Estimating Rapid Diversity Changes During Acute Herbicide Contamination Using Environmental DNA
Bibliographic record
Abstract
ABSTRACT The biodiversity of freshwater ecosystems globally is facing severe threats due to various anthropogenic stressors, such as habitat degradation, introduction of invasive species, and pollution. Assessing the effects of human‐induced environmental stressors on population and community persistence requires accurate biodiversity estimates. While environmental DNA (eDNA) metabarcoding has emerged as a promising tool, its effectiveness in capturing rapid biodiversity responses to acute stressors across levels of biological organization (community, population, and intra‐specific levels) remains to be investigated. In this study, we tested the efficacy of eDNA metabarcoding in assessing rapid changes in aquatic zooplankton and insect communities by conducting a two‐month mesocosm experiment with pulses of glyphosate‐based herbicide under contrasting nutrient levels (mesotrophic and eutrophic). We examined the effects of treatments on community assemblages, family richness, and intraspecific diversity, and compared our findings with those obtained through a microscopy approach. Metabarcoding revealed partially congruent ecological findings with microscopy, indicating its potential in assessing rapid community changes. The herbicide induced shifts in community composition and differentially impacted zooplankton and insect family richness (increase in insects, and decrease in crustaceans and rotifers), suggesting a gradient of tolerance to the herbicide among taxa and potential top‐down regulation by insect larvae that may counteract the advantage gained by herbicide‐tolerant zooplankton. Finally, we showed that nutrient enrichment exacerbated the negative effects of the herbicide on intraspecific diversity, highlighting concerns about genetic erosion. Our findings underscore the complexity of responses to herbicide and nutrient enrichment in freshwater ecosystems. We conclude that eDNA metabarcoding can not only be used to estimate rapid changes in invertebrate communities but also provides additional value by offering a broader perspective on diversity dynamics and potential cascading effects at different scales of biological organization.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".