Modelling the effects of CO2 on C3 and C4 grass competition during the mid-Pleistocene transition in South Africa
Bibliographic record
Abstract
Abstract Palaeoenvironmental reconstructions of the interior of South Africa show a wetter environment than today and a non-analogous vegetation structure in the Early Pleistocene. This includes the presence of grasses following both C3 and C4 photosynthetic pathways, whereas C3 grasses decline after the mid-Pleistocene transition (MPT, c. 1.2–0.8 Ma). However, the local terrestrial proxy record cannot distinguish between the potential drivers of these vegetation changes. In this study we show that low glacial CO2 levels, similar to those at the MPT, lead to the local decline of C3 grasses under conditions of decreased water availability, using a vegetation model (LPX) driven by Atmosphere–Ocean coupled General Climate Model climate reconstructions. We modelled vegetation for glacial climates under different levels of CO2 and fire regimes and find evidence that a combination of low CO2 and changed seasonality is driving the changes in grass cover, whereas fire has little influence on the ratio of C3:C4 grasses. Our results suggest the prevalence of a less vegetated landscape with limited, seasonal water availability, which could potentially explain the much sparser mid-Pleistocene archaeological record in the southern Kalahari.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".