Social networks in the guppy (
            <i>Poecilia reticulata</i>
            )

Croft, Darren P.; Krause, Jens; James, Richard

doi:10.1098/rsbl.2004.0206

Cited by 249 publications

(247 citation statements)

References 9 publications

(14 reference statements)

Supporting

Mentioning

241

Contrasting

Order By: Relevance

“…Interestingly, many other biological systems exhibit variation in connectivity, with right-skewed distributions such as exponential, geometric or power-law degree distributions [3,[47][48][49]. Previous work on social insects shows that some individuals are more interactive than others in honeybees [20] and rock ants [52], as in other animals [53][54][55]. However, little is known about the functional importance of these highly interactive individuals and what processes lead certain individuals to engage in more interactions than others.…”

Section: Discussionmentioning

confidence: 99%

The effect of individual variation on the structure and function of interaction networks in harvester ants

Pinter‐Wollman

Wollman

Guetz

et al. 2011

J. R. Soc. Interface.

123

119

View full text Add to dashboard Cite

Social insects exhibit coordinated behaviour without central control. Local interactions among individuals determine their behaviour and regulate the activity of the colony. Harvester ants are recruited for outside work, using networks of brief antennal contacts, in the nest chamber closest to the nest exit: the entrance chamber. Here, we combine empirical observations, image analysis and computer simulations to investigate the structure and function of the interaction network in the entrance chamber. Ant interactions were distributed heterogeneously in the chamber, with an interaction hot-spot at the entrance leading further into the nest. The distribution of the total interactions per ant followed a right-skewed distribution, indicating the presence of highly connected individuals. Numbers of ant encounters observed positively correlated with the duration of observation. Individuals varied in interaction frequency, even after accounting for the duration of observation. An ant's interaction frequency was explained by its path shape and location within the entrance chamber. Computer simulations demonstrate that variation among individuals in connectivity accelerates information flow to an extent equivalent to an increase in the total number of interactions. Individual variation in connectivity, arising from variation among ants in location and spatial behaviour, creates interaction centres, which may expedite information flow.

show abstract

Section: Discussionmentioning

confidence: 99%

The effect of individual variation on the structure and function of interaction networks in harvester ants

Pinter‐Wollman

Wollman

Guetz

et al. 2011

J. R. Soc. Interface.

123

119

View full text Add to dashboard Cite

show abstract

“…Only females were used as they form the core of guppy shoals [31] and to reduce the confounding effect of sexual behaviour on association patterns. Shoals were kept in these tanks for 24 h before experiments began.…”

Section: Materials and Methods (A) Study Species And Husbandrymentioning

confidence: 99%

‘Selfish herds’ of guppies follow complex movement rules, but not when information is limited

Kimbell¹,

Morrell²

2015

Proc. R. Soc. B.

View full text Add to dashboard Cite

Under the threat of predation, animals can decrease their level of risk by moving towards other individuals to form compact groups. A significant body of theoretical work has proposed multiple movement rules, varying in complexity, which might underlie this process of aggregation. However, if and how animals use these rules to form compact groups is still not well understood, and how environmental factors affect the use of these rules even less so. Here, we evaluate the success of different movement rules, by comparing their predictions with the movement seen when shoals of guppies (Poecilia reticulata) form under the threat of predation. We repeated the experiment in a turbid environment to assess how the use of the movement rules changed when visual information is reduced. During a simulated predator attack, guppies in clear water used complex rules that took multiple neighbours into account, forming compact groups. In turbid water, the difference between all rule predictions and fish movement paths increased, particularly for complex rules, and the resulting shoals were more fragmented than in clear water. We conclude that guppies are able to use complex rules to form dense aggregations, but that environmental factors can limit their ability to do so.

show abstract

“…In population biology one also studies proximity and mobility networks of animals [16,31,101,143,150]; see Fig. 3.…”

Section: H Ecological Networkmentioning

confidence: 99%

Temporal networks

2012

View full text Add to dashboard Cite

A great variety of systems in nature, society and technology-from the web of sexual contacts to the Internet, from the nervous system to power grids-can be modeled as graphs of vertices coupled by edges. The network structure, describing how the graph is wired, helps us understand, predict and optimize the behavior of dynamical systems. In many cases, however, the edges are not continuously active. As an example, in networks of communication via email, text messages, or phone calls, edges represent sequences of instantaneous or practically instantaneous contacts. In some cases, edges are active for non-negligible periods of time: e.g., the proximity patterns of inpatients at hospitals can be represented by a graph where an edge between two individuals is on throughout the time they are at the same ward. Like network topology, the temporal structure of edge activations can affect dynamics of systems interacting through the network, from disease contagion on the network of patients to information diffusion over an e-mail network. In this review, we present the emergent field of temporal networks, and discuss methods for analyzing topological and temporal structure and models for elucidating their relation to the behavior of dynamical systems. In the light of traditional network theory, one can see this framework as moving the information of when things happen from the dynamical system on the network, to the network itself. Since fundamental properties, such as the transitivity of edges, do not necessarily hold in temporal networks, many of these methods need to be quite different from those for static networks. The study of temporal networks is very interdisciplinary in nature. Reflecting this, even the object of study has many names

show abstract

Social networks in the guppy ( Poecilia reticulata )

Cited by 249 publications

References 9 publications

The effect of individual variation on the structure and function of interaction networks in harvester ants

The effect of individual variation on the structure and function of interaction networks in harvester ants

‘Selfish herds’ of guppies follow complex movement rules, but not when information is limited

Temporal networks

Contact Info

Product

Resources

About