Search

Coevolution is one of the major drivers of complex dynamics in population ecology. Historically, antagonistic coevolution in victim‐exploiter systems has been a topic of special interest, and involves traits with various genetic architectures (e.g., the number of genes involved) and effects on interactions. For example, exploiters may need to have traits that "match" those of victims for successful exploitation (i.e., a matching interaction), or traits that exceed those of victims (i.e., a difference interaction). Different models exist which are appropriate for different types of traits, including Mendelian (discrete) and quantitative (continuous) traits. For models with multiple Mendelian traits, recent studies have shown that antagonistic coevolutionary patterns that appear as matching interactions can arise due to multiple difference interactions with costs of having large trait values. Here we generalize their findings to quantitative traits and show, analogously, that the multidimensional difference interactions with costs sometimes behave qualitatively the same as matching interactions. While previous studies in quantitative genetics have used the dichotomy between matching and difference frameworks to explore coevolutionary dynamics, we suggest that exploring multidimensional trait space is important to examine the generality of results obtained from one‐dimensional traits. [ABSTRACT FROM AUTHOR]

Understanding fluctuating selection is important for our understanding of patterns of spatial and temporal diversity in nature. Host-parasite theory has classically assumed fluctuations either occur between highly specific genotypes (matching allele: MA) or from specialism to generalism (gene-for-gene: GFG). However, while MA can only generate one mode of fluctuating selection, we show that GFG can in fact produce both rapid 'within-range' fluctuations (among genotypes with identical levels of investment but which specialise on different subsets of the population) and slower cycling 'between ranges' (different levels of investment), emphasising that MA is a subset of GFG. Our findings closely match empirical observations, although sampling rates need to be high to detect these novel dynamics empirically. Within-range cycling is an overlooked process by which fluctuating selection can occur in nature, suggesting that fluctuating selection may be a more common and important process than previously thought in generating and maintaining diversity. [ABSTRACT FROM AUTHOR]

Host-parasite infection genetics can be more complex than envisioned by classic models such as the gene-for-gene or matching-allele models. By means of a mathematical model, I investigate the coevolutionary dynamics arising from a large set of generalized models of infection genetics in which hosts are either fully resistant or fully susceptible to a parasite, depending on the genotype of both individuals. With a single diploid interaction locus in the hosts, many of the infection genetic models produce stable or neutrally stable genotype polymorphisms. However, only a few models, which are all different versions of the matching-allele model, lead to sustained cycles of genotype frequency fluctuations in both interacting species ("Red Queen" dynamics). By contrast, with two diploid interaction loci in the hosts, many infection genetics models that cannot be classified as one of the standard infection genetics models produce Red Queen dynamics. Sexual versus asexual reproduction and, in the former case, the rate of recombination between the interaction loci have a large impact on whether Red Queen dynamics arise from a given infection genetics model. This may have interesting but as yet unexplored implications with respect to the Red Queen hypothesis for the evolution of sex. [ABSTRACT FROM AUTHOR]

The Red Queen hypothesis (RQH) predicts that parasite-mediated selection will maintain sexual individuals in the face of competition from asexual lineages. The prediction is that sexual individuals will be difficult targets for coevolving parasites if they give rise to more genetically diverse offspring than asexual lineages. However, increasing host genetic diversity is known to suppress parasite spread, which could provide a short-term advantage to clonal lineages and lead to the extinction of sex. We test these ideas using a stochastic individual-based model. We find that if parasites are readily transmissible, then sex is most likely to be maintained when host diversity is high, in agreement with the RQH. If transmission rates are lower, however, we find that sexual populations are most likely to persist for intermediate levels of diversity. Our findings thus highlight the importance of genetic diversity and its impact on epidemiological dynamics for the maintenance of sex by parasites. [ABSTRACT FROM AUTHOR]

There is typically considerable variation in the level of infectivity of parasites and the degree of resistance of hosts within populations. This trait variation is critical not only to the evolutionary dynamics but also to the epidemiology, and potentially the control of infectious disease. However, we lack an understanding of the processes that generate and maintain this trait diversity. We examine theoretically how epidemiological feedbacks and the characteristics of the interaction between host types and parasites strains determine the coevolution of host-parasite diversity. The interactions include continuous characterizations of the key phenotypic features of classic gene-for-gene and matching allele models. We show that when there are costs to resistance in the hosts and infectivity in the parasite, epidemiological feedbacks may generate diversity but this is limited to dimorphism, often of extreme types, in a broad range of realistic infection scenarios. For trait polymorphism, there needs to be both specificity of infection between host types and parasite strains as well as incompatibility between particular strains and types. We emphasize that although the high specificity is well known to promote temporal 'Red Queen' diversity, it is costs and combinations of hosts and parasites that cannot infect that will promote static trait diversity. [ABSTRACT FROM AUTHOR]

The genetic basis of infection in host-parasite interactions has traditionally been considered within the framework of either gene-for-gene (GFG) or matching-allele models. We present an alternative model, termed inverse-gene-for-gene (IGFG), where pathogen infectiousness is determined by parasite recognition of host signals and/or receptors or where there is active host searching by parasites. We show that coevolutionary dynamics under IGFG are both qualitatively and quantitatively different from those of the GFG model, and we suggest that this new approach may be applicable to a range of important host-parasite systems that are not currently catered for by the existing frameworks. [ABSTRACT FROM AUTHOR]