Predicting plant invasiveness from native range size: clues from the Kashmir Himalaya
Bibliographic record
Abstract
In view of the growing interest in modelling the potential spread of invasive species, prediction of plant invasiveness on the basis of native range size holds considerable promise. Our objective was to use a simple model to evaluate whether a wider native range predisposes plant species to become invasive in non-native regions and to easily identify potential invaders on this basis. The Kashmir Himalayan alien flora, of which a large proportion is native to Europe, was used to test this model. The Kashmir Himalayan alien flora comprises 436 species of vascular plants at different stages of invasion. We focussed on plant species at two critical invasion stages (sensuColautti and MacIsaac 2004), i.e. Stage II (species that are just at the earliest phase of introduction) and Stage V (species that are widespread and dominant in the invaded region and are thus considered invasive). We used the territorial distribution in Europe (number of countries) as a surrogate for the native range size of plants of European origin. Using a subset of 88 species, for which information on the native European range was available, we showed that a large proportion (68%) of Stage II species growing in the Kashmir Valley had a relatively restricted European range (present in ≤20 countries); on the other hand, 77% of Stage V species had an extensive native range (present in >20 countries). We consequently hypothesized that 14 Kashmir Himalayan Stage II species of European origin that are distributed in >20 European countries are at risk of becoming future invaders in Kashmir. On the other hand, those Kashmir Himalayan Stage II species of European origin distributed in ≤20 European countries are less likely to become invasive. Although this analysis is quite simple, the data suggest that a wider native range is a good predictor of plant invasiveness and could be used as a simple and low-cost early warning tool in predicting potential invasive species.
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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 | 0.000 |
| 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) | 0.002 | 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, 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".