Effects of climate variability on the temporal population dynamics of southern fulmars
Bibliographic record
Abstract
Ecological and population processes are affected by large-scale climatic fluctuations, and top predators such as seabirds can provide an integrative view on the consequences of environmental variability on ecosystems. Here, we examine the dynamics of a southern fulmar population in Antarctica over a 39-year period and evaluate the impact of environmental variability on the life history traits of this top predator species. Between 1963 and 2002, the number of breeding pairs fluctuated between seven and 53 in relation to variations in sea ice concentration, and increased overall (annual growth rate: 1·0035). Breeding performance tended to be lower in years with low sea ice concentration. The proportion of birds attempting to breed varied strongly from one year to the next despite the birds were alive, indicating strong environmental forcing on the decision to breed. The number of new local recruits and immigrants was correlated highly with the number of local breeders, and capture probabilities were positively related to the breeding population size. Local recruitment, number of local breeders and proportion of birds attempting to breed were lower when sea ice concentration during summer was low. Adult survival between 1964 and 2002 was on average 0·923 ± 0·006, and decreased during years with high sea surface temperature and low sea ice concentration. Modelled population growth rate, estimated using matrix models, of the population was 0·9728, a difference of 3·6% compared to the observed rate of increase. This discrepancy is due probably to the immigration rate (3 ± 3%). Demographic parameters were affected by sea ice concentration and sea surface temperature anomalies, probably through an impact on krill availability, the main prey of southern fulmars. During warm anomalies, birds skip breeding probably because the food availability was low and limiting for the highly energy demanding reproductive activities. We also emphasize that demographic parameters were very low during the period 1975-80 and showed a higher variability after 1980, which could be interpreted in the context of a regime shift. Our study indicates that the southern fulmar population dynamics may be very susceptible to environmental variability. Further long-lasting warm anomalies are likely to affect negatively their populations.
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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 | 0.001 |
| 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".