Fecal DNA metabarcoding helps characterize the Canada jay’s diet and confirms its reliance on stored food for winter survival and breeding
Bibliographic record
Abstract
Accurately determining the diet of wild animals can be challenging if food items are small, visible only briefly, or rendered visually unidentifiable in the digestive system. In some food caching species, an additional challenge is determining whether consumed diet items have been previously stored or are fresh. The Canada jay (Perisoreus canadensis) is a generalist resident of North American boreal and subalpine forests with anatomical and behavioural adaptations allowing it to make thousands of arboreal food caches in summer and fall that are presumably responsible for its high winter survival and late winter/early spring breeding. We used DNA fecal metabarcoding to obtain novel information on nestling diets and compiled a dataset of 662 published and unpublished direct observations or stomach contents identifications of natural foods consumed by Canada jays throughout the year. We then used detailed natural history information to make informed decisions on whether each item identified to species in the diets of winter adults and nestlings was best characterized as 'likely cached', 'likely fresh' (i.e., was available as a non-cached item when it appeared in a jay's feces or stomach), or 'either possible'. Of the 87 food items consumed by adults in the winter, 39% were classified as 'likely cached' and 6% were deemed to be 'likely fresh'. For nestlings, 29% of 125 food items identified to species were 'likely cached' and 38% were 'likely fresh'. Our results support both the indispensability of cached food for Canada jay winter survival and previous suggestions that cached food is important for late winter/early spring breeding. Our work highlights the value of combining metabarcoding, stomach contents analysis, and direct observations to determine the cached vs. non-cached origins of consumed food items and the identity of food caches, some of which could be especially vulnerable to degradation through climate change.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".