Graptolite community responses to global climate change and the Late Ordovician mass extinction
Bibliographic record
Abstract
Mass extinctions disrupt ecological communities. Although climate changes produce stress in ecological communities, few paleobiological studies have systematically addressed the impact of global climate changes on the fine details of community structure with a view to understanding how changes in community structure presage, or even cause, biodiversity decline during mass extinctions. Based on a novel Bayesian approach to biotope assessment, we present a study of changes in species abundance distribution patterns of macroplanktonic graptolite faunas (∼447-444 Ma) leading into the Late Ordovician mass extinction. Communities at two contrasting sites exhibit significant decreases in complexity and evenness as a consequence of the preferential decline in abundance of dysaerobic zone specialist species. The observed changes in community complexity and evenness commenced well before the dramatic population depletions that mark the tipping point of the extinction event. Initially, community changes tracked changes in the oceanic water masses, but these relations broke down during the onset of mass extinction. Environmental isotope and biomarker data suggest that sea surface temperature and nutrient cycling in the paleotropical oceans changed sharply during the latest Katian time, with consequent changes in the extent of the oxygen minimum zone and phytoplankton community composition. Although many impacted species persisted in ephemeral populations, increased extinction risk selectively depleted the diversity of paleotropical graptolite species during the latest Katian and early Hirnantian. The effects of long-term climate change on habitats can thus degrade populations in ways that cascade through communities, with effects that culminate in mass extinction.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".