Impacts des sociétés agro-pastorales sur la biodiversité : lecture croisée paléogénomique, paléoécologique et archéologique
Bibliographic record
Abstract
The emergence of the agro-pastoral way of life transformed the ecosystems and the dynamics of the biodiversity. This transition took place in a period of important climate variability, marked by different climatic events, which have influenced its spread and the local biodiversity. Nevertheless, differentiate which part of the fauna and flora variability results from the anthropic or climatic impacts is challenging. The study of environmental proxies in two different contexts, the Armorican Massif in North-Western Europe and the Saint-Pierre and Miquelon archipelago in North-Eastern Canada can unveil new insights to discuss this question. In this work we analyzed palaeoecological pollen and DNA proxies on different environmental archives. We observed through a conjoint review and meta-analysis the gradual opening of the Armorican landscape in response to the arrival of farming communities. The pollen-based climate reconstruction in this area put in evidence rapid climate variability and its influence on agro-pastoral activities. The study of ancient environmental DNA, through metagenomics strategies can complement pollen and archaeological data. Notably the use of bioinformatically designed probes in targeted capture enrichment hold the potential to retrieve diverse ecologically informative taxa. The application of these strategies in ombrotrophic peat bogs in Sain-Pierre and Miquelon notes the need to approach this type of archive with caution. To, conclude the work presented in this thesis allowed to enrich our knowledge on biodiversity dynamics during the agro-pastoral transition. It call for an enhanced transdisciplinary approach of environmental archives and pave the way for new palaeogenomic work on peatlands.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".