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The Role of Stochastic Simulations to Extend Food Web Analyses
Abstract
Food webs are schematic representations of who eats whom in ecosystems. They are widely used in linking process to pattern (e.g., degree distribution and vulnerability) and investigating the roles played by particular species within the interaction web (e.g., centrality indices and trophic position). First, I present the dominator tree, a topological structure reducing food web complexity into linear pathways that are essential for energy delivery. Then, I describe how the dominance relations based on dominator trees extracted from binary food webs may be modified by including interaction strength. Consequences related to the skewed distribution of weak links towards the trophic chain are discussed to explain higher risks of secondary extinction that characterize top predators dominated by basal species. Finally, stochastic simulations are introduced to suggest an alternative approach to static analyses based on food web topology. Ranking species importance using stochastic-based simulations partially contradicts the predictions based on network analyses.
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