Modelling the Impact of Temperature under Climate Change Scenarios on Native and Invasive Vascular Vegetation on the Antarctic Peninsula and Surrounding Islands
Bibliographic record
Abstract
There are only two species of native vascular plants found on the Antarctic Peninsula and the surrounding islands, Deschampsia Antarctica, and Colobanthus quitensis. Poa annua, a successful invasive species, poses a threat to D. antarctica and C. quitensis. This region may experience extreme changes in biodiversity due to climate change over the next 100 years. This study explores the relationship between vascular vegetation and changing temperature on the Antarctic Peninsula and uses a systems modelling approach to account for three climate change scenarios over a 100-year period. The results of this study indicate that (1) D. antarctica, C. quitensis, and P. annua will likely be impacted by temperature increases, and greater temperature increases will facilitate more rapid species expansion, (2) in all scenarios D. antarctica species occurrences increase to higher values compared to C. quitensis and P. annua, suggesting that D. antarctica populations may be more successful at expanding into newly forming ice-free areas, (3) C. quitensis may be more vulnerable to the spread of P. annua than D. antarctica if less extreme warming occurs, and (4) C. quitensis relative growth rate is capable of reaching higher values than D. antarctica and P. annua, but only under extreme warming conditions.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".