The Potential Global Distribution and Voltinism of the Japanese Beetle (Coleoptera: Scarabaeidae) Under Current and Future Climates
Bibliographic record
Abstract
Japanese beetle, Popillia japonica (Newman), is a severe invasive insect pest of turf, landscapes, and horticultural crops. It has successfully colonized much of the United States and has recently established in mainland Europe. The distribution and voltinism of P. japonica will undoubtedly change as a consequence of climate change, posing additional challenges to the management of this species. To assess these challenges, a process-oriented bioclimatic niche model for P. japonica was developed to examine its potential global distribution under current (1981-2010) and projected climatic conditions (2040-2059) using one emission scenario (representative concentration pathway [RCP] 8.5) and two global climate models, ACCESS1-0 and CNRM-CM5. Under current climatic conditions, the bioclimatic niche model agreed well with all credible distribution data. Model projections indicate a strong possibility of further range expansion throughout mainland Europe under both current and future climates. In North America, projected increases in temperature would enable northward range expansion across Canada while simultaneously shifting southern range limits in the United States. In Europe, the suitable range for P. japonica would increase by 23% by midcentury, especially across portions of the United Kingdom, Ireland, and Scandinavia. Under the RCP 8.5 scenario, cumulative growing degree-days increased, thereby reducing the probability of biannual life cycles in northern latitudes where they can occur, including Hokkaido, Japan, northeastern portions of the United States, and southern Ontario, Canada. The results of this study highlight several regions of increasing and emerging risk from P. japonica that should be considered routinely in ongoing biosecurity and pest management surveys.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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 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".