Constraints on range expansion of introduced red squirrels (<i>Tamiasciurus hudsonicus</i>) in an island ecosystem
Bibliographic record
Abstract
Factors that limit the range expansion of introduced species can offer insights into the basic ecology of these species and inform conservation of associated endemic species. North American red squirrels (Tamiasciurus hudsonicus (Erxleben, 1777)) were recently introduced to the island of Newfoundland, Canada, where they have been implicated in the decline of two endemic bird subspecies. During the summers of 2016 (following conifer masting) and 2017 (following nonmasting), we conducted surveys with 1960 point counts and playback to assess red squirrel distribution and habitat use across a 257 km2 montane landscape in western Newfoundland. We used generalized additive models with stepwise model selection to assess the relationship between land cover and red squirrel occurrence each summer. Red squirrels were most common at low elevations and were not detected at elevations above ∼500 m. Their occurrence was negatively associated with the presence of water, coniferous scrub, and 10- to 30-year-old fir–spruce but positively associated with the presence of 30- to 70-year-old fir–spruce and >70-year-old fir. Red squirrel presence was related to more land cover variables in 2016, after a masting year. The absence of red squirrels from forests at higher elevations apparently resulted from lack of suitable habitat rather than incomplete range expansion. Climate- or silviculture-induced changes in vegetation may alter mid- and upper-elevation habitat suitability.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".