Amoebozoan testate amoebae illuminate the diversity of heterotrophs and the complexity of ecosystems throughout geological time
Bibliographic record
Abstract
Heterotrophic microbial eukaryotes play a pivotal role in aquatic and terrestrial ecosystems, contributing to carbon and nutrient cycles. These microorganisms, capable of phagocytosis, act as predators of bacterial communities and other microeukaryotes, occupying a significant position in complex food webs. The timing of the origin and diversification of heterotrophic microeukaryotes remain unclear. Fossil evidence and molecular data suggest that the emergence of predatory microeukaryotes and the transition to a eukaryote-dominant marine environment occurred around 800 million years ago (mya). Vase-shaped microfossils (VSMs), the fossil record linked to Arcellinida testate amoebae, represent the oldest known evidence of heterotrophic microeukaryotes in marine environments and terrestrial habitats. In this study, we investigate the early divergence and diversification of Arcellinida and related amoebozoan taxa using a relaxed molecular clock approach. Phylogenomic reconstructions reveal a well-resolved tree of amoebozoan testate amoebae, including a monophyletic Arcellinida with three suborders and five infraorders. Through calibration using fossils and rigorous clock models, we estimate the timing of diversification of Arcellinida during the early Neoproterozoic (886 - 764 mya), shedding light on the expansion of life during this period. Our results suggest an established biological complexity in shallow marine ecosystems, involving both phototrophic and heterotrophic microeukaryotes during the Neoproterozoic, followed by an invasion of freshwater systems potentially during Cryogenian and subsequent diversification of Arcellinida in the Phanerozoic. Overall, these findings provide valuable insights into heterotrophic microeukaryotes' evolutionary history and ecological significance in Earth's ecosystems.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".