Assessing climate change impacts on the geographical distribution of Cupressus sempervirens in the Mediterranean region
Bibliographic record
Abstract
Cupressus sempervirens L., a long-lived conifer of the Cupressaceae family, plays a vital ecological, medicinal, and economic role in the Mediterranean basin. Due to the species' sensitivity to climatic fluctuations, particularly temperature and precipitation regimes, understanding its potential distributional shifts under climate change is critical. This study employs ecological niche modeling to quantify the current and future potential geographic distribution of C. sempervirens under two Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5) for the mid-twenty-first century (2041-2060). Model outputs identified mean diurnal range (bio2), precipitation seasonality (bio15), and annual precipitation (bio12) as key determinants of habitat suitability. Presently, suitable habitats are concentrated throughout the Mediterranean region, with moderate suitability extending into the Euro-Siberian and Irano-Turanian domains. Future climate projections indicated an expansion of climatically suitable areas, most consistently within the Mediterranean basin, where predictions showed higher reliability, whereas additional gains in northern regions (e.g., around the Caspian and Black seas) were associated with greater model uncertainty, reflecting overall increases in suitable habitat of 14.7% under SSP2-4.5 and 16.4% under SSP5-8.5. These findings provide critical insights for developing effective monitoring frameworks and conservation strategies to enhance the resilience and adaptive capacity of C. sempervirens populations amid ongoing climate change.
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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 | 0.001 |
| 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".