Inferring animal social networks with imperfect detection

Giménez, Olivier; Mansilla, Lorena; Klaich, M. Javier; Coscarella, Mariano Alberto; Pedraza, Susana N.; Crespo, Enrique A.

doi:10.1016/j.ecolmodel.2019.04.001

Cited by 15 publications

(19 citation statements)

References 32 publications

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“…Extensions of recent work using hidden state modelling may be more appropriate for disentangling true association patterns when detections are potentially biased or imperfect (Gimenez et al, 2019).…”

Section: Carrying Out Regression In Social Network By Separating Nmentioning

confidence: 99%

Common datastream permutations of animal social network data are not appropriate for hypothesis testing using regression models

et al. 2020

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Section: Carrying Out Regression In Social Network By Separating Nmentioning

confidence: 99%

Common datastream permutations of animal social network data are not appropriate for hypothesis testing using regression models

et al. 2020

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“…The detection of co‐captures and movements in CMR datasets will depend on capture effort. Spatial or temporal variation in capture effort could therefore lead to spurious differences in network structure being detected if not adequately controlled (Gimenez et al., 2019). Care should be taken when using the network approaches described here when this is likely to be the case.…”

Section: Key Considerations When Using Cmrnetmentioning

confidence: 99%

“…the location, time and date of each capture are recorded), then under the assumption that co‐located individuals tend to be social associates, co‐captures could be used as a proxy for social associations (e.g. Gimenez et al., 2019; Perkins et al., 2009). Information on co‐location also permits inference of a spatial network of the movement of individuals within a population (Jacoby & Freeman, 2016).…”

Section: Introductionmentioning

confidence: 99%

CMRnet: An r package to derive networks of social interactions and movement from mark–recapture data

Silk

McDonald

Delahay³

et al. 2020

Methods Ecol Evol

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Social structure and population dynamics are closely intertwined (Shizuka & Johnson, 2019). The social structure of populations is critical in shaping key ecological processes, such as the spread of information and infections (Allen et al., 2013;Aplin et al., 2015;White et al., 2017), and in driving patterns of evolutionary change (Fisher & McAdam, 2017). On the one hand, social relationships will be influenced by demographic changes; for example, individuals may interact more with others at higher population densities (O'Brien et al., 2018). On the other hand, social relationships may influence key demographic processes, such as reproductive rates (McDonald, 2007), dispersal (Blumstein et al., 2009) or survival (Ellis et al., 2017). Hence, the interplay between demography and social structure is of immediate relevance to tackling numerous important questions in behavioural and evolutionary ecology, and yet longterm demographic data are rarely associated with detailed social analyses.Many long-term studies of wild animals involve the collection of data based on capture-mark-recapture (CMR) approaches, where individuals are given a unique identifier when first captured, allowing identification if subsequently recaptured. If CMR data are spatiotemporally referenced (i.e. the location, time and date of each capture are recorded), then under the assumption that co-located

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“…For that being accurate, “individuals should be missing at random”, an assumption we feel confident with because we have no reason to suspect that those individuals that we fail to observe each year in the field are not a random sample of all the individuals. Coping with missing data is highly relevant when analysing sociality on wild populations, as detection rate for individuals is almost always imperfect, and properly controlling for missed observations is a very important step in social network analysis 76 , 77 . To create and visualize our networks we used the packages Amen 73 , Asnipe 78 , gdata 79 and igraph in R 80 .…”

Section: Methodsmentioning

confidence: 99%

Decrease in social cohesion in a colonial seabird under a perturbation regime

Genovart

Giménez

Bertolero³

et al. 2020

Sci Rep

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Social interactions, through influence on behavioural processes, can play an important role in populations’ resilience (i.e. ability to cope with perturbations). However little is known about the effects of perturbations on the strength of social cohesion in wild populations. Long-term associations between individuals may reflect the existence of social cohesion for seizing the evolutionary advantages of social living. We explore the existence of social cohesion and its dynamics under perturbations by analysing long-term social associations, in a colonial seabird, the Audouin’s gull Larus audouinii, living in a site experiencing a shift to a perturbed regime. Our goals were namely (1) to uncover the occurrence of long-term social ties (i.e. associations) between individuals and (2) to examine whether the perturbation regime affected this form of social cohesion. We analysed a dataset of more than 3500 individuals from 25 years of monitoring by means of contingency tables and within the Social Network Analysis framework. We showed that associations between individuals are not only due to philopatry or random gregariousness but that there are social ties between individuals over the years. Furthermore, social cohesion decreased under the perturbation regime. We sustain that perturbations may lead not only to changes in individuals’ behaviour and fitness but also to a change in populations’ social cohesion. The consequences of decreasing social cohesion are still not well understood, but they can be critical for the population dynamics of social species.

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Inferring animal social networks with imperfect detection

Cited by 15 publications

References 32 publications

Common datastream permutations of animal social network data are not appropriate for hypothesis testing using regression models

Common datastream permutations of animal social network data are not appropriate for hypothesis testing using regression models

CMRnet: An r package to derive networks of social interactions and movement from mark–recapture data

Decrease in social cohesion in a colonial seabird under a perturbation regime

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