Personality in a group living species : social information, collective movements and social decision-making
Bibliographic record
Abstract
movements.Leadership is the initiation of new directions of locomotion by one or more individuals, which are then followed by other group members (Krause et al. 2000). Social information useOne of the benefits of living in groups is that an individual has access to social information.Individuals might use two forms of information, either personal information, usually retrieved on a trial and error basis by interacting with the physical environment, or they might use information made available by other individuals, known as social information (Danchin et al. 2004;Dall et al. 2005).Social information use has been studied extensively in a wide variety of species and in many different contexts (Galef & Giraldeau 2001;Valone & Templeton 2002;Danchin et al. 2004;Valone 2007).Individuals use social information to decide with whom to mate (mate choice copying, Nordell & Valone 1998;Valone & Templeton 2002), where to breed (habitat copying, Danchin et al. 1998), where to forage (Drent & Swierstra 1977; Coolen et al. 2003), when to leave a food patch (Templeton & Giraldeau 1995, 1996), what food to eat (Galef 1990) and when to flee from a predator (Chivers & Smith 1998).Social information use indeed affects various important aspects of an individual's ecology, such as foraging, dispersal and space use (Seppänen et al. 2007).Despite a rich tradition of studies on social information use the relationship between animal personality and social information use is poorly studied.In this thesis I studied whether variation in personality traits is correlated with variation in the use of social information.That the value of social information might be different for 2 individuals in a group can be illustrated by a simple example.Consider a group of 3 individuals with individual a dominant over b and c, and individual b dominant over c.If individual b finds a food patch which can be monopolized this information is valuable for individual a, as it can displace individual b and take over the food patch.However, for individual c the exact same information is not valuable since it cannot use the information as it can not displace individual b and access the food.This illustrates that within a group of individuals the value of social information might differ between individuals.Despite this obvious example, there are few studies which take an individual approach to social information use and generally it is assumed that social information is equally valuable to each individual in a population and consequently most studies focus on the conditions under which an animal is expected to use social information (Galef & Giraldeau 2001;Danchin et al. 2004;Kendal et al. 2005;Valone 2007).In this thesis I studied the relationship between social information use and personality in several different contexts to test if variation in personality reflects differences in the use of social information.Maintenance of variation One of the major challenges in animal personality is to explain the evolution and maintenance of animal personality.Several (non-mutually exclusive) mechanisms have been suggested, including spatiotemporal variation in environmental conditions (Sih et al. 2003;Dall et al. 2004;Dingemanse et al. 2004;Smith & Blumstein 2008;Réale et al. 2010), differences in life-history trade-offs (Wolf et al. 2007;Gyuris et al. 2010; see also Biro & Stamps 2008;Réale et al. 2009) and sexual selection (Schuett et al. 2010).A fourth mechanism is negative frequency dependent selection (Wolf et al. 2008).
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".