Large and irregular population fluctuations in migratory Pacific ( <i>Calidris alpina pacifica</i> ) and Atlantic ( <i>C. a. hudsonica</i> ) dunlins are driven by density‐dependence and climatic factors
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Understanding the forces driving population dynamics is critical for species conservation and population management. For migratory birds, factors that regulate population abundance could come from effects experienced on breeding areas, wintering grounds, or during migration. We compiled survey data for Pacific and Atlantic subspecies of dunlins ( Calidris alpina pacifica and C. a. hudsonica ) from range‐wide Christmas bird counts (1975–2010), and investigated the influences on this population index of density‐dependence, falcon numbers, a set of seasonal environmental conditions during breeding, migration and non‐breeding periods, and large‐scale meteorological measures. For both sub‐species, numbers fluctuated irregularly, varying threefold over the survey period, with no long‐term upward or downward trend. Based on Royama's general model framework, the change in numbers between successive years for both sub‐species was negatively affected by the total count in the previous year (i.e., negative density‐dependence) and by the eastward component of storm movement during fall migration, with slower motion associated with higher population growth. The remaining environmental factors differed between the sub‐species (snowmelt date on the Pacific, temperature on the Atlantic) or acted in opposite directions (soil moisture). The directional effects of each of these factors are consistent with the biology of dunlin, and together they explain 67.4 (72.9 %) of the variation in the rate of change of Pacific (Atlantic) dunlin annual counts. Falcon numbers were not predictive, despite a tenfold increase in abundance, suggesting compensatory mortality. This study highlights directions for future studies, and provides a model for the analysis of other migratory species.
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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) | 0.000 | 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 it