Attributing forest responses to global‐change drivers: limited evidence of a<scp>CO</scp><sub>2</sub>‐fertilization effect in Iberian pine growth
Bibliographic record
Abstract
Abstract Aim Forest responses to global‐change drivers such as rising atmospheric CO 2 concentrations ( C a ), warming temperatures and increased aridification will depend on tree species and site characteristics. We aim to determine if rising C a enhances growth of coexisting pine species along broad ecological gradients in a drought‐prone area. Location Iberian Range, Spain. Methods We sampled 557 trees of five pine species encompassing a wide climatic gradient and measured their radial growth. We used nonlinear flexible statistics (generalized additive mixed models) to characterize growth trends and relate them to C a , temperature and water balance. Results The sites most responsive to the growing‐season water balance were dominated by Pinus pinaster and Pinus nigra at low elevations, whereas those most responsive to temperatures were high‐elevation Pinus sylvestris and Pinus uncinata stands. From 1950 onwards, most sites and species showed decreasing radial growth trends. Growth trends were coherent with a CO 2 ‐related fertilization effect only in one P. sylvestris site. Main conclusions We found little evidence of growth stimulation of Iberian pine forests due to rising C a . The results indicated that any positive effect of a C a ‐induced growth increase was unlikely to reverse or cancel out the drought‐driven trends of reduced growth in most Mediterranean pine forests. Further assessments of CO 2 ‐fertilization effects on forest growth should be carried out in sites where climatic stressors such as drought do not override the effects of rising C a on forest growth.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".