Plant invasion in Mediterranean Europe: current hotspots and future scenarios
Bibliographic record
Abstract
The Mediterranean Basin has historically been subject to alien plant invasions that threaten its unique biodiversity. This seasonally dry and densely populated region is undergoing severe climatic and socioeconomic changes, and it is unclear whether these changes will worsen or mitigate plant invasions. Predictions are often biased, as species may not be in equilibrium in the invaded environment, depending on their invasion stage and ecological characteristics. To address future predictions uncertainty, we identified invasion hotspots across multiple biased modelling scenarios and ecological characteristics of successful invaders. We selected 92 alien plant species widespread in Mediterranean Europe and compiled data on their distribution in the Mediterranean and worldwide. We combined these data with environmental and propagule pressure variables to model global and regional species niches, and map their current and future habitat suitability. We identified invasion hotspots, examined their potential future shifts, and compared the results of different modelling strategies. Finally, we generalised our findings by using linear models to determine the traits and biogeographic features of invaders most likely to benefit from global change. Currently, invasion hotspots are found near ports and coastlines throughout Mediterranean Europe. However, many species occupy only a small portion of the environmental conditions to which they are preadapted, suggesting that their invasion is still an ongoing process. Future conditions will lead to declines in many currently widespread aliens, which will tend to move to higher elevations and latitudes. Our trait models indicate that future climates will generally favour species with conservative ecological strategies that can cope with reduced water availability, such as those with short stature and low specific leaf area. Taken together, our results suggest that in future environments, these conservative aliens will move farther from the introduction areas and upslope, threatening mountain ecosystems that have been spared from invasions so far.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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".