Effects of genetically modified, herbicide‐tolerant crops and their management on soil food web properties and crop litter decomposition
Bibliographic record
Abstract
1 Genetically modified (GM), herbicide-tolerant crops have been adopted extensively worldwide, resulting in increased homogenization of agricultural practices. However, several countries still view GM crops with trepidation, citing potential risks to human health and the environment. We currently know little about how non-target biota responds to cultivation of GM crops under field conditions. 2 This study describes a series of microcosm and field experiments in Ontario, Canada, that estimated the effects of transgenic, glyphosate-tolerant (GT) crops and their management on the abundances of detritivorous soil biota and crop litter decomposition. 3 Absolute abundance of few of the measured biotic groups were affected by either the herbicide or variety treatments and, where significant effects were observed, the responses were not consistent across all years or for all sample dates within a year. More frequently, but not consistently, the GT herbicide system was associated with increased fungal : bacterial biomass ratios, suggesting a state of reduced enrichment. 4 Although the conventional and GT varieties studied differed in composition, we observed few effects of the modification for glyphosate-tolerance on maize Zea mays and soybean Glycine max litter decomposition. Overall, the herbicide system associated with GT crops reduced soybean- and corn-litter decomposition, but responses were inconsistent across Ontario, with many trials demonstrating no effect. Effects were probably underrepresented in this study as average daily precipitation was positively correlated with the magnitude of this system effect and many sites received well-below average levels of precipitation. 5 Synthesis and applications. Most concerns regarding the potential impacts of GM crops on non-target biota have targeted traits associated with the biotechnology itself. However, shifts in management practices associated with biotechnology are also widespread and have the same, if not greater, potential to alter the structure and functioning of agroecosystem biodiversity. The lack of observed permanent negative effects on soil biota in this study is heartening; however, more research is required to determine the functional consequences of observed transient effects and effects on other biota, as well as how altered crop litter decomposition affects agroecosystem nutrient cycling and carbon sequestration.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".