Published in

Elsevier, Animal Behaviour, (103), p. 17-28, 2015

DOI: 10.1016/j.anbehav.2015.01.039

Links

Tools

Export citation

Search in Google Scholar

A comparison between traditional kernel-based methods and network analysis: An example from two nearshore shark species

This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Green circle
Preprint: archiving allowed
Orange circle
Postprint: archiving restricted
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

Understanding how marine species use their environment has become increasingly important in management and conservation. Acoustic monitoring allows long-term tracking of marine animal movement that is traditionally analysed using kernel-based home range estimators. These traditional methods, however, are limited because they do not examine movement pathways within activity spaces. Network analysis (NA) provides an alternative approach to traditional home range analysis that treats acoustic receivers as network nodes and analyses movement between nodes. To investigate the utility of NA in identifying core use areas and compare the results with traditional analysis, a case study using acoustically monitored coastal sharks was conducted. To make direct comparisons with static traditional analysis a temporal scale was not explicitly explored. Comparison of traditional analysis and NA demonstrated that both methods provided similar results for identifying core use areas (50% kernel utilization distribution (KUD) equivalent), but that NA tended to overestimate general use areas (95% KUD equivalent) compared to kernel-based methods. Furthermore, frequent bidirectional movements within core use areas were identified by NA, indicating the importance of movement corridors within or between core areas. Movements between acoustic receivers outside core use areas were less frequent and unidirectional suggesting transiting movements. Therefore, NA may be a practical alternative to traditional home range metrics by providing useful data interpretation that allows for a comprehensive picture of animal movement, including identifying core use areas and pathways used.