Incorporating plant phenological responses into species distribution models reduces estimates of future species loss and turnover.

Anthropogenetic climate change has caused range shifts among many species. Species distribution models (SDMs) are used to predict how species ranges may change in the future. However, most SDMs rarely consider how climate-sensitive traits, such as phenology, which affect individuals' demography and fitness, may influence species' ranges. Using > 120 000 herbarium specimens representing 360 plant species distributed across the eastern United States, we developed a novel 'phenology-informed' SDM that integrates phenological responses to changing climates. We compared the ranges of each species forecast by the phenology-informed SDM with those from conventional SDMs. We further validated the modeling approach using hindcasting. When examining the range changes of all species, our phenology-informed SDMs forecast less species loss and turnover under climate change than conventional SDMs. These results suggest that dynamic phenological responses of species may help them adjust their ecological niches and persist in their habitats as the climate changes. Plant phenology can modulate species' responses to climate change, mitigating its negative effects on species persistence. Further application of our framework will contribute to a generalized understanding of how traits affect species distributions along environmental gradients and facilitate the use of trait-based SDMs across spatial and taxonomic scales.

Plasticity and not adaptation is the primary source of temperature-mediated variation in flowering phenology in North America.

Phenology varies widely over space and time because of its sensitivity to climate. However, whether phenological variation is primarily generated by rapid organismal responses (plasticity) or local adaptation remains unresolved. Here we used 1,038,027 herbarium specimens representing 1,605 species from the continental United States to measure flowering-time sensitivity to temperature over time (Stime) and space (Sspace). By comparing these estimates, we inferred how adaptation and plasticity historically influenced phenology along temperature gradients and how their contributions vary among species with different phenology and native climates and among ecoregions differing in species composition. Parameters Sspace and Stime were positively correlated (r = 0.87), of similar magnitude and more frequently consistent with plasticity than adaptation. Apparent plasticity and adaptation generated earlier flowering in spring, limited responsiveness in late summer and delayed flowering in autumn in response to temperature increases. Nonetheless, ecoregions differed in the relative contributions of adaptation and plasticity, from consistently greater importance of plasticity (for example, southeastern United States plains) to their nearly equal importance throughout the season (for example, Western Sierra Madre Piedmont). Our results support the hypothesis that plasticity is the primary driver of flowering-time variation along temperature gradients, with local adaptation having a widespread but comparatively limited role.

When the neighborhood matters: contextual selection on seedling traits in native and non-native California grasses.

Plants interact extensively with their neighbors, but the evolutionary consequences of variation in neighbor identity are not well understood. Seedling traits are likely to experience selection that depends on the identity of neighbors because they influence competitive outcomes. To explore this, we evaluated selection on seed mass and emergence time in two California grasses, the native perennial Stipa pulchra, and the non-native annual Bromus diandrus, in the field with six other native and non-native neighbor grasses in single- and mixed-species treatments. We also quantified characteristics of each neighbor treatment to further investigate factors influencing their effects on fitness and phenotypic selection. Selection favored larger seeds in both focal species and this was largely independent of neighbor identity. Selection generally favored earlier emergence in both focal species, but neighbor identity influenced the strength and direction of selection on emergence time in S. pulchra, but not B. diandrus. Greater light interception, higher soil moisture, and greater productivity of neighbors were associated with more intense selection for earlier emergence and larger seeds. Our findings suggest that changes in plant community composition can alter patterns of selection in seedling traits, and that these effects can be associated with measurable characteristics of the community.

Heritability and variance components of seed size in wild species: influences of breeding design and the number of genotypes tested.

Seed size affects individual fitness in wild plant populations, but its ability to evolve may be limited by low narrow-sense heritability (h2). h2 is estimated as the proportion of total phenotypic variance (σ2P) attributable to additive genetic variance (σ2A), so low values of h2 may be due to low σ2A (potentially eroded by natural selection) or to high values of the other factors that contribute to σ2P, such as extranuclear maternal effects (m2) and environmental variance effects (e2). Here, we reviewed the published literature and performed a meta-analysis to determine whether h2 of seed size is routinely low in wild populations and, if so, which components of σ2P contribute most strongly to total phenotypic variance. We analyzed available estimates of narrow-sense heritability (h2) of seed size, as well as the variance components contributing to these parameters. Maternal and environmental components of σ2P were significantly greater than σ2A, dominance, paternal, and epistatic components. These results suggest that low h2 of seed size in wild populations (the mean value observed in this study was 0.13) is due to both high values of maternally derived and environmental (residual) σ2, and low values of σ2A in seed size. The type of breeding design used to estimate h2 and m2 also influenced their values, with studies using diallel designs generating lower variance ratios than nested and other designs. e2 was not influenced by breeding design. For some breeding designs, the number of genotypes included in a study also influenced the resulting h2 and e2 estimates, but not m2. Our data support the view that a diallel design is better suited than the alternatives for the accurate estimation of σ2A in seed size due to its factorial design and the inclusion of reciprocal crosses, which allows the independent estimation of both additive and non-additive components of variance.

Genotype × environment interaction obscures genetic sources of variation in seed size in Dithyrea californica but provides the opportunity for selection on phenotypic plasticity.

PREMISE: In many species, seed size influences individual fitness, but its heritability is low, impeding its evolution. In heterogeneous environments, even if heritability of seed size is low, genetic variation in phenotypic plasticity for seed size may provide the opportunity for selection, but this possibility has rarely been investigated in wild species. The evolutionary trajectory of seed size depends on whether additive, maternal, or non-additive genetic variance dominates; moreover, the expression of any of these sources of variance may be environment-dependent, reflecting genetic variation in plasticity. In this study, we examined these sources of variation in seed size and their response to drought in Dithyrea californica. METHODS: We used a diallel design to estimate variance components for seed size in three greenhouse-raised populations sampled from California and northern Mexico. We replicated diallels in two watering treatments to examine genetic parameters and genotype × environment interactions affecting seed size. We estimated general (GCA) and specific (SCA) combining ability, reciprocal effects (RGCA and RSCA), and their interactions with water availability, and we sought evidence that sexual conflict influences seed size. RESULTS: Norms of reaction revealed genetic variation in plasticity for seed size in each population. Seed size in D. californica is determined by the combination of watering treatment, GCA and RGCA; parental identity and water availability do not consistently affect seed size, and we detected no evidence for sexual conflict. CONCLUSIONS: Multiple sources of genetic variation in phenotypic plasticity for seed size have the potential to influence its evolutionary trajectory in heterogenous environments.

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.

Context-dependent concordance between physiological divergence and phenotypic selection in sister taxa with contrasting phenology and mating systems.

PREMISE: The study of phenotypic divergence of, and selection on, functional traits in closely related taxa provides the opportunity to detect the role of natural selection in driving diversification. If the strength or direction of selection in field populations differs between taxa in a pattern that is consistent with the phenotypic difference between them, then natural selection reinforces the divergence. Few studies have sought evidence for such concordance for physiological traits. METHODS: Herbarium specimen records were used to detect phenological differences between sister taxa independent of the effects on flowering time of long-term variation in the climate across collection sites. In the field, physiological divergence in photosynthetic rate, transpiration rate, and instantaneous water-use efficiency were recorded during vegetative growth and flowering in 13 field populations of two taxon pairs of Clarkia, each comprising a self-pollinating and a outcrossing taxon. RESULTS: Historically, each selfing taxon flowered earlier than its outcrossing sister taxon, independent of the effects of local long-term climatic conditions. Sister taxa differed in all focal traits, but the degree and (in one case) the direction of divergence depended on life stage. In general, self-pollinating taxa had higher gas exchange rates, consistent with their earlier maturation. In 6 of 18 comparisons, patterns of selection were concordant with the phenotypic divergence (or lack thereof) between sister taxa. CONCLUSIONS: Patterns of selection on physiological traits measured in heterogeneous conditions do not reliably reflect divergence between sister taxa, underscoring the need for replicated studies of the direction of selection within and among taxa.

Geographic variation in offspring size: Long- and short-term climate affect mean seed mass of Streptanthus populations.

Offspring size is a key functional trait that can affect subsequent life history stages; in many species, it exhibits both local adaptation and phenotypic plasticity. Variation among populations in offspring size may be explained by various factors, including local climatic conditions. However, geographic variation in climate may be partitioned into long-term and interannual sources of variation, which may differ in their effects on population mean offspring size. To assess environmental correlates of offspring size, we evaluated geographic variation in seed mass among 88 populations representing 6 species of Streptanthus (Brassicaceae) distributed across a broad climatic gradient in California. We examined the effects of temperature-mediated growing season length and precipitation on population mean seed mass to determine whether it is best explained by (1) long-term mean climatic conditions; (2) interannual climate anomalies (i.e., deviations in climate from long-term means) during the year of seed development, or (3) interactions between climate variables. Both long-term mean climate and climate anomalies in the year of collection were associated with population mean seed mass, but their effects differed in direction and magnitude. Relatively large seeds were produced at chronically wet sites but also during drier-than-average years. This contrast indicates that these associations may be generated by different mechanisms (i.e., adaptive evolution vs. phenotypic plasticity) and may be evidence of countergradient plasticity in seed mass. In addition, populations occurring in locations characterized by relatively long growing seasons produced comparatively large seeds, particularly among chronically dry sites. This study highlights the need to consider that the responses of seed mass to long-term versus recent climatic conditions may differ and that climate variables may interact to predict seed mass. Such considerations are especially important when using these patterns to forecast the long- and short-term responses of seed mass to climate change. The results presented here also contribute to our broader understanding of how climate drives long-term (e.g., local adaptation) and short-term (e.g., phenotypic plasticity) variation in functional traits, such as offspring size across landscapes.

Machine Learning Undercounts Reproductive Organs on Herbarium Specimens but Accurately Derives Their Quantitative Phenological Status: A Case Study of Streptanthus tortuosus.

Machine learning (ML) can accelerate the extraction of phenological data from herbarium specimens; however, no studies have assessed whether ML-derived phenological data can be used reliably to evaluate ecological patterns. In this study, 709 herbarium specimens representing a widespread annual herb, Streptanthus tortuosus, were scored both manually by human observers and by a mask R-CNN object detection model to (1) evaluate the concordance between ML and manually-derived phenological data and (2) determine whether ML-derived data can be used to reliably assess phenological patterns. The ML model generally underestimated the number of reproductive structures present on each specimen; however, when these counts were used to provide a quantitative estimate of the phenological stage of plants on a given sheet (i.e., the phenological index or PI), the ML and manually-derived PI's were highly concordant. Moreover, herbarium specimen age had no effect on the estimated PI of a given sheet. Finally, including ML-derived PIs as predictor variables in phenological models produced estimates of the phenological sensitivity of this species to climate, temporal shifts in flowering time, and the rate of phenological progression that are indistinguishable from those produced by models based on data provided by human observers. This study demonstrates that phenological data extracted using machine learning can be used reliably to estimate the phenological stage of herbarium specimens and to detect phenological patterns.

Region-specific phenological sensitivities and rates of climate warming generate divergent temporal shifts in flowering date across a species' range.

PREMISE: Forecasting how species will respond phenologically to future changes in climate is a major challenge. Many studies have focused on estimating species- and community-wide phenological sensitivities to climate to make such predictions, but sensitivities may vary within species, which could result in divergent phenological responses to climate change. METHODS: We used 743 herbarium specimens of the mountain jewelflower (Streptanthus tortuosus, Brassicaceae) collected over 112 years to investigate whether individuals sampled from relatively warm vs. cool regions differ in their sensitivity to climate and whether this difference has resulted in divergent phenological shifts in response to climate warming. RESULTS: During the past century, individuals sampled from warm regions exhibited a 20-day advancement in flowering date; individuals in cool regions showed no evidence of a shift. We evaluated two potential drivers of these divergent responses: differences between regions in (1) the degree of phenological sensitivity to climate and (2) the magnitude of climate change experienced by plants, or (3) both. Plants sampled from warm regions were more sensitive to temperature-related variables and were subjected to a greater degree of climate warming than those from cool regions; thus our results suggest that the greater temporal shift in flowering date in warm regions is driven by both of these factors. CONCLUSIONS: Our results are among the first to demonstrate that species exhibited intraspecific variation in sensitivity to climate and that this variation can contribute to divergent responses to climate change. Future studies attempting to forecast temporal shifts in phenology should consider intraspecific variation.

Trade-off drives Pareto optimality of within- and among-year emergence timing in response to increasing aridity.

Adaptation to current and future climates can be constrained by trade-offs between fitness-related traits. Early seedling emergence often enhances plant fitness in seasonal environments, but if earlier emergence in response to seasonal cues is genetically correlated with lower potential to spread emergence among years (i.e., bet-hedging), then this functional trade-off could constrain adaptive evolution. Consequently, selection favoring both earlier within-year emergence and greater spread of emergence among years-as is expected in more arid environments-may constrain adaptive responses to trait value combinations at which a performance gain in either function (i.e., evolving earlier within- or greater among-year emergence) generates a performance loss in the other. All such trait value combinations that cannot be improved for both functions simultaneously are described as Pareto optimal and together constitute the Pareto front. To investigate how this potential emergence timing trade-off might constrain adaptation to increasing aridity, we sourced seeds of two grasses, Stipa pulchra and Bromus diandrus, from multiple maternal lines within populations across an aridity gradient in California and examined their performance in a greenhouse experiment. We monitored emergence and assayed ungerminated seeds for viability to determine seed persistence, a metric of potential among-year emergence spread. In both species, maternal lines with larger fractions of persistent seeds emerged later, indicating a trade-off between within-year emergence speed and potential among-year emergence spread. In both species, populations on the Pareto front for both earlier emergence and larger seed persistence fraction occupied significantly more arid sites than populations off the Pareto front, consistent with the hypothesis that more arid sites impose the strongest selection for earlier within-year emergence and greater among-year emergence spread. Our results provide an example of how evaluating genetically based correlations within populations and applying Pareto optimality among populations can be used to detect evolutionary constraints and adaptation across environmental gradients.

Advancing frost dates have reduced frost risk among most North American angiosperms since 1980.

In recent decades, the final frost dates of winter have advanced throughout North America, and many angiosperm taxa have simultaneously advanced their flowering times as the climate has warmed. Phenological advancement may reduce plant fitness, as flowering prior to the final frost date of the winter/spring transition may damage flower buds or open flowers, limiting fruit and seed production. The risk of floral exposure to frost in the recent past and in the future, however, also depends on whether the last day of winter frost is advancing more rapidly, or less rapidly, than the date of onset of flowering in response to climate warming. This study presents the first continental-scale assessment of recent changes in frost risk to floral tissues, using digital records of 475,694 herbarium specimens representing 1,653 angiosperm species collected across North America from 1920 to 2015. For most species, among sites from which they have been collected, dates of last frost have advanced much more rapidly than flowering dates. As a result, frost risk has declined in 66% of sampled species. Moreover, exotic species consistently exhibit lower frost risk than native species, primarily because the former occupy warmer habitats where the annual frost-free period begins earlier. While reducing the probability of exposure to frost has clear benefits for the survival of flower buds and flowers, such phenological advancement may disrupt other ecological processes across North America, including pollination, herbivory, and disease transmission.

Climate Predicts UV Floral Pattern Size, Anthocyanin Concentration, and Pollen Performance in Clarkia unguiculata.

Given that flower size and pigmentation can mediate plant-pollinator interactions, many studies have focused on pollinator-driven selection on these floral traits. However, abiotic factors such as precipitation, temperature, and solar radiation also contribute to geographic variation in floral color, pattern, and size within multiple species. Several studies have described an ecogeographic pattern within species in which high temperature, high ultraviolet (UV) radiation, low precipitation and/or low latitudes are associated with increased floral anthocyanin production, smaller flowers, and/or larger UV-absorbing floral patterns (nectar guides or bullseyes). However, latitude or elevation is often used as a proxy variable to study variation in floral traits associated with a wide range of climatic variables, making the proximate abiotic drivers of variation difficult to identify. In this study, we tested and corroborated several predictions for how the abiotic environment may directly or indirectly shape geographic patterns of floral color, pattern, and size in Clarkia unguiculata (Onagraceae). This study provides the first report of geographic variation in multispectral floral color and pattern in C. unguiculata, while also providing an experimental test of the putative protective role of UV absorption for pollen performance. We quantified geographic variation among greenhouse-raised populations in UV floral pattern size, mean UV petal reflectance, anthocyanin concentration, and petal area in C. unguiculata across its natural range in California and, using 30 year climate normals for each population, we identified climatic and topographic attributes that are correlated with our focal floral traits. In addition, we examined pollen performance under high and low UV light conditions to detect the protective function (if any) of UV floral patterns in this species. Contrary to our expectations, the nectar guide and the proportion of the petal occupied by the UV nectar guide were largest in low solar UV populations. Estimated floral anthocyanin concentration was highest in populations with high solar UV, which does support our predictions. The size of the UV nectar guide did not affect pollen performance in either of the light treatments used in this study. We conclude that, under the conditions examined here, UV-absorbing floral patterns do not serve a direct "pollen protection" function in C. unguiculata. Our results only partially align with expected ecogeographic patterns in these floral traits, highlighting the need for research in a wider range of taxa in order to detect and interpret broad scale patterns of floral color variation.

A new fine-grained method for automated visual analysis of herbarium specimens: A case study for phenological data extraction.

PREMISE: Herbarium specimens represent an outstanding source of material with which to study plant phenological changes in response to climate change. The fine-scale phenological annotation of such specimens is nevertheless highly time consuming and requires substantial human investment and expertise, which are difficult to rapidly mobilize. METHODS: We trained and evaluated new deep learning models to automate the detection, segmentation, and classification of four reproductive structures of Streptanthus tortuosus (flower buds, flowers, immature fruits, and mature fruits). We used a training data set of 21 digitized herbarium sheets for which the position and outlines of 1036 reproductive structures were annotated manually. We adjusted the hyperparameters of a mask R-CNN (regional convolutional neural network) to this specific task and evaluated the resulting trained models for their ability to count reproductive structures and estimate their size. RESULTS: The main outcome of our study is that the performance of detection and segmentation can vary significantly with: (i) the type of annotations used for training, (ii) the type of reproductive structures, and (iii) the size of the reproductive structures. In the case of Streptanthus tortuosus, the method can provide quite accurate estimates (77.9% of cases) of the number of reproductive structures, which is better estimated for flowers than for immature fruits and buds. The size estimation results are also encouraging, showing a difference of only a few millimeters between the predicted and actual sizes of buds and flowers. DISCUSSION: This method has great potential for automating the analysis of reproductive structures in high-resolution images of herbarium sheets. Deeper investigations regarding the taxonomic scalability of this approach and its potential improvement will be conducted in future work.

Machine Learning Using Digitized Herbarium Specimens to Advance Phenological Research.

Machine learning (ML) has great potential to drive scientific discovery by harvesting data from images of herbarium specimens-preserved plant material curated in natural history collections-but ML techniques have only recently been applied to this rich resource. ML has particularly strong prospects for the study of plant phenological events such as growth and reproduction. As a major indicator of climate change, driver of ecological processes, and critical determinant of plant fitness, plant phenology is an important frontier for the application of ML techniques for science and society. In the present article, we describe a generalized, modular ML workflow for extracting phenological data from images of herbarium specimens, and we discuss the advantages, limitations, and potential future improvements of this workflow. Strategic research and investment in specimen-based ML methods, along with the aggregation of herbarium specimen data, may give rise to a better understanding of life on Earth.

Sex-specific floral attraction traits in a sequentially hermaphroditic species.

●Many angiosperms are hermaphroditic and produce bisexual flowers in which male (pollen export) and female (stigma receptivity) functions are separated temporally. This sequential hermaphroditism may be associated with variation in flower size, color, or pattern, all of which may influence pollinator attraction. In this study, we describe variation in these traits across discrete functional sex stages within and between 225 greenhouse-grown individuals of Clarkia unguiculata (Onagraceae). In addition, to identify the effects of floral phenotype on pollinator attraction in this species, we examine the effects of these floral traits on pollen receipt in ~180 individuals in an experimental field array.●Petal area, ultraviolet (UV)-absorbing nectar guide area, and blue and green mean petal reflectance differ significantly across the functional sex stages of C. unguiculata. Male- and female-phase flowers display significantly different pollinator attraction traits. Petal and UV nectar guide area increase as flowers progress from male phase to female phase, while blue reflectance and green reflectance peak during anther maturation.●In field arrays of C. unguiculata, female-phase flowers with large UV nectar guides receive more pollen than those with small nectar guides, and female-phase flowers with high mean blue reflectance values are more likely to receive pollen than those with low blue reflectance. Female-phase flowers with green mean reflectance values that differ most from background foliage also receive more pollen than those that are more similar to foliage. These findings indicate that components of flower color and pattern influence pollen receipt, independent of other plant attributes that may covary with floral traits. We discuss these results in the context of hypotheses that have been proposed to explain sex-specific floral attraction traits, and we suggest future research that could improve our understanding of sexual dimorphism in sequentially hermaphroditic species and the evolution of features that promote outcrossing.

A new phenological metric for use in pheno-climatic models: A case study using herbarium specimens of Streptanthus tortuosus.

PREMISE: Herbarium specimens have been used to detect climate-induced shifts in flowering time by using the day of year of collection (DOY) as a proxy for first or peak flowering date. Variation among herbarium sheets in their phenological status, however, undermines the assumption that DOY accurately represents any particular phenophase. Ignoring this variation can reduce the explanatory power of pheno-climatic models (PCMs) designed to predict the effects of climate on flowering date. METHODS: Here we present a protocol for the phenological scoring of imaged herbarium specimens using an ImageJ plugin, and we introduce a quantitative metric of a specimen's phenological status, the phenological index (PI), which we use in PCMs to control for phenological variation among specimens of Streptanthus tortuosus (Brassicaceeae) when testing for the effects of climate on DOY. We demonstrate that including PI as an independent variable improves model fit. RESULTS: Including PI in PCMs increased the model R 2 relative to PCMs that excluded PI; regression coefficients for climatic parameters, however, remained constant. DISCUSSION: Our protocol provides a simple, quantitative phenological metric for any observed plant. Including PI in PCMs increases R 2 and enables predictions of the DOY of any phenophase under any specified climatic conditions.

PhenoForecaster: A software package for the prediction of flowering phenology.

PREMISE OF THE STUDY: Predicting the flowering times of angiosperm taxa is a goal of mounting importance in the face of future climate change, with applications not only in plant biology and ecology, but also horticulture, agriculture, and invasive species management. To date, no tool is available to facilitate predictions of flowering phenology using multivariate phenoclimatic models. Such a tool is needed by researchers and other stakeholders who need to predict phenological activity, but are unfamiliar with phenoclimate modeling techniques. PhenoForecaster allows users of any background to conduct species-specific phenological predictions using an intuitive graphical interface and provides an estimate of each prediction's accuracy. METHODS AND RESULTS: Elastic net regression techniques were used to develop species-specific models capable of predicting the flowering dates of 2320 angiosperm species. CONCLUSIONS: PhenoForecaster is the first stand-alone package to make phenological modeling directly accessible to users without the need for in-depth phenological observations.

Floral traits influence the opportunity for selection among male gametophytes: independent and combined effects of style length and petal area.

PREMISE: Strong correlations between traits can obscure their independent effects on components of reproduction. Style length (SL) and petal area (PA) vary within species, for example, but their independent effects on the opportunity for selection among pollen genotypes are poorly understood. Previous work in Clarkia detected a positive effect of SL on pollen receipt, potentially intensifying selection. However, this apparent effect of SL may be influenced by a correlated trait, such as PA. Here, we examine the independent effects of these two traits on pollen receipt and performance. METHODS: We collected petals and styles from wild populations of two insect-pollinated Clarkia taxa and estimated the independent and combined effects of SL and PA on pollen receipt and performance. RESULTS: In both taxa, SL and PA are positively correlated. In C. unguiculata, both traits positively and independently affect pollen receipt, but in C. xantiana ssp. xantiana, the two traits act only in combination to affect pollen receipt. In both taxa, pollen receipt positively affects the numbers of pollen tubes entering and penetrating the style, as well as pollen tube attrition. CONCLUSIONS: The effects of SL and PA on pollen receipt and performance are taxon specific. In C. unguiculata, both traits may be independent targets of selection due to their effects on pollen receipt. In C. xantiana ssp. xantiana, by contrast, the combined (but not independent) effects of SL and PA influence pollen receipt. Ecological differences between these taxa require exploration to understand the mechanisms by which these traits affect pollinator behavior.

Heteranthery in Clarkia: pollen performance of dimorphic anthers contradicts expectations.

PREMISE OF THE STUDY: Wild plant species that require the services of pollen-feeding insects for reliable pollination may evolve features that attract and reward their mutualistic partners. Heterantherous species have been proposed to exhibit a "division of labor" whereby "feeding anthers" (which produce pollen that may be consumed by an insect) are distinguished from "reproductive anthers" (which produce pollen more likely to contribute to reproduction). In some heterantherous species, including Clarkia unguiculata (Onagraceae), these two anther types differ with respect to stamen length, anther size, pollen production, and pollen color. METHODS: The primary goal of this study was to test one component of the "division of labor" hypothesis by comparing the performance of the pollen produced by each type of anther in C. unguiculata. To achieve this goal, under greenhouse conditions, we hand pollinated and assessed pollen performance (using epifluorescence microscopy) within ~228 flowers. KEY RESULTS: The pollen produced by the two anther types differed significantly with respect to both stigma and style penetration. The inner series of anthers produce pollen with higher performance than the outer series of longer, dark red anthers. CONCLUSIONS: These findings contradict previous descriptions of the genus, reporting that the inner diminutive series of anthers in Clarkia produce "abortive and nonfunctional" pollen. We outline the future research required to demonstrate the ecological function of heteranthery in this iconic wildflower group.