Responses of Pine and Oak Species to Drought: A Bibliometric Analysis
Bibliographic record
Abstract
Pines (Pinus, with approximately 113 species) and oaks (Quercus, with around 435 species) are key genera that form forests across the entire Northern Hemisphere. These regions are often associated with seasonal drought and forest fires, worsening conditions due to climate change. In this study, we used bibliometric techniques to analyse research patterns regarding the drought responses of pine and oak species from 1977 to 2024. Our analysis relied on the Web of Science (WoS) database, focusing on publications indexed in both the Science Citation Index and the Social Science Citation Index. Our review included 104 studies examining 29 pine and 42 oak species in 58 combinations. Notably, many pine and oak species have yet to be studied. The most researched species include P. sylvestris (27 studies), P. halepensis (25 studies), and Q. ilex (27 studies). Geographically, the Mediterranean basins were found to be the most prominent areas of study. Much of the research originated in the United States and France, while recent contributions have come from China, Spain, and Canada. Research publications on this topic have increased since the 1990s, with noticeable peaks in 2008, 2011, and 2023. The journals contributing significantly to this body of knowledge include Tree Physiology, Forest Ecology and Management, and the Journal of Experimental Botany. Interestingly, while drought is a crucial aspect of plant ecology, much research has focused on physiological and botanical considerations. In the past two decades, there has been a marked increase in integrating climate-related variables with traditional physiological components and water management. The bibliometric analysis concluded that, at the genus level, the primary strategy of pines in response to drought stress is predominantly isohydric, while oaks tend to be anisohydric. This difference allows oaks to maintain gas exchange and carbon fixation, even for increased water loss. The shared occurrence of pine and oak species throughout the Northern Hemisphere suggests that proper management practices can be developed to promote the growth of one species through the other, especially by learning from post-drought recovery processes and succession.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.112 | 0.140 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".