Combined effects of nutrient enrichment and inorganic sedimentation on benthic biota in an experimental stream system
Bibliographic record
Abstract
Sedimentation and nutrient loading are among the most prevalent threats to fluvial ecosystem integrity. This study employed artificial streams (mesocosms) to simulate individual and combined impacts of nutrient enrichment and deposited fine sediment on benthic biota. Ninety-six circular mesocosms were used in a 21-day crossed experiment that measured the impact of three substrate compositions (0, 25, and 50% fines <2 mm) and four nitrogen concentrations (17, 22, 43, and 94 μg L–1 (soluble inorganic nitrogen)) on periphyton and benthic macroinvertebrate assemblages. Permutational multivariate analysis of variance (PERMANOVA) of macroinvertebrate assemblages indicated substantial shifts in structural composition, while univariate models for Lepidostomatidae and total Ephemeroptera, Plecoptera and Trichoptera revealed that nutrient and sediment subsidies related to single factors were suppressed by an additional stressor. Stressor mechanism overlap was evident at higher treatment levels, as moderate nutrient enrichment increased nutritional resources but high nitrogen concentrations lead to substrate smothering by periphyton, contributing to habitat degradation originating from inorganic sedimentation. Our study is consistent with research showing that nutrient loading and sedimentation interact to deteriorate lotic systems beyond levels attributable to either individual stressor. Management practices and pollution standards need to incorporate relationships between stressors tightly co-vary 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 | 0.003 | 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".