Drought Coincided with, but Does Not Explain, Late Holocene Megafauna Extinctions in SW Madagascar
Bibliographic record
Abstract
Climate drying could have transformed ecosystems in southern Madagascar during recent millennia by contributing to the extinction of endemic megafauna. However, the extent of regional aridification during the past 2000 years is poorly known, as are the responses of endemic animals and economically important livestock to drying. We inferred ~1600 years of climate change around Lake Ranobe, SW Madagascar, using oxygen isotope analyses of monospecific freshwater ostracods (Bradleystrandesia cf. fuscata) and elemental analyses of lake core sediment. We inferred past changes in habitat and diet of introduced and extinct endemic megaherbivores using bone collagen stable isotope and 14C datasets (n = 63). Extinct pygmy hippos and multiple giant lemur species disappeared from the vicinity of Ranobe during a dry interval ~1000–700 cal yr BP, but the simultaneous appearance of introduced cattle, high charcoal concentrations, and other evidence of human activity confound inference of drought-driven extirpations. Unlike the endemic megafauna, relatively low collagen stable nitrogen isotope values among cattle suggest they survived dry intervals by exploiting patches of wet habitat. Although megafaunal extirpations coincided with drought in SW Madagascar, coupled data from bone and lake sediments do not support the hypothesis that extinct megafauna populations collapsed solely because of drought. Given that the reliance of livestock on mesic patches will become more important in the face of projected climate drying, we argue that sustainable conservation of spiny forests in SW Madagascar should support local livelihoods by ensuring that zebu have access to mesic habitat. Additionally, the current interactions between pastoralism and riparian habitats should be studied to help conserve the island’s biodiversity.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".