Microhabitat separation during winter among sympatric giant pandas, red pandas, and tufted deer: the effects of diet, body size, and energy metabolism
Bibliographic record
Abstract
The giant panda (Ailuropoda melanoleuca (David, 1869)), red panda (Ailurus fulgens F.G. Cuvier, 1825), and tufted deer (Elaphodus cephalophus Milne-Edwards, 1872) are endemic to the Himalayan Hengduan Mountains; the red panda extends into India, Burma, Bhutan, and Nepal, and the tufted deer extends marginally into Burma, while the giant panda is endemic to China. In Sichuan Province, uniquely, all three species occur sympatrically. We investigated microhabitat characteristics at 150 fecal-group sites from November 2002 to March 2003 to improve understanding of microhabitat separation among the three species at the Fengtongzhai Nature Reserve, Baoxing County, Sichuan Province, People's Republic of China. Density and height of bamboo were greater in the giant and red pandas' micro habitats than in those of the tufted deer. The red panda preferred microhabitats with greater tree-stump density, smaller trees, and shorter fallen log dispersion distance than the other two species. Tufted deer often occurred at sites with greater shrub density and herb cover and more open land with poorer concealment conditions than sites where the two panda species occurred. Both pandas' microhabitats were mostly concentrated on the upper hillside, unlike those of the tufted deer. The giant panda preferred microhabitats with a gentler slope and lower density of fallen logs. Selection of specific microhabitats by each species is an ecological adaptation dependent on behavior linked to its diet, body size, energy metabolism, and other factors. Microhabitat separation among these species reflects the integrated effects of their differences in diet, body size, and energy metabolism, which could facilitate their successful coexistence.
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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) | 0.000 | 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 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".