Every forest tree is an ecosystem with a complex community of microbes that interact with their hosts on a spectrum of relationships from mutualist to pathogen, sometimes switching those ecological roles with changes in the host or environment. This forms the basis of the disease triangle, the basic model of disease emergence with proven etiological value but lower predictive power. Epidemiological models have great merit in predicting transmission and disease emergence for a range of infectious pathogens, but the predictive power of these models has yet to be applied across the full spectrum of interactions encompassed by the disease triangle.
Results/Conclusions
I present a generalized epidemiological model of the disease triangle using the familiar SIR-type model basis. I present a parameter-based framework for incorporating key host factors such as response to drought, cross talk between biochemical pathways, and host density changes at environmental range limits. A similar solution to pathogen responses to moisture and temperature dynamics is presented in the same SIR framework that in turn also accounts for changes in host density. The model demonstrates tradeoffs between host, pathogen, and environmental factors in terms of their effects on disease. Importantly, ‘hidden’ disease dynamics resulting from widespread but relatively weak pathogens are revealed by the model suggesting that variation in drought-associated mortality may be driven by heterogeneous microbial communities. Predictive use of the model relies on a strong basis for parameter values including pathogen and host responses to a changing environment. However, the model is likely to hold immediate application to synthesizing hypotheses and directing data collection for emerging forest mortality events.