Elevated ozone and carbon dioxide affects the composition of volatile organic compounds emitted by Vicia faba (L.) and visitation by European orchard bee (Osmia cornuta)

Mark Otieno; Zsolt Karpati; Marcell K. Peters; Laura Duque; Thomas Schmitt; Ingolf Steffan-Dewenter

doi:10.1371/journal.pone.0283480

Abstract

Recent studies link increased ozone (O₃) and carbon dioxide (CO₂) levels to alteration of plant performance and plant-herbivore interactions, but their interactive effects on plant-pollinator interactions are little understood. Extra floral nectaries (EFNs) are essential organs used by some plants for stimulating defense against herbivory and for the attraction of insect pollinators, e.g., bees. The factors driving the interactions between bees and plants regarding the visitation of bees to EFNs are poorly understood, especially in the face of global change driven by greenhouse gases. Here, we experimentally tested whether elevated levels of O₃ and CO₂ individually and interactively alter the emission of Volatile Organic Compound (VOC) profiles in the field bean plant (Vicia faba, L., Fabaceae), EFN nectar production and EFN visitation by the European orchard bee (Osmia cornuta, Latreille, Megachilidae). Our results showed that O₃ alone had significant negative effects on the blends of VOCs emitted while the treatment with elevated CO₂ alone did not differ from the control. Furthermore, as with O₃ alone, the mixture of O₃ and CO₂ also had a significant difference in the VOCs’ profile. O₃ exposure was also linked to reduced nectar volume and had a negative impact on EFN visitation by bees. Increased CO₂ level, on the other hand, had a positive impact on bee visits. Our results add to the knowledge of the interactive effects of O₃ and CO₂ on plant volatiles emitted by Vicia faba and bee responses. As greenhouse gas levels continue to rise globally, it is important to take these findings into consideration to better prepare for changes in plant-insect interactions.

Citation: Otieno M, Karpati Z, Peters MK, Duque L, Schmitt T, Steffan-Dewenter I (2023) Elevated ozone and carbon dioxide affects the composition of volatile organic compounds emitted by Vicia faba (L.) and visitation by European orchard bee (Osmia cornuta). PLoS ONE 18(4): e0283480. https://doi.org/10.1371/journal.pone.0283480

Editor: Federico Brilli, National Research Council of Italy (CNR), ITALY

Received: August 30, 2022; Accepted: March 9, 2023; Published: April 26, 2023

Copyright: © 2023 Otieno et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data generated during this study is deposited in DRYAD (https://doi.org/10.5061/dryad.2jm63xsts).

Funding: This work was supported by the Alexander von Humboldt Foundation [Georg Forster Research Fellowship for Experienced Researchers awarded to MO]. This publication was supported by the Open Access Publication Fund of the University of Wuerzburg. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors declare no competing interests.

Introduction

Global climate change is triggered by increasing carbon dioxide (CO₂) concentrations paralleled by higher ozone (O₃) concentrations, which have direct impacts on plant physiology [1,2] and indirect effects on interactions with associated insects [3]. Currently, such plant-mediated effects on plant-insect interactions have been increasingly clarified but combined effects of O₃ and CO₂ are still unknown, in particular for plant-pollinator interactions [4]. Both O₃ and CO₂ can disrupt plant-insect communication by changing the Volatile Organic Compounds (VOCs) profile emitted by the plants or by altering nectar quality and quantity [5,6]. Tropospheric O₃ can affect VOCs by altering plant allocation and inducing changes in VOCs’ emission or by chemically reacting with the emitted VOCs to alter their chemical structure [7]. Some studies have linked elevated ozone levels to reduced photosynthesis as a result of lower performance of stomatal conductance [8,9] and reduced reproductive capacity of plants, foliar damage, increased abscission rates and senescence [2]. However, many papers also indicate that the effect on photosynthesis is through effects on Rubisco rather than stomatal conductance [e.g. 10–12]. Intuitively, altered physiology will affect the normal functioning of the plant, and this may include changed emissions of VOCs. In this case, O₃ could have indirect effects on VOC emission via modification of the plants’ physiology. Such a modification may, in turn, lead to changes in the concentration or composition of floral scents. When this happens, the visitation could be reduced because the attractiveness of VOCs detected by the pollinators become lower both in quality and in quantity [13]. Studies that simultaneously investigated the effects of O₃ on VOC emission and consequences for flower visits are rare [but see 13].

Increased CO₂ concentration in the air can also directly affect insect-plant interactions via altered VOC emission by changing the total emission rates and VOC composition [5]. Also, compositional changes of the VOCs emitted by the plant can act as a repellent for insects [3]. The changes in VOC composition have been documented to impede plant–plant communication [14,15] and between plants and insects compromising the ability of insects to detect VOC cues [16]. Indirectly, elevated CO₂ can alter VOC emission via modification of photosynthesis and plant growth. Elevated CO₂ has been linked to higher photosynthesis rates, which increases the amount of carbohydrates in the plant available for greater starch reserves and growth [17,18]. Good physiological processes are responsible for increased plant growth and performance, which can include elevated emission of VOCs [see 19].

Among the plant organs involved in plant-animal interactions that are sensitive to changes in growth and physiology are extra floral nectaries (EFNs). EFNs are important plant organs that produce nectar as a primary reward for the organisms which defend them against herbivory. The nectar produced by these glandular organs is rich in carbohydrates, lipids, and amino acids and attracts a wide diversity of arthropods [20,21]. EFNs are located on plant parts other than the flowers, typically on stipules, petioles, or leaf bases [22], but can also occur on flower buds [23]. The occurrence of EFNs is widespread in the plant kingdom, recorded in over 3,900 species of plants belonging to 806 genera and 110 families [22].

Legume is recognized as the most common EFN-producing plant family and it has a well-known diversity of insect mutualisms [24–27]. Despite the large diversity of bees visiting legume EFNs, the interactions between these bee species and EFNs are still poorly understood. Bees visit flowers primarily to collect pollen and nectar to provide the protein and carbohydrates they need for themselves and to feed the developing larvae [28,29]. Learning to visit high rewarding plants [30] by utilizing multiple traits, including nectar and floral scent has been evolved in bees [31,32]. This allows the bees to locate and collect food with maximum efficiency [30]. In most legume species, flowers secrete little amounts of nectar not sufficient to meet pollinators’ energy needs [33]. This inadequacy forces the insects to forage on plant species that produce large amounts of nectar or utilize extra floral nectar from legume plants, if available.

Bees, e.g., Osmia cornuta (Hymenoptera, Megachilidae), are the primary visitors of flowers and EFNs of many legume plants including field bean (Vicia faba L., Fabaceae), a globally important pulse crop often grown as monoculture [34–37]. Vicia faba plants produce extra floral nectar primarily for ant attraction to defend itself against herbivores [38], but bees also frequently utilize these organs to obtain nectar as an extra reward in addition to the pollen and nectar they obtain from the flowers [39]. Numerous studies have investigated the effects of O₃ and CO₂ enrichment both individually and in interaction on plant growth responses in different free-air concentration-enrichment (FACE) experiments [e.g. 18,40–42]. However, none has studied the effects of the two atmospheric gases on VOC emission, EFN nectar volume and sugar concentration.

Although Vicia faba’s growth, development, and reproduction are known to be affected by O₃ and CO₂ [1,43,44], studies addressing the effects of these gases on EFN nectar production (volume and sugar concentration) are non-existent. Furthermore, the interactive effects of these gases on insect-EFN mutualisms in Vicia faba are unknown.

In this study conducted in a greenhouse environment, we tested whether VOCs, nectar volume and sugar concentration from the EFNs of V. faba are affected by increased O₃ and CO₂ levels both independently and in interaction and whether there are consequences for bee visits to these EFNs. Vicia faba was selected as a ubiquitous crop in Europe and a crucial global food security and bioenergy crop with existing knowledge on its reproduction to understand how the likely rise in atmospheric pollution could impact the interactions with its pollinators.

Materials and methods

This study was conducted through a series of experiments from January to April 2020 in a greenhouse located at the Biocenter, the University of Würzburg in Germany. Vicia faba plants were exposed to elevated levels of O₃ and/or CO₂. EFN nectar secretion of the plants and the behavior of the European orchard bee (Osmia cornuta, Latreille, Megachilidae) were assessed later under normal atmospheric conditions.

Crop establishment

The Vicia faba variety Fuego, a regionally important cultivar in Bavaria, Germany, was used in the experiments. The crop was planted in 18 cm x 18 cm pots filled with a peat-based rooting media composed of a 2:1 ratio of peat (Einheits Erde CL ED 73) and sand (Hamann Filters and 0.7–1.25 mm). Greenhouse environmental conditions were controlled at 25°C in 16 hours of light, and at 18°C in 8 hours of dark.

In the greenhouse, there were two pests noticed during the experiment; the fungus gnats (Sciara hemerobioides: Sciaridae) and the western flower thrips (Frankliniella occidentalis: Thripidae). The pests were controlled as described by [45]. We used the nematode, Steinernema feltiae: Steinernematidae from Katz Biotech AG (www.katzbiotech.de) to control the fungus gnats eggs and larvae. The nematode was added to the soil at a rate of 50 million per 100 m² as recommended by the manufacturer. The Adult insects of this pest species were controlled using yellow sticky traps. Predatory mites (Amblyseius cucumeris: Phytoseiidae) from Katz Biotech AG and Biobest^® (www.biobestgroup.com) were used to manage the western flower thrips (Frankliniella occidentalis: Thripidae) on the plant leaves and flowers at the rate of 50/m².

Two cohorts, each with 32 plants, were planted on the 2^nd and 12^th January 2020. The plants were watered every three days, and pests were managed using established biological control measures.

Fumigation experimental set-up

The fumigation set-up was comprised of components assembled as described in details in [45–47]: The setup (Fig 1) had:

Two glass chambers (chamber 1 and 2) made of a stainless-steel door frame each with an approximate volume of 1000 dm³;
An O₃ gas generator (INNOTEC high engineering GmbH) linked to an air dryer (AIRdryer3.2, INNOTEC);
A CO₂ cylinder linked to a regulator calibrated to allow for the amount of CO₂ required in the chamber. The CO₂ regulator was an assembly comprising seven components manufactured by Grow Control Company (www.growcontrol.de). The assembly had (a) manometer cylinder pressure, (b) flow rate indicator, (c) shut-off valve, (d) Solenoid switching valve, (e) flow adjustment knob, (f) cylinder connector and (g) upper pressure valve;
An O₃ analyzer (APOA-370, Horiba Ltd.);
A CO₂ analyzer (GrowControl GrowBase EC Pro) linked to the regulator described in (iii) above;
A controller that links the O₃ analyzer and the O₃ generator that was used to regulate the O₃ concentration in the chamber;
A timer;
A primary stream of compressed air allowed to pass through an activated charcoal filter and a particle filter before it reaches the chambers;
A secondary stream of air branching from the primary one, passing through the air dryer and the O₃ generator and discharges in the main air stream, allowing for O₃ enrichment of the incoming air;
2 rotameters that allowed for leveling the amount of incoming air to each chamber to 70 L/min.

Download:

Fig 1. Representation of the ozone—Carbon dioxide exposure system experimental setup.

https://doi.org/10.1371/journal.pone.0283480.g001

The photoperiod conditions were the same as in the greenhouse itself (16 hours of light, and 8 hours of dark from 5 am to 8 pm) because the two chambers were almost exclusively made of transparent glass. The two chambers allowed us to have, at any given time, an O₃-clean environment and normal CO₂ levels in one chamber (chamber 2) and an O₃ and/or CO₂ enriched environments at different times of the fumigation experiments (chamber 1). The O₃ and CO₂ analyzers were constantly sucking in the air from the chamber used for the treatments with these gases and analyzing it for its O₃ or CO₂ content or both depending on which fumigation experiment was running. This information was then passed on to the controllers that give feedback to the CO₂ and O₃ generators, switching them on or off accordingly in order to achieve the desired average CO₂ or O₃ concentrations, which could be modified in the controller.

Fumigation consisted of exposing the plants in the chambers for five continuous hours/day between 5 am and 8 pm for five consecutive days. Sets of eight plants in the stage of flower initiation were exposed to one of the four following treatments:

Control—Exposure to air purified with charcoal filters in chamber 2. The O₃ and CO₂ concentrations were not permanently monitored in this chamber, but pretesting revealed that the mean concentrations in this chamber were ~0 ppb and ~346 ppm for O₃ and CO₂, respectively.
O₃—exposure to enhanced levels of O₃ (120 ppb).
CO₂—exposure to enhanced levels of CO₂ (900 ppm).
O₃ + CO₂—simultaneous exposure to enhanced levels of O₃ and CO₂ at the above enhanced levels for each gas.

The 120 ppb of O₃ treatment used in our experiments might seem high, however, the exposure period was short (just five days). The relevance of using these amounts is the high O₃ episodes which are not uncommon for example in southern Europe.

See S1-S3 Tables in S1 File for detailed information on the sequence of fumigations and the concentration of the gases in chamber 1.

Greenhouse set up

After fumigation, the 32 plants per cohort (eight control, eight O₃, eight CO₂, eight O₃ + CO₂) were placed in the greenhouse in a completely randomized block design pattern. For the next five days after fumigation treatments, bees were introduced into the greenhouse and allowed to visit the EFNs.

VOC sample collection and TD-GC-MS analysis

The volatile organic compounds (VOCs) emitted from EFNs were collected between 22^nd February and 8^th March 2020 between 09h00 and 16h00 when bees were most active. Quartz glass tubes (15 mm × 1.9 mm internal diameter) filled with tenax (1.5 mg) and carbotrap (1.5 mg) adsorbents were used to collect the VOCs. Both sides were closed with glass wool to keep the adsorption material in place (Jürgens et al 2006). Tubes were conditioned by heating them up for 30 min at 250 °C. EFNs on the upper three nodes (~12 EFNs) per plant were enclosed in polyacetate (oven) bags (Toppits, Minden, Germany) three hours prior to volatile collection. Subsequently, the air, containing the odors, was sucked trough the quartz glass tube for 15 minutes (1.1 l/min) using a battery-powered DC pump (Fürgut, Tannheim, Germany. The quartz glass tube was transferred into a glass-wool-packed thermodesorption tube and placed in the thermodesorper unit (TDU; TD100-xr, Markes, Offenbach am Main, Germany) connected to a GC/MS (Agilent 7890B GC and 5977 MS, Agilent Technologies, Palo Alto, USA). The thermodesorption tube, was heated up to 260 °C for 10 min. The desorbed components were transferred to the cold trap of the TDU (5 °C) to focus the analytes using N₂ as carrier gas. The cold trap was heated up to 310 °C at a rate of 60 °C/sec and held for 5 min. The VOCs were transferred to the injector port of the GC/MS via a heated transfer line (300 °C) and with N₂ as carrier gas. The GC was equipped with an HP-5MS UI capillary column (30 m × 0.25 mm × 0.25 μm, J&W Scientific, Folsom, CA, USA). Helium was used as carrier gas with constant pressure of 1 bar. The initial GC oven temperature was 40 °C for 1 min, then raised to 300 °C at 5 °C min^-1 where it was held for 3 minutes. The transfer line temperature between GC and MS was 300 °C. The mass spectrometer was operated in electron impact (EI; 70 eV) ionization mode, scanning m/z from 40 to 650, at 2.4 scans s^-1.

Volatile organic compounds (VOCs) were identified based on their mass spectra, which were compared with the MS Library (NIST 2.3) using Agilent MSD Productivity ChemStation (MSD ChemStation F.01.03.2357—Agilent Technologies, Inc.) software. Additionally, the identification was verified by the calculated Retention Indices (RI), based on our n-alkanes’ Retention Times (RT), and the values (RI) were compared with both the published values [48] and with the NIST Chemistry WebBook database. All potential contaminants (plastic softeners, column bleeding material etc.) and compounds with similar mass spectra were eliminated from the VOC table. We then compared each compound with similar mass spectra and retention index across all samples per treatment and only retained the compounds present in at least 50% of the samples per treatment (S4 Table in S1 File). We calculated the relative amount for each compound per sample in each treatment by taking the integrated peak area of each compound divided by the total area for all compounds. We used the relative ratio to perform NMDS and Random Forest analysis described in the data analysis section.

Measurement of extra floral nectar volume and sugar concentration

Extra floral nectar was collected using graduated 5 μl micropipettes. Because the nectar volume from one EFN gland was relatively low, five random EFN glands per plant were used to estimate nectar volume. On each randomly selected EFN gland, extra floral nectar was tapped by placing one end of the micropipette to the EFN gland and the other end left open to allow the nectar to be drawn into the micropipette by capillary force. The micropipette was put in place until all the nectar had been drawn before moving to the next gland. Nectar volume was determined from the scale on the side of the micropipette.

Sugar concentration of nectar was measured using a portable optical light refractometer (Bellingham and Stanley–Eclipse 45–81 °Brix). The total nectar sugar concentration is expressed in °Brix, which is the sugar content of an aqueous solution. For the calculation of the quantity of sugar in the nectar, the optical light refractometers measure the percentage of sucrose on the Bx scale (1 °Bx is 1 g of sucrose in 100 g of solution). The total sugar concentration in the nectar is assessed by extracting the nectar from the flower with a micropipette and emptying the liquid onto the light refractometer’s glass prism. The ºBx is read by holding the device against light to determine its refractive index. The refractive index of nectar is used as a measure of sugar equivalent in the solution [49].

In total, we made three measurement rounds of nectar volume and sugar concentration per plant per treatment for each cohort.

Bee visitation to extra floral nectaries

Observation of bee visits to EFN was done in two phases, each with 32 plants due to the greenhouse’s limited space. The first set of 32 plants were placed in the greenhouse for five continuous days from 23^rd to 27^th February 2020 and the second set from 3^rd to 7^th March 2020, each time with 50 individuals of O. cornuta obtained from Mauerbienen company (www.mauerbienen.com). Both sets were exposed to bees immediately after the end of the fumigation period. A group of four plants, one from each treatment, was observed for 15 continuous minutes twice a day (in the morning and afternoon) for five consecutive days. During this period, the number of bees visiting the plant’s extra floral nectaries was recorded.

Data analysis

Statistical analyses were performed in R version 4.2.1 [50]. We used Non-metric Multidimensional Scaling (NMDS) to visualize the degree of chemical distances among VOCs based on their relative amounts in different treatments. To investigate which VOCs were associated with each treatment, we correlated values on the NMDS axes to metrics of VOCs based on Bray-Curtis dissimilarities with the vegan package version 2.6–2 in R. Adonis test, an implementation of PERMANOVA, was used to test for the significance of differences among the groups.

In the next step, we ran a random Forest model in MetaboAnalyst 5.0 (https://www.metaboanalyst.ca/) to determine which decisive compounds are most important for the separation of the groups [51]. First, we compared all VOCs between O₃ and control treatments. Second, we compared these VOCs with O₃ versus O₃ + CO₂. We did not have comparisons between CO₂ with other treatments because this treatment was not significant in the NMDS analysis. We used the mean decrease of accuracy to interpret the VOCs importance in making the differences as suggested by [52]. According to [51], the mean decrease in accuracy (MDA) for a compound or variable is the normalized difference of the classification accuracy for the out-of-bag data when the data for that variable is included as observed, and the classification accuracy for the out-of-bag data when the values of the variable in the out-of-bag data have been randomly permuted.

We further constructed a second NMDS with only the decisive VOCs identified by the random Forest model to examine how they relate with the treatments, without all the other non-decisive chemicals tested in the first NMDS. Again, we used adonis test in PERMANOVA to test for significant differences among the groups.

To test for treatment effect on EFN nectar volume and sugar content, we used Linear Mixed Models (LMM) as implemented in the lme function (R package nlme). Here we used either nectar volume or sugar content as response variables and fitted each LMM with CO₂ and O₃ (and their interaction) as fixed effects, and plant ID as the random effect. We also constructed a LMM with bee visits as the response variable and used CO₂, O₃ (and their interaction), nectar volume, and sugar concentration as fixed factors to test whether these variables modulated the number of visits to EFNs. We retained the plant ID as the random effect. We used Tukey test to separate the means of treatments means where significant differences were found. Before analysis, each response variable was tested for normality using the Shapiro Wilk test [53]. If the test returned a significant result (p<0.05), the data were log-transformed to improve normality and fulfill the parametric tests’ assumptions before further analysis [54].

Results

A bouquet of 101 VOC compounds (S4 Table in S1 File) was found in the headspace of Vicia faba. Out of these, 53 were identifiable. The VOC classes based on the number of compounds were alcohols (9%), Aldehydes (9%), Anisoles (2%), Benzoids (4%), Esters (5%) Ketones (7%), Terpenes (16%), and unknowns (48%)

Effect of O₃ and CO₂ on VOCs

We found that both axes 1 and 2 of the first NMDS values could explain the variations in VOC values (Fig 2). Based on permutation test for adonis, the VOCs significantly differed between treatments (F_3,27 = 2.193, P = 0.001). When further subjected to pairwise adonis comparisons, significant effects were observed due to differences between O₃ versus control (adonis p = 0.006) and O₃ versus O₃ + CO₂ (adonis p = 0.012), respectively.

Download:

Fig 2. NMDS panel figure displaying the relationship between various Volatile Organic Compounds of Vicia faba plants’ headspace for each atmospheric treatment.

https://doi.org/10.1371/journal.pone.0283480.g002

Based on the random Forest model, we listed the top 15 decisive compounds for O₃ versus control (Fig 3a) and O₃ versus O₃ + CO₂ (Fig 3b) from the bouquet of 112 compounds based on their MDA. From the top 15 decisive compounds in each group, we identified four (Fig 3a) and seven compounds (Fig 3b), which had higher MDA value than the steepest point (MDA>0.010), as the most important ones for the separation of treatments. We therefore used the top four compounds in Fig 3a and top seven in Fig 3b for the second NMDS analysis described below.

Download:

Fig 3. Outputs of the decisive VOCs identified by random Forest model relating to (a) control versus O₃ and (b) O₃ versus O₃ + CO₂.

The compounds are ranked in decreasing order based on the model’s predictive accuracy from permuting the values in each feature.

https://doi.org/10.1371/journal.pone.0283480.g003

In the second NMDS which was constructed with only the decisive VOCs identified by the random Forest model to relate these decisive VOCS with the treatments, both axes 1 and 2 of the NMDS values could explain the variations in the decisive VOC values (Fig 4). The decisive VOC composition significantly differed between treatments (F_1,29 = 2.19, P<0.001). When further subjected to pairwise adonis comparisons, significant effects were observed due to differences between O₃ versus control (adonis p = 0.003) and O₃ versus O₃ + CO₂ (adonis p = 0.003), We also confirmed significant effects between control versus O₃ + CO₂ (adonis p = 0.009).

Download:

Fig 4. NMDS panel figure displaying the relationship between decisive Volatile Organic Compounds identified by the random Forest model and each atmospheric treatment.

https://doi.org/10.1371/journal.pone.0283480.g004

Effects of O₃ and CO₂ on EFN nectar and consequences for bee visits

Plants from the control treatment produced the highest nectar volume (3.2 ± 0.8 μl), followed by the plants treated with elevated CO₂ (2.8 ± 0.4 μl), a mixture of O₃ and CO₂ (2.2 ± 0.5 μl) and O₃ (1.7 ± 0.3 μl), respectively (Fig 5a). For the nectar sugar concentration, the plants treated with O₃ had 15.6 ± 2.5 °Bx, followed by CO₂ (12.4 ± 1.7 °Bx), control treatment (11.6 ±1.5 °Bx), and a mixture of O₃ and CO₂ (10.2 ± 1.6 °Bx), respectively (Fig 5b).

Download:

Fig 5. Volume (a) and sugar concentration (b) of nectar produced by five extra floral nectaries of plants in each atmospheric treatment.

The different letters over the bars in the histogram indicate significant differences based LMMs. Same letters indicate no significant difference.

https://doi.org/10.1371/journal.pone.0283480.g005

Based on the LMMs, elevated O₃ had a significant negative effect on nectar volume (t = -2.192, p = 0.032), while CO₂ and the interaction between the two gases had no effect (p = 0.5 and p = 0.321), respectively (S5 Table in S1 File). For nectar sugar concentration, neither O₃, CO₂ nor their interaction had significant effects (p = 0.136, p = 0.768, and p = 0.102, respectively (Fig 5).

A total of 246 bee visits to EFNs were recorded. Most visits were to plants exposed to elevated CO₂ (Mean 7.8 ± 0.9 SE per plant within the ten days of sampling), followed by visits to control plants (4.2 ± 0.8), to a mixture of CO₂ and O₃ (2.1 ± 0.7), and to O₃ (1.4 ± 0.4), respectively (Fig 6). CO₂ enhanced bee visits (t = 3.105, p = 0.03) but O₃ and O₃ + CO₂ had negative effects on bee visits (t = -2.229, p = 0.30 and t = -2.081, p = 0.042, respectively).

Download:

Fig 6. Osmia cornuta visits to EFNs on plants in each atmospheric treatment per plant over the ten-day sampling period.

The different letters over the bars in the histogram indicate significant differences based on Tukey tests. Same letters indicate no significant difference.

https://doi.org/10.1371/journal.pone.0283480.g006

Discussion

Our results show that increased O₃ had significantly negative effects on the blends of VOCs emitted, nectar volume secreted by the EFNs, and bee visits. There is a possibility O₃ affects these secondary-metabolites and bee visits through plant physiology [55]. CO₂ combined with enhanced O₃ levels showed distinct VOC profiles and significantly lower visitation rates compared to plants only exposed to enhanced CO₂ concentrations. Our results underpin that the understanding of plant-mediated responses requires the consideration of interactive effects of different atmospheric compounds.

Effect of O3 and CO2 on VOCs

We found that the VOC blend changed when the plants were treated with elevated O₃. Because the VOCs were trapped after the plants’ exposure to O₃ and or CO₂, the results indicate effects mediated via modified plants physiology. Our study findings are consistent with other studies, notably: [56–59], where collection of VOCs was performed after exposure to O₃ had ceased.

From our findings, it is highly likely that O₃ indirectly affected the emission of VOCs through modified plant physiology. This modification could either be through decreased photosynthesis due to reduced stomatal conductance [8,9] or the effects of O₃ on Rubisco [11], which have a net negative impact on biomass accumulation [8,9]. Our results indicate that O₃-stressed plants with presumably reduced energy reserves, lower primary productivity and further changes in plant metabolism have a lower net emission of VOCs than a plant under normal environmental conditions [60].

Effect of O₃ on EFN nectar production

Elevated O₃ had a significant negative effect on nectar volume, while CO₂ had no effect. Little is known about how O₃ influences changes in nectar secretion in Fabaceae, but it may influence resource allocation to vital plant parts, e.g., leaves, stems, flowers, storage organs, and extra floral nectaries [see 61]. These changes could have knock-on effects on nectar production [62].

When O₃ is sequestered into plant tissue, e.g., the leaf parenchyma, it is partially broken down to derivatives that can affect photosynthesis [61]. This damage affects the demand for carbon needed to support the repair process, as the plant demands more carbohydrates [63]. Carbohydrates, primarily glucose, sucrose, and fructose, are the most abundant nutrients in nectar [64]. The phloem tissue is responsible for synthesizing these essential compounds of nectar [64]. In Vicia faba plants, the nectary tissue can also be photosynthetically active since it contains chloroplasts in the nectary parenchyma [65]. O₃ can influence many factors identified contributing to the phloem constituents, the chloroplasts in the nectary tissue, and the amount of nectar produced by these plant parts [see 66,67]. It is also possible that elevated ozone affected water availability/water allocation reducing the volume of EFN. This is because in response to elevated ozone, plants close their stomata which affect their transpiration rate [8,9]. These effects would have explained our results for nectar volume production under the O₃ treatment.

Nectar sugar concentration was not significantly influenced by O₃, although there was a positive trend for plants exposed to O₃ compared to other treatments. Previous studies have found that the effects of O₃ on monosaccharides and total soluble carbohydrates, including total sugars, depend on the severity of the stress [55], which is a function of dosage and the length of exposure [3]. It is noteworthy that the Nectar sugar concentration is higher in O₃ exposed plants, which have low nectar volume.

Behavioral consequences of increased O₃ and CO₂ on bees utilizing EFNs

Osmia cornuta bee visits to EFNs were significantly higher on plants exposed to elevated CO₂ but significantly lower on plants exposed to O₃ and a mixture of O₃ and CO₂. From our results, bees had a stronger preference for CO₂-treated plants than we would assume from the nectar volume as the mean was higher for control than CO₂ treated plants, while visitation rates was two-fold higher for CO₂ plants. This might indicate that further changes in the VOC profiles/blend are added to the attractiveness of the EFNs in this treatment. We can more generally draw the conclusion from these results that, in addition to the effects mediated by plant nectar volume and sugar concentration, changes in the relative amounts of VOCs in the different treatments may also explain the high or low visitation rates. It is well established that plants attract and maintain their appeal to pollinators primarily via visual cues and VOCs, which enables pollinators to find appropriate flowers to collect nectar and pollen [68]. It may be possible that ozone alters color of flowers and leaves via oxidative stress [69]. However, we did not observe a change in the color of flowers under O₃ stress but injuries on leaves. The VOCs play an essential role in the discernment of the level and composition of resources, enabling insects to forage on the most rewarding plants [70,71]. O₃, however, is reported to affect this plant-pollinator communication by altering the VOC blend making it difficult for pollinators to find appropriate flowers [see 13]. A recent review paper by [55] reports that elevated O₃ alters the composition and diversity of plant communities through its effects on key physiological functions, and changes the emission of VOCs, which affect plant-insect interactions and the composition of insect communities.

It should be noted that nectar volume is a secondary factor affected by O₃ to regulate bee visits. In general, nectar volume functions as an attractive factor in bee visits and O₃ makes nectar volume significantly lower than control. Some of the VOCs such estragole, and beta-linalool that we identified are the most dominant VOCs emitted by the flowers of a variety of plant species, especially those attractive to pollinators [72–74]. These VOCs were amongst the most severely affected VOCs by O₃ in our study. Estragole is an important insect pollinator attractant for plants such as oil palm [74]. Often pollinators react to specific ratios of volatiles in a blend, rather than to specific volatiles. Our results indicate that O₃ altered some ratios of VOC composition that are important for pollinator recognition.

In our study, we found significant negative effects of O₃ on bee visitation, nectar volume, and VOCs, which may have provided a different olfactory cues to the bees compared to the CO₂ treated plants, making it less apparent to find the most resourceful plants [75]. Previous findings have found correlations between the frequency of visits by Osmia bees and the degree of rewarding (e.g., nectar volume) [76]. For instance, female Osmia bees were found to use nectar VOCs to identify the most rewarding Penstemon caesius (Plantaginaceae) flowers before landing on the corolla [76]. Osmia species have innate preferences towards specific blends of VOCs typical of their host plants [77,78]. Therefore, they may easily find their appropriate plants, instead of plants that do not fit their inner reference templates (e.g. O₃-treated plants).

The exposure of plants to CO₂ is likely to have increased the attractiveness of the plants to bee visitors through increased biomass accumulation due to increased photosynthesis. Although we did not measure photosynthetic activity, future investigations should determine if physiological changes in plants due to CO₂ exposure can cause enhanced attractiveness. Previous studies have established that Vicia faba invests in extra assimilate in the initiation and maintenance of flowers at elevated CO₂, increasing overall floral display [see 1]. An increase in floral display or longevity may be due to the changes in resource allocation within the plant. From an energy efficiency perspective, bees generally have more visits to plants with more flowers (and EFNs) and higher floral display because they can utilize less energy to forage on more flowers in a small area [79]. The EFNs on the plants with higher floral display stand a better chance of being visited, which is the likely case in our study.

Conclusion

Our results showed that elevated O₃ levels altered the VOC composition and the amount of EFN nectar reward, threatening the interactions between bee pollinators and Vicia faba plants, as shown to reduce bee visits in this research. While, within the scope of this study, increases in O₃ level were associated with changes in VOCs relevant to bee attraction to the flowers, nectar volume, and bee visitation, CO₂ seemed to partly but not significantly compensate for these effects. Our results add essential information to the general knowledge on the effects of O₃ and CO₂ on the profiles of volatiles emitted by Vicia faba plants and bee responses to these changes. Further work is needed to test the responses of bees to the individual VOCs and different blends if the composition and relative amounts of different VOCs play an important role, to determine the thresholds at which they respond to these compounds to fully understand the behavioural responses of different pollinator species to plants exposed to greenhouse gases.

As greenhouse gas levels continue to rise globally, it is important to take these findings interactive effects with enhanced O₃ levels into serious consideration to better prepare for future scenarios of plant responses and threats for plant-insect interactions.

Supporting information

S1 File.

https://doi.org/10.1371/journal.pone.0283480.s001

(PDF)

Acknowledgments

We are grateful to Thomas Igerst and Nobert Schneider for constructing the O₃ and CO₂ fumigation chambers and maintaining the system throughout the experimental period. We thank Beate Krischke and Susanne Schiele for offering technical and logistical support with providing the needed materials for the experiments.

References

1. Osborne JL, Awmack CS, Clark SJ, Williams IH and Mills VC. Nectar and flower production in Vicia faba L. (field bean) at ambient and elevated carbon dioxide. Apidologie. 1997; 28, 43–55.
- View Article
- Google Scholar
2. Chen Z, Cao J, Yu H, and Shang H. Effects of elevated ozone levels on photosynthesis, biomass and non-structural carbohydrates of Phoebe bournei and Phoebe zhennan in subtropical china. Frontiers of Plant Sciences. 2018. pmid:30555502
- View Article
- PubMed/NCBI
- Google Scholar
3. Masui N, Agathokleous E, Mochizuki T, Tani A, Matsuura H, Koike T. Ozone disrupts the communication between plants and insects in urban and suburban areas: an updated insight on plant volatiles. Journal of Forest Research (Harbin). 2021; 10:1–13. pmid:33456272
- View Article
- PubMed/NCBI
- Google Scholar
4. Jamieson MA, Burkle LA, Manson JS, Runyon JB, Trowbridge AM, Zientek J. Global change effects on plant-insect interactions: The role of phytochemistry. Current Opinion in Insect Sciences. 2017; 23, 70–80. pmid:29129286
- View Article
- PubMed/NCBI
- Google Scholar
5. Peñuelas J and Staudt M. BVOCs and global change. Trends in Plant Science. 2010; 15, 133–144. pmid:20097116
- View Article
- PubMed/NCBI
- Google Scholar
6. Dötterl S, Vater M, Rupp T and Held A. Ozone differentially affects perception of volatiles in western honeybees. Journal of Chemical Ecology. 2016; 42, 486–489.
- View Article
- Google Scholar
7. Holopainen JK, Nerg AM and Blande JD. Multitrophic signaling in polluted atmospheres, in Biology, Controls and Models of Tree Volatile Organic Compound Emissions. Tree Physiology, eds Ü. Niinemets and R. K. Monson (Springer). 2013.
8. Wang LL, He XY, Chen W. Effects of elevated CO2 or/and O3 on growth and daily changes of photosynthesis in leaves of Pinus armandi. Huan Jing Ke Xue. 2010; 31(1): 36–40.
- View Article
- Google Scholar
9. Hasan MM, Rahman MA, Skalicky M, Alabdallah NM, Waseem M, Jahan MS, et al. Ozone Induced Stomatal Regulations, MAPK and Phytohormone Signaling in Plants. International Journal of Molecular Sciences. 2021; 22(12): 6304. pmid:34208343
- View Article
- PubMed/NCBI
- Google Scholar
10. Watanabe M, Hoshika Y, Koike T and Izuta T. Effects of Ozone on Japanese Trees. In: Izuta T. (eds) Air Pollution Impacts on Plants in East Asia. Springer, Tokyo. 2017.
11. Feng Z, Shang B, Gao F and Calatayud V. Current ambient and elevated ozone effects on poplar: A global meta-analysis and response relationships. Science of The Total Environment. 2019; 654: 832–840. pmid:30453256
- View Article
- PubMed/NCBI
- Google Scholar
12. Xu Y, Feng Z, Peng J, Tarvainen L. Elevated ozone decreases the activity of Rubisco in poplar but not its activation under fluctuating light. Tree Physiology. 2022. 42(9): 1762–1775. pmid:35445727
- View Article
- PubMed/NCBI
- Google Scholar
13. Farré-Armengol G, Peñuelas J, Li T, Yli-Pirilä P, Filella I, Llusia J, et al. Ozone degrades floral scent and reduces pollinator attraction to flowers. New Phytologist. 2016; 209(1), 152–160. pmid:26346807
- View Article
- PubMed/NCBI
- Google Scholar
14. Blande JD, Holopainen J K and Li T. Air pollution impedes plant-to-plant communication by volatiles. Ecology Letters. 2010;13, 1172–1181. pmid:20602627
- View Article
- PubMed/NCBI
- Google Scholar
15. Li T. and Blande JD. Associational susceptibility in broccoli: mediated by plant volatiles, impeded by O3. Global Change Biology. 2015; 21, 1993–2004.
- View Article
- Google Scholar
16. Blande JD, Holopainen JK and Niinemets Ü. Plant volatiles in polluted atmospheres: stress responses and signal degradation. Plant, Cell and Environment. 2014; 37, 892–1904. pmid:24738697
- View Article
- PubMed/NCBI
- Google Scholar
17. Wang D, Heckathorn SA, Wang X and Philpott SM. A meta-analysis of plant physiological and growth responses to temperature and elevated CO2. Oecologia. 2012; 169, 1–13. pmid:22037993
- View Article
- PubMed/NCBI
- Google Scholar
18. Ainsworth EA, Leakey ADB, Ort DR and Long SP. FACE-ing the facts: inconsistencies and interdependence among field, chamber and modeling studies of elevated [CO2] impacts on crop yield and food supply. New Phytologist. 2008; 179, 5–9. pmid:18482226
- View Article
- PubMed/NCBI
- Google Scholar
19. Jasoni R, Kane C, Green C, Peffley E, Tissue D, Thompson L, et al. Altered leaf and root emissions from onion (Allium cepa L.) grown under elevated CO2 condition. Environmental and Experimental Botany. 2004; 51(3) 273–280.
- View Article
- Google Scholar
20. Lange D, Dáttilo W, Del-Claro K. Influence of extra floralnectary phenology on ant-plant mutualistic networks in a neotropical savanna. Ecologial Entomology. 2013; 38: 463–469.
- View Article
- Google Scholar
21. Belchior C. Sendoya SF, Del-Claro K. Temporal Variation in the Abundance and Richness of Foliage-Dwelling Ants Mediated by Extra floralNectar. PLoS One. 2016; 11(7): e0158283. pmid:27438722
- View Article
- PubMed/NCBI
- Google Scholar
22. Weber MG, Porturas LD, Keeler KH. World list of plants with extra floral nectaries. http://www.extrafloralnectaries.org. 2015.
23. Mesquita-Neto JN, Paiva EAS, Galetto L and Schlindwein C. Nectar Secretion of Floral Buds of Tococa guianensis Mediates Interactions With Generalist Ants That Reduce Florivory. Frontiers in Plant Science. 2020; 11:627.
- View Article
- Google Scholar
24. McKey D. Interactions between ants and leguminous plants. In’Advances in Legume Biology’. (Eds CH Stirton, JL Zarucchi). Monographs in Systematic Botany from the Missouri. BotanicalGarden. 1989.;29, 673–718. (Missouri Botanical Garden Press: Saint Louis, MO, USA.
25. Heil M. Extrafloral Nectar at the Plant-Insect Interface: A Spotlight on Chemical Ecology, Phenotypic Plasticity, and Food Webs. Annual Review of Entomology. 2015; 60:1, 213–232.
- View Article
- Google Scholar
26. Patt JM and Rohrig E. Laboratory Evaluations of the Foraging Success of Tamarixia radiata (Hymenoptera: Eulophidae) on Flowers and Extrafloral Nectaries: Potential use of Nectar Plants for Conservation Biological Control of Asian Citrus Psyllid (Hemiptera: Liviidae). Florida Entomologist. 2017; 100(1): 149–156.
- View Article
- Google Scholar
27. Beyer N, Gabriel D, Kirsch F, Schulz-Kesting K, Dauber J, Westphal C. Functional groups of wild bees respond differently to faba bean Vicia faba L. cultivation at landscape scale. Journal of Applied Ecology. 2020; 57(12):2499–2508.
- View Article
- Google Scholar
28. Michener C.D. The Bees of the World, 1st Ed., John Hopkins University Press, Baltimore. 2000.
29. Roulston TH, Cane JH and Buchmann SL. What governs the protein content of pollen grains: pollinator preferences, pollen- pistil interactions, or phylogeny. Ecological Monographs. 2000. 70(4); 617–643.
- View Article
- Google Scholar
30. Ceuppens B, Eeraerts M, Vleugels T, Cnops G, Roldan-Ruiz I and Smagghe G. Effects of dietary lambda-cyhalothrin exposure on bumblebee survival, reproduction, and foraging behaviour in laboratory and greenhouse. Journal of Pest Science. 2015; 88, 777–783.
- View Article
- Google Scholar
31. Dudareva N, Pichersky E, Dudareva N, Pichersky E. Floral scent metabolic pathways: Their regulation and evolution. In Biology of Floral Scent, Dudareva N., Pichersky E., eds (Boca Raton, FL: CRC Press), 2006; pp. 55–78.
32. Raguso RA. Floral scent in a whole-plant context: moving beyond pollinator attraction. Functional Ecology. 2009; 23(5), 837–840.
- View Article
- Google Scholar
33. Marazzi B, Gonzalez AM, Delgado-Salinas A, Luckow MA, Ringelberg JJ, Hughes CE. Extra floral nectaries in Leguminosae: phylogenetic distribution, morphological diversity and evolution. Australian Systematic Botany. 2019; 32, 409–458.
- View Article
- Google Scholar
34. Klein AM, Vaissiere BE, Cane JH, Steffan-Dewenter I, Cunningham SA, Kremen C et al. Importance of pollinators in changing landscapes for world crops. Proceedings of the Royal Society of London B: Biological Sciences. 2007; 274 (1608), 303–313. pmid:17164193
- View Article
- PubMed/NCBI
- Google Scholar
35. Klatt BK, Holzschuh A, Westphal C, Clough Y, Smit I, Pawelzik E et al. Bee pollination improves crop quality, shelf life and commercial value. Proceedings of the Royal Society of London B: Biological Sciences. 2014; 281 (1775), 20132440. pmid:24307669
- View Article
- PubMed/NCBI
- Google Scholar
36. Bartomeus I, Potts SG, Steffan-Dewenter I, Vaissiere BE, Woyciechowski M, Krewenka KM, et al. Contribution of insect pollinators to crop yield and quality varies with agricultural intensification. PeerJ. 2014; 2, e328. pmid:24749007
- View Article
- PubMed/NCBI
- Google Scholar
37. Nayak GK, Roberts SPM, Garratt M, Breeze TD, Tscheulin T, Harrison-Cripps J, et al. Interactive effect of floral abundance and semi-natural habitats on pollinators in field beans (Vicia faba). Agriculture, Ecosystems and Environment. 2015; 199, 58–66.
- View Article
- Google Scholar
38. Katayama N, and Suzuki N. Role of extra floral nectaries of Vicia faba in attraction of ants and herbivore exclusion by ants. Entomological Science. 2004; 7(2): 119–124.
- View Article
- Google Scholar
39. Marzinzig B, Brünjes L, Biagioni S, Behling H, Link W, and Westphal C. Bee pollinators of faba bean (Vicia faba L.) differ in their foraging behaviour and pollination efficiency Agriculture Ecosystems and Environment, 2018; 264: 24–33.
- View Article
- Google Scholar
40. Burton, Andrew J., Zak, Donald R., Kubiske, Mark E., and Pregitzer, Kurt S. Impacts of interacting elevated atmospheric co2 and o3 on the structure and functioning of a northern forest ecosystem: operating and decommissioning the aspen face project. United States: N. p., 2014.
41. Gustafson E.J., Kubiske M.E., Miranda B.R. et al. Extrapolating plot-scale CO₂ and ozone enrichment experimental results to novel conditions and scales using mechanistic modeling. Ecol Process. 2018; 7, 31.
- View Article
- Google Scholar
42. Tobita H, Komatsu M, Harayama H, Yazaki K, Kitaoka S and Kitao M. Effects of Combined CO2 and O3 Exposures on Net CO2 Assimilation and Biomass Allocation in Seedlings of the Late-Successional Fagus Crenata. Climate 2019, 7(10), 117.
- View Article
- Google Scholar
43. Almohisen IAA and Alyemeni MN. Effect of Ozone on the Quality of Two Legume Crops (Vicia faba and Pisum sativum) around Riyadh City. Life Science Journal. 2013; 10(4), 2297–2302.
- View Article
- Google Scholar
44. Stabler D. Impacts of ozone pollution on nectar and pollen quality and their significance for pollinators. School of Biology. Newcastle, UK, Newcastle University. PhD thesis. 2016.
45. Otieno M., Peters K. M., Duque L. and Steffan-Dewenter I. Interactive effects of ozone and carbon dioxide on plant-pollinator interactions and yields in a legume crop. Environmental Advances. 2022; 9: 100285.
- View Article
- Google Scholar
46. Duque L, Poelman EH, Steffan-Dewenter I. Plant-mediated effects of ozone on herbivores depend on exposure duration and temperature. Scientific Reports. 2019; 9, 19891. pmid:31882632
- View Article
- PubMed/NCBI
- Google Scholar
47. Duque L, Poelman EH, Steffan-Dewenter I. Effects of ozone stress on flowering phenology, plant-pollinator interactions and plant reproductive success. Environmental Pollution. 2021; 272, 115953. pmid:33190978
- View Article
- PubMed/NCBI
- Google Scholar
48. Adams RP. Identification of essential oil components by gas chromotography/mass spectrometry, 4th edn. Allured publishing, Carol Stream; 2017.
49. Aronne G and Malara P. Fiber-optic refractometer for in vivo sugar concentration measurements of low-nectar-producing flowers. New Phytologist. 2019; 224: 987–993.
- View Article
- Google Scholar
50. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2022.
51. Jansen J, Pokorny T and Schmitt T. Disentangling the effect of insemination and ovary development on the cuticular hydrocarbon profile in the bumblebee Bombus terrestris (Hymenoptera: Apidae). Apidologie. 2016; 47, 101–113.
- View Article
- Google Scholar
52. Cutler DR, Edwards TC Jr, Beard KH, Cutler A, Hess KT, Gibson J, et al. Random forests for classification in ecology. Ecology. 2007; 88 (11), 2783–2792. pmid:18051647
- View Article
- PubMed/NCBI
- Google Scholar
53. Hanusz Z and Tarasińska J. Normalization of the Kolmogorov–Smirnov and Shapiro–Wilk tests of normality. Biometrical Letters. 2015; 52(2)85–93.
- View Article
- Google Scholar
54. Ribeiro-Oliveira JP, de Santana DG, Pereira VJ, dos Santos CM, Data transformation: an underestimated tool by inappropriate use. Acta Scientiarum Agronomy, 2018; 40.
- View Article
- Google Scholar
55. Agathokleous E, Feng Z, Oksanen E, Sicard P, Wang Q, Saitanis CJ, et al. Ozone affects plant, insect, and soil microbial communities: A threat to terrestrial ecosystems and biodiversity. Science Advances. 2020;12;6(33):eabc1176. pmid:32851188
- View Article
- PubMed/NCBI
- Google Scholar
56. Saunier A and Blande JD. The effect of elevated ozone on floral chemistry of brassicaceae species. Environmental Pollution. 2019; 255: 10. pmid:31546077
- View Article
- PubMed/NCBI
- Google Scholar
57. Heiden AC, Hoffmann T, Kahl J, et al. Emission of volatile organic compounds from ozone-exposed plants. Ecological Applications.1999; 9: 1160–1167.
- View Article
- Google Scholar
58. Brosset A, Saunier A, Kivimaenpaa M, et al. Does ozone exposure affect herbivore-induced plant volatile emissions differently in wild and cultivated plants? Environmental Sciences and Pollution Research. 2020; 27: 30448–30459. pmid:32468369
- View Article
- PubMed/NCBI
- Google Scholar
59. Cui HY, Su JW, Wei JN, et al. Elevated o₃ enhances the attraction of whitefly-infested tomato plants to Encarsia formosa. Scientific Reports. 2014; 4: 6.
- View Article
- Google Scholar
60. Yuan X, Calatayud V, Gao F, Fares S, Paoletti E, Tian Y, et al. Interaction of drought and ozone exposure on isoprene emission from extensively cultivated poplar. 2016; 39(10): 2276–2287.
- View Article
- Google Scholar
61. Emberson LD, Pleijel H, Ainsworth EA, van den Berg M, Ren W, Osborn et al. Ozone effects on crops and consideration in crop models. European Journal of Agronomy. 2018.
- View Article
- Google Scholar
62. Jones IM, and Koptur S. Dynamic extra floral nectar production: the timing of leaf damage affects the defensive response in Senna Mexicana var. chapmanii (Fabaceae). American Journal of Botany. 2015.102:58–66.
- View Article
- Google Scholar
63. Andersen CP. Source-sink balance and carbon allocation below ground in plants exposed to ozone. New Phytologist. 2003. 157, 213–228. pmid:33873636
- View Article
- PubMed/NCBI
- Google Scholar
64. Nicolson S.W., Thornburg R.W. 2007. Nectar chemistry. In: Nicolson SW, Nepi M, Pacini E (eds) Nectaries and nectar. Springer, Dordrecht, pp 215–263.
65. Davis A R, Peterson RL, Shuel RW. Vasculature and ultrastructure of the floral and stipular nectaries of Vicia faba (Leguminosae). Canadian Journal of Botany. 1988; 66: 1435–1448.
- View Article
- Google Scholar
66. Pacini E, Nepi M, Vesprini JL. Nectary biodiversity: a short review. Plant Systematics and Evolution. 2003; 238:7–21.
- View Article
- Google Scholar
67. Nepi M, von Aderkas P, Wagner R, Mugnaini S, Coulter A, Pacini E. Nectar and pollination drops: how different are they? Annals of Botany. 2009; 104:205–219. pmid:19477895
- View Article
- PubMed/NCBI
- Google Scholar
68. Zariman AZ, Omar NA and Nurul Huda A. Plant Attractants and Rewards for Pollinators: Their Significance to Successful Crop Pollination. International Journal of Life Sciences and Biotechnology, 2022; 5(2): p. 270–293.
- View Article
- Google Scholar
69. Caregnato FF, Clebsch CC, Rocha RF, Feistauer LBH, Oliveira PL, Divan AD Junior et al. Ozone exposure differentially affects oxidative stress parameters in distinct Phaseolus vulgaris L. varieties. Journal of Plant Interactions. 2010; 5(2): 111–115.
- View Article
- Google Scholar
70. Wright GA, and Schiestl FP. The evolution of floral scent: The influence of olfactory learning by insect pollinators on the honest signaling of floral rewards. Functional Ecology. 2009; 23(5), 841–851.
- View Article
- Google Scholar
71. Parachnowitsch AL, Raguso RA and Kessler A. Phenotypic selection to increase floral scent emission, but not flower size or colour in bee-pollinated Penstemon digitalis. New Phytologist. 2012; 195: 667–675.
- View Article
- Google Scholar
72. Griffiths DW, Robertson GW, Shepherd T and Ramsay G. Epicuticular waxes and volatiles from faba bean (Vicia faba) flowers. Phytochemistry. 1999. 52 (4): 607–612.
- View Article
- Google Scholar
73. Knudsen JT, Eriksson R, Gershenzon J, and Ståhl B. Diversity and distribution of floral scent. Botanical reviews. Rev. 2006; 72, 1–120.
- View Article
- Google Scholar
74. Fahmi-Halil M, Haris-Hussain M, Mirad R, Idris AG, and Jalinas J. Responses of Oil Palm Pollinator, Elaeidobius kamerunicus to Different Concentrations of Estragoles. bioRxiv. 2021.
- View Article
- Google Scholar
75. Glenny WR, Runyon JB, Burkle LA. Drought and increased CO₂ alter floral visual and olfactory traits with context-dependent effects on pollinator visitation. New Phytologist. 2018; 220:785–798.
- View Article
- Google Scholar
76. Howell AD and Alarcón R. Osmia bees (Hymenoptera: Megachilidae) can detect nectar-rewarding flowers using olfactory cues. Animal Behaviour. 2007; 74, 199–205.
- View Article
- Google Scholar
77. Riffell JA. The Neuroecology of a Pollinator’s Buffet: Olfactory Preferences and Learning in Insect Pollinators. Integrative and Comparative Biology. 2011; 51, 781–793. pmid:21803792
- View Article
- PubMed/NCBI
- Google Scholar
78. Riffell JA, Lei H, Abrell L and Hildebrand JG. Neural Basis of a Pollinator’s Buffet: Olfactory Specialization and Learning in Manduca sexta. Science. 2013; 339, 200–204.
- View Article
- Google Scholar
79. Harder LD and Barrett S CH. Pollen dispersal and mating patterns in animal-pollinated plants. In: Lloyd D. G. & Barrett S. C. H. (eds). Floral Biology: Studies on Floral Evolution in Animal-Pollinated Plants. Chapman & Hall, New York, 1996; pp. 140–190.

[ref1] 1. Osborne JL, Awmack CS, Clark SJ, Williams IH and Mills VC. Nectar and flower production in Vicia faba L. (field bean) at ambient and elevated carbon dioxide. Apidologie. 1997; 28, 43–55.
View Article
Google Scholar

[2] View Article

[3] Google Scholar

[ref2] 2. Chen Z, Cao J, Yu H, and Shang H. Effects of elevated ozone levels on photosynthesis, biomass and non-structural carbohydrates of Phoebe bournei and Phoebe zhennan in subtropical china. Frontiers of Plant Sciences. 2018. pmid:30555502
View Article
PubMed/NCBI
Google Scholar

[5] View Article

[6] PubMed/NCBI

[7] Google Scholar

[ref3] 3. Masui N, Agathokleous E, Mochizuki T, Tani A, Matsuura H, Koike T. Ozone disrupts the communication between plants and insects in urban and suburban areas: an updated insight on plant volatiles. Journal of Forest Research (Harbin). 2021; 10:1–13. pmid:33456272
View Article
PubMed/NCBI
Google Scholar

[9] View Article

[10] PubMed/NCBI

[11] Google Scholar

[ref4] 4. Jamieson MA, Burkle LA, Manson JS, Runyon JB, Trowbridge AM, Zientek J. Global change effects on plant-insect interactions: The role of phytochemistry. Current Opinion in Insect Sciences. 2017; 23, 70–80. pmid:29129286
View Article
PubMed/NCBI
Google Scholar

[13] View Article

[14] PubMed/NCBI

[15] Google Scholar

[ref5] 5. Peñuelas J and Staudt M. BVOCs and global change. Trends in Plant Science. 2010; 15, 133–144. pmid:20097116
View Article
PubMed/NCBI
Google Scholar

[17] View Article

[18] PubMed/NCBI

[19] Google Scholar

[ref6] 6. Dötterl S, Vater M, Rupp T and Held A. Ozone differentially affects perception of volatiles in western honeybees. Journal of Chemical Ecology. 2016; 42, 486–489.
View Article
Google Scholar

[21] View Article

[22] Google Scholar

[ref7] 7. Holopainen JK, Nerg AM and Blande JD. Multitrophic signaling in polluted atmospheres, in Biology, Controls and Models of Tree Volatile Organic Compound Emissions. Tree Physiology, eds Ü. Niinemets and R. K. Monson (Springer). 2013.

[ref8] 8. Wang LL, He XY, Chen W. Effects of elevated CO2 or/and O3 on growth and daily changes of photosynthesis in leaves of Pinus armandi. Huan Jing Ke Xue. 2010; 31(1): 36–40.
View Article
Google Scholar

[25] View Article

[26] Google Scholar

[ref9] 9. Hasan MM, Rahman MA, Skalicky M, Alabdallah NM, Waseem M, Jahan MS, et al. Ozone Induced Stomatal Regulations, MAPK and Phytohormone Signaling in Plants. International Journal of Molecular Sciences. 2021; 22(12): 6304. pmid:34208343
View Article
PubMed/NCBI
Google Scholar

[28] View Article

[29] PubMed/NCBI

[30] Google Scholar

[ref10] 10. Watanabe M, Hoshika Y, Koike T and Izuta T. Effects of Ozone on Japanese Trees. In: Izuta T. (eds) Air Pollution Impacts on Plants in East Asia. Springer, Tokyo. 2017.

[ref11] 11. Feng Z, Shang B, Gao F and Calatayud V. Current ambient and elevated ozone effects on poplar: A global meta-analysis and response relationships. Science of The Total Environment. 2019; 654: 832–840. pmid:30453256
View Article
PubMed/NCBI
Google Scholar

[33] View Article

[34] PubMed/NCBI

[35] Google Scholar

[ref12] 12. Xu Y, Feng Z, Peng J, Tarvainen L. Elevated ozone decreases the activity of Rubisco in poplar but not its activation under fluctuating light. Tree Physiology. 2022. 42(9): 1762–1775. pmid:35445727
View Article
PubMed/NCBI
Google Scholar

[37] View Article

[38] PubMed/NCBI

[39] Google Scholar

[ref13] 13. Farré-Armengol G, Peñuelas J, Li T, Yli-Pirilä P, Filella I, Llusia J, et al. Ozone degrades floral scent and reduces pollinator attraction to flowers. New Phytologist. 2016; 209(1), 152–160. pmid:26346807
View Article
PubMed/NCBI
Google Scholar

[41] View Article

[42] PubMed/NCBI

[43] Google Scholar

[ref14] 14. Blande JD, Holopainen J K and Li T. Air pollution impedes plant-to-plant communication by volatiles. Ecology Letters. 2010;13, 1172–1181. pmid:20602627
View Article
PubMed/NCBI
Google Scholar

[45] View Article

[46] PubMed/NCBI

[47] Google Scholar

[ref15] 15. Li T. and Blande JD. Associational susceptibility in broccoli: mediated by plant volatiles, impeded by O3. Global Change Biology. 2015; 21, 1993–2004.
View Article
Google Scholar

[49] View Article

[50] Google Scholar

[ref16] 16. Blande JD, Holopainen JK and Niinemets Ü. Plant volatiles in polluted atmospheres: stress responses and signal degradation. Plant, Cell and Environment. 2014; 37, 892–1904. pmid:24738697
View Article
PubMed/NCBI
Google Scholar

[52] View Article

[53] PubMed/NCBI

[54] Google Scholar

[ref17] 17. Wang D, Heckathorn SA, Wang X and Philpott SM. A meta-analysis of plant physiological and growth responses to temperature and elevated CO2. Oecologia. 2012; 169, 1–13. pmid:22037993
View Article
PubMed/NCBI
Google Scholar

[56] View Article

[57] PubMed/NCBI

[58] Google Scholar

[ref18] 18. Ainsworth EA, Leakey ADB, Ort DR and Long SP. FACE-ing the facts: inconsistencies and interdependence among field, chamber and modeling studies of elevated [CO2] impacts on crop yield and food supply. New Phytologist. 2008; 179, 5–9. pmid:18482226
View Article
PubMed/NCBI
Google Scholar

[60] View Article

[61] PubMed/NCBI

[62] Google Scholar

[ref19] 19. Jasoni R, Kane C, Green C, Peffley E, Tissue D, Thompson L, et al. Altered leaf and root emissions from onion (Allium cepa L.) grown under elevated CO2 condition. Environmental and Experimental Botany. 2004; 51(3) 273–280.
View Article
Google Scholar

[64] View Article

[65] Google Scholar

[ref20] 20. Lange D, Dáttilo W, Del-Claro K. Influence of extra floralnectary phenology on ant-plant mutualistic networks in a neotropical savanna. Ecologial Entomology. 2013; 38: 463–469.
View Article
Google Scholar

[67] View Article

[68] Google Scholar

[ref21] 21. Belchior C. Sendoya SF, Del-Claro K. Temporal Variation in the Abundance and Richness of Foliage-Dwelling Ants Mediated by Extra floralNectar. PLoS One. 2016; 11(7): e0158283. pmid:27438722
View Article
PubMed/NCBI
Google Scholar

[70] View Article

[71] PubMed/NCBI

[72] Google Scholar

[ref22] 22. Weber MG, Porturas LD, Keeler KH. World list of plants with extra floral nectaries. http://www.extrafloralnectaries.org. 2015.

[ref23] 23. Mesquita-Neto JN, Paiva EAS, Galetto L and Schlindwein C. Nectar Secretion of Floral Buds of Tococa guianensis Mediates Interactions With Generalist Ants That Reduce Florivory. Frontiers in Plant Science. 2020; 11:627.
View Article
Google Scholar

[75] View Article

[76] Google Scholar

[ref24] 24. McKey D. Interactions between ants and leguminous plants. In’Advances in Legume Biology’. (Eds CH Stirton, JL Zarucchi). Monographs in Systematic Botany from the Missouri. BotanicalGarden. 1989.;29, 673–718. (Missouri Botanical Garden Press: Saint Louis, MO, USA.

[ref25] 25. Heil M. Extrafloral Nectar at the Plant-Insect Interface: A Spotlight on Chemical Ecology, Phenotypic Plasticity, and Food Webs. Annual Review of Entomology. 2015; 60:1, 213–232.
View Article
Google Scholar

[79] View Article

[80] Google Scholar

[ref26] 26. Patt JM and Rohrig E. Laboratory Evaluations of the Foraging Success of Tamarixia radiata (Hymenoptera: Eulophidae) on Flowers and Extrafloral Nectaries: Potential use of Nectar Plants for Conservation Biological Control of Asian Citrus Psyllid (Hemiptera: Liviidae). Florida Entomologist. 2017; 100(1): 149–156.
View Article
Google Scholar

[82] View Article

[83] Google Scholar

[ref27] 27. Beyer N, Gabriel D, Kirsch F, Schulz-Kesting K, Dauber J, Westphal C. Functional groups of wild bees respond differently to faba bean Vicia faba L. cultivation at landscape scale. Journal of Applied Ecology. 2020; 57(12):2499–2508.
View Article
Google Scholar

[85] View Article

[86] Google Scholar

[ref28] 28. Michener C.D. The Bees of the World, 1st Ed., John Hopkins University Press, Baltimore. 2000.

[ref29] 29. Roulston TH, Cane JH and Buchmann SL. What governs the protein content of pollen grains: pollinator preferences, pollen- pistil interactions, or phylogeny. Ecological Monographs. 2000. 70(4); 617–643.
View Article
Google Scholar

[89] View Article

[90] Google Scholar

[ref30] 30. Ceuppens B, Eeraerts M, Vleugels T, Cnops G, Roldan-Ruiz I and Smagghe G. Effects of dietary lambda-cyhalothrin exposure on bumblebee survival, reproduction, and foraging behaviour in laboratory and greenhouse. Journal of Pest Science. 2015; 88, 777–783.
View Article
Google Scholar

[92] View Article

[93] Google Scholar

[ref31] 31. Dudareva N, Pichersky E, Dudareva N, Pichersky E. Floral scent metabolic pathways: Their regulation and evolution. In Biology of Floral Scent, Dudareva N., Pichersky E., eds (Boca Raton, FL: CRC Press), 2006; pp. 55–78.

[ref32] 32. Raguso RA. Floral scent in a whole-plant context: moving beyond pollinator attraction. Functional Ecology. 2009; 23(5), 837–840.
View Article
Google Scholar

[96] View Article

[97] Google Scholar

[ref33] 33. Marazzi B, Gonzalez AM, Delgado-Salinas A, Luckow MA, Ringelberg JJ, Hughes CE. Extra floral nectaries in Leguminosae: phylogenetic distribution, morphological diversity and evolution. Australian Systematic Botany. 2019; 32, 409–458.
View Article
Google Scholar

[99] View Article

[100] Google Scholar

[ref34] 34. Klein AM, Vaissiere BE, Cane JH, Steffan-Dewenter I, Cunningham SA, Kremen C et al. Importance of pollinators in changing landscapes for world crops. Proceedings of the Royal Society of London B: Biological Sciences. 2007; 274 (1608), 303–313. pmid:17164193
View Article
PubMed/NCBI
Google Scholar

[102] View Article

[103] PubMed/NCBI

[104] Google Scholar

[ref35] 35. Klatt BK, Holzschuh A, Westphal C, Clough Y, Smit I, Pawelzik E et al. Bee pollination improves crop quality, shelf life and commercial value. Proceedings of the Royal Society of London B: Biological Sciences. 2014; 281 (1775), 20132440. pmid:24307669
View Article
PubMed/NCBI
Google Scholar

[106] View Article

[107] PubMed/NCBI

[108] Google Scholar

[ref36] 36. Bartomeus I, Potts SG, Steffan-Dewenter I, Vaissiere BE, Woyciechowski M, Krewenka KM, et al. Contribution of insect pollinators to crop yield and quality varies with agricultural intensification. PeerJ. 2014; 2, e328. pmid:24749007
View Article
PubMed/NCBI
Google Scholar

[110] View Article

[111] PubMed/NCBI

[112] Google Scholar

[ref37] 37. Nayak GK, Roberts SPM, Garratt M, Breeze TD, Tscheulin T, Harrison-Cripps J, et al. Interactive effect of floral abundance and semi-natural habitats on pollinators in field beans (Vicia faba). Agriculture, Ecosystems and Environment. 2015; 199, 58–66.
View Article
Google Scholar

[114] View Article

[115] Google Scholar

[ref38] 38. Katayama N, and Suzuki N. Role of extra floral nectaries of Vicia faba in attraction of ants and herbivore exclusion by ants. Entomological Science. 2004; 7(2): 119–124.
View Article
Google Scholar

[117] View Article

[118] Google Scholar

[ref39] 39. Marzinzig B, Brünjes L, Biagioni S, Behling H, Link W, and Westphal C. Bee pollinators of faba bean (Vicia faba L.) differ in their foraging behaviour and pollination efficiency Agriculture Ecosystems and Environment, 2018; 264: 24–33.
View Article
Google Scholar

[120] View Article

[121] Google Scholar

[ref40] 40. Burton, Andrew J., Zak, Donald R., Kubiske, Mark E., and Pregitzer, Kurt S. Impacts of interacting elevated atmospheric co2 and o3 on the structure and functioning of a northern forest ecosystem: operating and decommissioning the aspen face project. United States: N. p., 2014.

[ref41] 41. Gustafson E.J., Kubiske M.E., Miranda B.R. et al. Extrapolating plot-scale CO₂ and ozone enrichment experimental results to novel conditions and scales using mechanistic modeling. Ecol Process. 2018; 7, 31.
View Article
Google Scholar

[124] View Article

[125] Google Scholar

[ref42] 42. Tobita H, Komatsu M, Harayama H, Yazaki K, Kitaoka S and Kitao M. Effects of Combined CO2 and O3 Exposures on Net CO2 Assimilation and Biomass Allocation in Seedlings of the Late-Successional Fagus Crenata. Climate 2019, 7(10), 117.
View Article
Google Scholar

[127] View Article

[128] Google Scholar

[ref43] 43. Almohisen IAA and Alyemeni MN. Effect of Ozone on the Quality of Two Legume Crops (Vicia faba and Pisum sativum) around Riyadh City. Life Science Journal. 2013; 10(4), 2297–2302.
View Article
Google Scholar

[130] View Article

[131] Google Scholar

[ref44] 44. Stabler D. Impacts of ozone pollution on nectar and pollen quality and their significance for pollinators. School of Biology. Newcastle, UK, Newcastle University. PhD thesis. 2016.

[ref45] 45. Otieno M., Peters K. M., Duque L. and Steffan-Dewenter I. Interactive effects of ozone and carbon dioxide on plant-pollinator interactions and yields in a legume crop. Environmental Advances. 2022; 9: 100285.
View Article
Google Scholar

[134] View Article

[135] Google Scholar

[ref46] 46. Duque L, Poelman EH, Steffan-Dewenter I. Plant-mediated effects of ozone on herbivores depend on exposure duration and temperature. Scientific Reports. 2019; 9, 19891. pmid:31882632
View Article
PubMed/NCBI
Google Scholar

[137] View Article

[138] PubMed/NCBI

[139] Google Scholar

[ref47] 47. Duque L, Poelman EH, Steffan-Dewenter I. Effects of ozone stress on flowering phenology, plant-pollinator interactions and plant reproductive success. Environmental Pollution. 2021; 272, 115953. pmid:33190978
View Article
PubMed/NCBI
Google Scholar

[141] View Article

[142] PubMed/NCBI

[143] Google Scholar

[ref48] 48. Adams RP. Identification of essential oil components by gas chromotography/mass spectrometry, 4th edn. Allured publishing, Carol Stream; 2017.

[ref49] 49. Aronne G and Malara P. Fiber-optic refractometer for in vivo sugar concentration measurements of low-nectar-producing flowers. New Phytologist. 2019; 224: 987–993.
View Article
Google Scholar

[146] View Article

[147] Google Scholar

[ref50] 50. R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2022.

[ref51] 51. Jansen J, Pokorny T and Schmitt T. Disentangling the effect of insemination and ovary development on the cuticular hydrocarbon profile in the bumblebee Bombus terrestris (Hymenoptera: Apidae). Apidologie. 2016; 47, 101–113.
View Article
Google Scholar

[150] View Article

[151] Google Scholar

[ref52] 52. Cutler DR, Edwards TC Jr, Beard KH, Cutler A, Hess KT, Gibson J, et al. Random forests for classification in ecology. Ecology. 2007; 88 (11), 2783–2792. pmid:18051647
View Article
PubMed/NCBI
Google Scholar

[153] View Article

[154] PubMed/NCBI

[155] Google Scholar

[ref53] 53. Hanusz Z and Tarasińska J. Normalization of the Kolmogorov–Smirnov and Shapiro–Wilk tests of normality. Biometrical Letters. 2015; 52(2)85–93.
View Article
Google Scholar

[157] View Article

[158] Google Scholar

[ref54] 54. Ribeiro-Oliveira JP, de Santana DG, Pereira VJ, dos Santos CM, Data transformation: an underestimated tool by inappropriate use. Acta Scientiarum Agronomy, 2018; 40.
View Article
Google Scholar

[160] View Article

[161] Google Scholar

[ref55] 55. Agathokleous E, Feng Z, Oksanen E, Sicard P, Wang Q, Saitanis CJ, et al. Ozone affects plant, insect, and soil microbial communities: A threat to terrestrial ecosystems and biodiversity. Science Advances. 2020;12;6(33):eabc1176. pmid:32851188
View Article
PubMed/NCBI
Google Scholar

[163] View Article

[164] PubMed/NCBI

[165] Google Scholar

[ref56] 56. Saunier A and Blande JD. The effect of elevated ozone on floral chemistry of brassicaceae species. Environmental Pollution. 2019; 255: 10. pmid:31546077
View Article
PubMed/NCBI
Google Scholar

[167] View Article

[168] PubMed/NCBI

[169] Google Scholar

[ref57] 57. Heiden AC, Hoffmann T, Kahl J, et al. Emission of volatile organic compounds from ozone-exposed plants. Ecological Applications.1999; 9: 1160–1167.
View Article
Google Scholar

[171] View Article

[172] Google Scholar

[ref58] 58. Brosset A, Saunier A, Kivimaenpaa M, et al. Does ozone exposure affect herbivore-induced plant volatile emissions differently in wild and cultivated plants? Environmental Sciences and Pollution Research. 2020; 27: 30448–30459. pmid:32468369
View Article
PubMed/NCBI
Google Scholar

[174] View Article

[175] PubMed/NCBI

[176] Google Scholar

[ref59] 59. Cui HY, Su JW, Wei JN, et al. Elevated o₃ enhances the attraction of whitefly-infested tomato plants to Encarsia formosa. Scientific Reports. 2014; 4: 6.
View Article
Google Scholar

[178] View Article

[179] Google Scholar

[ref60] 60. Yuan X, Calatayud V, Gao F, Fares S, Paoletti E, Tian Y, et al. Interaction of drought and ozone exposure on isoprene emission from extensively cultivated poplar. 2016; 39(10): 2276–2287.
View Article
Google Scholar

[181] View Article

[182] Google Scholar

[ref61] 61. Emberson LD, Pleijel H, Ainsworth EA, van den Berg M, Ren W, Osborn et al. Ozone effects on crops and consideration in crop models. European Journal of Agronomy. 2018.
View Article
Google Scholar

[184] View Article

[185] Google Scholar

[ref62] 62. Jones IM, and Koptur S. Dynamic extra floral nectar production: the timing of leaf damage affects the defensive response in Senna Mexicana var. chapmanii (Fabaceae). American Journal of Botany. 2015.102:58–66.
View Article
Google Scholar

[187] View Article

[188] Google Scholar

[ref63] 63. Andersen CP. Source-sink balance and carbon allocation below ground in plants exposed to ozone. New Phytologist. 2003. 157, 213–228. pmid:33873636
View Article
PubMed/NCBI
Google Scholar

[190] View Article

[191] PubMed/NCBI

[192] Google Scholar

[ref64] 64. Nicolson S.W., Thornburg R.W. 2007. Nectar chemistry. In: Nicolson SW, Nepi M, Pacini E (eds) Nectaries and nectar. Springer, Dordrecht, pp 215–263.

[ref65] 65. Davis A R, Peterson RL, Shuel RW. Vasculature and ultrastructure of the floral and stipular nectaries of Vicia faba (Leguminosae). Canadian Journal of Botany. 1988; 66: 1435–1448.
View Article
Google Scholar

[195] View Article

[196] Google Scholar

[ref66] 66. Pacini E, Nepi M, Vesprini JL. Nectary biodiversity: a short review. Plant Systematics and Evolution. 2003; 238:7–21.
View Article
Google Scholar

[198] View Article

[199] Google Scholar

[ref67] 67. Nepi M, von Aderkas P, Wagner R, Mugnaini S, Coulter A, Pacini E. Nectar and pollination drops: how different are they? Annals of Botany. 2009; 104:205–219. pmid:19477895
View Article
PubMed/NCBI
Google Scholar

[201] View Article

[202] PubMed/NCBI

[203] Google Scholar

[ref68] 68. Zariman AZ, Omar NA and Nurul Huda A. Plant Attractants and Rewards for Pollinators: Their Significance to Successful Crop Pollination. International Journal of Life Sciences and Biotechnology, 2022; 5(2): p. 270–293.
View Article
Google Scholar

[205] View Article

[206] Google Scholar

[ref69] 69. Caregnato FF, Clebsch CC, Rocha RF, Feistauer LBH, Oliveira PL, Divan AD Junior et al. Ozone exposure differentially affects oxidative stress parameters in distinct Phaseolus vulgaris L. varieties. Journal of Plant Interactions. 2010; 5(2): 111–115.
View Article
Google Scholar

[208] View Article

[209] Google Scholar

[ref70] 70. Wright GA, and Schiestl FP. The evolution of floral scent: The influence of olfactory learning by insect pollinators on the honest signaling of floral rewards. Functional Ecology. 2009; 23(5), 841–851.
View Article
Google Scholar

[211] View Article

[212] Google Scholar

[ref71] 71. Parachnowitsch AL, Raguso RA and Kessler A. Phenotypic selection to increase floral scent emission, but not flower size or colour in bee-pollinated Penstemon digitalis. New Phytologist. 2012; 195: 667–675.
View Article
Google Scholar

[214] View Article

[215] Google Scholar

[ref72] 72. Griffiths DW, Robertson GW, Shepherd T and Ramsay G. Epicuticular waxes and volatiles from faba bean (Vicia faba) flowers. Phytochemistry. 1999. 52 (4): 607–612.
View Article
Google Scholar

[217] View Article

[218] Google Scholar

[ref73] 73. Knudsen JT, Eriksson R, Gershenzon J, and Ståhl B. Diversity and distribution of floral scent. Botanical reviews. Rev. 2006; 72, 1–120.
View Article
Google Scholar

[220] View Article

[221] Google Scholar

[ref74] 74. Fahmi-Halil M, Haris-Hussain M, Mirad R, Idris AG, and Jalinas J. Responses of Oil Palm Pollinator, Elaeidobius kamerunicus to Different Concentrations of Estragoles. bioRxiv. 2021.
View Article
Google Scholar

[223] View Article

[224] Google Scholar

[ref75] 75. Glenny WR, Runyon JB, Burkle LA. Drought and increased CO₂ alter floral visual and olfactory traits with context-dependent effects on pollinator visitation. New Phytologist. 2018; 220:785–798.
View Article
Google Scholar

[226] View Article

[227] Google Scholar

[ref76] 76. Howell AD and Alarcón R. Osmia bees (Hymenoptera: Megachilidae) can detect nectar-rewarding flowers using olfactory cues. Animal Behaviour. 2007; 74, 199–205.
View Article
Google Scholar

[229] View Article

[230] Google Scholar

[ref77] 77. Riffell JA. The Neuroecology of a Pollinator’s Buffet: Olfactory Preferences and Learning in Insect Pollinators. Integrative and Comparative Biology. 2011; 51, 781–793. pmid:21803792
View Article
PubMed/NCBI
Google Scholar

[232] View Article

[233] PubMed/NCBI

[234] Google Scholar

[ref78] 78. Riffell JA, Lei H, Abrell L and Hildebrand JG. Neural Basis of a Pollinator’s Buffet: Olfactory Specialization and Learning in Manduca sexta. Science. 2013; 339, 200–204.
View Article
Google Scholar

[236] View Article

[237] Google Scholar

[ref79] 79. Harder LD and Barrett S CH. Pollen dispersal and mating patterns in animal-pollinated plants. In: Lloyd D. G. & Barrett S. C. H. (eds). Floral Biology: Studies on Floral Evolution in Animal-Pollinated Plants. Chapman & Hall, New York, 1996; pp. 140–190.

Figures

Abstract

Introduction

Materials and methods

Crop establishment

Fumigation experimental set-up

Greenhouse set up

VOC sample collection and TD-GC-MS analysis

Measurement of extra floral nectar volume and sugar concentration

Bee visitation to extra floral nectaries

Data analysis

Results

Effect of O3 and CO2 on VOCs

Effects of O3 and CO2 on EFN nectar and consequences for bee visits

Discussion

Effect of O3 and CO2 on VOCs

Effect of O3 on EFN nectar production

Behavioral consequences of increased O3 and CO2 on bees utilizing EFNs

Conclusion

Supporting information

S1 File.

Acknowledgments

References

Effect of O₃ and CO₂ on VOCs

Effects of O₃ and CO₂ on EFN nectar and consequences for bee visits

Effect of O₃ on EFN nectar production

Behavioral consequences of increased O₃ and CO₂ on bees utilizing EFNs