The impacts of climate change on the abundance and distribution of the Spotted Wing Drosophila (<i>Drosophila suzukii</i>) in the United States and Canada
Bibliographic record
Abstract
D. suzukiiis a relatively recent and destructive pest species to the North American soft-skinned fruit industry. Understanding this species’ potential to shift in abundance and range due to changing climate is an important part of an effective mitigation and management strategy. We parameterized a temperature-drivenD. suzukiipopulation dynamics model using temperature data derived from several Global Circulation Models (CMIP5) with a range of relative concentration pathway (RCP) predictions. Mean consensus between the models suggest that without adaptation to both higher prolonged temperatures and higher short-term temperature eventsD. suzukiipopulation levels are likely to drop in currently higher-risk regions. The potential drop in population is evident both as time progresses and as the severity of the RCP scenario increases. Some regions, particularly in northern latitudes, may experience increased populations due to milder winter and more developmentally-ideal summer conditions, but many of these regions are not currently known for soft-skinned fruit production and so the effects of this population increase may not have a significant impact.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".