Extreme climate events counteract the effects of climate and land‐use changes in <scp>A</scp>lpine tree lines
Bibliographic record
Abstract
Summary Climate change and extreme events, such as drought, threaten ecosystems world‐wide and in particular mountain ecosystems, where species often live at their environmental tolerance limits. In the European Alps, plant communities are also influenced by land‐use abandonment leading to woody encroachment of subalpine and alpine grasslands. In this study, we explored how the forest–grassland ecotone of Alpine tree lines will respond to gradual climate warming, drought events and land‐use change in terms of forest expansion rates, taxonomic diversity and functional composition. We used a previously validated dynamic vegetation model, FATE ‐ HD , parameterized for plant communities in the Ecrins National Park in the French Alps. Our results showed that intense drought counteracted the forest expansion at higher elevations driven by land‐use abandonment and climate change, especially when combined with high drought frequency (occurring every 2 or less than 2 years). Furthermore, intense and frequent drought accelerated the rates of taxonomic change and resulted in overall higher taxonomic spatial heterogeneity of the ecotone than would be expected under gradual climate and land‐use changes only. Synthesis and applications . The results from our model show that intense and frequent drought counteracts forest expansion driven by climate and land‐use changes in the forest–grassland ecotone of Alpine tree lines. We argue that land‐use planning must consider the effects of extreme events, such as drought, as well as climate and land‐use changes, since extreme events might interfere with trends predicted under gradual climate warming and agricultural abandonment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".