Wood Growth in Pure and Mixed Quercus ilex L. Forests: Drought Influence Depends on Site Conditions
Bibliographic record
Abstract
Climate response of tree-species growth may be influenced by intra- and inter-specific interactions. The different physiological strategies of stress response and resource use among species may lead to different levels of competition and/or complementarity, likely changing in space and time according to climatic conditions. Investigating the drivers of inter- and intra-specific interactions under a changing climate is important when managing mixed and pure stands, especially in a climate change hot spot as the Mediterranean basin. Mediterranean tree rings show intra-annual density fluctuations (IADFs): the links among their occurrence, anatomical traits, wood growth and stable isotope ratios can help understanding tree physiological responses to drought. In this study, we compared wood production and tree-ring traits in Quercus ilex L. dominant trees growing in two pure and two mixed stands with Pinus pinea at two sites in Southern Italy, on the basis of the temporal variation of cumulative basal area, intrinsic water use efficiency (WUEi), δ18O and IADF frequency in long tree-ring chronologies. The general aim was to assess whether Q. ilex trees growing in pure or mixed stands have a different wood production through time, depending on climatic conditions and stand structure. The occurrence of dry climatic conditions triggered opposite complementarity interactions for Q. ilex growing with P. pinea trees at the two sites. Competitive reduction was experienced at the T site characterized by higher soil water holding capacity, lower stand density and less steep slope than the S site; on the opposite, high competition occurred at S site. The observed difference in wood growth was accompanied by a higher WUEi due to a higher photosynthetic rate at the T site, while by a tighter stomatal control in mixed stand of S site. IADF frequency in Q. ilex tree rings was linked to higher WUEi, thus to stressful conditions and could be interpreted as strategy to cope with dry periods, independently from the different wood growth. Considering the forecasted water shortage, inter-specific competition should be reduced in denser stands of Q. ilex mixed with P. pinea. Such findings have important implications for forest management of mixed and pure Q. ilex forests.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.001 |
| 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".