Population Dynamics and Habitat Selection of Resident Urban Canada Geese (Branta canadensis) Scottsdale, AZ
Bibliographic record
Abstract
abstract: Populations of resident Canada geese (Branta canadensis) that nest and reside within the contiguous United States have increased at a rate of 7.9% per year to over 3.5 million over the last few decades. Enlarged population levels have resulted in conflicts between geese and humans, including property damage and human health and safety concerns. Noticeable growth of the population of Canada geese in the Indian Bend Wash area of Scottsdale, AZ has been observed in recent years sparking concern that this population will continue to grow at high rates as seen in other urban areas throughout North America. This study was initiated to determine the current population structure, distribution, and productivity of this population of resident geese. During the 2009 to 2010 post-breeding molt, 255 geese were captured and affixed with neck collars allowing individual identification. I conducted surveys from October 2008 to September 2010 and calculated weekly population estimates from mark recapture survey data using the Lincoln-Peterson method. Productivity was also investigated. Nesting was largely limited to one island within the study area, suggesting geese preferentially nest in insular areas to avoid human disturbance. Despite limited nesting opportunities, there was a significant population increase of 15 to 25% from 2009 to 2010 based on population estimates. Goose movement patterns indicate this population has a high level of site fidelity to nesting and molting areas, as has been found in other studies of resident Canada geese. I suggest that management should be implemented to 1) reduce the current population of resident geese through adult removal and 2) limit future recruitment into the population through control of reproduction and habitat modification.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".