Friday, December 2, 2011

Cronin, J.P., et al. Ecology Letters. (2010).

"Host physiological phenotype explains pathogen reservoir potential".

Reviewed: 12/02/11

The framework for approaching disease should not always be focused at the level of the individual or population of hosts only. The capacity any given individual has for disease directly affects how that disease might be transferred to other potential hosts within its community. The authors of this study set out to assess the reservoir potential of 6 different grass species, important to California grasslands, as they relate to the the viral pathogen Barley Yellow Dwarf Virus-PAV (BYDV-PAV) and the aphid vector Rhopalosiphum padi. Reservoir potential has been linked to three measurable epidemiological traits: the susceptibility of any given host to transfer of virus by the vector, the competence of the host to pass on the virus to a feeding aphid after the disease had become internally systemic, and lastly the host ability to support vector populations.
During the first Greenhouse experiment physiological traits were measured for the 6 different grasses, independent of viral infection, under conditions of low and high nitrogen. Principal Component Analysis (PCA) was able to condense the results of all five traits down to two primary principal component axes (PC1 and PC2). PC1 explained 50% of the variance in the results and was linked with a beforehand hypothesized continuum of 'Quick-Return' and 'Slow-Return' phenotypes, QR and SR respectively. The QR-SR continuum is a classification continuum that posits that quick growing host species will be more poorly defended but faster growing, while slow return species will allocate less overall to rapid, short-term growth but will have high defenses to enemies. The link of PC1 with this continuum was important for the researchers as it cohesively combined a complex array of traits into one definable axis of study.
Under the two nitrogen regimes, those grasses grown under higher nitrogen were consistently shifted more toward a QR phenotype, except for a single grass host.
The second part of the experiment was designed to test whether the conglomerate of physiological traits was sufficient to explain the three epidemiological parameters previously outlined, or whether host lifespan, phylogeny, and provenance (native vs. exotic) were also required. Nested models were used to test this theory by systematically dropping explanatory terms from the model, and using AIC for comparison. Host physiological traits, in the form of PC1, were consistently necessary to explain host reservoir potential. QR type hosts are more efficient as reservoir hosts, meaning that can support high levels of aphid vectros, become infected more easily, and transfer pathogens more easily. The authors propose host physiology as primary in importance for predicting epidemiological parameters, however the phylogenetic history and lifespan/provenance of a host is still relevant to the discussion, as shown by their significant inclusion in two of the paramters: vector population size and host susceptibility.
This study looked at five traits and ran them through a PCA, however future studies should expand beyond the nitrogen centered framework used here. Multiple nutrients are responsible for the dynamics seen in terrestrial systems, (eg Nitrogen and Phosphorus, as wel as other micronutrients). In this experiment nitrogen was shown to shift grasses towards being a better host. If phosphorus addition or faster growth do to rising CO2 levels do the same, then this will have important implications for global change analysts and the disease emergence in the future. Inclusion of more broad-scope traits would impove the results of this analysis.

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