Bibliographic record
Abstract
Impact craters contain ecosystems that are often very different from the ecosystems that surround them. On Earth over 150 impact craters have been identified in a wide diversity of biomes. All natural events that can cause localized disruption of ecosystems have quite distinct patterns of rccovery. Impact events are unique in that they are the only extraterrestrial mechanism capable of disrupting an ecosystem locally in space and time. Thus, elucidating the chronological sequence of change at the sites of impacts is of ecological interest. In this synthetic review we use the existing literature, coupled with our own observations at the Haughton impact structure, Devon Island, Nunavut, Canada to consider the patterns of biological recovery at the site of impact craters and the ecological characteristics of impact craters. Three phases of recovery are suggested. The Phase of Thermal Biology, a phase associated with the localized, ephemeral thermal anomaly generated by an impact event. The Phase of Impact Succession and Climax, a phase marked by multiple primary and secondary succession events both in the aquatic realm (impact crater-lakes) and terrestrial realm (colonization of paleolacustrine deposits and impact-generated substrata) that are followed by periods of climax ecology. In the case of large-scale impact events (> 10(4) Mt), this latter phase may also be influenced by successional changes in the global environment. Finally, during the Phase of Ecological Assimilation, the disappearance of the surface geological expression of an impact structure results in a concomitant loss of ecological distinctiveness. In extreme cases, the impact structure is buried. Impact succession displays similarities and differences to succession following other agents of ecological disturbance, particularly volcanism.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".