Recovery of aquatic and terrestrial populations in the context of European pesticide risk assessment
Bibliographic record
Abstract
In the present review, we compiled and evaluated the available information supporting the assessment of population and community recovery after pesticide application. This information is crucial for the environmental risk assessment of pesticides. We reviewed more than 3900 manuscripts on those organism groups relevant or likely to become relevant for the risk assessment procedures in Europe, that is, aquatic invertebrates, algae, aquatic plants, fish, aquatic microbes, amphibians, as well as birds and mammals, non-target terrestrial arthropods including honeybees, non-arthropod invertebrates, terrestrial microbes, non-target terrestrial plants, nematodes, and reptiles. Finally, 106 aquatic and 76 terrestrial studies met our selection criteria and were evaluated in detail. We extracted the following general conclusions. (i) Internal recovery depends strongly on reproduction capacity. For aquatic invertebrates, recovery was generally observed within a maximum of five generation times. (ii) In cases where recovery occurred within one generation, migration from uncontaminated areas was identified as the main pathway for aquatic and terrestrial invertebrates, in particular, for insect species with the ability for aerial recolonization. (iii) Community composition in general did not recover within the study duration in the majority of cases. (iv) The ecological context, including factors such as food resources, habitat quality, and recolonization potential, is a crucial factor for recovery from pesticide effects. (v) Indirect effects acting through food chain processes, including predation and competition, are highly relevant for increasing the magnitude of effect and for prolonging recovery time. Based on our findings, we recommend defining realistic scenarios for risk assessment regarding exposure, taxa considered, environmental conditions, and ecological context. In addition to experimental studies, field monitoring was shown to yield valuable information to identify relevant taxa, long-term effects, and the conditions for recovery, and should therefore be considered to validate approaches of risk assessment. Likewise, ecological modelling was found to be a valuable tool for assessing recovery. Finally, both study design and interpretation of results still often suffer from missing ecological information or from neglect of the available knowledge. Hence, a more rigorous utilization of existing knowledge (e.g., from general disturbance ecology) and the generation of systematic ecological knowledge on the various factors influencing recovery are needed.
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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 | 0.001 | 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) | 0.000 | 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".