Trait-based paleontological niche prediction recovers extinct ecological breadth of the earliest specialized ant predators - INSU - Institut national des sciences de l'Univers Accéder directement au contenu
Article Dans Une Revue The American Naturalist Année : 2023

Trait-based paleontological niche prediction recovers extinct ecological breadth of the earliest specialized ant predators

Résumé

Paleoecological estimation is fundamental to the reconstruction of evolutionary and environmental histories. The ant fossil record preserves a range of species in three-dimensional fidelity and chronicles faunal turnover across the Cretaceous and Cenozoic; taxonomically rich and ecologically diverse, ants are an exemplar system to test new methods of paleoecological estimation in evaluating hypotheses. We apply a broad extant ecomorphological dataset to evaluate Random Forest machine learning classification in predicting the total ecological breadth of extinct and enigmatic "hell ants". In contrast to previous hypotheses of extinctionprone arboreality, we find hell ants were primarily leaf litter or ground-nesting and foraging predators, and by comparing ecospace occupations of hell ants and their extant analogues, we recover a signature of ecomorphological turnover across temporally and phylogenetically distinct lineages on opposing sides of the KPg boundary. This paleoecological predictive framework is applicable across lineages and may provide new avenues for testing hypotheses over deep time.

Domaines

Paléontologie
Fichier principal
Vignette du fichier
soziak-2023.pdf (10.8 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

insu-04167916 , version 1 (21-07-2023)

Identifiants

Citer

Christine Sosiak, Tyler Janovitz, Vincent Perrichot, John Paul Timonera, Phillip Barden. Trait-based paleontological niche prediction recovers extinct ecological breadth of the earliest specialized ant predators. The American Naturalist, 2023, 202 (6), pp.737-855. ⟨10.1086/726739⟩. ⟨insu-04167916⟩
27 Consultations
87 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More