Land‐use legacies rather than climate change are driving the recent upward shift of the mountain tree line in the <scp>P</scp>yrenees
Bibliographic record
Abstract
Abstract Aim To assess the effects of climate change, past land uses and physiography on the current position of the tree line in the C atalan P yrenees and its dynamics between 1956 and 2006. Location More than 1000 linear kilometres of sub‐alpine tree line in the C atalan P yrenees (north‐east S pain) Methods Using aerial photographs and supervised classification, we reclassified the images into a binary raster with ‘tree’ and ‘non‐tree’ values, and determined canopy cover in 1956 and 2006. We then determined the change in position of the tree line between 1956 and 2006 based on changes in forest cover. We used the distance from the position of the tree line in 1956 to the theoretical potential tree line – determined from interpretation of aerial photographs, identifying the highest old remnants of forest for homogeneous areas of the landscape in terms of bioclimatic conditions, bedrock, landform and exposure – as a surrogate of intensity of past land uses. Results Our analyses showed that the P yrenean tree line has moved upwards on average almost 40 m (mean advance ± SE : 35.3 ± 0.5 m, P < 0.001), although in most cases it has remained unchanged (61.8%) or advanced moderately, i.e. between 25 and 100 m (23.7%); only 9.2% of the locations have advanced more than 100 m. Upward shifts of the tree line were significantly larger in locations heavily modified in the past by anthropogenic disturbance (mean advance 50.8 ± 1.1 m) compared with near natural tree line locations (19.7 ± 0.8 m, P < 0.001), where the mean displacement was much lower than expected and was not related to changes in temperature along the study period. Main conclusions Our results stress the impact of the cessation of human activity in driving forest dynamics at the tree line in the C atalan P yrenees, and reveal a very low or even negligible signal of climate change in the study area.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".