Dietary innovations spurred the diversification of ruminants during the Caenozoic
Bibliographic record
Abstract
Global climate shifts and ecological flexibility are two major factors that may affect rates of speciation and extinction across clades. Here, we connect past climate to changes in diet and diversification dynamics of ruminant mammals. Using novel versions of Multi-State Speciation and Extinction models, we explore the most likely scenarios for evolutionary transitions among diets in this clade and ask whether ruminant lineages with different feeding styles (browsing, grazing and mixed feeding) underwent differential rates of diversification concomitant with global temperature change. The best model of trait change had transitions from browsers to grazers via mixed feeding, with appreciable rates of transition to and from grazing and mixed feeding. Diversification rates in mixed-feeder and grazer lineages tracked the palaeotemperature curve, exhibiting higher rates during the Miocene thermal maxima. The origination of facultative mixed diet and grazing states may have triggered two adaptive radiations--one during the Oligocene-Miocene transition and the other during Middle-to-Late Miocene. Our estimate of mixed diets for basal lineages of both bovids and cervids is congruent with fossil evidence, while the reconstruction of browser ancestors for some impoverished clades--Giraffidae and Tragulidae--is not. Our results offer model-based neontological support to previous palaeontological findings and fossil-based hypothesis highlighting the importance of dietary innovations--especially mixed feeding--in the success of ruminants during the Neogene.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".