PREDATION RISK FOR HOARY MARMOTS IN THE CHANGING CLIMATE OF WASHINGTON’S NORTH CASCADES
Bibliographic record
Abstract
Climatic changes can reduce habitat availability of high-elevation specialists such as the hoary marmot (Marmota caligata), a hibernating rodent of subalpine meadows and talus fields. Observed hoary marmot mean abundance in North Cascades National Park (NOCA) has declined by 74%, and though declines of other marmot populations have been attributed to increasing predation pressure, this relationship remains unexplored in NOCA. To examine the link between potential predators and hoary marmots in NOCA, I coupled surveys of hoary marmot vigilance behavior with estimates of predation risk based on predator diet composition and probability of use near hoary marmot colonies. We conducted 145 focal-animal surveys to determine the proportion of time hoary marmots spent vigilant. We surveyed 9,930 trap nights using 130 remote cameras and modeled predator occupancy using environmental covariates. We used genetic metabarcoding to identify predator and prey DNA in 413 scat samples. From camera traps and fecal DNA, we detected ten predator species in the study area, and we detected hoary marmots in the scats of five species. The proportion of observed hoary marmot predation was highest for coyotes (Canis latrans) (Χ2 = 31.78, p < 0.0001) at 50%. To our knowledge, we also report the first record of hoary marmots being consumed by Pacific martens (Martes caurina),which were also significant predators (proportion of observed consumption = 32%). Although I expected that predators with low-elevation habits would use sites with lower snow persistence, this prediction was supported only for coyotes, but not for other low-elevation predators. Combining probability of use estimates with observed hoary marmot consumption rates to develop a predation risk index, we found the risk was highest from Pacific martens (0.20) and lowest from Canada lynx (Lynx canadensis) (< 0.01). However, estimates of predation risk and human use of sites did not explain the variation in hoary marmot vigilance, despite hoary marmots allocating > 50% of their time to vigilance. Our findings of consumption of hoary marmots by predators are similar to other studies of imperiled marmot populations, highlighting the need to better understand the effect of climate-driven shifts in predator-prey ecology in NOCA.
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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 | 0.001 | 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".