Palaeomacroecology: large scale patterns in species diversity through the fossil record
Notice bibliographique
Résumé
Palaeomacroecology is the study of large scale patterns of species diversity in the fossil record, encompassing a variety of subtopics. This thesis also addresses a variety of these subtopics, making it difficult to define under one heading.The first portion of the thesis deals with a new package of software tools for the analysis of large scale datasets, with a specific focus towards palaeoecology and palaeogeography. These software tools have been combined into a package called fossil that has been released on the Comprehensive R Archive Network (CRAN), and is already being used by other palaeoecologists. While the majority of these tools had a basis in previous statistical methods, I have also independently developed a clustering algorithm for use with biogeographic datasets. This clustering algorithm is relational, non-Euclidean and non-hierarchical and as such is called Non-Euclidean Relational Clustering (NERC). NERC eliminates several of the assumptions common to most other clustering methods that are often violated by biogeographic data.The next portion of my thesis describes a new Triassic aged flora from Axel Heiberg Island in Nunavut. Macroecological studies typically use large databases compiled from individual samples; therefore, these individual samples represent the foundation on which macroecological analyses rest, and collection and description of new fossil bearing sites is vital to the advancement of palaeomacroecology.Chapter 5 is an analysis of the provinciality and beta diversity of dinosaurs in the Late Cretaceous of North America. This analysis found that contrary to previous studies, dinosaur genera were widespread across the continent and not restricted to small geographic ranges. Chapter 6 is the final culmination of my thesis, and where I see palaeomacroecology headed in the future. It is an analysis of how latitudinal diversity gradients in plants have changed through time. The analysis assesses the impact of changing climate in creating and sustaining the latitudinal diversity gradient, and lends support to the idea that temperatures are important drivers of the gradient.The final chapter is a summary of where palaeomacroecology has been, and where its future work might be best focused. While the field of palaeontology is vital to our understanding of large scale, especially temporally, patterns of species diversity, the field of palaeontology has an opportunity to advance our understanding at an even more rapid pace provided we ask the appropriate questions of our data.
Conservé avec la notice de tri, où il sert de preuve aux étiquettes ci-dessus.
Comment cette classification a été obtenuedéplier
Le tri à trois modèles
les 5 600 travaux triés →Les trois modèles l'ont jugé hors champ.
Palaeoecology thesis on diversity patterns in the fossil record; includes an R package and a clustering algorithm, but these are domain analysis tools and the object is species diversity.
This thesis develops tools and analyzes fossil biodiversity while studying paleontology, not research itself.
Paleontology thesis on large-scale fossil diversity patterns; domain science, not metaresearch.
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,002 |
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.
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 source (Gemma direct ou Codex distillé), 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 ».