Range Expansion and Migration of Trumpeter Swans in North America: Relationship Between Summer and Winter Distributions
Bibliographic record
Abstract
Trumpeter Swans were extirpated from Ontario in the late 1800s and by the early 1900s, only three breeding populations remained, with most of the surviving birds in Alaska (Pacific Coast Population), fewer in Canada (Western Canada Population), and a population in the Greater Yellowstone area of the contiguous United States. The Ontario reintroduction program ended in 2006, and limited empirical analyses have been conducted since, hence, this paper examines the Ontario breeding distribution of TRUS (1991-2021) to see if there is evidence of density dependent range expansion in areas around the captive breeding release sites. To do this, I first quantified the seasonal distribution by grid cells count (2.96 km x 2.96 km) followed by kernel density mapping. Secondly, I assessed the occurrence and extent of short-stopping by calculating the average geographic location o sightings and the minimum distance between each wintering location and release sites. These drivers acted as independent variables for the regression model, and it was found that the R2 of 0.15 (Fstat = 1117.328, p<0.0001). The most important predictor in the model was distance to release sites (-0.225), followed closely by distance to winter sites (-0.205), in which they both had a negative relationship with the dependent variable. On the other hand, human population density had a positive relationship of 0.078 with the dependent variable. The results from this study confirmed that the Ontario breeding distribution of TRUS (1991-2020) shows evidence of density dependent range expansion in areas around captive breeding release sites, confirming short-stopping in winter as well.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".