Data from: Soil-mediated impacts of an invasive thistle inhibit the recruitment of certain native plants
Bibliographic record
Abstract
Invasive plants may outcompete and replace native plant species through a variety of mechanisms. Recent evidence indicates that soil microbial pathways such as pathogen accumulation may have a considerable role in facilitating competition between native and invasive plants. To assess microbe-mediated pathways of invasion, we tested the impacts of invaded and non-invaded field soils on plant establishment using naturally-occurring populations of the common Eurasian invader Cirsium arvense (Canada thistle) in Southern Ontario, Canada. Linked field and greenhouse experiments were used to quantify differences in the germinability and early growth rates of native plant species, depending on exposure to the microbial community in invaded or non-invaded soils. The invaded microbial community significantly reduced early growth rates for two of the seven native species surveyed, and decreased seed germination for another. In contrast, the germination and growth of invasive Cirsium were not affected by its own soil microbial community. These results demonstrate that the invasion of Cirsium arvense can reduce the performance of some native plant species through changes to the soil microbial community. Different effects on different species suggest this invader may also change the relative importance of certain natives in the invaded community. If these effects influence plant abundance in the field, microbially-mediated interactions in the soil may aid the invasion of Cirsium arvense and facilitate the disruption of invaded communities.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.033 | 0.023 |
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".