Season and ambient air temperature influence the distribution of mites (<i>Proctophyllodes stylifer</i>) across the wings of blue tits (<i>Parus caeruleus</i>)
Bibliographic record
Abstract
Changes in the distribution of the wing-feather mite Proctophyllodes stylifer (Buckholz 1869) on the flight feathers of blue tits (Parus caeruleus) were studied throughout the seasons and in relation to ambient air temperature at three combinations of study sites (Lancashire, West Midlands, and South Midlands). We tested the hypotheses that the distribution of mites is influenced in part by season and ambient air temperature. In the winter months mites clustered predominantly on the tertiary feathers, whereas in late spring, summer, and autumn, mite-infestation scores were higher on the proximal primary and secondary feathers. Three approaches were employed to determine whether this seasonal redistribution of mites arose as a response to changes in microclimate, probably ambient air temperature, rather than to season per se. Firstly, meteorological data for the Lancashire study sites, and our own monitoring of the precise air temperature at the time of handling and inspection at the West Midlands study sites, enabled us to establish a link between distribution pattern and ambient temperature. Secondly, limited observations on the distribution of mites on birds recaptured when ambient air temperatures differed by 5°C or more between first and second nettings, one temperature being below 10°C and the other above, supported the idea that the change in distribution was associated with air temperature. Finally, the results of a small experiment in which heavily infested birds caught on a day when air temperatures ranged from 9 to 11°C were taken indoors and temporarily subjected to a higher ambient air temperature (20 min) prior to re-inspection and release also confirmed that mite movement was associated with the temperature of their environment. We conclude that the seasonal changes in distribution were driven by microclimatic changes, in part by temperature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".