Top of the food chains: an ecological network of the marine Paja Formation biota from the Early Cretaceous of Colombia reveals the highest trophic levels ever estimated
Bibliographic record
Abstract
Abstract The Mesozoic Marine Revolution restructured the world’s ocean biodiversity into the complex marine ecosystems of today. This revolution began during the Triassic but the origin of this complexity is poorly understood due to a lack of detailed ecosystem reconstructions throughout time. We present the first site-specific ecological network for a marine Mesozoic fauna based on the Early Cretaceous Paja Formation biota of Colombia that preserves numerous, large-bodied, predatory marine reptiles. The trophic food-web was quantitatively reconstructed based on inferred trophic interactions of marine producers, consumers, and large apex predators. Compared to well-studied Caribbean reef ecosystem networks, the Paja biota network is missing a great proportion of benthic invertebrates and fishes, despite its rich higher trophic levels. We hypothesize that the ammonites from the Paja biota either mirrored the diversity represented by some fishes today or established a novel trophic unit with no living analogue. Recalibrating the Paja biota network to trophic analogues in the Caribbean, such as sea turtles, estimates that the largest Paja marine reptile hyper-apex predators occupied trophic levels a full tier higher than any extant marine apex predator. The Paja biota network is a starting point to tracing the evolution of marine ecosystems across the Mesozoic Marine Revolution.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".