Lethal risk to birds from insecticide use in the United States—a spatial and temporal analysis
Bibliographic record
Abstract
We used pesticide use data and previously published models to estimate the lethal risk to birds from insecticides used in U.S. agriculture. Data from the U.S. Department of Agriculture's National Agricultural Statistical Service (NASS, Washington, D.C.) were used to assess how the lethal risk to birds has changed over the period 1991 to 2003 and to compare risk among crop types according to the most recently available surveys. Because the NASS data coverage is incomplete, both with respect to crop and state, we also used a database assembled by the National Center for Food and Agriculture Policy (NCFAP, Washington, D.C.) for the 1997 reference year, to which we added state-specific average application rates for crop/insecticide combinations. For each state/crop/insecticide combination (>6000 entries), we assessed the proportion of crop area on which avian mortality was deemed probable, as well as the extended number of hectares this represented. The crops responsible for most potential bird mortality in the United States were corn and cotton, followed more distantly by alfalfa, wheat, potato, peanut, sugar beet, sorghum, tobacco, and citrus. Other crops represented a higher risk to birds on a per hectare basis. The southeast United States generally had the highest proportion of farmland with a lethal risk to birds. On a positive note, the lethal risk to birds has generally declined over the last decade in most crops, although there are exceptions such as small fruit crops. The reasons for this improvement vary from crop to crop, but usually entail the replacement of older more hazardous products with newer ones with lower acute toxicity to birds.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".