Conducting social network analysis with animal telemetry data: Applications and methods using spatsoc

Robitaille, Alec L.; Webber, Quinn M. R.; Wal, Eric Vander

doi:10.1111/2041-210x.13215

Cited by 68 publications

(74 citation statements)

References 37 publications

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“…Wildlife telemetry data can be a powerful tool for remotely detecting animal associations for use in network estimation, social network analysis and pathogen transmission modelling (Robitaille, Webber, & Vander Wal, 2019). However, regardless of study objective, variations in telemetry sampling effort can have a significant impact on the structure of subsequent contact networks.…”

Section: Discussionmentioning

confidence: 99%

Trade‐offs with telemetry‐derived contact networks for infectious disease studies in wildlife

2020

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Network analysis of infectious disease in wildlife can reveal traits or individuals critical to pathogen transmission and help inform disease management strategies. However, estimates of contact between animals are notoriously difficult to acquire. Researchers commonly use telemetry technologies to identify animal associations, but such data may have different sampling intervals and often captures a small subset of the population. The objectives of this study were to outline best practices for telemetry sampling in network studies of infectious disease by determining (a) the consequences of telemetry sampling on our ability to estimate network structure, (b) whether contact networks can be approximated using purely spatial contact definitions and (c) how wildlife spatial configurations may influence telemetry sampling requirements. We simulated individual movement trajectories for wildlife populations using a home range‐like movement model, creating full location datasets and corresponding ‘complete’ networks. To mimic telemetry data, we created ‘sample’ networks by subsampling the population (10%–100% of individuals) with a range of sampling intervals (every minute to every 3 days). We varied the definition of contact for sample networks, using either spatiotemporal or spatial overlap, and varied the spatial configuration of populations (random, lattice or clustered). To compare complete and sample networks, we calculated seven network metrics important for disease transmission and assessed mean ranked correlation coefficients and percent error between complete and sample network metrics. Telemetry sampling severely reduced our ability to calculate global node‐level network metrics, but had less impact on local and network‐level metrics. Even so, in populations with infrequent associations, high intensity telemetry sampling may still be necessary. Defining contact in terms of spatial overlap generally resulted in overly connected networks, but in some instances, could compensate for otherwise coarse telemetry data. By synthesizing movement and disease ecology with computational approaches, we characterized trade‐offs important for using wildlife telemetry data beyond ecological studies of individual movement, and found that careful use of telemetry data has the potential to inform network models. Thus, with informed application of telemetry data, we can make significant advances in leveraging its use for a better understanding and management of wildlife infectious disease.

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Section: Discussionmentioning

confidence: 99%

Trade‐offs with telemetry‐derived contact networks for infectious disease studies in wildlife

2020

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“…We used R package spatsoc (version 0.1.6, Robitaille, Webber, & Vander, ) in R version 1.1.383 (R Core Team, ) to generate proximity‐based social networks (PBSNs) from GPS telemetry data. We generated social networks for each herd in each season based on proximity of GPS fixes for individual caribou.…”

Section: Methodsmentioning

confidence: 99%

Space use and social association in a gregarious ungulate: Testing the conspecific attraction and resource dispersion hypotheses

Peignier

Webber

Koen

et al. 2019

Ecology and Evolution

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Animals use a variety of proximate cues to assess habitat quality when resources vary spatiotemporally. Two nonmutually exclusive strategies to assess habitat quality involve either direct assessment of landscape features or observation of social cues from conspecifics as a form of information transfer about forage resources. The conspecific attraction hypothesis proposes that individual space use is dependent on the distribution of conspecifics rather than the location of resource patches, whereas the resource dispersion hypothesis proposes that individual space use and social association are driven by the abundance and distribution of resources. We tested the conspecific attraction and the resource dispersion hypotheses as two nonmutually exclusive hypotheses explaining social association and of adult female caribou ( Rangifer tarandus ). We used location data from GPS collars to estimate interannual site fidelity and networks representing home range overlap and social associations among individual caribou. We found that home range overlap and social associations were correlated with resource distribution in summer and conspecific attraction in winter. In summer, when resources were distributed relatively homogeneously, interannual site fidelity was high and home range overlap and social associations were low. Conversely, in winter when resources were distributed relatively heterogeneously, interannual site fidelity was low and home range overlap and social associations were high. As access to resources changes across seasons, caribou appear to alter social behavior and space use. In summer, caribou may use cues associated with the distribution of forage, and in winter caribou may use cues from conspecifics to access forage. Our results have broad implications for our understanding of caribou socioecology, suggesting that caribou use season‐specific strategies to locate forage. Caribou populations continue to decline globally, and our finding that conspecific attraction is likely related to access to forage suggests that further fragmentation of caribou habitat could limit social association among caribou, particularly in winter when access to resources may be limited.

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“…Since most animals (including those studied here) frequently interact with social partners or competitors, a major challenge for future studies is to analyse the temporal behavioural movement patterns of interacting animals. Important steps have been made to develop new methods to extract social network from animal trajectories and future directions have been pointed towards using social telemetry data to identify preferred habitats for entire groups (Robitaille, Webber, & Vander Wal, 2019). Our method can help analyse these data by allowing the characterization of complex behavioural patterns of space use by multiple interacting individuals.…”

Section: Discussionmentioning

confidence: 99%

Analysis of temporal patterns in animal movement networks

et al. 2020

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1. Understanding how animal movements change across space and time is a fundamental question in ecology. While classical analyses of trajectories give insightful descriptors of spatial patterns, a satisfying method for assessing the temporal succession of such patterns is lacking.2. Network analyses are increasingly used to capture properties of complex animal trajectories in simple graphical metrics. Here, building on this approach, we introduce a method that incorporates time into movement network analyses based on temporal sequences of network motifs.3. We illustrate our method using four example trajectories (bumblebee, black kite, roe deer, wolf) collected with different technologies (harmonic radar, platform terminal transmitter, global positioning system). First, we transformed each trajectory into a spatial network by defining the animal's coordinates as nodes and movements in between as edges. Second, we extracted temporal sequences of network motifs from each movement network and compare the resulting behavioural profiles to topological features of the original trajectory. Finally, we compared each sequence of motifs with simulated Brownian and Lévy random motions to statistically determine differences between trajectories and classical movement models. 4. Our analysis of the temporal sequences of network motifs in individual movement networks revealed successions of spatial patterns corresponding to changes in behavioural modes that can be attributed to specific spatio-temporal events of each animal trajectory. Future applications of our method to multi-layered movement and social network analysis yield considerable promises for extending the study of complex movement patterns at the population level.

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Conducting social network analysis with animal telemetry data: Applications and methods using spatsoc

Cited by 68 publications

References 37 publications

Trade‐offs with telemetry‐derived contact networks for infectious disease studies in wildlife

Trade‐offs with telemetry‐derived contact networks for infectious disease studies in wildlife

Space use and social association in a gregarious ungulate: Testing the conspecific attraction and resource dispersion hypotheses

Analysis of temporal patterns in animal movement networks

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