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Record W1964130063 · doi:10.2181/036.045.0206

Burrowing Owl (<i>Athene cunicularia</i>) Habitat Associations in Agriculture Fields and along Canal Trails in Phoenix, Arizona

2014· article· en· W1964130063 on OpenAlexaboutno aff
Shaneen R. H. Beebe, Aaron B. Switalski, Heather L. Bateman, Kiril Hristovski

Bibliographic record

VenueJournal of the Arizona-Nevada Academy of Science · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsOccupancyHabitatGeographyLand coverEcologyUrbanizationPopulationLand useEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Burrowing Owls (Athene cunicularia) have experienced significant population declines over the last 100 years in parts of the United States and Canada. This decline may be associated with increasing urbanization and land-cover change; however, owls can occupy urbanized environments. To determine habitat selection in the southeast valley of Phoenix, Arizona, we conducted visual surveys for owls during summer 2011 and measured microhabitat and landscape characteristics in 23 agricultural fields (fields) and along 15 canal right-of-ways (trails). We estimated occupancy rate and detectability using Program MARK. We identified microhabitat selection to relate owl occurrence to landscape variables. Occupancy rate was 32% in both fields and trails and owls had greater detectability along trails. Burrowing Owl occurrence was similar in fields with varying agricultural stages (from undisturbed to harvested) and moisture conditions. Owl occupancy was positively associated with soil type and canal water presence, and occupancy decreased when developed landscape cover (e.g., roads and buildings) increased. These findings suggest that Burrowing Owls are able to live in urbanized environments below 40% developed land cover provided that water and suitable soils are available.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.023
Threshold uncertainty score0.314

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.223
Teacher spread0.214 · 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 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

Citations3
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Arizona-Nevada Academy of ScienceSame topicWildlife Ecology and ConservationFrench-language works237,207