Genetic and spatial variation in vegetative and floral traits across a hybrid zone

Natural selection on floral volatiles and other traits can change with snowmelt timing and summer precipitation

Climate change is disrupting floral traits that mediate mutualistic and antagonistic species interactions. Plastic responses of these traits to multiple shifting conditions may be adaptive, depending on natural selection in new environments. We manipulated snowmelt date over three seasons (3-11 d earlier) in factorial combination with growing-season precipitation (normal, halved, or doubled) to measure plastic responses of volatile emissions and other floral traits in Ipomopsis aggregata. We quantified how precipitation and early snowmelt affected selection on traits by seed predators and pollinators. Within years, floral emissions did not respond to precipitation treatments but shifted with snowmelt treatment depending on the year. Across 3 yr, emissions correlated with both precipitation and snowmelt date. These effects were driven by changes in soil moisture. Selection on several traits changed with earlier snowmelt or reduced precipitation, in some cases driven by predispersal seed predation. Floral trait plasticity was not generally adaptive. Floral volatile emissions shifted in the face of two effects of climate change, and the new environments modulated selection imposed by interacting species. The complexity of the responses underscores the need for more studies of how climate change will affect floral volatiles and other floral traits.

Pollinator and habitat-mediated selection as potential contributors to ecological speciation in two closely related species

In ecological speciation, incipient species diverge due to natural selection that is ecologically based. In flowering plants, different pollinators could mediate that selection (pollinator-mediated divergent selection) or other features of the environment that differ between habitats of 2 species could do so (environment-mediated divergent selection). Although these mechanisms are well understood, they have received little rigorous testing, as few studies of divergent selection across sites of closely related species include both floral traits that influence pollination and vegetative traits that influence survival. This study employed common gardens in sites of the 2 parental species and a hybrid site, each containing advanced generation hybrids along with the parental species, to test these forms of ecological speciation in plants of the genus Ipomopsis. A total of 3 vegetative traits (specific leaf area, leaf trichomes, and photosynthetic water-use efficiency) and 5 floral traits (corolla length and width, anther insertion, petal color, and nectar production) were analyzed for impacts on fitness components (survival to flowering and seeds per flower, respectively). These traits exhibited strong clines across the elevational gradient in the hybrid zone, with narrower clines in theory reflecting stronger selection or higher genetic variance. Plants with long corollas and inserted anthers had higher seeds per flower at the Ipomopsis tenuituba site, whereas selection favored the reverse condition at the Ipomopsis aggregata site, a signature of divergent selection. In contrast, no divergent selection due to variation in survival was detected on any vegetative trait. Selection within the hybrid zone most closely resembled selection within the I. aggregata site. Across traits, the strength of divergent selection was not significantly correlated with width of the cline, which was better predicted by evolvability (standardized genetic variance). These results support the role of pollinator-mediated divergent selection in ecological speciation and illustrate the importance of genetic variance in determining divergence across hybrid zones.

Chasing the fitness optimum: temporal variation in the genetic and environmental expression of life-history traits for a perennial plant

BACKGROUND AND AIMS

The ability of plants to track shifting fitness optima is crucial within the context of global change, where increasing environmental extremes may have dramatic consequences for life history, fitness, and ultimately population persistence. However, tracking changing conditions relies on the relationship between genetic and environmental variance, where selection may favour plasticity, the evolution of genetic differences, or both depending on the spatial and temporal scale of environmental heterogeneity.

METHODS

Over three years, we compared the genetic and environmental components of phenological and life-history variation in a common environment for the spring perennial Geum triflorum. Populations were sourced from alvar habitats that exhibit extreme but predictable annual flood-desiccation cycles and prairie habitats that exhibit similar but less predictable variation in water availability.

KEY RESULTS

Heritability was generally higher for early life-history (emergence probability) relative to later life-history traits (total seed mass), indicating that traits associated with establishment are under stronger genetic control relative to later life-history fitness expressions, where plasticity may play a larger role. This pattern was particularly notable in seeds sourced from environmentally extreme but predictable alvar habitats relative to less predictable prairie environments. Fitness landscapes based on seed source origin, largely characterized by varying water availability and flower production, described selection as the degree of maladaptation of seed source environment relative to the prairie common garden environment. Plants from alvar populations were consistently closer to the fitness optimum across all years. Annually, the breadth of the fitness optimum expanded primarily along a moisture gradient, with inclusion of more populations onto the expanding optimum.

CONCLUSIONS

These results highlight the importance of temporally and spatially varying selection in life-history evolution, indicating plasticity may become a primary mechanism needed to track fitness for later life-history events within perennial systems.

Genetic and spatial variation in vegetative and floral traits across a hybrid zone

PREMISE

Genetic variation influences the potential for evolution to rescue populations from impacts of environmental change. Most studies of genetic variation in fitness-related traits focus on either vegetative or floral traits, with few on floral scent. How vegetative and floral traits compare in potential for adaptive evolution is poorly understood.

METHODS

We measured variation across source populations, planting sites, and genetic families for vegetative and floral traits in a hybrid zone. Seeds from families of Ipomopsis aggregata, I. tenuituba, and F₁ and F₂ hybrids of the two species were planted into three common gardens. Measured traits included specific leaf area (SLA), trichomes, water-use efficiency (WUE), floral morphology, petal color, nectar, and floral volatiles.

RESULTS

Vegetative traits SLA and WUE varied greatly among planting sites, while showing weak or no genetic variation among source populations. Specific leaf area and trichomes responded plastically to snowmelt date, and SLA exhibited within-population genetic variation. All aspects of floral morphology varied genetically among source populations, and corolla length, corolla width, and sepal width varied genetically within populations. Heritability was not detected for volatiles due to high environmental variation, although one terpene had high evolvability, and high emission of two terpenes, a class of compounds emitted more strongly from the calyx than the corolla, correlated genetically with sepal width. Environmental variation across sites was weak for floral morphology and stronger for volatiles and vegetative traits. The inheritance of three of four volatiles departed from additive.

CONCLUSIONS

Results indicate stronger genetic potential for evolutionary responses to selection in floral morphology compared with scent and vegetative traits and suggest potentially adaptive plasticity in some vegetative traits.

What determines the evolutionary trajectories of wild plant species? Approaches to the study of quantitative fitness-related traits

Wild plant species provide excellent examples of qualitative traits that evolve in response to environmental challenges (e.g., flower color, heavy metal tolerance, cyanogenesis, and male sterility). In addition to such discrete characters, a dazzling array of continuously distributed, quantitative traits are expressed at every phase of the life cycle. These traits are known or suspected to have evolved by natural selection because they are heritable, differ among populations or closely related taxa occupying distinct habitats, and have individual phenotypes associated with survival and reproductive success. This special issue [American Journal of Botany 109(11)] focuses on the tools and approaches for detecting or inferring the ecological and genetic factors contributing to changes in genetically based variation of quantitative traits within or among populations, or causing their divergence among taxa. The assembled articles use one or more of three primary approaches to detect the process or outcome of natural selection on morphological, life history, reproductive, chemical, and physiological quantitative traits: the analysis of phenotypic or artificially imposed selection to detect direct and indirect selection on traits whose function is well-understood; common garden experiments, including reciprocal transplants and "resurrection" experiments; and quantitative genetic analyses designed to detect and to estimate the environmental and genetic sources of phenotypic variation or to forecast short-term evolutionary change. Together, these articles examine and reveal the adaptive capacity of quantitative traits and the genetically based constraints that may limit their directional evolutionary change, thereby informing and testing inferences, hypotheses, and predictions concerning the evolutionary trajectories of wild plant species.

An analytical pipeline to support robust research on the ecology, evolution, and function of floral volatiles

Research on floral volatiles has grown substantially in the last 20 years, which has generated insights into their diversity and prevalence. These studies have paved the way for new research that explores the evolutionary origins and ecological consequences of different types of variation in floral scent, including community-level, functional, and environmentally induced variation. However, to address these types of questions, novel approaches are needed that can handle large sample sizes, provide quality control measures, and make volatile research more transparent and accessible, particularly for scientists without prior experience in this field. Drawing upon a literature review and our own experiences, we present a set of best practices for next-generation research in floral scent. We outline methods for data collection (experimental designs, methods for conducting field collections, analytical chemistry, compound identification) and data analysis (statistical analysis, database integration) that will facilitate the generation and interpretation of quality data. For the intermediate step of data processing, we created the R package bouquet, which provides a data analysis pipeline. The package contains functions that enable users to convert chromatographic peak integrations to a filtered data table that can be used in subsequent statistical analyses. This package includes default settings for filtering out non-floral compounds, including background contamination, based on our best-practice guidelines, but functions and workflows can be easily customized as necessary. Next-generation research into the ecology and evolution of floral scent has the potential to generate broadly relevant insights into how complex traits evolve, their genomic architecture, and their consequences for ecological interactions. In order to fulfill this potential, the methodology of floral scent studies needs to become more transparent and reproducible. By outlining best practices throughout the lifecycle of a project, from experimental design to statistical analysis, and providing an R package that standardizes the data processing pipeline, we provide a resource for new and seasoned researchers in this field and in adjacent fields, where high-throughput and multi-dimensional datasets are common.