Late Quaternary megafaunal extinctions on the continents: a short review
Bibliographic record
Abstract
This paper provides an overview of the contentious issue of global megafaunal extinctions in the Late Quaternary. The main proposed causes are ‘overkill’, environmental change or a combination of both. There are major objections to the other suggested causes. Extinctions were highly variable in their severity between different zoogeographical regions, with the greatest impact in North America, South America and Australia, but also substantial in northern Eurasia. Sub‐Saharan Africa and Southern Asia were much less affected. For northern Eurasia, detailed chronologies show a staggered extinction pattern, in which each megafaunal species exhibits unique and complex distributional shifts, culminating in extinction for some species and survival in others. Environmental drivers were clearly very important, although the possible role of humans is not yet clear. Alaska/Yukon also has a good radiocarbon record which also suggests a staggered extinction pattern. However, the available data for the rest of North America are largely unsatisfactory. South America also boasted spectacular extinct megafauna, but again the currently available dates are insufficient to reliably discern patterns or possible causes. Australia and New Guinea also suffered major losses, but extinctions probably occurred much earlier than elsewhere, so that establishing a chronology is especially difficult. Africa and Southern Asia have the least available data. In order to make meaningful progress, it is vital to establish a large database of reliable radiocarbon dates for each region made directly on securely identified megafaunal remains. The need is for much more high quality data, not more debate based on imperfect evidence. Copyright © 2014 John Wiley & Sons, Ltd.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".