Abstract
SOCPROG is a set of programs which analyses data on animal associations. Data usually come from observations of the social behaviour of individually identifiable animals. Associations among animals, sampling periods, restrictions on the data and association indices can be defined very flexibly. SOCPROG can analyse data sets including 1,000 or more individuals. Association matrices are displayed using sociograms, principal coordinates analysis, multidimensional scaling and cluster analyses. Permutation tests, Mantel and related tests and matrix correlation methods examine hypotheses about preferred associations among individuals and classes of individual. Weighted network statistics are calculated and can be tested against null hypotheses. Temporal analyses include displays of lagged association rates (rates of reassociation following an association). Models can be fitted to lagged association rates. Multiple association measures, including measures produced by other programs such as genetic or range use data, may be analysed using Mantel tests and principal components analysis. SOCPROG also performs mark-recapture population analyses and movement analyses. SOCPROG is written in the programming language MATLAB and may be downloaded free from the World Wide Web.
Original language | English |
---|---|
Pages (from-to) | 765-778 |
Number of pages | 14 |
Journal | Behavioral Ecology and Sociobiology |
Volume | 63 |
Issue number | 5 |
DOIs | |
Publication status | Published - Mar 2009 |
Bibliographical note
Funding Information:Acknowledgements Thanks to Robin Baird, Jenny Christal, Susan Dufault, Shane Gero, Shannon Gowans, Andrea Ottensmeyer and, especially, David Lusseau for ideas and testing of the programs. Susan Dufault put SOCPROG on the World Wide Web. The research was funded by the Natural Sciences and Engineering Research Council of Canada. I am grateful for the constructive and detailed comments of two anonymous reviewers.
ASJC Scopus Subject Areas
- Ecology, Evolution, Behavior and Systematics
- Animal Science and Zoology