Adverse impacts of Roundup on soil bacteria, soil chemistry and mycorrhizal fungi during restoration of a Colorado grassland
Bibliographic record
Abstract
Glyphosate is a widely used herbicide in agricultural, domestic, and restoration settings to manage weeds and invasive plants and is the active ingredient in the herbicide formulation Roundup. Concurrently with its drastic increase in usage, concern over indirect ecosystem effects and effects on non-target species has grown. In restoration, glyphosate is often used to remove invasive plants so native plants may be re-introduced. However, successful reintroductions require soils and microbial communities that support native plant growth, and it is critical that glyphosate applications do not harm soil microbes such as mycorrhizal fungi. Despite previous studies investigating the effects of glyphosate on soils and microbial communities, comprehensive field experiments combining soil chemistry and next generation sequencing technologies to describe both bacterial and eukaryotic responses to glyphosate are limited, especially in the contexts of ecosystem restoration and soil health. We studied the effects of the glyphosate-based herbicide Roundup Promax at frequencies of 0, 2, 4, and 5 applications over the course of 12 months on soil biotic and abiotic soil health indicators in a Colorado prairie dominated by the invasive cool-season grass Bromus inermis. Here we report cascading effects on soil chemistry, with increases in nitrate and acidity and consequent decreases in calcium content and cation exchange capacity. Bacterial and archaeal communities were more affected by Roundup Promax than eukaryotic communities, with decreases in phylogenetic diversity and changes in community structure following Roundup Promax applications, particularly after five applications. More critically, the colonization of plant roots by arbuscular mycorrhizal fungi decreased significantly in plots receiving even just two applications of Roundup Promax, and dark septate endophytes decreased after four applications. Our work shows that Roundup Promax had multiple negative effects on soil biota in this field study due to either direct effects or indirect effects mediated through plant removal. Our results suggest that repeated herbicide applications are especially damaging to soil health and microbe-plant associations. These effects in turn could severely hamper the ability of native plants to establish during ecosystem restoration projects.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".