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For decades, mathematical models have been used to understand the course and outcome of malaria infections (i.e., infection dynamics) and the evolutionary dynamics of the parasites that cause them. A key conclusion of these models is that red blood cell (RBC) availability is a fundamental driver of infection dynamics and parasite trait evolution. The extent to which this conclusion holds will in part depend on model assumptions about the host-mediated processes that regulate RBC availability i.e., removal of uninfected RBCs and supply of RBCs. Diverse mathematical functions have been used to describe host-mediated RBC supply and clearance, but it remains unclear whether they adequately capture the dynamics of RBC supply and clearance during infection. Here, we use a unique dataset, comprising time-series measurements of erythrocyte (i.e., mature RBC) and reticulocyte (i.e., newly supplied RBC) densities during Plasmodium chabaudi malaria infection, and a quantitative data-transformation scheme to elucidate whether RBC dynamics conform to common model assumptions. We found that RBC clearance and supply are not well described by mathematical functions commonly used to model these processes. Furthermore, the temporal dynamics of both processes vary with parasite growth rate in a manner again not captured by existing models. Together, these finding suggest that new model formulations are required if we are to explain and ultimately predict the within-host population dynamics and evolution of malaria parasites.

As a corollary to the Red Queen hypothesis, host-parasite coevolution has been hypothesized to maintain genetic variation in both species. Recent theoretical work, however, suggests that reciprocal natural selection alone is insufficient to maintain variation at individual loci. As highlighted by our brief review of the theoretical literature, models of host-parasite coevolution often vary along multiple axes (e.g. inclusion of ecological feedbacks or abiotic selection mosaics), complicating a comprehensive understanding of the effects of interacting evolutionary processes on diversity. Here we develop a series of comparable models to explore the effect of interactions between spatial structures and antagonistic coevolution on genetic diversity. Using a matching alleles model in finite populations connected by migration, we find that, in contrast to panmictic populations, coevolution in a spatially structured environment can maintain genetic variation relative to neutral expectations with migration alone. These results demonstrate that geographic structure is essential for understanding the effect of coevolution on biological diversity., (© 2023 The Authors. Journal of Evolutionary Biology published by John Wiley & Sons Ltd on behalf of European Society for Evolutionary Biology.)

Inferring biological processes from population dynamics is a common challenge in ecology, particularly when faced with incomplete data. This challenge extends to inferring parasite traits from within-host infection dynamics. We focus on rodent malaria infections ( Plasmodium berghei ), a system for which previous work inferred an immune-mediated extension in the length of the parasite development cycle within red blood cells. By developing a system of delay-differential equations to describe within-host infection dynamics and simulating data, we demonstrate the potential to obtain biased estimates of parasite (and host) traits when key biological processes are not considered. Despite generating infection dynamics using a fixed parasite developmental cycle length, we find that known sources of measurement bias in parasite stage and abundance data can affect estimates of parasite developmental duration, with stage misclassification driving inferences about extended cycle length. We discuss alternative protocols and statistical methods that can mitigate such misestimation.

Premise: The ecological outcomes of mutualism are well known to shift across abiotic or biotic environments, but few studies have addressed how different environments impact evolutionary responses, including the intensity of selection on and the expression of genetic variance in key mutualism-related traits., Methods: We planted 30 maternal lines of the legume Medicago lupulina in four field common gardens and compared our measures of selection on and genetic variance in nodulation, a key trait reflecting legume investment in the symbiosis, with those from a previous greenhouse experiment using the same 30 M. lupulina lines., Results: We found that both the mean and genetic variance for nodulation were much greater in the greenhouse than in the field and that the form of selection on nodulation significantly differed across environments. We also found significant genotype-by-environment (G × E) effects for fitness-related traits that were generated by differences in the rank order of plant lines among environments., Conclusions: Overall, our results suggest that the expression of genotypic variation and selection on nodulation differ across environments. In the field, significant rank-order changes for plant fitness potentially help maintain genetic variation in natural populations, even in the face of directional or stabilizing selection., (© 2020 Botanical Society of America.)

Pollen is generally dispersed over short distances, which promotes population genetic structure across continuous two-dimensional space. Quantitative genetic variance in flowering time structures mating pools in the temporal dimension, at least with respect to the phenology loci. We asked if these two phenomena, isolation by distance (IBD) and isolation by phenology (IBP), synergistically promote genetic structure. We constructed an individual-based model that tracked genotype frequencies at flowering time and neutral loci across a uniform landscape, over multiple generations, under four mating schemes: panmixia, IBD only, IBP only, and IBP × IBD. IBD × IBP divided the population into spatial clusters of early-, mid-, and late-flowering genotypes and strongly increased its quantitative genetic variance. Flowering time did not cluster under IBP, but its genetic variance increased moderately. IBD induced mild spatial structure in a nonassortative reference trait but did not change its variance. Importantly, the spatial correlation of genotypes at neutral loci was twice as strong under IBD × IBP compared with IBD alone. IBD × IBP also drew neutral loci into gametic disequilibrium with flowering time loci, structuring them temporally. Temporal and spatial mating pool structure promotes local differentiation. This trend would facilitate adaptation on small spatial scales., (© 2019 The Authors. New Phytologist © 2019 New Phytologist Trust.)

Coexpression of genes in plant sporophytes and gametophytes allows correlated gametic and sporophytic selection. Theory predicts that, under outcrossing, an allele conferring greater pollen competitive ability should fix within a population unless antagonistic pleiotropy with the sporophyte stage is strong. However, under strong selfing, pollen competitiveness is immaterial as superior and inferior competitors are deposited on opposite stigmas, producing assortative competition. Because many plant species have mixed-mating systems, selfing should be critical in the spread and maintenance of pollen-expressed genes affecting competitiveness. We present two one-locus, two-allele population genetic models for the evolution of a locus controlling pleiotropic antagonism between pollen competitiveness and diploid fitness. Analytical solutions provide minimum and maximum selfing rates allowing invasion of alleles with greater diploid and haploid fitness, respectively. Further, polymorphism is only maintained when diploid selection is recessive. Fixation of the allele conferring greater pollen competitiveness may be prevented, even with weak sporophytic counterselection, with sufficiently high selfing. Finally, selfing expands and limits the range of haploid-diploid selection coefficients allowing polymorphism, depending on dominance and selfing mode., (© 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.)