Social structure mediates environmental effects on group size in an obligate cooperative breeder,<i>Suricata suricatta</i>
Bibliographic record
Abstract
Population dynamics in group-living species can be strongly affected both by features of sociality per se and by resultant population structure. To develop a mechanistic understanding of population dynamics in highly social species we need to investigate how processes within groups, processes linking groups, and external drivers act and interact to produce observed patterns. We model social group dynamics in cooperatively breeding meerkats, Suricata suricatta, paying attention to local demographic as well as dispersal processes. We use generalized additive models to describe the influence of group size, population density, and environmental conditions on demographic rates for each sex and stage, and we combine these models into predictive and individual-based simulation models of group dynamics. Short-term predictions of expected group size and simulated group trajectories over the longer term agree well with observations. Group dynamics are characterized by slow increases during the breeding season and relatively sharp declines during the pre-breeding season, particularly after dry years. We examine the demographic mechanisms responsible for environmental dependence. While individuals appear more prone to emigrate after dry years, seasons of low rainfall also cause reductions in reproductive output that produce adult-biased age distributions in the following dispersal season. Adult subordinates are much more likely to disperse or be evicted than immature individuals, and demographic structure thus contributes to crashes in group size. Our results demonstrate the role of social structure in characterizing a population's response to environmental variation. We discuss the implications of our findings for the population dynamics of cooperative breeders and population dynamics generally.
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How this classification was reachedexpand
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) | 0.001 | 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 teacher head, 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".