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Record W7036423228

Assessment of resident Canada goose management in Kansas

2021· dissertation· en· W7036423228 on OpenAlexaboutno aff

Bibliographic record

VenueK-State Research Exchange (Kansas State University) · 2021
Typedissertation
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGooseWaterfowlWildlife managementCensusFishing
DOInot available

Abstract

fetched live from OpenAlex

Resident Canada geese (Branta canadensis, geese nesting in the conterminous United States) was one of the many wildlife species declining by the early 1900s due to large-scale human disturbance (e.g., overharvest and habitat destruction). After decades without recognized breeding populations, many thought resident Canada geese were extinct in Kansas and the rest of the United States. Today, certain populations of resident Canada geese are so abundant they can be a nuisance; especially during spring breeding season. Resident Canada geese provide intrinsic value to Kansans as well as economic value through hunting licenses, travel, lodging, and taxes leveed on guns and ammunition. My goal was to address information gaps necessary to make science-based management decisions for resident Canada geese in Kansas. My objective for the first chapter was to determine the effect of translocation on urban-banded nuisance geese. My objective for the second chapter was to assess potential changes to the statewide spring breeding population survey for nesting geese in Kansas, to reduce bias and variation while maintaining or reducing survey cost. My objective for the third chapter was to determine the effect of latitude on age-class specific recovery patterns for resident Canada geese in the eastern tier of the Central Flyway. I estimated survival and recovery probabilities from hunter-harvested band recoveries for normal and translocated (i.e., urban geese relocated to rural areas) resident Canada geese. Annual survival differed between normal (S ̂ = 0.761, 95% CI 0.734-0.785) and translocated (S ̂ = 0.598, 95% CI 0.528-0.665) geese. Recovery probability also differed between normal and translocated adults (normal wild f ̂ = 0.074, 95% CI = 0.069-0.078; translocated f ̂ = 0.138, 95% CI = 0.120-0.158) and juveniles (normal wild f ̂ = 0.067, 95% CI = 0.059-0.075; translocated f ̂ = 0.250, 95% CI = 0.199-0.310). Recovery probability did not differ between status in the sub-adult age class (normal wild f ̂ = 0.126, 95% CI = 0.115-0.137; translocated f ̂ = 0.090, 95% CI = 0.055-0.144). Since 2014, Kansas Department of Wildlife and Parks has used fixed-wing aircraft to survey 160 1-mi² plots in 2 landcover strata (80 high and 80 medium strata) based on expected abundance of breeding Canada geese. I used survey data from 2019 to estimate change in bias of potential plot reallocation scenarios focusing on inter-plot count variation. I simulated design scenarios by reallocating plots in groups of 10 (e.g., 90 medium, 70 high). I simulated each scenario 100 times and calculated density and associated standard deviation, 90% confidence intervals, and coefficient of variation (CV) for each iteration. The top-ranked survey design based on the greatest reduction in bias predicted reallocating 40 medium stratum plots to the high strata would be the most effective method to increase statistical power and reduce coefficient of variation. Finally, I investigated the effects of banding latitude (i.e., banding state) and age-class on geospatial recovery patterns of resident Canada geese in the eastern-tier states of the Central Flyway, 2012–2019. I used optimized hot spot analyses and inverse distance weighting to measure how recoveries of sub-adult and adult geese differed spatially as insight into latitudinal effects of molt migration. Sub-adult geese from southern-banding states were recovered disproportionately at more northerly latitudes than sub-adult geese from northern banding states. Adult geese were disproportionately recovered in their respective banding state. These results will be used to inform the Kansas Department of Wildlife and Parks revision of the state resident Canada goose management plan.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.112

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.027
GPT teacher head0.288
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractno

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