Uncovering food web structure using a novel trophic similarity measure

作者：Gao Peng^*; Kupfer John A

来源：Ecological Informatics, 2015, 30: 110-118.

DOI：10.1016/j.ecoinf.2015.09.013

• Trophic role
• Serengeti
• Spatial guilds
• Body mass

Aggregation of species on the basis of their trophic relationships is a fundamental step for quantifying, visualizing and thereby uncovering the structure of food webs. Although the Additive Jaccard Similarity (AJS) has been widely used to measure trophic similarity between species, it has also been criticized for its limited ability to find species with equivalent trophic roles, especially when they do not share the same predators and prey. In this study, we proposed a new trophic similarity measure, the Extended Additive Jaccard Similarity (EAJS), which quantifies trophic similarity between species based not only on the similarity of their shared predators and prey at adjacent trophic levels but at all trophic levels throughout a food web. Average linkage clustering was then used to aggregate species in the mammalian food web for the Serengeti ecosystem in northern Tanzania and southern Kenya on the basis of both trophic similarity measures.
Compared to groups identified on the basis of AJS values, groups derived using EAJS had greater within-group similarity in terms of species' trophic relationships and greater discrimination vs. those in other groups. Groups based on EAJS values also better reflected ecological factors known to structure food webs, including producer-level habitat segregation and mammalian body mass. The advantage of EAJS lies in the fact that it is designed to consider species feeding relations in food webs that is not limited to adjacent trophic levels. Our approach provides a means for revealing the patterns of trophic relations among species in food webs and exploring known and unknown factors shaping food web structure.

• 出版日期2015-11