No Future Growth Enhancement Expected at the Northern Edge for European Beech due to Continued Water Limitation
Bibliographic record
Abstract
ABSTRACT With ongoing global warming, increasing water deficits promote physiological stress on forest ecosystems with negative impacts on tree growth, vitality, and survival. How individual tree species will react to increased drought stress is therefore a key research question to address for carbon accounting and the development of climate change mitigation strategies. Recent tree‐ring studies have shown that trees at higher latitudes will benefit from warmer temperatures, yet this is likely highly species‐dependent and less well‐known for more temperate tree species. Using a unique pan‐European tree‐ring network of 26,430 European beech ( Fagus sylvatica L. ) trees from 2118 sites, we applied a linear mixed‐effects modeling framework to (i) explain variation in climate‐dependent growth and (ii) project growth for the near future (2021–2050) across the entire distribution of beech. We modeled the spatial pattern of radial growth responses to annually varying climate as a function of mean climate conditions (mean annual temperature, mean annual climatic water balance, and continentality). Over the calibration period (1952–2011), the model yielded high regional explanatory power ( R 2 = 0.38–0.72). Considering a moderate climate change scenario (CMIP6 SSP2‐4.5), beech growth is projected to decrease in the future across most of its distribution range. In particular, projected growth decreases by 12%–18% (interquartile range) in northwestern Central Europe and by 11%–21% in the Mediterranean region. In contrast, climate‐driven growth increases are limited to around 13% of the current occurrence, where the historical mean annual temperature was below ~6°C. More specifically, the model predicts a 3%–24% growth increase in the high‐elevation clusters of the Alps and Carpathian Arc. Notably, we find little potential for future growth increases (−10 to +2%) at the poleward leading edge in southern Scandinavia. Because in this region beech growth is found to be primarily water‐limited, a northward shift in its distributional range will be constrained by water availability.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".