Species interactions affect the spread of vector-borne plant pathogens independent of transmission mode

David W. Crowder, Jing Li, Elizabeth T. Borer, Deborah L. Finke, Rakefet Sharon, David E. Pattemore, Jan Medlock

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Within food webs, vectors of plant pathogens interact with individuals of other species across multiple trophic levels, including predators, competitors, and mutualists. These interactions may in turn affect vector-borne pathogens by altering vector fitness and behavior. Predators, for example, consume vectors and reduce their abundance, but often spur movement of vectors as they seek to avoid predation. However, a general framework to predict how species interactions affect vectors of plant pathogens, and the resulting spread of vector-borne pathogens, is lacking. Here we developed a mathematical model to assess whether interactions such as predation, competition, and mutualism affected the spread of vector-borne plant pathogens with nonpersistent or persistent transmission modes. We considered transmission mode because interactions affecting vector–host encounter rates were expected to most strongly affect nonpersistent pathogens that are transmitted with short feeding bouts; interactions that affect vector feeding duration were expected to most strongly affect persistent pathogens that require long feeding bouts for transmission. Our results show that interactions that affected vector behavior (feeding duration, vector–host encounter rates) substantially altered rates of spread for vector-borne plant pathogens, whereas those affecting vector fitness (births, deaths) had relatively small effects. These effects of species interactions were largely independent of transmission mode, except when interactions affected vector–host encounter rates, where effects were strongest for nonpersistent pathogens. Our results suggest that a better understanding of how vectors interact with other species within food webs could enhance our understanding of disease ecology.

Original languageEnglish (US)
Article numbere02782
JournalEcology
Volume100
Issue number9
DOIs
StatePublished - Sep 1 2019

Bibliographical note

Funding Information:
This work was conducted as part of a Work Group at the National Institute for Mathematical and Biological Synthesis, sponsored by the National Science Foundation through Award DBI-1300426, with support from the University of Tennessee. We thank Y. Orukaze for help making Fig.

Publisher Copyright:
© 2019 by the Ecological Society of America

Keywords

  • community ecology
  • disease ecology
  • food web
  • mathematical model
  • vector-borne pathogen

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