Habitat suitability or female availability? What influences males’ home-range size in a neotropical montane lizard?
Bibliographic record
Abstract
In many species, the shape, size, and location of home ranges depend on the spatial positioning of resources. Therefore, evaluating the resources and conditions related to the space use of individuals can provide crucial information on the species’ ecology and sociobiology. In this study, we evaluated factors shaping the use of space by the lizard Tropidurus montanus M.T. Rodrigues, 1987 and assessed how the distribution of resources can affect the size of the home range and how the quality of the male's home range can influence the number of associated females. We hypothesized that ( i) males with a larger body size would have a higher-quality home range, and ( ii) there would be a positive relationship between the home-range size and home-range quality of males and the number of associated females. Our results suggest that males, females, and juveniles adopt different strategies. While females and juveniles have relatively small home ranges located in more suitable locations, males invest in larger home ranges, including in lower-quality habitat patches. Our results suggest that males increase their home ranges to incorporate resources females prefer, enlarging the number of females in their harems.
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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 | 0.001 |
| 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) | 0.002 | 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".