Behavioral adaptations of scatterhoarders to seasonal flooding
Bibliographic record
Abstract
Scatterhoarder responses to factors that influence stored food (i.e., flooding) is important given the strong reliance on hoarded food for survival. We examined how eastern gray squirrels ( Sciurus carolinensis, Gmelin 1778) have adapted to a seasonally flooded ecosystem in Alabama. Our study area was dry September–November and flooded the rest of the year. We predicted squirrels would respond to flooding by storing food in areas that stay dry during winter, seasonally shifting to dry habitat, or decreasing the amount of hard mast in their winter diet. We also examined previously reported survival differences between the dry and flooded seasons. During the dry season, 72% of acorns were buried in areas that later flooded. Habitat use did not change significantly during the flooded and dry seasons; however, squirrels used habitat that stayed dry during flooding to a greater degree during non-flood seasons. The amount of hard mast in the diet did not change significantly between the dry and flooded seasons. However, squirrels were more likely to die during the flooded season ( P = 0.02). We did not find any behavioral adaptations to seasonal flooding. Further research is needed to fully understand the effects of fluctuating environmental conditions on scatterhoarders.
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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 | 0.000 |
| 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 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".