Canada goldenrod (Solidago canadensis): An invasive alien weed rapidly spreading in China
Bibliographic record
Abstract
Invasive species pose a serious threat to native ecosystems and their biodiversity, and cause considerable economic loss to the regions they invade. In the case of Canada goldenrod (Solidago canadensis L.) (Compositae), a long-lived perennial plant native to North America, it was initially introduced as an ornamental plant to Shanghai in 1935, it then escaped into the wild and it is now spreading rapidly in China, especially in eastern China. We here describe briefly this species in relation to invasion biology. S. canadensis is actually a Canada-goldenrod complex that consists of at least six subspecies and varieties. S. canadensis has great reproductive capacity (through both seed production and clonal growth) and high genetic variation, both of which contribute to its great invasiveness. S. canadensis may outcompete or allelopathically exclude native plant species, resulting in monospecific stands with concomitant loss of plant and insect diversity, and ultimately alteration in ecosystem functioning. Lack of natural enemies in the invaded ecosystems makes this species highly invasive. Abiotic factors such as niche opportunities created by habitat disturbance and human activities, and nitrogen deposition, can promote S. canadensis’ establishment and spread through seed dispersal and vegetative structures. In addition, the species’ capacity for early season emergence and growth, rapid clonal growth, wide physiological tolerance, and high architectural plasticity make the species highly aggressive under a wide range of ecological conditions. Although commonly used control methods of weeds may also be suitable for S. canadensis, minimising its seed production seems to be critical to its effective control, which requires that all the control measures be taken during its vegetative growth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".