Temporal and Spatial Changes in a Metapopulation of the Rust Pathogen Triphragmium Ulmariae and its Host, Filipendula Ulmaria

Burdon, Jeremy J.; Ericson, Lars; Müller, W. J.

doi:10.2307/2261179

Cited by 89 publications

(114 citation statements)

References 19 publications

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“…This result is consistent with the findings of Condeso and Meentemeyer (2007) that landscape heterogeneity of host vegetation influences pathogen inoculum load. The relationship between woodland area and disease is also consistent with other epidemiological studies of interactions between the size of host populations and rates of infection (Burdon et al 1995, Thrall et al 2003. Large areas of host vegetation may also increase colonization rates by providing larger areas for interception of wind-blown spores than smaller ones (Burdon 1987, Condeso andMeentemeyer 2007).…”

Section: Discussionsupporting

confidence: 85%

Influence of Land-Cover Change on the Spread of an Invasive Forest Pathogen

Meentemeyer

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et al. 2008

Ecological Applications

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Abstract. Human-caused changes in land use and land cover have dramatically altered ecosystems worldwide and may facilitate the spread of infectious diseases. To address this issue, we examined the influence of land-cover changes between 1942 and 2000 on the establishment of an invasive pathogen, Phytophthora ramorum, which causes the forest disease known as Sudden Oak Death. We assessed effects of land-cover change, forest structure, and understory microclimate on measures of inoculum load and disease prevalence in 102 15 3 15 m plots within a 275-km 2 region in northern California. Within a 150 m radius area around each plot, we mapped types of land cover (oak woodland, chaparral, grassland, vineyard, and development) in 1942 and 2000 using detailed aerial photos. During this 58-year period, oak woodlands significantly increased in area by 25%, while grassland and chaparral decreased by 34% and 51%, respectively. Analysis of covariance revealed that vegetation type in 1942 and woodland expansion were significant predictors of pathogen inoculum load in bay laurel (Umbellularia californica), the primary inoculum-producing host for P. ramorum in mixed evergreen forests. Path analysis showed that woodland expansion resulted in larger forests with higher densities of the primary host trees (U. californica, Quercus agrifolia, Q. kelloggii) and cooler understory temperatures. Together, the positive effects of woodland size and negative effects of understory temperature explained significant variation in inoculum load and disease prevalence in bay laurel; host stem density had additional positive effects on inoculum load. We conclude that enlargement of woodlands and closure of canopy gaps, likely due largely to years of fire suppression, facilitated establishment of P. ramorum by increasing the area occupied by inoculum-production foliar hosts and enhancing forest microclimate conditions. Epidemiological studies that incorporate land-use change are rare but may increase understanding of disease dynamics and improve our ability to manage invasive forest pathogens.

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Section: Discussionsupporting

confidence: 85%

Influence of Land-Cover Change on the Spread of an Invasive Forest Pathogen

Meentemeyer

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et al. 2008

Ecological Applications

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“…habitat heterogeneity, metapopulation) substantially affect parasite transmission, thereby violating the assumption of a homogeneously (i.e. randomly) mixed system (Grosholz 1993;Burdon et al 1995;Fromont et al 1998;Lopez et al 2005). Additionally, the host's immune system may buffer against the initial increase in parasite abundance up to a certain point, depending on the (genetically based) immunological heterogeneity of the host and the initial parasite inoculum (Antia et al 1994;Antia & Lipsitch 1997;Leite et al 2000).…”

Section: Introductionmentioning

confidence: 99%

A quantitative test of the relationship between parasite dose and infection probability across different host–parasite combinations

2008

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Epidemiological models generally assume that the number of susceptible individuals that become infected within a unit of time depends on the density of the hosts and the concentration of parasites (i.e. mass-action principle). However, empirical studies have found significant deviations from this assumption due to biotic and abiotic factors, such as seasonality, the spatial structure of the host population and host heterogeneity with respect to immunity and susceptibility. In this paper, we examine the effect of the dose level of the bacterial endoparasite Pasteuria ramosa on the infection rate of its host, the water flea Daphnia magna. Using seven host clones and two parasite isolates, we measure the fraction of infected hosts after exposure to eight different parasite doses to determine whether there is variation in the infection process across different host clone-parasite isolate combinations. In five combinations, a pronounced dose-dependent infection pattern was found. Using a likelihood approach, we compare the infection data of these five combinations to the fit of three mathematical models: a mass-action model, a parasite antagonism model (i.e. an increase in the parasite dose leads to an under-proportionate increase in the infection rate per host) and a heterogeneous host model. We found that the host heterogeneity model, in which we assumed the existence of non-inherited phenotypic differences in host susceptibilities to the parasite, provides the best fit. Our analysis suggests that among 5 out of the 14 host clone-parasite isolate combinations that resulted in appreciable infections, non-genetic host heterogeneity plays an important role.

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“…Janzen (1980), coevolution refers to how two species evolve in response to each other, without regard to the time scale of evolutionary dynamics or the impact of evolutionary changes on ecological aspects like population dynamics), several recent studies have shown that plant-pathogen coevolution and local adaptation can be rapid ( (Burdon 1987(Burdon , 1993Antonovics et al 1994;Thrall and Burdon 1999;Burdon and Thrall 2013). To explain what happens in local populations, pathologists have expanded their scope and explored processes at the metapopulation scale like gene flow and extinction-colonization dynamics (Jarosz and Burdon 1991;Carlsson and Elmqvist 1992;Antonovics et al 1994;Burdon et al 1995;Ericson et al 1999;Thrall et al 2001;Petrželová and Lebeda 2004;Laine and Hanski 2006). In such spatially structured environments, we may expect local adaptation to emerge as a result of plant-pathogen coevolution (Kaltz and Shykoff 1998).…”

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confidence: 99%

Spatial eco-evolutionary feedback in plant-pathogen interactions

Tack

Laine

2013

Eur J Plant Pathol

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In recent years the potential for evolutionary change to drive ecological dynamics, and vice versa, has been widely recognized. However, the convincing examples of eco-evolutionary dynamics mainly stem from highly artificial experimental systems, with conspicuously few examples contributed by field systems. While rarely considered in the eco-evolutionary literature, the genefor-gene hypothesis inherently recognizes the tight link between evolutionary and ecological dynamics. The boom-and-bust dynamics of some agricultural pathogens are an extreme demonstration of this. In this perspective, we place plant-pathogen systems in a spatial ecoevolutionary framework, which recognizes that ecology and evolution are tightly linked, take place at the same time scale and are strongly influenced by spatial structure. Specifically, we i) exemplify how the ecological process of dispersal modifies rapid local coevolutionary dynamics and thereby shapes spatial variation in resistance, infectivity, and local adaptation; and ii) illustrate how the outcome of coevolution (spatial distribution in resistance, infectivity and local adaptation) drives ecological metapopulation processes. Overall, we conclude that both agricultural and wild pathosystems provide a unique illustration of the high relevance of spatial eco-evolutionary feedback in understanding species interactions. 3 Eco-evolutionary dynamicsThe potential for eco-evolutionary feedback loops in determining the dynamics of populations has been increasingly recognized in recent years Post and Palkovacs 2009;Schoener 2011;Ellner 2013;Reznick 2013). This feedback is comprised of two pathways: the ecology-to-evolution pathway, where ecological change generates genetic and phenotypic responses (natural selection); and the evolution-to-ecology pathway, where genetic and phenotypic change affects ecological quantities, often measured as the population growth rate. However, while the potential of species to adapt to ecological conditions has long been realized, the effect of rapid evolutionary change on ecological dynamics is still poorly understood. In part, this is due to the fact that traditionally evolution has been viewed as a slow process operating at a timescale that is very different from ecological time (Slobodkin 1961;Hutchinson 1965). From such a perspective, ecological dynamics would play out as if evolution was not occurring, as evolutionary change would be non-significant on the ecological time-scale. Likewise, short-term fluctuations in ecological variables would average out over evolutionary time-scales, and only the long-term average would affect evolution (Hairston et al. 2005). However, it is becoming increasingly clear that evolutionary change can be extremely rapid, and there are compelling examples of this in a diversity of traits ranging from life-histories to behaviour and physiology (as reviewed in Thompson 2013). Moreover, a rapidly increasing number of studies suggest that eco-evolutionary dynamics and feedbacks have the potential to play a promin...

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Temporal and Spatial Changes in a Metapopulation of the Rust Pathogen Triphragmium Ulmariae and its Host, Filipendula Ulmaria

Cited by 89 publications

References 19 publications

Influence of Land-Cover Change on the Spread of an Invasive Forest Pathogen

Influence of Land-Cover Change on the Spread of an Invasive Forest Pathogen

A quantitative test of the relationship between parasite dose and infection probability across different host–parasite combinations

Spatial eco-evolutionary feedback in plant-pathogen interactions

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