Individual Factors Predicting the Disappearance and Reproductive Success of Vervet Monkeys (Chlorocebus pygerythrus)

Simple item page
dc.contributor.advisorSchoof, Valerie
dc.contributor.authorSchwegel, Megan Anna
dc.date.accessioned2023-08-04T15:06:21Z
dc.date.available2023-08-04T15:06:21Z
dc.date.issued2023-08-04
dc.date.updated2023-08-04T15:06:20Z
dc.degree.disciplineBiology
dc.degree.levelMaster's
dc.degree.nameMSc - Master of Science
dc.description.abstractSocial network analysis (SNA) is an increasingly popular method of quantifying social interactions and relating these to individual characteristics. However, few studies have considered how demographic events influence social networks and how social position affects fitness among species that live around humans. Using the gambit of the group and proximity data, I performed SNA on vervet monkeys to determine how social centrality predicted which individuals were more likely to disappear and to have infants that survived past one year. Older males with a lower or decrease in social centrality were more likely to disappear, where older males were more likely to emigrate, and individuals who decreased in their eigenvector centrality were more likely to have a human-related death. Females with a greater betweenness tended to have greater infant survival rates. Overall, emigration was influenced by natural history while human-related disappearances and reproductive success were mediated by social position.
dc.identifier.urihttps://hdl.handle.net/10315/41301
dc.languageen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectBiology
dc.subjectAnimal behavior
dc.subjectEcology
dc.subject.keywordsDynamic social network analysis
dc.subject.keywordsHuman-modified landscape
dc.subject.keywordsPrimates
dc.subject.keywordsDispersal
dc.subject.keywordsDeath
dc.titleIndividual Factors Predicting the Disappearance and Reproductive Success of Vervet Monkeys (Chlorocebus pygerythrus)
dc.typeElectronic Thesis or Dissertation

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Schwegel_Megan_A_2023_Masters.pdf
Size:
1.16 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 2 of 2
No Thumbnail Available
Name:
license.txt
Size:
1.87 KB
Format:
Plain Text
Description:
Download
No Thumbnail Available
Name:
YorkU_ETDlicense.txt
Size:
3.39 KB
Format:
Plain Text
Description:
Download

Collections

Biology

All items in the YorkSpace institutional repository are protected by copyright, with all rights reserved except where explicitly noted.