Derivation of an aquatic benchmark for invertebrates potentially exposed to imidacloprid
Bibliographic record
Abstract
Water quality benchmarks are developed by many jurisdictions worldwide with the general goal of identifying concentrations that protect aquatic communities. Imidacloprid is a widely-used neonicotinoid insecticide for which benchmark values vary widely between North America and Europe. For example, the European Food Safety Authority (EFSA) and Dutch National Institute for Public Health and the Environment (RIVM) recently established chronic water quality benchmarks for imidacloprid of 0.009 and 0.0083 µg/L, respectively. In Canada and the United States (US), however, the current chronic water quality benchmarks – termed aquatic life benchmark by the United States Environmental Protection Agency (US EPA) – for freshwater biota are orders of magnitude higher, i.e., 0.23 and 1.05 µg/L, respectively. Historically, aquatic benchmarks for imidacloprid have been derived for invertebrates because they are the most sensitive aquatic receptors. To date, derivation of water quality benchmarks for imidacloprid have relied on the results of laboratory-based toxicity tests on single invertebrate species. Such tests do not account for environmental factors affecting bioavailability and toxicity or species interactions and potential for recovery. Microcosm, mesocosm and field studies are available for aquatic invertebrate communities exposed to imidacloprid. These higher tier studies are more representative of the natural environment and can be used to derive a chronic benchmark for imidacloprid. A water quality benchmark based on the results of higher tier studies is protective of freshwater invertebrate communities without the uncertainty associated with extrapolating from laboratory studies to field conditions. We used the results of higher tier studies to derive a chronic water quality benchmark for imidacloprid as follows: (1) for each taxon (family, subfamily or class depending on the study), we determined the most sensitive 21-day No Observed Effects Concentration (NOEC), (2) we fit the taxon NOECs to five distributions and determined the best-fit distribution, and (3) we determined the HC5 from the best-fit distribution. The higher tier chronic HC5 for imidacloprid is 1.01 µg/L, which is close to the current US EPA chronic aquatic life benchmark of 1.05 µg/L.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".