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Record W7083286891 · doi:10.1093/jue/juaf014

Attraction to birdseed by non-target wildlife and implications for management of urban coyotes (<i>Canis latrans</i>)

2025· article· en· W7083286891 on OpenAlexafffundabout

Bibliographic record

VenueJournal of Urban Ecology · 2025
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAttractionWildlifeMammalHuman–wildlife conflictPredationRodentCharadriiformesUrban ecology

Abstract

fetched live from OpenAlex

Abstract Conflicts between humans and coyotes are increasing in urban areas across North America and often stem from access to anthropogenic food. Birdseed is an abundant, but potentially underappreciated, source of anthropogenic food that may attract coyotes (Canis latrans) and their prey to residential yards. This attraction could worsen conflict with urban coyotes via food conditioning that increases aggressive behavior, reductions in body condition that increase dependency on human resources, and exposure to parasites shared by coyotes and their rodent prey, particularly Echinococcus multilocularis, an emerging zoonotic tapeworm. We explored how birdseed that is inadvertently spilled beneath feeders potentially attracts coyotes and mouse-sized rodents in 43 residential yards near urban greenspaces in Edmonton, Canada. We used a before-after control-impact (BACI) study design to test whether mammal attraction is reduced by adding seed hoops to collect spilled seed. Coyotes and rodents visited bird feeders in most yards, but seed hoops did not significantly decrease the detection rates of either group, perhaps owing to our short, autumnal study period and the locations of our study sites. Coyotes tended to visit feeders that provided sunflower seeds over mixed seed. Our results suggest that individuals who feed birds can discourage coyotes by providing seeds that are less palatable to coyotes. Logic and much other research suggest that coyotes will be less attracted to sites where all forms of anthropogenic food are removed or secured.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.802
Threshold uncertainty score0.314

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.245
Teacher spread0.236 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2025
Admission routes3
Has abstractyes

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