Measuring, comparing and interpreting phenotypic selection on floral scent

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.

Testing the effect of individual scent compounds on pollinator attraction in nature using quasi-isogenic Capsella lines

PREMISE

Floral scent, usually consisting of multiple compounds, is a complex trait, and its role in pollinator attraction has received increasing attention. However, disentangling the effect of individual floral scent compounds is difficult due to the complexity of isolating the effect of single compounds by traditional methods.

METHODS

Using available quasi-isogenic lines (qILs) that were generated as part of the original mapping of the floral scent volatile-related loci CNL1 (benzaldehyde) and TPS2 (β-ocimene) in Capsella, we generated four genotypes that should only differ in these two compounds. Plants of the four genotypes were introduced into a common garden outside the natural range of C. rubella or C. grandiflora, with individuals of a self-compatible C. grandiflora line as pollen donors, whose different genetic background facilitates the detection of outcrossing events. Visitors to flowers of all five genotypes were compared, and the seeds set during the common-garden period were collected for high-throughput amplicon-based sequencing to estimate their outcrossing rates.

RESULTS

Benzaldehyde and β-ocimene emissions were detected in the floral scent of corresponding genotypes. While some pollinator groups showed specific visitation preferences depending on scent compounds, the outcrossing rates in seeds did not vary among the four scent-manipulated genotypes.

CONCLUSIONS

The scent-manipulated Capsella materials constructed using qILs provide a powerful system to study the ecological effects of individual floral scent compounds under largely natural environments. In Capsella, individual benzaldehyde and β-ocimene emission may act as attractants for different types of pollinators.

Water deficit changes patterns of selection on floral signals and nectar rewards in the common morning glory

Understanding whether and how resource limitation alters phenotypic selection on floral traits is key to predict the evolution of plant-pollinator interactions under climate change. Two important resources predicted to decline with our changing climate are pollinators and water in the form of increased droughts. Most work, however, has studied these selective agents separately and in the case of water deficit, studies are rare. Here, we use the common morning glory (Ipomoea purpurea) to investigate the effects of experimental reduction in pollinator access and water availability on floral signals and nectar rewards and their effects on phenotypic selection on these traits. We conducted a manipulative experiment in a common garden, where we grew plants in three treatments: (1) pollinator restriction, (2) water reduction and (3) unmanipulated control. Plants in pollinator restriction and control treatments were well-watered compared to water deficit. We found that in contrast to pollinator restriction, water deficit had strong effects altering floral signals and nectar rewards but also differed in the direction and strength of selection on these traits compared to control plants. Water deficit increased the opportunity for selection, and selection in this treatment favoured lower nectar volumes and larger floral sizes, which might further alter pollinator visitation. In addition, well-watered plants, both in control and pollinator deficit, showed similar patterns of selection to increase nectar volume suggesting non-pollinator-mediated selection on nectar. Our study shows that floral traits may evolve in response to reduction in water access faster than to declines in pollinators and reinforces that abiotic factors can be important agents of selection for floral traits. Although only few experimental selection studies have manipulated access to biotic and abiotic resources, our results suggest that this approach is key for understanding how pollination systems may evolve under climate change.

Variation in scent amount but not in composition correlates with pollinator visits within populations of deceptive Arum maculatum L. (Araceae)

Floral scent is vital for pollinator attraction and varies among and within plant species. However, little is known about how inter-individual variation in floral scent affects the abundance and composition of floral visitor assemblages within populations. Moreover, for deceptive plants it is predicted that intra-population variation in scent can be maintained by negative frequency-dependent selection, but empirical evidence is still lacking. To investigate the ecological and evolutionary relations between inter-individual scent variation (i.e., total emission and composition) and floral visitors in deceptive plants, we studied floral scent, visitor assemblages, and fruit set in two populations of fly-pollinated (Psychodidae, Sphaeroceridae; Diptera) and deceptive Arum maculatum from Austria (JOS) and northern Italy (DAO). By correlating individual data on floral scent and visitor assemblages, we show that inter-individual variation in floral scent partly explains variation in visitor assemblages. The quantity of floral scent emitted per individual correlated positively with visitor abundance in both populations but explained visitor composition only in DAO, where strongly scented inflorescences attracted more sphaerocerid flies. However, in each population, the composition of floral scent did not correlate with the composition of floral visitors. There was also no evidence of negative frequency-dependent selection on floral scent. Instead, in JOS, more frequent scent phenotypes attracted more pollinators and were more likely to set an infructescence than rarer ones. Our results show that floral scent, despite being key in pollinator attraction in A. maculatum, only partly explains variation in pollinator abundance and composition. Overall, this study is the first to shed light on the importance of inter-individual variation in floral scent in explaining floral visitor assemblages at the population level in a deceptive 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.