Macroevolution of Leaf Defenses and Secondary Metabolites Across the Genus Helianthus

Research

Macroevolution of leaf defenses and secondary metabolites across the genus Helianthus

Chase M. Mason1, Alan W. Bowsher1, Breanna L. Crowell1, Rhodesia M. Celoy2, Chung-Jui Tsai2 and Lisa A. Donovan1 1Department of Plant Biology, University of Georgia, Athens, GA 30602, USA; 2Warnell School of Forestry and Natural Resources, and Department of Genetics, University of Georgia, Athens, GA 30602, USA

Summary Author for correspondence: Leaf defenses are widely recognized as key adaptations and drivers of plant evolution. Chase M. Mason Across environmentally diverse habitats, the macroevolution of leaf defenses can be predicted Tel: +1 386 916 6578 by the univariate trade-off model, which predicts that defenses are functionally redundant Email: [email protected] and thus trade off, and the resource availability hypothesis, which predicts that defense Received: 10 April 2015 investment is determined by inherent growth rate and that higher defense will evolve in lower Accepted: 6 October 2015 resource environments. Here, we examined the evolution of leaf physical and chemical defenses and secondary New Phytologist (2015) metabolites in relation to environmental characteristics and leaf economic strategy across 28 doi: 10.1111/nph.13749 species of Helianthus (the sunflowers). Using a phylogenetic comparative approach, we found few evolutionary trade-offs among Key words: chemical, herbivory, high- defenses and no evidence for defense syndromes. We also found that leaf defenses are performance liquid chromatography–mass strongly related to leaf economic strategy, with higher defense in more resource-conservative spectrometry (HPLC-MS), pathogen, species, although there is little support for the evolution of higher defense in low-resource physical, sunflowers. habitats. A wide variety of physical and chemical defenses predict resistance to different insect herbivores, fungal pathogens, and a parasitic plant, suggesting that most sunflower defenses are not redundant in function and that wild Helianthus represents a rich source of variation for the improvement of crop sunflower.

differentiation among plant populations and species (Fine et al., Introduction 2004; Agrawal et al., 2012; Zust€ et al., 2012). Over the past half Plants and their herbivores constitute over half of all described century, dozens of explanations have been put forward to account species, and the evolutionary arms race between these two groups for the broad interspecific variation observed in plant defenses, is hypothesized to explain much of the enormous global diversity although few have withstood empirical assessment across multiple in plant and herbivore species (Futuyma & Agrawal, 2009). Key systems (Stamp, 2003; Agrawal, 2007; Johnson, 2011). When plant traits known as defenses work to reduce herbivore damage considering the evolutionary radiation of a group of species into and improve fitness in the face of herbivore pressure (Stamp, broadly distributed and environmentally variable habitats, two 2003; Boege & Marquis, 2005; Carmona et al., 2011). The evo- major explanations of defense variation make the most testable lution of such defenses is known to have resulted in adaptive radi- predictions: the univariate trade-off model and the resource avail- ations (Farrell et al., 1991; Agrawal et al., 2009a), and plant– ability hypothesis. herbivore interactions have become a major focus of evolutionary The univariate trade-off model is central to many major ecology (Agrawal, 2011; Johnson, 2011). Because plants mediate defense hypotheses (Agrawal, 2007). Because investment in the primary flow of energy into almost all terrestrial ecosystems, defense comes at the expense of growth (Bazzaz et al., 1987), the the plant–herbivore interaction is the foundation of nearly all ter- univariate trade-off model predicts that trade-offs will exist restrial food webs and is thus arguably one of the most important among defenses such that only one defense performing a particu- ecological processes on Earth. In addition to reducing herbivory, lar protective function will be invested in by a plant at any given many plant defenses also reduce susceptibility to pathogen attack time, and all comparable redundant defenses will not be allocated (Levin, 1976; Lattanzio et al., 2006; Treutter, 2006), and thus resources because of energetic cost (Agrawal, 2007). Many exami- play multiple roles in determining plant fitness under pressure nations of species at community and global scales have explored from natural enemies. Consequently, both physical and chemical the possibility of trade-offs occurring among various defenses, defenses have been demonstrated to mediate adaptive but have generally found mixed support for univariate trade-offs

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(Steward & Keeler, 1988; Twigg & Socha, 1996; Koricheva under the resource availability hypothesis. One would therefore et al., 2004; Read et al., 2009). By contrast, if effective plant expect species with a more resource-acquisitive leaf economic defense is conferred by multiple defense traits acting together, we strategy to invest less in defense than species with a more should expect positive covariation among certain subsets of traits, resource-conservative strategy. However, the hypothesis of a leaf- forming defense syndromes in which distantly related species level relationship between leaf economics and leaf defense invest- adopt similar multivariate defense phenotypes (Agrawal & Fish- ment has yet to be rigorously tested. bein, 2006; Agrawal, 2007). Potential examples of such syn- Here, we investigated the evolution of leaf defenses and puta- dromes include convergent strategies for defending against tively defensive secondary metabolites across the genus different feeding guilds of herbivores – such as chewing versus Helianthus (the sunflowers). Sunflowers are a diverse group of piercing-sucking insects – or convergent defense strategies species that have radiated into a wide variety of habitats through- favored in different habitats or in conjunction with different life out North America, including deserts, grasslands and prairies, history characteristics. The largest world-wide analysis to date of evergreen and deciduous forests, freshwater wetlands and salt univariate trade-offs and defense syndromes in a phylogenetic marshes, coastal dunes, rock outcrops, and ruderal habitats context found little evidence for either trade-offs or syndromes at (Heiser et al., 1969). Many studies have explored physiological a global scale, but hypothesized that both could exist at lower adaptation to variation in abiotic environmental conditions in levels of evolutionary organization, such as within individual gen- wild sunflowers (Rosenthal et al., 2002; Sambatti & Rice, 2007; era (Moles et al., 2013). Donovan et al., 2009; Kawakami et al., 2011; Brouillette et al., The resource availability hypothesis (also known as the growth 2014; Mason & Donovan, 2015b), but little work has investi- rate hypothesis) attempts to explain variation in plant defense gated how members of Helianthus have differentiated in response through two primary mechanisms – inherent growth rate and to biotic pressures such as herbivory or disease (Fig. 1). Here, we resource availability. First, this hypothesis predicts that defense use a phylogenetic comparative approach to examine: (1) whether variation occurs as a result of differences in the cost–benefit ratio there are univariate trade-offs or syndromes in leaf defenses across of investment in defenses as a function of inherent plant growth Helianthus; (2) how leaf defenses relate to the leaf economics rate (Coley et al., 1985; Coley, 1987; Stamp, 2003; Endara & spectrum; (3) how leaf defenses vary across environmental gradi- Coley, 2011). For inherently fast-growing species, investing in ents; and (4) how leaf defense traits predict resistance to known defenses has the potential to reduce growth much more than in sunflower herbivores and pathogens, and accompanying plant inherently slow-growing species, and fast-growing species can performance under attack. more quickly replace leaf area lost to herbivory or disease (Coley et al., 1985). Second, under this hypothesis the inherent growth Materials and Methods rate of a species is assumed to be determined primarily by resource availability in the habitat to which it is adapted (Endara Study system & Coley, 2011). Under this assumption, a plant species adapted to a resource-rich environment would benefit more from invest- To examine the evolution of leaf defenses across Helianthus,we ing in growth than defense, as better access to water or nutrients selected 28 diploid nonhybrid species to make use of the most renders herbivory less costly (Horsfall & Cowling, 1980). Con- versely, a species adapted to a resource-poor environment would benefit more from a large investment in defenses, as resource lim- (a) (b) itation makes lost leaf tissue more difficult to replace. The resource availability hypothesis has been well supported by meta- analysis across studies of interspecific variation in defense (Endara & Coley, 2011), although there have been relatively few studies of this hypothesis in a phylogenetic context. Because of the explicit linkage of defense investment with growth rate and environmental resource availability, the resource availability hypothesis also offers the potential for explaining leaf defense variation in relation to other aspects of leaf physiology. One major axis of variation in nondefense leaf physiology is the leaf economics spectrum, which describes suites of leaf traits gov- erning carbon and nutrient investment and return that form ecological strategies ranging from resource-acquisitive to resource- conservative (Reich et al., 1997; Wright et al., 2004). This spectrum strongly predicts whole-plant growth rate and tolerance of low-resource conditions (Poorter et al., 1990; Sterck et al., 2006; Fig. 1 Sunflower herbivory in the field. Leaf and floral damage by spotted Hallik et al., 2009; Nardini et al., 2012), such that the leaf eco- cucumber beetle (Diabrotica undecimpunctata)onHelianthus petiolaris nomics spectrum should predict the interspecific differences in in Illinois, USA (a), and leaf damage by the eastern lubber grasshopper inherent growth rate that define differences in defense investment (Romalea guttata)onHelianthus agrestis in Florida (b) are shown.

New Phytologist (2015) Ó 2015 The Authors www.newphytologist.com New Phytologist Ó 2015 New Phytologist Trust New Phytologist Research 3 recent and robust phylogeny of the diploid backbone of the genus and leaf dry matter content (LDMC) are common measures of (Stephens et al., 2015). These 28 species make up the vast major- leaf palatability and digestibility, with higher dry matter content, ity of the diploid nonhybrids in the genus (34 total), and repre- toughness, and thickness often correlating with reduced her- sent over half of the genus as a whole, which contains c.50 bivory and herbivore growth (Scriber, 1977; Elger & Willby, species in total (Heiser et al., 1969; Timme et al., 2007). To cap- 2003; Hanley et al., 2007; Kitajima & Poorter, 2010; Kitajima ture intraspecific variation, two to four populations were identi- et al., 2012), although extremely low dry matter content (i.e. suc- fied from across the documented geographic range of each of the culence) can also deter herbivory (Perez-Harguindeguy et al., 28 species (83 populations in total). Seeds from these populations 2003; Moles et al., 2013). Trichomes block or ensnare small her- were either wild-collected or obtained from accessions main- bivores such as insects or gastropods, interfering with feeding or tained by the USDA National Genetic Resources Program (Sup- oviposition, and may keep pathogen-containing water droplets porting Information Notes S1). away from the leaf surface (Levin, 1973; Horsfall & Cowling, 1980; Hanley et al., 2007). Glandular trichomes are also known to secrete secondary compounds, which may deter small herbi- Plant growth vores and inhibit the colonization and growth of pathogens Leaf defenses are known to be highly environmentally labile (Levin, 1973; Horsfall & Cowling, 1980; Hanley et al., 2007). (Lieurance & Cipollini, 2013; Moore et al., 2014). In order to Tannins are polyphenolic compounds traditionally recognized minimize environmentally induced variation, a common garden for their protein precipitation capacity, and more recently for approach was used, with plants grown under controlled high- their strong oxidative activity against herbivores (Salminen & resource glasshouse conditions. Although this approach does not Karonen, 2011). Tannins are widespread in plants, and have been eliminate the possibility of maternal effects from field-sampled demonstrated to reduce herbivory by reducing leaf protein seeds, maternal effects nevertheless contribute to trait variation digestibility, damaging the digestive system, and generally inter- among species and populations in nature; therefore, the potential fering with metabolism and growth (Shimada, 2006; Roslin & inclusion of maternal effects in our study should not impact con- Salminen, 2008; Spalinger et al., 2010; Moles et al., 2011). Tan- clusions related to trait trade-offs and defense syndromes. nins have also been implicated in pathogen resistance (Levin, To accommodate all 83 populations, the 28 species were 1976; Lattanzio et al., 2006). Leaf lipid content is a combined divided into two common garden experiments performed in the proxy for leaf oils, resins, and waxes (Moles et al., 2011), all of summers of 2012 and 2013 at the University of Georgia Plant which deter herbivory and pathogen attack (Levin, 1976; Hors- Biology glasshouses. To minimize differences between the two fall & Cowling, 1980; Coley et al., 1985; Lincoln, 1985; Marko common gardens, experimental timing was synchronized et al., 2008). Leaf ash content reflects the relative presence of between years and environmental conditions were kept as similar inorganic substances, including two major classes of compounds: as possible, including the use of identical pots, soil mixture, irri- calcium oxalates and silicate phytoliths (Lanning & Eleuterius, gation, fertilization, and glasshouse temperature controls. Three 1985; Franceschi & Nakata, 2005; Moles et al., 2011). These species representing a cross-section of life history and overall increase the abrasiveness of leaves, grinding down the mouthparts morphology (Helianthus annuus L., Helianthus radula (Pursh) of chewing herbivores and disrupting their digestion, resulting in Torr. & A. Gray, and Helianthus silphioides Nutt.) were grown reduced growth rates (Korth et al., 2006; Massey et al., 2006; in both years as phytometers to assess and correct for any other Hanley et al., 2007; Moles et al., 2011). Silicate phytoliths have uncontrollable differences in environmental conditions between also been demonstrated to increase resistance to fungal infection the two common gardens. These common gardens were addi- (Horsfall & Cowling, 1980; Cooke & Leishman, 2011). tionally used for the study of the evolution of leaf economic Together, these seven leaf traits reflect a wide variety of different strategy, with experimental conditions described in detail in a classes and mechanisms of putative leaf defenses present in plants previous study (Mason & Donovan, 2015b). In brief, seeds were globally (Moles et al., 2013). germinated in Petri dishes before being transplanted into 6-l Leaf sampling was standardized by ontogenetic stage, in order pots with a 3 : 1 sand-calcined clay soil mixture. Eight replicate to account for large variation among species in growth form, plants per population were assigned to a randomized complete growth rate, and whole-plant development (Mason et al., 2013; block design to account for spatial variation in the glasshouse. Mason & Donovan, 2015a). Thus, each species was considered High water and nutrient availability was ensured through daily separately, and all populations and replicates of each species were drip irrigation to field capacity and fertilization with 20 g sampled on a single day, once all replicate plants had produced at of slow-release fertilizer (Osmocote Plus 15-9-12; Scotts, least four fully expanded leaf pairs but before the onset of repro- Marysville, OH, USA), along with initial liquid fertilization duction (Mason & Donovan, 2015b). A single leaf was harvested during establishment. from each replicate plant to assess the seven leaf defense traits described above, using established protocols as described in Methods S1. Leaf defense measurements In addition to defenses, two other previously reported leaf Seven putative leaf defense traits were included in this study: traits (Mason & Donovan, 2015b) are included here as descrip- thickness, toughness, dry matter content, trichome density, tan- tors of nondefense leaf physiology. These traits are carbon nin activity, lipid content, and ash content. Thickness, toughness, (C) : nitrogen (N) ratio, a common measure of leaf palatability/

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nutritional quality (Perez-Harguindeguy et al., 2003; Agrawal were initially included for HPLC-MS analysis, although this & Fishbein, 2006), and leaf economic strategy, defined as the was reduced to an average of 3.77 because of instrument break- first principal component (LES PC1) capturing 51.5% of varia- downs. tion across the 28 Helianthus species in six leaf economic traits: In total, HPLC-MS analysis yielded 1744 distinct peaks across photosynthetic and respiration rates, N and phosphorus con- all species, hereafter referred to as the HeliaMet database (Notes centrations, leaf mass per area, and leaf lifespan (Mason & S2). Populations were scored for the presence of each of these Donovan, 2015b). These traits were measured simultaneously compounds, defined as presence in at least 75% of replicates in a with the leaf defenses described above on the same replicate population to limit false positives. Presence/absence data were plants, and with the exception of leaf lifespan were all assessed used to determine the number of compounds present in each on either the exact same leaf used for assessment of defense population, as well as to perform principal coordinates analyses traits or the opposite leaf of the same leaf pair. C : N ratio and at the population level, in order to describe overall variation in leaf economic strategy are therefore physiologically paired to secondary metabolite composition as the first two axes of varia- the defenses of interest. tion (HeliaMet PCO1 and HeliaMet PCO2). While these popu- For each leaf trait, population least-squares means were calcu- lation-level metrics were used to investigate correlated evolution lated by ANOVA in order to account for the randomized com- between secondary metabolite composition and leaf-level plete block design. To check for any consistent differences defenses and environmental characteristics, species-level metrics between the two common gardens, trait values obtained for all were needed in order to investigate evolutionary correlations with replicates of the three species (nine populations) grown in both species-level estimates of resistance to herbivores, pathogens, and years as phytometers were assessed by ANOVA. ANOVAs run parasites. To obtain these, species were scored for the presence or on individual replicate plants of each phytometer species (includ- absence of compounds, defined as presence in any population by ing year, population, and block effects with interactions) deter- the criteria used at the population level, and the average number mined that no traits showed significant differences between years of compounds present in each species was calculated. Principal across all three phytometer species, as well as only one significant coordinates analysis was repeated at the species level to calculate population 9 year interaction (for leaf lipid content in the first two axes of variation (HeliaMet PCO1 and HeliaMet H. annuus). Accordingly, no corrections of traits between years PCO2). were performed and least-squares trait means for the nine phy- To characterize the most common secondary metabolites tometer populations were averaged between the 2 years for use in across Helianthus, all compounds present in at least 20 species subsequent analyses. were selected for further analyses. For this subset of 22 compounds, mean peak areas for each compound were calculated for each population, and species means were calculated from popula- Secondary metabolite screening tion means. Normalized peak area data were used to perform To characterize broad secondary metabolite variation across principal components analyses at the population and species species, we used a nontargeted profiling approach to capture vari- levels, in order to describe overall quantitative variation in the ation in as many compounds as possible, rather than a priori most common secondary metabolites as the first two axes of vari- selection of specific compounds or classes of interest. Previous ation (HeliaMet Subset PC1 and HeliaMet Subset PC2). These studies of both wild and cultivated sunflowers have mostly two axes together explained 47.4% of quantitative variation focused on individual groups of charismatic compounds such as among populations in the 22 focal compounds, and 54.9% of coumarins, flavonoids, or sesquiterpene lactones (Schilling & variation among species. Putative compound identities for the 22 Mabry, 1981; Schilling, 1983; Rogers et al., 1987; Spring & focal compounds (Table S1) were determined by comparing with Schilling, 1989; Olson & Roseland, 1991; Roseland & Grosz, authentic standards where possible, by searching predicted m/z 1997; Rowe et al., 2012), but to date no study to our knowledge ratios in the METLIN database (Smith et al., 2005), or by com- has characterized broad variation in secondary metabolites across parison with predicted m/z ratios of compounds detected in pre- the wild sunflowers. vious studies of sunflower (Tal & Robeson, 1986; Spring & In brief, a single leaf was collected from each plant, snap- Schilling, 1989; Olson & Roseland, 1991; Rowe et al., 2012), frozen in liquid nitrogen, and stored at À80°C. Samples were with specific focus on coumarins and terpenoids (including ground in liquid nitrogen, and 10 mg of freeze-dried leaf pow- sesquiterpene lactones). der was extracted in 400 ll of 1 : 1 methanol : chloroform (v/v) containing three internal standards (13C -cinnamic acid, D - 6 5 Environmental data benzoic acid, and resorcinol) by sonication in ice-chilled water for 30 min. After the addition of 200 ll of high-performance Soil and climate characteristics were obtained for the source site liquid chromatography (HPLC)-grade water, samples were vor- of each population, as reported previously in Mason & Donovan texed and centrifuged, and the aqueous layer was collected and (2015b), and detailed in Methods S1. In brief, five soil cores were re-centrifuged. Leaf extracts were analyzed by reverse-phase collected at representative locations throughout each population high-performance liquid chromatography–mass spectrometry to a depth of c. 20 cm, dried at 60°C and homogenized before (HPLC-MS) as described in Xue et al. (2013) and in Methods analysis for soil fertility characteristics, with replicate cores aver- S1. Individual samples from four replicate plants per population aged to generate site means for use in subsequent analyses.

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Climate data were obtained for each population source site using comparisons correction (Benjamini & Hochberg, 1995) was the WorldClim database (Hijmans et al., 2005) and the CGIAR implemented on correlations in each set of analyses: trait–trait Global Aridity and PET database (Zomer et al., 2008). correlations, trait–environment correlations, and trait–resistance/ performance correlations. Maximum likelihood ancestral state reconstructions were per- Herbivore and pathogen resistance formed with the fastAnc function in the R package phytools (Rev- Wild Helianthus species have long been screened for herbivore ell, 2012). The phylomorphospace function in phytools was used to and pathogen resistance, primarily with the intention of identify- visualize the evolution of the two primary axes of secondary ing useful germplasm for improved breeding of crop sunflower. metabolite variation across Helianthus. To assess trait differences Here, we made use of data from seven such studies, yielding between annuals, erect perennials, and basal rosette perennials, species-level data on responses to a variety of common sunflower PGLS-ANOVA was performed using the gls function in the R pests and diseases. These include the aphid Masonaphis masoni package nlme (Pinheiro et al., 2014), with post hoc tests per- (Rogers & Thompson, 1978), the western potato leafhopper formed with the glht function in the multcomp package (Hothorn Empoasca abrupta (Rogers, 1981), the painted lady butterfly et al., 2008). To assess the presence of syndromes of defenses caterpillar Vanessa cardui (E. W. Goolsby et al., unpublished), across species, we employed the general approach of Agrawal & the parasitic broomrape plant Orobanche cernua (Ruso et al., Fishbein (2006). Both principal components analysis and stan- 1996), leaf blight caused by Alternaria helianthi (Morris et al., dardized hierarchical clustering analysis (Ward method) were 1983), head rot caused by Rhizopus species (Yang et al., 1980), performed on species trait means in JMP PRO v.11 (SAS Institute, and powdery mildew caused by Erysiphe chicoracearum (Salimen Cary, NC, USA). To test for significant clustering of species by et al., 1982). In all these studies, a cross-section of species were defenses, the similarity profile routine (SIMPROF) was imple- challenged with the focal pest or disease under experimental field mented using Euclidean distance with 9999 permutations in the or glasshouse conditions, and responses recorded. Aggregated software package PRIMER v.7 (Clarke et al., 2008; Moles et al., data from these studies can be found in Notes S1. 2013).

Phylogenetic and clustering analyses Results All phylogenetic analyses were performed with the most recent Correlated evolution of leaf defenses across Helianthus phylogeny of the genus Helianthus, which was built using 170 nuclear genes and is well supported (Stephens et al., 2015). The Among leaf-level defenses, most of the significant macroevolu- tree topology was inferred by the coalescent method MP-EST tionary correlations between traits exhibit R2 < 0.25 (Table 1), (maximum pseudo-likelihood estimation of species trees), with suggesting a general lack of direct mechanistic relationships branch lengths fitted to that topology using maximum likelihood between defense traits (Poorter et al., 2014). However, there are in RAxML (Stephens et al., 2015). several important exceptions to this finding. First, leaf thickness To assess pairwise macroevolutionary correlations among traits is strongly negatively related to LDMC and strongly positively and between traits and environmental characteristics, we used related to ash content, indicating repeated evolution of high leaf phylogenetic mixed models on population trait means to account thickness in more succulent-leaved species and those with high for within-species trait variation (Felsenstein, 2008). Under this ash content (Table 1). Second, ash content is positively correlated method, within- and among-species trait covariances are esti- with leaf toughness, indicating that ash content probably con- mated iteratively using an expectation-maximization algorithm tributes to leaf toughness across Helianthus (Table 1). Third, tan- assuming a Brownian motion model of evolution (Felsenstein, nin activity is strongly positively correlated with leaf C : N ratio, 2008). Tests comparing Brownian motion models of evolution indicating repeated evolution of high protein-precipitation capac- to a star-phylogeny model found mixed support among individ- ity in leaves with low N reserves (Table 1). While there are strong ual traits, so Brownian motion was used in all analyses as a con- relationships among some individual defenses, the low propor- servative approach, given that simulation has shown phylogenetic tion of significant macroevolutionary correlations is not what models to outperform nonphylogenetic models even when model would be expected in the presence of distinct defense syndromes. assumptions are violated (Martins et al., 2002). To implement Additionally, hierarchical cluster analysis yielded no significant phylogenetic mixed models, the contrast program in PHYLIP clustering of species (SIMPROF; p = 2.55; P = 0.432), and principal v.3.68 (Felsenstein, 2004) was called using the varCompPhylip components analysis of defenses showed that multivariate trait function of the R package ape (Paradis et al., 2004). To assess space is continuously filled by species, rather than displaying pairwise macroevolutionary correlations between traits and met- groups of species as would be expected if defenses formed strong rics of herbivory and pathogen resistance (for which only species- syndromes (Fig. 2). level data are available), we used species trait means calculated as In general, lower defense is associated with a more resource- the average of population trait means and estimated correlations acquisitive leaf economic strategy (as defined by LES PC1; using the phylopars method which allows for missing data Mason & Donovan, 2015b). The evolution of more resource- (Bruggeman et al., 2009). Given the large number of pairwise acquisitive leaves is correlated with lower toughness and higher correlations being estimated, false discovery rate multiple LDMC, and strongly correlated with lower tannin activity

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Table 1 Macroevolutionary correlations among leaf physical and chemical defenses, carbon : nitrogen (C : N) ratio, leaf economic spectrum (LES) strategy, and HeliaMet metrics of secondary metabolite variation as assessed by phylogenetic mixed model

Avg Trichome Thickness Toughness LDMC Tannin Lipid Ash C : N LES HeliaMet HeliaMet no. of HeliaMet density activity content content ratio PC1 PCO1 PCO2 compounds Subset PC1 Thickness (+)0.12 Toughness (–)0.00 (+)0.16 LDMC (+)0.00 (–)0.61 (–)0.17 Tannin activity (–)0.01 (–)0.02 (+)0.05 (–)0.03 Lipid content (+)0.00 (–)0.19 (–)0.00 (+)0.13 (–)0.03 Ash content (+)0.03 (+)0.51 (+)0.30 (–)0.20 (–)0.03 (–)0.11 C : N ratio (–)0.00 (+)0.01 (+)0.21 (–)0.13 (+)0.77 (–)0.01 (–)0.01 LES PC1 (–)0.00 (–)0.07 (–)0.20 (+)0.20 (–)0.50 (+)0.06 (–)0.00 (–)0.77 HeliaMet PCO1 (+)0.06 (+)0.26 (+)0.16 (–)0.05 (+)0.00 (–)0.05 (+)0.24 (+)0.11 (–)0.13 HeliaMet PCO2 (+)0.02 (+)0.00 (–)0.07 (+)0.05 (–)0.22 (+)0.06 (+)0.03 (–)0.18 (+)0.26 (–)0.05 Avg. no. of (–)0.01 (–)0.17 (–)0.12 (+)0.05 (–)0.02 (+)0.17 (–)0.44 (–)0.12 (+)0.11 (–)0.82 (+)0.08 compounds HeliaMet Subset PC1 (–)0.01 (–)0.09 (–)0.01 (+)0.01 (+)0.07 (–)0.08 (–)0.27 (+)0.04 (–)0.05 (–)0.02 (–)0.56 (–)0.00 HeliaMet Subset PC2 (–)0.00 (–)0.20 (–)0.02 (+)0.51 (–)0.15 (+)0.08 (–)0.02 (–)0.25 (+)0.44 (–)0.42 (+)0.08 (+)0.33 (–)0.02 R2 and directionality of correlations are presented, with those found to be significant at P<0.05 in blue, and those found to be also significant at the more stringent multiple comparisons cutoff (false discovery rate; Benjamini & Hochberg, 1995) in red. LDMC, leaf dry matter content; PC1, PC2, first and second principal components axes; PCO1, PCO2, first and second principal coordinate axes.

(Table 1). As expected, leaf economic strategy is a strong predic- described by HeliaMet Subset PC1 (Table S1, Fig. S1), correlates tor of leaf palatability as defined by the C : N ratio (Table 1). negatively with ash content but no other leaf-level defenses However, leaf economic strategy is not evolutionarily correlated (Table 1). Conversely, HeliaMet Subset PC2 correlates strongly with trichome density, leaf thickness, leaf ash content, or leaf positively with LDMC and negatively with thickness, tannin lipid content (Table 1). In addition, no leaf-level defenses signifi- activity, and C : N ratio (Table 1). cantly differ among growth forms or life histories by PGLS- ANOVA. Environmental gradients in defense and secondary metabolites Secondary metabolite variation with defense traits and life Across Helianthus, there are many significant correlations history between defenses and environmental characteristics. Shifts into Among metrics of secondary metabolite composition, HeliaMet warmer environments are associated with increased trichome PCO1 correlates strongly negatively with the average number of density, leaf thickness, C : N ratio, and reduced lipid content, compounds detected (R2 = 0.82; Table 1), while HeliaMet while only C : N ratio is associated with shifts in temperature sea- PCO2 correlates strongly negatively with the abundance of the sonality (Fig. 4; Table S2). Shifts into wetter environments are most common compounds as described by HeliaMet Subset associated with reduced toughness and ash content, and shifts PC1 (R2 = 0.56; Table 1). HeliaMet PCO2 reflects a general into environments with more seasonal rainfall are associated with differentiation between annual and perennial Helianthus species increased ash content (Fig. 4; Table S2). Lastly, shifts on to soils that is significant by PGLS-ANOVA (Fig. 3). With respect to with higher organic matter, N, and phosphorus are associated leaf-level defenses, HeliaMet PCO1 correlates positively with with decreased thickness and ash content, as well as increased thickness, toughness, and ash content, while HeliaMet PCO2 lipid content (Fig. 4; Table S2). correlates negatively with tannin activity and C : N ratio, Secondary metabolite variation is also correlated with environ- although none of these correlations is particularly strong mental characteristics. HeliaMet PCO1 (reflecting the average (R2 ≤ 0.26; Table 1). number of compounds) is associated with shifts in soil organic The subset of 22 secondary compounds present in at least 20 matter and N content, with higher average number of com- species of Helianthus is dominated by phenylpropanoids, espe- pounds detected in more fertile environments (Fig. 4; Table S2). cially hydroxycinnamoyl-quinic acid conjugates (Table S1). The Both HeliaMet PCO2 and HeliaMet Subset PC1 are associated list also includes three putative coumarins (coumarin, scopolin, with shifts in aridity index and precipitation seasonality, with and scopoletin) as well as one putative terpenoid (ciliarin), all of higher abundance of the most common compounds in wetter and which have been previously reported in sunflowers (Table S1; Tal less seasonal environments (Fig. 4; Table S2). Additionally, & Robeson, 1986; Spring & Schilling, 1990; Olson & Roseland, HeliaMet Subset PC2 is correlated with mean annual temperature, 1991). The overall abundance of these 22 compounds, as temperature seasonality, and soil phosphorus (Fig. 4; Table S2).

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(a)

(b)

Fig. 2 Lack of coherent defense syndromes across Helianthus. (a) Principal components analysis shows continuous variation among species across multivariate trait space (left), as well as a lack of prominent axes of variation across leaf-level defenses and the HeliaMet metrics of average number of compounds and HeliaMet subset PC1 (right). (b) Comparison of phylogentic relationships (left, Stephens et al., 2015) with dendrogram of defense trait similarity using Ward’s clustering algorithm on standardized data (right). Similarity proﬁling (SIMPROF) yields no signiﬁcant clustering of species (p = 2.55; P = 0.432).

and long-term infestation. At 1 wk, species with a higher average Leaf defenses as predictors of herbivore and disease number of compounds are significantly healthier than those with resistance lower average numbers, while at 1 month species with higher Many leaf-level defenses and metrics of secondary metabolite abundance of the most common compounds (as described by variation predict differential species responses to herbivores and HeliaMet Subset PC1) are significantly healthier than those with disease reported in the literature. The proliferation of aphids lower abundance (Fig. 5; Table S3). Unlike aphids and leafhop- (Masonaphis masoni) is negatively correlated with tannin activity, pers, which both belong to the piercing/sucking feeding guild HeliaMet Subset PC1, and the average number of compounds and are impacted strongly by chemical traits, herbivory by the (Fig. 5; Table S3). Among individual compounds, aphid abun- chewing caterpillar larvae of the painted lady butterfly (Vanessa dance is negatively correlated with the abundance of several cardui) is strongly associated with physical defenses. The mass of HeliaMet peaks putatively identified as hydroxycinnamoyl-quinic leaf consumed in feeding trials is negatively correlated with both acid conjugates (Table S3). Contrary to expectations, trichome leaf toughness and ash content and strongly positively correlated density, ash content, and C : N ratio are positively correlated with with LDMC (Table S3). However, consumption by this herbi- aphid proliferation (Table S3). Unlike aphids, the proliferation vore also has the strongest correlations with individual secondary of leafhoppers (Empoasca abrupta) is weakly negatively correlated metabolites observed in this study, with p-coumaroylquinic acid with trichome density, and associated with no other traits and a compound putatively identified as syringic acid extremely (Table S3). Plant performance under leafhopper attack, however, predictive of consumption (Table S3). is associated with several traits, although correlations between With respect to disease resistance, leaf defenses and secondary traits and plant performance are highly variable between metabolite variation do not strongly predict resistance to leaf responses assessed at 1 wk and 1 month (Table S3), indicating blight by Alternaria helianthii or head rot by Rhizopus species that different traits probably govern plant response under short- (Table S4). However, resistance to powdery mildew (Erysiphe

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Fig. 3 Evolution of the two primary axes of secondary metabolite composition across Helianthus, as defined by species-level principal coordinates analysis and plotted using the phylomorphospace function in phytools (Revell, 2012). Species are coded by growth form and life history: annuals (red circles), erect perennials (green squares), and basal rosette perennials (blue triangles). Species are connected by phylogenetic relationships, with reconstructed ancestral states of internal nodes plotted in trait space. Note that HeliaMet PCO1 is strongly negatively correlated with the average number of compounds per species (R2 = 0.82; Table 1), HeliaMet PCO2 is strongly negatively correlated with abundance of the most common compounds as described by HeliaMet subset PC1 (R2 = 0.56; Table 1), and HeliaMet PCO2 is significantly associated with life history by PGLS-ANOVA (P = 0.0185), with annuals significantly different from both types of perennials by post hoc test.

chicoracearum) is strongly predicted by the abundance of the allowing for individual defenses to evolve in a labile manner with- most common secondary metabolites as described by HeliaMet out compromising overall plant defense (Agrawal, 2007, 2011). Subset PC1 (Fig. 5; Table S4), and level of infection is strongly This model of defense evolution explains why no strong global- negatively correlated with the majority of phenylpropanoid scale trade-offs in defenses have been identified (Moles et al., derivatives (Table S4). Most leaf-level defense traits are not con- 2013), but also why recurring evolution of syndromes of defenses sistently correlated with powdery mildew disease index under might be common within some genera but not others (Agrawal both field and glasshouse conditions, although ash content is con- & Fishbein, 2006; Agrawal, 2011; Haak et al., 2013; Johnson sistently positively correlated with the level of infection et al., 2014). (Table S4). In a similar manner, resistance to the parasitic plant Among the wild sunflowers assessed here, the most widespread broomrape (Orobanche cernua) is not strongly predicted by most group of secondary metabolites are the phenylpropanoids, with leaf-level defenses, with the exception of tannin activity, which is high levels evolving together repeatedly probably as a result of negatively correlated with the incidence of broomrape infection shared biosynthetic pathways (Salminen & Karonen, 2011). (Fig. 5; Table S4). Some of these metabolites have been previously identified as the most abundant phenolics in crop sunflower seeds (Weisz et al., Discussion 2009). Additionally, the three putative coumarins found to be widespread across the genus (coumarin, scopolin, and scopoletin) are known to contribute to herbivore and pathogen resistance in Little evidence for trade-offs or syndromes in defense cultivated sunflower (Tal & Robeson, 1986; Olson & Roseland, Across Helianthus, there is little evidence for univariate trade-offs 1991) and its wild progenitor (Roseland & Grosz, 1997). Our among leaf-level defense traits, as well as little evidence for recur- results suggest that phenolics and coumarins are abundant across ring defense syndromes. In general, many different combinations the wild members of the genus as well, and thus probably play a of physical and chemical defenses have evolved across sunflowers. role in herbivore and pathogen resistance as in crop sunflower. This supports the emerging model of plant defense that suggests The relative lack of sesquiterpene lactones and other terpenoids that the overall function of defenses (to reduce total herbivore may reflect limitations of the analytical procedures used in this and pathogen pressure) is achieved by the totality of defenses pre- study. Alternatively, the apparent limited distribution within the sent, and that investment in multiple defenses is unlikely to be genus of individual sesquiterpene lactones and other terpenoids redundant or wasteful (Agrawal, 2007, 2011). Rather than may reflect rapid diversification of these compounds within the responding to individual defenses, herbivores and pathogens genus, such that few individual compounds are shared across experience the full suite of defense traits in a multivariate way, many species. Early work characterizing these compounds in wild

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r investment in these defenses probably trades off with inherent growth rate. This fits with the first prediction of the resource availability hypothesis, with higher defense in species with leaf physiology supporting slower inherent growth (Endara & Coley, 2011). However, the second prediction of the hypothesis – that faster inherent growth rate is driven by higher resource availabil- Soil phosphorus MAT Temp. seasonality Aridity index Precip. seasonality Soil organic matte Soil nitrogen ity – does not hold across Helianthus (Mason & Donovan, Trichome density + 2015b). For instance, while faster leaf economic strategy is generally positively related to metrics of soil fertility, faster leaf eco- Thickness + – – nomic strategy is strongly negatively related to water availability Toughness – (Mason & Donovan, 2015b).While we lack detailed information on which resources most limit growth across environments in LDMC Helianthus, it appears that water availability plays a relatively Tannin activity stronger role than soil fertility (Mason & Donovan, 2015b). In fact, some of the fastest growing annual sunflowers occur in arid Lipid content – + + + deserts, while some of the slowest growing basal rosette perennials occur in the moist habitats of the southeastern USA (Mason & Ash content – + – – – Donovan, 2015b). Given this, associations between defense traits and environmental characteristics were highly mixed in strength C:N ratio + – and direction and did not support the second prediction of the HeliaMet PCO1 – – resource availability hypothesis. This pattern is likely to hold across habitats in many short-lived herbaceous plants, where HeliaMet PCO2 – + + drought-escape and other fast-growth strategies for overcoming abiotic stress often dominate low-resource habitats. This calls Avg. no. of compounds + + into question the applicability of the second prediction of the resource availability hypothesis for herbaceous plants, in contrast HeliaMet Subset PC1 + – to the persistent woody species for which the hypothesis was orig- HeliaMet Subset PC2 – + + inally developed (Coley et al., 1985, Coley, 1987; Stamp, 2003). Because many leaf defense traits also serve other physiological Fig. 4 Macroevolutionary correlations between selected environmental functions, environmental correlations should be interpreted with characteristics and leaf physical defenses, chemical defenses, caution in relation to the resource availability hypothesis. Many carbon : nitrogen (C : N) ratio, leaf economic spectrum (LES) strategy, and HeliaMet metrics, as assessed by phylogenetic mixed model. Directionality defense traits may evolve primarily under selection from the abi- of significant correlations (P < 0.05) is presented, with correlations in boxes otic environment, despite providing effective defense against outlined in bold significant at the more stringent multiple comparisons cut- herbivores (Agrawal, 2011). This may be the case across off (false discovery rate; Benjamini & Hochberg, 1995). R2 values and Helianthus, where for instance we find repeated evolution of correlations with additional environmental characteristics are listed in higher trichome density with increasing mean annual tempera- Supporting Information Table S2. LDMC, leaf dry matter content; MAT, mean annual temperature; PC1 and PC2, first and second principal ture. Trichomes are known to be important for preventing water components axes; PCO1 and PCO2, first and second principal coordinate loss, excessive heat build-up, and the absorbance of harmful axes. ultraviolet radiation, all of which are important functions in hot environments (Levin, 1973; Karabourniotis et al., 1992; Save sunflowers found that many were detected in only a handful of et al., 2000; Hanley et al., 2007). These effects have been found species, and many more were variable within species (Spring & for the North American milkweeds, in which trichome density Schilling, 1989, 1990, 1991), suggesting that terpenoids indeed evolves primarily in response to aridity despite having anti- evolve more rapidly than phenolics and coumarins. herbivore function (Agrawal et al., 2009b). We also find repeated evolution across Helianthus of higher leaf toughness, with shifts to both drier environments and those with a higher Mixed support for the resource availability hypothesis diurnal temperature range, and toughness is known to be associ- across Helianthus ated with reduced water loss in drier environments, as well as Across Helianthus, species with more resource-conservative leaf potentially provide protection against extreme temperatures economic traits supporting a slower-growth persistence strategy (Bacelar et al., 2004; Groom et al., 2004; Hanley et al., 2007). have tougher, more succulent leaves with higher tannin activity. Additionally, the resource availability hypothesis was developed Interestingly, these three defenses have previously been linked to to predict investment in herbivore resistance, and may not apply shifts in leaf economic strategy through whole-plant ontogeny in to the less straightforward selective pressures imposed by plant three species of wild sunflowers (Mason & Donovan, 2015a). disease. For instance, in wetter environments and those with less This suggests that relationships between leaf economic traits and seasonal precipitation, we find repeated evolution of higher these defenses hold across scales in Helianthus, and that abundance of the most common secondary metabolites

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Fig. 5 Ancestral state reconstruction of selected traits and correlations with metrics of plant performance under herbivore, pathogen, or parasite pressure. Reconstructions were performed with maximum likelihood using the fastAnc function in the R package phytools (Revell, 2012). Macroevolutionary correlations were calculated using the phylopars method (Bruggeman et al., 2009), and regression slopes were calculated from phylogenetic trait covariance. Additional correlations are listed in Supporting Information Tables S3 and S4.

(HeliaMet Subset PC1). Wetter environments are known to pathogen load (Burdon et al., 1989; Freckleton & Lewis, 2006), promote the dispersal, colonization, and growth of bacterial and such that infertile soils provide a refuge from pathogens fungal pathogens on leaf surfaces (Fitt et al., 1989; Bradley et al., (Springer, 2009). 2003), and it is possible that higher abundance of hydroxycinnamoyl-quinate derivatives (which have known antimicrobial Defenses and secondary metabolites predict herbivory and activity) may prevent infection in wet environments (Zhu et al., € disease resistance 2004; Ozcßelik et al., 2011). Similarly, we also ﬁnd repeated evolution of higher lipid content (including resins, waxes, and oils), Despite the fact that responses to herbivory and disease were and higher metabolite proﬁle complexity in more fertile environ- assembled from across a variety of previous screening studies of ments. These traits may function in a similar manner if fertile wild Helianthus, strong relationships were found here between environments promote denser vegetation and a higher ambient variation in leaf-level defenses and secondary metabolites and

New Phytologist (2015) Ó 2015 The Authors www.newphytologist.com New Phytologist Ó 2015 New Phytologist Trust New Phytologist Research 11 variation in responses to insect herbivores, fungal pathogens, and a parasitic plant. This suggests that constitutive defenses assessed References here play a large role in the response to herbivory and disease Agrawal AA. 2007. Macroevolution of plant defense strategies. Trends in Ecology – across Helianthus, as if differences in resistance among species & Evolution 22: 103 109. Agrawal AA. 2011. Current trends in the evolutionary ecology of plant defence. were primarily attributable to inducible defenses we would not Functional Ecology 25: 420–432. be able to detect the strong patterns observed here. That being Agrawal AA, Fishbein M. 2006. Plant defense syndromes. 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Table S1 Putative identities and factor loadings for the 22 most Notes S1 Population source localities and USDA accessions, common HeliaMet compounds population trait means, species trait means, and herbivore and disease resistance data (data used in this study (Notes S1 and Table S2 Macroevolutionary correlations between defenses and Notes S2) are available via Dryad: doi: 10.5061/dryad.5hq56) environmental characteristics Notes S2 HeliaMet database: normalized peak data obtained by Table S3 Macroevolutionary correlations between defenses and HPLC-MS. herbivores Please note: Wiley Blackwell are not responsible for the content Table S4 Macroevolutionary correlations between defenses and or functionality of any supporting information supplied by the pathogens/parasites authors. Any queries (other than missing material) should be directed to the New Phytologist Central Ofﬁce. Methods S1 Additional methodological details.

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