Choice of foraging habitat by northern flickers reflects changes in availability of their ant prey linked to ambient temperature
Bibliographic record
Abstract
Foraging theory suggests animals should prefer habitats with a greater density of prey, but few have investigated whether birds change foraging habitats according to short-term changes in prey abundance caused by weather. We studied a woodpecker, the northern flicker (Colaptes auratus), in which the diet is composed mainly of ants collected on the ground surface. We measured the surface density of the ant prey in 1-m2 quadrats placed in 2 habitat types that had different thermal properties: open grassland and forest. The density of ants varied according to year of the study, habitat type, date during the summer, and time of day and was strongly associated with ambient temperature. In the shaded forest habitat, ant density increased linearly with air temperatures between 6 and 28 °C. In contrast, the surface activity of ants in the open habitat exposed to sun began to decline once ground surface temperatures reached 26 °C. Ant densities were higher in the open habitat than in the shade in relatively cold conditions but were higher in the shaded forest habitat when it was hot. Using radio telemetry, we recorded the habitat use of foraging flickers and found they shifted from foraging in the open when it was cold to foraging in shaded habitats when it was hot. Flickers tracked the density of their main prey on fine spatial and short temporal scales consistent with foraging theory.
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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".