Why Is Living Fast Dangerous? Disentangling the Roles of Resistance and Tolerance of Disease

Cronin, James Patrick; Rúa, Megan A.; Mitchell, Charles E.

doi:10.1086/676854

Cited by 35 publications

(51 citation statements)

References 79 publications

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“…Interestingly, in this system we cannot equate short and long lifespan with the physiological phenotypes of Quick- or Slow-Return, since rosette relative growth rate was higher in the long-lived Ll-0 genotype than in the short-lived Ler, but leaf mass per unit area did not differ between both genotypes. This unexpected result is at odds with evidence derived from the comparison of different plant species [8], [24], [59], [60], and suggests that the trade-off between lifespan and development and reproductive rates [61] may not apply at the level of within-species diversity, or at the temporal scale at which the lifespan of Ler and Ll-0 differ. The different performance of aphids in each genotype, regardless of similar LMA, could be explained by differences in nutrient composition in the phloem sap [62], which would not translate into detectable differences in LMA.…”

Section: Discussionmentioning

confidence: 77%

“…Rosette relative growth rate (cm/(day×cm)) was estimated by digital capture and further measure of rosette diameter increase every 2 days for a period of 12 days post inoculation. LMA and relative growth rate are parameters that relate to quick-return and slow-return physiological phenotypes, which may influence host competence, susceptibility, and the ability to support vectors [8], [24].…”

Section: Materials and Experimental Methodsmentioning

confidence: 99%

“…For plants, there is evidence that short-lived species of grasses (Poaceae) have a high reservoir potential of a generalist plant virus for long-lived hosts [22], [23]. Also, it has been experimentally shown that defenses reducing susceptibility to infection by that virus was lower in short-lived (annual) that in long-lived (perennial) species of grasses, while competence was not explained by lifespan [8], [24].To our knowledge, the relationship between host lifespan and reservoir potential has not been analyzed at the within-species diversity level.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Relationship between Host Lifespan and Pathogen Reservoir Potential: An Analysis in the System Arabidopsis thaliana-Cucumber mosaic virus

et al. 2014

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Identification of the determinants of pathogen reservoir potential is central to understand disease emergence. It has been proposed that host lifespan is one such determinant: short-lived hosts will invest less in costly defenses against pathogens, so that they will be more susceptible to infection, more competent as sources of infection and/or will sustain larger vector populations, thus being effective reservoirs for the infection of long-lived hosts. This hypothesis is sustained by analyses of different hosts of multihost pathogens, but not of different genotypes of the same host species. Here we examined this hypothesis by comparing two genotypes of the plant Arabidopsis thaliana that differ largely both in life-span and in tolerance to its natural pathogen Cucumber mosaic virus (CMV). Experiments with the aphid vector Myzus persicae showed that both genotypes were similarly competent as sources for virus transmission, but the short-lived genotype was more susceptible to infection and was able to sustain larger vector populations. To explore how differences in defense against CMV and its vector relate to reservoir potential, we developed a model that was run for a set of experimentally-determined parameters, and for a realistic range of host plant and vector population densities. Model simulations showed that the less efficient defenses of the short-lived genotype resulted in higher reservoir potential, which in heterogeneous host populations may be balanced by the longer infectious period of the long-lived genotype. This balance was modulated by the demography of both host and vector populations, and by the genetic composition of the host population. Thus, within-species genetic diversity for lifespan and defenses against pathogens will result in polymorphisms for pathogen reservoir potential, which will condition within-population infection dynamics. These results are relevant for a better understanding of host-pathogen co-evolution, and of the dynamics of pathogen emergence.

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Section: Discussionmentioning

confidence: 77%

Section: Materials and Experimental Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Relationship between Host Lifespan and Pathogen Reservoir Potential: An Analysis in the System Arabidopsis thaliana-Cucumber mosaic virus

et al. 2014

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“…A priori identification of such individual hosts is challenging, but essential to understanding and potentially managing disease outbreaks. These hosts are expected to have greater probabilities of (i) infection given pathogen exposure (susceptibility), (ii) transmission of pathogens per contact, (iii) contacts, (iv) harbouring or shedding greater pathogen populations and (v) persistence with infection (tolerance) [1][2][3]. Because host behaviour and physiology underlie such disease dynamics, functional traits that integrate and represent characteristic phenotypes could be valuable in the a priori identification of 'super-spreaders'-individuals with a disproportionate potential to spread disease [1,2,4].…”

Section: Introductionmentioning

confidence: 99%

“…Behavioural phenotypes could underlie disease transmission, because variation among individuals in activity and conspecific interactions could influence both exposure to pathogens and host infectiousness. Infectiousness is defined as the capacity of an infected host to transmit an infection by contact with a susceptible host [1,2,13]. Here, we measured infectiousness as the proportion of susceptible animals infected after exposure to an infected conspecific.…”

Section: Introductionmentioning

confidence: 99%

Behavioural phenotypes predict disease susceptibility and infectiousness

Araujo

Kirschman²

2016

Biol. Lett.

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Behavioural phenotypes may provide a means for identifying individuals that disproportionally contribute to disease spread and epizootic outbreaks. For example, bolder phenotypes may experience greater exposure and susceptibility to pathogenic infection because of distinct interactions with conspecifics and their environment. We tested the value of behavioural phenotypes in larval amphibians for predicting ranavirus transmission in experimental trials. We found that behavioural phenotypes characterized by latency-to-food and swimming profiles were predictive of disease susceptibility and infectiousness defined as the capacity of an infected host to transmit an infection by contacts. While viral shedding rates were positively associated with transmission, we also found an inverse relationship between contacts and infections. Together these results suggest intrinsic traits that influence behaviour and the quantity of pathogens shed during conspecific interactions may be an important contributor to ranavirus transmission. These results suggest that behavioural phenotypes provide a means to identify individuals more likely to spread disease and thus give insights into disease outbreaks that threaten wildlife and humans.

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Quantifying relative importance: computing standardized effects in models with binary outcomes

et al. 2018

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Scientists commonly ask questions about the relative importance of processes and then turn to statistical models for answers. Standardized coefficients are typically used in such situations, with the goal being to compare effects on a common scale. Traditional approaches to obtaining standardized coefficients were developed with idealized Gaussian variables in mind. When responses are binary, complications arise that impact standardization methods. In this paper, we review, evaluate, and propose new methods for standardizing coefficients from models that contain binary outcomes. We first consider the interpretability of unstandardized coefficients and then examine two main approaches to standardization. One approach, which we refer to as the latent‐theoretical (LT) method, assumes that underlying binary observations, there exists a latent, continuous propensity linearly related to the coefficients. A second approach, which we refer to as the observed‐empirical (OE) method, assumes responses are purely discrete and estimates error variance empirically via reference to a classical R2 estimator. We also evaluate the standard formula for calculating standardized coefficients based on standard deviations. Criticisms of this practice have been persistent, leading us to propose an alternative formula that is based on user‐defined “relevant ranges.” Finally, we implement all of the above in an open‐source package for the statistical software R. Results from simulation studies show that both the LT and OE methods of standardization support a similarly broad range of coefficient comparisons. The LT method estimates effects that reflect underlying latent‐linear propensities, while the OE method computes a linear approximation for the effects of predictors on binary responses. The contrast between assumptions for the two methods is reflected in persistently weaker standardized effects associated with OE standardization. Reliance on standard deviations for standardization (the traditional approach) is critically examined and shown to introduce substantial biases when predictors are non‐Gaussian. The use of relevant ranges in place of standard deviations has the capacity to place LT and OE standardized coefficients on a more comparable scale. As ecologists address increasingly complex hypotheses, especially those that comparing the influences of different controlling factors (e.g., top‐down vs. bottom‐up or biotic vs. abiotic controls), comparable coefficients become necessary for evaluations.

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Why Is Living Fast Dangerous? Disentangling the Roles of Resistance and Tolerance of Disease

Cited by 35 publications

References 79 publications

The Relationship between Host Lifespan and Pathogen Reservoir Potential: An Analysis in the System Arabidopsis thaliana-Cucumber mosaic virus

The Relationship between Host Lifespan and Pathogen Reservoir Potential: An Analysis in the System Arabidopsis thaliana-Cucumber mosaic virus

Behavioural phenotypes predict disease susceptibility and infectiousness

Quantifying relative importance: computing standardized effects in models with binary outcomes

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