El tamaño del ámbito hogareño y el uso de hábitat de la zorra gris (Urocyon cinereoargenteus) en un bosque templado de Durango, México
Bibliographic record
Abstract
Introduction: The gray fox ( Urocyon cinereoargenteus ) is distributed throughout Mexico, and yet there is little information about its life history and behavioral ecology. Basic knowledge about losses in distribution, preferred habitat features, and home range size are badly needed. This study describes the use of habitat and home range size of gray fox inhabiting the temperate forests in the La Michilla Biosphere Reserve, Durango, and makes comparisons with these features as described for this species in the United States of America and in Canada. Methodology: Radio-collars were attached to six adult foxes. They were monitored using radiotelemetry and triangulation of radio fixes. Intensive tracking involved hourly locations over 24 hr periods. Day and night time fixes were analyzed separately. Different seasons of the year were also sampled. Locations of each individual were transferred to maps, and 95% of locations were used calculate minimum convex polygons for home range estimates. Habitat usage was determined with a vegetation map of the area. Results: Our gray foxes exhibited an average home range size of 135 hectares ( n = 6). Males averaged 90 ha ( n = 4), and females averaged 224 ha ( n = 2). Females averaged larger range sizes at all seasons of the year. There was significant seasonal variation in home range size ( P < 0.001). Seven habitats were used by the foxes, and this usage pattern was significantly heterogeneous ( P < 0.001). They preferred pine-oak forests while grassland with pine-oak regeneration and crop areas were less used. Discussion and conclusions: The home range size and habitat use found in this study in Durango does not differ significantly from those reported by other studies elsewhere in North American temperate forests. We intend to continue marking and monitoring more individuals in our study area in the future, and this should increase the reliability of the information reported here. Key words: canid, carnivore, gray fox, home range, mesopredator, Mexico, mixed forests, radiotelemetry, Sierra Madre Occidental.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".