaps) predicting future biodiversification (though we might not have called it that a decade ago). A decade on, it is well established that trees shapes contain interesting and important information about the evolutionary process (see, e.g., Gaston and Spicer, 1998; Schluter, 2000; Felsenstein, in press). For the 2001 joint SSB/SSE/ASN meeting, we were fortunate to be able to organize a symposium titled Developing uses for phylogenetic tree shape in the study of evolution, an opportunity to organize the decade's work and foster collaboration for the future. Collected here are papers representing many of the contributing authors and others who presented related material in other sessions of that 2001 meeting. We gratefully acknowledge the support of the Society of Systematic Biologists, which both sponsored the symposium and agreed to review these papers for publication. These papers are an excellent, if incomplete, update on the decade's work on tree shape. As expected, the descriptive aspect has become more sophisticated, with new software tools and ever better statistical power (contributions in this issue by Agapow and Purvis, and Chan and Moore; see also McKenzie and Steel, 2000; Stam, 2002). We are getting better at incorporating and analyzing branch length information (the latest update and extension is by Pybus et al., this issue). There are also some new observations: perhaps the most intriguing is the idea that species-level and higher level phylogenies might actually differ in shape (Purvis and Agapow, this issue). Along with these changes is a welcome expansion into new fields. Two sampled here are comparative methods (a potentially powerful way to summarize tree shapes is presented by Martins and Housworth, this issue) and community structure (Webb and Pitman, this issue). An important distinction between neontological and paleontological phylogenies has been recognized, and tools for dealing with the latter have been developed (Harcourt-Brown, this issue). Finally, Alan de Queiroz submits a provocative essay on the complexity of the question of why some taxonomic groups might diversify more than others. But we have still just begun. The patterns are certainly real and are becoming better documented (Purvis and Agapow, and Savolainen et al., this issue; Stam, 2002), and the evolutionary models are inching towards increased realism (Heard and Mooers, this issue). However, present explanations for nonrandom tree shapes are incomplete, and the application of tree-shape concepts in related disciplines is still in its infancy (see, e.g., Heard and Mooers, 2000; von Euler, 2001). We expect to see major advances made with

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,673
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,002

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,252
Tête enseignante GPT0,355
Écart entre enseignants0,103 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeRevue systématique
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations19
Publié2002
Routes d'admission1
Résumé présentoui

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