Dinosaur Palaeoecology in the Late Cretaceous of Alberta: Quantitative Assessments Using Vertebrate Microfossil Bonebeds and Stable Isotope Analyses
Bibliographic record
Abstract
The Belly River Group (BRG) of Alberta is one of the best-sampled Late Cretaceous terrestrial faunal assemblages in the world, providing a high-resolution biostratigraphic record of terrestrial vertebrate diversity, and has potential to be a model system for testing hypotheses of dinosaur palaeoecological dynamics. Vertebrate microfossil bonebeds (VMBs; assemblages of small bones and teeth concentrated together over a relatively short time and representative of community composition) offer an unparalleled dataset to better test these hypotheses by ameliorating problems of sample size, geography, and chronostratigraphic control that hamper many palaeoecological analyses. The first half of this thesis uses the largest VMB dataset yet assembled to test if trends in vertebrate diversity and community structure in the BRG are best explained as a response to environmental and sea-level change, and finds that while the vertebrate community as a whole was sensitive to these changes, the dinosaurs were not. This provides evidence against the long-held idea that dinosaur communities were sensitive to small-scale environmental gradients within a single depositional basin. The second half of this thesis tests hypotheses of dinosaur diet and niche partitioning using stable carbon and oxygen isotope analyses of species and guilds in a VMB assemblage. Results of these analyses refute the hypothesis that large diet-tissue fractionations explain enriched stable carbon values previously found in dinosaurs, as similarly enriched values are found in multiple sampled vertebrate groups, suggesting instead that they are related to changes in local isotopic baseline. These isotope data were then compared with a similar analytical sample from a modern analogue vertebrate community collected from Louisiana. Broad overlap exists in many of the species and guild distributions in both the extant and fossil systems, suggesting a lack of community-level saturation in resource use, less exclusionary control on niche occupation, and stronger selection for generalists rather than specialists. Overall, the results of this thesis suggest that greater care should be taken when making inferences into dinosaur community dynamics in the absence of thorough quantitative assessments and extant analogue data.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".