Chemical composition of wildfire ash produced in contrasting ecosystems and its toxicity to Daphnia magna
Bibliographic record
Abstract
It is well established in the world’s fire-prone regions that wildfires can considerably change the hydrological dynamics of freshwater catchments. Limited research, however, has focused on the potential impacts of wildfire ash toxicity on aquatic biota. Here, we assess the chemical composition and toxicity of ash generated from wildfires in six contrasting vegetation types distributed globally (UK grassland, Spanish pine forest, Spanish heathland, USA chaparral, Australian eucalypt forest and Canadian spruce forest). Acute (48 h) immobilisation tests were conducted on the extensively studied aquatic macroinvertebrate Daphnia magna, a sensitive indicator of aquatic contaminants. We found significant differences between the chemical composition and toxicity of these ash types. The UK and Spanish ash had no detectable toxicity to Daphnia magna, whereas the Australian eucalypt, USA chaparral and Canadian spruce ash all caused significant toxicity (immobilisation). The principal characteristics of the latter ash types were their high pH, and NO3−, Cl− and conductivity levels. Elevated water-soluble and total concentrations of metals (e.g. Mn, Fe, Zn, Pb, Cu and As) and total polycyclic aromatic hydrocarbons (PAHs) were not linked to toxicity.
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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) | 0.000 | 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".