Population fitness has a concave relationship with migration distance in Sanderlings
Bibliographic record
Abstract
In Focus: Reneerkens, J., Versluijs, T. S. L., Piersma, T., Alves, J. A., Boorman, M., Corse, C., … Lok, T. (2020). Low fitness at low latitudes: wintering in the tropics increases migratory delays and mortality rates in an Arctic breeding shorebird. Journal of Animal Ecology, 89, 691-703. A central question in migratory ecology has been to understand the fitness consequences of individual variation in migration distance among different species and populations. Reneerkens et al. (2020) investigated the demographic consequences of long-distance migration for Sanderlings Calidris alba, an Arctic-breeding species of sandpiper. Their study population has a remarkable geographic distribution with a breeding range that is concentrated in northeast Greenland and Ellesmere Island, Canada but a nonbreeding range that extends across 85° of latitude from Scotland to Namibia. The authors report on unexpected patterns of latitudinal variation in three demographic parameters: timing of passage on northward migration, probability of juvenile migration and apparent survival of adults. Sanderlings travelling 1,800-2,800 km to settle at north temperate sites during the nonbreeding season had earlier passage dates, and also higher probabilities of migration and apparent survival. In contrast, birds travelling 6,000-7,800 km to equatorial sites experienced later passage dates, delayed maturity and lower apparent survival. However, if Sanderlings migrated even farther and flew over 11,000 km to nonbreeding sites in Namibia, then their performance was restored to early passage dates and higher survival. Movement tracks from birds tagged with geolocators showed that birds wintering in Namibia make nonstop flights of 7,500 km that bypass West Africa during northward migration. Thus, all lines of evidence suggest that Sanderlings face adversity when spending the nonbreeding season at equatorial latitudes. Moreover, the central finding that components of fitness can have nonlinear relationships with migration distance is a novel discovery that leads to many additional questions. The new findings have broader implications for theoretical models of migration, and for understanding how different patterns of movements may arise or be maintained in migratory species.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".