Over-summering as a risk effect reducing population growth in a long-distance migrant shorebird
Bibliographic record
Abstract
That anti-predator behavior can have large demographic consequences (called risk effects) is theoretically well-founded and experimentally supported. Here we investigate whether this mechanism could be contributing to population declines reported over recent decades for many shorebird species, especially long-distance migrants. Sandpipers are known to have adjusted behavioral and morphological traits to counter the migratory danger posed by the increase in abundance of an important predator, the Peregrine Falcon (Falco peregrinus), ongoing steadily since the mid-1970s. Individuals in some shorebird species skip migration and breeding (over-summer), remaining instead on or near non-breeding areas. Over-summering can be considered an anti-predator tactic because it avoids all exposure to predators during migration, though at the expense of a foregone breeding season. We hypothesize that over-summering by the Semipalmated Sandpiper (Calidris pusilla) has increased during recent decades as migration became more dangerous. A stage-structured matrix population model based on survival rates measured in Perú 2011–2017 indicates that Semipalmated Sandpiper population growth is negative at current over-summering levels (adults 19%, yearlings 28%). A substantial proportion of the large reduction in their numbers since 1980 could theoretically be accounted for if over-summering levels rose to this level after ~1980. Though good data are scanty, the historical level of over-summering appears to have been lower. The powerful ecological effects of apex predators have been recognized in many systems, but to date the recovery of falcon populations has not been considered as a possible factor in shorebird declines. Closer scrutiny of this hypothesis is warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.003 | 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 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".