Menges, E. S. | Search bioRxiv

bioRxiv2020

Understanding how an amphicarpic species with a mixed mating system responds to fire: a population genetic approach

Amphicarphic species produce both aboveground and belowground seeds; the belowground seeds have been proposed to be an adaptation to disturbed sites because they are protected belowground, enabling them to persist and recolonize a site after disturbance. However, it is unknown whether such seeds indeed serve as the main colonizers after a disturbance. The amphicarpic species Polygala lewtonii is endemic to fire-prone Florida sandhill and scrub and is among only a few species with three flower types (aboveground chasmogamous flowers and both above and belowground cleistogamous flowers). The goal of this study was to understand whether recolonization of sites by P. lewtonii was accomplished primarily through germination of belowground seed. First, we quantified the outcrossing rate in seeds produced by aboveground chasmogamous flowers to determine whether we could detect differences in colonization of between seeds produced aboveground vs. belowground. Approximately 25% of seeds from aboveground chasmogamous flowers showed evidence of cross pollination and the seeds showed greater heterozygosity and lower inbreeding coefficients than pure selfing, indicating that it is possible to differentiate between selfed and non-selfed seed types in postfire colonization. Second, we analyzed genetic diversity, inbreeding, and genetic structure of the populations before and after a prescribed fire. If heterozygosity and admixture increased, and spatial population genetic structure and inbreeding decreased, this would indicate that fire promoted germination of outcrossed seed from aboveground flowers. However, inbreeding increased and spatial genetic structure and admixture decreased after fire, suggesting that selfed seed produced by belowground flowers predominantly recolonized the site after fire. Thus, amphicarpy is a powerful adaptation to fire-maintained environments by producing seeds that are well suited to the range of conditions presented by a highly variable, disturbance prone habitat.

plant biology↗

bioRxiv2017

Exploring population responses to environmental change when there’s never enough data; a factor analytic approach

O_LITemporal variability in the environment drives variation in individuals vital rates, with consequences for population dynamics and life history evolution. Integral projection models (IPMs) are data-driven models widely used to study population dynamics and life history evolution of structured populations in temporally variable environments. However, many data sets have insufficient temporal replication for the environmental drivers of vital rates to be identified with confidence, limiting their use for evaluating population level responses to environmental change.\nC_LIO_LIParameter selection, where the kernel is constructed at each time step by randomly selecting the time-varying parameters from their joint probability distribution, is one approach to including stochasticity in IPMs. We consider a factor analytic (FA) approach for modelling the covariance matrix of time-varying parameters, whereby latent variable(s) describe the covariance among vital rate parameters. This decreases the number of parameters to estimate and, where the covariance is positive, the latent variable can be interpreted as a measure of environmental quality. We demonstrate this using simulation studies and two case studies.\nC_LIO_LIThe simulation studies suggest the FA approach provides similarly accurate estimates of stochastic population growth rate to estimating an unstructured covariance matrix. We demonstrate how the latent parameter can be perturbed to show how selection on reproductive delays in the monocarp Carduus nutans changes under different environmental conditions. We develop a demographic model of the fire dependent herb Eryngium cuneifolium to show how a causal indicator (i.e. a driver of the changes in the environmental quality) can be incorporated with the addition of a single parameter. Using perturbation analyses we determine optimal management strategies for this species.\nC_LIO_LIThis approach estimates fewer parameters than previous approaches and allows novel eco-evolutionary insights. Predictions on population dynamics and life history evolution under different environmental conditions can be made without necessarily identifying causal factors. Environmental drivers can be incorporated with relatively few parameters, allowing for predictions on how populations will be affected by changes to these drivers.\nC_LI

ecology↗