Ediacaran marine animal forests and the ventilation of the oceans
Bibliographic record
Abstract
The rise of animals across the Ediacaran–Cambrian transition marked a step-change in the history of life, from a microbially dominated world to the complex macroscopic biosphere we see today. 1 , 2 , 3 While the importance of bioturbation and swimming in altering the structure and function of Earth systems is well established, 4 , 5 , 6 the influence of epifaunal animals on the hydrodynamics of marine environments is not well understood. Of particular interest are the oldest "marine animal forests," 7 which comprise a diversity of sessile soft-bodied organisms dominated by the fractally branching rangeomorphs. 8 , 9 Typified by fossil assemblages from the Ediacaran of Mistaken Point, Newfoundland, 8 , 10 , 11 these ancient communities might have played a pivotal role in structuring marine environments, similar to modern ecosystems, 7 , 12 , 13 but our understanding of how they impacted fluid flow in the water column is limited. Here, we use ecological modeling and computational flow simulations to explore how Ediacaran marine animal forests influenced their surrounding environment. Our results reveal how organism morphology and community structure and composition combined to impact vertical mixing of the surrounding water. We find that Mistaken Point communities were capable of generating high-mixing conditions, thereby likely promoting gas and nutrient transport within the "canopy." This mixing could have served to enhance local-scale oxygen concentrations and redistribute resources like dissolved organic carbon. Our work suggests that Ediacaran marine animal forests may have contributed to the ventilation of the oceans over 560 million years ago, well before the Cambrian explosion of animals.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".