Economic Impact from Unrestricted Spread of Potato Cyst Nematodes in Australia
Bibliographic record
Abstract
ABSTRACT Potato cyst nematodes (PCN) (Globodera spp.) are quarantine pests with serious potential economic consequences. Recent new detections in Australia, Canada, and the United States have focussed attention on the consequences of spread and economic justifications for alternative responses. Here, a full assessment of the economic impact of PCN spread from a small initial incursion is presented. Models linking spread, population growth, and economic impact are combined to estimate costs of spread without restriction in Australia. Because the characteristics of the Australian PCN populations are currently unknown, the known ranges of parameters were used to obtain cost scenarios, an approach which makes the model predictions applicable generally. Our analysis indicates that mean annual costs associated with spread of PCN would increase rapidly initially, associated with increased testing. Costs would then increase more slowly to peak at over AUD$20 million per year approximately 10 years into the future. Afterward, this annual cost would decrease slightly due to discounting factors. Mean annual costs over 20 years were $18.7 million, with a 90% confidence interval between AUD$11.9 million and AUD$27.0 million. Thus, cumulative losses to Australian agriculture over 20 years may exceed $370 million without action to prevent spread of PCN and entry to new areas.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".