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Annals of Botany logoLink to Annals of Botany
. 2023 Jul 7;132(1):95–106. doi: 10.1093/aob/mcad082

The role of within-plant variation in nectar production: an experimental approach

Michelle Maldonado 1, Juan Fornoni 2, Karina Boege 3, Rubén Pérez Ishiwara 4, Rocío Santos-Gally 5,✉, César A Domínguez 6,✉
PMCID: PMC10550272  PMID: 37419457

Abstract

Background and aims

Nectar, a plant reward for pollinators, can be energetically expensive. Hence, a higher investment in nectar production can lead to reduced allocation to other vital functions and/or increased geitonogamous pollination. One possible strategy employed by plants to reduce these costs is to offer variable amounts of nectar among flowers within a plant, to manipulate pollinator behaviour. Using artificial flowers, we tested this hypothesis by examining how pollinator visitation responds to inter- and intra-plant variation in nectar production, assessing how these responses impact the energetic cost per visit.

Methods

We conducted a 2 × 2 factorial experiment using artificial flowers, with two levels of nectar investment (high and low sugar concentration) and two degrees of intra-plant variation in nectar concentration (coefficient of variation 0 and 20 %). The experimental plants were exposed to visits (number and type) from a captive Bombus impatiens colony, and we recorded the total visitation rate, distinguishing geitonogamous from exogamous visits. Additionally, we calculated two estimators of the energetic cost per visit and examined whether flowers with higher nectar concentrations (richer flowers) attracted more bumblebees.

Key Results

Plants in the variable nectar production treatment (coefficient of variation 20 %) had a greater proportion of flowers visited by pollinators, with higher rates of total, geitonogamous and exogamous visitation, compared with plants with invariable nectar production. When assuming no nectar reabsorption, variable plants incurred a lower cost per visit compared with invariable plants. Moreover, highly rewarding flowers on variable plants had higher rates of pollination visits compared with flowers with few rewards.

Conclusions

Intra-plant variation in nectar concentration can represent a mechanism for pollinator manipulation, enabling plants to decrease the energetic costs of the interaction while still ensuring consistent pollinator visitation. However, our findings did not provide support for the hypothesis that intra-plant variation in nectar concentration acts as a mechanism to avoid geitonogamy. Additionally, our results confirmed the hypothesis that increased visitation to variable plants is dependent on the presence of flowers with nectar concentration above the mean.

Keywords: Cost of reproduction, exogamy, geitonogamy, investment, nectar, pollinator manipulation, within-plant variation

INTRODUCTION

Pollination is a mutually beneficial interaction where species exchange resources that they cannot produce or obtain on their own. Plants offer commodities such as nectar, oils, fragrances and pollen in exchange for the service of gamete transportation provided by pollinators (Simpson and Neff, 1981). These resources and services are typically costly, so natural selection is expected to favour strategies that maximize the benefit:cost ratio for each partner involved in the exchange. However, as the gain of one partner comes at the expense of the other partner, conflicts of interest regarding resource investment underlie mutualistic interactions (Pellmyr, 2002). This reciprocal exploitation (Bronstein, 2001) can be conceptualized as an evolutionary game (Pyke, 2016) where the outcome of the interaction for one partner depends on the strategy employed by the other partner (Pyke, 1978, 2016; Cohen and Shmida, 1993).

Optimality theory predicts the evolution of an optimal investment determined by the maximum benefit:cost ratio derived from the interaction (Smith, 1978). In the case of plant–pollinator interactions, the production of plant rewards, such as nectar, can represent a significant allocation of resources that are no longer available for plant maintenance. In fact, nectar production can account for up to 37 % of a plant’s photosynthate budget (Pleasants and Chaplin, 1983; Southwick, 1984). Therefore, natural selection is expected to favour strategies that minimize the costs of reward production without compromising the benefits of pollination visitation.

In this context, and in accordance with optimality theory (Bell, 1986; Pyke, 2016), we propose that plants can achieve this goal by modifying two components of nectar production without sacrificing the benefits provided by pollinators: the total investment in terms of quantity (e.g. nectar volume) and/or quality (e.g. nectar concentration), as well as how this investment is distributed among the flowers within a given plant (e.g. modifying the intra-individual variance; Parachnowitsch et al., 2019).

Empirical evidence reveals that in many plant species the quantity and quality of rewards offered to mutualistic animals (such as pollinators, dispersers, guards, etc.) exhibit significant intra- and inter-individual variation. For example, studies have shown variation in nectar sugar composition (Herrera et al., 2006; Canto et al., 2007), nectar volume (Lu et al., 2015), and both volume and nectar sugar composition (Pacini and Nepi, 2007; Herrera, 2009; Parachnowitsch et al., 2019). Intra-individual coefficients of variation in nectar volume can be much more variable (range 5–350 %) compared with morphological floral traits (range 1.7–16.3 %) (Cresswell, 1998; Herrera et al., 2006; Canto et al., 2007, 2011; Herrera, 2009). This intra-plant variation in reward production can impact the foraging behaviour of birds, bees and bumblebees, thus affecting pollination success (Feinsinger, 1978; Biernaskie et al., 2002; Hirabayashi et al. 2006; Keasar et al., 2008; Pyke, 2010). Usually, this variation has been attributed to environmentally induced heterogeneity in resource availability (Leiss and Klinkhamer, 2005; Parachnowitsch et al., 2019) or developmental instability (Møller and Shykoff, 1999; Møller, 2000; Bissell and Diggle, 2010). However, if such variation influences pollinator behaviour, it could represent an adaptive mutualist manipulative strategy.

Pollinators employ economic decision-making strategies during foraging to optimize their energy intake while minimizing the time spent in this activity and the associated risks (a process known as optimal foraging behaviour; Pyke, 2010; Dreisig, 2012). Charnov (1976) proposed that, because food distribution is uneven and occurs in patches with varying qualities (plants within patches and flowers within plants), foraging animals should use available information to predict the expected gains from staying in one patch versus moving to another. Therefore, optimal foraging relies on the forager’s ability to assess patch value and its knowledge of the average payoff of the entire foraging area (Biernaskie et al., 2009). However, foraging animals seldom reach a perfect assessment of resource distribution (Soberón, 1986), opening the possibility for plants to employ intra-individual variation in reward production as a manipulative strategy to optimize resources. Feinsinger (1978), for example, showed significant variability in nectar secretion within individuals across five species of hummingbird-pollinated plants. He suggested that a ‘bonanza–blank’ pattern (a combination of rewarding and nectarless flowers) might reduce total investment in nectar, compelling pollinators to visit more flowers. This interpretation found support in the theoretical model by Bell (1986), wherein he simulated pollinator visits to plants bearing both rewarding and non-rewarding flowers. Three decades later, Pyke (2016) argued that, rather than acting as an attractant, floral nectar should be considered as a mechanism for manipulating nectar-feeding pollinators, as they have the ability to detect and respond to differences in nectar volume, composition and concentration (Fleming et al., 2004; Wang et al., 2013; Pyke, 2016).

From a different rationale, Klinkhamer and de Jong (1993) proposed that plants with high intra-individual variability experience fewer visits during foraging bouts, thereby reducing the risk of geitonogamous pollination and inbreeding depression. Consequently, plants may avoid the negative consequences of attractiveness by increasing the intra-plant variance in nectar production (Smithson and Gigord, 2003; Bailey et al., 2007; Keasar et al., 2008; Zhao et al., 2016; Nepi et al., 2018). These alternative hypotheses present opposing predictions. Whereas the resource-saving hypothesis (referred to as the bonanza–blank hypothesis; Feinsinger, 1978) suggests no reduction or even an increase in the rate of pollination visitation in variable plants, and a reduction in resources invested in reward production, the geitonogamy avoidance hypothesis predicts a decrease in visitation rate among flowers of the same plant, regardless of the level of investment. Both hypotheses rely on the assumption that, despite the interests of pollinators, intra-individual variation in nectar can function as a mechanism for manipulating pollinators.

In this study, we explored if at least a fraction of the intra-plant variation in nectar concentration represents an adaptive (manipulative) strategy (Feinsinger, 1978; Bell, 1986; Biernaskie et al., 2002). We assessed how pollinators respond to inter- and intra-individual variation in nectar investment (nectar concentration) and how these responses impact various proxies of plant fitness (such as the rate of pollinator visitation and energetic cost per visit). Therefore, the experimental design enabled us to test both the resource-saving and the geitonogamy avoidance hypotheses. We opted to work with variation in nectar concentration rather than its volume, as it is a better descriptor of nectar quality, and because social bees are particularly responsive to this trait given its impact on energy intake and fitness (Pamminger et al., 2019). We conducted a two-way factorial experiment using artificial plants/flowers, manipulating both the average (total investment) and intra-individual variance in nectar concentration per plant. While a reasonable expectation is that pollinators should show a preference for plants with higher concentrations of nectar, both hypotheses predict suboptimal foraging behaviour when pollinators encounter intra-individual variation in nectar concentration. Consequently, we anticipated that pollinator visitation rates should be higher in plants with high nectar investment. However, the resource-saving hypothesis suggests that the variability treatment would also yield similar or even higher visitation rates, regardless of the investment level. Furthermore, we expected the lowest cost per visit in variable plants with low investments in nectar. On the other hand, according to the geitonogamy avoidance hypothesis, we predict a lower geitonogamous visitation rate in the high-variance treatment, regardless of the level of investment. Last, by recording all pollinator visits received by artificial plants, we were able to assess whether highly rewarding flowers within variable plants represent the primary attractant or ‘magnet’ for these plants (Thomson, 1978; Craig and Johnson, 2008). We anticipated higher visitation rates in these flowers within a variable plant, compared with flowers with lower sugar concentration.

MATERIALS AND METHODS

Experimental design

The experiments were conducted at the Institute of Ecology of UNAM, Mexico City, in March 2018, within a mesh enclosure measuring 3 × 8 × 2.20 m. We used a captive Bombus impatiens colony (Koppert Biological Systems, México) and artificial multiflowered plants (referred to as ‘plants’ hereafter) in a 2 × 2 factorial experimental design, considering two levels of either investment or intra-individual variance in nectar concentration. The experimental plants consisted of vertical wooden boards measuring 50 cm in length and 9 cm in width, with two parallel rows of eight holes where artificial flowers were positioned. Artificial flowers (referred to as ‘flowers’ hereafter) were made using 1.5-mL Eppendorf tubes with a round cardboard corolla (ultra lemon-yellow, 3.5 cm in diameter) surrounding the opening of the tube. Before the onset of the experiment, each flower was impregnated with 5 µL of lavender essence. Bumblebees were trained to visit artificial plants by placing them near to the nest and filling the flowers with artificial nectar. Sugar concentration in the nectar ranged from 21 to 46 % (fructose content by weight), which falls within the observed range for bumblebee-pollinated species (Kwak et al., 1985; Pamminger et al., 2019). The different nectar concentrations used in these experiments were made by diluting a 60 % (w/w) fructose solution (Koppert Biological Systems, Mexico). Once bumblebees learned to visit artificial plants, the experimental trials were performed by arranging the plants in a perpendicular row, with a separation of 7.5 m from the nest.

Experimental trials

The colony housed ~50 bumblebee workers, which had unrestricted access to exit the colony throughout the entire experimental phase. During the observations, a maximum of three workers per artificial plant could be observed simultaneously. Throughout the 1-h duration of the daily trial, the bumblebees freely fed on the 320 artificial flowers. The experimental design comprised five plants in each treatment combination and 16 flowers per plant for a total of 320 flowers per day. We repeated this experimental trial for a total of 12 consecutive days. To simulate the costs a plant would pay to produce nectar, our experimental design consisted of a 2 × 2 factorial arrangement with two treatments: the level of sugar concentration (low and high sugar investment per plant, 51.35 and 57.6 g, respectively, representing an 11 % difference in total sugar investment per plant), and the degree of intra-individual variation in nectar concentration [invariable and variable, with a coefficient of variation (CV) of 0 and 20 %, respectively]. For the low and high levels of investment (respectively), the flowers had either a 32 or 36 % sugar concentration (w/w), in the invariable treatment. In the variable treatment, to achieve the two levels of investment we used five flowers with 25 % sugar concentration, six flowers with 30 %, and five flowers with 42 % for the low investment–variable treatment. For the high investment–variable treatment, we used five flowers with a 36 % sugar concentration, six flowers with 33 % and five flowers with 46 %.

As mentioned above, plants with a high sugar concentration would allocate 11 % more resources to nectar production compared with plants in the low-concentration treatment. This difference can be significant for plants considering that resources could be allocated to other primary functions (Pyke, 1991; Ordano and Ornelas, 2005; Whitehead et al., 2012; Nepi et al., 2018). While Chittka and Thomson (2011) suggested that bees are indifferent to differences in sugar concentration below 5 % (w/w), it is important to note that our experimental setup included flowers with nectar concentrations ranging from 25 to 46 % in the variable treatment (Supplementary Data Table S1). On the other hand, the limited available studies indicate that the within-plant CV of nectar concentration ranges from 10 to 80 % (Wang et al., 2013; C. A. Domínguez et al., unpubl. data). To be conservative in our approach, we selected a CV of 20 % for plants in the variable treatment.

Artificial plants bore 16 artificial flowers, each filled with 100 µL of nectar. For each trial, the position of the flowers within the plants and the placement of the plants (treatments) within the experimental setting were randomly assigned. Bumblebee foraging behaviour was recorded using three stationary video cameras (GoPro Hero 5) that captured all the 320 flowers. The recorded videos were later reviewed at the laboratory, and the total number of visits per plant was counted, distinguishing between exogamous visits (visits from other plants) or geitonogamous visits (visits from other flowers within the same plant). Additionally, we measured the amount of nectar remaining in each flower to estimate the cost per visit for each treatment. After each trial, bumblebees were provided with 20 g of pollen and 64 flowers, each containing 1 mL of 36 % nectar. The nest was closed at dusk.

Because we were able to record all the visits received by each experimental plant during a given trial, we calculated six response variables representing different components of the quality of pollinator service. First, the visitation rate (VR), measured as the number of visits per hour, was calculated for each plant by adding up all the visits, regardless of whether they were geitonogamous or exogamous. The exogamous visitation rate (EVR) was also calculated for each plant considering the first visit by a bumblebee and previous visits to other plants. Geitonogamous visitation rate (GVR) denoted the number of visits originating within the same plant. Considering that pollinator visits may be concentrated in a few flowers, we additionally measured the proportion of visited flowers (PVF) for each plant as an indicator of pollinator quality. The PVF was calculated by dividing the number of flowers in a plant that received at least one visit by the total number of flowers in the plant (16 in all cases). Furthermore, we calculated the proportion of flowers with exogamous (PFEV) and the proportion of flowers with geitonogamous visitation (PFGV).

We estimated two additional variables representing the energetic cost per visit for each plant (ECx) in each combination of both treatments. The first estimation assumes that plants are unable to reabsorb nectar, thus requiring the inclusion of nectar left by pollinators in the cost calculation (Nepi and Stpiczynska, 2008a, b). In this scenario, the investment per visit was determined by the ratio between the total amount of nectar assigned to a specific plant (treatment) and the number of visits:

ECx=TinvVisits

where ECx represents the energetic cost per visit (milligrams of sugar per visit) of plant x, Tinv represents the total sugar investment (milligrams of sugar) of plant x (based on the treatment assigned to plant x), and Visits denotes the number of visits received by plant x.

The second estimation considers that many plant species can reabsorb nectar not consumed by pollinators (Nepi and Stpiczyńska, 2008a, b; Heil, 2011; Nepi et al., 2011), thereby maximizing the efficient use of this potentially costly resource. Because we measured the amount of nectar remaining in each flower after pollinator visits, we were able to estimate a proxy of the energetic cost per visit for each plant, assuming nectar reabsorption, as:

ECx=Tinv−∑i=1n⁡RNiVisits

where ECx represents the energetic cost per visit (milligrams of sugar per visit) of plant x, Tinv denotes the total sugar investment (milligrams of sugar) of plant x (depending on the treatment assigned to plant x), RNi signifies the quantity of sugar (mg) left by pollinators in flower i of plant x, and Visits indicates the number of visits received by plant x.

For all trials, we recorded the temperature at the time of each trial, because it can influence the foraging behaviour of bumblebees, as their flight muscles need to reach a temperature of 30°C in order to engage in this activity (Nieh et al., 2006). We incorporated this covariate into all the statistical analyses.

Statistical analyses

We initially examined the effect of investment and variation on the total, geitonogamous and exogamous visitation rates. As the data were overdispersed in relation to a Poisson model, we used generalized linear models (GLMs) with negative binomial-distributed errors and a logit-link function (using the MASS package in R; Lesnoff and Lancelot, 2012). For the proportion of visited flowers (total, geitonogamous and exogamous) we used a β binomial distribution model with a logit-link function (using the aod package in R; Lesnoff and Lancelot, 2012). The models incorporated investment and variation as discrete predictors with the temperature at the time of the trial as a covariate. Interactions and main effects were analysed in all cases. We calculated the marginal means of the model based on the median value of the temperature covariate. To evaluate the impact of investment and variation on the two different estimates of the cost per visit, we conducted two independent GLMs with Gaussian distribution in R (R Core Team, 2020). The dependent variables were log-transformed for these models.

Because we filmed all visits received by the artificial plants, we were able to produce a detailed record of the number of visits received by each flower within every plant. These data enabled us to evaluate whether flowers with higher nectar richness within variable plants function as the primary attractant (magnet) to these plants (Thomson, 1978; Craig and Johnson, 2008). To examine this, we used a generalized linear mixed model with a Poisson distribution and log-link function using the lme4 package in R (Bates et al., 2015). The model included the number of visits per flower as the response variable, sugar concentration of each flower as a predictor, and plant as a random effect. To assess differences in the number of visits per flower by each nectar sugar concentration, we performed a post hoc Tukey test.

RESULTS

Visitation rate

Results from our experiments demonstrated significant effects of intra-individual variation, investment (high and low sugar concentration) and day (temperature) on visitation rate (z = 4.58, P < 0.0001; z = −2.05, P = 0.04; and z = −2.28, P = 0.02, respectively; Supplementary Data Table S1). Variable plants received 35–38 % more visits than invariable plants, while plants in the high-investment treatment received 13–18 % more visits than those in the low-investment treatment (Fig. 1A). The interaction term did not have a significant effect on visitation rate (Supplementary Data Table S1). To further examine the impact of experimental treatments on visitation rates, we analysed geitonogamous and exogamous visitation separately. In terms of geitonogamy, variable plants obtained nearly twice the number of geitonogamous visits compared with invariable plants (Fig. 1B). Likewise, we observed a higher frequency of geitonogamous visitation in the high-investment treatment compared with the low-investment treatment (Fig. 1B). Once again, we found significant effects of variation, investment and temperature on visitation rate, while the interaction term did not yield significant results (z = 4.32, P < 0.0001; z = −2.0, P = 0.045; z = −1.99, P = 0.047; and z = −0.441, P = 0.66, respectively; Supplementary Data Table S1). Analysis of the exogamous visitation rate revealed a significant effect of variation (z = 4.362, P < 0.0001), investment (z = 1.881, P = 0.06) and temperature (z = 1.881, P = 0.06), with no significant effect observed for the interaction term (Supplementary Data Table S1). Variable plants obtained 30–32 % more exogamous visits than invariable plants (Fig. 1C), while a 14–15 % increase in visits was observed in the high-investment treatment (Fig. 1C). Thus, variable plants enhanced the benefits of pollination without reducing geitonogamy.

Fig. 1.

Fig. 1.

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Effects of plant investment and nectar variation on (A) total visitation rate (mean ± standard error), (B) geitonogamous visitation rate (mean ± standard error) and (C) exogamous visitation rate (mean ± standard error) during 1 h of B. impatiens foraging. Blue symbols indicate visits to plants without nectar variation, while red symbols indicate visits to plants with nectar variation. Black asterisks represent post hoc significance between the nectar variation treatments, and grey asterisks represents post hoc significance between the investment treatments.

Proportion of visited flowers.

Our findings demonstrated that, regardless of the experimental treatment, a substantial proportion of the flowers received at least one visit (0.90 ± 0.014; Fig. 2A). GLM analyses further indicated that variable plants had a 4–5 % higher proportion of visited flowers compared with those in the invariable treatment (Fig. 2A, z = 2.77, P = 0.006; Supplementary Data Table S2). There were no significant effects of investment or the interaction term (z = −0.746, P = 0.453 and z = −0.410, P = 0.682, respectively; Supplementary Data Table S2).

Fig. 2.

Fig. 2.

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Effects of plant investment and nectar variation on (A) proportion of flowers visited (mean ± standard error) and (B and C) proportion of flowers with geitonogamous (mean ± standard error) and exogamous (outcross) visits, respectively (mean ± standard error). Blue symbols indicate visits to plants without nectar variation, while red symbols indicate visits to plants with nectar variation. Asterisks represent post hoc significance between the investment treatments.

In separate analyses of geitonogamous and exogamous visitation, we found that the average proportion of flowers receiving geitonogamous visitation was 0.71 (± 0.025), while for exogamous visitation it was 0.79 (± 0.019). Variable plants exhibited a 6–13 % higher proportion of visited flowers compared with those in the invariable treatment (Fig. 2B, C). Analysing the proportion of geitonogamous visitation, we showed a significant effect of variation (z = 3.182, P = 0.001), but no significant effects of investment (z = −1.411, P = 0.158) or the interaction term (z = 0.091, P = 0.927; Supplementary Data Table S2). Similarly, for the proportion of exogamous visitation, we found a significant effect of variation (z = 2.893, P = 0.004), but no significant effects of investment (z = 0.525, P = 0.599) or the interaction term (z = 0.860, P = 0.390; Supplementary Data Table S2).

Cost per visit.

When we assumed that plants cannot reabsorb nectar, we found that variation was the only significant treatment affecting the cost per visit (z = −4.699, P < 0.0001; Supplementary Data Table S3). Plants in the variable treatment paid less sugar per visit than in the invariable treatment, independently of the investment treatment (Fig. 3A). On the other hand, when we assumed plants were capable of reabsorbing nectar, we found that investment had a significant effect on the energetic cost per visit (z = −8.454, P < 0.0001). Plants in the high-investment treatment paid the highest cost per visit regardless of the variation treatment (Fig. 3B). As indicated by the significance of the interaction term (z = 3.356, P = 0.001; Supplementary Data Table S3), the invariable–low-investment treatment achieved the lowest cost per visit (Fig. 3B), followed by the variable–low-investment treatment (Fig. 3B).

Fig. 3.

Fig. 3.

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Cost per visit in plants without nectar reabsorption (A) (mean ± standard error) and with nectar reabsorption (B) (mean ± standard error). Asterisks represent post hoc significance between the investment treatment. Note that the values on the Y-axis differ between panels (A) and (B) because the energy cost per visit (mg/visit) increases under the assumption of no nectar reabsorption.

Effect of high-rewarding flowers on pollinator foraging

Consistent with our hypothesis that richer flowers function as magnets in variable plants, we observed that flowers with the highest sugar concentration in such plants received significantly more visits than flowers with lower sugar concentration, regardless of the total investment in nectar (Fig. 4). The results of the full models and post hoc Tukey tests can be found in Supplementary Data Table S4.

Fig. 4.

Fig. 4.

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Number of visits per flower (mean ± standard error) in plants with different sugar concentrations and with intra-plant nectar variation. (A) Low investment. (B) High investment. Different letters indicate significant differences between the groups (P < 0.05).

DISCUSSION

The results of this study provide support for the resource-saving hypothesis, which suggests that intra-individual variation in nectar production (concentration) enables plants to conserve resources while still receiving effective pollinator services (Feinsinger, 1978; Bell, 1986; Biernaskie et al., 2002; Pyke, 2016). Variable plants, which offer a diverse range of reward to pollinators, exhibited a significantly higher visitation rate compared with invariable plants, and this pattern held true when considering geitonogamy and exogamy separately. Not only did variable plants receive more visits per hour, but a larger proportion of their flowers were visited in terms of both total and geitonogamous visitation. Interestingly, the presence of intra-plant variation in nectar concentration resulted in an increase in geitonogamous visitation, rather than a decrease. Therefore, the findings of this study contradict the hypothesis that intra-individual variance in nectar concentration serves as a mechanism to avoid geitonogamy (Rathcke, 1992; de Jong et al., 1993; Biernaskie et al., 2002).

Our findings demonstrate that intra-individual variation in nectar concentration provides several advantages in terms of pollination visitation, including a higher number of visits per hour and a greater proportion of visited flowers, in terms of both overall and geitonogamous visitation. Bumblebees showed a preference for variable plants and highly rewarding flowers (those surpassing the population mean; Charnov, 1976), which acted as the primary attractants within variable plants. Estimations of the energetic cost per visit revealed that variable plants required fewer resources per visit when nectar reabsorption was not assumed. However, if we consider the ability of plants to reabsorb nectar, variable plants in the low-investment treatment rank as the second most cost-effective strategy, with the low-investment–invariable treatment being the most cost-effective. Overall, our results support the hypothesis that intra-individual variation in nectar concentration can effectively manipulate pollinator behaviour and represent a resource-saving strategy, depending on the plant’s ability to reabsorb nectar (Nepi and Stpiczyńska, 2008a, b; Heil, 2011; Nepi et al., 2011).

While our experimental approach provided precise control over the experimental conditions, such as levels of investment and intra-individual variance, and allowed us to investigate the foraging responses of bumblebees to different levels of investment and intra-individual variation in reward production, the use of artificial plants limited our ability to measure plant fitness-related variables such as pollen export-deposition and fruit and seed production. Although an ideal experiment would involve a real plant species and its natural pollinators, we chose this experimental approach due to the challenges associated with controlling the exact amount and concentration of nectar (Pacini and Nepi, 2007) and the limited generalizability of studying a single plant species. Controlling the amount and variation of nectar production in natural systems is hindered by environmental factors such as humidity, soil composition, temperature, light and CO2 concentration. Furthermore, variation in nectar production associated with factors like morph, sex, position or flower age, as well as interactions with pollinators and herbivores, further complicates the desired experimental design (reviewed by Renner, 2006; Parachnowitsch et al., 2019). The quantification of nectar is an invasive activity, so the simple action of measuring it modifies or destroys the essence of the phenomenon we want to study. Last, differences in mating system, habit, life cycle, size, flowering display and other factors have the potential to influence the effects of intra-individual variation on pollinator foraging and plant fitness. Given these limitations, our experimental setup explored a simplified and controlled scenario in which the pollinator foraging decisions depended solely on two variables: the cost of the interaction (investment) and the putative manipulation mechanism (intra-individual variation; Pyke, 2016) employed by the plants.

Results from this study support Pyke’s hypothesis (2016) that intra-individual variation in nectar crop can be interpreted as a mechanism for manipulating pollinators. Moreover, our experiments suggest that this manipulation allows plants to save resources, thereby reducing the cost of the interaction. It has been shown that, under conditions of limited resources, plants reduce reward production (Muñoz et al., 2005; Descamps et al., 2018; Phillips et al., 2018) in favour of other essential functions, such as growth, defence and maintenance (Bazzaz et al., 1987; Ashman, 1994; Obeso, 2002; Cepeda-Cornejo and Dirzo, 2010; Wenk and Falster, 2015). Hence, natural selection is expected to favour any strategy that enhances the benefit:cost ratio of the interaction (Noë and Hammerstein, 1995; Holland et al., 2004). Interestingly, analysis of total visitation revealed that more visits were observed in the high-investment treatment, indicating that pollinators detected the 11 % difference in sugar investment between the high and low treatments (representing the simulated amount of saved resources). Nonetheless, variable plants in the low and high nectar concentration (investment) treatments obtained similar pollinator visitation, suggesting that intra-individual variation compensated for the difference in investment. This result indicates that, even though the difference we used in these experiments is above the threshold detectable by pollinators (Chittka and Thomson, 2011), it may confer an advantage if the saved resources can be allocated to other essential functions (Pyke, 1991; Ordano and Ornelas, 2005; Whitehead et al., 2012; Nepi et al., 2018).

We highlight these results as an illustration of one of the key elements of the putative manipulation strategy: if plants are indeed exploiting pollinators through the provision of a variable reward, then savings should not exceed the threshold that elicits a negative response from pollinators.

Accordingly, we have shown that intra-individual variation in reward offering can confer an advantage in terms of pollination service. Variable plants in both the high- and low-investment treatments received more visits, had a greater proportion of visited flowers, and invested fewer resources per visit compared with invariable plants, assuming no nectar reabsorption. Our findings also suggest that nectar reabsorption serves as an efficient resource-saving mechanism (Nepi and Stpiczynska, 2008a, b), which, once in place, diminishes the benefits of intra-individual variation. In fact, when nectar reabsorption was assumed, the cost per visit was higher for variable plants.

Naturally, these observations call for mechanistic explanations. Why did variable plants receive more visits? Several studies have demonstrated that pollinators, such as flies, bees, bumblebees and hummingbirds, are capable of detecting and exhibit a preference for the more rewarding flowers within a plant (Feinsinger, 1978; Fischer and Leal, 2006; Jersáková and Johnson, 2006; Jersáková et al., 2008; Brandenburg et al., 2012; Zhao et al., 2016; Essenberg, 2021), suggesting that these flowers may function as supernormal stimuli (Kral, 2016). Most animals, including insect and vertebrate pollinators, tend to respond more strongly to stimuli associated with the highest relative rewards (Staddon, 1975; Castillo et al., 2012; Lea and Ryan, 2015). Highly rewarding flowers of variable plants represent above-average alternatives (Charnov, 1976) and are expected to be particularly attractive in resource-scarce environments (Kral, 2016). Our observations that the highly rewarding flowers of variable plants received significantly more visits support this interpretation.

On the other hand, an intriguing finding was that variable plants paid a higher cost per visit when nectar reabsorption was assumed. This result aligns with previous interpretations suggesting that nectar reabsorption, by recycling resources invested in nectar production, can be a resource-recovery strategy (Nepi and Stpiczynska, 2008a, b; Heil, 2011; Nepi et al., 2011). Although this finding could imply that nectar reabsorption nullifies the potential advantages of intra-individual variation in nectar production (concentration), it should be noted that variable plants, compared with invariable plants, had 58 % more visits but paid only 20 % more sugar. Thus, the lower cost paid by invariable plants comes at the expense of obtaining inferior pollinator service.

This study demonstrates that variable plants, depending on the assumptions made, achieve a suitable level of pollinator service at a lower net cost compared with invariable plants. This supports the notion that pollinators are manipulated because they receive fewer rewards when visiting variable–low-investment plants.

Using the observations on pollinator behaviour we tested the effect of within-plant variation in nectar production (concentration) on the occurrence of geitonogamy. Interestingly, our results did not support the hypotheses proposing that within-plant variation in reward production reduces geitonogamy incidence (Biernaskie et al., 2002; Smithson and Gigord, 2003; Bailey et al., 2007; Keasar et al., 2008; Nepi et al., 2018). Pollinators showed a preference for variable plants over invariable plants, resulting in higher levels of geitonogamous pollination. This outcome can be explained by our observation that pollinators favoured the richer flowers within variable plants. As these richer flowers were the most rewarding ones encountered by pollinators in the experiment, they likely required longer feeding times per flower (Essenberg, 2021) and misled pollinators about the average payoff of the plant they were foraging on (Biernaskie et al., 2009). These nectar-induced foraging behaviours may lead to increased foraging bouts and consequently geitonogamy. Thus, our results revealed that plants can manipulate pollinator behaviour, reducing the costs of the interaction, depending on the combination of the total reward investment and of intra-individual variation.

Although the findings of this study suggest that within-plant variation in nectar concentration may result in increased and more cost-effective visitation, it is reasonable to expect this phenomenon to be species-specific. Pollination, which involves the deposition of pollen on conspecific stigmas, is just one phase in the complex process of producing viable seeds (Jing et al., 2021). Factors such as mating system, the presence and nature of self-incompatibility, pollen competition, patterns of resource allocation, and non-random abortion play a crucial role in determining whether the observed visitation patterns confer a fitness advantage on plants. For example, plants in the variable treatment exhibited the highest rate of geitonogamy, in terms of both pollinator visitation and the proportion of visited flowers. Clearly, within-plant variation in nectar concentration would be advantageous only for self-incompatible plants or when the costs associated with inbreeding and/or pollen and ovule discounting were low (Lloyd, 1992; de Jong et al., 1993; Harder and Wilson, 1998; Barrett, 2003; Galloway et al., 2003; Smithson, 2006; Mitchell et al., 2009; Huang et al., 2020). Therefore, while the results of these experiments depict a simplified scenario, the specific consequences of intra-individual variation in reward production would depend on the biology of the studied species. For instance, studies have demonstrated that within-plant variability in nectar production (Biernaskie and Cartar, 2004) and geitonogamy (Lloyd, 1992; Harder and Barrett, 1995; Snow et al., 1996; Eckert, 2000; Lau et al., 2008; Karron and Mitchell, 2012), increase with the relative number of open flowers within a plant. Hence, species or plants with relatively small flowering displays are not expected to benefit from within-plant variability in nectar production. On the other hand, if geitonogamy is widespread among self-compatible plants with large flowering displays (de Jong et al., 1993; Harder and Barrett, 1995; Vaughton and Ramsey, 2010), mechanisms other than intra-individual variation in nectar production should compensate for the high levels of geitonogamy, or even benefit from this reproductive bias (e.g. Huang et al., 2020).

Overall, the results of this study provide support for Pyke’s hypothesis that intra-individual variance in nectar production (concentration) should be regarded as a pollinator manipulation mechanism, enabling plants to reduce the energetic costs associated with the interaction. Further research is needed to thoroughly investigate the role of within-plant variation in nectar quality/quantity in natural settings to gain a deeper understanding of this hypothesis.

SUPPLEMENTARY DATA

Supplementary data are available online at https://academic.oup.com/aob and consist of the following. Table S1: generalized linear model results of the effect of variation, investment and temperature on total visitation and geitonogamous and exogamous visitation rates. Table S2: generalized linear model results of the effect of variation, investment and temperature on the proportion of visited flowers and the proportion of geitonogamous and exogamous visitation. Table S3: linear model results of the effect of the cost per visit without and with reabsorption nectar by treatment variation, investment, their interaction and the temperature when the trial took place. Table S4: generalized linear mixed model results of visits to flowers in variable plants with different sugar concentration.

mcad082_suppl_Supplementary_Tables
Click here for additional data file. (311.4KB, docx)

ACKNOWLEDGEMENTS

Y. A. Bernal González assisted with experimental work. M. Strelin contributed to early discussions and statistical analyses of this work. This work was part of M.M.’s MSc thesis in the Posgrado en Ciencias Biológicas at Universidad Nacional Autónoma de México. Declarations of interests: None.

Contributor Information

Michelle Maldonado, Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México A.P. 70-275, 04510 Mexico City, Mexico.

Juan Fornoni, Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México A.P. 70-275, 04510 Mexico City, Mexico.

Karina Boege, Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México A.P. 70-275, 04510 Mexico City, Mexico.

Rubén Pérez Ishiwara, Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México A.P. 70-275, 04510 Mexico City, Mexico.

Rocío Santos-Gally, CONAHCYT-Instituto de Ecología, Departamento de Ecología Evolutiva, Universidad Nacional Autónoma de México A.P. 70-275, 04510 Mexico City, Mexico.

César A Domínguez, Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México A.P. 70-275, 04510 Mexico City, Mexico.

FUNDING

This work was supported by funding from the PAPIIT-UNAM (grant IN210617). M.M. was supported by a fellowship from Consejo Nacional de Humanidades, Ciencia y Tecnología (CONHACyT).

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