Fish assemblage–environment relationships suggest differential trophic responses to heavy metal contamination
Bibliographic record
Abstract
Abstract While ecotoxicology has long recognised the importance of identifying levels at which contaminants pose threats to biota, most estimates of species responses to toxicants are derived from controlled laboratory studies and may hold limited relevance to natural systems. However, designing appropriate field‐based studies investigating contaminant induced changes in assemblages has been challenging, partially due to the difficulty in identifying comparable uncontaminated reference sites. The aim of this study is to characterise the effects of heavy metal contamination on natural fish assemblages using an ecologically relevant catchment‐scale design. We hypothesise that environmental variables, including discharge, sediment, and landscape variables, can be used to characterise differences in fish species richness and abundances between sites contaminated with heavy metals and uncontaminated reference sites. We apply a geographic information systems approach that uses assemblage–environment relationships developed using hydrologic model outputs, land cover, and topographic data from uncontaminated reference sites to predict expected fish species richness and abundance at sites contaminated with heavy‐metals within the Big River catchment in south‐eastern Missouri, U.S.A. These predicted levels of richness and abundance are then compared to observed assemblages at contaminated sites to estimate the potential impacts of historical lead mining activities on freshwater taxa. We developed models that characterised variation in Centrarchidae (bass and sunfish) richness and abundance, Cyprinidae (minnows) abundance, and Percidae (darters) richness using variables including streamflow regime, suspended sediment concentration, and land cover at uncontaminated sites. Using these relationships, we predicted expected fish species richness and abundance at heavy metal contaminated sites across the Big River catchment and found a significant reduction in centrarchid abundance from field‐collected data compared to predicted estimates. Our results suggest that centrarchids, which tend to occupy a higher trophic level than cyprinids and percids, have lower abundances at sites contaminated with heavy metals than predicted by assemblage–environment relationships. These decreases in abundance are not associated with decreases in centrarchid species richness, cyprinid abundance, or percid richness. This geographic information systems‐based approach provides a useful and ecologically relevant framework for understanding the response of taxa to the presence of contaminants without assuming habitat equivalence across sites. Our findings also suggest the need for further research regarding how heavy metals impact fishes of varying trophic levels in natural settings.
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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) | 0.009 | 0.006 |
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; both teacher heads agree on what is shown here.
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".