Free amino acids in nectar: its composition and variability among bat-pollinated plants

Aminoácidos libres en el néctar: composición y variabilidad en plantas polinizadas por murciélagos

In addition to sugars, proteins and free amino acids commonly occur in floral nectar of most plant species (Baker & Baker, 1975, 1977, 1982; Nicolson & Thornburg, 2007). Although free amino acids in nectar are known to influence the foraging behavior of pollinator guilds (Alm et al., 1990; Bluthgen & Fiedler, 2004; Hainsworth & Wolf, 1976; Ignell et al., 2010; Inouye & Waller, 1984; Rodríguez-Peña et al., 2013), it is unknown whether particular free amino acid types, constancy or variability in nectar confer advantages to the plant within the context of pollination ecology.

Several of the early studies within the field of nectar focused on describing sugars, amino acids, proteins, lipids and alkaloids among other metabolites, and their relation to plants’ principal pollinator and plant taxonomy (Baker, 1978; Baker & Baker, 1973a, b, 1975, 1977, 1982, 1983, 1986). These studies show that nectar protein and amino acid concentration are related to the plant´s principal pollinator and usually differ among species. For example, they show that while the presence of single amino acids is constant within plant species, the nectar of bird and bat-pollinated plant species, compared to plants preferred by other pollinator types, is usually characterized as low in protein and amino acid total content as both bats and birds have alternative sources of these nutrients in their diet (i.e., pollen, fruit, insects). Recent studies within the context of pollination ecology have characterized the nectar protein and free amino acid total content of plant species from several regions and pollinator guilds (Galetto & Bernardello, 2004; Gottsberger et al., 1984; Herrera, 1989; Petanidou et al., 2006). A few other studies have focused on describing the free amino acid profile in nectar (Dress et al., 1997; Goldberg 2009; Nepi et al., 2012; Nicolson & Thornburg, 2007; Piechowski et al., 2010; Scogin, 1986; Tiedge & Lohaus, 2017). 

The relative abundance of sugars and amino acid types is important for providing characteristic taste profiles (Baker, 1978; Gardener & Gillman, 2002; Nepi, 2014; Nicolson & Thornburg, 2007), and it is well known that particular amino acid flavors in nectar solution vary with its concentration (Birch & Kemp, 1989). The influence of amino acids on nectar taste is widely documented for insect-pollinated plants where particular mixes and types of free amino acids and non-proteic amino acids (Carter et al., 2006; Lanza & Krauss, 1984; Nepi et al., 2012; Petanidou, 2007; Petanidou et al., 2006, Potter & Bertin, 1988) have been characterized as phagostimulants (Gardener & Gillman, 2002; Hansen et al., 1998; Shiraishi & Kuwabara, 1970; Teulier et al., 2016). However, this is not well documented for plants pollinated by other guilds. In the case of bat-pollination interactions, nectarivore bats have the capacity to differentiate and to show preferences between the 3 sugars that commonly occur in nectar, regardless of their concentration (Ayala-Berdon et al., 2013); however, they do not exhibit preferences for sugars found in the nectar of flowers they usually consume (Herrera, 1999; Rodríguez-Peña et al., 2016). Further, when the role of nitrogen and the relative abundance of free amino acids were tested, bats showed a preference for the most concentrated sugar-only nectar but were indifferent when nectar contained nitrogen (Rodríguez-Peña et al., 2013). In fact, nectarivore bats were capable of discriminating the nectar flavor of a particular plant species provided by its free amino acid relative abundance, when compared with that found in the nectar of other species. This suggests that plants might manipulate the relative abundance of their free amino acids in nectar influencing the foraging decisions of their pollinators. 

To date, only a few studies have analyzed the occurrence and relative abundance of some amino acids in nectar from a few bat-pollinated plant species (Goldberg, 2009; Gottlinger et al., 2019; Piechowski et al., 2010; Scogin, 1986). However, these studies mainly focused on identifying the occurrence of a few types of amino acids and documenting which of these have the highest concentration. The variation of amino acids in nectar from bat-pollinated species has yet to be determined. Identifying if particular amino acids vary among bat-pollinated plant species within a plant community will contribute to a better understanding of their significance in the context of pollination ecology. The overall goal of this study was to document the occurrence of 17 free amino acids in nectar and assess whether they differ among 8 bat-pollinated plant species from 5 families in a Tropical Dry Forest in Mexico. We focused on the following questions: i) do the same types of free amino acids occur in the nectar of bat-pollinated plant species? and ii) which free amino acid types differ in concentration among bat-pollinated plant species? Finally, we discuss the implications of our results in the context of bat pollination ecology.

Study site and plant species

Field collections were made at the Chamela-Cuixmala Biosphere Reserve on the central Pacific coast of Mexico (ca. 19º22’ – 19º35’ N, 104º56’ – 105º03’ W). The predominant vegetation type is tropical lowland deciduous forest with patches of riparian forest (Lott 1993). 

Nectar collection

We sampled the 8 most common plant species in the study area and well documented for their importance to the diet of nectarivorous bats in this region: Crescentia alata (Bignoniaceae; n = 5); Pachycereus pecten (Cactaceae; n = 2); Ipomoea ampullacea (Convolvulaceae; n = 4); Bahuinia pauletia (Fabaceae; n = 5); Ceiba aesculifolia (n = 5), Ceiba grandiflora (n = 4), Ceiba pentandra (n = 5) and Pseudobombax ellipticum (Malvaceae; n = 5) (Herrera et al., 2001; Sánchez-Casas & Álvarez, 2000; Stoner et al., 2003). Sample collection was carried out opportunistically, following the flowering season of each plant species throughout a year period. In brief, one mature flower bud from different individuals of each species, were covered with mesh bags 1 h before sunset. Bags were removed 1 h after anthesis, and nectar was extracted with capillary glass tubes. In order to avoid possible nectar contamination with pollen grains amino acid content, particular care was taken to carefully remove stigma to one side of the flower, due to the capillary tube manipulation, until reaching the nectary. Nectar samples were immediately stored in eppendorf tubes at -80 ºC until analysis. 

Nectar amino acid quantification

High Performance Liquid Chromatography (HPLC) was used to measure concentrations of 17 free amino acids: aspartic acid (Asp), glutamic acid (Glu), serine (Ser), histidine (His), glycine (Gly), threonine (Thr), arginine (Arg), alanine (Ala), tyrosine (Tyr) cysteine (Cys), valine (Val), methionine (Met), phenylalanine (Phe), isoleucine (Ile), leucine (Leu), lysine (Lys) and proline (Pro). Analyses were performed in an Agilent 1100 Series (Hewlett Packard), following the Agilent 1090 series method, by using a two-step precolumn derivatization, with ortho-phthalaldehyde (OPA) for primary amino acids and 9-fluorenylmethyl chloroformate (FMOC) for the secondary amines as previously published for C. aesculifolia (Malvaceae) and Pachycereus pecten (Cactaceae; Rodríguez-Peña et al., 2013). In brief, a 0.4 N borate buffer was used with pH 10.4. Separation was performed by using a Hypersil AA – ODS2.1 x 200 mm Agilent column. We used a solvent gradient system with 2 mobile phases. The first mobile phase (A) consisted of sodium acetate, trietilamine and tetrahydrofuran water mix, and the second mobile phase (B) consisted of sodium acetate, acetonitrile and methanol water mix buffers (pH 7.20). The gradient started with 100% A, at 17 minutes 60% B, at 18.1 minutes flow 0.45, at 18.5 minutes flow 0.8, at 23.9 minutes flow 0.8, at 24 minutes 100% B and flow 0.45, at 25 minutes 0% B. Detection was via a Perkin Elmer (LS50B) Luminescence Spectrometer (excitation at 340 nm and emission at 450 nm for primary amino acids and excitation at 266 nm and emission at 305 nm for secondary amino acids). Data collection was done by FL Win Lab Perkin Elmer software. Chromatograms were compared with authentic standards of individual amino acids with known concentrations for identification and quantification. Total concentration and percentage of each amino acid was calculated for each sample.

Data analysis

We used Kruskall-Wallis to analyze whether differences exist in the relative abundance of the 17 amino acids among the 8 plant species. We used eta-squared (η²) as measure of effect size, in which, scales of magnitude indicate a small effect (0.01 ≤ 0.06); moderate effect (0.06 ≤ 0.14); and a large effect ( 0.14). Further, η² values multiplied by 100 indicate the percentage (%) of variance in the dependent variable (amino acid type) which is explained by the independent variable (plant species; Snyder & Lawson, 1993), meaning that the larger the effect size is, the stronger the relationship between the 2 variables (Cohen, 1988; Lalongo, 2016; Tomczak & Tomczak, 2014). To find which pairs of groups differ significantly we used Dunn´s post-hoc tests. Analyses were performed in Statistica ® Version 7 and SPSS ® Version 20 (IBM, 2011).

Nectar free amino acids among bat-pollinated plant species

All 17 free amino acids were found in the nectar of the 8 plant species (Table 1). Kruskall-Wallis test showed significant differences in the concentration of Asp (H = 23.7; p = 0.001), Glu (H = 20.8; p = 0.004), Ser (H = 15.1; p = 0.035), Gly (H = 14.6; p = 0.041), and Cys (H = 19.9; p = 0.006), among all 8 of the bat-pollinated plants (Table 2). 

When calculated η² values for Thr, Arg and Ile, a small size effect was found (0.01 ≤ 0.06); while for Asp, Glu, Ser, His, Gly, Tyr, Cys, Val, Met, Phe, Lys and Pro the obtained size effect was large (≥ 0.14); showing that in the case of these last twelve amino acids, plant species explained its concentration by up to 19 to 58% depending on the amino acid type. No effect size was detected for Ala and Leu (Table 3). 

Finally, significant differences were found for Asp concentration between Ceiba grandiflora (Malvaceae) when compared with both, Bahuinia pauletia (Fabaceae; p = 0.005) and Ceiba aesculifolia (Malvaceae; p = 0.038); and for Glu concentration when compared to Ipomoea ampullacea (Convolvulaceae; p = 0.009). No significant differences were found among other plant species and amino acid types. 

Free amino acid total concentration in nectar has been found to greatly vary among plant species (Baker & Baker, 1977; Galetto & Bernardello, 2004; Gardener & Gilman, 2001; Gottsberger et al., 1984; Scogin, 1986). However, due to the low concentration of free amino acids in the nectar of bat-pollinated flowers, it has been less studied in the past compared to flowers pollinated by other animals. This study provides the first attempt to identify differences in particular free amino acids in nectar among bat-pollinated plants collected in a uniform way within one study site. In this section, we discuss the ecological implications of our findings. 

Table 1

Free nectar amino acids presence for 8 species and 5 families of bat-pollinated plants in a Tropical Dry Forest in Mexico.

Amino acid	Bignoniaceae	Cactaceae	Convolvulaceae	Fabaceae	Malvaceae
	C. alata	P. pecten	I. ampullacea	B. pauletia	C. aesculifolia	C. grandiflora	C. pentandra	P. ellipticum
Asp	5/5	2/2	4/4	5/5	5/5	4/4	5/5	5/5
Glu	5/5	2/2	4/4	5/5	5/5	4/4	5/5	5/5
Ser	4/5	2/2	3/4	5/5	5/5	4/4	5/5	4/5
His	5/5	2/2	2/4	4/5	5/5	4/4	5/5	5/5
Gly	5/5	2/2	4/4	5/5	5/5	4/4	5/5	5/5
Thr	5/5	2/2	4/4	5/5	5/5	4/4	5/5	5/5
Ala	5/5	2/2	4/4	4/5	4/5	4/4	5/5	5/5
Arg	5/5	2/2	4/4	4/5	5/5	4/4	5/5	5/5
Tyr	5/5	2/2	4/4	5/5	5/5	4/4	5/5	5/5
Cys	5/5	2/2	4/4	5/5	5/5	4/4	5/5	5/5
Val	5/5	2/2	3/4	5/5	4/5	4/4	5/5	5/5
Met	5/5	2/2	4/4	5/5	4/5	4/4	5/5	5/5
Phe	5/5	2/2	4/4	5/5	4/5	3/4	5/5	5/5
Ile	4/5	2/2	4/4	5/5	5/5	4/4	5/5	5/5
Leu	5/5	2/2	4/4	5/5	5/5	4/4	5/5	5/5
Lys	5/5	2/2	4/4	5/5	5/5	4/4	5/5	5/5
Pro	5/5	2/2	4/4	5/5	5/5	4/4	5/5	5/5

Numbers in parentheses indicate (particular amino acid occurrence / n = sampled flowers) for each plant species. For all plant species, n = 5, except P. pecten (n = 2), and C. grandiflora and I. ampullaceae (n = 4).

Table 2

Free nectar amino acid concentration (µg/ml) for 8 species and 5 families of bat-pollinated plants in a Tropical Dry Forest in Mexico.

Amino acid	Bignoniaceae	Cactaceae	Convolvulaceae	Fabaceae	Malvaceae
	C. alata	P. pecten	I. ampullacea	B. pauletia	C. aesculifolia	C. grandiflora	C. pentandra	P. ellipticum
	mean±SD	mean±SD	mean±SD	mean±SD	mean±SD	mean±SD	mean±SD	mean±SD
Asp	11.75±6.09	33.69±0.46	3.99±2.36	2.71±2.16	5.18±5.09	38.75±5.96	6.17±1.99	6.48±2.09
Glu	17.46±9.13	34.56±6.02	2.85±1.14	5.66±4.05	7.41±7.57	37.43±7.55	6.87±1.55	5.84±3.13
Ser	11.95±23.79	29.70±26.07	1.04±1.16	4.35±2.78	20.02±13.73	15.66±4.52	4.73±3.61	12.97±24.69
His	28.87±19.54	54.54±7.62	12.99±21.25	8.72±13.97	17.95±21.11	10.69±6.32	2.91±1.21	8.76±5.49
Gly	5.59±4.84	19.675.92	10.88±9.20	36.44±33.74	2.41±1.79	17.46±2.19	2.83±2.95	4.87±2.73
Thr	4.31±2.32	3.42±0.66	6.49±3.46	5.84±5.75	6.72±7.36	2.23±1.21	3.21±4.51	2.90±2.87
Ala	5.19±6.67	1.19±0.04	1.34±1.63	1.92±2.22	1.54±1.86	1.07±0.06	1.88±1.05	6.36±10.58
Arg	11.78±6.66	10.86±7.88	10.47±15.10	11.61±10.35	9.68±15.23	5.79±0.56	2.31±1.37	12.72±20.52
Tyr	2.03±1.75	15.29±14.47	4.68±3.92	1.65±1.49	0.40±0.26	0.23±0.10	1.62±1.73	1.44±0.59
Cys	3.23±2.03	1.32±0.82	5.96±4.20	4.79±4.90	0.36±0.35	0.83±0.07	0.33±0.25	1.09±0.69
Val	0.81±0.54	12.95±5.65	5.68±8.31	2.74±3.53	5.76±6.72	17.28±3.80	1.22±0.68	1.47±1.42
Met	1.11±1.28	5.53±3.39	0.75±0.32	5.17±5.42	1.82±1.71	1.95±0.26	2.90±2.95	0.83±0.62
Phe	6.20±6.39	0.89±0.46	0.78±0.52	2.461.79	1.04±0.75	0.16±0.11	1.20±1.24	0.78±0.17
Ile	7.95±4.77	12.59±5.69	9.05±2.40	8.65±3.81	10.63±4.91	9.54±0.33	12.55±5.65	5.23±4.69
Leu	14.44±17.10	23.44±1.39	51.35±52.88	20.32±24.07	18.10±8.91	3.21±2.79	9.64±5.13	22.35±24.24
Lys	14.65±5.42	32.46±1.25	35.29±22.78	30.63±11.11	27.52±21.79	24.05±4.71	23.33±3.36	170.05±208.67
Pro	7.44±2.70	32.08±29.14	8.69±9.28	8.66±3.25	23.68±32.76	2.34±1.28	18.40±16.27	2.52±1.48

For all plant species n = 5, except P. pecten (n = 2), and C. grandiflora and I. ampullaceae (n = 4).

Are the same types of free amino acids present in the nectar of all bat-pollinated plant species?

The presence of the 17 quantified free amino acid types in this study was found in all analyzed bat-pollinated plant species. This concurs with Baker and Baker (1977, 1986), who found that the occurrence of individual amino acids in floral nectar is generally constant within a species, and accordingly to Tiedge and Lohaus (2017). Our results clearly showed that most free amino acid types occur in floral nectars of bat-pollinated plants, although they occur in variable concentrations. In contrast with our findings, several other studies have reported fewer amino acids in bat-pollinated species. For example, Scogin (1986) only found 5 amino acids (Ala, Ser, His, Thr and Gly) in the nectar of Cheirosemon platanoides (Sterculiaceae) and Kigelia pinnata (Bignoniaceae). Similarly, Goldberg (2009) only found cysteine (Cys) in all nectar samples of Helicteres baruensis (Sterculiaceae) even though their study evaluated the same 17 free amino acids found in our study. In the bat-pollinated Parkia pendula (Fabaceae), Piechowski et al. (2010) documented 5 of 14 amino acids analyzed and only found proline (Pro) and one other unidentified amino acid in all 5 samples. 

Results also showed that within the same species, not all amino acid types were present in all flowers. Nectar amino acids differences have been explained due that nectar composition reflects the amino acid composition of the phloem and nectaries owing to amino acids are leaching from nectaries (Nicolson & Thornburg, 2007). Also, carbon and nitrogen content in soil have been found to be related to nectar amino acids composition (Gijbels et al., 2014). 

Which free amino acid types discriminate among bat-pollinated plant species?

Our results showed that particular amino acid concentrations were different among Ceiba grandiflora (Malvaceae) with Bahuinia pauletia and Ceiba aesculifolia and with Ipomoea ampullacea for Asp and Glu, respectively. It is well recognized that plants can regulate the feeding behavior of animals via manipulating nectar metabolites such as sugars and free amino acids (Borghi & Ferni, 2017; Shoonhoven et al., 2005). While sugars constitute the energy content in nectar, free amino acids provide the discriminant taste and act as stimulators and contributors to the overall nectar palatability (Brito, 2011; Gardener & Gillman, 2002; Petanidou et al., 2006). Moreover, a positive relationship has been recognized between a particular amino acid taste in nectar and its concentration (Birch & Kemp, 1989). In the case of bats, only one study has evaluated the potential phagostimulant effect of amino acids and experimentally demonstrated that the flavor provided by the relative abundance of amino acids in nectar can be perceived and preferred by bats and influence their foraging decisions (Rodríguez-Peña et al., 2013). 

Although free amino acid types were present in nectar from all bat-pollinated studied species, differences on amino acid concentrations were only found in 2 out of 17 amino acids types and among few plant species. Future studies should focus on the study of nectar amino acids ecology within a phylogenetical framework.

Table 3

Nectar amino acids statistics by Kruskall-Wallis test and η² (%) for 8 species and 5 families of bat – pollinated plants in a Tropical Dry Forest in Mexico. Significant values (p < 0.05) are presented in bold.

Amino acid type	H	p-value	η2 %
Asp	23.69	0.0013	58.1
Glu	20.82	0.0041	51.2
Ser	15.08	0.0350	29.9
His	12.86	0.0756	21.7
Gly	14.61	0.0413	28.2
Thr	8.21	0.3140	4.5
Ala	3.21	0.8651	0
Arg	7.91	0.341	3.4
Tyr	13.76	0.0555	25
Cys	19.91	0.0058	47.8
Val	12.39	0.0885	19.9
Met	12.82	0.0765	21.6
Phe	13.12	0.0691	22.7
Ile	7.57	0.3715	2.1
Leu	5.19	0.6363	0
Lys	12.79	0.0775	21.4
Pro	13.12	0.0691	22.9

Eta-squared (η²) values are presented as percentages (%), indicating the variance in the dependent variable (amino acid type) explained by the independent variable (plant species).

 

Acknowledgements

We thank J. Vázquez for help in the laboratory, and the Estación de Biología Chamela for logistical support. This work was supported by a grant from the Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica PAPIIT (IN226007) to KES; and from Conacyt (293893) to Laboratorio Nacional en Salud, FES – Iztacala to CMF-O. 

References

Alm, J., Ohnmeiss, T. E., Lanza, J., & Vriesenga, L. (1990). Preference of cabbage white butterflies and honeybees for nectar that contains amino acids. Oecology, 84, 53–57. https://doi.org/10.1007/BF00665594 

Ayala-Berdon, J., Rodriguez-Peña, N., García, L. C., Stoner, K. E., & Schondube, J. E. (2013). Sugar gustatory thresholds and sugar selection in two species of Neotropical nectar-eating bats. Comparative Biochemistry and Physiology A Molecular Integrative and Physiology, 164, 307–313. https://doi.org/10.1016/j.cbpa.2012.10.019 

Baker, H. G. (1978). Chemical aspects of the pollination biology of woody plants in the tropics. In P. B. Tomlinson, & M. H. Zimmerman (Eds.), Tropical trees as living systems (pp. 57–82). Cambridge: Cambridge University.

Baker, H. G., & Baker, I. (1973a). Amino acids in nectar and their evolutionary significance. Nature, 241, 543–545. https://doi.org/10.1038/241543b0

Baker, H. G., & Baker, I. (1973b). Some anthecological aspects of the evolution of nectar-producing flowers, particularly amino acid production in nectar. In V. H. Heywood (Ed.), Taxonomy and ecology (pp. 243-264). London, New York: Academic Press. 

Baker, H. G., & Baker I. (1975). Studies of nectar constitution and pollinator-plant coevolution. In L. E. Gilbert & P. H. Raven (Ed.), Coevolution of animals and plants (pp. 100–140). Austin, London: University of Texas Press. 

Baker, H. G., & Baker, I. (1977). Intraspecific constancy of floral nectar amino acid complements. Botanical Gazette, 138, 183–191. 

Baker, H. G., & Baker, I. (1982). Chemical constituents of nectar in relation to pollination mechanisms and phylogeny. In M. H. Nitecki (Ed.), Biochemical aspects of evolutionary biology. Proceedings of the 4th Annual Spring Systematics Symposium (pp. 131–172). Chicago.

Baker, H. G., & Baker, I. (1983). A brief historical review of the chemistry of floral nectar. In B. Bentley, & T. Elias (Ed.), The biology of nectaries (pp. 126–152). New York: Columbia University.

Baker, H. G., & Baker, I. (1986). The occurrence and significance of amino acids in floral nectar. Plant Systematics and Evolution, 151, 175–186. https://doi.org/10.1007/BF02430273

Birch, G. G., & Kemp, S. E. (1989). Apparent specific volumes and tastes of amino acids. Chemical Senses, 14, 249–258. https://doi.org/10.1093/chemse/14.2.249

Bluthgen, N., & Fiedler, K. (2004), Preferences for sugars and amino acids and their conditionality in a diverse nectar-feeding ant community. Journal of Animal Ecology, 73, 155–166. https://doi.org/10.1111/j.1365-2656.2004.00789.x

Borghi, M., & Fernie, A. R. (2017). Floral metabolism of sugars and amino acids: implications for pollinators preferences and seed and fruit set. Plant Physiology, 175, 1510–1524. https://doi.org/10.1104/pp.17.01164 

Brito, S. M. G. (2011). Taste perception in honeybees. Chemical Senses, 36, 675–692. https://doi.org/10.1093/chemse/bjr040

Carter, C., Shafir, S., Yehonatan, L., Palmer, R. G., & Thornburg, R. (2006). A novel role for proline in plant floral nectars. Naturwissenschaften, 93, 72–79. https://doi.org/10.1007/s00114-005-0062-1

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, N. J.: Lawrence Erlbaum Associates.

Dress, W. J., Newell, S., Nastase, A., & Ford, J. (1997). Analysis of amino acids in nectar from pitchers of Sarracenia purpurea (Sarraceniaceae). American Journal of Botany, 84, 1701–1706. 

Galetto, L., & Bernardello, G. (2004). Floral Nectaries, nectar production dynamics and chemical composition in six Ipomoea species (Convolvulaceae) in relation to pollinators. Annals of Botany (London), 94, 269–280. https://doi.org/10.1093/aob/mch137

Gardener, M. C., & Gillman, M. P. (2001). Analyzing variability in nectar amino acids: composition is less variable than concentration. Journal of Chemical Ecology, 27, 2545–2558. https://doi.org/10.1023/a:1013687701120  

Gardener, M. C., & Gillman, M. P. (2002). The taste of nectar, a neglected area of pollination ecology. Oikos, 98, 552–557. https://doi.org/10.1034/j.1600-0706.2002.980322.x

Gijbels P., Van den Ende, W., & Honnay, O. (2014). Landscape sacale variation in nectar amino acid and sugar composition in a Lepidoptera pollinated orchid species and its relation with fruit set. Journal of Ecology, 102, 136–144. https://doi.org/10.1111/1365-2745.12183

Goldberg, L. (2009). Patterns of nectar production composition and morphology of floral nectaries in Helicteres guzumifolia and Helicteres baruensis (Sterculiaceae): two sympatric species from the Costa Rican tropical dry forest. Revista de Biología Tropical, 57, 161–177.

Gottlinger, T., Schwerdtfeger, M., Tiedge, K., & Lohaus, G. (2019). What do nectarivorous bats like? Nectar composition in Bromeliaceae with special emphasis on bat-pollinated species. Frontiers in Plant Science, 10, 1–17. https://doi.org/10.3389/fpls.2019.00205

Gottsberger, G., Schrauwen, J., & Linskens, H. F. (1984). Amino acids and sugars in nectar, and their putative evolutionary significance. Plant Systematics and Evolution, 145, 55–77. https://doi.org/10.1007/BF00984031

Hainsworth, F. R., & Wolf, L. L. (1976). Nectar characteristics and food selection by hummingbirds. Oecologia, 25, 101–113. https://doi.org/10.1007/BF00368847 

Hansen, K., Wacht, S., Seebauer, H., & Schnuch, M. (1998). New aspects of chemoreception in flies. Annals of the New York Academy of Sciences, 30, 143–147. https://doi.org/
10.1111/j.1749-6632.1998.tb10556.x 

Herrera, J. (1989). Aminoácidos en el néctar de plantas del sur de España. Anales del Jardín Botanico de Madrid, 45, 475–482.

Herrera, M., L. G. (1999). Preferences for different sugars in neotropical nectarivorous and frugivorous bats. Journal of Mammalogy, 80, 683–688. https://doi.org/10.2307/1383312

Herrera, M., L. G., Keith, A. H., Mirón, M. L., Ramírez, P. N., Méndez, C. G., & Sánchez-Cordero, V. (2001). Sources of protein in two species of phytophagous bats in a seasonal dry forest: evidence from stable-isotope analysis. Journal of Mammalogy, 82, 352–361. https://doi.org/10.1644/1545-1542(2001)082<0352:SOPITS>2.0.CO;2

IBM Corp. (2011). IBM SPSS Statistics for Windows, Version 20.0. Armonk, NY: IBM Corp.

Ignell, R., Okawa, S., Englund, J., & Hill, S. R. (2010). Assessment of diet choice by the yellow fever mosquito Aedes aegypti. Physiological Entomology, 35, 274–286. https://doi.org/10.1111/j.1365-3032.2010.00740.x 

Inouye, D. W., & Waller, G. D. (1984). Responses of honey bees (Apis mellifera) to amino acid solutions mimicking floral nectars. Ecology, 65, 618–625. 

Lalongo, C. (2016). Understanding the effect size and its measures. Biochemia Medica, 26, 150–163. https://doi.org/10.11613/BM.2016.015 

Lanza, J., & Krauss, B. R. (1984). Detection of amino acids in artificial nectars by two tropical ants, Leptothorax and Monomorium. Oecologia, 63, 423–425. https://doi.org/10.1007/BF00390676 

Lott, E. J. (1993). Annotated checklist of the vascular flora of the Chamela Bay region Jalisco, Mexico. Occasional papers of the California Academy of Sciences, 148, 1–60.

Nepi, M., Soligo, C., Nocentini, D., Abate, M., Guarnieri, M., Cai, G., Bini, L., Puglia, M., Bianchi, L., & Pacini, E. (2012). Amino acids and protein profile in floral nectar: Much more than a simple reward. Flora, 207, 475–481. https://doi.org/10.1016/j.flora.2012.06.002

Nepi, M. (2014). Beyond nectar sweeteness: the hidden ecological role of non-protein amino acids in nectar. Journal of Ecology, 102, 108–115. https://doi.org/10.1111/1365-2745.12170

Nicolson, S. W., & Thornburg, R. W. (2007). Nectar chemistry. In S. W. Nicolson, M. Nepi, & E. Pacini (Eds.), Nectaries and nectar (pp. 215–263). Dordrecht: Springer.

Petanidou, T. (2007). Ecological and evolutionary aspects of floral nectars in Mediterranean habitats. In S. W. Nicolson, M. Nepi., & E. Pacini (Eds.), Nectaries and nectar (pp. 347–379). Dordrecht: Springer.

Petanidou, T., Van Laere, A., Ellis, W. N., & Smets, E. (2006). What shapes amino acid and sugar composition in Mediterranean floral nectars? Oikos, 115, 155–169. https://doi.org/10.1111/j.2006.0030-1299.14487.x

Piechowski, D., Dotterl, S., & Gottsberger, G. (2010). Pollination biology and floral scent chemistry of the neotropical chiropterophilus Parkia pendula. Plant Biology, 12, 172–182. https://doi.org/10.1111/j.1438-8677.2009.00215.x  

Potter, C. F., & Bertin, R. I. (1988). Amino acids in artificial nectar: feeding preferences of the flesh fly Sarcophaga bullata. American Midland Naturalist, 120, 156–162. https://doi.org/10.2307/2425896 

Rodríguez-Peña, N., Stoner, K. E., Ayala-Berdon, J., Flores-Ortiz, C. M., Duran, A., & Schondube, J. E. (2013). Nitrogen and amino acids in nectar modify food selection of nectarivorous bats. Journal of Animal Ecology, 82, 1106–1115. https://doi.org/10.1111/1365-2656.12069 

Rodríguez-Peña, N., Stoner, K. E., Flores-Ortiz, C. M., Ayala-Berdón, J., Munguía-Rosas, M. A., Sánchez-Cordero, V., & Schondube, J. E. (2016). Factors affecting nectar sugar composition in chiropterophilic plants. Revista Mexicana de Biodiversidad, 87, 465–473. https://doi.org/10.1016/j.rmb.2016.03.002

Sánchez-Casas, N., & Álvarez, T. (2000). Palinofagia de los murciélagos del género Glossophaga (Mammalia: Chiroptera) en México. Acta Zoológica Mexicana, 81, 23–62. https://doi.org/10.21829/azm.2000.81811870

Scogin, R. (1986). Reproductive phytochemistry of Bombacaceae: floral anthocyanins and nectar constituents. ALISO, 11, 377–385.

Shiraishi, A., & Kuwabara, M. (1970). The effects of amino acids on the labellar hair chemosensory cells of the fly. Journal of General Physiology, 56, 768–782. https://doi.org/10.1085/jgp.56.6.768

Shoonhoven, L. M., van Loon, J. A., & Dicke, M. (2005). Insect-plant biology. Oxford: Oxford University Press. 

Snyder, P., & Lawson, S. (1993). Evaluating results using corrected and uncorrected effect size estimates. The Journal of Experimental Education, 61, 334–349. 

Stoner, K. E., Salazar, K. A. O., Fernández, R. C. R., & Quesada, M. (2003). Population dynamics, reproduction, and diet of the lesser long-nosed bat (Leptonycteris curasoae) in Jalisco, Mexico: implications for conservation. Biodiversity and Conservation, 12, 357–373. https://doi.org/10.1023/A:1021963819751

Teulier, L., Weber, J. M., Crevier, J., & Darveau, C. A. (2016). Proline as a fuel for insect flight: enhancing carbohydrate oxidation in hymenopterans. Proceedings of the Royal Society B: Biological Sciences, 283, 20160333. https://doi.org/10.1098/rspb.2016.0333

Tiedge, K., & Lohaus, G. (2017). Nectar sugars and amino acids in day- and night- flowering Nicotiana species are more strongly shaped by pollinators´preferences than organic acids and inorganic ions. Plos One, 12, 2–25. https://doi.org/10.1371/journal.pone.0176865 

Tomczak, M., & Tomczak, E. (2014). The need to report effect size estimates revisited. An overview of some recommended measures of effect size. Trends in Sport Sciences, 1, 19–25.