BIOMASS, PRODUCTIVITY, AND DOMINANCE OF ALIEN PLANTS: A MULTIHABITAT STUDY IN A NATIONAL PARK
Bibliographic record
Abstract
The invasion of natural and anthropogenic habitats by alien plants is a global problem. To understand the factors that regulate the success of alien plant species we sampled alien plant biomass and species composition in 66 sites representing a wide variety of habitat types within Bruce Peninsula National Park, Ontario, Canada. We quantified the response of existing alien biomass to a suite of habitat variables including habitat productivity, standing biomass, species richness, soil nutrients and disturbance factors. Standing biomass in the sites varied from 0 to nearly 60 000 g/m2 and annual productivity ranged from 0 to nearly 800 g·m−2·yr−1. The response of both absolute and relative alien biomass (dominance) to the independent variables was assessed using univariate plots and multivariate canonical correspondence analysis. The results show that total standing alien biomass and site disturbance history can predict alien dominance, but other factors including primary productivity, nutrient levels, and site species richness cannot. In the multivariate analysis, species composition of both aliens and natives was best explained by nutrient levels, disturbance type, biomass, and, to a lesser extent, productivity. The study illustrates the value of examining both absolute abundance and dominance of aliens across a broad array of habitat types, and in the context of a large suite of possible driving functions.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".