The Dynamical Consequences of Developmental Variability and Demographic Stochasticity for Host-Parasitoid Interactions

Wearing,; Rohani,; Cameron,; Sait,

doi:10.2307/3473402

Cited by 9 publications

(10 citation statements)

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“…For 1% of the transmission events, the pathogen virulence mutates within Ϫ0.2 and 0.2 units, with a uniform probability for all values within that range. For a detailed account of the conversion of a deterministic model into a stochastic simulation using the Gillespie algorithm, see Wearing et al (2004).…”

Section: Stochastic Simulation Of Coevolving Contact and Virulencementioning

confidence: 99%

Higher Disease Prevalence Can Induce Greater Sociality: A Game Theoretic Coevolutionary Model

et al. 2005

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Abstract. There is growing evidence that communicable diseases constitute a strong selective force on the evolution of social systems. It has been suggested that infectious diseases may determine upper limits of host sociality by, for example, inducing territoriality or early juvenile dispersal. Here we use game theory to model the evolution of host sociality in the context of communicable diseases. Our model is then augmented with the evolution of virulence to determine coevolutionarily stable strategies of host sociality and pathogen virulence. In contrast to a controversial hypothesis by Ewald (1994), our analysis indicates that pathogens may become more virulent when contact rates are low, and their prevalence can ultimately induce greater sociality.

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Section: Stochastic Simulation Of Coevolving Contact and Virulencementioning

confidence: 99%

Higher Disease Prevalence Can Induce Greater Sociality: A Game Theoretic Coevolutionary Model

et al. 2005

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“…Considering that Venturia selectively parasitise the largest larvae (Sait et al 1995, 1997), it is well documented that larger Plodia larvae are stronger, more aggressive competitors and asymmetric competition is important in driving the population dynamics observed in closed experimental populations (Sait et al 1994, Bjørnstad et al 1998, Briggs et al 2000, Wearing et al 2004a,b). Parasitised larvae may then be competitively dominant in fighting bouts over healthy larvae due to their larger size, rather than their infective state.…”

Section: Discussionmentioning

confidence: 99%

A koinobiont parasitoid mediates competition and generates additive mortality in healthy host populations

Cameron

Wearing²,

Rohani³

et al. 2005

Oikos

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Insects are subject to attack from a range of natural enemies. Many natural enemies, such as parasitoids, do not immediately, or ever, kill their victims but they are nevertheless important in structuring biological communities. The lag that often occurs between attack and host death results in mixed populations of healthy and parasitised hosts. However, little is understood about how the effects of parasitism during this lag period affect the competitive ability of parasitised hosts and how this, in turn, affects the survival and dynamics of the surviving healthy host populations. Here we investigate the impact of the timing of introduction, and the strength of that introduction, of a parasitoid natural enemy Venturia canescens (Gravenhorst) on the outcome of intraspecific competition between larvae of the Indian meal moth, Plodia interpunctella (Hübner). In contrast to healthy hosts alone, we find reduced survival of healthy larvae with increasing periods of exposure to greater numbers of parasitised conspecifics. This represents indirect mortality of the host, which is in addition to that imposed by parasitism itself. Furthermore, longer periods of exposure to parasitised larvae resulted in an increase in development time of healthy individuals and they were larger when they emerged as adults. These results are relevant to both insect–parasitoid and insect–pathogen systems where there is a lag in host death following infection or attack.

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“…; Wearing et al . ). However, the distributions of stage durations created by virtual stages are limited to independent gamma distributions.…”

Section: Three Traditions Of Stage‐structured Modellingmentioning

confidence: 97%

The importance of individual developmental variation in stage‐structured population models

et al. 2014

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Population stage structure is fundamental to ecology, and models of this structure have proven useful in many different systems. Many ecological variables other than stage, such as habitat type, site occupancy and metapopulation status are also modelled using transitions among discrete states. Transitions among life stages can be characterised by the distribution of time spent in each stage, including the mean and variance of each stage duration and within-individual correlations among multiple stage durations. Three modelling traditions represent stage durations differently. Matrix models can be derived as a long-run approximation from any distribution of stage durations, but they are often interpreted directly as a Markov model for stage transitions. Statistical stage-duration distribution models accommodate the variation typical of cohort development data, but such realism has rarely been incorporated in population theory or statistical population models. Delay-differential equation models include lags but no variation, except in limited cases. We synthesise these models in one framework and illustrate how individual variation and correlations in development can impact population growth. Furthermore, different development models can yield the same long-term matrix transition rates but different sensitivities and elasticities. Finally, we discuss future directions for estimating realistic stage duration models from data.

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The Dynamical Consequences of Developmental Variability and Demographic Stochasticity for Host-Parasitoid Interactions

Cited by 9 publications

References 0 publications

Higher Disease Prevalence Can Induce Greater Sociality: A Game Theoretic Coevolutionary Model

Higher Disease Prevalence Can Induce Greater Sociality: A Game Theoretic Coevolutionary Model

A koinobiont parasitoid mediates competition and generates additive mortality in healthy host populations

The importance of individual developmental variation in stage‐structured population models

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