Prospects for studying continentalization and the origin of terrestrial ecosystems during the late Paleozoic
Bibliographic record
Abstract
The origin of terrestrial ecosystems during the Paleozoic is pivotal in the history of life on Earth. This is a fascinating case for testing hypotheses about how ecological novelty arises at the organismal, lineage, and community levels. In this paper, I review research on community assembly and change in deep time and discuss this work in the context of investigating the continentalization of ecosystems. The extensive study of large-scale Phanerozoic trends in taxonomic and autecological diversity, particularly in the marine realm, provides an important theoretical framework. However, the interactions between these trends and community-level properties such as stability and the species carrying capacity are not as well understood. The growing body of paleo-food web literature has returned ambiguous results, and it is not clear whether the bounds of community performance have shifted over time or not. Importantly, these studies are conducted either entirely in the marine realm or in the terrestrial realm, but not yet on communities representing the initial expansion of life into non-marine and, eventually, terrestrial habitats. Modern-day systems such as island colonization might provide some useful insights into continentalization in deep time, but are effectively instances of terrestrial ecosystems being reproduced using extant terrestrial taxa, not terrestrial ecosystems developing de novo. The timeline of Paleozoic continentalization as currently understood is reviewed. Although the process was already underway, the Late Paleozoic (Devonian–Permian) emerged as a key interval for the study of continentalization. Food web modeling methods and hypotheses are discussed. Although challenging, going forward, this area of research has great potential to address questions of relevance to paleontologists, neontologists, and ecologists alike.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".