Interacting effects of cold snaps, rain, and agriculture on the fledging success of a declining aerial insectivore
Bibliographic record
Abstract
Climate change predicts the increased frequency, duration, and intensity of inclement weather periods such as unseasonably low temperatures (i.e., cold snaps) and prolonged precipitation. Many migratory species have advanced the phenology of important life history stages and, as a result, are likely to be exposed to these periods of inclement spring weather more often, therefore risking reduced fitness and population growth. For declining avian species, including aerial insectivores, anthropogenic landscape changes such as agricultural intensification are another driver of population declines. These landscape changes may affect the foraging ability of food provisioning parents and reduce the survival of nestlings exposed to inclement weather through, for example, pesticide exposure impairing thermoregulation and punctual anorexia. Breeding in agro-intensive landscapes may therefore exacerbate the negative effects of inclement weather under climate change. We observed that a significant reduction in the availability of insect prey occurred when daily maximum temperatures fell below 18.3°C, and thereby defined any day when the maximum temperature fell below this value as a day witnessing a cold snap. We then combined daily information on the occurrence of cold snaps and measures of precipitation to assess their impact on the fledging success of Tree Swallows (Tachycineta bicolor) occupying a nest box system placed across a gradient of agricultural intensification. Estimated fledging success of this declining aerial insectivore was 36.2% lower for broods experiencing 4 cold-snap days during the 12 days post-hatching period versus broods experiencing none, and this relationship was worsened when facing more precipitation. We further found that the overall negative effects of a brood experiencing periods of inclement weather was exacerbated in more agro-intensive landscapes. Our results indicate that two of the primary hypothesized drivers of many avian population declines may interact to further increase the rate of declines in certain landscape contexts.
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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 | 0.000 |
| 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 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".