Total Communicability of Temporal Matrix vs Aggregate Graph Using a Food Web Open Access
Breeden Jr., Brian David (2014)
Published
Abstract
Node centrality is an important metric in network analysis, allowing the most influential nodes in a system to be identified. This thesis analyzes a directed food web network in order to discover the most influential predator and prey species in the ecosystem, and to examine the different possible constructs for analyzing time-dependent networks. The communicability matrices for each individual month as well as the aggregate graph, and three variations of the temporal communicability matrix were computed. The individual months were compared, revealing a unique top predator species for almost every month, but a mostly fixed list of top preys. The aggregate graph appeared to favor the species expected from comparing the graphs. The temporal matrices, on the other hand, yielded seemingly conflicting results between predators and prey on what resulted in a top species. Predator rankings seemed to depend heavily on which temporal matrix was used, while top prey rankings were relatively stable.
Table of Contents
1 Introduction 1 2 Background 4 3 Problem 10 4 Methods 12 5 Results and Discussion 14 5.1 Communicabilities in Individual Months . . . . . . . . . . . . . . . . 14 5.2 Temporal Communicability vs Aggregate Graph . . . . . . . . . . . . 21 6 Conclusion 29 7 Appendix 32
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Total Communicability of Temporal Matrix vs Aggregate Graph Using a Food Web () | 2018-08-28 14:40:13 -0400 |
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