Modeling and Analysis of Interaction Networks in Ecological Systems

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Understanding how networks form and evolve is an important question in many fields such as ecology, epidemiology, economics, and sociology. Studying the mechanisms of network formation can yield insight into which factors are involved in edge formation and network growth. This thesis explores network formation within ecological systems, focusing on herbivore-plant interaction networks using field data collected in Ecuador. Two modeling frameworks are considered: the repeated choice model (RCM) and the stochastic actor-oriented model (SAOM). The RCM treats network formation as a sequence of discrete choices, modeling herbivores' selection of host plants based on plant-level attributes such as leaf count. The SAOM models network evolution as a continuous-time stochastic process influenced by both individual traits and the existing network structure. This thesis presents a comparative analysis of these two approaches, highlighting their respective assumptions, estimation strategies, and shortcomings. Results from applying both models to empirical data are presented, offering insights into the dynamics of ecological network formation.

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