Partial Altitudinal Migration of a Himalayan Forest Pheasant
Bibliographic record
Abstract
BACKGROUND: Altitudinal migration systems are poorly understood. Recent advances in animal telemetry which enables tracking of migrants across their annual cycles will help illustrate unknown migration patterns and test existing hypotheses. Using telemetry, we show the existence of a complex partial altitudinal migration system in the Himalayas and discuss our findings to help better understand partial and altitudinal migration. METHODOLOGY/PRINCIPAL FINDINGS: We used GPS/accelerometer tags to monitor the migration of Satyr tragopan (Tragopan satyra) in the Bhutan Himalayas. We tagged 38 birds from 2009 - 2011 and found that tragopans are partially migratory. Fall migration lasted from the 3(rd) week of September till the 3(rd) week of November with migrants traveling distances ranging from 1.25 km to 13.5 km over 1 to 32 days. Snowfall did not influence the onset of migration. Return migration started by the 1(st) week of March and lasted until the 1(st) week of April. Individuals returned within 4 to 10 days and displayed site fidelity. One bird switched from being a migrant to a non-migrant. Tragopans displayed three main migration patterns: 1) crossing multiple mountains; 2) descending/ascending longitudinally; 3) moving higher up in winter and lower down in summer. More females migrated than males; but, within males, body size was not a factor for predicting migrants. CONCLUSIONS/SIGNIFICANCE: Our observations of migrants traversing over multiple mountain ridges and even of others climbing to higher elevations is novel. We support the need for existing hypotheses to consider how best to explain inter- as well as intra-sexual differences. Most importantly, having shown that the patterns of an altitudinal migration system are complex and not a simple up and down slope movement, we hope our findings will influence the way altitudinal migrations are perceived and thereby contribute to a better understanding of how species may respond to climate change.
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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".