POPULATION STRUCTURE ALONG A STEEP ENVIRONMENTAL GRADIENT: CONSEQUENCES OF FLOWERING TIME AND HABITAT VARIATION IN THE SNOW BUTTERCUP, RANUNCULUS ADONEUS

Abstract

Few studies have determined how gene flow and selection interact to generate population genetic structure in heterogeneous environments. One way to identify the potential role played by natural selection is to compare patterns of spatial genetic structure between different life cycle stages and among microenvironments. We examined patterns of spatial structure in a population of the snow buttercup (Ranunculus adoneus), using both adult plants and newly emerged seedlings. The study population spans a steep environmental gradient caused by gradual melting of snow within a permanent snowbed. Early-melting sites are characterized by denser vegetation, more fertile soils, and a longer growing season than late-melting sites tens of meters away. The flowering time of R. adoneus is controlled entirely by time of snowmelt, so the contiguous population is phenologically substructured into a series of successively flowering cohorts, reducing the opportunity for direct pollen transfer between early- and late-melting sites. For four highly polymorphic enzyme loci in this tetraploid species, there was subtle, but statistically significant, genetic differentiation between early, middle, and late-melting cohorts; adults usually showed greater differentiation among snowmelt zones than did seedlings. At two loci in adults and one locus in seedlings, homozygotes were more common than predicted at Hardy-Weinberg equilibrium, even when assuming maximum levels of double reduction during meiosis. This pattern suggests the occurrence of self-fertilization and/or population substructure. To determine how spatial isolation and phenological separation each contribute to genetic substructure, we used bivariate regression models to predict the numbers of allele differences between randomly paired individuals as a function of meters separation in space and days separation in flowering time. For newly emerged seedlings, we found that spatial separation was positively associated with genetic difference, but that the additional contribution of phenological separation to genetic difference was not significant. This implies that seeds and/or pollen move effectively across the snowmelt gradient, despite differences in flowering time. As was true for seedlings, spatial separation between paired adults contributed to greater genetic difference, but for a given spatial separation, the genetic difference between adult plants was reduced by phenological separation. This result implies that postemergence selection is favoring at least some seeds that migrate across the snowmelt gradient. Directional gene flow across the snowmelt gradient probably results from a genetic source-sink interaction, that is, the colonization of ecologically marginal late-melting sites by high quality seeds produced by the larger subpopulation in early-melting sites. Effective gene flow from high to low quality microenvironments is likely to impede adaptation to late-melting locations.

Genetic Fingerprint-Inferred Population Subdivision and Spatial Genetic Tests for Isolation by Distance and Adaptation in the Coastal Plant Limonium carolinianum

“…Transplant data indicate that this genetic similarity across local environments is not due to local adaptation, but rather directional gene flow from higher quality to lower quality microsites (Stanton and Galen, in press). Such directional gene flow can be caused by biased seed and pollen dispersal distributions as well as environmentally based fitness differences for seeds dispersing within and between habitat types (see appendix by M. Turelli in Stanton et al 1997). For Limonium, there is no evidence that plant genotype or tidal elevation causes differential annual seed production (but see below), factors that could lead to directional gene flow.…”

Divergent Selection on Flowering Time Contributes to Local Adaptation in Mimulus Guttatus Populations

“…The timing of reproduction is a critical component of any organism's life cycle, and in nature it can be a primary determinant of an individual's lifetime fitness. In plants, the timing of flowering results from interactions between the complex network of genes that controls development (reviewed in Simpson and Dean 2002;Koornneef et al 2004) and specific environmental cues, such as day length (Lacey 1988;Olsson and Å gren 2002;Weinig et al 2002;Griffith and Watson 2005;Riihimaki et al 2005), light level (Stanton et al 2000), temperature (Eckhart et al 2004), time of snowmelt (Stanton et al 1997), nutrient level (Stanton et al 2000), and water availability (Vasek and Sauer 1971;Aronson et al 1992;Fox 1990;Bennington and McGraw 1995;Eckhart et al 2004;Franke et al 2006;Petru et al 2006). Because the optimal timing of flowering may vary tremendously across different habitats, it is reasonable to suspect that populations and closely related species should be genetically divergent in their flowering response to environmental cues.…”

Carryover effects from natal habitat type upon competitive ability lead to trait divergence or source–sink dynamics

“…As a final example, in the snow buttercup (Ranunculus adoneus), early-snow-melting sites have a longer growing season and thus produced higher quality seeds. The asymmetric gene flow from early-melting to late-melting sites was found to have a homogenising effect; it was strong enough to counteract the localised adaptation that would have otherwise been expected given the large difference in flowering phenology between sites (Stanton et al 1997). Figure 4 A conceptual diagram of the interaction between trait divergence, landscape composition, and habitat quality, showing the positive feedback mechanisms that enhance trait divergence when the minority habitat type has high quality and is rarer in the landscape.…”

“…Mumme et al 2015). For example: early-life nutrition (Metcalfe & Monaghan 2001) can influence adult size (Hopwood et al 2014) or other characteristics relevant to within-sex competition for territory and mates (Spencer et al 2004;Wilkin & Sheldon 2009;Grava et al 2012); local habitat factors can improve propagule quality (Stanton et al 1997); and early resource timing may provide a competitive advantage to young adults (Johansson et al 2014) in cases where there is a prior residence effect (Braddock 1949;Kokko et al 2006).…”

“…Asymmetric gene flow from high-to low-quality habitat may counteract adaptation to the lowquality habitat type (c.f. Stanton et al 1997) if high-quality habitat is relatively common in the landscape; if it is rare, local adaptation to the low-quality habitat type may also occur.…”