Fledgling production and population trends in Finnish common eiders (Somateria mollissima mollissima) — evidence for density dependence
Bibliographic record
Abstract
We present a 57-year time series of a common eider, Somateria mollissima mollissima (L., 1758), population from one of the core monitoring areas in the Baltic Sea, the Söderskär bird sanctuary, Gulf of Finland. We applied permutation tests to inspect the relationships between breeding parameters and population density. Of the parameters studied, only fledging rate (during a 34-year period) showed a significant negative relationship with population size, indicating density dependence. Furthermore, the fledging rate responded strongly to the population growth rate and to the rate of recruitment. Clutch size and duckling (downy young entering the water) rate did not show negative density dependence. Thus, losses during brood rearing seem to be the regulatory factor. The population decline at Söderskär is similar to those recorded in many other monitoring sites around the southern coast of Finland. Compared with data from more productive sea districts in northwestern Europe (Dutch Wadden Sea and Scottish North Sea), the Finnish fledging rates do not seem excessively bad. There are indications of viral infections playing an increasingly central role in duckling mortality, whereas adult female mortality has not been affected.
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 | 0.001 | 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 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".