Coyote (<i>Canis latrans</i>) Macronutrient Consumption and Diet Relative to Seasonality and Urbanization
Bibliographic record
Abstract
ABSTRACT Diet selection informs the health, fitness, and behavior of wild predators. Due to assumptions that vertebrate prey contains similar compositions of macronutrients (i.e., protein, carbohydrates, and lipids), whole prey items traditionally define carnivore diets. However, increasing evidence suggests that prey differ in terms of their macronutrient compositions, particularly relative to body size. Furthermore, omnivorous predators, like coyotes ( Canis latrans ), integrate both prey and nonprey diet items whose macronutrient compositions vary. This is particularly important in urbanized systems, which introduce or alter the distributions of prey (e.g., domestic pets) and nonprey (e.g., ornamental plants) foods in ways that contribute to carnivore diet selection and human–wildlife coexistence. We assessed the macronutrient composition of coyote diets seasonally and relative to urbanization in the Phoenix Metropolitan Area, AZ, USA. We collected coyote scats in the field and assessed their macronutrient compositions using values gathered from the literature, as well as the volumetric composition of diet items found in coyote scats. We then assessed the macronutrient composition of coyote diets in geometric space using the geometric framework of nutrition. We observed that the macronutrient composition of coyote diets was similar between moderately and less urbanized sites, particularly in the spring–summer season. However, coyote macronutrient consumption differed seasonally, with coyotes eating more nonprotein energy relative to protein energy when carbohydrate‐rich mesquite ( Prosopis spp.) was more available in the fall–winter. Our results suggest that the seasonal availability and macronutrient composition of foods contribute to coyote diets. Macronutrients directly translate to energy and subsequent animal physiology and behavior. Our findings therefore advance our understanding of coyote behavior, particularly in ways that support human–wildlife management in anthropogenic areas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".