Spatial and temporal variation in abundance of introduced African fig fly ( <i>Zaprionus indianus</i> ) (Diptera: Drosophilidae) in the eastern United States
Bibliographic record
Abstract
Abstract The African fig fly, Zaprionus indianus (Gupta), has spread globally from its native range in tropical Africa, becoming an invasive crop pest in select areas such as Brazil. Z. indianus was first reported in the United States in 2005 and has since been documented as far north as Canada. As a tropical species, Z. indianus is expected to have low cold tolerance, likely limiting its ability to persist at northern latitudes. In North America, the geographic regions where Z. indianus can thrive and seasonal fluctuations in its abundance are not well understood. The purpose of this study was to characterize the temporal and spatial variation in Z. indianus abundance to better understand its invasion of the eastern United States. We sampled drosophilid communities over the growing season at two orchards in Virginia from 2020-2022 and several locations along the East Coast during the fall of 2022. Virginia abundance curves showed similar seasonal dynamics across years with individuals first detected around July and becoming absent around December. Massachusetts was the northernmost population and no Z. indianus were detected in Maine. Variation in Z. indianus relative abundance was high between nearby orchards and across different fruits within orchards but was not correlated with latitude. Fitness of wild-caught females decreased later in the season and at higher latitudes. The patterns of Z. indianus abundance shown here demonstrate an apparent susceptibility to cold and highlight a need for systematic sampling to accurately characterize the range and spread of Z. indianus .
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".