Bioclimatic approach to assessing the potential impact of climate change on wheat midge (Diptera: Cecidomyiidae) in North America
Bibliographic record
Abstract
Abstract Wheat midge,Sitodiplosis mosellana(Géhin) (Diptera: Cecidomyiidae), Palaearctic in origin, is thought to have been introduced into North America in the early 1800s. It is a major pest of spring wheat (Triticum aestivumLinnaeus (Poaceae)), durum wheat (T. durumDesfontaines), triticale (X-Triticosecale), and, to a lesser extent, spring rye (Secale cerealeLinnaeus (Poaceae)) throughout the northern Great Plains. Climate is the principal factor regulating the distribution and abundance of most insects. A bioclimate simulation model was developed to explain the current distribution and abundance ofS. mosellana. The current distribution for North America, Europe, and Asia was consistent with model projections. General circulation model scenarios (CSIRO-MK 3.0 and MIROC-H) for the 2030 and 2070 time periods were applied to the bioclimate simulation model ofS. mosellanato assess the potential impact of changing climates on their distribution and relative abundance. Potential changes to relative abundance and distribution were most sensitive to time period, as opposed to climate change scenario. Differences between the MIROC-H and CSIRO-MK 3.0 models were restricted to particular regions in North America. The study found that the range and abundance ofS. mosellana, and associated crop risk, was predicted to expand in a northerly direction and contract across the present southern limits.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".