Annals of Botany 118: 135–148, 2016 doi:10.1093/aob/mcw072, available online at www.aob.oxfordjournals.org
PART OF A HIGHLIGHT ON ORCHID BIOLOGY
Evolution and diversity of floral scent chemistry in the euglossine bee-pollinated orchid genus Gongora Molly C. Hetherington-Rauth1,2 and Santiago R. Ramırez2,* 1
Biology Department, University of Toronto Mississauga, 3359 Mississauga Road North, Mississauga, ON L5L 1C6, Canada and 2Department of Evolution and Ecology, University of California, Davis, 1 Shields Avenue, Davis, CA 95616, USA *For correspondence. E-mail [email protected] Received: 15 December 2015 Returned for revision: 29 February 2016 Accepted: 16 March 2016 Published electronically: 30 May 2016
Background and Aims Animal-pollinated angiosperms have evolved a variety of signalling mechanisms to attract pollinators. Floral scent is a key component of pollinator attraction, and its chemistry modulates both pollinator behaviour and the formation of plant–pollinator networks. The neotropical orchid genus Gongora exhibits specialized pollinator associations with male orchid bees (Euglossini). Male bees visit orchid flowers to collect volatile chemical compounds that they store in hind-leg pouches to use subsequently during courtship display. Hence, Gongora floral scent compounds simultaneously serve as signalling molecules and pollinator rewards. Furthermore, because floral scent acts as the predominant reproductive isolating barrier among lineages, it has been hypothesized that chemical traits are highly species specific. A comparative analysis of intra- and inter-specific variation of floral scent chemistry was conducted to investigate the evolutionary patterns across the genus. Methods Gas chromatography–mass spectrometry (GC-MS) was used to analyse the floral scent of 78 individuals belonging to 28 different species of Gongora from two of the three major lineages sampled across the neotropical region. Multidimensional scaling and indicator value analyses were implemented to investigate the patterns of chemical diversity within and among taxonomic groups at various geographic scales. Additionally, pollinator observations were conducted on a sympatric community of Gongora orchids exhibiting distinct floral scent phenotypes. Key Results A total of 83 floral volatiles, mainly terpenes and aromatic compounds, were detected. Many of the identified compounds are common across diverse angiosperm families (e.g. cineole, eugenol, b-ocimene, b-pinene and terpinen-4-ol), while others are relatively rare outside euglossine bee-pollinated orchid lineages. Additionally, 29 volatiles were identified that are known to attract and elicit collection behaviour in male bees. Floral scent traits were less variable within species than between species, and the analysis revealed exceptional levels of cryptic diversity. Gongora species were divided into 15 fragrance groups based on shared compounds. Fragrance groups indicate that floral scent variation is not predicted by taxonomic rank or biogeographic region. Conclusions Gongora orchids emit a diverse array of scent molecules that are largely species specific, and closely related taxa exhibit qualitatively and quantitatively divergent chemical profiles. It is shown that within a community, Gongora scent chemotypes are correlated with near non-overlapping bee pollinator assemblies. The results lend support to the hypothesis that floral scent traits regulate the architecture of bee pollinator associations. Thus, Gongora provides unique opportunities to examine the interplay between floral traits and pollinator specialization in plant–pollinator mutualisms. Key words: Euglossine bees, floral scent, orchid genus Gongora, plant–pollinator mutualism, Euglossa.
INTRODUCTION Mutualisms between flowering plants and their insect pollinators have shaped the evolution of floral traits and are thought to contribute significantly to angiosperm diversification (Darwin, 1862; Crepet, 1984; Johnson, 1996; Dodd, et al., 1999; Kay, 2006; Kay and Sargent, 2009; Schiestl and Schlu¨ter, 2009; van der Niet et al., 2014; Breitkopf et al., 2015). Pollinator attraction is often mediated by multimodal signalling mechanisms, including floral morphology, colour and scent (Raguso, 2001; Willmer, 2011). Floral scent is thought to play a central role in mediating pollinator attraction and specificity, especially among highly specialized plant–pollinator interactions (Raguso, 2001; Schiestl and Ayasse, 2002; Mant et al., 2005; Peakall et al., 2010; Willmer, 2011; Xu et al., 2011; Ju¨rgens et al., 2013; Peakall and Whitehead, 2014; van der Niet et al., 2014).
Angiosperms emit an exceptionally diverse array of floral scent molecules (Knudsen et al., 1993; Knudsen and Gershenzon, 2006), and many classes of volatile compounds are recurrently associated with specific pollinators, thus suggesting that olfactory sensory mechanisms and behavioural preferences of pollinators have shaped the evolution of floral scent chemistry (Schiestl et al., 2010; Ramırez et al., 2011; Steiger et al., 2011; Schiestl and Do¨tterl, 2012; Ju¨rgens et al., 2013). The neotropical orchid genus Gongora (Orchidaceae: Cymbidieae) exhibits specialized mutualistic associations with scent-collecting male euglossine bees (Fig. 1), in which floral scent volatiles act simultaneously as attractant molecules and insect pollinator rewards (Dodson et al., 1969). Male euglossine bees (Apidae: Euglossini) visit a diverse array of floral sources (e.g. orchids and other angiosperm families) as well as
C The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. V This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Hetherington-Rauth & Ramırez — Evolution of floral scent in Gongora
136 A
C
Subgenus Portentosa
Subgenus Acropera
Section Acropera
G. galeata Lindley
Section Armeniaca Section Cassidea
B Section Gongora
Subgenus Gongora
G. cassidea Rchb.f. G. aceras Dressler G. aromatica Rchb.f. G. chocoensis Jenny G. clavidora Dressler G. cruciformis Whitten & D.E.Benn G. fulva Lindley G. gracilis Jenny G. ilense Whitten & Jenny G. leucochila Lemaire G. aff. odoratissma Lemaire G. pleiochroma Rchb.f. G. powellii Schlechter G. aff. quinquenervis Ruiz & Pavon G. rufescens Jenny G. sp. (Brazil) G. sp. Chemotype A G. sp. Chemotype M G. sp. Chemotype S G. superflua Rchb.f. G. tricolor [Lindley] Rchb.f. G. aff. unicolor Schlechter
Section Gratulabunda Section Grossa
Section Truncata
G. grossa Rchb.f. G. scaphephorus Rchb.f. & Warsc. G. sphaerica Jenny G. tracyana Rolfe G. truncata Lindley
FIG. 1. (A) Gongora sp. chemotype M (subgenus Gongora, section Gongora) being visited by Euglossa dodsoni. (B) Male euglossine bees collect perfume compounds and store them in hind-leg pockets (arrow) subsequently to expose to females during courtship display (photo: B. Jacobi). (C) Putative phylogenetic relationships of Gongora lineages sampled in the present study (as summarized by Hetherington-Rauth and Ramırez, 2015).
non-floral resources (e.g. fungi, rotting vegetation and decaying wood) in order to gather and concoct species-specific perfume blends, which they store in pockets located in the hind tibiae (Eltz et al., 1999). Male bees subsequently expose perfume compounds during courtship to convey information on male quality (fitness) or identity (species) (Eltz et al., 2003). While gathering floral volatiles from orchids, male bees inadvertently remove pollinaria and upon visitation of another flower deposit pollinaria on the stigmatic surface (Allen, 1954; Dressler, 1981; Rodriguez Flores et al., 1995; Hetherington-Rauth and Ramırez, 2015). Thus, reliable floral cues (scents) are needed to ensure species-specific pollination. Because Gongora orchids lack additional floral rewards (such as nectar and/or edible pollen) that could potentially attract other pollinators, they rely exclusively on male euglossine bees for sexual reproduction. Between one and five species of eulgossine bee visit a single species of Gongora in a given locality (Dressler, 1968a; Whitten, 1985; Hentrich, 2004; Hetherington-Rauth and Ramırez, 2015). Euglossine bees occur throughout the neotropical region, with >230 described species (Ramırez et al., 2002, 2010b;
Nemesio and Silveira, 2007). Male bees partition chemical niche space by collecting species-specific perfumes (Zimmermann et al., 2009). The chemical phenotype of each species’ perfume is conserved across geography, even among populations inhabiting disparate habitats (Zimmermann et al., 2006; Ramırez, et al., 2010a). Therefore, the chemical preferences of male bees probably exert strong selective pressures on the chemistry and phenotypic variation of orchid floral scent (Ramırez et al., 2011). In fact, Dressler (1966) remarked that by placing two varieties of Gongora that differed in their perceivable floral scent on either side of a trail, he was able to invent an ‘excellent bee sorter’ (p. 220) with only green bees visiting one variety and only blue bees visiting the other. This demonstrated the potential of floral scent to attract specific pollinator assemblages, and raised the possibility that positive assortative mating could emerge, with variation in floral scent resulting in pre-pollination ethological isolation among orchid populations (Jones, 2001). The genus Gongora contains 60–70 species that are broadly distributed throughout lowland neotropical rain forests (Jenny, 1993). Gongora orchids are long-lived perennial epiphytes that
Hetherington-Rauth & Ramırez — Evolution of floral scent in Gongora produce pendent inflorescences with approx. 10–20 flowers (but some produce up to 50 flowers) that open simultaneously and smell strongest in the morning hours when male bees are most active (Fig. 1A, B) (Hetherington-Rauth and Ramırez, 2015). Flowers typically last a few days before wilting. Although no species-level phylogeny exists for the genus, molecular data support a division of Gongora into three subgenera – subgenus Portentosa, subgenus Acropera and subgenus Gongora – and places subgenus Portentosa as sister to the clade Acropera þ Gongora (Whitten et al., 2000, 2014; Hetherington-Rauth and Ramırez, 2015). The subgenus Gongora is divided into four sections – section Gongora, section Grossa, section Gratulabunda and section Truncata (Fig. 1C). Gongora is hypothesized to have experienced a relatively recent diversification within the sub-tribe Stanhopeinae (þCoeliopsidinae) for which euglossine bee pollination is the ancestral state (Whitten et al., 1986; Ramırez et al., 2011; Hetherington-Rauth and Ramırez, 2015). Species diagnoses in Gongora are largely based on floral morphology, and although floral scent has a major impact on reproductive isolation, scent traits and/or pollinator associations have not been used to define species. Hence, taxonomic confusion has accumulated, particularly in the subgenus Gongora section Gongora, where seemingly distinct species exist – as evidenced by the presence of non-overlapping pollinator assemblages – with little morphological differentiation (Dressler, 1966, 1968a; Whitten, 1985; Jenny, 1993; Hentrich, 2004; Hetherington-Rauth and Ramırez, 2015). Although floral scent appears to play a central role in reproductive isolation in Gongora, little is known about its chemistry, variation and evolution across the genus. Previous studies on scent chemistry have been restricted to either a few species or populations from a single locality (Hills et al., 1972; Gerlach and Schill, 1991; Kaiser, 1993). Notably, Whitten (1985) and Hentrich (2004) conducted detailed studies of two different species complexes in the genus Gongora from central Panama and the central Pacific coast of Costa Rica, respectively. Each study identified putative cryptic species through the combination of chemical analyses of floral scent and pollinator observations, and both clearly demonstrated that (1) otherwise indistinguishable individuals produce qualitatively distinct scent phenotypes and (2) floral scent phenotypes correlate with non-overlapping assemblages of bee pollinators. These studies highlight that phenotypic variation in floral scent can influence the formation of specialized plant–pollinator networks, which in turn can lead to the formation of reproductive barriers. We conducted a comparative analysis of floral scent chemistry using approx. 28 species of Gongora from two of the three subgenera with taxa sampled from a broad geographic distribution. In particular, we asked the following questions. (1) What floral volatiles are present in the floral scent? (2) Do species produce species-specific scent bouquets as hypothesized by the existence of strong ethological reproductive isolation and, if so, can floral scent traits inform species delimitation? (3) Are scent chemotypes correlated with the identity of bee pollinator assemblages? (4) Is floral scent taxonomically conserved among subgenera and sections? (5) How are floral scent phenotypes distributed across geography with emphasis on sympatric lineages?
137
MATERIALS AND METHODS Plant material
Gongora orchids were cultivated in a greenhouse facility at the University of California, Davis. In addition, several species used in this study were maintained in outdoor nurseries near Virterbo (Colombia) and La Gamba Tropical Field Station near Golfito (Costa Rica). Plants from La Gamba were collected from the surrounding Esquinas Rainforest on the southern Pacific peninsula of Costa Rica. Plants were identified to species based on floral characters. Individuals that could not be unambiguously identified to species were given a species affinis (aff.) name. No species names are available for La Gamba Gongora and thus these are referred based on their scent profiles: chemotype A, chemotype S and chemotype M. We only used individuals with known and/or inferred collection localities (Supplementary Data Table S1). Collection of floral volatiles
We sampled floral scent using a static headspace method (Williams and Whitten, 1983; Tholl et al., 2006) from plants kept in the greenhouse or in the field. Sampling was conducted between 0800 and 1300 h on the first, second or third day of anthesis, which corresponds to the time when euglossine bees are most active and floral scent production peaks (Whitten, 1985; Hills, 1989; Hills and Williams, 1990). We bagged one inflorescence with nylon oven bags (Reynolds Kitchens, Richmond, VA, USA) closed at the top with metal wire (Stewart-Jones and Poppy, 2006). Inflorescences were bagged for 30 min. Subsequently, we connected scent traps to an electrical vacuum pump (Parker, Cleveland, OH, USA) via Tygon tubing (ID 33 mm) and continuously extracted air from the bag through a small slit. Single-use scent traps were constructed using clear glass tubing (24 mm ID, 35 cm length) plugged at both ends with glass wool and filled with 20 mg of bulk carbide (charcoal) and 20 mg of Tenax GC (SUPELCO, Bellefonte, PA, USA; mesh size 60/80) (Williams and Whitten, 1983; Whitten, 1985; Raguso and Pellmyr, 1998). Scent traps were conditioned by passing 5 mL of hexane. Air was pulled from the headspace through the scent trap at 25 L min1 for 2 h. Scent traps were eluted with 200 lL of hexane into conical inserts (Agilent Technologies, Santa Clara, CA, USA) held in 2 mL auto-sampler vials (Agilent Technologies). Auto-sampler vials were capped with screw cap PTFE/silicon lids (Agilent Technologies) and stored at –20 C until analysed. Control samples were collected simultaneously in the same manner from oven bags filled with ambient air. Samples were acquired between January 2014 and April 2015. Whenever possible, we sampled three unique inflorescences per plant. Gas chromatography–mass spectrometry (GC-MS) analysis
We analysed samples with an Agilent 7890B GC fitted with a 30 m 025 mm 025 lm HP-5 Ultra Inert column coupled to an Agilent 5977A mass spectrometer (Agilent Technologies). Using an auto-sampler, we injected 1 lL into the gas chromatograph at a 5:1 split ratio. The split ratio was adjusted for some samples to increase detection thresholds (see
138
Hetherington-Rauth & Ramırez — Evolution of floral scent in Gongora
Table S1). Oven temperature was held at 60 C for 3 min and then increased by 10 C min1 until it reached 300 C; then the oven temperature was kept at 315 C for 1 min. Both injector and transfer line temperatures were kept constant at 250 C. Helium served as the carrier gas with a constant flow rate set to 12 mL min1. Electron impact mass spectra were obtained by scanning between 30 and 550 m/z. GC-MS data were processed using MassHunter GC/MS Acquisition software vB.07.00 (Agilent) and MSD ChemStation Enhanced Data Analysis Software vF.01.00 (Agilent). Compound characterization
We tentatively identified individual compounds using the NIST05 mass spectral database and the NIST MS Search software v2.0. We confirmed compound identification by comparing relative retention times of authentic chemical standards run under the same conditions. In addition, we compared the calculated Kovats Retention Indexes, estimated with a series of alkane standards (C7–C30), with that of published data (Adams, 2007). For compounds that we were unable to identify unambiguously, we list their EI mass spectrum ions. We removed putative contaminant compounds when present with comparable peak areas (within a factor of 10) in both the control and the sample. We determined total ion abundances by integrating peaks in the MSD ChemStation software using the RTE integrator. Only peaks with an area 3 % of the largest peak were included in downstream analyses. When compound co-elution occurred, de-convolution was performed using AMDIS software v2.64. The total peak area was partitioned among co-eluting peaks based on the relative areas of two to three diagnostic ions. Compounds contributing less than one-tenth to the total peak area were discarded. Statistical analysis
We implemented multivariate statistical approaches to investigate the variation of chemical profiles among individuals and taxa. Briefly, we normalized raw chromatogram peak areas by calculating the contribution of each compound relative to the total area. We averaged the relative proportion of each compound across samples of the same individual. In addition, we created a binary matrix (presence/absence) in which all compounds are equally weighted. We calculated pairwise distance among individuals for both relative proportions and binary values using the Bray–Curtis dissimilarity metric in the package ‘ecodist’ v1.2.9. The Bray–Curtis dissimilarity metric is unaffected by ‘double zeros’ and only considers compounds that are jointly shared between individuals (Beals, 1984; Zimmermann et al., 2009; Legendre and Legendre, 2012). The dissimilarity matrices were used to conduct non-metric multidimensional scaling (nMDS) analysis. This method visually represents similarity amongst individuals in pre-specified reduced space dimensions, using a non-eigenvector approach that allows for a flexible choice of distance metrics (e.g. Bray–Curtis) (Jones, 2001; Zimmermann et al., 2009). We constructed two-dimensional plots using two different algorithms: the ‘metaMDS’ algorithm in ‘vegan’ v2.2-1 and the ‘nmds’ algorithm in ‘ecodist’ v1.2.9. Each algorithm produced similar plots but differed in
that the ‘vegan’ algorithm tended to minimize variation relative to the ‘ecodist’ algorithm. We used 20 random starting configurations. The resulting inter-point distances attempt to maximize the rank-ordered chemical distances among individuals (Clarke and Warwick, 2001). Individuals clustering together share a similar floral scent composition. The stress value (ranging from 0 to 1) associated with the nMDS plot reflects how well the algorithm preserved the rank-ordered distance measures. Stress values
PART OF A HIGHLIGHT ON ORCHID BIOLOGY
Evolution and diversity of floral scent chemistry in the euglossine bee-pollinated orchid genus Gongora Molly C. Hetherington-Rauth1,2 and Santiago R. Ramırez2,* 1
Biology Department, University of Toronto Mississauga, 3359 Mississauga Road North, Mississauga, ON L5L 1C6, Canada and 2Department of Evolution and Ecology, University of California, Davis, 1 Shields Avenue, Davis, CA 95616, USA *For correspondence. E-mail [email protected] Received: 15 December 2015 Returned for revision: 29 February 2016 Accepted: 16 March 2016 Published electronically: 30 May 2016
Background and Aims Animal-pollinated angiosperms have evolved a variety of signalling mechanisms to attract pollinators. Floral scent is a key component of pollinator attraction, and its chemistry modulates both pollinator behaviour and the formation of plant–pollinator networks. The neotropical orchid genus Gongora exhibits specialized pollinator associations with male orchid bees (Euglossini). Male bees visit orchid flowers to collect volatile chemical compounds that they store in hind-leg pouches to use subsequently during courtship display. Hence, Gongora floral scent compounds simultaneously serve as signalling molecules and pollinator rewards. Furthermore, because floral scent acts as the predominant reproductive isolating barrier among lineages, it has been hypothesized that chemical traits are highly species specific. A comparative analysis of intra- and inter-specific variation of floral scent chemistry was conducted to investigate the evolutionary patterns across the genus. Methods Gas chromatography–mass spectrometry (GC-MS) was used to analyse the floral scent of 78 individuals belonging to 28 different species of Gongora from two of the three major lineages sampled across the neotropical region. Multidimensional scaling and indicator value analyses were implemented to investigate the patterns of chemical diversity within and among taxonomic groups at various geographic scales. Additionally, pollinator observations were conducted on a sympatric community of Gongora orchids exhibiting distinct floral scent phenotypes. Key Results A total of 83 floral volatiles, mainly terpenes and aromatic compounds, were detected. Many of the identified compounds are common across diverse angiosperm families (e.g. cineole, eugenol, b-ocimene, b-pinene and terpinen-4-ol), while others are relatively rare outside euglossine bee-pollinated orchid lineages. Additionally, 29 volatiles were identified that are known to attract and elicit collection behaviour in male bees. Floral scent traits were less variable within species than between species, and the analysis revealed exceptional levels of cryptic diversity. Gongora species were divided into 15 fragrance groups based on shared compounds. Fragrance groups indicate that floral scent variation is not predicted by taxonomic rank or biogeographic region. Conclusions Gongora orchids emit a diverse array of scent molecules that are largely species specific, and closely related taxa exhibit qualitatively and quantitatively divergent chemical profiles. It is shown that within a community, Gongora scent chemotypes are correlated with near non-overlapping bee pollinator assemblies. The results lend support to the hypothesis that floral scent traits regulate the architecture of bee pollinator associations. Thus, Gongora provides unique opportunities to examine the interplay between floral traits and pollinator specialization in plant–pollinator mutualisms. Key words: Euglossine bees, floral scent, orchid genus Gongora, plant–pollinator mutualism, Euglossa.
INTRODUCTION Mutualisms between flowering plants and their insect pollinators have shaped the evolution of floral traits and are thought to contribute significantly to angiosperm diversification (Darwin, 1862; Crepet, 1984; Johnson, 1996; Dodd, et al., 1999; Kay, 2006; Kay and Sargent, 2009; Schiestl and Schlu¨ter, 2009; van der Niet et al., 2014; Breitkopf et al., 2015). Pollinator attraction is often mediated by multimodal signalling mechanisms, including floral morphology, colour and scent (Raguso, 2001; Willmer, 2011). Floral scent is thought to play a central role in mediating pollinator attraction and specificity, especially among highly specialized plant–pollinator interactions (Raguso, 2001; Schiestl and Ayasse, 2002; Mant et al., 2005; Peakall et al., 2010; Willmer, 2011; Xu et al., 2011; Ju¨rgens et al., 2013; Peakall and Whitehead, 2014; van der Niet et al., 2014).
Angiosperms emit an exceptionally diverse array of floral scent molecules (Knudsen et al., 1993; Knudsen and Gershenzon, 2006), and many classes of volatile compounds are recurrently associated with specific pollinators, thus suggesting that olfactory sensory mechanisms and behavioural preferences of pollinators have shaped the evolution of floral scent chemistry (Schiestl et al., 2010; Ramırez et al., 2011; Steiger et al., 2011; Schiestl and Do¨tterl, 2012; Ju¨rgens et al., 2013). The neotropical orchid genus Gongora (Orchidaceae: Cymbidieae) exhibits specialized mutualistic associations with scent-collecting male euglossine bees (Fig. 1), in which floral scent volatiles act simultaneously as attractant molecules and insect pollinator rewards (Dodson et al., 1969). Male euglossine bees (Apidae: Euglossini) visit a diverse array of floral sources (e.g. orchids and other angiosperm families) as well as
C The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. V This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Hetherington-Rauth & Ramırez — Evolution of floral scent in Gongora
136 A
C
Subgenus Portentosa
Subgenus Acropera
Section Acropera
G. galeata Lindley
Section Armeniaca Section Cassidea
B Section Gongora
Subgenus Gongora
G. cassidea Rchb.f. G. aceras Dressler G. aromatica Rchb.f. G. chocoensis Jenny G. clavidora Dressler G. cruciformis Whitten & D.E.Benn G. fulva Lindley G. gracilis Jenny G. ilense Whitten & Jenny G. leucochila Lemaire G. aff. odoratissma Lemaire G. pleiochroma Rchb.f. G. powellii Schlechter G. aff. quinquenervis Ruiz & Pavon G. rufescens Jenny G. sp. (Brazil) G. sp. Chemotype A G. sp. Chemotype M G. sp. Chemotype S G. superflua Rchb.f. G. tricolor [Lindley] Rchb.f. G. aff. unicolor Schlechter
Section Gratulabunda Section Grossa
Section Truncata
G. grossa Rchb.f. G. scaphephorus Rchb.f. & Warsc. G. sphaerica Jenny G. tracyana Rolfe G. truncata Lindley
FIG. 1. (A) Gongora sp. chemotype M (subgenus Gongora, section Gongora) being visited by Euglossa dodsoni. (B) Male euglossine bees collect perfume compounds and store them in hind-leg pockets (arrow) subsequently to expose to females during courtship display (photo: B. Jacobi). (C) Putative phylogenetic relationships of Gongora lineages sampled in the present study (as summarized by Hetherington-Rauth and Ramırez, 2015).
non-floral resources (e.g. fungi, rotting vegetation and decaying wood) in order to gather and concoct species-specific perfume blends, which they store in pockets located in the hind tibiae (Eltz et al., 1999). Male bees subsequently expose perfume compounds during courtship to convey information on male quality (fitness) or identity (species) (Eltz et al., 2003). While gathering floral volatiles from orchids, male bees inadvertently remove pollinaria and upon visitation of another flower deposit pollinaria on the stigmatic surface (Allen, 1954; Dressler, 1981; Rodriguez Flores et al., 1995; Hetherington-Rauth and Ramırez, 2015). Thus, reliable floral cues (scents) are needed to ensure species-specific pollination. Because Gongora orchids lack additional floral rewards (such as nectar and/or edible pollen) that could potentially attract other pollinators, they rely exclusively on male euglossine bees for sexual reproduction. Between one and five species of eulgossine bee visit a single species of Gongora in a given locality (Dressler, 1968a; Whitten, 1985; Hentrich, 2004; Hetherington-Rauth and Ramırez, 2015). Euglossine bees occur throughout the neotropical region, with >230 described species (Ramırez et al., 2002, 2010b;
Nemesio and Silveira, 2007). Male bees partition chemical niche space by collecting species-specific perfumes (Zimmermann et al., 2009). The chemical phenotype of each species’ perfume is conserved across geography, even among populations inhabiting disparate habitats (Zimmermann et al., 2006; Ramırez, et al., 2010a). Therefore, the chemical preferences of male bees probably exert strong selective pressures on the chemistry and phenotypic variation of orchid floral scent (Ramırez et al., 2011). In fact, Dressler (1966) remarked that by placing two varieties of Gongora that differed in their perceivable floral scent on either side of a trail, he was able to invent an ‘excellent bee sorter’ (p. 220) with only green bees visiting one variety and only blue bees visiting the other. This demonstrated the potential of floral scent to attract specific pollinator assemblages, and raised the possibility that positive assortative mating could emerge, with variation in floral scent resulting in pre-pollination ethological isolation among orchid populations (Jones, 2001). The genus Gongora contains 60–70 species that are broadly distributed throughout lowland neotropical rain forests (Jenny, 1993). Gongora orchids are long-lived perennial epiphytes that
Hetherington-Rauth & Ramırez — Evolution of floral scent in Gongora produce pendent inflorescences with approx. 10–20 flowers (but some produce up to 50 flowers) that open simultaneously and smell strongest in the morning hours when male bees are most active (Fig. 1A, B) (Hetherington-Rauth and Ramırez, 2015). Flowers typically last a few days before wilting. Although no species-level phylogeny exists for the genus, molecular data support a division of Gongora into three subgenera – subgenus Portentosa, subgenus Acropera and subgenus Gongora – and places subgenus Portentosa as sister to the clade Acropera þ Gongora (Whitten et al., 2000, 2014; Hetherington-Rauth and Ramırez, 2015). The subgenus Gongora is divided into four sections – section Gongora, section Grossa, section Gratulabunda and section Truncata (Fig. 1C). Gongora is hypothesized to have experienced a relatively recent diversification within the sub-tribe Stanhopeinae (þCoeliopsidinae) for which euglossine bee pollination is the ancestral state (Whitten et al., 1986; Ramırez et al., 2011; Hetherington-Rauth and Ramırez, 2015). Species diagnoses in Gongora are largely based on floral morphology, and although floral scent has a major impact on reproductive isolation, scent traits and/or pollinator associations have not been used to define species. Hence, taxonomic confusion has accumulated, particularly in the subgenus Gongora section Gongora, where seemingly distinct species exist – as evidenced by the presence of non-overlapping pollinator assemblages – with little morphological differentiation (Dressler, 1966, 1968a; Whitten, 1985; Jenny, 1993; Hentrich, 2004; Hetherington-Rauth and Ramırez, 2015). Although floral scent appears to play a central role in reproductive isolation in Gongora, little is known about its chemistry, variation and evolution across the genus. Previous studies on scent chemistry have been restricted to either a few species or populations from a single locality (Hills et al., 1972; Gerlach and Schill, 1991; Kaiser, 1993). Notably, Whitten (1985) and Hentrich (2004) conducted detailed studies of two different species complexes in the genus Gongora from central Panama and the central Pacific coast of Costa Rica, respectively. Each study identified putative cryptic species through the combination of chemical analyses of floral scent and pollinator observations, and both clearly demonstrated that (1) otherwise indistinguishable individuals produce qualitatively distinct scent phenotypes and (2) floral scent phenotypes correlate with non-overlapping assemblages of bee pollinators. These studies highlight that phenotypic variation in floral scent can influence the formation of specialized plant–pollinator networks, which in turn can lead to the formation of reproductive barriers. We conducted a comparative analysis of floral scent chemistry using approx. 28 species of Gongora from two of the three subgenera with taxa sampled from a broad geographic distribution. In particular, we asked the following questions. (1) What floral volatiles are present in the floral scent? (2) Do species produce species-specific scent bouquets as hypothesized by the existence of strong ethological reproductive isolation and, if so, can floral scent traits inform species delimitation? (3) Are scent chemotypes correlated with the identity of bee pollinator assemblages? (4) Is floral scent taxonomically conserved among subgenera and sections? (5) How are floral scent phenotypes distributed across geography with emphasis on sympatric lineages?
137
MATERIALS AND METHODS Plant material
Gongora orchids were cultivated in a greenhouse facility at the University of California, Davis. In addition, several species used in this study were maintained in outdoor nurseries near Virterbo (Colombia) and La Gamba Tropical Field Station near Golfito (Costa Rica). Plants from La Gamba were collected from the surrounding Esquinas Rainforest on the southern Pacific peninsula of Costa Rica. Plants were identified to species based on floral characters. Individuals that could not be unambiguously identified to species were given a species affinis (aff.) name. No species names are available for La Gamba Gongora and thus these are referred based on their scent profiles: chemotype A, chemotype S and chemotype M. We only used individuals with known and/or inferred collection localities (Supplementary Data Table S1). Collection of floral volatiles
We sampled floral scent using a static headspace method (Williams and Whitten, 1983; Tholl et al., 2006) from plants kept in the greenhouse or in the field. Sampling was conducted between 0800 and 1300 h on the first, second or third day of anthesis, which corresponds to the time when euglossine bees are most active and floral scent production peaks (Whitten, 1985; Hills, 1989; Hills and Williams, 1990). We bagged one inflorescence with nylon oven bags (Reynolds Kitchens, Richmond, VA, USA) closed at the top with metal wire (Stewart-Jones and Poppy, 2006). Inflorescences were bagged for 30 min. Subsequently, we connected scent traps to an electrical vacuum pump (Parker, Cleveland, OH, USA) via Tygon tubing (ID 33 mm) and continuously extracted air from the bag through a small slit. Single-use scent traps were constructed using clear glass tubing (24 mm ID, 35 cm length) plugged at both ends with glass wool and filled with 20 mg of bulk carbide (charcoal) and 20 mg of Tenax GC (SUPELCO, Bellefonte, PA, USA; mesh size 60/80) (Williams and Whitten, 1983; Whitten, 1985; Raguso and Pellmyr, 1998). Scent traps were conditioned by passing 5 mL of hexane. Air was pulled from the headspace through the scent trap at 25 L min1 for 2 h. Scent traps were eluted with 200 lL of hexane into conical inserts (Agilent Technologies, Santa Clara, CA, USA) held in 2 mL auto-sampler vials (Agilent Technologies). Auto-sampler vials were capped with screw cap PTFE/silicon lids (Agilent Technologies) and stored at –20 C until analysed. Control samples were collected simultaneously in the same manner from oven bags filled with ambient air. Samples were acquired between January 2014 and April 2015. Whenever possible, we sampled three unique inflorescences per plant. Gas chromatography–mass spectrometry (GC-MS) analysis
We analysed samples with an Agilent 7890B GC fitted with a 30 m 025 mm 025 lm HP-5 Ultra Inert column coupled to an Agilent 5977A mass spectrometer (Agilent Technologies). Using an auto-sampler, we injected 1 lL into the gas chromatograph at a 5:1 split ratio. The split ratio was adjusted for some samples to increase detection thresholds (see
138
Hetherington-Rauth & Ramırez — Evolution of floral scent in Gongora
Table S1). Oven temperature was held at 60 C for 3 min and then increased by 10 C min1 until it reached 300 C; then the oven temperature was kept at 315 C for 1 min. Both injector and transfer line temperatures were kept constant at 250 C. Helium served as the carrier gas with a constant flow rate set to 12 mL min1. Electron impact mass spectra were obtained by scanning between 30 and 550 m/z. GC-MS data were processed using MassHunter GC/MS Acquisition software vB.07.00 (Agilent) and MSD ChemStation Enhanced Data Analysis Software vF.01.00 (Agilent). Compound characterization
We tentatively identified individual compounds using the NIST05 mass spectral database and the NIST MS Search software v2.0. We confirmed compound identification by comparing relative retention times of authentic chemical standards run under the same conditions. In addition, we compared the calculated Kovats Retention Indexes, estimated with a series of alkane standards (C7–C30), with that of published data (Adams, 2007). For compounds that we were unable to identify unambiguously, we list their EI mass spectrum ions. We removed putative contaminant compounds when present with comparable peak areas (within a factor of 10) in both the control and the sample. We determined total ion abundances by integrating peaks in the MSD ChemStation software using the RTE integrator. Only peaks with an area 3 % of the largest peak were included in downstream analyses. When compound co-elution occurred, de-convolution was performed using AMDIS software v2.64. The total peak area was partitioned among co-eluting peaks based on the relative areas of two to three diagnostic ions. Compounds contributing less than one-tenth to the total peak area were discarded. Statistical analysis
We implemented multivariate statistical approaches to investigate the variation of chemical profiles among individuals and taxa. Briefly, we normalized raw chromatogram peak areas by calculating the contribution of each compound relative to the total area. We averaged the relative proportion of each compound across samples of the same individual. In addition, we created a binary matrix (presence/absence) in which all compounds are equally weighted. We calculated pairwise distance among individuals for both relative proportions and binary values using the Bray–Curtis dissimilarity metric in the package ‘ecodist’ v1.2.9. The Bray–Curtis dissimilarity metric is unaffected by ‘double zeros’ and only considers compounds that are jointly shared between individuals (Beals, 1984; Zimmermann et al., 2009; Legendre and Legendre, 2012). The dissimilarity matrices were used to conduct non-metric multidimensional scaling (nMDS) analysis. This method visually represents similarity amongst individuals in pre-specified reduced space dimensions, using a non-eigenvector approach that allows for a flexible choice of distance metrics (e.g. Bray–Curtis) (Jones, 2001; Zimmermann et al., 2009). We constructed two-dimensional plots using two different algorithms: the ‘metaMDS’ algorithm in ‘vegan’ v2.2-1 and the ‘nmds’ algorithm in ‘ecodist’ v1.2.9. Each algorithm produced similar plots but differed in
that the ‘vegan’ algorithm tended to minimize variation relative to the ‘ecodist’ algorithm. We used 20 random starting configurations. The resulting inter-point distances attempt to maximize the rank-ordered chemical distances among individuals (Clarke and Warwick, 2001). Individuals clustering together share a similar floral scent composition. The stress value (ranging from 0 to 1) associated with the nMDS plot reflects how well the algorithm preserved the rank-ordered distance measures. Stress values
