Impacts of two invasive goldenrod (Solidago) species at home and away
Bibliographic record
Abstract
Exotic plant invasions impose strong shifts in biotic interactions. These changes affect species abundance and distribution, driving changes in ecosystem function. A prominent change involves the remarkable capability of some invasive species to suppress native species. In this context, we investigated the stem density of a highly problematic invasive weed in Europe, giant goldenrod (Solidago gigantea), and compared it to the total plant species richness and native species diversity in plots located in both the northwestern United States and in Hungary. We found an increase in stem density of S. gigantea correlated to a significant decrease in total species diversity and native species diversity in Europe, but not in North America. We have initiated a similar field survey of Canada goldenrod (Solidago canadensis), another highly invasive weed in Europe, which will be completed during the summer of 2013. Preliminary results indicate that native plots are showing the same trend of total species richness as plots containing S. gigantea. We also compared the effect of S. gigantea and S. canadensis leachate on the germination and growth of co-occurring plant species native to North America and Europe. Solidago gigantea root leachate suppressed germination and growth of European species, but not North American species. With limited species tested, S. canadensis root leachate shows greater suppression of germination on European species than North American species, but does not show differences in the suppression of growth. A competition experiment investigating the competitive effects of entire S. canadensis plants on five co-occurring North American species and five co-occurring European species is currently underway. Initial results generally demonstrate a strong biogeographic context to exotic plant invasions and have the potential to reveal extremely significant ecological and evolutionary processes in 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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".