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Record W2781403025 · doi:10.1139/cjz-2017-0246

Resource partitioning between kit foxes (<i>Vulpes macrotis</i>) and coyotes (<i>Canis latrans</i>): a comparison of historical and contemporary dietary overlap

2017· article· en· W2781403025 on OpenAlexvenueno aff
Paige Byerly, Robert C. Lonsinger, Eric M. Gese, Adam Kozlowski, Lisette P. Waits

Bibliographic record

VenueCanadian Journal of Zoology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
FundersU.S. Bureau of Land Management
KeywordsVulpesCanisBiologyPredationForagingGeneralist and specialist speciesEcologyZoologyPopulationSympatric speciationPredatorHabitat

Abstract

fetched live from OpenAlex

Range expansions by generalists can alter communities and introduce competitive pressures on native species. In the Great Basin Desert, USA, coyotes (Canis latrans Say, 1823) have colonized and are now sympatric with native kit foxes (Vulpes macrotis Merriam, 1888). Since both species have similar diets, dietary partitioning may facilitate coexistence. We analyzed coyote and kit fox diets, then compared our results to an earlier study. Because populations are dynamic, we expected that decreases in prey or increases in predator abundance could alter dietary patterns. We found no significant changes in population-level prey diversity for kit foxes or coyotes, but found high levels of dietary overlap between species. We did detect a significant decrease in the relative importance of leporids (family Leporidae) in the diets of both canids, but they remained important for coyotes. The relative importance of small mammals was greater for kit foxes than coyotes, but their importance had not changed significantly over time. We detected significant declines in prey diversity per sample (scat-level dietary diversity) for both canids, suggesting that during a foraging event, individuals may encounter less diverse prey now than historically. These findings suggested that kit foxes and coyotes were not limited by prey, despite high dietary overlap.

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 score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

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

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 head0.035
GPT teacher head0.246
Teacher spread0.212 · 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

Citations20
Published2017
Admission routes1
Has abstractyes

Explore more

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