Classifying the migration behaviors of pronghorn on their northern range
Bibliographic record
Abstract
ABSTRACT Migration functions as an adaptive strategy to improve fitness by allowing individuals to exploit spatiotemporal gradients of resources. Yet migration, especially among large ungulates, is increasingly threatened by human activities, making it necessary to understand variation in migratory behavior. We identified different movement strategies for pronghorn (Antilocapra americana) at the northern limit of the species’ range, and tested hypotheses for variation between migratory behaviors. From 2003–2010, we captured 185 female pronghorn across Alberta and Saskatchewan, Canada, and Montana, USA. We identified discrete migratory behaviors, including seasonal migration, facultative winter migration, potential post‐fawning migration, and the use of stopover sites. Fifty‐five percent of individuals undertook seasonal migrations, and we recorded the longest reported round‐trip migration for the species at 888 km. Some (22%) seasonal migrations included ≥1 stopover sites, with significantly greater use of stopovers during spring than fall. Migrants (34%) and residents (20%) undertook facultative winter migrations, with the majority (68%) undertaken by migrants. Additionally, 12% of individuals exhibited potential post‐fawning migrations. For each season, we estimated a suite of movement metrics and used multivariate statistics to compare movement similarities across migration behaviors. Correspondence analyses revealed 3 groupings of migration behavior. Spring migration was its own grouping, characterized by more sinuous and slower movements, consistent with the forage maturation hypothesis. Fall migration, facultative winter migration, and potential post‐fawning migration clustered in a single group that displayed linear, fast movements, consistent with being influenced by ecologically limited resources such as severe winters or predation avoidance. Lastly, spring and fall stopover sites were grouped together as a means to use high‐quality forage during migration, also consistent with the forage maturation hypothesis. At the northern periphery of pronghorn range, differences between migratory behaviors are influenced by various ecological factors, merit increased attention, and contribute to overall persistence. © 2018 The Wildlife Society.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".