Show simple item record

dc.contributor.authorWilson, ADMen
dc.contributor.authorBrownscombe, JWen
dc.contributor.authorKrause, Jen
dc.contributor.authorKrause, Sen
dc.contributor.authorGutowsky, LFGen
dc.contributor.authorBrooks, EJen
dc.contributor.authorCooke, SJen

© 2015 The Author 2015. Published by Oxford University Press on behalf of the International Society for Behavioral Ecology. All rights reserved. For permissions, please e-mail: Group living in animals is a well-studied phenomenon, having been documented extensively in a wide range of terrestrial, freshwater, and marine species. Although social dynamics are complex across space and time, recent technological and analytical advances enable deeper understanding of their nature and ecological implications. While for some taxa, a great deal of information is known regarding the mechanistic underpinnings of these social processes, knowledge of these mechanisms in elasmobranchs is lacking. Here, we used an integrative and novel combination of direct observation, accelerometer biologgers, and recent advances in network analysis to better understand the mechanistic bases of individual-level differences in sociality (leadership, network attributes) and diel patterns of locomotor activity in a widespread marine predator, the lemon shark (Negaprion brevirostris). We found that dynamic models of interaction based on Markov chains can accurately predict juvenile lemon shark social behavior and that lemon sharks did not occupy consistent positions within their network. Lemon sharks did however preferentially associate with specific group members, by sex as well as by similarity or nonsimilarity for a number of behavioral (nonsimilarity: leadership) and locomotor traits (similarity: proportion of time swimming "fast," mean swim duration; nonsimilarity: proportion of swimming bursts/transitions between activity states). Our study provides some of the first information on the mechanistic bases of group living and personality in sharks and further, a potential experimental approach for studying fine-scale differences in behavior and locomotor patterns in difficult-to-study organisms.

dc.format.extent1577 - 1586en
dc.titleIntegrating network analysis, sensor tags, and observation to understand shark ecology and behavioren
dc.typeJournal Article
plymouth.journalBehavioral Ecologyen
plymouth.organisational-group/Plymouth/00 Groups by role
plymouth.organisational-group/Plymouth/00 Groups by role/Academics
plymouth.organisational-group/Plymouth/Faculty of Health and Human Sciences
plymouth.organisational-group/Plymouth/Faculty of Health and Human Sciences/School of Psychology
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering/School of Biological and Marine Sciences
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA07 Earth Systems and Environmental Sciences
dc.rights.embargoperiodNo embargoen
rioxxterms.typeJournal Article/Reviewen

Files in this item


This item appears in the following Collection(s)

Show simple item record

All items in PEARL are protected by copyright law.
Author manuscripts deposited to comply with open access mandates are made available in accordance with publisher policies. Please cite only the published version using the details provided on the item record or document. In the absence of an open licence (e.g. Creative Commons), permissions for further reuse of content should be sought from the publisher or author.
Theme by 
@mire NV