Raw data for: Are standard test species still relevant? A comprehensive assessment of Daphnia pulex reared in laboratory and wild environments and their responses to organic ultraviolet filters
Bibliographic record
Abstract
The establishment of laboratory-based species has facilitated the standardization of biological research methods; however, stable culturing conditions of laboratories are dissimilar to the dynamic conditions of natural environments, potentially influencing fundamentally different research outcomes between lab and wild populations. This study sought to compare the toxicity of ultraviolet filters (UVFs) avobenzone, octocrylene and oxybenzone to lab and wild populations of Daphnia pulex, while also testing the effects of culturing both populations in either OECD (lab) or lake water in 48 h and 21 d toxicity tests. Both daphnid populations demonstrated poor performance when cultured in non-ancestral waters for three generations (i.e., lab Daphnia in lake water or wild Daphnia in OECD water), including 25% decreased reproduction in control treatments and ≥50% mortality in most UVF treatments. Toxicity varied in each population cultured in ancestral waters; lab D. pulex were more sensitive to 30.7 μg/L of avobenzone and 18.8 μg/L of oxybenzone (>25% greater mortality, ≥20% decreased reproduction vs wild daphnids), while wild D. pulex were more sensitive to 25.6 μg/L of octocrylene (30% decreased mortality, 44% decreased reproduction vs lab daphnids). These results demonstrate that Daphnia populations can deviate after decades of isolation, highlighting the challenges of relating laboratory-generated data to field results. In addition, culture water greatly impacted daphnid performance during experimentation, potentially leading to misinterpreted results when studying wild organisms. This research highlights the importance of understanding how lab and wild organisms can differ, so that research modelling environmental outcomes can be applied in an appropriate context.
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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 | 0.017 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.074 | 0.036 |
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".