Bibliographic record
Abstract
Temperate-breeding Canada geese (Branta canadensis maxima) were once extirpated from much of their native range in North America. Extensive reintroduction and management efforts have been incredibly successful in restoring Canada goose populations. Canada goose abundance has increased to historic levels, providing social, ecological, and economic value. However, human-goose conflict including reduced water quality, damaged landscape aesthetics, crop depredation, and safety concerns related to aircraft strikes are costs associated with Canada geese. The adaptability of geese to urban areas creates novel problems that traditional wildlife management actions may not fully address. Increasing human-goose conflict in Iowa’s urban areas led to a partnership between the Iowa Department of Natural Resources and Iowa State University to examine ecology of Canada geese in urban settings. Our research objectives were to 1) evaluate movement and harvest susceptibility during the special September and regular goose hunting seasons of Canada geese captured in urban areas and compare to movement and susceptibility of geese captured in rural locations where the goose-hunting season is closed, and 2) estimate annual survival and recovery rates for Canada geese banded in urban and rural areas in Iowa using three-age-class joint live-dead band recovery models.\nWe investigated movement ecology of Canada geese nesting at urban and rural sites in Iowa during the 2018-2019 and 2019-2020 Mississippi Flyway Canada goose hunting season frameworks. We captured Canada geese during brood rearing and marked adult females with a neck-mounted GPS-GSM transmitter in 2018 (n=30 urban, n=15 rural) and 2019 (n=15 urban, n=11 rural). Susceptibility to hunter harvest, or the proportion of locations geese were in areas available to hunters, was lower for urban geese (0.07 [95% CI: 0.04-0.13]) than rural geese (0.56 [95% CI: 0.34-0.76]). However, home range area was similar for urban and rural geese, and decreased in size from autumn to late winter. Urban geese were more likely to select developed areas and less likely to select wetlands than rural geese. Additionally, urban geese had higher selection of agricultural fields located inside municipal city limits than agricultural fields outside city limits.\nWe estimated survival, dead recovery rates, live recapture rates, and fidelity for Canada geese banded in Iowa 1999-2019 using Burnham joint live-dead models in program MARK via RMark. Model covariates included goose age (adult, subadult, juvenile), banding site (urban or rural), time (year as a factor), Time (trend over years), harvest regulation index, and winter severity index. The most parsimonious model indicated interactive effects of age, banding site, and trend over time for survival and dead recovery rate parameters. Adult survival was relatively constant and did not differ for geese banded in urban (0.75 [range: 0.60-0.92]) or rural (0.75 [range: 0.66-0.82]) areas. Juvenile survival in urban areas tended to be lower than in rural areas, and dead recovery rates were higher for urban juveniles during liberalization of harvest regulations. Subadults had higher survival in urban areas, although survival decreased and dead recovery rates increased.\nAdult Canada geese breeding in urban areas had similar survival and were recovered at similar rates as rural adults despite lower availability of urban adult geese to hunters. Thus, despite lower susceptibility, geese using urban areas contribute considerably to harvest. Opportunity exists to evaluate further liberalization of harvest regulations around large metropolitan areas and increased susceptibility of urban geese using early seasons, improved hunter access to urban agricultural fields, and expanded urban Canada goose management zones. Further management actions in addition to increasing harvest opportunity will likely be required to achieve goals.
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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 | 0.000 |
| 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 | 0.000 | 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".