Severity of impacts of an introduced species corresponds with regional eco‐evolutionary experience
Bibliographic record
Abstract
Invasive plant impacts vary widely across introduced ranges. We tested the hypothesis that differences in the eco‐evolutionary experience of native communities with the invader correspond with the impacts of invasive species on native vegetation, with impacts increasing with ecological novelty. We compared plant species richness and composition beneath Pinus contorta to that in adjacent vegetation and other P. contorta stands across a network of sites in its native (Canada and USA) and non‐native (Argentina, Chile, Finland, New Zealand, Scotland, Sweden) ranges. At sites in North America and Europe, within the natural distribution of the genus Pinus , P. contorta was not associated with decreases in diversity. In the Southern Hemisphere, where there are no native Pinaceae, plant communities beneath P. contorta were less diverse than in other regions and compared to uninvaded native vegetation. Effects on native vegetation were particularly pronounced where P. contorta was a more novel life form and exhibited higher growth rates. Our results support the hypothesis that the eco‐evolutionary experience of the native vegetation, and thus the novelty of the invader, determines the magnitude of invader impacts on native communities. Understanding the eco‐evolutionary context of invasions will help to better understand and predict where invasion impacts will be greatest and to prioritize invasive species management.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".