Projecting the Global Potential Distribution of <i>Cydia pomonella</i> (Lepidoptera: Tortricidae) Under Historical and RCP4.5 Climate Scenarios
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The codling moth Cydia pomonella (L.) (Lepidoptera: Tortricidae) is a destructive pest of apple (Malus domestica (Rosales: Rosaceae)), pear (Pyrus spp. (Rosales: Rosaceae)), and other pome tree fruits; outbreaks cause significant ecological and economic losses. In this study, we used CLIMEX model to predict and evaluate the global risk of C. pomonella based on historical climate data (1989-2018) and simulated future climate data (2071-2100) under the RCP4.5 scenarios. Cydia pomonella exhibited a wide distribution under both historical and future climate conditions. Climate change is predicted to expand the northern boundary of the potential distribution from approximately 60°N to 75°N. Temperature was the most dominant factor in climatic suitability for the pest. Combinations of multiple meteorological factors (relative humidity and precipitation) associated with a failure to break diapause in certain regions also affect suitability, particularly in northern South America and central Africa. Irrigation only had a slight impact on species favorability in some areas. The projections established in our study present insight into the global potential suitability of C. pomonella under climate change scenarios by the end of the 21st century. Farmers should be aware of the risk associated with the pest based on the results, which would provide guidance for quarantine agencies and trade negotiators worldwide.
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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 | 0.000 |
| 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 | 0.001 |
| 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 it