The Importance of Size and Location Within Gregarious Populations of Ernietta plateauensis
Bibliographic record
Abstract
Ernietta plateauensis is a semi-infaunal macroscopic eukaryote of unknown affinities common in latest Ediacaran (∼548–539 Ma) shallow marine settings in Namibia. The discovery of in-situ assemblages of Ernietta has demonstrated that these organisms lived in aggregated populations, while studies employing computational fluid dynamics (CFD) modeling have supported the hypothesis that these organisms were likely behaving as gregarious suspension feeders, analogous to many extant invertebrate phyla in present-day marine environments. Careful census and measurement of individuals within these in-situ populations offers an opportunity to examine how their size and location within a larger population affect nutrient delivery dynamics. In this study, we build on previous work by simulating fluid flow over aggregations of Ernietta comprising individuals of disparate sizes, and additionally reconstruct a population of Ernietta preserved in-situ from Farm Hansburg, Namibia. We use a combination of stationary and time-dependent CFD to reconstruct nutrient carrying flow paths, and compare the efficiency with which nutrients are partitioned between individuals of different shapes and sizes. Our results demonstrate that smaller Ernietta experience limited recirculation within their cavities compared to larger individuals. Furthermore, in spatially-accurate distributions, reduced recirculation is limited to isolated individuals of any size, while smaller individuals found downstream of larger ones receive enhanced cavity mixing. These reconstructed flow patterns illustrate that the disadvantage associated with small size is apparently mediated by location within the overall aggregation, suggesting a complex interplay of controls on feeding efficiency. This in turn suggests that aggregations of adult Ernietta would likely have performed a ‘nursery’ function, creating localized conditions ideal for the settlement and growth of younger individuals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".