Thermal influences on summer habitat use by Western Rattlesnakes (Crotalus Oreganus) in British Columbia
Bibliographic record
Abstract
The importance of thermal features to habitat selection by terrestrial ectotherms such as reptiles has been well documented, but rarely has it been considered in larger-scale analyses of habitat use and selection, such as those routinely conducted using more-standard habitat features such as vegetation types and physical structure. Selection of habitat based on thermal attributes may be of particular importance for ectothermic species, especially in colder climates. In British Columbia, Canada, Western Rattlesnakes ( Crotalus oreganus) reach their northern limits. While commonly associated with low-elevation grasslands and open Ponderosa pine habitats, recent work indicates that some populations of these animals may use higher-elevation Douglas-fir forests. The reasons and implications for this strik ing contrast of habitat use patterns by these animals was the subject of this thesis. I investigated the reason(s) for this phenomenon by monitoring the migratory movements of 35 snakes away from 10 di fferent den sites, and comparing it to thermal landscape GIS maps generated for different periods of the active season. My work confirmed that dichotomous habitat use by denning populations of these snakes occurs throughout much of their range, and rattlesnakes in this region can no longer be strictly associated with grassland habitat. I found that snakes utilizing the higher-elevation forests not only moved relatively further during the course of their annual migrations, but were also more likely to use warmer areas of the landscape during their annual migration. In addition to thermal benefits, prey availability and/or outbreeding may be at least partially responsible for these patterns, but at this time there is limited data to test these alternative hypotheses. Regardless, snakes utilizing the higher-elevation forests had better body condition, indicating a definite advantage to this strategy . On a smaller scale, thermoregulatory behaviours appear to be less constrained by thermal factors in forest habitats, potentially allowing forest snakes increased time for\nhunting and travelling. Insight into these and other behavioural differences between neighbouring rattlesnake populations will allow managers to tailor management strategies to specific dens. Finally, the local and landscape scale patterns I detected have obvious repercussions for snakes in the event climate change produces shifting ecosystem boundaries and thermal regimes.
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 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".