Social Experience of Captive Livingstone’s Fruit Bats (Pteropus livingstonii)

Abstract

Social network analysis has been highlighted as a powerful tool to enhance the evidence-based management of captive-housed species through its ability to quantify the social experience of individuals. We apply this technique to explore the social structure and social roles of 50 Livingstone’s fruit bats (Pteropus livingstonii) housed at Jersey Zoo, Channel Islands, through the observation of associative, affiliative, and aggressive interactions over two data collection periods. We implement binomial mixture modelling and characteristic-based assortment quantification to describe the complexity and organisation of social networks, as well as a multiple regression quadratic assignment procedural (MRQAP) test to analyse the relationship between network types. We examine the effects of individual characteristics (i.e., sex, age, and dominance rank) on social role by fitting models to explain the magnitude of node metrics. Additionally, we utilize a quadratic assignment procedural (QAP) test to assess the temporal stability of social roles over two seasons. Our results indicate that P. livingstonii display a non-random network structure. Observed social networks are positively assorted by age, as well as dominance rank. The frequency of association between individuals correlates with a higher frequency of behavioural interactions, both affiliative and aggressive. Individual social roles remain consistent over ten months. We recommend that, to improve welfare and captive breeding success, relationships between individuals of similar ages and dominance levels should be allowed to persist in this group where possible, and separating individuals that interact frequently in an affiliative context should be avoided.

Body-size dependent foraging strategies in the Christmas Island flying-fox: implications for seed and pollen dispersal within a threatened island ecosystem

“…Resource defense generally functions to provide a dominant individual with an adequate supply of some critical resource (often food) at the expense of less dominant individuals (usually conspecifics; [ 16 , 44 ] who are forced to move more often to acquire undefended foraging resources [ 16 , 28 ]. Although not directly tested in our study, in many territorial species, dominance is linked to body size [ 21 , 22 , 38 , 52 , 87 ], and the observed body size-dependent foraging movements of P. natalis are consistent with those of other nectivorous animals, including bats, that actively defend foraging resources [ 44 , 46 ].…”

“…While anecdotal observations suggest that smaller flying-fox individuals can be displaced from foraging sites by larger, dominant individuals (e.g., [ 53 ], to our knowledge, no studies of free ranging populations have directly tested whether foraging resource defense is body size-dependent in this taxon. This is likely due to the difficulty of observing individuals of known body mass interacting at foraging sites; however, diet and behavioral studies on captive populations of P. livingstonii demonstrated that older individuals [ 22 ], were more dominant and defended and/or displace smaller individuals from foraging resources [ 52 , 87 ].…”

“…In flying-foxes, larger, older and more experienced individuals defend territories and displace subordinates from foraging areas [ 22 , 52 , 71 , 87 ] using a variety of mechanisms including threatening vocalizations and threatening gestures such as wing spreading or clapping, and chases, fighting and aerial pursuit [ 14 , 60 , 71 , 81 , 89 , 90 ]. When the abundance of flying-foxes declines, resource defense interactions become less common, and so flying-foxes may become functionally extinct, ceasing to be effective dispersal agents long before becoming rare [ 53 ].…”

A comparison of low‐cost behavioral observation software applications for handheld computers and recommendations for use

“…Animal Observer was designed by Damien Caillaud and his team from the Dian Fossey Gorilla Fund International and first released in 2012. The application has been used to collect behavioral data in, for example, primates (Harrison et al, 2020;Schrock et al, 2019), humans (Dai et al, 2020), bats (Welch et al, 2020), and birds (van der Marel, Prasher, et al, 2020). The main sampling methods included in Animal Observer are focal animal and scan sampling.…”

Long term analysis of social structure: evidence of age-based consistent associations in male Alpine ibex

“…One of the most attractive features of SNA is that it allows to study the social organisation of animals at all levels (individual, dyad, group, population) and for all types of interaction (e.g., aggressive, cooperative, sexual, Krause et al, 2009), allowing a plethora of novel insights into the evolution and maintenance of sociality to be elucidated (Wey et al, 2008;Pinter-Wollman et al, 2014;Krause et al, 2015;Webber and Vander Wal 2019;Sosa et al, 2021b). As social structure can also affect population growth rates, dispersal and gene flow, network analysis also has the potential to be an important tool in the management of wild populations (Tarlow & Blumstein, 2007;Schakner et al, 2017, Snijders et al, 2017, Welch et al, 2020.…”