Reconstruction of the abiotic characteristics of past biomes: An example from the last glacial-interglacial cycle in France
Bibliographic record
Abstract
The abiotic conditions (soil properties, water balance) associated with terrestrial biomes in France during the last climatic cycle have been quantified using an indirect method. A set of potential modern climatic analogues across the world was first selected for each biome type. The edaphic features corresponding to the chosen analogue vegetation were then taken from a global soil database and attributed to the biomes. Finally, the hydrological parameters were simulated for these analogues using a vegetation model. We have identified five groups of modern analogues with either higher latitudes or higher elevations than the average present environment of France. From these five groups of analogues, the first two represent boreal forest, two others are steppic, and the last one represents tundra. The first group of analogues represents boreal forests at high latitudes (averaged latitude: 61° N, average elevation: 300 m) with mainly sandy podzolized soils and intermittent permafrost, high precipitation and rapid drainage. The second group of analogues represents boreal forests at higher elevations and lower latitudes (44° N, 2100 m) with stony soil and lower precipitation as well as poorer drainage. The first group of steppes at low elevations and high latitudes (64° N, 500 m) is characterized by cambisol or gleysol soils. The second group of steppes at high elevations and relatively low latitudes (41° N, 2900 m) has a hydrological regime with high evapotranspiration and poor drainage that is compatible with presence of xerosols and yermosols. The tundra group (57° N, 1400 m) has lithosolic, cambisolic and gleysolic soils. The approach used here can be applied on a global scale and could provide useful boundary conditions for simulating past climate with general circulation models.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".