Invasive Species: Major Threat to Caribbean Netherlands Biodiversity
Bibliographic record
Abstract
Not all introductions of exotic species will ultimately result in biological establishment or invasive tendencies but do carry that risk.Assessment of risks is complicated; assessment of invasions is somewhat easier after a non-native species has been present for a shorter or longer period and risks differ greatly depending on the species.However, once invasion takes place and becomes evident typically any action to reverse the problem is too late and the ecology of the area invaded will likely forever be impacted.Therefore, in this assessment of the invasive species problem we use exotic species as the barometer for the invasive alien species (IAS) problem.A first assessment of invasive alien species (IAS) within the Dutch Caribbean was performed in 2011, which indicated the presence of 211 exotic, non-native species across different invasion stages.These included 27 marine, 65 terrestrial plant, and 72 terrestrial animal species as well as 47 introduced pests and diseases.Lists of these species, pests and diseases are found in respectively Debrot et al.(2011), van der Burg et al. ( 2012), and van Buurt and Debrot (2012;2011).Even without an exhaustive review, we here now report an additional 710 new island occurrences of (potentially invasive) exotic taxa which have been documented from nature on one or more of the six Dutch Caribbean islands (Bonaire, Saba, St. Eustatius) since the 2011 inventory.These new island occurrences amount to for example, 40 records of exotic reptiles, 54 records of exotic snails, 10 records of non-native land flatworms, 448 records of exotic weedy plants, and 100 records of exotic insects (Table 1).The NEPP for the Caribbean Netherlands assigns a high priority to the invasive species problem (Min. LNV et al., 2020), which worldwide is considered second only to habitat destruction as a long-term threat to biodiversity (Kaiser, 1999; Mooney and Hobbs, 2001).Table 1.Number of newly identified non-native species among the Dutch Caribbean islands.(see Appendix 3 for full listing).
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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; both teacher heads agree on what is shown here.
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".