Weak intra-guild predation facilitates consumer coexistence but does not guarantee higher consumer density

Feng Hsun Chang, Po Ju Ke, Bradley Cardinale

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


In plant communities, resource partitioning has been shown to facilitate species coexistence and, in turn, enhance community density. Such positive effects of resource partitioning in higher trophic levels are not as obvious possibly due to the occurrence of intra-guild predation (IGP). We thus built a model to explore the joint effects of IGP and resource partitioning on consumer coexistence and their collective density as rarely have studies investigated this joint effect. The model consists of two prey resources that do not directly compete with each other and two consumers that are engaged in IGP and can partition their use of the two prey resources. This model shows that the effects of IGP on consumer coexistence depend on which consumer requires the lower resource density to persist. When the IG predator is the inferior competitor, weak IGP enhances coexistence by lowering the minimum degree of partitioning that is required for coexistence; otherwise, IGP always constrains coexistence. In addition, the effects of IGP on total consumer density (Ztot) depends on which consumer has the lower maximum growth potential, defined as the difference between their maximum growth rate and mortality. Weak IGP increases Ztot when the IG predator has lower maximum growth potential; otherwise, IGP always decreases Ztot. Last, the criterion for IGP to have positive effects on consumer coexistence and Ztot are different. Our results show that weak to intermediate strengths of intra-guild predation can facilitate consumer coexistence and total community density, but consumer coexistence does not guarantee higher consumer density.

Original languageEnglish (US)
Article number109019
JournalEcological Modelling
StatePublished - May 15 2020

All Science Journal Classification (ASJC) codes

  • Ecological Modeling


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