A probabilistic risk assessment for the Kirtland's warbler potentially exposed to chlorpyrifos and malathion during the breeding season and migration
Bibliographic record
Abstract
Abstract Two organophosphate pesticides, chlorpyrifos and malathion, are currently undergoing reregistration in the United States and were recently used by the US Environmental Protection Agency (USEPA) as case studies to develop a national procedure for evaluating risks to endangered species. One of the endangered bird species considered by the USEPA was the Kirtland's warbler (Setophaga kirtlandii). The Kirtland's warbler is an endangered migratory species that nests exclusively in young jack pine stands in Michigan and Wisconsin, and winters in the Bahamas. We developed probabilistic models to assess the risks of chlorpyrifos and malathion to Kirtland's warblers during the breeding season and the spring and fall migrations. The breeding area model simulates acute and chronic exposure and risk to each of 10 000 birds over a 60-d period following initial pesticide application. The model is highly species specific with regard to the foraging behavior of Kirtland's warblers during the breeding season. We simulated the maximum application rate and number of applications allowed on the labels for representative use patterns that could be found within 3 km of the breeding areas of Kirtland's warbler. The migration model simulates 10 000 birds during the course of their 12- to 23-d migration between their breeding area and the Bahamas. The model takes advantage of more than a century of observations of when, where, and for how long Kirtland's warblers forage in different habitats during the course of their migration. The data indicate that warblers only infrequently stop over in habitats that could be treated with chlorpyrifos and malathion. The breeding area and migration models resulted in predictions of very low acute and chronic risk for both pesticides to Kirtland's warblers. These results were expected, given that field observations indicate that the Kirtland's warbler has dramatically increased in abundance in recent decades. Integr Environ Assess Manag 2018;14:252–269. © 2017 SETAC Key Points Probabilistic exposure models were developed to assess the risks of chlorpyrifos and malathion to Kirtland's warblers during the breeding season and during spring and fall migrations. The migration model simulated birds during their 13- to 23-d migrations, and the breeding area model simulated birds for a 60-d period following pesticide application in proximity to their breeding habitats. Using realistic and species-specific models and inputs resulted in predictions of very low acute and chronic risk of chlorpyrifos and malathion to Kirtland's warblers. These results were expected, given that the Kirtland's warbler has dramatically increased in abundance in recent decades despite widespread usage of chlorpyrifos and malathion.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".