Mycorrhizae Alter Constitutive and Herbivore-Induced Volatile Emissions by Milkweeds

Abstract

Plants use volatile organic compounds (VOCs) to cue natural enemies to their herbivore prey on plants. Simultaneously, herbivores utilize volatile cues to identify appropriate hosts. Despite extensive efforts to understand sources of variation in plant communication by VOCs, we lack an understanding of how ubiquitous belowground mutualists, such as arbuscular mycorrhizal fungi (AMF), influence plant VOC emissions. In a full factorial experiment, we subjected plants of two milkweed (Asclepias) species under three levels of AMF availability to damage by aphids (Aphis nerii). We then measured plant headspace volatiles and chemical defenses (cardenolides) and compared these to VOCs emitted and cardenolides produced by plants without herbivores. We found that AMF have plant species-specific effects on constitutive and aphid-induced VOC emissions. High AMF availability increased emissions of total VOCs, two green leaf volatiles (3-hexenyl acetate and hexyl acetate), and methyl salicylate in A. curassavica, but did not affect emissions in A. incarnata. In contrast, aphids consistently increased emissions of 6-methyl-5-hepten-2-one and benzeneacetaldehyde in both species, independent of AMF availability. Both high AMF availability and aphids alone suppressed emissions of individual terpenes. However, aphid damage on plants under high AMF availability increased, or did not affect, emissions of those terpenes. Lastly, aphid feeding suppressed cardenolide concentrations only in A. curassavica, and AMF did not affect cardenolides in either plant species. Our findings suggest that by altering milkweed VOC profiles, AMF may affect both herbivore performance and natural enemy attraction.

Introduction

Plants communicate with and respond to other members of their communities via volatile organic compounds (VOCs) (Dicke and Baldwin 2010; Hare 2011; Karban et al. 2014b; Kessler and Baldwin 2001; Rowen and Kaplan 2016; Turlings and Erb 2018). Using VOCs, plants communicate not only among distant plant parts (Frost et al. 2007; Heil and Ton 2008), but also with neighboring plants (Karban et al. 2014a, 2014b, 2016). Furthermore, plant VOCs cross trophic levels by acting as plant indirect defenses, cueing natural enemies to their herbivore prey on plants, thereby reducing herbivore damage (Kessler and Baldwin 2001; Turlings and Erb 2018). At the same time, herbivores utilize volatile cues to identify appropriate hosts (Bruce et al. 2005; Bruce and Pickett 2011). Plant volatile emissions vary with plant genotype, the identity of the herbivore attackers, and abiotic conditions, generating substantial spatial and temporal variation in multitrophic interactions (Gouinguené and Turlings 2002; Holopainen and Gershenzon 2010; Loreto et al. 2006; Loreto and Schnitzler 2010; Rowen and Kaplan 2016; Trowbridge et al. 2014; Staudt et al. 2010; Turlings and Erb 2018).

Despite extensive efforts to understand sources of variation in plant communication by VOCs (Turlings and Erb 2018), we still lack an understanding of how ubiquitous mutualists of plants, such as arbuscular mycorrhizal fungi (AMF), influence plant constitutive and herbivore-induced VOC emissions. AMF colonize the roots of over 80% of plant species, providing nutrients and water in exchange for plant sugars (Smith and Read 2008; Wang and Qiu 2006). In doing so, AMF interact with plant defensive signaling pathways, including the jasmonic acid (JA) and salicylic acid (SA) pathways (Bucher et al. 2014; Cameron et al. 2013; Gutjahr 2014; Jung et al. 2012). By altering plant nutrient uptake and defensive signaling pathways, AMF influence a diversity of plant primary and secondary metabolites (Bennett et al. 2009; Schweiger et al. 2014; Schweiger and Müller 2015; Vannette et al. 2013). These metabolomic changes may affect plant quality for herbivores (Hartley and Gange 2009; Koricheva et al. 2009). The association with AMF is often mutualistic for plants; AMF frequently stimulate plant growth and mitigate abiotic and pathogen stress (Smith and Read 2008). However, the effects of AMF on plant growth and defense range from beneficial to detrimental, depending on the environment (Hoeksema et al. 2010), plant and AMF identity (Klironomos 2003; Tao et al. 2016), and the density of AMF inoculum available to plants (Garrido et al. 2010; Vannette and Hunter 2011, 2013).

While the effects of AMF on constitutive and herbivore-induced secondary metabolites in leaf tissue are well-established (Barber 2013; Bennett et al. 2009; Kempel et al. 2010; Meier and Hunter 2018a; Vannette and Hunter 2011; Tao et al. 2016; Wang et al. 2015), the role of AMF in shaping plant constitutive and herbivore-induced volatile emissions remains far less understood. Here, we refer to constitutive traits as those always present in plants and herbivore-induced traits as those altered in quantity or synthesized anew in response to herbivore damage (e.g. Karban and Baldwin 1997). AMF alter plant constitutive and herbivore-induced foliar secondary metabolites in a species-specific manner. For instance, several plant species only exhibit herbivore-induction of defensive secondary metabolites when colonized by AMF (Kempel et al. 2010; Barber 2013). Yet in other plant species, AMF suppress herbivore-induction of secondary metabolites, but enhance constitutive defenses (Bennett et al. 2009; Meier and Hunter 2018a; Wang et al. 2015). Similarly, the few studies that have assessed AMF effects on plant volatile emissions demonstrate that AMF have strong, but variable, effects on constitutive and herbivore-induced foliar volatile profiles. For instance, AMF increase (Asensio et al. 2012; Schausberger et al. 2012; Shrivastava et al. 2015), decrease (Babikova et al. 2014a, b; Fontana et al. 2009; Leitner et al. 2010), or do not affect foliar terpene emissions (Rapparini et al. 2008), depending on the specific AMF and plant species involved. Similarly, AMF have species-specific effects on green leaf volatile (GLV) emissions (Babikova et al. 2014a; Fontana et al. 2009). These volatile classes are known to influence herbivore and natural enemy attraction (Arimura et al. 2009; Bruce et al. 2005; Turlings and Erb 2018), indicating that AMF mediation of VOC profiles may affect multitrophic interactions. Indeed, both aphids (Babikova et al. 2014a, b) and their parasitoids (Guerrieri et al. 2004) are more attracted to plants colonized by AMF. Interestingly, mycorrhizal plants not damaged by aphids are as attractive to parasitoid wasps as are non-mycorrhizal plants infested with aphids (Guerrieri et al. 2004). Similarly, predatory mites (Phytoseiulus persimilis) are more attracted to volatiles produced by mycorrhizal plants infested with spider mites (Tetranychus urticae) than to those of infested plants without AMF (Schausberger et al. 2012).

Most studies to date assessing how AMF influence plant VOC emissions have been limited to crop plant species. Only few have considered how AMF affect plant VOC emissions and foliar secondary metabolites simultaneously (but see Fontana et al. 2009). The investment of resources into defensive traits can be costly and potentially result in resource allocation constraints among defenses (Koricheva et al. 2004). Indeed, some plant species that exhibit low levels of chemical defenses to herbivores have higher VOC emissions (Ballhorn et al. 2008), although this is not always the case (Rasmann et al. 2011; Wason and Hunter 2014). AMF, by altering plant nutrient uptake and interacting with plant defensive signaling pathways (Smith and Read 2008), may alter relationships between VOC emissions and foliar metabolite production.

Furthermore, the availability of AMF inoculum in soil may influence VOC emissions. The extent of AMF inoculum available to plants varies among habitats (Koide and Mooney 1987; Soudzilovskaia et al. 2015) and with land management practices (Lekberg and Koide 2005). AMF availability varies on the meter (Carvalho et al. 2003) to centimeter scale (Wolfe et al. 2007). Plant constitutive ( Tao et al. 2016; Vannette and Hunter 2011; Vannette et al. 2013) and herbivore-induced foliar metabolites (Meier and Hunter 2018a) are affected substantially by the availability of AMF, with consequences for insect herbivores (Meier and Hunter 2018b; Vannette and Hunter 2013). Therefore, it seems likely that the extent of AMF inoculum available to plants may also influence plant constitutive and induced VOC profiles.

Here, we evaluate how AMF influence constitutive and aphid-induced VOC emissions and chemical defenses in two closely related milkweed species (Asclepias incarnata and A. curassavica). These species vary substantially in their foliar chemical defenses (cardenolides) and exhibit AMF-mediated variation in their cardenolide concentrations (Tao et al. 2016; Vannette et al. 2013). Cardenolides are toxic, bitter-tasting steroids that disrupt the functioning of sodium-potassium channels in animal cells (Agrawal et al. 2012). They negatively affect specialist milkweed herbivores, despite herbivore adaptations to resist these defenses (Agrawal 2004; Sternberg et al. 2012). Feeding by oleander aphids (Aphis nerii) suppresses cardenolide concentrations in milkweeds (de Roode et al. 2011; Zehnder and Hunter 2007), likely through interactions with phytohormonal signaling pathways (Ali and Agrawal 2014). In addition, the extent of aphid suppression of cardenolides varies with AMF availability (Meier and Hunter 2018a), suggesting that AMF and aphids may also interact to influence milkweed VOC emissions.

Milkweed species vary in their sesquiterpene emissions, which correlate with top-down pressure by predators on herbivores in the field (Mooney et al. 2010). Furthermore, common milkweed plants (A. syriaca) emit herbivore-induced plant volatiles (HIPVs) in response to caterpillar damage that attract natural enemies, indicating that milkweed species have effective indirect defenses (Wason and Hunter 2014). In the field, A. nerii aphids are killed by a suite of generalist predators and parasitoids, including lacewings (Neuroptera), syrphids (Diptera), coccinellids (Coleoptera), spiders (Araneae), aphid midge flies (Diptera), and parasitoid wasps (Hymenoptera) ( Helms et al. 2004; Malcolm 1992; Mohl et al. 2016; Mooney et al. 2010). Given that these predators and parasitoids respond to HIPVs in other systems (Dicke and Baldwin 2010; Turlings and Erb 2018), it is likely that any AMF and aphid-mediated changes in VOC emissions in milkweeds could affect predator attraction in the field.

To assess the influence of AMF availability, aphid herbivory, and their interaction on plant volatile emissions and tissue metabolites between plant species, we performed a full-factorial experiment, manipulating oleander aphids (Aphis nerii) on two milkweed species (Asclepias incarnata and A. curassavica) provided with different amounts of AMF inoculum. We focused on two compound groups, VOCs and cardenolides (tissue metabolites). Aphids generally suppress VOC emissions (Danner et al. 2018; Rowen and Kaplan 2016; Schwartzberg et al. 2011; Staudt et al. 2010). Aphids are considered ‘stealthy feeders’, as they induce plant responses by inserting stylets between plant cells, avoiding cell damage (Walling 2008). In addition, aphids can manipulate the induction of plant responses to their benefit through salivary effectors (Züst and Agrawal 2016). Indeed, previous studies have demonstrated that A. nerii suppress cardenolide concentrations in milkweed species (de Roode et al. 2011; Meier and Hunter 2018a; Zehnder and Hunter 2007). Therefore, we expected aphid feeding to suppress milkweed VOC emissions and cardenolide concentrations to varying extents between milkweed species. Because AMF alter plant nutrient uptake and interact with plant defensive signaling pathways (Smith and Read 2008), we expected AMF to alter constitutive and aphid-induced VOC emissions and cardenolide concentrations in a plant species-specific manner, with the strength of these effects varying with AMF availability. We did not have specific predictions for the direction of these effects because the outcomes of many AMF-plant associations are specific to the AMF and plant species involved (e.g. Anacker et al. 2014; Barber et al. 2013; Grman 2012; Tao et al. 2016). Lastly, we expected that AMF and aphid herbivory would influence the relative investment by plants in VOCs and cardenolides in a plant species-specific manner.

Methods and Materials

Experimental Protocols

To evaluate the effects of AMF availability and aphid feeding on the VOCs and cardenolides of two milkweed species, we performed a full factorial experiment. We subjected plants of two milkweed species (Asclepias incarnata and A. curassavica) under three levels of AMF availability (zero, medium, and high) to damage by aphids (Aphis nerii) or no herbivores. We measured plant headspace volatiles and foliar cardenolides (defensive metabolites) (2 plant species x 2 aphid treatments x 3 levels of AMF availability x 12 replicates = 144 samples). In addition, we measured environmental variables (temperature, vapor pressure deficit, photosynthetically active radiation (PAR)) to account for variation in volatile emissions resulting from differing environmental conditions among sampling days. We also counted aphids present on plants during sampling and measured plant aboveground biomass to account for aphid abundance and plant size on VOC emissions. We describe our methods in detail below.

Asclepias incarnata seeds were collected from naturally occurring populations in Emmet County, MI. Asclepias curassavica seeds were purchased from Victory Seeds (Molalla, OR, www.victoryseeds.com). We used AMF inoculum from Mycorrhizal Applications (Grants Pass, OR, USA), which is advertised to contain four AMF species including Rhizophagus intraradices, Funneliformis mosseae, Glomus aggregatum, and Claroideoglomus etunicatum (33 spores of each AMF species per gram inoculum, www.plant-success.com). However, we later found this mix to contain only Funneliformis mosseae (Meier and Hunter 2018b). Milkweed species grow in habitats that host a diversity of AMF taxa (Öpik et al. 2006), and can form associations with these cosmopolitan AMF species in natural and experimental populations (Meier and Hunter 2018b; Tao et al. 2016; Vannette et al. 2013), although the frequency of such interactions is unknown. Oleander aphids were derived from a single aphid collected in October 2016 from Ann Arbor, MI and reared indoors on A. tuberosa for one month prior to the experiment.

After 6 weeks of cold and moist stratification at 4 °C (A. incarnata only; A. curassavica did not require stratification), we surface-sterilized seeds in 5% bleach and germinated them at room temperature. We planted seedlings in a mix of autoclaved soil (Metromix 360, Sun Gro Horticulture Canada CM Ltd., Vancouver, BC, Canada) and sand (5:3) with AMF inoculum in conical deepots (D40H, Stuewe and Sons Inc., Corvallis, OR, USA). We manipulated the amount of AMF inoculum available to plants to generate zero, medium, and high levels of AMF colonization. Previous experiments showed that the amount of inoculum available to milkweed plants alters the proportion of roots colonized by AMF (Vannette and Hunter 2011, 2013; Tao et al. 2016). We homogenized 4.20 g live AMF inoculum (high treatment), 1.20 g live and 3.00 g autoclaved inoculum (medium treatment), or 4.20 g autoclaved inoculum (zero treatment) in 200 ml autoclaved soil and sand. This was placed between 400 ml of autoclaved soil and sand to prevent the transfer of AMF spores and hyphae among experimental plants. We returned the natural bacterial community of the potting soil to each pot by adding 20 ml of a bacterial solution made by filtering a suspension of 100 ml potting soil in 1L deionized water through an ultra-fine sieve (32 micron) to remove AMF hyphae and spores. Plants were fertilized weekly with 30 ml of 15-0-15 (N-P-K, 567 ppm) dark weather fertilizer (JR Peters Inc., Allentown, PA) and watered ad libitum. All experiments were conducted in a greenhouse under a 15:9 day:night regime. Because VOC measurements were spread out over several weeks (below), we planted one cohort of plants in May 2017 and second cohort three weeks later in June 2017, to reduce any effects of variation in plant age on variation in VOC emissions.

VOC Collections

In a fully factorial design, we placed 20 reproductive oleander aphids or no herbivores on 12 plants of each plant species x AMF treatment (N=144). Dead or missing reproductive aphids were replaced for the first three days. We allowed herbivores to feed and reproduce for seven days to attain population sizes representative of those observed in the field (Helms et al. 2004). Seven days of feeding is sufficient for oleander aphids to induce cardenolides in these two milkweed species (Meier and Hunter 2018a) and in other systems is sufficient for aphids to induce plant volatiles (Kunert et al. 2002; Schaub et al. 2010). All plants were enclosed in white nylon mesh bags to prevent aphid movement among experimental plants. Nets were secured around plant stems over a strip of cotton wool to prevent damage to stems.

Seven days after the aphids were added, we collected plant volatiles once from each individual plant using a pull-system. Aphids were allowed to remain on plants during VOC collections, as this represents the most ecologically relevant combination of VOCs for natural enemies. Our sampling system allowed us to collect VOCs from seven chambers each day (6 experimental plants, 1 empty control chamber). Because we were only able to collect VOCs from 6 experimental plants per day, we could only measure VOCs from experimental plants of one plant species, with all AMF x aphid treatment combinations represented, per day. We therefore measured volatiles from each plant species every two days, with the species order randomized, to avoid confounding plant species with sampling date. In order to collect volatiles from all 144 plants, we collected VOCs from July 11 through August 3, always establishing aphids on their experimental plants 7 days before measurement. Plants varied between 6 and 9 weeks of age when sampled for volatiles; plant ages were equally represented among all treatments. Moreover, on each sampling day, only plants from the same planting date were used, and sampling date was included as a random effect in all statistical analyses (below). All plants lacked reproductive structures when sampled.

Plants were enclosed in 9 L glass chambers placed atop Teflon guillotine stands (Sigma Scientific LLC, Micanopy, FL, USA), which separated plant roots and potting soil from the volatile collections. Strips of cotton wool were wrapped around the base of the plant stem where it entered the guillotine plate to prevent aphids from leaving the chamber. Aluminum foil was wrapped around the root collar at the top of each pot to further prevent root and soil volatiles from entering the chamber. After placing plants in the chambers, we first withdrew air from the enclosures for 1 h through Teflon tubing with chemical traps bypassed to purge any volatiles released due to handling of the plants. Flowmeters and a vacuum pump (CADS-8Pull System, Sigma Scientific LLC, Micanopy, FL, USA) maintained the flow rate for each enclosure at 1.3 L min-1 for both the purge and sample collections. After the purge, we placed volatile collection traps containing 25 mg of Porapak Q (Sigma Scientific LLC, Micanopy, FL, USA) inline at the top of the chambers secured in Teflon corks. To control for ambient volatiles, we also collected VOCs from an empty chamber on each sampling day. We collected volatiles for 8 h from approximately 11:00 to 19:00 each day. Immediately after sampling, we removed the volatile collection traps, wrapped them in aluminum foil, and kept them on ice until returning them to the lab within an hour. To prevent overheating in the greenhouse, we partially shaded the entire setup using shade cloth. Chambers and guillotine plates were rinsed with hexane after removing plants each evening, and again before enclosing new experimental plants the following morning, to ensure that there were no residual volatiles from the previous sampling day.

To account for effects of environmental variables on VOC emissions (Kesselmeier and Staudt 1999; Loreto and Schnitzler 2010), we measured temperature and relative humidity using HOBO data loggers (Onset Computer Corporation, Bourne, MA, USA) and photosynthetically active radiation using PAR sensors (SQ-420, Apogee Instruments, North Logan, UT, USA) every minute over the 8 hours of sampling. Three sensors measuring temperature and relative humidity and two sensors measuring PAR were placed among the chambers. Relative humidity was temperature-transformed to vapor pressure deficit for the following analyses. We summed the data from each sensor from each minute over the 8 h sampling period to yield a cumulative value for each of the variables per sampling day. We used cumulative values to account for temporal variation in environmental variables over the 8 hours of sampling. We combined the cumulative measures of temperature, vapor pressure deficit, and PAR, as well as minimum and maximum temperature, using principal components analysis (PCA) with the package FactoMineR (Lê et al. 2008) in R v 3.5.0 (R Core Team 2018) to account for covariance among environmental variables. PCA axes were kept if the eigenvalue of the axis was greater than one and the axis explained at least 10% of the total variance in the PCA. Ultimately, environmental data were combined into two PCA axes which explained 71.6 and 14.1% of the daily variation in temperature, vapor pressure deficit, and PAR. These PCA axes were used as covariates in all analyses of VOCs to account for variation in VOC emissions with environmental variables.

After collecting VOCs, we counted aphids present on each plant, rinsed aphids and honeydew off plants with reverse osmosis water, and thoroughly cleaned roots in reverse osmosis water. One leaf of the third leaf pair was taken from each plant, dried at 50 °C, weighed, and then stored in methanol at -10 °C until cardenolide analysis. Above- and belowground tissues were dried in paper bags at 50 °C and weighed to measure above- and belowground biomass (see Supplementary Material for details). A random subsample of approximately 20 mg of dry fine root was taken from each plant, rehydrated for 48 h, and stained to quantify AMF colonization. Specifically, roots were cleared with 10% KOH for 10 min, acidified using 2% HCl, and stained in 0.05% trypan blue in 1:1:1 water:glycerol:lactic acid (Vannette and Hunter 2011). We mounted roots on slides and scored AMF colonization in at least 100 root intersections per plant using the magnified gridline intersect method (McGonigle et al. 1990) with a Nikon compound microscope (Melville, NY, USA). An intersection was considered colonized if AMF hyphae, arbuscules, spores, or vesicles were present. Inoculation of plants with AMF led to successful root colonization, such that plants inoculated without live AMF had no colonization (0 ± 0%), and inoculation with medium and high amounts of AMF resulted in an average of 3.9 (± 1.4%) and 11.4 (± 1.7%) root colonization, respectively (AMF F2,110=23.5, P<0.001). Plants exposed to high AMF availability had 5.2 (± 1.0%) arbuscules, plants exposed to medium AMF availability had 1.6 (± 0.9%) arbuscules, and plants without AMF had no arbuscules (F2,110=12.42, P<0.001). The proportion of roots colonized by AMF did not vary between plants species and was unaffected by aphid feeding (Table 1).

Table 1 F-values, degrees of freedom, and P-values of linear mixed model analyses of the effects of plant species, the availability of arbuscular mycorrhizal fungi (AMF) inoculum, aphid feeding, and their interactions on plant traits, including the proportion of roots colonized by any AMF structures and by arbuscules only, natural log-transformed foliar cardenolide concentration (mg/g), cardenolide diversity, and cardenolide polarity. N= 12 per treatment group

Analysis and Identification of VOCs

We eluted volatile collection traps with 250 μl n-hexane (MS SupraSolv, Sigma-Aldrich, US) and purged traps with N2 to ensure that all hexane was eluted. We added 0.161 ng nonyl acetate to 50 μl of each sample as an internal standard, while keeping all samples on dry ice to prevent evaporation. Samples were stored at -70 °C until analysis. We analyzed 2-μl aliquots of VOC samples by gas chromatography mass spectrometry (GCMS, Agilent Technologies, Santa Clara, CA, USA) using the following GC method: injector held at 250 °C, initial column temperature at 50 °C held for 10 min, ramped at 5 °C min−1 to 200 °C, held for 10 min, with helium carrier gas at a flowrate of 1.3 ml min-1. We used an Agilent J&W HP-5ms Ultra Inert 30 m x 0.25 mm inner-diameter column with 0.25 μm film thickness (Agilent Technologies, Santa Clara, CA, USA).

We tentatively identified compounds using the NIST 2005 library database. In addition, we injected a continuous series of n-alkanes (C8-C24; Sigma-Aldrich) to calculate linear retention indices (RIs) for each compound on the same column used in the above analyses. We compared calculated RIs of peaks from representative samples and standards to published values available on Pherobase (pherobase.com). When possible, we also verified the identity of peaks using authentic standards. Ultimately, we verified the identity of 31 out of 49 plant peaks, with 18 remaining unverified. When possible, we estimated the chemical classes of unverified peaks tentatively according to the number of carbons in the compounds, the compound class proposed by the NIST database, and by the MS and peak retention times. Our estimates took into account the top three identifications proposed by the MS. We could not identify 13 compounds nor assign them to a chemical class because the MS did not provide a consistent molecular formula for those peaks.

We quantified the concentrations of each compound by comparing its peak area with that of the internal standard, nonyl acetate. Synthetic chemicals and any VOCs consistently collected in empty, control chambers were omitted from the dataset. To account for ambient concentrations of any additional plant volatiles, we subtracted the concentrations of compounds present in the control chamber from the concentrations measured in chambers containing experimental plants on the same sampling day. Concentrations of volatiles were standardized for the number of hours for which they were collected from each chamber, and for aboveground plant biomass.

Cardenolide Analyses

To compare how AMF and aphids affect the defensive metabolites of milkweed tissues, we quantified foliar cardenolide concentrations following established methods (Zehnder and Hunter 2007; Meier and Hunter 2018b). In brief, cardenolides were extracted from foliar samples in methanol. Samples were then separated by ultra performance liquid chromatography (UPLC; Waters Inc., Milford, MA, USA) using a Luna 2.5 μm C18(2) column (Phenomenex Inc., Torrance, CA, USA) with digitoxin as an internal standard. Cardenolide peaks with symmetrical absorbance between 218 and 222 nm were quantified. Total cardenolide concentrations were calculated as the sum of individual peaks. In addition, we calculated cardenolide diversity using Shannon’s index and a cardenolide polarity index (the relative representation of lipophilic cardenolides) by summing the relative peak areas multiplied by each peaks’ retention time (Rasmann and Agrawal 2011; Sternberg et al. 2012). We calculated these indices because there is evidence suggesting that more diverse and lipophilic cardenolides are more toxic than are less diverse or more polar mixes (Fordyce and Malcolm 2000; Sternberg et al. 2012).

Statistical Analyses

We performed all following analyses in R v 3.5.0 (R Core Team 2018). To compare the effects of AMF inoculum availability and aphid feeding on VOC emissions, we used linear mixed models using the ‘lmer’ function in the ‘lme4’ package (Bates et al. 2015). Significance of treatments was assessed using the ‘anova’ function in the ‘lmerTest’ package (Kuznetsova et al. 2017). Measures of individual VOCs were the dependent variables and milkweed species, AMF inoculum availability, aphid treatment, and their interactions were fixed effects. Because each plant species emitted distinct blends of VOCs, we analyzed total VOC emissions separately for each species, with AMF inoculum availability, aphid treatment, and their interaction as fixed effects. To account for variation in environmental factors during VOC sampling, we included the two PCA axes of environmental variables (see above) as covariates in all analyses. In addition, we included the identity of the chamber in which the VOCs were collected and sampling date as random effects. The residuals of all analyses were checked for normality and homogeneity of variance. Total VOC emissions were log-transformed, and individual compounds were cube root-transformed to meet assumptions of normality and homogeneity of variance. If samples from one plant species never contained a particular VOC, all samples from that plant species were excluded from analyses of that VOC. We used Tukey’s adjustment for multiple comparisons to identify significant differences among treatments using the ‘lsmeans’ function in the ‘lsmeans’ package. Sample sizes were reduced substantially in these analyses comparing herbivore and AMF treatments within plant species. Therefore, we considered differences to be significant at P < 0.1 for the Tukey’s adjustments within plant species to avoid Type II error. Even large effect sizes are less likely to be distinguished as statistically significant when sample sizes are low (Sokal and Rohlf 2012).

We also evaluated differences in volatile community composition among plant species, AMF treatments, aphid feeding, and their interactions using permutational multivariate ANOVA (PERMANOVA; McCune et al. 2002). To do so, we used the ‘adonis’ function in the ‘vegan’ package (Oksanen et al. 2015) and calculated dissimilarities among samples using the Bray-Curtis metric for PERMANOVA. To visualize VOC composition, we used non-metric multidimensional scaling (NMDS) through the ‘vegan’ package.

To assess whether the final number of aphids on each plant during VOC sampling varied among plant species and AMF treatments, we fit a generalized linear mixed model with a Poisson distribution and log link function using the ‘glmer’ function in the ‘lme4’ package. Aphid number was the dependent variable, and plant species, AMF treatment, and their interaction were fixed effects. Sampling date was a random effect. Significance of treatments was assessed by Wald Chi Square analysis of deviance using the ‘Anova’ function in the ‘car’ package (Fox and Weisberg 2014). In addition, to evaluate whether aphid density affected VOC emissions, we fit linear mixed models with volatiles that were affected by the aphid feeding treatment (Table S1) as the dependent variables. Aphid density and PCA axes of environmental variables were covariates, and plant species, AMF treatment, and their interaction were fixed effects. Sampling date and chamber identity were designated as random effects. The residuals of analyses were checked for normality and homogeneity of variance.

We used linear mixed models to evaluate how AMF and aphids influenced foliar cardenolide concentration, diversity, and polarity, and the proportion of roots colonized by AMF. Plant traits were dependent variables while plant species, AMF inoculum availability, aphid treatment, and their interactions were fixed effects. Sampling date was a random effect. The residuals of all analyses were checked for normality and homogeneity of variance. Cardenolide concentrations were natural log-transformed to meet assumptions of normality and homogeneity of variance. In addition, we evaluated differences in cardenolide composition among plant species, AMF treatments, aphid feeding, and their interactions using PERMANOVA.

Finally, to evaluate how the amount of AMF available to plants may have influenced their relative allocation to cardenolides and VOCs, we built linear mixed models. We started with the simplest models, with total VOC emissions or the individual NMDS axes that characterize VOC blends as the dependent variable, and cardenolide concentration or cardenolide polarity as the independent variable. We also included the two PCA axes of environmental variables as covariates, and chamber identity and sampling date as random effects. To evaluate whether relationships between cardenolide and VOC production were affected by AMF and herbivory, we first evaluated relationships between cardenolide and VOC production. We then added AMF and herbivory, and all interactions among main effects, to models as additional independent variables. Total VOC emissions were log-transformed and cardenolide concentrations were natural log-transformed to meet assumptions of normality and homogeneity of variance. Because A. incarnata and A. curassavica exhibit very different cardenolide and VOC profiles (below), we analyzed relationships between cardenolides and VOCs separately for each species. Furthermore, because A. incarnata produced so few individual cardenolides (1-2 compounds), we did not evaluate relationships between cardenolide polarity and VOC emissions for A. incarnata plants.

Data Availability

Data available from the Dryad Digital Repository: https://doi.org/10.5061/dryad.6hm5760.

Results

We found that the blend of volatiles emitted by milkweed plants was affected substantially by AMF availability and aphid feeding, as well as their interaction. The concentrations of defensive foliar metabolites (cardenolides) were affected only by aphid feeding. We describe the effects of milkweed species, AMF inoculum availability, and aphid feeding on all plant traits and VOCs in Tables 1, 2, S1, and S2. We describe significant results in more detail below.

Table 2 F-values, degrees of freedom, and P-values of linear mixed model analyses of the effects of the availability of arbuscular mycorrhizal fungi (AMF) inoculum, aphid feeding, and their interaction on total VOC emissions in A. incarnata and A. curassavica. Two PCA axes of environmental variables are included as covariates to account for variation in environmental factors during VOC sampling (see text for details). N=12 per treatment group

VOC Emissions

Asclepias incarnata and A. curassavica differed strongly in their VOC profiles (PERMANOVA Plant species: F1,132=25.78, P<0.001). Asclepias incarnata plants emitted up to 48 different VOCs, whereas A. curassavica plants emitted up to 17 (Tables S1, S2). Much of this difference results from variation in sesquiterpenoid emissions between plant species; Asclepias incarnata plants emitted up to 15 different sesquiterpenoids, whereas A. curassavica plants produced only 2 sesquiterpenoids (Tables S1, S2).

The amount of AMF available to plants altered total VOC emissions differently between plant species. Inoculation with high amounts of AMF increased total VOC emissions in A. curassavica from 4.57 ng (nonyl acetate equivalents) gDW-1 h-1 (± 0.93) and 4.27 ng gDW-1 h-1 (± 0.67) under zero and medium AMF availability, respectively, to 7.13 ng gDW-1 h-1 (± 1.40) under high AMF availability (AMF: F2,52.3=3.20, P=0.049). In contrast, AMF availability did not affect total VOC emissions of A. incarnata (AMF: F2, 51.6=1.29, P=0.285). AMF also did not affect the composition of VOCs emitted by either plant species, as estimated by PERMANOVA (AMF: F2,132=0.50, P=0.859, Plant species x AMF: F2,132=1.38, P=0.202). This was despite the fact that concentrations of individual compounds were affected (Tables S1, S2, and below).

AMF had strong, plant species-specific effects on emissions of GLVs and methyl salicylate. Specifically, A. curassavica plants emitted the greatest concentrations of two GLVs (3-hexenyl acetate and hexyl acetate) under high AMF availability, but emissions of these GLVs were unaffected by AMF availability in A. incarnata (Plant species x AMF 3-hexenyl acetate: F2,108.9=3.6, P=0.031; hexyl acetate: F2,108.6=3.29, P=0.041; Figs. 1a, b). Similarly, methyl salicylate emissions increased substantially in A. curassavica plants under high AMF availability, in comparison to zero or medium AMF plants, but emissions were unaffected by AMF availability in A. incarnata (Plant species x AMF: F2,107.5=3.31, P=0.04, Fig. 1c). Emissions of unknown compound 9 followed the same pattern as GLV and methyl salicylate emissions in A. curassavica, such that high AMF availability tended to increase emissions compared to plants without AMF or under medium AMF availability. However, inoculation of A. incarnata plants with high amounts of AMF actually reduced emissions of unknown compound 9 relative to plants without AMF (Plant species x AMF: F2,107.7=4.56, P=0.013, Fig. 1d).

Fig. 1
figure1

Emissions (ng nonyl acetate equivalents gDW-1 h-1 ± 1 SE) of a) 3-hexenyl acetate, b) hexyl acetate, c) methyl salicylate, and d) unknown compound 9 by two species of milkweed (A. incarnata and A. curassavica) subjected to different levels of AMF inoculum availability (Plant species x AMF 3-hexenyl acetate: F2,108.9=3.6, P=0.031, hexyl acetate: F2,108.6=3.29, P=0.041; methyl salicylate: F2,107.5=3.31, P=0.04; compound 9: F2,107.7=4.56, P=0.013). N= 24 per treatment combination. Bars display the mean. Different letters indicate significantly (P < 0.1) different AMF treatment means within each plant species, using Tukey adjustments for comparisons

Aphid feeding did not affect total VOC emissions (Table 2) or the overall VOC composition of either plant species (PERMANOVA Aphids: F1,132=0.63, P=0.613, Plant species x Aphids: F1,132=0.42, P=0.823). However, aphids increased emissions of 6-methyl-5-hepten-2-one and benezenacetaldehyde consistently in both A. incarnata and A. curassavica, regardless of AMF treatment (Aphids 6-methyl-5-hepten-2-one: F1,110=6.15, P=0.015; benzeneacetaldehyde F1,107.2=116.24, P<0.001; Figs. 2a, b). The number of aphids present on plants during VOC collections varied slightly among AMF treatments and between plant species, with the greatest number of aphids on A. curassavica plants under high AMF availability, and the greatest on A. incarnata plants under medium AMF availability (Plant species x AMF: χ2=91.48, df=2, P<0.001, Table S3). While emissions of benzeneacetaldehyde increased with aphid abundance (Aphid abundance: F1,57.9=4.85, P=0.032), aphid abundance did not influence the emissions of any other compound affected by our herbivore treatment (Table S4).

Fig. 2
figure2

Emissions (ng nonyl acetate equivalents gDW-1 h-1 ± 1 SE) of a) 6-methyl-5-hepten-2-one and b) benzeneacetaldehyde by two milkweed species (A. incarnata and A. curassavica) subjected to either no damage or aphid feeding (Aphids 6-methyl-5-hepten-2-one: F1,110=6.15, P=0.015; benzeneacetaldehyde: F1,107=116.24, P<0.001). N=36 per treatment combination. Bars display the mean. * indicate significant differences (P < 0.1) between control and aphid-damaged plants within plant species, using Tukey adjustments for all pairwise comparison.

Aphid feeding and AMF availability also did not interact to affect total VOC emissions (Table 2) or the composition of VOCs in either plant species (PERMANOVA AMF x Aphids: F2,132=0.77, P=0.61, Plant species x AMF x Aphids: F2,132=0.55, P=0.833). However, the effects of aphid feeding on emissions of individual terpenes varied with AMF availability, highlighting the role that AMF play in mediating VOC production in response to herbivore damage. For example, in the absence of AMF, aphids suppressed emissions of the monoterpene cis-ocimene in A. incarnata and A. curassavica (Fig. 3). Inoculation with medium or high amounts of AMF also suppressed emissions in A. incarnata and A. curassavica in the absence of aphids. However, aphids could not suppress cis-ocimene emissions to the same degree under medium and high AMF availability that they could under zero AMF availability (AMF x Aphids: F2,110=3.14, 0.047, Fig. 3). Similarly, aphids suppressed the emissions of four sesquiterpenes produced by A. incarnata (copaene, beta-cubebene, unknown sesquiterpene 2, and delta-cadinene), in those plants without AMF or under medium AMF availability (Fig. 4, Tables S1, S2). In the absence of aphids, high AMF availability suppressed emissions of these compounds compared to plants without AMF or under medium AMF availability (Fig. 4). Similar to the pattern for cis-ocimene, aphid suppression of these four sesquiterpenes was compromised under high AMF, such that aphids even increased emissions under high AMF availability (AMF x Aphids copaene: F2,55=5.88, P=0.005; beta-cubebene: F2,52.5=3.46, P=0.039; unknown sesquiterpene 2: F2,51.5=8.72, P<0.001; delta-cadinene: F2,55=5.47, P=0.007; Fig. 4, Table S2). Emissions of caryophyllene and unknown compound 10 were affected in the same manner by aphids and AMF, although effects were only marginally significant for caryophyllene (compound 10: F2,51.3=4.84, P=0.012; Tables S1, S2).

Fig. 3
figure3

Emissions (ng nonyl acetate equivalents gDW-1 h-1 ± 1 SE) of cis-ocimene by two species of milkweed (A. incarnata and A. curassavica) subjected to different levels of AMF inoculum availability and feeding by aphids (AMF x Aphids: F2,110=3.14, P=0.047). N=12 plants per treatment combination. Bars display the mean. * indicate significant differences (P < 0.1) between control and aphid-damaged plants within AMF treatments per plant species, using Tukey adjustments for all pairwise comparisons

Fig. 4
figure4

Emissions (ng nonyl acetate equivalents gDW-1 h-1 ± 1 SE) of a) copaene, b) beta-cubebene, c) unknown sesquiterpene 2, and d) delta-cadinene by A. incarnata subjected to different levels of AMF inoculum availability and aphid herbivory (AMF x Aphids copaene: F2,55=5.88, P=0.005; beta-cubebene F2,52.5=3.46, P=0.039; unknown sesquiterpene 2: F2,51.5=8.72, P<0.001; delta-cadinene: F2,55=5.47, P=0.007). N=12 per treatment combination. Bars display the mean. * indicate significant differences (P < 0.1) between control and aphid-damaged plants within AMF treatments, using Tukey adjustments for all pairwise comparisons

Cardenolides

As expected (Rasmann and Agrawal 2011; Vannette et al. 2013), foliar cardenolide concentrations differed greatly between milkweed species, with A. curassavica producing higher concentrations of cardenolides than A. incarnata (Plant species: F1,22=616.08, P<0.001, Fig. 5). In addition, A. curassavica produced more diverse and lipophilic cardenolides, as well as an overall different composition of cardenolides than did A. incarnata (Plant species Diversity: F1,21.2=2514.66, P<0.001; Polarity: F1,21.8=6.49, P=0.019; PERMANOVA F1,120=133.18, P<0.001). In contrast to the strong effects of AMF on VOC emissions (above), AMF did not affect foliar cardenolide concentrations (Table 1). Also as expected (de Roode et al. 2011; Zehnder and Hunter 2007), aphid feeding suppressed foliar cardenolide concentrations in A. curassavica, but did not affect cardenolide concentrations in A. incarnata (Plant species x Aphids: F1,110=6.95, P=0.01, Fig. 5). In addition, neither AMF, aphids, nor their interaction affected the diversity, polarity, or composition of cardenolides expressed in either plant species (Table 1, PERMANOVA AMF: F2,120=1.11, P=0.329, Plant species x AMF: F2,120= 1.16, P=0.315; Aphids: F1,120=1.17, P=0.276; Plant species x Aphids: F1,120=0.48, P=0.713; AMF x Aphids: F2,120=0.31, P=0.961; Plant species x AMF x Aphids: F2,120=0.379, P= 0.902).

Fig. 5
figure5

Foliar cardenolide concentrations (mg cardenolides gDW-1 ± 1 SE) of two species of milkweed (A. incarnata and A. curassavica) subjected to either no damage or aphid feeding (Plant species x Aphids: F1,110=6.95, P=0.01). N=36 per treatment combination. Bars display the mean. * indicate significant differences (P < 0.1) between control and aphid-damaged plants within plant species, using Tukey adjustments for all pairwise comparisons

Trade-offs between VOCs and cardenolides

We found evidence for links between the VOC and cardenolide concentrations expressed by both milkweed species. For A. incarnata, plants that produced high concentrations of cardenolides emitted low concentrations of VOCs, suggesting a potential allocation tradeoff between cardenolide and VOC production (Cardenolide concentration: F1,16.6=10.78, P=0.005; Fig. 6a). VOC emissions of A. incarnata also varied with AMF availability (AMF: F2,52.1=3.9, P=0.026), but AMF did not affect the negative relationship between cardenolides and VOCs (AMF x Cardenolide concentration: F2,54.1=2.35, P=0.105; Fig. 6a). In contrast, there was no evidence of an allocation tradeoff between total VOC emissions and cardenolide concentrations in A. curassavica plants (Cardenolide concentration: F1,64.9=0.03, P=0.869). However, the VOC blend emitted by A. curassavica plants (NMDS axis 1) varied with foliar cardenolide concentration (Cardenolide concentration: F1,63.6=4.34, P=0.041, Fig. 6b, Table 3). Moreover, A. curassavica plants that produced a high proportion of lipophilic (more toxic) cardenolides also emitted different blends of VOCs (Polarity: F1,67.9=4.46, P=0.038, Fig. 6c, Table 3). Furthermore, the relationship between lipophilic cardenolides and a second NMDS axis characterizing VOC blends was apparent only in the presence of AMF (Polarity x AMF: F2,54=3.37, P=0.042; Fig. 6d, Table 3), suggesting that the availability of AMF in soil may influence how milkweeds allocate resources between lipophilic cardenolides and their VOC blends.

Fig. 6
figure6

Relationships between VOC emissions and foliar cardenolides in two species of milkweed. Effects of foliar cardenolide concentrations on a) total VOC concentrations emitted by A. incarnata plants among AMF treatments (Cardenolide concentration: F1,16.6=10.78, P=0.005; AMF: F2,52.1=3.9, P=0.026) and b) NMDS axis 1 of the VOC blend emitted by A. curassavica plants (Cardenolide concentration: F1,63.6=4.34, P=0.041). Effects of increasing production of lipophilic cardenolides on c) NMDS axis 1 (Polarity: F1,67.9=4.46, P=0.038) and d) NMDS axis 2 that together characterize the VOC blends emitted by A. curassavica plants. In (d), the relationship varies among AMF treatments (Polarity x AMF: F2,54=3.37, P=0.042). The shaded areas represent 95% confidence intervals around the curves

Table 3 Axis loadings (Pearson correlation coefficients) relating individual VOCs to NMDS axes 1 and 2 that characterize the VOC blends emitted by A. curassavica

Discussion

Here, we report that AMF have plant species-specific effects on the constitutive and aphid-induced VOC emissions of milkweeds. Specifically, we found that 1) high AMF availability increases emissions of total VOCs, two GLVs (3-hexenyl acetate, hexyl acetate), and methyl salicylate in A. curassavica, but does not affect these emissions in A. incarnata plants. While unknown compound 9 tends to follow the same pattern in response to AMF availability in A. curassavica, emissions are actually decreased under high AMF availability in A. incarnata. 2) Aphids consistently increase emissions of 6-methyl-5-hepten-2-one and benzeneacetaldehyde in both A. incarnata and A. curassavica, but AMF availability does not affect these emissions. 3) Aphids suppress emissions of individual terpenes (cis-ocimene, copaene, beta-cubebene, unknown sesquiterpene 2, delta-cadinene) in the absence of AMF. However, high AMF availability suppresses terpene emissions to levels equivalent to those mediated by aphids, such that aphid damage on plants under high AMF availability does not suppress terpene emissions. 4) Aphid feeding suppresses cardenolide concentrations only in A. curassavica. AMF do not affect cardenolides in either plant species, despite having strong effects on VOC emissions. 5) Asclepias incarnata plants that invest more in cardenolides invest less in total VOC emissions. 6) In A. curassavica, the blends of VOCs emitted vary with the concentration and polarity of foliar cardenolides, with the latter effect mediated by AMF availability. Our findings suggest that by altering milkweed VOC profiles, AMF may generate subsequent effects on herbivore and natural enemy attraction, and that AMF affect the indirect defenses of these milkweed species differently.

Our finding of plant species-specific effects of AMF on milkweed VOC emissions is consistent with previous studies. For example, AMF increase VOC emissions in one Medicago truncatula cultivar, yet suppress VOCs in another (Leitner et al. 2010). Similarly, AMF can increase (Fontana et al. 2009) or decrease (Babikova et al. 2014a) GLV emissions, depending on the plant species. These plant species-specific effects of AMF on VOC production may result from the varying ability of plant species to control carbon allocation to AMF (Grman 2012). In addition, VOC emissions are mediated by interactions among phytohormones (Arimura et al. 2009; Turlings and Erb 2018) that AMF also affect (Bucher et al. 2014; Cameron et al. 2013; Gutjahr 2014; Jung et al. 2012). As milkweed species vary in their hormonal responses in leaves to herbivore damage (Agrawal et al. 2014; Ali and Agrawal 2014), it is possible that milkweed species may also vary in their responses to AMF inoculation, leading to the observed differences in VOC emissions.

In addition to their differing responses to AMF availability, A. incarnata and A. curassavica appear to have very different defense syndromes. Asclepias incarnata plants invested heavily in VOCs but minimally in tissue metabolites (cardenolides), whereas A. curassavica plants appeared to do the opposite (Fig. 5, Table S2). Furthermore, these plant species varied in their relative allocation to cardenolides and VOC emissions on an individual-plant level. Asclepias incarnata plants exhibited a potential allocation tradeoff between total cardenolide concentrations and VOC emissions (Fig. 6a), but the blend of VOCs produced by A. incarnata plants did not vary with foliar cardenolide concentrations. In contrast, while A. curassavica plants exhibited no such putative tradeoff between VOC and cardenolide concentrations, the blend of VOCs produced by A. curassavica plants varied with both the concentration of cardenolides produced and with the relative expression of lipophilic cardenolides (Figs. 6b, c, d). Similarly, A. syriaca plants exhibit no tradeoff between VOC and cardenolide concentrations either in leaves (Wason and Hunter 2014) or roots (Rasmann et al. 2011), but A. syriaca foliar cardenolides are related to VOC blends (Wason and Hunter 2014). In addition, while AMF did not alter the putative tradeoff between VOCs and cardenolides in A. incarnata, the relationship between lipophilic cardenolides and VOC blends in A. curasssavica plants varied with the availability of AMF. Overall, these findings suggest that milkweed species vary in their allocation to VOCs and cardenolides, and that AMF may have species-specific effects on this allocation. However, future work is needed that considers this relative allocation in a breadth of milkweed species.

We show, for the first time, that it is not only the presence of AMF, but the amount AMF inoculum available to plants, that affects VOC emissions. Overall, when compared with zero AMF treatments, medium AMF availability had much weaker effects on VOC emissions than did high AMF availability in both milkweed species. Levels of AMF colonization of plant roots were quite low under medium AMF availability, so there may have been limited nutrient transfer and interactions with phytohormones under medium AMF availability. In the field, milkweed plants generally have colonization levels ranging from 10 to 80% (Vannette 2011), and low inoculum availability can limit the establishment of milkweeds (R. L. Vannette, N. L. Haan, and M. D. Hunter, unpublished data). In this study, plants under medium AMF availability only had, on average, 4% root colonization. Under high AMF availability (11% root colonization, on average) there was likely greater nutrient exchange between plants and AMF, and potentially more substantial interactions with phytohormones (Vannette and Hunter 2011), leading to the stronger effects on VOC emissions. Future work should consider how a broader range of AMF inoculum available to plants affects VOC emissions, as well as herbivore and natural enemy attraction, to evaluate whether there is an optimal level of AMF that promotes plant indirect defenses.

By strongly increasing emissions of total VOCs, GLVs, and methyl salicylate in A. curassavica, but not affecting them in A. incarnata, AMF may alter herbivore and carnivore attraction to these plant species differently. Particular ratios of constitutive GLVs alter the ability of herbivores to locate their hosts (Bruce et al. 2005; Natale et al. 2003; Visser and Avé 1978), and plants that emit GLVs sustain higher levels of herbivory than do transgenic plants deficient in GLVs (Halitschke et al. 2008). Similarly, high concentrations of methyl salicylate deter some aphid species from colonizing their host plants (Babikova et al. 2014a; Hardie et al. 1994; Pettersson et al. 1987), although others are attracted (Pope et al. 2007). Therefore, AMF-mediated increases and decreases in constitutive GLV and methyl salicylate emissions likely influence herbivore attraction. In addition, aphid predators and parasitoids are attracted to increased GLV emissions ( Du et al. 1998; Wei et al. 2007; Whitman and Eller 1990), and transgenic plants deficient in GLVs experience reduced predator pressure (Halitschke et al. 2008). Similarly, methyl salicylate attracts a breadth of aphid predators, including syrphids, lacewings, coccinellids, parasitoid wasps, and spiders (James 2005; Mallinger et al. 2011; Pareja et al. 2009; Rodriguez-Saona et al. 2011; Zhu and Park 2005), indicating that AMF may affect natural enemy attraction in a plant species-specific manner.

In contrast to the plant species-specific effects of AMF on GLV and methyl salicylate emissions, AMF consistently decreased cis-ocimene emissions in both milkweed species. They also decreased specific sesquiterpenes that were produced only in A. incarnata. Our findings of AMF-mediated suppression of specific terpenes confirms similar effects of AMF on terpenoid emissions in Plantago lanceolata (Fontana et al. 2009), Vicia faba (Babikova et al. 2014a, b), and Medicago truncatula (Leitner et al. 2010). Interestingly, AMF-mediated declines in emissions of terpenoid compounds mirror aphid-induced declines in the same compounds in the absence of AMF (Figs. 4, 5). Particular blends of sesquiterpenes act as cues for natural enemies, as herbivores often induce specific terpenoid blends (Bruce and Pickett 2011; Turlings and Erb 2018). Because plants under high AMF availability exhibited the same profile of terpenoids in the absence of aphids as zero AMF plants with aphids, AMF may improve natural enemy attraction. Indeed mycorrhizal tomato plants without aphids are equally attractive to parasitoids as non-mycorrhizal plants attacked by aphids (Guerrieri et al. 2004), leading to the suggestion that AMF may lead plants to emit profiles indicating herbivore attack in the absence of herbivores (Rasmann et al. 2017).

Likewise, the effects of aphids on VOC emissions were typically consistent between milkweed species. Our findings that aphids cause only limited induction of HIPVs, and actually suppress emissions of particular VOCs, is consistent with plant responses to aphids in other systems ( Danner et al. 2018; Rowen and Kaplan 2016; Schwartzberg et al. 2011; Staudt et al. 2010). This lack of induction of VOCs may be mediated by aphids inducing limited plant responses by maneuvering stylets between plant cells and avoiding cell damage, thereby eliciting SA rather than JA-mediated defenses (Walling 2008; Züst and Agrawal 2016). Indeed, Aphis nerii feeding has been found to increase SA levels and suppress the induction of JA in milkweed species (Ali and Agrawal 2014). Furthermore, aphid suppression of HIPVs could be mediated by aphid salivary effector proteins, which can manipulate plant signaling to benefit aphids (Züst and Agrawal 2016). Although aphids induced only minor differences in VOC profiles, the differences may be ecologically relevant. 6-methyl-5-hepten-2-one emissions, which aphids increased strongly (Fig. 2), are a known attractant of aphid parasitoids (Du et al. 1998). In addition, 6-methyl-5-hepten-2-one deters aphids, as it indicates low quality plants with high aphid densities (Quiroz et al. 1997). Benzeneacetaldehyde, which aphid feeding increased substantially, attracts aphid midge flies (Watanabe et al. 2016), important predators of A. nerii in the field (Mohl et al. 2016). Furthermore, although AMF did not alter aphid induction of 6-methyl-5-hepten-2-one or benzeneacetaldehyde, by altering GLV, methyl salicylate, and terpene emissions, AMF altered the overall blends of HIPVs produced (Table S2). While individual compounds are important in herbivore and natural enemy attraction, it is more often the particular blend of compounds that matters (Bruce et al. 2005; Bruce and Pickett 2011). For instance, AMF suppress spider mite-induced emissions of methyl salicylate in Phaseolus vulgaris, but increase emissions of beta-ocimene and beta-caryophyllene, ultimately leading to increased predatory mite attraction (Schausberger et al. 2012). Future work must consider how AMF mediation of constitutive and aphid-induced volatiles influences herbivore and natural enemy attraction in the field to understand the implications of AMF mediation of milkweed VOC profiles.

Surprisingly, AMF had no effect on the foliar cardenolide concentrations of either milkweed species, despite having strong effects on plant volatile emissions. Our findings confirm those of Fontana et al. (2009), who similarly found that AMF altered constitutive and induced VOC emissions of Plantago lanceolata, but did not affect leaf concentrations of iridoid glycosides. However, our findings contrast with previous studies that have found strong effects of AMF availability on A. curassavica cardenolide concentrations ( Meier and Hunter 2018ab; Vannette et al. 2013; Tao et al. 2016). We believe that this variation is due to differences in plant age among studies. The plants in this experiment were much younger than those in previous studies. We found that AMF do not affect cardenolide concentrations of 6-week old milkweed plants but do affect cardenolides of 3-month old plants (A. R. Meier, unpublished data). Future work should consider how AMF influence allocation to VOCs and foliar secondary metabolites over ontogeny.

In conclusion, we found that AMF affect plant constitutive and aphid-induced VOC emissions in a plant-species specific manner. Our findings suggest that AMF availability may have substantial effects on multitrophic interactions in the field by altering milkweed indirect defenses. However, additional experiments are needed to evaluate whether AMF-mediated blends of constitutive and aphid-induced volatiles alter herbivore and natural enemy attraction in the field.

References

  1. Agrawal AA (2004) Plant defense and density dependence in the population growth of herbivores. Am Nat 164:113–120. https://doi.org/10.1086/420980

    Article  PubMed  Google Scholar 

  2. Agrawal AA, Petschenka G, Bingham RA et al (2012) Toxic cardenolides: chemical ecology and coevolution of specialized plant-herbivore interactions. New Phytol 194:28–45. https://doi.org/10.1111/j.1469-8137.2011.04049.x

    Article  CAS  PubMed  Google Scholar 

  3. Agrawal AA, Hastings AP, Patrick ET, Knight AC (2014) Specificity of herbivore-induced hormonal signaling and defensive traits in five closely related milkweeds (Asclepias spp.). J Chem Ecol 40:717–729. https://doi.org/10.1007/s10886-014-0449-6

    Article  CAS  PubMed  Google Scholar 

  4. Ali JG, Agrawal AA (2014) Asymmetry of plant-mediated interactions between specialist aphids and caterpillars on two milkweeds. Funct Ecol 28:1404–1412. https://doi.org/10.1111/1365-2435.12271

    Article  Google Scholar 

  5. Anacker BL, Klironomos JN, Maherali H et al (2014) Phylogenetic conservatism in plant-soil feedback and its implications for plant abundance. Ecol Lett 17:1613–1621. https://doi.org/10.1111/ele.12378

    Article  PubMed  Google Scholar 

  6. Arimura GI, Matsui K, Takabayashi J (2009) Chemical and molecular ecology of herbivore-induced plant volatiles: proximate factors and their ultimate functions. Plant Cell Physiol 50:911–923. https://doi.org/10.1093/pcp/pcp030

    Article  CAS  PubMed  Google Scholar 

  7. Asensio D, Rapparini F, Peñuelas J (2012) AM fungi root colonization increases the production of essential isoprenoids vs. nonessential isoprenoids especially under drought stress conditions or after jasmonic acid application. Phytochemistry 77:149–161. https://doi.org/10.1016/j.phytochem.2011.12.012

    Article  CAS  PubMed  Google Scholar 

  8. Babikova Z, Gilbert L, Bruce T et al (2014a) Arbuscular mycorrhizal fungi and aphids interact by changing host plant quality and volatile emission. Funct Ecol 28:375–385. https://doi.org/10.1111/1365-2435.12181

    Article  Google Scholar 

  9. Babikova Z, Gilbert L, Randall KC et al (2014b) Increasing phosphorus supply is not the mechanism by which arbuscular mycorrhiza increase attractiveness of bean (Vicia faba) to aphids. J Exp Bot 65:5231–5241. https://doi.org/10.1093/jxb/eru283

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Ballhorn DJ, Kautz S, Lion U, Heil M (2008) Trade-offs between direct and indirect defences of lima bean (Phaseolus lunatus). J Ecol 96:971–980. https://doi.org/10.1111/j.1365-2745.2008.01404.x

    Article  CAS  Google Scholar 

  11. Barber NA (2013) Arbuscular mycorrhizal fungi are necessary for the induced response to herbivores by Cucumis sativus. J Plant Ecol 6:171–176. https://doi.org/10.1093/jpe/rts026

    Article  Google Scholar 

  12. Barber NA, Kiers ET, Hazzard RV, Adler LS (2013) Context-dependency of arbuscular mycorrhizal fungi on plant-insect interactions in an agroecosystem. Front Plant Sci 4:338. https://doi.org/10.3389/fpls.2013.00338

    Article  PubMed  PubMed Central  Google Scholar 

  13. Bates D, Mächler M, Bolker B, Walker S (2015) Fitting linear mixed-effects models using lme4. J Stat Softw 67:1–48. https://doi.org/10.18637/jss.v067.i01

  14. Bennett AE, Bever JD, Bowers MD (2009) Arbuscular mycorrhizal fungal species suppress inducible plant responses and alter defensive strategies following herbivory. Oecologia 160:771–779. https://doi.org/10.1007/s00442-009-1338-5

    Article  PubMed  Google Scholar 

  15. Bruce TJA, Pickett JA (2011) Perception of plant volatile blends by herbivorous insects - finding the right mix. Phytochemistry 72:1605–1611. https://doi.org/10.1016/j.phytochem.2011.04.011

    Article  CAS  PubMed  Google Scholar 

  16. Bruce TJA, Wadhams LJ, Woodcock CM (2005) Insect host location: a volatile situation. Trends Plant Sci. 10:269–274. https://doi.org/10.1016/j.tplants.2005.04.003

  17. Bucher M, Hause B, Krajinski F, Küster H (2014) Through the doors of perception to function in arbuscular mycorrhizal symbioses. New Phytol 204:833–840. https://doi.org/10.1111/nph.12862

    Article  CAS  PubMed  Google Scholar 

  18. Cameron DD, Neal AL, van Wees SCM, Ton J (2013) Mycorrhiza-induced resistance: more than the sum of its parts? Trends Plant Sci 18:539–545. https://doi.org/10.1016/j.tplants.2013.06.004

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Carvalho LM, Correia PM, Ryel RJ, Martins-Loução MA (2003) Spatial variability of arbuscular mycorrhizal fungal spores in two natural plant communities. Plant Soil 251:227–236. https://doi.org/10.1023/A:1023016317269

    Article  CAS  Google Scholar 

  20. de Roode JC, Rarick RM, Mongue AJ et al (2011) Aphids indirectly increase virulence and transmission potential of a monarch butterfly parasite by reducing defensive chemistry of a shared food plant. Ecol Lett 14:453–461. https://doi.org/10.1111/j.1461-0248.2011.01604.x

  21. Danner H, Desurmont GA, Cristescu SM, van Dam NM (2018) Herbivore-induced plant volatiles accurately predict history of coexistence, diet breadth, and feeding mode of herbivores. New Phytol 220:726–738. https://doi.org/10.1111/nph.14428

    Article  CAS  PubMed  Google Scholar 

  22. Dicke M, Baldwin IT (2010) The evolutionary context for herbivore-induced plant volatiles: beyond the “cry for help”. Trends Plant Sci 15:167–175. https://doi.org/10.1016/j.tplants.2009.12.002

  23. Du YJ, Poppy GM, Powell W et al (1998) Identification of semiochemicals released during aphid feeding that attract parasitoid Aphidius ervi. J Chem Ecol 24:1355–1368. https://doi.org/10.1023/A:1021278816970

    Article  CAS  Google Scholar 

  24. Fontana A, Reichelt M, Hempel S et al (2009) The effects of arbuscular mycorrhizal fungi on direct and indirect defense metabolites of Plantago lanceolata L. J Chem Ecol 35:833–843. https://doi.org/10.1007/s10886-009-9654-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Fordyce JA, Malcolm SB (2000) Specialist weevil, Rhyssomatus lineaticollis, does not spatially avoid cardenolide defenses of common milkweed by ovipositing into pith tissue. J Chem Ecol 26:2857–2874. https://doi.org/10.1023/A:1026450112601

    Article  CAS  Google Scholar 

  26. Fox J, Weisberg S (2014) An R Companion to Applied Regression, Second edition. Sage, Thousand Oaks, CA

    Google Scholar 

  27. Frost CJ, Appel HM, Carlson JE et al (2007) Within-plant signalling via volatiles overcomes vascular constraints on systemic signalling and primes responses against herbivores. Ecol Lett 10:490–498. https://doi.org/10.1111/j.1461-0248.2007.01043.x

    Article  PubMed  Google Scholar 

  28. Garrido E, Bennett AE, Fornoni J, Strauss SY (2010) Variation in arbuscular mycorrhizal fungi colonization modifies the expression of tolerance to above-ground defoliation. J Ecol 98:43–49. https://doi.org/10.1111/j.1365-2745.2009.01586.x

    Article  Google Scholar 

  29. Gouinguené SP, Turlings TCJ (2002) The effects of abiotic factors on induced volatile emissions in corn plants. Plant Physiol 129:1296–1307. https://doi.org/10.1104/pp.001941

  30. Grman E (2012) Plant species differ in their ability to reduce allocation to non-beneficial arbuscular mycorrhizal fungi. Ecology 93:711–718. https://doi.org/10.1890/11-1358.1

    Article  PubMed  Google Scholar 

  31. Guerrieri E, Lingua G, Digilio MC et al (2004) Do interactions between plant roots and the rhizosphere affect parasitoid behaviour? Ecol Entomol 29:753–756. https://doi.org/10.1111/j.0307-6946.2004.00644.x

    Article  Google Scholar 

  32. Gutjahr C (2014) Phytohormone signaling in arbuscular mycorhiza development. Curr Opin Plant Biol 20:26–34. https://doi.org/10.1016/j.pbi.2014.04.003

    Article  CAS  PubMed  Google Scholar 

  33. Halitschke R, Stenberg JA, Kessler D et al (2008) Shared signals - “alarm calls” from plants increase apparency to herbivores and their enemies in nature. Ecol Lett 11:24–34. https://doi.org/10.1111/j.1461-0248.2007.01123.x

    Article  PubMed  Google Scholar 

  34. Hardie J, Isaacs R, Pickett JA et al (1994) Methyl salicylate and (-)-(1R,5S)-myrtenal are plant-derived repellents for black bean aphid, Aphis fabae Scop. (Homoptera: Aphididae). J Chem Ecol 20:2847–2855. https://doi.org/10.1007/BF02098393

    Article  CAS  PubMed  Google Scholar 

  35. Hare JD (2011) Ecological role of volatiles produced by plants in response to damage by herbivorous insects. Annu Rev Entomol 56:161–180. https://doi.org/10.1146/annurev-ento-120709-144753

    Article  CAS  PubMed  Google Scholar 

  36. Hartley SE, Gange AC (2009) Impacts of plant symbiotic fungi on insect herbivores: mutualism in a multitrophic context. Annu Rev Entomol 54:323–342. https://doi.org/10.1146/annurev.ento.54.110807.090614

    Article  CAS  PubMed  Google Scholar 

  37. Heil M, Ton J (2008) Long-distance signalling in plant defence. Trends Plant Sci 13:264–272. https://doi.org/10.1016/j.tplants.2008.03.005

    Article  CAS  PubMed  Google Scholar 

  38. Helms SE, Connelly SJ, Hunter MD (2004) Effects of variation among plant species on the interaction between a herbivore and its parasitoid. Ecol Entomol 29:44–51. https://doi.org/10.1111/j.0307-6946.2004.00566.x

    Article  Google Scholar 

  39. Hoeksema JD, Chaudhary VB, Gehring CA et al (2010) A meta-analysis of context-dependency in plant response to inoculation with mycorrhizal fungi. Ecol Lett 13:394–407. https://doi.org/10.1111/j.1461-0248.2009.01430.x

    Article  PubMed  Google Scholar 

  40. Holopainen JK, Gershenzon J (2010) Multiple stress factors and the emission of plant VOCs. Trends Plant Sci 15:176–184. https://doi.org/10.1016/j.tplants.2010.01.006

    Article  CAS  PubMed  Google Scholar 

  41. James DG (2005) Further field evaluation of synthetic herbivore-induced plan volatiles as attractants for beneficial insects. J Chem Ecol 31:481–495. https://doi.org/10.1007/s10886-005-2020-y

    Article  CAS  PubMed  Google Scholar 

  42. Jung SC, Martinez-Medina A, Lopez-Raez JA, Pozo MJ (2012) Mycorrhiza-induced resistance and priming of plant defenses. J Chem Ecol 38:651–664. https://doi.org/10.1007/s10886-012-0134-6

    Article  CAS  PubMed  Google Scholar 

  43. Lê S, Josse J, Husson F (2008) FactoMineR: an R package for multivariate analysis. J Stat Softw 25:1-18. https://doi.org/10.18637/jss.v025.i01

  44. Karban R, Baldwin IT (1997) Induced responses to herbivory. University of Chicago Press

  45. Karban R, Wetzel WC, Shiojiri K et al (2014a) Deciphering the language of plant communication: volatile chemotypes of sagebrush. J Physiol 204:380–385. https://doi.org/10.1111/nph.12887

    Article  Google Scholar 

  46. Karban R, Yang LH, Edwards KF (2014b) Volatile communication between plants that affects herbivory: a meta-analysis. Ecol Lett 17:44–52. https://doi.org/10.1111/ele.12205

    Article  PubMed  Google Scholar 

  47. Karban R, Wetzel WC, Shiojiri K et al (2016) Geographic dialects in volatile communication between sagebrush individuals. Ecology 97:2917–2924. https://doi.org/10.1002/ecy.1573

    Article  PubMed  Google Scholar 

  48. Kempel A, Schmidt AK, Brandl R, Schädler M (2010) Support from the underground: induced plant resistance depends on arbuscular mycorrhizal fungi. Funct Ecol 24:293–300. https://doi.org/10.1111/j.1365-2435.2009.01647.x

    Article  Google Scholar 

  49. Kesselmeier J, Staudt M (1999) Biogenic volatile organic compounds (VOC): an overview on emission, physiology and ecology. J Atmos Chem 33:23–88. https://doi.org/10.1023/A:1006127516791

    Article  CAS  Google Scholar 

  50. Kessler A, Baldwin IT (2001) Defensive function of herbivore-induced plant volatile emissions in nature. Science 291:2141-2144  https://doi.org/10.1126/science.291.5511.2141

  51. Klironomos JH (2003) Variation in plant response to native and exotic arbuscular mycorrhizal fungi. Ecology 84:2292–2301. https://doi.org/10.2307/3450135

    Article  Google Scholar 

  52. Koide RT, Mooney HA (1987) Spatial variation in inoculum potential of vesicular-arbuscular mycorrhizal fungi caused by rormation of gopher mounds. New Phytol 107:173–182. https://doi.org/10.1111/j.1469-8137.1987.tb04891.x

    Article  Google Scholar 

  53. Koricheva J, Nykänen H, Gianoli E (2004) Meta-analysis of trade-offs among plant antiherbivore defenses: are plants jacks-of-all-trades, masters of all? Am Nat 163:E64–E75. https://doi.org/10.1086/382601

    Article  PubMed  Google Scholar 

  54. Koricheva J, Gange AC, Jones T (2009) Effects of mycorrhizal fungi on insect herbivores: a meta-analysis. Ecology 90:2088–2097. https://doi.org/10.1890/08-1555.1

    Article  PubMed  Google Scholar 

  55. Kunert M, Biedermann A, Koch T, Boland W (2002) Ultrafast sampling and analysis of plant volatiles by a hand-held miniaturised GC with pre-concentration unit: kinetic and quantitative aspects of plant volatile production. J Sep Sci 25:677–684. https://doi.org/10.1002/1615-9314(20020701)25:10/11<677::AID-JSSC677>3.0.CO;2-5

    Article  CAS  Google Scholar 

  56. Kuznetsova A, Brockhoff PB, Christensen RHB (2017) lmerTest package: tests in linear mixed effects models. J Stat Softw 82:1–26. doi: 10.18637/jss.v082.i13

  57. Leitner M, Kaiser R, Hause B et al (2010) Does mycorrhization influence herbivore-induced volatile emission in Medicago truncatula? Mycorrhiza 20:89–101. https://doi.org/10.1007/s00572-009-0264-z

    Article  PubMed  Google Scholar 

  58. Lekberg Y, Koide RT (2005) Is plant performance limited by abundance of arbuscular mycorrhizal fungi? A meta-analysis of studies published between 1988 and 2003. New Phytol 168:189–204. https://doi.org/10.1111/j.1469-8137.2005.01490.x

    Article  CAS  PubMed  Google Scholar 

  59. Loreto F, Schnitzler JP (2010) Abiotic stresses and induced BVOCs. Trends Plant Sci 15:154–166. https://doi.org/10.1016/j.tplants.2009.12.006

    Article  CAS  PubMed  Google Scholar 

  60. Loreto F, Barta C, Brilli F, Nogues I (2006) On the induction of volatile organic compound emissions by plants as consequence of wounding or fluctuations of light and temperature. Plant, Cell Environ 29:1820–1828. https://doi.org/10.1111/j.1365-3040.2006.01561.x

    Article  CAS  Google Scholar 

  61. Malcolm SB (1992) Prey Defence and Predator Foraging. In: Crawley MJ (ed) Natural Enemies: The Population Biology of Predators, Parasites, and Diseases. Blackwell Scientific Publications, Oxford, UK, pp 458–475

  62. Mallinger RE, Hogg DB, Gratton C (2011) Methyl salicylate attracts natural enemies and reduces populations of soybean aphids (Hemiptera: Aphididae) in soybean agroecosystems. J Econ Entomol 104:115–124. https://doi.org/10.1603/EC10253

    Article  PubMed  Google Scholar 

  63. McCune B, Grace JB, Urban DL (2002) Analysis of ecological communities. MjM Software Design. Gleneden Beach, OR

    Google Scholar 

  64. McGonigle TP, Miller MH, Evans DG et al (1990) A new method which gives an objective measure of colonization of roots by vesicular—arbuscular mycorrhizal fungi. New Phytol 115:495–501. https://doi.org/10.1111/j.1469-8137.1990.tb00476.x

    Article  Google Scholar 

  65. Meier AR, Hunter MD (2018a) Arbuscular mycorrhizal fungi mediate herbivore-induction of plant defenses differently above and belowground. Oikos 127:1759–1775. https://doi.org/10.1111/oik.05402

  66. Meier AR, Hunter MD (2018b) Mycorrhizae alter toxin sequestration and performance of two specialist herbivores. Front Ecol Evol 6:33. https://doi.org/10.3389/fevo.2018.00033

    Article  Google Scholar 

  67. Mohl EK, Santa-Martinez E, Heimpel GE (2016) Interspecific differences in milkweeds alter predator density and the strength of trophic cascades. Arthropod Plant Interact 10:249–261. https://doi.org/10.1007/s11829-016-9430-3

    Article  Google Scholar 

  68. Mooney KA, Halitschke R, Kessler A, Agrawal AA (2010) Evolutionary trade-offs in plants mediate the strength of trophic cascades. Science 327:1642–1644. https://doi.org/10.1126/science.1184814

  69. Natale D, Mattiacci L, Hern A et al (2003) Response of female Cydia molesta (Lepidoptera: Tortricidae) to plant derived volatiles. Bull Entomol Res 93:335–342. https://doi.org/10.1079/BER2003250

    Article  CAS  PubMed  Google Scholar 

  70. Oksanen J, Blanchet FG, Kindt R, et al (2015) Vegan: community ecology package, version 2.2-1. R package vegan, vers. 2.2-1

  71. Öpik M, Moora M, Liira J, Zobel M (2006) Composition of root-colonizing arbuscular mycorrhizal fungal communities in different ecosystems around the globe. J Ecol 94:778–790. https://doi.org/10.1111/j.1365-2745.2006.01136.x

    Article  Google Scholar 

  72. Pareja M, Mohib A, Birkett MA et al (2009) Multivariate statistics coupled to generalized linear models reveal complex use of chemical cues by a parasitoid. Anim Behav 77:901–909. https://doi.org/10.1016/j.anbehav.2008.12.016

    Article  Google Scholar 

  73. Pettersson J, Pickett JA, Pye BJ et al (1987) Winter host component reduces colonization by bird-cherry-oat aphid, Rhopalosiphum padi (L.) (homoptera, aphididae), and other aphids in cereal fields. J Chem Ecol 20:2565–2574. https://doi.org/10.1007/BF02036192

    Article  Google Scholar 

  74. Pope TW, Campbell CAM, Hardie J et al (2007) Interactions between host-plant volatiles and the sex pheromones of the bird cherry-oat aphid, Rhopalosiphum padi and the damson-hop aphid, Phorodon humuli. J Chem Ecol 33:157–165. https://doi.org/10.1007/s10886-006-9199-4

    Article  CAS  PubMed  Google Scholar 

  75. Quiroz A, Pettersson J, Pickett JA et al (1997) Semiochemicals mediating spacing behavior of bird cherry-oat aphid, Rhopalosiphum padi feeding on cereals. J Chem Ecol 23:2599–2607. https://doi.org/10.1023/B:JOEC.0000006669.34845.0d

    Article  CAS  Google Scholar 

  76. R Core Team (2018) R: a language and environment for statistical computing.  R Foundation for Statistical Computing, Vienna, Austria. Available online at https://www.R-project.org/.

  77. Rapparini F, Llusià J, Peñuelas J (2008) Effect of arbuscular mycorrhizal (AM) colonization on terpene emission and content of Artemisia annua L. Plant Biol 10:108–122. https://doi.org/10.1055/s-2007-964963

    Article  CAS  PubMed  Google Scholar 

  78. Rasmann S, Agrawal AA (2011) Latitudinal patterns in plant defense: evolution of cardenolides, their toxicity and induction following herbivory. Ecol Lett 14:476–483. https://doi.org/10.1111/j.1461-0248.2011.01609.x

    Article  PubMed  Google Scholar 

  79. Rasmann S, Erwin AC, Halitschke R, Agrawal AA (2011) Direct and indirect root defences of milkweed (Asclepias syriaca): Trophic cascades, trade-offs and novel methods for studying subterranean herbivory. J Ecol 99:16–25. https://doi.org/10.1111/j.1365-2745.2010.01713.x

    Article  CAS  Google Scholar 

  80. Rasmann S, Bennett A, Biere A et al (2017) Root symbionts: powerful drivers of plant above- and belowground indirect defenses. Insect Sci 24:947–960. https://doi.org/10.1111/1744-7917.12464

    Article  CAS  PubMed  Google Scholar 

  81. Rodriguez-Saona C, Kaplan I, Braasch J et al (2011) Field responses of predaceous arthropods to methyl salicylate: a meta-analysis and case study in cranberries. Biol Control 59:294–303. https://doi.org/10.1016/j.biocontrol.2011.06.017

    Article  CAS  Google Scholar 

  82. Rowen E, Kaplan I (2016) Eco-evolutionary factors drive induced plant volatiles: a meta-analysis. New Phytol 210:284–294. https://doi.org/10.1111/nph.13804

    Article  CAS  PubMed  Google Scholar 

  83. Schaub A, Blande JD, Graus M et al (2010) Real-time monitoring of herbivore induced volatile emissions in the field. Physiol Plant 138:123–133. https://doi.org/10.1111/j.1399-3054.2009.01322.x

    Article  CAS  PubMed  Google Scholar 

  84. Schausberger P, Peneder S, Jürschik S, Hoffmann D (2012) Mycorrhiza changes plant volatiles to attract spider mite enemies. Funct Ecol 26:441–449. https://doi.org/10.1111/j.1365-2435.2011.01947.x

    Article  Google Scholar 

  85. Schwartzberg EG, Böröczky K, Tumlinson JH (2011) Pea aphids, Acyrthosiphon pisum, suppress induced plant volatiles in broad bean, Vicia faba. J Chem Ecol 37:1055–1062. https://doi.org/10.1007/s10886-011-0006-5

    Article  CAS  PubMed  Google Scholar 

  86. Schweiger R, Müller C (2015) Leaf metabolome in arbuscular mycorrhizal symbiosis. Curr Opin Plant Biol 26:120–126. https://doi.org/10.1016/j.pbi.2015.06.009

    Article  CAS  PubMed  Google Scholar 

  87. Schweiger R, Baier MC, Persicke M, Müller C (2014) High specificity in plant leaf metabolic responses to arbuscular mycorrhiza. Nat Commun 5:3886. https://doi.org/10.1038/ncomms4886

    Article  CAS  PubMed  Google Scholar 

  88. Shrivastava G, Ownley BH, Augé RM et al (2015) Colonization by arbuscular mycorrhizal and endophytic fungi enhanced terpene production in tomato plants and their defense against a herbivorous insect. Symbiosis 65:65–74. https://doi.org/10.1007/s13199-015-0319-1

    Article  CAS  Google Scholar 

  89. Smith SE, Read D (2008) Mycorrhizal symbiosis, Third edition. Academic Press, London

  90. Sokal RR, Rohlf FJ (2012) Biometry: The principles and practice of statistics in biological research, Fourth edition. W. H. Freeman, New York, NY, USA

  91. Soudzilovskaia NA, Douma JC, Akhmetzhanova AA et al (2015) Global patterns of plant root colonization intensity by mycorrhizal fungi explained by climate and soil chemistry. Glob Ecol Biogeogr 24:371–382. https://doi.org/10.1111/geb.12272

    Article  Google Scholar 

  92. Staudt M, Jackson B, El-Aouni H et al (2010) Volatile organic compound emissions induced by the aphid Myzus persicae differ among resistant and susceptible peach cultivars and a wild relative. Tree Physiol 30:1320–1334. https://doi.org/10.1093/treephys/tpq072

    Article  CAS  PubMed  Google Scholar 

  93. Sternberg ED, Lefèvre T, Li J et al (2012) Food plant derived disease tolerance and resistance in a natural butterfly-plant-parasite interactions. Evolution 66:3367–3376. https://doi.org/10.1111/j.1558-5646.2012.01693.x

  94. Tao L, Ahmad A, de Roode JC, Hunter MD (2016) Arbuscular mycorrhizal fungi affect plant tolerance and chemical defences to herbivory through different mechanisms. J Ecol 104:561–571. https://doi.org/10.1111/1365-2745.12535

    Article  Google Scholar 

  95. Trowbridge AM, Daly RW, Helmig D et al (2014) Herbivory and climate interact serially to control monoterpene emissions from pinyon pine forests. Ecology 95:1591–1603. https://doi.org/10.1890/13-0989.1

    Article  PubMed  Google Scholar 

  96. Turlings TCJ, Erb M (2018) Tritrophic interactions mediated by herbivore-induced plant volatiles: mechanisms, ecological relevance, and application potential. Annu Rev Entomol 63:433–452. https://doi.org/10.1146/annurev-ento-020117-043507

    Article  CAS  PubMed  Google Scholar 

  97. Vannette RL (2011) Whose phenotype is it anyway? The complex role of species interactions and resource availability in determining plant defense phenotype and community consequences. University of Michigan

    Google Scholar 

  98. Vannette RL, Hunter MD (2011) Plant defence theory re-examined: nonlinear expectations based on the costs and benefits of resource mutualisms. J Ecol 99:66–76. https://doi.org/10.1111/j.1365-2745.2010.01755.x

    Article  Google Scholar 

  99. Vannette RL, Hunter MD (2013) Mycorrhizal abundance affects the expression of plant resistance traits and herbivore performance. J Ecol 101:1019–1029. https://doi.org/10.1111/1365-2745.12111

    Article  CAS  Google Scholar 

  100. Vannette RL, Hunter MD, Rasmann S (2013) Arbuscular mycorrhizal fungi alter above- and below-ground chemical defense expression differentially among Asclepias species. Front Plant Sci 4:361. https://doi.org/10.3389/fpls.2013.00361

    Article  PubMed  PubMed Central  Google Scholar 

  101. Visser JH, Avé DA (1978) General green leaf volatiles in the olfactory orientation of the colorado beetle, Leptinotarsa decemlineata. Entomol Exp Appl 24:738–749. https://doi.org/10.1111/j.1570-7458.1978.tb02838.x

    Article  CAS  Google Scholar 

  102. Walling LL (2008) Avoiding effective defenses: strategies employed by phloem-feeding insects. Plant Physiol 146:859–866. https://doi.org/10.1104/pp.107.113142

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Wang B, Qiu YL (2006) Phylogenetic distribution and evolution of mycorrhizas in land plants. Mycorrhiza 16:299–363. https://doi.org/10.1007/s00572-005-0033-6

    Article  CAS  PubMed  Google Scholar 

  104. Wang M, Bezemer TM, van der Putten WH, Biere A (2015) Effects of the timing of herbivory on plant defense induction and insect performance in ribwort plantain (Plantago lanceolata L.) depend on plant mycorrhizal status. J Chem Ecol 41:1006–1017. https://doi.org/10.1007/s10886-015-0644-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Wason EL, Hunter MD (2014) Genetic variation in plant volatile emission does not result in differential attraction of natural enemies in the field. Oecologia 174:479–491. https://doi.org/10.1007/s00442-013-2787-4

    Article  PubMed  Google Scholar 

  106. Watanabe H, Yano E, Higashida K et al (2016) An attractant of the aphidophagous gall midge Aphidoletes aphidimyza from honeydew of Aphis gossypii. J Chem Ecol 42:149–155. https://doi.org/10.1007/s10886-016-0666-2

    Article  CAS  PubMed  Google Scholar 

  107. Wei J, Wang L, Zhu J et al (2007) Plants attract parasitic wasps to defend themselves against insect pests by releasing hexenol. PLoS One 2:e852. https://doi.org/10.1371/journal.pone.0000852

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Whitman DW, Eller FJ (1990) Parasitic wasps orient to green leaf volatiles. Chemoecology 1:69–76. https://doi.org/10.1007/BF01325231

    Article  CAS  Google Scholar 

  109. Wolfe BE, Mummey DL, Rillig MC, Klironomos JN (2007) Small-scale spatial heterogeneity of arbuscular mycorrhizal fungal abundance and community composition in a wetland plant community. Mycorrhiza 17:175–183. https://doi.org/10.1007/s00572-006-0089-y

    Article  PubMed  Google Scholar 

  110. Zehnder CB, Hunter MD (2007) Interspecific variation within the genus Asclepias in response to herbivory by a phloem-feeding insect herbivore. J Chem Ecol 33:2044–2053. https://doi.org/10.1007/s10886-007-9364-4

    Article  CAS  PubMed  Google Scholar 

  111. Zhu J, Park KC (2005) Methyl salicylate, a soybean aphid-induced plant volatile attractive to the predator Coccinella septempunctata. J Chem Ecol 31:1733–1746. https://doi.org/10.1007/s10886-005-5923-8

    Article  CAS  PubMed  Google Scholar 

  112. Züst T, Agrawal AA (2016) Mechanisms and evolution of plant resistance to aphids. Nat Plants 2:1–9. https://doi.org/10.1038/nplants.2015.206

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We would like to thank the Matthaei Botanical Gardens for greenhouse space and help with plant care. We gratefully acknowledge Lucas Michelotti, Hillary Streit, Anne Bonds, Kamren Johnson, Jackie Kristofik, and Kathleen Moriarty for help with the experiment and chemical analyses. We thank Christopher Frost and Ken Keefover-Ring for assistance in designing the volatile collection system. We also thank three reviewers for their constructive comments on an earlier draft of the paper. The work was supported by a Block Grant, Matthaei Botanical Gardens Research Award, and Rackham Graduate Student Research Grant from the University of Michigan to ARM, a National Science Foundation Graduate Research Fellowship to ARM, and a National Science Foundation Division of Environmental Biology 1256115 grant to MDH.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Amanda R. Meier.

Electronic supplementary material

ESM 1

(DOCX 65.1 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Meier, A.R., Hunter, M.D. Mycorrhizae Alter Constitutive and Herbivore-Induced Volatile Emissions by Milkweeds. J Chem Ecol 45, 610–625 (2019). https://doi.org/10.1007/s10886-019-01080-6

Download citation

Keywords

  • Arbuscular mycorrhizal fungi (AMF)
  • Volatile organic compounds (VOCs)
  • Microbe-plant-insect interactions
  • Indirect defense
  • Asclepias
  • Aphis nerii