The Toledo Mountains: A Resilient Landscape and a Landscape for Resilience? Hazards and Strategies in a Mid-Elevation Mountain Region in Central Spain
Bibliographic record
Abstract
The Toledo Mountains are a mid-elevation mountain range that separates the Tagus and Guadiana basins in the central area of the Iberian Peninsula. The location of these mountains allows the development of typical Mediterranean vegetation with some Atlantic influence. Consequently, typical broadleaved evergreen Mediterranean vegetation currently dominates the regional landscape, with the remarkable presence of more mesophilous species in sheltered and more humid microsites such as gorges (e.g., Prunus lusitanica, Taxus baccata, Ilex aquifolium) and mires/bogs (e.g., Betula pendula susbp. fontqueri, Erica tetralix, Myrica gale). Palaeoecological studies in these mountains are essential to understand the long-term ecology and original distribution of these valuable communities and are key to assess their resilience. Understanding the hazards and opportunities faced in the past by the plant communities of the Toledo Mountains is necessary to enhance the management and protection of those species currently threatened. This study focuses on El Perro mire, a peatland on the southern Toledo Mountains (central Spain) where climatic variability has played a major role in landscape dynamics at multi-decadal to millennial timescales. Climatic events such as the 4.2 ka cal. Before Present (BP) or the Little Ice Age triggered relevant landscape changes such as the spread and latter decline of birch and hazel forests. Human communities also seemed to be affected by these events, as their resilience was apparently jeopardized by the new climatic conditions and they were forced to find new strategies to cope with the new scenarios.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".