Darwin wasp fossil diversity and their fate during the K-Pg mass extinction
Notice bibliographique
Résumé
The objective of this thesis was to investigate the fossil species diversity of Darwin wasps, ranging from the Paleogene to the Cretaceous, with a particular emphasis on their morphology and taxonomic placement. On a broader scale, I aimed to create a morphological and molecular dataset including extant and fossil ichneumonids, to assess if they were impacted by the last catastrophic mass extinction event of the K-Pg and to create the first dated phylogeny of the family including all extant and fossil subfamilies. Here I provide a short general overview of my thesis, which includes six chapters, followed by a one-page summary for each chapter. Through extensive collaboration with curators from various palaeontological collections, I obtained and analyzed significant fossil material from seven fossil localities (Dominican amber, Calcaires de Campagne-Calavon Formation, Baltic amber, Fur Formation, Oise amber, Canadian amber, Taimyr amber). In this thesis, I described 7 new genera and 15 new fossil species (Chapters 1–5), of which many were described as the first finds of their respective subfamilies in amber. Notably, I described four fossil species of Phygadeuontinae, a subfamily that is among the most abundant today and the most frequently recorded in Baltic amber. However, prior to my work, no Phygadeuontinae fossil had been described from amber. I evaluated the morphology of the new fossil species to greatly enhance our understanding of the Darwin wasps' ancient diversity. By doing this I extensively expanded our morphological dataset and taxon sampling. In chapter 1, I described two specimens, and revised another one from Oise amber, which are especially valuable because they are well preserved and are from a fossil locality with an age of 53 million years, belonging to a time interval from which very few fossil insect species are described. In chapters 2 and 4, I evaluated the shape of the wing venation of sediment fossils using geometric morphometrics to determine subfamily-specific and tribe-specific characteristics. These characteristics were later implemented as new characters and character states in the morphological matrix. With the fore and hind wing shape data, I provide a dataset that can be used to increase the certainty of taxonomic placement in fossil specimens, as demonstrated in both chapters. In chapter 3, I used micro-CT scans of amber specimen, to increase the accessibility of morphological details, improving fossil placement in an undated combined morphological and molecular analysis. Those specimens are among the best-coded taxa in the final dataset, which I assume positively impacts the final analysis. In chapter 5, I evaluate taphonomic influences in Baltic amber specimens and discuss the evidence found in the amber, including the fossils' morphology, their state of preservation, and their body position, to hypothesize about the species' ecology and probable cause of death. In this chapter we used micro-CT scans again to improve the interpretation of morphology, aiding our understanding of taphonomic influences. The expansion of our morphological matrix resulted in 264 morphological characters. Including the newly described species, I morphologically coded 22 Cenozoic fossils, 17 Mesozoic fossils, and 117 extant taxa, covering all extant and fossil subfamilies, and combined this data with a previous matrix that has been compiled by Spasojevic et al. (2021). Using this data, combined with conserved genomic regions called Ultra-Conserved Elements (UCE), I conducted a total-evidence dating analysis under the FBD model in chapter 6. In this final chapter, we explored the challenges in estimating the impact of the Cretaceous-Paleogene (K-Pg) mass extinction event on Darwin wasps. Although we did not detect an impact on Darwin wasps and found that some estimated ages were too young, we explore the challenges of the model assumptions in detail and discuss potential improvements to the model setup to overcome these issues. Given that this is the first study using the FBD prior under TED in such a hyperdiverse and very sparsely sampled insect group, it is understandable that achieving precise results is a work in progress.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,006 | 0,000 |
| Communication savante | 0,003 | 0,006 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».