Reality mining of animal social systems

Krause, Jens; Krause, Stefan; Arlinghaus, Robert; Psorakis, Ioannis; Roberts, Stephen; Rutz, Christian

doi:10.1016/j.tree.2013.06.002

Cited by 244 publications

(258 citation statements)

References 75 publications

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“…This 'bio-logging' allows remote reconstruction of behavior over large spatiotemporal extents, providing essential individual viewpoints, tracks, and life histories, and thus important ecological and evolutionary insights [9][10][11]. Image-based tracking, for example with video, is another tracking method that shows great potential in ecology.…”

Section: Glossarymentioning

confidence: 99%

Automated image-based tracking and its application in ecology

Dell

Bender²,

Branson

et al. 2014

Trends in Ecology & Evolution

433

481

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The behavior of individuals determines the strength and outcome of ecological interactions, which drive population, community, and ecosystem organization. Bio-logging, such as telemetry and animal-borne imaging, provides essential individual viewpoints, tracks, and life histories, but requires capture of individuals and is often impractical to scale. Recent developments in automated image-based tracking offers opportunities to remotely quantify and understand individual behavior at scales and resolutions not previously possible, providing an essential supplement to other tracking methodologies in ecology. Automated image-based tracking should continue to advance the field of ecology by enabling better understanding of the linkages between individual and higher-level ecological processes, via high-throughput quantitative analysis of complex ecological patterns and processes across scales, including analysis of environmental drivers. Measuring behaviorIndividual behavior (see Glossary) underlies almost all aspects of ecology [1][2][3][4][5]. Accurate and highly resolved behavioral data are therefore critical for obtaining a mechanistic and predictive understanding of ecological systems [5]. Historically, direct observation by trained biologists was used to quantify behavior [6,7]. However, the extent and resolution to which direct observations can be made is highly constrained [8] and the number of individuals that can be observed simultaneously is small. In addition, an exact record of events is not preserved, only the biologist's subjective account of them.Recent technological advances in tracking now make it possible to collect large amounts of highly precise and accurate behavioral data. For many organisms equipment can be attached that provide information about the Glossary Background subtraction: a method used by software to compare the current video frame with a stored picture of the background; any pixel of the current frame that is significantly different from the corresponding pixel in the background is likely to be associated with the body of an animal. Useful in situations where the background is unchanging, for example, when the surface of the background is rigid and lighting does not change. Behavior: the actions of individuals, often in response to stimuli. Behavior can involve movement of the individual's body through space, such as walking or chasing, or can occur while the animal is stationary, such as grooming or eating. Bio-logging: attachment or implantation of equipment to organisms to provide information about their identity, location, behavior, or physiology (e.g., global positioning systems, accelerometers, video cameras, telemetry tags). Ecological interaction: any interaction between an organism and its environment, or between two organisms (i.e., including interactions between conspecifics). Fingerprinting: a method used to identify unmarked individuals using natural variation in their physical and/or behavioral appearance. The method works by transforming the images of each individual ...

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Section: Glossarymentioning

confidence: 99%

Automated image-based tracking and its application in ecology

Dell

Bender²,

Branson

et al. 2014

Trends in Ecology & Evolution

433

481

View full text Add to dashboard Cite

show abstract

“…Given the weaknesses of traditional link creation approaches, Psorakis et al (2012) proposed a methodology that exploits key statistical properties of the data stream in order to reveal a temporal modular structure of gathering events that allows retrieving groups of connected individuals. The purposes of this study are to (i) highlight the frequently overlooked problems associated with the choice of the graph construction method, (ii) compare the different available methods and (iii) discuss which approach is most appropriate for time stamped detection data that are typical of those collected by many studies (Krause et al 2013). There is also the general problem of selecting both a temporal and a spatial resolution for our data.…”

Section: Communicated By D P Croftmentioning

confidence: 99%

“…PIT tags are a form of radio frequency identification (RFID) that allow automatic identification through the contactless transfer of data. RFID technology enables standardised data collection for large samples of individuals, which has broad applications for ornithological research (Garroway et al 2015), but see Gibbons and Andrews (2004), Krause et al (2013) and Smyth and Nebel (2013) for potential caveats of this technology. An antenna at a feeding station is used to interact with the electric circuit of the PIT tag via electromagnetic induction.…”

Section: Study Site and Data Collectionmentioning

confidence: 99%

Inferring social structure from temporal data

Psorakis

Voelkl

Garroway

et al. 2015

Behav Ecol Sociobiol

Self Cite

112

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Social network analysis has become a popular tool for characterising the social structure of populations. Animal social networks can be built either by observing individuals and defining links based on the occurrence of specific types of social interactions, or by linking individuals based on observations of physical proximity or group membership, given a certain behavioural activity. The latter approaches of discovering network structure require splitting the temporal observation stream into discrete events given an appropriate time resolution parameter. This process poses several non-trivial problems which have not received adequate attention so far. Here, using data from a study of passive integrated transponder (PIT)-tagged great tits Parus major, we discuss these problems, demonstrate how the choice of the extraction method and the temporal resolution parameter influence the appearance and properties of the retrieved network and suggest a modus operandi that minimises observer bias due to arbitrary parameter choice. Our results have important implications for all studies of social networks where associations are based on spatio-temporal proximity, and more generally for all studies where we seek to uncover the relationships amongst a population of individuals that are observed through a temporal data stream of appearance records.

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“…Both approaches have exploited the increasing availability of high resolution bio-logging technology to quantify how variation in host behaviour contributes to heterogeneity in pathogen transmission opportunities (Krause et al, 2013;White et al, 2017). Recent developments in network analytical approaches have included the development of a general multilayer network approach that considers multiple interdependent networks within the same analytical framework (Kivelä et al, 2014;De Domenico et al, 2016;Pilosof et al, 2017b).…”

Section: Introductionmentioning

confidence: 99%

Quantifying direct and indirect contacts for the potential transmission of infection between species using a multilayer contact network

Silk

Drewe

Delahay

et al. 2018

Behav.

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Detecting opportunities for between-species transmission of pathogens can be challenging, particularly if rare behaviours or environmental transmission are involved. We present a multilayer network framework to quantify transmission potential in multi-host systems, incorporating environmental transmission, by using empirical data on direct and indirect contacts between European badgers Meles meles and domestic cattle. We identify that indirect contacts via the environment at badger latrines on pasture are likely to be important for transmission within badger populations and between badgers and cattle. We also find a positive correlation between the role of individual badgers within the badger social network, and their role in the overall badger-cattle-environment network, suggesting that the same behavioural traits contribute to the role of individual badgers in within-and between-species transmission. These findings have implications for disease management interventions in this system, and our novel network approach can provide general insights into transmission in other multi-host disease systems.

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Reality mining of animal social systems

Cited by 244 publications

References 75 publications

Automated image-based tracking and its application in ecology

Automated image-based tracking and its application in ecology

Inferring social structure from temporal data

Quantifying direct and indirect contacts for the potential transmission of infection between species using a multilayer contact network

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