Determinants of rapid response success for alien invasive species in aquatic ecosystems
Bibliographic record
Abstract
Alien invasive species (AIS) have received much attention for their harmful effects on health, ecology and the global economy. In response to this threat, many countries have adopted the Convention on Biological Diversity, which requires prevention or eradication of AIS. The best management approach is prevention, however when this fails and AIS establish, it is imperative that cost-efficient, rapid-response (RR) countermeasures be available. We performed a meta-analysis of case studies involving successful and failed RR to AIS in temperate aquatic ecosystems. We examined eight variables including ecosystem type (freshwater vs. marine), method type (chemical vs. mechanical), number of methods (multiple vs. single), taxonomy (animal vs. plant), population abundance (number of organisms), infestation extent (surface area of infestation), habitat size (surface area of management site), and project duration (length of project in number of months). Eradication success was significantly greater for plant (89 %) versus animal AIS (64 %) while suppression of AIS was most successful for projects using chemical versus mechanical methods and when conducted in small habitats. Managers should expect that taxonomy will be highly influential to the success of eradication-based RR, while both method type and management surface area influence suppression outcomes.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".