Short-Term Effects of Droughts and Cold Winters on the Growth of Scots Pine at Coastal Sand Dunes around the South Baltic Sea
Bibliographic record
Abstract
Coastal dunes near the Baltic Sea are often stabilized by Scots pine forests and are characterized by a mild climate. These ecosystems are affected by water shortages and might be influenced by climate extremes. Considering future climate change, utilizing tree rings could help assess the role of climate extremes on coastal forest growth. We used superposed epoch analysis to study Scots pine responses to droughts and cold winters, with focus on frequency, timing, and duration. We measured ring widths (RW) and latewood blue intensity (LBI) on samples extracted from trees growing at dune ridge and bottom microsites at the south Baltic Sea. At the regional scale, we observed some similarities in tree responses to both extremes between RW and LBI within the same microsite type and region. At the local scale, RW and LBI were more frequently influenced by cold winters than droughts. RW and LBI from dune ridges were more frequently influenced by droughts than RW and LBI from dune bottoms. LBI from both microsites was more often influenced by droughts than RW. RW and LBI from both microsites were similarly often influenced by cold winters. At both scales, the response time of RW and LBI after droughts predominantly lagged by one year, while cold winters were recorded in the same year. The typical duration of growth reductions after both extremes was one year for both RW and LBI. Our study indicates that Scots pine from the Baltic Sea region is sensitive to climate extremes, especially cold winters.
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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".