Margaret W. Simon, University of Kansas, USA, discusses her article: Fast-growing annual plants drive disease spillover in multi-host communities
Infectious plant diseases affect hosts in natural, agricultural, and urban systems. Modeling studies can help predict these effects, but traditional disease models were developed for animal systems. These models are not well suited for plant disease because plants often experience localized rather than systemic disease. Thus, infection levels should be tracked within each individual plant, rather than characterizing an individual as infected or uninfected. Additionally, annual plants grow and complete their life cycle on timescales comparable to disease progression, thereby creating feedbacks between tissue growth and pathogen spread. Such feedbacks could alter the biomass accrual rate of an individual, and disease trajectories in the community.
When a plant pathogen exploits two (or more) host species, an indirect interaction occurs whereby an increase in population size of one host supports an increase in pathogen numbers, subsequently negatively affecting the alternative host(s) in the community, and vice versa. This type of indirect interaction, called apparent competition, occurs not only in plant-pathogen systems, but also predator-prey and host-parasite systems. In such systems, prey (or host) species with high population growth rates sustain greater predator (pathogen) abundances, which then suppress other, slower-growing, prey (host) species in the community.
We hypothesized that a similar phenomenon could be occurring among plant species that share a common pathogen, and whose individuals have different biomass accrual rates. The idea is that the accrual rate of a host individual could serve a similar purpose to a host’s population growth rate. Consider a system of two annual plant species (species 1 and 2) that share a pathogen and have the same biomass accrual rate for all individuals within a species, but with different rates between species. If our hypothesis were true, we would expect species 1 individuals to experience a greater reduction in biomass yield when species 2 individuals have a faster biomass accrual rate (and vice versa). To test this, we developed a mathematical model that incorporates the biological features of an annual plant, including localized infection, and pathogen life cycles and biomass accrual rates that occur at similar time scales. We used this model to conduct computer simulation experiments between two theoretical plant species that share a pathogen, but do not compete for resources. Importantly, we set biomass accrual rates to be the same for all individuals within a host species, but to differ between the two species. We assumed that the pathogen has the same qualitative effect on both species – i.e., it uses up resources in its host, hindering that individual’s ability to grow in proportion to the amount of infection the individual has. The amount of infection within an individual will change over time as the pathogen transmits within and between individuals.
We found that the pathogen caused greatest declines in the biomass yield of species 1 when species 2 was faster at biomass-accruing, especially when the difference between the two species’ biomass accrual rates was large. We do not allow for resource competition in the model, so these effects can only be accounted for by indirect effects mediated by the pathogen (i.e., apparent competition).
We also found that, when both host species are equally defended (or undefended) against the pathogen, the species with the faster biomass accrual rate produced more pathogens per individual than its apparent competitor.
In a community of equal parts species 1 and species 2, this translates into a greater production of pathogens (i.e., higher disease levels) by the faster-accruing species. Consequently, the faster-accruing species can amplify disease levels in a multi-host community, while the slower-accruing species generally dilutes it. These results highlight the importance of biomass accrual rates as a potential driver of infectious disease outcomes in multi-host annual plant communities.
