Host-feeding strategies of parasitoid wasps

Summary Three models of the evolution of host-feeding behaviour in parasitoid wasps are developed. The first assumes that the wasp host feeds purely to obtain resources to mature eggs (limited resource model) while the second assumes that host feeding provides energy for maintenance (pro-ovigenic model). The third model assumes that host feeding provides resources for both maintenance and egg maturation (resource pool model). Two variants of the third model are examined: the first assumes that the risk of mortality is constant and state-independent, the second that resource-depleted individuals suffer a higher risk of mortality. The models are analysed using a combination of stochastic dynamic programming and analytical techniques. The models make different predictions about the relationships between the probability of host feeding and egg load and host density. The available experimental evidence best supports the resource pool model.     

A Stochastic Process and Generalized Distributions for the Study of Oviposition Evolution of a Parasite

This paper considers a generalized birth process {X^m(t), t > 0} and presents a new stochastic model for the number of eggs laid by a parasite on a host. Also, given an underlying distribution for the number of visits between parasites and a host, this distribution is generalized by the distribution of the number of eggs per visit laid on the host. If a certain number of eggs are already present on the host, a parasite such as a Japanese weevil, may avoid oviposition in subsequent visits (see JANARDAN (1980)) to the same host. A class of generalized distributions are presented to model such situations. The case of a single egg laying parasite and a Poisson distribution for the number of visits of the parasite to the same host yields a distribution of particular interest. In order to develop this model, certain lemmas are derived. Finally a characteristic property of this stochastic model is presented.     

Estimation of Parameters for Macroparasite Population Evolution Using Approximate Bayesian Computation

Summary We estimate the parameters of a stochastic process model for a macroparasite population within a host using approximate Bayesian computation (ABC). The immunity of the host is an unobserved model variable and only mature macroparasites at sacrifice of the host are counted. With very limited data, process rates are inferred reasonably precisely. Modeling involves a three variable Markov process for which the observed data likelihood is computationally intractable. ABC methods are particularly useful when the likelihood is analytically or computationally intractable. The ABC algorithm we present is based on sequential Monte Carlo, is adaptive in nature, and overcomes some drawbacks of previous approaches to ABC. The algorithm is validated on a test example involving simulated data from an autologistic model before being used to infer parameters of the Markov process model for experimental data. The fitted model explains the observed extra‐binomial variation in terms of a zero‐one immunity variable, which has a short‐lived presence in the host.     

Host-feeding and oviposition by parasitoids on hosts of different fitness value: Influences of egg load and encounter rate

A dynamic optimization model is presented for the decision to host feed or oviposit on hosts by female parasitoids. Optimal host utilization decisions are compared between two host types with different fitness payoffs for oviposition. The model predicts that hosts of higher fitness value should always be used for oviposition unless the egg load approaches zero. This general prediction is not influenced by levels of host availability or metabolic reserves, the age of the parasitoid, or the magnitude of the fitness difference. An egg-load threshold is predicted above which lower value hosts should be used for oviposition and below which they are used for host feeding. The position of this egg-load threshold is higher when the difference in fitness between host types is larger. The threshold is also higher when overall host availability is high or metabolic reserves for the production of new eggs are low. The threshold for oviposition on low-value hosts decreases to zero near the end of the parasitoid’s life. Under conditions where high-value hosts are rarely encountered compared to low-value hosts, the model predicts that lower value hosts should be accepted for oviposition at a lower egg-load threshold.     

A simple model of host-parasitoid interaction with host-feeding

Summary A simple mathematical model of host-parasitoid interaction with host-feeding was presented with special reference to the system of the greenhouse whitefly and the parasitoidEncarsia formosa. In the model, when a parasitoid encounters a host, it has a choice between feeding the host and ovipositing one egg in the host. It was shown that an intermediate value of the feeding ratio of all attacks gives the minimum equilibrium host density and the minimum amplitudes of fluctuation in the densities of the two species. Computer simulations of a modified model with time lags also gave the similar results. The model suggested for natural enemy introduction program that parasitoid species with host-feeding habits are promising agents for effective controls for pest insects and that the timing of introduction is very important. By an evolutionary analysis, it was shown that the feeding ratio evolves to minimize the host density under natural selection among parasitoids.     

Combined effects of host quality and local mate competition on sex allocation inLariophagus distinguendus

Summary Many parasitoid wasps are known to adjust sex ratio in response to either local mate competition (LMC) or host quality. Nevertheless, few studies have investigated the combined effects of these two factors on sex allocation. The sex allocation pattern inLariophagus distinguendus, a parasitoid of granary weevil larvae, is contrasted to the expectations of Werren's (1984) model combining LMC and host quality. Several predictions of the model are confirmed, but others are not. Sex ratio on both large and small hosts declines with proportion of small hosts attacked in a manner consistent with the model. However, when only one host size is parasitized, sex ratio is not independent of that host size, as predicted by the model. Various possibilities for the deviation between expected and observed are discussed. A partial LMC/host quality model is developed which allows for some matings outside the natal patch, and predictions of this model conform more closely to the pattern observed inL. distinguendus. Finally, the application of parasitoid studies to basic questions in evolutionary ecology is briefly discussed.     

Phylogenetic analysis reveals positive correlations between adaptations to diverse hosts in a group of pathogen‐like herbivores

A jack of all trades can be master of none—this intuitive idea underlies most theoretical models of host‐use evolution in plant‐feeding insects, yet empirical support for trade‐offs in performance on distinct host plants is weak. Trade‐offs may influence the long‐term evolution of host use while being difficult to detect in extant populations, but host‐use evolution may also be driven by adaptations for generalism. Here we used host‐use data from insect collection records to parameterize a phylogenetic model of host‐use evolution in armored scale insects, a large family of plant‐feeding insects with a simple, pathogen‐like life history. We found that a model incorporating positive correlations between evolutionary changes in host performance best fit the observed patterns of diaspidid presence and absence on nearly all focal host taxa, suggesting that adaptations to particular hosts also enhance performance on other hosts. In contrast to the widely invoked trade‐off model, we advocate a “toolbox” model of host‐use evolution in which armored scale insects accumulate a set of independent genetic tools, each of which is under selection for a single function but may be useful on multiple hosts.     

Multilocus models of sympatric speciation: Bush versus Rice versus Felsenstein

Abstract. In populations of phytophagous insects that use the host plant as a rendezvous for mating, divergence in host preference could lead to sympatric speciation. Speciation requires the elimination of "generalist" genotypes, that is, those with intermediate host preference. This could occur because such genotypes have an inherent fitness disadvantage, or because preference alleles become associated with alleles that are oppositely selected on the two hosts. Although the former mechanism has been shown to be plausible, the latter mechanism has not been studied in detail. I consider a multilocus model (the "Bush model") in which one set of biallelic loci affects host preference, and a second set affects viability on the hosts once chosen. Alleles that increase viability on one host decrease viability on the other, and all loci are assumed to be unlinked. With moderately strong selection on the viability loci, preference alleles rapidly become associated with viability alleles, and the population splits into two reproductively isolated host specialist populations. The conditions for speciation to occur in this model, as measured by the strength of selection required, are somewhat more stringent than in a model in which preference and viability are controlled by the same loci (one-trait model). In contrast, the conditions are much less stringent than in a model in which speciation requires buildup of associations between viability loci and loci controlling a host-independent assortative mating trait (canonical two-trait model). Moreover, in the one-trait model, and to a lesser extent the Bush model, the strength of selection needed to initiate speciation is only slightly greater than that needed to complete it. This indicates that documenting instances of sympatric species that are reproductively isolated only by host or habitat preference would provide evidence for the plausibility of sympatric speciation in nature.     

Coevolution of an avian host and its parasitic cuckoo

Abstract We use a quantitative genetic model to examine the coevolution of host and cuckoo egg characters (termed "size" as a proxy for general appearance), host discrimination, and host and cuckoo population dynamics. A host decides whether to discard an egg using a comparison of the sizes of the eggs in her nest, which changes as host and cuckoo eggs evolve. Specifically, we assume that the probability that she discards the largest egg in her nest depends on how much larger it is than the second largest egg. This decision rule (i.e., the acceptable difference in egg sizes) also evolves, changing both the chance of successful rejection of a cuckoo egg in parasitized nests and the chance of mistaken rejection of a host egg in both parasitized and unparasitized nests. We find a stable equilibrium for coexistence of the host and cuckoo where there is cuckoo egg mimicry, evolutionary displacement of the host egg away from the cuckoo egg phenotype, and host discrimination against unusual eggs. Both host discrimination and host egg displacement are fairly weak at the equilibrium. Cuckoo egg mimicry, although imperfect, usually evolves more extensively and quickly than the responses of the host. Our model provides evidence for both the evolutionary equilibrium and evolutionary lag hypotheses of host acceptance of parasitic eggs.     

A minimal model for multiple epidemics and immunity spreading

Pathogens and parasites are ubiquitous in the living world, being limited only by availability of suitable hosts. The ability to transmit a particular disease depends on competing infections as well as on the status of host immunity. Multiple diseases compete for the same resource and their fate is coupled to each other. Such couplings have many facets, for example cross-immunization between related influenza strains, mutual inhibition by killing the host, or possible even a mutual catalytic effect if host immunity is impaired. We here introduce a minimal model for an unlimited number of unrelated pathogens whose interaction is simplified to simple mutual exclusion. The model incorporates an ongoing development of host immunity to past diseases, while leaving the system open for emergence of new diseases. The model exhibits a rich dynamical behavior with interacting infection waves, leaving broad trails of immunization in the host population. This obtained immunization pattern depends only on the system size and on the mutation rate that initiates new diseases.     

HOST LIFE HISTORY AND THE EVOLUTION OF PARASITE VIRULENCE

Abstract.— We present a general epidemiological model of host‐parasite interactions that includes various forms of superinfection. We use this model to study the effects of different host life‐history traits on the evolution of parasite virulence. In particular, we analyze the effects of natural host death rate on the evolutionarily stable parasite virulence. We show that, contrary to classical predictions, an increase in the natural host death rate may select for lower parasite virulence if some form of superinfection occurs. This result is in agreement with the experimental results and the verbal argument presented by Ebert and Mangin (1997). This experiment is discussed in the light of the present model. We also point out the importance of superinfections for the effect of nonspecific immunity on the evolution of virulence. In a broader perspective, this model demonstrates that the occurrence of multiple infections may qualitatively alter classical predictions concerning the effects of various host life‐history traits on the evolution of parasite virulence.     

Discrete-time host–parasitoid models with pest control

We propose a simple discrete-time host–parasitoid model to investigate the impact of external input of parasitoids upon the host–parasitoid interactions. It is proved that the input of the external parasitoids can eventually eliminate the host population if it is above a threshold and it also decreases the host population level in the unique interior equilibrium. It can simplify the host–parasitoid dynamics when the host population practices contest competition. We then consider a corresponding optimal control problem over a finite time period. We also derive an optimal control model using a chemical as a control for the hosts. Applying the forward–backward sweep method, we solve the optimal control problems numerically and compare the optimal host populations with the host populations when no control is applied. Our study concludes that applying a chemical to eliminate the hosts directly may be a more effective control strategy than using the parasitoids to indirectly suppress the hosts.     

Artificial neural networks in models of specialization, guild evolution and sympatric speciation

Sympatric speciation can arise as a result of disruptive selection with assortative mating as a pleiotropic by-product. Studies on host choice, employing artificial neural networks as models for the host recognition system in exploiters, illustrate how disruptive selection on host choice coupled with assortative mating can arise as a consequence of selection for specialization. Our studies demonstrate that a generalist exploiter population can evolve into a guild of specialists with an 'ideal free' frequency distribution across hosts. The ideal free distribution arises from variability in host suitability and density-dependent exploiter fitness on different host species. Specialists are less subject to inter-phenotypic competition than generalists and to harmful mutations that are common in generalists exploiting multiple hosts.When host signals used as cues by exploiters coevolve with exploiter recognition systems, our studies show that evolutionary changes may be continuous and cyclic. Selection changes back and forth between specialization and generalization in the exploiters, and weak and strong mimicry in the hosts, where non-defended hosts use the host investing in defence as a model. Thus, host signals and exploiter responses are engaged in a red-queen mimicry process that is ultimately cyclic rather then directional. In one phase, evolving signals of exploitable hosts mimic those of hosts less suitable for exploitation (i.e. the model). Signals in the model hosts also evolve through selection to escape the mimic and its exploiters. Response saturation constraints in the model hosts lead to the mimic hosts finally perfecting its mimicry, after which specialization in the exploiter guild is lost. This loss of exploiter specialization provides an opportunity for the model hosts to escape their mimics. Therefore, this cycle then repeats.We suggest that a species can readily evolve sympatrically when disruptive selection for specialization on hosts is the first step. In a sexual reproduction setting, partial reproductive isolation may first evolve by mate choice being confined to individuals on the same host. Secondly, this disruptive selection will favour assortative mate choice on genotype, thereby leading to increased reproductive isolation.     

The evolution of parasite virulence, superinfection, and host resistance

We analyze the evolutionary consequences of host resistance (the ability to decrease the probability of being infected by parasites) for the evolution of parasite virulence (the deleterious effect of a parasite on its host). When only single infections occur, host resistance does not affect the evolution of parasite virulence. However, when superinfections occur, resistance tends to decrease the evolutionarily stable (ES) level of parasite virulence. We first study a simple model in which the host does not coevolve with the parasite (i.e., the frequency of resistant hosts is independent of the parasite). We show that a higher proportion of resistant host decreases the ES level of parasite virulence. Higher levels of the efficiency of host resistance, however, do not always decrease the ES parasite virulence. The implications of these results for virulence management (evolutionary consequences of public health policies) are discussed. Second, we analyze the case where host resistance is allowed to coevolve with parasite virulence using the classical gene-for-gene (GFG) model of host-parasite interaction. It is shown that GFG coevolution leads to lower parasite virulence (in comparison with a fully susceptible host population). The model clarifies and relates the different components of the cost of parasitism: infectivity (ability to infect the host) and virulence (deleterious effect) in an evolutionary perspective.     

Body-size scaling in an SEI model of wildlife diseases

A number of wildlife pathogens are generalist and can affect different host species characterized by a wide range of body sizes. In this work we analyze the role of allometric scaling of host vital and epidemiological rates in a Susceptible-Exposed-Infected (SEI) model. Our analysis shows that the transmission coefficient threshold for the disease to establish in the population scales allometrically (exponent = 0.45) with host size as well as the threshold at which limit cycles occur. In contrast, the threshold of the basic reproduction number for sustained oscillations to occur is independent of the host size and is always greater than 5. In the case of rabies, we show that the oscillation periods predicted by the model match those observed in the field for a wide range of host sizes.The population dynamics of the SEI model is also analyzed in the case of pathogens affecting multiple coexisting hosts with different body sizes. Our analyses show that the basic reproduction number for limit cycles to occur depends on the ratio between host sizes, that the oscillation period in a multihost community is set by the smaller species dynamics, and that intermediate interspecific disease transmission can stabilize the epidemic occurrence in wildlife communities.     

Optimal growth strategies of larval helminths in their intermediate hosts

We consider optimal growth of larval stages in complex parasite life cycles where there is no constraint because of host immune responses. Our model predicts an individual's asymptotic size in its intermediate host, with and without competition from conspecific larvae. We match observed variations in larval growth patterns in pseudophyllid cestodes with theoretical predictions of our model. If survival of the host is vital for transmission, larvae should reduce asymptotic size as intensity increases, to avoid killing the host. The life history strategy (LHS) model predicts a size reduction <1/intensity, thus increasing the parasite burden on the host. We discuss whether body size of competing parasites is an evolved LHS or simply reflects resource constraints (RC) on growth fixed by the host, leading to a constant total burden with intensity. Growth under competition appears comparable with "the tragedy of the commons", much analysed in social sciences. Our LHS prediction suggests that evolution generates a solution that seems cooperative but is actually selfish.     

Parasite strain coexistence in a heterogeneous host population

Heterogeneity in host susceptibility and transmissibility to parasite attack allows a lower transmission rate to sustain an epidemic than is required in homogeneous host populations. However, this heterogeneity can leave some hosts with little susceptibility to disease, and at high transmission rates, epidemic size can be smaller than for diseases where the host population is homogeneous. In a heterogeneous host population, we model natural selection in a parasite population where host heterogeneity is exploited by different strains to varying degrees. This partitioning of the host population allows coexistence of competing parasite strains, with the heterogeneity-exploiting strains infecting the more susceptible hosts, in the absence of physiological tradeoffs and spatial heterogeneity, and even for markedly different transmission rates. In our model, intermediate-strategy parasites were selected against: should coexistence occur, an equilibrium is reached where strains occupied only the extreme ends of trait space, under appropriate conditions selecting for lower R₀.