Abstract
Floral features that affect the efficiency with which pollinators can harvest their resources, or the profitability they obtain from them, affect the foraging decisions of pollinators. Foraging choices of pollinators, in turn, affect pollen flow: increases in flower constancy lead to more efficient pollen transport. It follows that exploitation barriers—flower traits that differentially affect net intake rates of potential visitors—will promote resource partitioning and enhance pollen export. In this paper we first generalise foraging models to show that exploitation barriers can lead to partial resource partitioning even when flowers are randomly distributed in space. Then we develop a model to study how the foraging rules of pollinators, pollen removal and pollen deposition, affect pollen flow. The model shows that resource partitioning, even incomplete, can substantially increase the efficiency of pollen flow. Finally, we use computer simulations to demonstrate that exploitation barriers promoting partial resource partitioning can evolve. Many of the flower traits associated with pollination syndromes have small but consistent effects on the efficiency with which different taxonomic groups exploit flowers, and can be considered exploitation barriers. Even if these barriers are not strong enough to promote strict specialisation, and may have little effect on the female component of fitness when pollinators are not a limiting resource, they are likely to be selected because they enhance the male component of fitness.
Similar content being viewed by others
References
Adler LS (2000) The ecological significance of toxic nectar. Oikos 91:409–420
Archetti M (2011) Contract theory for the evolution of cooperation: the right incentives attract the right partners. J Theor Biol 269:201–207
Armbruster WS, Muchhala N (2009) Associations between floral specialization and species diversity: cause, effect, or correlation? Evol Ecol 23:159–179
Bohart GE (1957) Pollination of alfalfa and red clover. Annu Rev Entomol 2:355–380
Buchmann SL, Jones CE, Little RJ (1983) Buzz pollination in angiosperms. In: Jones CE, Little RJ (eds) Handbook of experimental pollination biology. Scientific & Academic Editions, van Nostrand Reinhold, New York, pp 73–113
Burger H, Dötterl S, Haberlein CM et al (2012) An arthropod deterrent attracts specialised bees to their host plants. Oecologia 168:727–736
Castellanos MC, Wilson P, Thomson JD (2003) Pollen transfer by hummingbirds and bumblebees, and the divergence of pollination modes in Penstemon. Evolution 57:2742–2752
Castellanos MC, Wilson P, Thomson JD (2004) ‘Anti-bee’ and ‘pro-bird’ changes during the evolution of hummingbird pollination in Penstemon flowers. J Evol Biol 17:876–885
Chittka L (1996) Does bee color vision predate the evolution of flower color? Naturwissenschaften 83:136–138
Clark JL, Clavijo L, Muchhala N (2014) Convergence of anti-bee pollination mechanisms in the Neotropical plant genus Drymonia (Gesneriaceae). Evol Ecol. doi:10.1007/s10682-014-9729-4
Cruden RW (2000) Pollen grains: why so many? Plant Evol Syst 222:143–165
de Jong TJ, Waser NM, Klinkhamer PGL (1993) Geitonogamy: the neglected side of selfing. Trends Ecol Evol 8:321–325
Dötterl S, Milchreit K, Schäffler I (2011) Behavioural plasticity and sex differences in host finding of a specialized bee species. J Comp Physiol A 197:1119–1126
Feinsinger P (1976) Organization of a tropical guild of nectarivorous birds. Ecol Monogr 46:257–291
Fenster CB, Armbruster WS, Wilson P, Dudash MR, Thomson JD (2004) Pollination syndromes and floral specialization. Annu Rev Ecol Evol Syst 35:375–403
Galen C, Gregory T (1989) Interspecific pollen transfer as a mechanism of competition: consequences of foreign pollen contamination for seed set in the alpine wildflower, Polemonium viscosum. Oecologia 81:120–123
Galen C, Rotenberry JT (1988) Variance in pollen carryover in animal–pollinated plants: implications for mate choice. J Theor Biol 135:419–429
Galen C, Kaczorowski R, Todd SL, Geib J, Raguso RA (2011) Dosage-dependent impacts of a floral volatile compound on pollinators, larcenists, and the potential for floral evolution in the alpine skypilot Polemonium viscosum. Am Nat 177:258–272
Gegear RJ, Burns JG (2007) The birds, the bees, and the virtual flowers: can pollinator behavior drive ecological speciation in flowering plants? Am Nat 170:551–566
Gomez JM, Perfectti F, Camacho JPM (2006) Natural selection on Erysimum mediohispanicum flower shape: insights into the evolution of zygomorphy. Am Nat 168:531–545
Gonzálvez FG, Santamaría L, Corlett RT et al (2013) Flowers attract weaver ants that deter less effective pollinators. J Ecol 101:78–85
Gorelick R (2001) Did insect pollination cause increased seed plant diversity? Biol J Linn Soc 74:407–427
Goyret J, Pfaff M, Raguso RA et al (2008) Why do Manduca sexta feed from white flowers? Innate and learnt colour preferences in a hawkmoth. Naturwissenschaften 95:569–576
Grant V (1994) Modes and origins of mechanical and ethological isolation. Proc Natl Acad Sci 91:3–10
Hannan GL, Prucher HA (1996) Reproductive biology of Caulophyllum thalictroides (Berberidaceae), an early flowering perennial of eastern North America. Am Midl Nat 136:267–277
Harder LD (1985) Morphology as a predictor of flower choice by bumble bees. Ecology 66:198–210
Harder LD (1990) Pollen removal by bumble bees and its implications for pollen dispersal. Ecology 71:1110–1125
Harder LD, Johnson SD (2009) Darwin’s beautiful contrivances: evolutionary and functional evidence for floral adaptation. New Phytol 183:530–545
Harder LD, Thomson JD (1989) Evolutionary options for maximizing pollen dispersal of animal–pollinated plants. Am Nat 133:323–344
Harder LD, Wilson WG (1998) Theoretical consequences of heterogeneous transport conditions for pollen dispersal by animals. Ecology 79:2789–2807
Houston A, Schmidhempel P, Kacelnik A (1988) Foraging strategy, worker mortality, and the growth of the colony in social insects. Am Nat 131:107–114
Inouye DW (1978) Resource partitioning in bumblebees: experimental studies of foraging behavior. Ecology 59:672–678
Irwin RE, Adler LS, Brody AK (2004) The dual role of floral traits: pollinator attraction and plant defense. Ecology 85:1503–1511
Jersáková J, Johnson SD (2006) Lack of floral nectar reduces self-pollination in a fly-pollinated orchid. Oecologia 147:60–68
Jersakova J, Johnson SD, Kindlmann P (2006) Mechanisms and evolution of deceptive pollination in orchids. Biol Rev 81:219–235
Kay KM, Sargent RD (2009) The role of animal pollination in plant speciation: integrating ecology, geography, and genetics. Annu Rev Ecol Evol Syst 40:637–656
Laverty TM (1980) The flower-visiting behaviour of bumble bees: floral complexity and learning. Can J Zool 58:1324–1335
Lebuhn G, Anderson GJ (1994) Anther tripping and pollen dispensing in Berberis thunbergii. Am Midl Nat 131:257–265
LeBuhn G, Holsinger K (1998) A sensitivity analysis of pollen-dispensing schedules. Evol Ecol 12:111–121
Lewis AC (1986) Memory constraints and flower choice in Pieris rapae. Science 232:863–865
McFall-Ngai MJ (1998) The development of cooperative associations between animals and bacteria: establishing detente among domains. Am Zool 38:593–608
Meléndez-Ackerman E, Campbell DR, Waser NM (1997) Hummingbird behavior and mechanisms of selection on flower color in Ipomopsis. Ecology 78:2532–2541
Molau U (1991) Gender variation in Bartsia alpina (Scrophulariaceae), a sub-arctic perennial hermaphrodite. Am J Bot 78:326–339
Muchhala N, Brown Z, Armbruster WS et al (2010) Competition drives specialization in pollination systems through costs to male fitness. Am Nat 176:732–743
Murcia C (1990) Effect of floral morphology and temperature on pollen receipt and removal in Ipomoea trichocarpa. Ecology 71:1098–1109
Murphy SD, Aarssen LW (1995) Reduced seed set in Elytrigia repens caused by allelopathic pollen from Phleum pratense. Can J Bot 73:1417–1422
Nicolson SW, Lerch-Henning S, Welsford M et al (this issue) Nectar palatability can selectively filter bird and insect visitors to coral tree flowers. Evol Ecol
Parachnowitsch AL, Raguso RA, Kessler A (2012) Phenotypic selection to increase floral scent emission, but not flower size or colour in bee-pollinated Penstemon digitalis. New Phytol 195:667–675
Possingham HP (1992) Habitat selection by two species of nectarivore: habitat quality isolines. Ecology 73:1903–1912
Pyke GH (1979) Optimal foraging in bumblebees: rule of movement between flowers within inflorescences. Anim Behav 27:1167–1181
Raguso RA (2008) Wake up and smell the roses: the ecology and evolution of floral scent. Annu Rev Ecol Evol Syst 39:549–569
Raine NE, Chittka L (2007) The adaptive significance of sensory bias in a foraging context: floral colour preferences in the bumblebee Bombus terrestris. PLoS One 2:e556
Ramírez SR, Eltz T, Fujiwara MK et al (2011) Asynchronous diversification in a specialized plant–pollinator mutualism. Science 333:1742–1746
Raven PH (1972) Why are bird-visited flowers predominantly red? Evolution 26:674
Rhoades DF, Bergdahl JC (1981) Adaptive significance of toxic nectar. Am Nat 117:798–803
Riffell JA, Alarcon R, Abrell L et al (2008) Behavioral consequences of innate preferences and olfactory learning in hawkmoth-flower interactions. Proc Natl Acad Sci USA 105:3404–3409
Rodríguez-Gironés MA (2006) Resource partitioning among flower visitors: extensions of Possingham’s model. Evol Ecol Res 8:765–783
Rodríguez-Gironés MA, Llandres AL (2008) Resource competition triggers the co-evolution of long tongues and deep corolla tubes. PLoS One 3:e2992
Rodríguez-Gironés MA, Santamaría L (2004) Why are so many bird flowers red? PLoS Biol 2:e350
Rodríguez-Gironés MA, Santamaría L (2005) Resource partitioning among flower visitors and evolution of nectar concealment in multi-species communities. Proc R Soc Sci B 272:187–192
Rodríguez-Gironés MA, Santamaría L (2006) Models of optimal foraging and resource partitioning: deep corollas for long tongues. Behav Ecol 17:905–910
Rodríguez-Gironés MA, Santamaría L (2007) Resource competition, character displacement, and the evolution of deep corolla tubes. Am Nat 170:455–464
Sánchez-Lafuente AM, Rodríguez-Gironés MA, Parra R (2012) Interaction frequency and per-interaction effects as predictors of total effects in plant–pollinator mutualisms: a case study with the self-incompatible herb Linaria lilacina. Oecologia 168:153–165
Sargent RD, Otto SP (2006) The role of local species abundance in the evolution of pollinator attraction in flowering plants. Am Nat 167:67–80
Schiestl FP (2010) The evolution of floral scent and insect chemical communication. Ecol Lett 13:643–656
Schiestl FP, Dötterl S (2012) The evolution of floral scent and olfactory preferences in pollinators: coevolution or pre-existing bias? Evolution 66:2042–2055
Schiestl FP, Johnson SD (2013) Pollinator-mediated evolution of floral signals. Trends Ecol Evol 28:307–315
Schuster A, Noymeir I, Heyn CC et al (1993) Pollination-dependent female reproductive success in a self-compatible outcrosser, Asphodelus aestivus Brot. New Phytol 123:165–174
Shuttleworth A, Johnson SD (2009) The importance of scent and nectar filters in a specialized wasp–pollination system. Funct Ecol 23:931–940
Smith SE, Read DJ (2008) Mycorrhizal symbiosis. Academic Press, New York
Soler JJ, Martín-Vivaldi M, Peralta-Sánchez JM, Ruiz-Rodríguez M (2010) Antibiotic-producing bacteria as a possible defence of birds against pathogenic microorganisms. Open Ornith J 3:93–100
Stebbins GL (1970) Adaptive radiation of reproductive characteristics in angiosperms, I: pollination mechanisms. Annu Rev Ecol Syst 1:307–326
Thomson JD (1986) Pollen transport and deposition by bumble bees in Erythronium: influences of floral nectar and bee grooming. J Ecol 74:329–341
Thomson JD, Goodell K (2001) Pollen removal and deposition by honeybee and bumblebee visitors to apple and almond flowers. J Appl Ecol 38:1032–1044
Thomson JD, Thomson BA (1992) Pollen presentation and viability schedules in animal–pollinated plants: consequences for reproductive success. In: Wyatt R (ed) Ecology and evolution of plant reproduction. Routledge Chapman & Hall Inc., New York, pp 1–24
Thorp RW (2000) The collection of pollen by bees. Plant Syst Evol 222:211–223
Waser NM (1998) Pollination, angiosperm speciation, and the nature of species boundaries. Oikos 82:198–201
Weiss MR (1997) Innate colour preferences and flexible colour learning in the pipevine swallowtail. Anim Behav 53:1043–1052
Zung JL, Forrest JRK, Castellanos MC et al (this issue) Bee- to bird-pollination shifts in Penstemon: effects of floral-lip removal and corolla constriction on the preferences of free-foraging bumble bees. Evol Ecol
Acknowledgments
This work was supported by the Ministerio de Ciencia e Innovación/FEDER (Project CGL2010-16795 to MARG and LS). S.S acknowledges support by the National Natural Science Foundation of China grant No. 31100277 and the Fundamental Research Funds for the Central Universities (lzujbky-2013-99).
Author information
Authors and Affiliations
Corresponding author
Appendix
Appendix
Generalities
We used a genetic algorithm to calculate the optimal foraging strategy of pollinators. Each generation 200 pollinators (100 of each species) foraged on a 100 × 100 square lattice (with periodic boundary conditions) containing one flower per cell. Cells were randomly assigned to plant species each generation (equal probability of belonging to each species; no spatial correlations). Pollinators, endowed with a genetically determined foraging strategy, foraged throughout the season (for most generations, 20,000 time units). At the end of the season a new generation of pollinators was produced: pollinators that obtained more nectar produced more offspring, and mutations were introduced to probe new foraging strategies. The process was iterated for 10,000 generations.
Nectar production
The volume of nectar per flower, V, increased according to
where θ is a parameter that determines the rate of nectar production and t represents the time since the flower was last visited.
Movement rules
At the beginning of each generation, pollinators were located at random positions of the grid. Thereafter, pollinators moved from the flower they occupied to one of its nearest neighbours, consumed the nectar encountered and moved on to a new flower. The program kept track of the amount of nectar ingested by each pollinator through the season. The foraging strategy of a pollinator simply determined to which flower it moved. It was coded in two genes (pollinators were haploid, and had a single copy of each gene) determining the attractiveness of flowers of each species, αA and αB. A pollinator on a flower had 8 nearest neighbours, indexed by l = 1, 2, … 8. Each neighbour was assigned a weight,
where dl represents the distance the pollinator must travel to reach the flower (dl = 1.414 for flowers along the diagonal, and dl = 1 otherwise), and the probability that the pollinator visited flower l was 0 if it was being exploited by another pollinator or had been visited by the focal pollinator in the ten previous rounds, and otherwise
where C is a normalisation constant.
Time budgets
The duration of a foraging cycle (time from the departure from one flower to the departure from the following flower) was equal to the sum of three terms: travel time, handling time and ingestion time.
We assumed that all pollinators flew at the same speed, equal to 1 grid cell per time unit. Travel time was therefore equal to 1 or 1.414 time units—depending on whether the pollinator travelled along one axis or along the diagonal.
Handling time, τij, had a species-specific component—determined by the phenotype of flowers and pollinators—and an individual component—determined by experience. The minimum and maximum handling times, Tmin,ij and Tmax,ij, were determined by the flower and pollinator species. Unexperienced individuals required a greater time, Tmax,ij, to get access to the nectar provided by the flower. Every time an i pollinator visited a j flower, the corresponding handling time decreased according to
Due to cognitive constraints, however, the handling time increased when the individual visited a flower of the opposite species (Laverty 1980; Lewis 1986). Specifically, we assumed that every time pollinators visited a flower of the opposite species, handling times at j flowers increased according to
As a result of 13 and 14, if a pollinator specialised on a particular flower type it achieved the minimum handling time at that flower type—at the cost of experiencing the maximum handling time if it once visited the other flower species. For pollinators visiting both flower types, handling times oscillated between their maximum and minimum values.
It takes longer to exploit flowers with more resources—a process encoded in the ingestion time. For simplicity, we assumed that ingestion time was proportional to the amount of nectar consumed.
Selection
At the end of the season we normalised the amount of intake consumed by the kth pollinator, Ik:
where Imax and Imin represent the maximum and minimum intakes by pollinators of the focal species. From this normalised intake we obtained the individual payoff, ωk:
Payoffs were used to select the “parents” of the pollinators that constituted the following generation. We selected parents at random, with probabilities proportional to ωk, with the constraint that one individual could not produce more than five offspring. Of every ten parents chosen, nine produced identical offspring. For the tenth parent, preference genes, αA and αB, had a 0.2 probability of mutating. Mutations steps were normally distributed, with mean zero and standard deviation 0.03. Preference genes were constrained to lie in the interval (10−4, 10).
Rights and permissions
About this article
Cite this article
Rodríguez-Gironés, M.A., Sun, S. & Santamaría, L. Passive partner choice through exploitation barriers. Evol Ecol 29, 323–340 (2015). https://doi.org/10.1007/s10682-014-9738-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10682-014-9738-3