Interactive effects of multiscale diversification practices on farmland bird stress
Bibliographic record
Abstract
Farmland diversification practices (i.e., methods used to produce food sustainably by enhancing biodiversity in cropping systems) are sometimes considered beneficial to both agriculture and biodiversity, but most studies of these practices rely on species richness, diversity, or abundance as a proxy for habitat quality. Biodiversity assessments may miss early clues that populations are imperiled when species presence does not imply persistence. Physiological stress indicators may help identify low-quality habitats before population declines occur. We explored how avian stress indicators respond to on-farm management practices and surrounding seminatural area (1-km radius) across 21 California strawberry farms. We examined whether commonly used biodiversity metrics correlate with stress responses in wild birds. We used ∼1000 blood and feather samples and body mass and wing chord measurements, mostly from passerines, to test the effects of diversification practices on four physiological stress indicators: heterophil to lymphocyte ratios (H:L), body condition, hematocrit values, and feather growth rates of individual birds. We then tested the relationship between physiological stress indicators and species richness, abundance, occurrence, and diversity derived from 285 bird point count surveys. After accounting for other biological drivers, landscape context mediated the effect of local farm management on H:L and body condition. Local diversification practices were associated with reduced individual stress in intensive agricultural landscapes but increased it in landscapes surrounded by relatively more seminatural area. Feathers grew more slowly in landscapes dominated by strawberry production, suggesting that nutritional condition was lower here than in landscapes with more crop types and seminatural areas. We found scant evidence that species richness, abundance, occurrence, or diversity metrics were correlated with the individual's physiological stress, suggesting that reliance on these metrics may obscure the impacts of management on species persistence. Our findings underscore the importance of considering landscape context when designing local management strategies to promote wildlife conservation.
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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".