and mechanisms of temporal resource partitioning among bee species visiting basil Ocimum basilicum...

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O RI G I N A L P A P E R

Patterns and mechanisms of temporal resource partitioningamong bee species visiting basil (Ocimum basilicum) flowers

Juliana M. Muniz Ana Lucia C. Pereira

Janete O. S. Valim Wellington G. Campos

Received: 18 December 2012 / Accepted: 25 June 2013 / Published online: 26 July 2013

Springer Science+Business Media Dordrecht 2013

Abstract The way in which flower visitors share floral

resources or compete for them throughout the day is adecisive factor for the effectiveness of pollination. We

described daily rhythms of flower visitation by bee species

and tested whether such patterns depend on: (1) the body

size of the species, (2) the daily patterns of variation in

weather and nectar standing crop, and (3) the effects of

weather on the daily rhythm of variation in nectar standing

crop. After 1 year of biweekly samplings, we encountered

56 bee species visiting basil flowers. Larger bee species

were more active in the cooler and more humid hours of the

morning. Smaller species foraged later, during the warmer

and drier hours. Throughout the day, nectar volume

decreased. In the laboratory, we determined a positive

effect of increase in temperature on nectar volume, unlike

the negative correlation recorded in the field. Nectar vol-

ume decreased in plants under experimental drought,

showing similarity with the driest hours of the day. The

daily cycle of temperature is the fundamental factor that,

directly and indirectly, via air humidity, soil moisture, and

nectar supply, influences bee activity according to body

size and physiological attributes. In the field, the positive

effect of increasing temperatures on nectar volume is

masked by a stronger, negative effect of decreasing air

humidity and soil moisture throughout the day.

Keywords Temperature Humidity Body size

Nectar standing crop Daily rhythms

Introduction

Bees are the most important pollinators in nature and are

highly adapted to flower visitation (Kevan and Baker

1983). In Brazil alone, there are an estimated 3,000 species,

most of them stingless native species, which are funda-

mental to the pollination process (Silveira et al. 2002).

Flower visitation is rewarded by the offer of nectar, pollen,

fragrances, and other floral resources that are used by both

adult bees and their larvae (Waser et al. 1996; Kevan and

Baker1998). Some species also use the flowers as breeding

sites and resting places (Pedro and Camargo1991).

Nectar is the principal floral attractive trait, and its main

characteristics are volume, concentration, content of sug-

ars, color, odor, and flavor (Nepi et al. 2003; Irwin et al.

2004). Nectar basically consists of a solution of water and

sugars, predominantly sucrose, fructose, and glucose

(Nicolson and Thornburg 2007; Vassilyev 2010). Other

constituents available in smaller quantities include inor-

ganic ions, lipids, amino acids, low-molecular weight

proteins, enzymes, antioxidants, and secondary compounds

as phenolics, alkaloids, and terpenoids (Baker 1997, Ni-

colson and Thornburg 2007). However, sugar is probably

the most important factor influencing insect visitation

patterns (Gottsberger et al. 1984). Besides the chemical

composition of the nectar and the density of plants and

flowers (Duffy and Stout 2008), variations in nectar

standing crop (the quantity of nectar in a flower at a given

time) and secretion rate (nectar increase over a known

period of time) (Corbet 2003) also affect flower visitation

(Castellanos et al. 2002, Keasar et al. 2008).

Handling editor: Steven Johnson

J. M. Muniz A. L. C. Pereira J. O. S. Valim

W. G. Campos (&)

Department of Biosystems Engineering, Federal University

of Sao Joao del Rei, Sao Joao del Rei, MG 36.301-160, Brazil

e-mail: [email protected]

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Arthropod-Plant Interactions (2013) 7:491502

DOI 10.1007/s11829-013-9271-2


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Temporal and spatial dynamics in standing crop or

secretion rate of floral nectar primarily relate to changes in

volume and sugar concentration. Since the sugars consti-

tute virtually all the dry weight of nectar, the solute con-

centration is a reliable estimate of the concentration of total

sugars (Roubik 1992). Volume, sugar concentration, and

sugar content of nectar depend on the size, shape, position,

and age of a flower, but external factors, such as abioticfactors and the frequency of foraging visits, are also of

great importance (Corbet 2003; Petanidou2007; Macuka-

novic-Jocic et al. 2008). Therefore, unlike pollen produc-

tion, nectar secretion and reabsorption by the plant or

depletion by foraging animals are rhythmic process (Gal-

leto and Bernardello2004; Pacini and Nepi2007) and the

nectar standing crop fluctuates throughout the day. The

daily foraging of bees should vary according to the volume

and sugar concentration of the nectar available through the

day, as well as external abiotic factors. Abiotic factors

strongly affect the interactions between flowers and poll-

inators (Corbet 1990; Petanidou 2007). Physical factorsconstrain the activity of pollinators, influence their

behavior at flowers, and modify the quality, quantity, and

presentation of floral rewards (Herrera 1995). Through

such indirect and direct effects, abiotic factors may thereby

become critical determinants of plant pollination.

Pollination is an ecosystem service essential to the

maintenance of wild plant populations and to food pro-

duction in agricultural environments (Constanza et al.

1997, Ricketts et al. 2008). The way in which flower vis-

itors share floral resources or compete for them throughout

the day is decisive factor for the effectiveness of pollina-

tion (Kevan and Baker 1983). Identifying patterns of visi-

tation and understanding the mechanisms of the

relationship between the plant and flower visitors contrib-

ute to the adequate management of crops and, conse-

quently, to increased plant and honey production. This

knowledge is also useful in the management and rehabili-

tation of degraded natural areas, by attracting and retaining

visitors and pollinators within the ecosystem.

Ocimum basilicum L. (basil) is an intensely cultivated

aromatic herb that belongs to the family Lamiaceae (Ozcan

and Chalchat 2002). Basil is a shrub that reaches about

5060 cm height, has a highly branched crown and simple,

small, green leaves. Its flowers are small, white, and fra-

grant, structured in terminal inflorescences. The plant is

perennial, and under conditions of successive pruning, it

presents intense flowering and large leaf production up to

the second year of the crop (Blank et al.2004). The flowers

have a sweet fragrance, with nectar storage at an appro-

priate depth for the length of the bee proboscis, and due to

the position of stamens, the pollen is easily collected on the

ventral part of the bees body (Macukanovic-Jocic et al.

2008). Although bee visitation to basil occurs very

frequently, information concerning the mechanisms of this

relationship remains scarce. This plant is appropriate for

studying the ecology of flower visitation, because it is

small and presents easy propagation, hardiness, low nutri-

tional requirements, and intense flower production all year

round. In this study, we used the basil as a model to

describe temporal patterns of flower visitation by bees and

tested whether such temporal patterns depend on: (1) thebody size of the species, (2) the daily patterns of variation

in weather and nectar standing crop, and (3) the effects of

weather on the daily rhythm of variation in nectar standing

crop.

Materials and methods

Characterization of the sample area

Field work was performed in green basil crops in Sao Joao

del Rei, MG, Brazil. The area is located at latitude of2106012.7500 south, a longitude 4414053.3400 west, and at

898 m altitude. The region is characterized by tropical,

high-altitude climate, and with two main seasons: a warm

rainy summer, with monthly averages of 22 C and

175 mm precipitation from October to March; and a cool

dry winter, with monthly averages of 17 C and 32 mm

precipitation from April to September. During the period of

the study, the average monthly minimum and maximum

temperatures were 12 and 27 C, respectively.

Basil seedlings were prepared for 2 months in 2-L pots

and then transplanted to the field 3 months before the onset

of bee samplings. In an area of 40 m2, 20 plants were

cultivated, distributed in two rows of 10 plants each, with

the plants spaced 1.0 m apart and 2.5 m between rows. The

rows were pruned and used alternately during the sampling

period.

Bee sampling and weather in the field

We conducted bee sampling biweekly for 1 year (25 col-

lection days), from 7 a.m. to 5 p.m., divided into 10 1-h

intervals. Two collectors captured the bees by oral suction

and entomological nets by moving along the row of 10

plants. The mean dry weight of the six most abundant

species was measured (20 individuals per species) and the

data were analyzed by ANOVA followed by the Holm-

Sidak post hoc test to compare the means. The patterns of

daily visits by these six species were described and

Gaussian equations were fitted to test whether species with

different body sizes have peaks of activity at different

times of the day. This and all other analyzes were per-

formed using GraphPad Prism 5.0, Graph Prism Inc., San

Diego, CA, and SigmaPlot 10, Systat Software Inc., San

492 J. M. Muniz et al.

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Jose, CA, and procedures for fitting the regressions

according to Motulsky and Christopoulos (2003). We

measured atmospheric temperature and relative air

humidity at the site, at 1-h intervals, using a portable digital

thermohygrometer (Incoterm). The local patterns of vari-

ation in temperature and relative humidity over the course

of the day were described. Polynomial equations were fit-

ted to test whether the temperature increases and the rel-ative humidity decreases from early morning until late

afternoon.

Nectar standing crop under field conditions

We conducted biweekly samplings of nectar in the field

over 12 days, between August and January. The sampling

period was from 7 a.m. to 5 p.m., divided into 10 1-h

intervals. Five plants were randomly sampled per interval

and nectar was collected from five individual flowers on

each plant. To quantify the mean of nectar standing cropper individual flower, we protected whole plants and their

inflorescences against flower visitations with a structure

made of organza, a soft and white fabric, for a 48-h period

prior to removal of the nectar. We individually marked the

flowers at the bud stage and collected nectar on day two of

the life of the flower, since nectar production is limited to

anthesis, initiating just prior to the opening of the flower

(Macukanovic-Jocicet al. 2008).

We measured the volume and concentration of sugars in

the floral nectar using capillary tubes and refractometers.

One end of the capillary tube was inserted into the nectar

droplet, extracted from the flower by capillarity (Corbet2003), using glass microcapillary tubes of 0.1 and 0.3 mm

in diameter. Following nectar collection, we measured the

height of the liquid in a capillary column, with the aid of a

digital calliper. We calculated the mean volume (lL) per

flower extracted from each plant according to Macukano-

vic-Jocic et al. (2008): V= R (r2pH)/N, where r= mi-

crocapillary tube radius (mm),H= height of the nectar in

the tube (mm), and N= number of flowers sampled from

the plant (=5).

We measured the concentration of sugars in the nectar

(g solute per 100 g solution) using manual refractometers

(Bellimgham and Stanley, mod. 45-81 Eclipse, resolution:

0.5 % BRIX, ranges 050 % and 4580 %), with a mini-

mum volume readability of 1 lL. After a drop of nectar

was placed at the center of the prism of the refractometer,

we performed the reading immediately to minimize evap-

oration of the droplet (Corbet 2003). The mean sugars

content, an estimate of energy available in each individual

flower, was calculated by converting mass/total mass

measurements in mass/volume according to Corbet (2003):

sugar (mg) = [(sugar concentration 9 q) /100] 9 volume,

where q = density (g/cm3) of a sucrose solution at each

observed concentration, read from tables. We calculated

overall nectar volume, sugar concentration, and sugar

content measurements per individual flower (5 flowers) for

plants sampled at the same time (5 plants) on each of the 12

sampling days.

We obtained temperature and humidity on site for each

sampling time using a portable digital thermohygrometer(Incoterm). The patterns of variation in nectar volume,

sugar concentration, and sugar content throughout the day

were described. Polynomial equations were fitted to test

whether the concentration increases and the volume

decreases from early morning until late afternoon. A linear

equation was fitted to test sugar content variation. The

relationships between both nectar volume and sugar con-

centration, and temperature and air relative humidity were

tested by regression analysis.

Nectar standing crop under controlled temperatures

Plants of O. basilicum were grown in 2-L pots under

controlled nutrition and irrigation. At the onset of the

flowering, we placed the pots in climatized chambers with

a 12-h photoperiod. To maintain the chamber atmosphere

and the soil water saturated, the pots were placed in plastic

trays partially filled with water. The temperature regimes

(treatment levels) in the chambers were maintained con-

stant at 5, 10, 15, 20, 25, 30, 35, and 40 C. Five flowering

plants were exposed to each of the eight thermal regimes,

24 h before nectar sampling. We sampled the nectar of five

flowers from each plant. We measured and calculated meannectar volume, sugar concentration, and sugar content of

each individual flower with microcapillaries and refrac-

tometers, as described previously. Nectar was analyzed as a

function of temperature by nonlinear regressions. The

preferred model was the one with highest R2 and fewer

parameters.

Nectar standing crop under controlled soil moisture

We submitted plants grown in 1-L pots to water treatment

under controlled conditions in a green house. The irrigation

regimes were 20, 40, 60, 80, 90, 100, 120, and 150 mL per

day for five consecutive days. Six plants were exposed to

each of the water regimes, and after day five, five flowers

per plant were sampled. We measured and calculated mean

nectar volume, sugar concentration, and sugar content of

each individual flower as described previously. Nectar was

analyzed as a function of the volume of water received by

the plants, and the preferred regression model was the one

with highest R2 and fewer parameters.

Patterns and mechanisms of temporal resource 493

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Results

Visitor bees and weather daily variations

During the collection period, we encountered 9,160 bees

belonging to 56 species, 90 males and 9,070 females.

Among the species collected, 26 belonged to the family

Apidae, 17 to Halictidae, 9 to Megachilidae, 2 to Colleti-dae, and 2 belonged to Andrenidae (Table1). Besides

showing the greatest diversity, Apidae was the most

abundant family with 8,820 individuals (96.3 % of the

abundance), followed by Halictidae with 247 individuals

(2.7 %). The dominant species were Paratrigona lineata

(Lepeletier) (58.8 %) and Apis mellifera Linnaeus

(30.2 %). Together, they accounted for 89.0 % of the total

abundance of bees visiting basil flowers.

We statistically described the daily patterns of basil

flower visitation for the six most abundant species

([0.2 %). The foraging activity of Bombus (Fervidobom-

bus) morio, A. mellifera, and Trigona spinipes was con-centrated in the early hours of the day, between 8 and 11

am in the morning (estimated peaks in hourly intervals of

2.38, 2.85, and 3.33, respectively). In contrast, Tetragoni-

sca angustula, P. lineata, and Dialictus sp. showed visi-

tation peaks in the late morning and early afternoon,

between approximately 11 a.m. and 2 p.m. (estimated

peaks in hourly intervals of 6.04, 6.19, and 5.23, respec-

tively) (Fig.1). The difference in mean individual dry

weight (as a measure of body size) between the extremes,

B. morio(0.197 g) and Dialictus sp. (0.0018 g), was more

than 100 times, but the six species can be categorized into

larger (B. morio, A. mellifera, and T. spinipes) and smaller

bees (T. angustula, P. lineata, and Dialictus sp) (Fig. 2).

The coldest temperatures were recorded in the early

hours of the day, and the hottest period was between 1 and

4 pm (Fig. 3a). Relative air humidity peaked in the early

morning and the lowest values were recorded between 1

and 4 p.m. (Fig. 3b). Thus, lower temperatures in the

morning coincided with higher relative humidity, while

higher temperatures in the afternoon coincided with lower

humidity.

Nectar standing crop under field conditions

Volume and sugar concentration of the nectar showed well-

defined, but inverse temporal patterns. Nectar volume

declined from the early hours of the morning onward and

showed minimum values at about 2 p.m. (Fig. 4a), while

the mean sugar concentration in nectar increased and

peaked at the same time (Fig. 4b). However, the content of

sugars in the nectar remained unchanged throughout the

day (Fig.4c).

Under uncontrolled field conditions, nectar volume and

sugar concentration in nectar were significantly correlated

(p\ 0.0001) with temperature and relative humidity.

However, relative air humidity was a better predictor of

nectar characteristics (R2= 0.77 and 0.79) (Fig.5a, b)

than atmospheric temperature (R2 = 0.21 and 0.20)

(Fig.5c, d).

Nectar standing crop under controlled temperatures

and moisture

In the laboratory, nectar volume increased with the

increasing temperature up to a maximum estimated peak at

28.4 C and then decreased again (Fig.6a). The response

of concentration to temperature was not symmetrically

opposite to the response of volume. Sugar concentration

gradually decreased up to 35 C, following which it

dropping sharply (Fig.6b). These responses to tempera-

ture, revealed by the experimental approach, were different

from those obtained during uncontrolled field observations(Fig.5c, d). If the same minimum and maximum thermal

limits in the field of 10 and 30 C were applied to the

laboratory results, the responses would be satisfactorily

described as linearly inverse for both conditions. The

content of sugar varied similarly to nectar volume (esti-

mated peak at 26.9 C) (Fig. 6c). Under controlled condi-

tions, nectar volume increased and sugar concentration

decreased linearly with the volume of water received by the

plant (Fig. 6d, e). However, the content of sugars in the

nectar reached a peak estimated at 59.6 mL of water and

then decreased again (Fig. 6f).

Discussion

Characterization of the fauna of bee visitors of basil

Ocimum basilicum attracted a great richness and abun-

dance of bees (Table1), probably because basil flowering

extends throughout the year, including seasons with lower

abundance of flowers. Apidae was the most representative

family mainly due to the eusocial behavior, the longevity

of the colony, and the generalist foraging (Roubik1992).

Eusocial bees usually possess populous colonies and

communicate the location of food sources to other workers

(Lindauer and Kerr 1960), permitting the meeting of a

large number of individuals from the same colony. These

characteristics are shared by the four most abundant spe-

cies that visited basil:P. lineata,A. mellifera,T. angustula,

and T. spinipes. The first two were clearly dominant

(90 %) over the other 54 species. The six most abundant

species can be categorized into morning foragers (B. morio,

A. mellifera, and T. spinipes) and afternoon foragers


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Table 1 Bees sampled on

inflorescences of basil (O.

basilicum) in Sao Joao del Rei

(MG), Brazil

Species Males Females Total

Andrenidae

Calliopsini

Acamptopoeum prinii (Holmberg, 1884) 1 1

Protandrenini

Psaenythia sp. Gerstacker, 1868 1 1

Apidae

Apini

Apis melliferaLinnaeus, 1758 2,767 2,767

Tetragonisca angustula(Latreille, 1811) 243 243

Paratrigona lineata (Lepeletier, 1836) 5,388 5,388

Trigona spinipes (Fabricius, 1793) 164 164

Tetragona cfr clavipes (Fabricius, 1804) 29 29

Geotrigona subterranea (Friese, 1901) 1 1

Partamona cfr. cupira 1 1

Bombus (Fervidobombus) morio (Swederus, 1787) 56 56

Bombus (Fervidobombus) atratus Franklin, 1913 9 9

Euglossa melanotricha Moure, 1967 1 1

Centridini

Centris (Hemisiella) tarsata Smith, 1874 7 1 8

Centris (Centris) sp. Fabricius, 1804 2 2

Ericrocidini

Mesocheira bicolor(Fabricius, 1804) 2 2

Eucerini

Pachysvastra leucocephala (Bertoni & Schrottky, 1910) 8 8

Melissoptila cnecomala (Moure, 1944) 4 7 11

Melissodes (Ecplectica) sexcincta (Lepeletier, 1841) 1 1 2

Gaesischiana (Gaesischiana) patellicornis (Ducke, 1910) 2 2

Exomalopsini

Exomalopsis (Exomalopsis) auropilosa Spinola, 1853 2 3 5Exomalopsis (Exomalopsis) analis Spinola, 1853 19 34 53

Exomalopsis (Exomalopsis) ypirangensis Schrottky, 1910 1 1

Tapinotaspidini

Monoecasp. Lepeletier & Serville, 1828 1 1

Paratetrapedia (Paratetrapedia)sp. Moure, 1941 3 3

Tetrapediini

Tetrapedia sp. 20 20

Ceratinini

Ceratina (Crewella) cfr rupestris Holmberg, 1884 5 5

Ceratina (Crewella) cfr punctulata Spin, 1841 2 2

Ceratina (Ceratinula) sp. Moure, 1941 36 36

Colletidae

Colletinae

Colletes rugicollis Friese, 1900 1 1

Hylaeinae

Hylaeussp. Fabricius, 1793 1 1

Halictidae

Augochlorini

Augochlora (Augochlora) foxianaCockerell, 1900 3 3

Augochlora sp. Smith, 1853 2 51 53

Augochlorella ephyra (Schrottky, 1910) 2 4 6


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(T. angustula, P. Lineata, and Dialictus sp.) (Fig. 1). This

fact calls for mechanistic explanations for different tem-

poral patterns of flower visitation among bee species.

Direct mechanisms: the predictable variation

in temperature

The three species with greatest body mass were those that

foraged earlier, under colder temperatures, particularly B.

(Fervidobombus) morio, the largest of all. In contrast, the

species with lower dry weight preferred visiting the flowers

later, during the hottest period of the day (Figs. 1, 2, 3a).

The preference for certain foraging times in insects can be

partially explained by the relationship between body size

and body temperature. Given their small size, insects are

generally dependent on ambient temperature and any heat

internally generated is quickly dissipated (Gullan and

Cranston2005). Accordingly, larger bees lose less heat to

the environment and are able to forage at lower tempera-

tures. In contrast, smaller bees are forced to forage during

the hotter hours of the day. For example, Bombus presents

better thermoregulatory ability, through internal physio-

logical mechanisms, than smaller bees, which are more

dependent on external sources of heat (Bisshop and Arm-

bruster 1999; Chown and Nicolson 2004). Bees generally

begin their flight activity only after the temperature reaches

a minimum value that varies from species to species

according to their body size and thermoregulation ability

(Burrill and Dietz 1981; Corbet et al. 1993; Danka et al.

2006). Therefore, the temporal patterns of bee visitation of

basil can be partially explained by the fact that the larger

bees show better tolerance to lower temperatures early in

the morning, unlike the smaller bees that concentrate their

activities during the hotter hours of the day.

Direct mechanisms: dynamic of nectar standing crop

Large bees, more efficient in producing endogenous body

heat, can fly at low temperatures in the early morning, but

this behavior has a higher energy cost than foraging at

Table 1 continuedSpecies Males Females Total

Augochlorella urania (Smith, 1853) 46 46

Augochloropsissp.01 2 2

Augochloropsis aurifluens (Vachal, 1903) 4 4

Augochloropsis brachycephalaMoure, 1943 7 7

Augochloropsis callichroa (Cockerell, 1900) 1 5 6

Augochloropsis patens (Vachal, 1903) 34 34

Augochloropsis smithiana(Cockerell, 1900) 6 6

Ceratalictussp. 1 1

Pseudaugochlora sp. Michener, 1954 1 1

Pseudaugochlora cfr indistincta 1 1

Halictini

Caenohalictus sp. Cameron, 1903 1 1

Dialictussp. Robertson, 1902 69 69

Habralictus sp. Moure, 1941 1 1

Pseudagapostemon (Pseudagapostemon) sp. 3 3 6

Megachilidae

Anthidiini

Anthodioctes megachiloides Holmberg, 1903 3 30 33

Epanthidium tigrinum (Schrottky, 1905) 4 4

Megachilini

Megachile (Austromegachile) susurransHaliday, 1836 4 15 19

Megachile (Dactylomegachile)sp.01 Mitchell, 1934 4 1 5

Megachile (Dactylomegachile)sp.02 13 13

Megachile (Leptorachis) aureiventrisSchrottky, 1902 8 8

Megachile (Leptorachis)sp.01 2 2

Megachile (Leptorachis) paulistanaSchrottky, 1902 2 2

Megachile (Ptilosaroides) neoxanthopteraCockerell, 1933 2 1 3

Total 90 9,070 9,160


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higher temperatures. Foraging in the early morning should

provide a net energy gain. Even though less volume is

available at afternoon, the sugar content (energy avail-

ability) of nectar of the basil remains unchanged through-

out the day (Fig. 4a, c). Therefore, foraging in the

afternoon may be as energetically interesting as foraging

early in the morning and the body energy consumption

would be lower. The disadvantage is finding that the

flowers are already depleted by early foragers.

The energy costs and benefits are affected by how the

nectar is presented, diluted or concentrated (Heinrich

1975). The increase in the concentration of sugars increases

Numberof

individualbees

A Bombus morioy = 0.102 + 0.358 exp {-0.5[(x-2.378)/1.572]

2}

R2= 0.98, F

9-3= 99, p < 0.0001

Numberofindividualbees

0

5

10

15

20

25

30

35B Apis melliferay = 3.22 + 26.18 exp {-0.5[(x-2.85)/1.23]

2}

R2= 0.98, F9-3= 124, p < 0.0001

Visitation times (hourly intervals in the day)

Numberofindividualbe

es

C Trigona spinipesy = 0.227 + 1.35 exp {-0.5[(x-3.331)/1.126]

2}

R2= 0.92, F9-3= 22, p = 0.0013

D Tetragonisca angustulay = 2.0 exp{-0.5[(x-6.04)/2.09]

2}

R2= 0.93, F9-2= 44, p = 0.0001

0

5

10

15

20

25

30

35

40

45

50

55E Paratrigona lineatay = 42.0 exp {-0.5 [(x-6.19)/2.15]

2}

R2= 0.97, F9-2=98, p < 0.0001

F Dialictus sp.y = 0.76 exp {-0.5[(x-5.23)/1.45]

2}

R2= 0.92, F9-2= 42, p = 0.0001

7-8 8-9 9-10 10-11 11-12 12-13 13-14 14-15 15-16 16-17 16-1715-1614-1513-1412-1311-1210-119-108-97-8

0.0

0.1

0.2

0.3

0.4

0.5

0.0

0.5

1.0

1.5

2.0

2.5

0.0 0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

0.2

0.4

0.6

0.8

1.0

Fig. 1 Patterns of variation in the abundance of the six principal beespecies visiting basil (O. basilicum) flowers throughout the day.

Species with greater body mass, on the left (ac), and lower body

mass, on theright(df) (see also Fig.2).Columnandbarindicate themean of 25 sampling days SE. In the equations,x ranges from 1 to

10 intervals in the day


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nectar viscosity that tends to reduce the flow rate of the

liquid (Josens and Farina 2001). The volume of liquid

ingested per lick by the bee remains constant when the

proboscis is in contact with the nectar; however, when the

viscosity increases, the volume ingested decreases,

Bee species

Dryweightofindividualbees(g)

-

A

B B

CCD

D

0.00

0.01

0.02

0.150.03

0.20

0.21

B.morioA.me

liferaT.sp

inipes

T.angustu

laP.lin

eataDialic

tussp.

Fig. 2 Dry weight of the six most abundant bee species visiting basil

(O. basilicum) flowers. Column and bar indicate a mean of 20

individual bees SE. Different letters indicate significant differences

according to ANOVA and Holm-Sidak post hoc test atp\ 0.05

Atmospherictemperature(C)

14

16

18

20

22

24

26

28

30

y = 15.6 + 1.55x + 0.21 x2- 0.026x3

R2= 0.99, F9-3= 915, p < 0.0001

Hourly intervals in the day

Relativeairhumidity(%)

40

50

60

70

80

90

y = 84.8 + 1.72x - 1.92x2+ 0.15x3

R2= 0.98, F9-3= 126, p 0,05C

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

Fig. 4 Variations in the volume (a), sugar concentration (b), and

sugar content (c) of the nectar encountered in individual basil

(O. basilicum) flowers throughout the day. Point and bar indicate

mean SE of 12 sampling days over a 6-month period, such that

each day, five different plants, five flowers per plant were sampled ateach time interval. In the equations, x ranges from 1 to 10 hourly

intervals in the day


1 3


9/12

resulting in a lower intake rate (Harder1986). Changes in

sugar concentration (Fig. 4b) and the difficulty involved in

the extraction of a more viscous solution could affect the

preference of foraging throughout the day. Thus, the small

bees that forage in the afternoon have to cope with the

more viscous nectar that is more difficult to extract. Again,

this may be a disadvantage due to their smaller capacity of

flight at lower temperatures.

Indirect mechanisms: temperature affects air humidity

and soil moisture, which regulate nectar standing crop

Air humidity and soil moisture can influence the quantity

of flower nectar (Corbet1978). Coinciding with changes in

temperature and relative humidity (Fig.3a, b), basil

revealed significant changes in nectar volume and sugar

concentration throughout the day (Fig 4a, b), but the con-

tent of sugars remained constant (Fig. 4c). This indicates

that the rates of secretion and reabsorption of solutes did

not change. Nectar secretion in basil is limited to anthesis,

initiating just prior to the opening of the flower (Macuka-

novic-Jocic et al. 2008). However, the water content of

nectar can be modified by condensation from humid air,

precipitation, and evaporation (Corbet 2003; Petanidou

2007). If evaporation, condensation, and soil moisture are

primarily influenced by temperature, the daily dynamics of

volume and sugar concentration depend on predictable

changes in the weather (Fig. 5ad).

At higher temperatures, Freeman and Head (1990) and

Snezana et al. (2010) demonstrated an increase in sugar

concentration. Despite reports in the literature and the

results recorded in this study, the negative relationship

between temperature and nectar volume and the positive

relationship between temperature and sugar concentration

of nectar (Fig. 5c, d) appear to be spurious. The diminished

nectar volume or increased sugar concentration throughout

the day are determined directly by a decrease in humidity

air (Fig.5a, b) and soil moisture, and not necessarily as a

direct result of the rising temperatures. Unlike the rela-

tionships observed in the field (Fig.5c, d), the initial

increase in temperature promoted an increase in nectar

volume and decreased sugar concentration under controlled

laboratory conditions. (Fig. 6a, b). However, there was an

optimum temperature, and negative effect on nectar

y = 2.59 - 0.071x

R2= 0.22, F119-1= 33, p < 0.0001

Atmospheric temperature (C)

5 10 15 20 25 30 35

y = - 0.99 + 1.86x

R2= 0.21, F119-1= 32, p < 0.0001

Volume(L)

0

1

2

3

4

y = 0.372 + 0.0007exp (0.0839x)

R2= 0.77, F119-2= 201, p


10/12

volume was observed when that temperature was exceeded.

Temperatures above this optimal range were not recorded

in the field ([32.5 C), where linear relationships were

observed (Fig. 5c, d). Notwithstanding, we determined a

direct positive effect of temperature increases up to an

estimated 28.4 C (Fig. 6a), possibly due to a stimulation

of the secretory metabolism of solutes (Fig.6c). In the

field, this direct positive effect appears to be obscured by

ou

me

y = 0.10 + 0.56 exp [ -0.5 (x - 28.38/7.53)2]

R2= 0.95, F7-3 = 28, p = 0.004

A

Concentration

(%)

10

20

30

40

50

60

70

80

y = (1 - 0.0242x)/(0.0148 - 0.0003x)

R2= 0.94, F7-2 = 38, p = 0.001

B

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Daily irrigation volume (mL)

10

20

30

40

50

60

y = 0.36 + 0.004x

R2= 0.93, F7-1= 76, p


11/12

the stronger negative effect of the decrease in humidity.

Thus, the indirect effect of rising temperatures, via the

reduction in air humidity, seems to be more important thanits direct effect on plant metabolism.

Under soil water deficit, the drought regime affects

secretion and other attributes of nectar; therefore, nectar

volume is lower and the concentration of sugars is

increased (Petanidou et al. 1999; Petanidou 2007;

Macukanovic-Jocicet al.2008; Snezana et al.2010). There

is an optimal level of water in the soil for the content of

sugars but, under conditions of water stress, we actually

measured a lower volume of nectar, with a higher con-

centration of solutes (Fig.6d, e, f), characteristic of our

findings for the hottest, driest hours of the day (Figs. 3,4).

Therefore, besides the drop in air humidity, water deficit in

the soil, under the primary effect of temperature, could

have contributed to regulating the dynamics of nectar

standing crop throughout the day.

Conclusions

It is well known that bee species have different foraging

schedules. Mechanisms regulating nectar secretion and

foraging activity of bees have been studied separately for a

long time. However, for the first time, this study goes

further to show how such mechanisms interact and affect

each other to generate predictable temporal patterns of

flower visitation (Fig.7). We provide evidence that a rich

fauna of bees can share a floral resource in the same place

by using different daily rhythms of activity. In direct

responses to temperature and the dynamics of nectar supplyby the plant (regulated by air and soil humidity), bees

divide the floral resource according to their body size and

physiological attributes (Fig. 7).

Acknowledgements The financial support provided by Fundacao de

Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG) is

acknowledged here. JM Muniz and ALC Pereira were supported by

Coordenacao de Aperfeicoamento de Pessoal de Nvel Superior

(CAPES) and Conselho Nacional de Desenvolvimento Cientfico e

Tecnologico (CNPq) fellowships. Species identification was super-

vised by Dr. Fernando Amaral da Silveira at the Laboratory of Sys-

tematics and Ecology of Bees of the Federal University of Minas

Gerais, Brazil, where the specimens are deposited. The comments

and suggestions provided by Dr. Bjorn Gucker, Dr. Steven D. John-son, and two anonymous reviewers were greatly appreciated and

acknowledged here.

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