Landscapes, habitat, and migratory behaviour: what drives the summer movements of a Northern viper?
Bibliographic record
Abstract
Studies on movement behaviour and habitat use are central to understanding the ecology of migratory animals and play an important role in the conservation and management of these species. However, individuals’ spatial ecology can vary substantially, and failing to understand differences within or between populations may be problematic. In British Columbia, Canada, where Western Rattlesnakes reach their northern range limit, individuals undertake seasonal migrations between communal hibernacula and summer hunting grounds. Western Rattlesnakes commonly are associated with low-elevation grasslands and open Ponderosa pine habitats; however, recent work has shown that some animals undertake longer-distance migrations into higher-elevation Douglas-fir forests. To further investigate multi-phenotypic migratory tactics and habitat use, we compiled all available raw data from radio-telemetry studies conducted on adult males ( n = 139) between 2005 and 2019 from nine study sites across the Canadian range of Western Rattlesnakes. We quantify variation in migration distance, timing, altitudinal migration, home range sizes, and destination habitats used across our sample, and we use a linear mixed-modelling approach to assess potential drivers of long-distance migration. On average, snakes migrated 1364 ± 781 m (ranging from 105 m to 3832 m) from their overwintering dens. Migratory distance differed significantly between sites and was higher among individuals using forests as their migratory destination, yet within-habitat variation was high, suggesting a continuum of migratory phenotypes. Migratory distance was best predicted by two top models: terrain and combined effects (including terrain, physiology, and vegetation factors). Even these top-performing models, however, left much of the variation in migratory distance unexplained ( r s = 0.65 and 0.64 respectively based on k-fold cross-validation where k = 10), suggesting other factors not measured here, such as genetics and prey quality, may also be contributing. Overall, this study provides critical knowledge on the movement ecology of a far-ranging reptile with implications for the conservation and management of the species in the far north where seasonal movements are commonplace. Our results shed light on some drivers of multi-phenotypic migration in a taxonomic group where this phenomenon has largely been unstudied, while contributing more broadly to a growing body of literature on migratory variation in animals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".