Predicting food web connectivity: Phylogenetic scope, evidence thresholds, and intelligent agents

Cynthia Parr, Joel Sachs, and Andriy Parafiynyk

August 8, 2006

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ecology, food web, modeling, rdf, semantic web, sparql

Presentation at the Ecological Society of America annual meeting in Memphis, TN August 8, 2006. Part of a symposium organized by Tim Keitt and Bill Fagan: Structure and Dynamics of Ecological Networks.

We parameterize a model for predicting trophic links using previously published interaction networks and phylogenetic/taxonomic trees. Interactors in given food webs are identified where possible to scientific name at the most appropriate taxonomic level so that a tree can used to search for evidence supporting or rejecting potential network links. To maximize accuracy and recall, we examine limits on the tree search, and different costs to apply to distances from the target taxa to those found in known networks. We find that negative evidence, where relatives of two organisms occur together but are not linked trophically, must be significantly down-weighted. Also, perhaps not surprisingly, recall is difficult but not impossible for large webs whose entities are well resolved to species. We also consider variation among phyla in parameterization success. We then use this model to predict links among new lists of taxa and consider properties of these webs (e.g. connectance). Finally, we present preliminary results of experiments using intelligent agents and ontologies to integrate life history datasets towards more realistic predictions.



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