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Hasenjager, M.J.; Dugatkin, L.A. |
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Social Network Analysis in Behavioral Ecology |
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Animal personalities; Animal social networks; Collective behavior; Cooperation; Dynamic networks; Emergent properties; Network theory; Social behavior; Social learning; Social structure |
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Abstract In recent years, behavioral ecologists have embraced social network analysis (SNA) in order to explore the structure of animal societies and the functional consequences of that structure. We provide a conceptual introduction to the field that focuses on historical developments, as well as on novel insights generated by recent work. First, we discuss major advances in the analysis of nonhuman societies, culminating in the use of SNA by behavioral ecologists. Next, we discuss how network-based approaches have enhanced our understanding of social structure and behavior over the past decade, focusing on: (1) information transmission, (2) collective behaviors, (3) animal personality, and (4) cooperation. These behaviors and phenomena possess several features—e.g., indirect effects, emergent properties—that network analysis is well equipped to handle. Finally, we highlight recent developments in SNA that are allowing behavioral ecologists to address increasingly sophisticated questions regarding the structure and function of animal sociality. |
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Academic Press |
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Advances in the Study of Behavior |
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Equine Behaviour @ team @ Hasenjager |
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5863 |
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Linklater, W.L.; Cameron, E.Z.; Stafford, K.J.; Veltman, C.J. |
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Social and spatial structure and range use by Kaimanawa wild horses (Equus caballus: Equidae) |
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2000 |
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New Zealand Journal of Ecology |
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New Zealand J. Ecol. |
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24 |
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2 |
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139-152 |
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Bachelor male; Band; Density; Habitat use; Home range; Management proposals; Micro-climate; Vegetation monitoring; habitat use; home range; mammal; social structure; spatial distribution; New Zealand; Equus caballus |
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We measured horse density, social structure, habitat use, home ranges and altitudinal micro-climates in the south-western Kaimanawa ranges east of Waiouru, New Zealand. Horse density in the Auahitotara ecological sector averaged 3.6 horses.km-2 and ranged from 0.9 to 5.2 horses.km-2 within different zones. The population's social structure was like that of other feral horse populations with an even adult sex ratio, year round breeding groups (bands) with stable adult membership consisting of 1 to 11 mares, 1 to 4 stallions, and their predispersal offspring, and bachelor groups with unstable membership. Bands and bachelor males were loyal to undefended home ranges with central core use areas. Band home range sizes varied positively with adult band size. Home ranges overlapped entirely with other home ranges. Horses were more likely to occupy north facing aspects, short tussock vegetation and flush zones and avoid high altitudes, southern aspects, steeper slopes, bare ground and forest remnants. Horses were more likely to be on north facing aspects, steeper slopes, in exotic and red tussock grasslands and flush zones during winter and at lower altitudes and on gentler slopes in spring and summer. Seasonal shifts by bands to river basin and stream valley floors in spring and higher altitudes in autumn and winter are attributed to the beginning of foaling and mating in spring and formation of frost inversion layers in winter. Given horse habitat selectivity and the presence of other ungulate herbivores, results from present exclosures are likely to exaggerate the size of horse impacts on range vegetation. Proposals to manage the population by relocation and confinement are likely to modify current social structure and range use behaviour and may lead to the need for more intensive management in the longer term. |
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Ecology Group, Institute of Natural Resources, Massey University, Private Bag 11-222, Palmerston North, New Zealand |
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01106465 (Issn) |
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Cited By (since 1996): 12; Export Date: 21 April 2007; Source: Scopus; Language of Original Document: English; Correspondence Address: Linklater, W.L.; Ecology Group; Institute of Natural Resources; Massey University; Private Bag 11-222 Palmerston North, New Zealand; email: wlinklater@hotmail.com |
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refbase @ user @ |
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793 |
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Sueur, C.; Jacobs, A.; Amblard, F.; Petit, O.; King, A.J. |
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How can social network analysis improve the study of primate behavior? |
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2010 |
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American Journal of Primatology |
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Am. J. Primatol. |
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73 |
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8 |
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703-719 |
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interaction; association; social system; social structure; methodology; behavioral sampling |
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Abstract When living in a group, individuals have to make trade-offs, and compromise, in order to balance the advantages and disadvantages of group life. Strategies that enable individuals to achieve this typically affect inter-individual interactions resulting in nonrandom associations. Studying the patterns of this assortativity using social network analyses can allow us to explore how individual behavior influences what happens at the group, or population level. Understanding the consequences of these interactions at multiple scales may allow us to better understand the fitness implications for individuals. Social network analyses offer the tools to achieve this. This special issue aims to highlight the benefits of social network analysis for the study of primate behaviour, assessing it's suitability for analyzing individual social characteristics as well as group/population patterns. In this introduction to the special issue, we first introduce social network theory, then demonstrate with examples how social networks can influence individual and collective behaviors, and finally conclude with some outstanding questions for future primatological research. Am. J. Primatol. 73:703?719, 2011. ? 2011 Wiley-Liss, Inc. |
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Wiley-Blackwell |
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0275-2565 |
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doi: 10.1002/ajp.20915 |
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Equine Behaviour @ team @ |
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6410 |
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