Vinícius Lourenço Garcia De Brito

Vinícius Lourenço Garcia de Brito

Reproductive strategies in Melastomataceae: study cases with different approaches

Estratégias reprodutivas em Melastomataceae: estudos de caso com diferentes abordagens

CAMPINAS 2015 ii

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Abstract

A reproductive strategy could be understood as complex of morphological and physiological traits involved in plant reproduction and, therefore, in its fitness. As the majority of species of the family Melastomataceae has poricide anthers and offers just pollen as reward to flower visitors, this pollen may face a double fate: be the male reproductive transport unit and food for flower visitors. Therefore, in plants belonging to this family, different reproductive strategies should have been favoured to solve this “pollen dilemma”. In this thesis, we describe some reproductive strategies and discuss their possible causes and consequences in four different study cases. The first one is about the reproductive phenology of species of Melastomataceae occurring in the Atlantic rainforest and Cerrado formations. The second study describes the nectar and pollen dynamics in Miconia theizans and its role in favouring the increase of visitor spectra and female reproductive success. The third describes the genetic structure and diversity of populations of Tibouchina pulchra occurring in extremes of an elevational gradient with different pollination dynamics. The fourth is concerned with the floral colour change phenomenon in the same species when considering the visual apparatus of the bees. We also present a review about the cognitive ecology of pollination as an appendix to the fouth study. The results of each study case are discussed in an eco-evolutionary context and may be extrapolated to other angiosperm groups that rely on bees for their pollination and offer just pollen as reward.

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Resumo

Uma estratégia reprodutiva pode ser entendida como um conjunto de características morfo- fisiológicas que são determinantes para a reprodução do organismo e, consequentemente, para sua aptidão. Como a maioria das espécies da família Melastomataceae apresenta anteras poricidas e apenas pólen como recurso, esses grãos de pólen devem cumprir uma dupla função: ser a unidade de transporte do gameta masculino da planta e alimento para os visitantes florais. Assim, em plantas desta família, diferentes estratégias reprodutivas podem ter sido favorecidas como solução para o que ficou conhecido como “dilema de pólen”. Nesta tese descrevemos algumas estratégias reprodutivas e discutimos suas possíveis causas e consequências em quatro estudos de caso que envolvem: 1) a fenologia reprodutiva das espécies de Melastomataceae ocorrentes em áreas de Mata Atlântica e Cerrado; 2) a dinâmica de néctar e pólen em Miconia theizans e seu papel no aumento do espectro de visitantes florais e consequente incremento do sucesso reprodutivo feminino; 3) a estrutura e diversidade genética em populações da mesma espécie ocorrente em extremos de um gradiente de altitude com diferentes dinâmicas de polinização e; 4) a mudança de cor em Tibouchina pulchra considerando o aparato visual- cognitivo das abelhas polinizadoras. Além disso, também apresentamos uma revisão sobre a ecologia cognitiva da polinização como um anexo ao quarto estudo. Os resultados obtidos separadamente em cada um destes trabalhos são discutidos em um contexto ecológico-evolutivo e podem ser extrapolados para outros grupos de plantas em que predomina o sistema de polinização dependente de abelhas baseado na oferta de apenas pólen como recurso. x

Summary

Introduction ...... 1 References ...... 3

Chapter I - Preliminary insights into the reproductive phenology of Melastomataceae species from two Brazilian biodiversity hotspots ...... 5 References ...... 15 Table ...... 23 Figures ...... 24 Supplementary Material ...... 30

Chapter II - The role of nectar production in the evolution of generalised pollination systems: a case study of Miconia theizans in Southeastern Brazil ...... 43 References ...... 55 Table ...... 59 Figures ...... 60 Supplementary Material ...... 66

Chapter III - Genetic structure and diversity of populations of Tibouchina pulchra Cogn. (Melastomataceae) under different pollination dynamics in extremes of an elevational gradient ...... 73 References ...... 86 Table ...... 91 Figures ...... 94

Chapter IV - Trees as huge flowers and flowers as oversized floral guides: the role of floral color change and retention of old flowers in Tibouchina pulchra ...... 101 References ...... 116 Figures ...... 123

Appendix I - Ecologia cognitiva da polinização ...... 129 Referências bibliográficas ...... 154 Tabela ...... 161 Figura ...... 162

Concluding remarks, caveats and future steps ...... 165

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Aos meus mestres

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“Então, ele vê que o Eu está contido no mundo e que, na verdade não há Eu, e, por isso, o mundo não pode prejudicá-lo, e, então ele se tranquiliza; ou, então, ele vê que o mundo está contido no Eu, e que, afinal, não há mundo, e, por isso, ele também não pode prejudicar o Eu, o que o tranquiliza também."

Martin Buber – Eu e Tu, 1974

“Agir por natureza pelo bem- estar dos seres significa atuar através da expressão da natureza inata de todas as coisas que é absolutamente “coisa nenhuma”, mas que, no entanto, se manifesta de todas as maneiras possíveis”

Padmasambava, séc VIII

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Agradecimentos

A existência de cada coisa distinguível no mundo surge através de alguma interação. Assim, eu não poderia me sentir o executor de qualquer coisa que seja. Esse trabalho é um resultado natural de todos aqueles que cruzaram seus caminhos até aqui e deve ser celebrado como algo manifesto conjuntamente. Por isso vou evitar apontar nomes, certo de que estaria cometendo um erro maior do que já estou comentendo agora deixando tantas lembranças especiais já esquecidas. Agradeço a presença, paciência e disponibilidade da minha querida orientadora professora Marlies nesses nove anos de trabalho conjunto. Aqui relembro a importância que outros mestres, acadêmicos ou não, tiveram para mim durante o processo do doutorado, em especial o professor Klaus Lunau. Agradeço também todo o aprendizado que meus colegas de laboratório me proporcionaram. Eu me sinto sempre como que caminhando e cantando em uma trilha que foram eles que abriram no peito em uma mata bastante densa. Agradeço especialmente aos colaboradores de cada trabalho apresentado nesta tese, todos os textos apresentados aqui são de vocês também. Agradeço aos membros da banca, pré-banca e todos aqueles que leram alguma parte de algum texto que está sendo aqui apresentado e deixaram suas contribuições. Agradeço aos meus familiares e todos aqueles que compartilharam minha vida comum no período do doutorado. Agradeço também aos meus amigos da alma, cujos laços se formaram a partir de relações não-consanguíneas. Estas pessoas são as grandes referências que dão sentido a minha existência. Viver para mim não é nada a mais que ter vocês ao meu lado. Também agradeço a todo o pessoal do Departamento de Botânica e do Laboratório de Análises Genética e Molecular na Unicamp e do Institute of Sensory Ecology em Duesseldorf na Alemanha por disponibilizarem o espaço fisíco e intelectual para minha formação acadêmica. Agradeço aos Parques, seus gestores e funcionários, que permitiram e facilitaram a coleta de dados no campo. Por fim, agradeço as agências de fomento dos trabalhos aqui expostos, especialmente a Fapesp (processo 2010/51494-5 e 2012/50425-5) e FAEPEX (Projeto 519.292 - Auxílio 588/11).

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Introduction

A reproductive strategy could be understood as an organismal evolved complex of traits, which is determinant for its reproduction. Therefore, such strategies are built from several morphological and physiological traits in the life history of plants, each of them interfering somehow in the specimen fitness (Doust 1989). Moreover, these strategies must be determined by the energy allocation patterns in space and time (Thompson 1975). In general, there are two non-excluding causes of reproductive strategies: developmental constraints and evolutionary forces, such as the natural selection, being this one of the most investigated in plant reproduction studies (Doust 1989). A typical example of adaptive plant reproductive strategy is the solution to the “pollen dilemma”. In plants that offer just pollen as reward, the pollen grains have two fundamental roles: be the transport unit of the male gametes in plant reproduction and feed the adults or larvae of flower visitors (Thorp 1979; Harder and Thomson 1989; Westerkamp 1996; Lunau et al. 2014). Therefore, in such pollen-rewarded plants, many floral traits are interpreted as protection strategies of this valuable resource against flower visitors. Some possible solutions to the pollen dilemma are: pollinaria produced by orchids (Johnson and Edwards 2000), pollen deposition in safety sites in bee body (Westerkamp and Claßen-Bockhoff 2007), toxic pollen (Detzel & Wink 1993; Roulston & Cane 2000; Praz et al. 2008) and spines on the pollen exine which difficult the pollen collection by bees (Lunau 2014). The major aim of this thesis is to present and discuss different reproductive strategies in Melastomataceae with different approaches. The common axis of the thesis was the use of species of Melastomataceae family as study model. This plant family comprehends 166 genera and about 4500 lianas, shrubs, herbs and tree species occurring in forests, savannahs, riparian forests and disturbed areas in the tropical regions (Clausing & Renner 2001, Renner 1993). In Brazil, there are 65 genera and about 1300 species (Renner 1993, Goldenberg et al. 2012). The most important diagnostic trait for this family is the opposed leaves with acrodromous nervures and the anthers with poricidal dehiscence, being this of major relevance for this study. 2

The typical structure of the anthers in the Melastomataceae family makes the pollen grains (often the only reward) available just for bees able to buzz their wing muscles. Therefore, the evolutionary history of this family is strictly associated with a bee pollination system called “buzz pollination” (Buchmann 1983). In this sense, different reproductive strategies should be favoured in this family to avoid pollen wastage by bee collection and solve the pollen dilemma. As an example of a reproductive strategy interpreted as a solution to the pollen dilemma in this family is the recurrent appearance of anthers of different sizes (heteranthery) in the tribes Melastomeae and Microlicieae. These anthers would have a partition function, splitting the total amount of pollen grains in two portions: one to feed the bees larvae and the other to be used in the pollination process. Charles Darwin called this idea “division of labour” after the suggestion made by Fritz Müller and his brother Hermann Müller (Vallejo-Marín et al. 2009, Luo et al. 2008). Another possible solution of the pollen dilemma in this family is the relatively recent reported nectar production in some species of the genus Miconia, which would function as resource to pollinators other than bees, increasing the visitor spectra (Goldenberg & Sheperd 1998, Varassin et al. 2008, Santos et al. 2010, Kriebel & Zumbado 2014). Different reproductive strategies in the family Melastomataceae should be favoured as solutions of the pollen dilemma not only in intra-flower level. Therefore, we propose to describe and analyze some reproductive strategies and their consequences in different study cases. In the first chapter, we preliminarly describe the reproductive phenology of Melastomataceae species occurring in two biodiversity hotspots showing that such reproductive strategies might be determinant in flowering and fruiting. The second chapter shows how the nectar production is related to the increase in abundance and richness of floral visitors in Miconia theizans and we discuss how this strategy may increase the female reproductive success in such plants. In the third chapter, we describe the genetic structure of two populations of Tibouchina pulchra (which has heterantherous and high herkogamic flowers) occurring in two extremes of an elevational gradient and relate it to differences in pollination dynamics of each region. At last, in the fourth chapter we discuss the phenomenon of floral colour change in Tibouchina pulchra and how it would be favoured by increasing the attractiveness across long distances and directing the pollinator to new flowers avoiding pollen loss. As an introduction to this chapter, we present a review on the cognitive ecology of pollination. 3

References Buchmann SL. 1983. Buzz pollination in angiosperms. In: Jones CE, Little RJ (eds) Handbook of experimental pollination biology, 1st edn. Van Nostrand Reinhold, New York, pp 73–113. Clausing G & Renner SS. 2001. Molecular phylogenetics of Melastomataceae and Memecylaceae: implications for character evolution. American Journal of Botany 88(3): 486–498. Detzel A & Wink M. 1993. Attraction, deterrence or intoxication of bees (Apis mellifera) by plant allelochemicals. Chemoecology 4: 8–18. Doust JL. 1989. Plant reproductive strategies and resource allocation. Trends in Ecology and Evolution 4 (8): 230 – 234. Goldenberg R & Shepherd GJ. 1998. Studies in reproductive biology of Melastomataceae in “cerrado” vegetation. Plant Systematics and Evolution 211: 13 – 29. Goldenberg R, Baumgratz JFA & Souza MLDR. 2012. Taxonomia de Melastomataceae no Brasil: retrospectiva, perspectivas e chave de identificação para os gêneros. Rodriguésia 63: 145-161. Harder LD, Thomson JD. 1989. Evolutionary options for maximizing pollen dispersal of animal-pollinated plants. The American Naturalist 133: 323–344. Johnson SD & Edwards TJ. 2000. The structure and function of orchid pollinaria. Plant Systematics and Evolution: 222: 243–269. Kriebel R & Zumbado MA. 2014. New reports of generalist insect visitation to flowers of species of Miconia (Miconieae: Melastomataceae) and their evolutionary implications. Brittonia DOI 10.1007/s12228-014-9337-1. Lunau K, Piorek V, Krohn O & Pacini E. 2014. Just spines—mechanical defense of malvaceous pollen against collection by corbiculate bees. Apidologie. DOI: 10.1007/s13592-014-0310-5. Luo Z, Zhang D & Renner SS. 2008. Why two kinds of stamens in buzz-pollinated flowers? Experimental support for Darwin’s division-of-labour hypothesis. Functional Ecology 22: 794–800. Praz CJ, Müller A & Dorn S. 2008. Specialized bees fail to develop on non-host pollen: do plants chemically protect their pollen? Ecology 89: 795–804. 4

Renner SS. 1993. Phylogeny and classification of the Melastomataceae and Memecylaceae. Nordic Journal of Botany 13:519-540. Roulston, TH & Cane JH. 2000. Pollen nutritional content and digestibility for animals. Plant Systematics and Evolution 222: 187–209. Santos APM, Romero R & Oliveira PEAM. 2010. Biologia reprodutiva de Miconia angelana (Melastomataceae), endêmica da Serra da Canastra, Minas Gerais. Revista Brasileira de Botânica 33 (20): 333-341. Thompson JN. 1975. Reproductive strategies: a review of concepts with particular reference to the number of offspring produced per reproductive period. Biologist 57: 14-25. Thorp RW. 1979. Structural, behavioral, and physiological adaptations of bees (Apoidea) for collecting pollen. Annals of the Missouri Botanical Garden 66: 788–812. Vallejo-Marín M., Manson JS, Thomson JD & Barrett SCH. 2009. Division of labour within flowers: heteranthery, a floral strategy to reconcile contrasting pollen fates. Journal of Evolutionary Biology 22: 828 – 839. Varassin IG, Penneys DS & Michelangeli FA. 2008. Comparative anatomy and morphology of nectar-producing Melastomataceae. Annals of Botany 102: 899–909. Westerkamp C. 1996. Pollen in bee-flower relations. Some considerations on melittophily. Botanica Acta 109: 325–332. Westerkamp C & Claßen-Bockhoff R. 2007. Bilabiate flowers - the ultimate response to bees? Annals of Botany 100: 361–374.

Chapter I

Preliminary insights into the reproductive phenology of Melastomataceae species from two Brazilian biodiversity hotspots

Vinícius L. G. Brito1*, Vanessa G. Staggemeier2, Fabiano Rodrigo da Maia3, Fernando A. O. Silveira4, Carla Magioni Fracasso1, José Pires Lemos-Filho4, G. Wilson Fernandes5, Renato Goldenberg3, L. Patrícia C. Morellato2 and Marlies Sazima6

1. Programa de Pós Graduação em Biologia Vegetal, Unicamp. 2. Laboratório de Fenologia, Departamento de Botânica, UNESP- Rio Claro 3. Departamento de Botânica, UFPR 4. Departamento de Botânica, UFMG 5. Laboratório de Ecologia Evolutiva e Biodiversidade, Departamento de Biologia Vegetal, UFMG 6. Laboratório de Biossistemática, Departamento de Biologia Vegetal, Unicamp

*Correspondence: [email protected]

Running title: Reproductive phenology of Melastomataceae

Abstract

Flowering and fruiting are crucial events in the life history of plants, and both are critical to reproductive success with ecological and evolutionary consequences. In general, the timing of plant reproductive phenology is first related to climatic factors and then shaped by biotic interactions with pollinators and dispersers. In Melastomataceae, a dominant family in the Neotropical region, different reproductive strategies from biotic pollination to apomixy and from dry, self-dispersed fruits to fleshy, vertebrate-dispersed fruits have evolved and it may affect the reproductive phenological patterns. In this study, we described in a wide geographical scale the flowering and fruiting phenology of 81 Melastomataceae species occurring in two biodiversity hotspots: the Atlantic forest and Cerrado. We aim to disentangle the role of abiotic and biotic factors defining flowering and fruiting times considering the contrasting reproductive systems. We found high values of synchronization in flowering and fruiting phenology in Atlantic rainforest and Cerrado and a weak seasonality in flowering of species dependent of pollinators to set their fruits. Such results may indicate that the species reproductive systems is relatively more important for reproductive phenology in Melastomataceae than the differential environmental climatic conditions.

Key words: abiotic factors, Atlantic forest, Cerrado, dispersal, flowering, fruiting pollination, zoochory

Introduction Flowering and fruiting are crucial events in the life history of plants, and both are critical to reproductive success with ecological and evolutionary consequences for plants (Ratcke & Lacey 1985, Wang & Smith 2002, Wolkovich et al. 2014). Climatic variables such as temperature, rainfall and day length are considered the major factors driving plant phenology in the tropics (Opler et al., 1976; Fenner, 1998; Zimmerman et al., 2007, Morellato et al. 2000, Borchert et al. 2005, Calle et al. 2010). On the other hand, when seasonal environmental conditions are not restrictive to plant growth and reproduction, the biotic factors such as the abundance of pollinators and seed dispersers, might shape phenological patterns (Ollerton & Lack, 1992; van Schaik et al. 1993; Morellato et al., 2000; 2013, Griscom et al., 2007). The phenological reproductive response is tied to climatic variables because these favour intrinsic plant traits like germination, photosynthesis, and growth rate (van Schaik et al. 1993). Therefore, the production of flowers and fruits undergoes temporal variation, especially in seasonal environments, and climate may define the timing and length of growth and reproductive seasons (van Schaik et al. 1993, Morellato et al. 2013). Such seasonal rhythms in plants may favour interactions with pollinators and dispersers directly responsible for their reproduction success. Therefore, biotic or abiotic final selective forces may define the distribution of plant reproductive phenology across the temporal niche (Wolkovich et al. 2014). The Melastomataceae comprises 4,200–4,500 species all over the world in the tropic and subtropic regions, and it is well represented in the Neotropics, with approximately 3,000 species (Renner 1993). In the Brazilian Atlantic rainforest and Cerrado, both endangered hotspots of biodiversity (Myers et al 2000), Melastomataceae stands out as one of the most important family in species diversity, area of occurrence and endemism (Silveira et al. 2013). Different reproductive strategies have evolved in this family, from biotic pollination to apomixy (Goldenberg & Shepherd 1998, Goldenberg & Varassin 2001) and from dry, self-dispersed fruits to fleshy vertebrate-dispersed fruits (Clausing et al 2000). The dominant biotic pollination system in Melastomataceae is dependent on buzzing bees, favoured by the poricide anthers and highly herkogamous flowers (Renner 1989, Romero & Martins 2002, Brito & Sazima 2010). On the other side, there are self-pollinated or apomictic species that do not require pollinators for fruit set 8

(Goldenberg & Shepherd 1998, Goldenberg & Varassin 2001). Considering the dispersal system, the majority of species is zoochoric, with seeds dispersed mainly by birds (Silveira et al. 2013), and also ants (Lima et al. 2013), while non-biotic seed dispersal systems include the wind, water or gravity (Renner 1989, Kessler-Rios & Kattan 2012, Maruyama et al. 2007, Silveira et al 2013, Pizo & Morellato 2002). Therefore, this ecological diversity in pollination and dispersal systems makes this family an interesting model to untangle the role of abiotic and biotic vectors triggering plant reproductive phenology. If we consider the three major tribes of Neotropical Melastomataceae, Miconieae presents many species that do not rely on pollinators to produce fleshy fruits mainly dispersed by birds (Goldenberg & Shepherd 1998, Santos et al. 2012), while Melastomeae and Microliceae are mainly dependent on pollinators to produce fruits but seeds are self-dispersed or dispersed by the wind (Brito & Sazima 2010) (Figure 1). In this study, we describe the flowering and fruiting phenology of 81 species of Melastomataceae occurring in two biodiversity hotspots with contrasting environmental conditions: the rainy Atlantic forest and the seasonally dry ecosystem Cerrado. We aim to disentangle the role of abiotic and biotic factors defining flowering and fruiting times considering the contrasting reproductive systems present in Melastomataceae. We expect that the species reproductive systems will be relatively more important for reproductive phenology in Melastomataceae than the differential environmental seasonality of each hotspot.

Materials and methods

Study areas, climate and vegetation

The study was conducted in five areas: two in the Atlantic forest in the Parque Estadual da Serra do Mar in São Paulo State (Figure S1), and three Cerrado savannah-like formations (Figure S2); one in the Parque Nacional da Serra da Canastra and one in the Espinhaço Range, both at the Minas Gerais State, and other in the Parque Estadual do Guaterlá, Paraná State. We collected the historical (Figure S3) and actual climatic information (Figure S4) in different sources and periods (Table S1). The day length for each area was calculated according to Pereira et al. (2001). The description of each area is given below. 9

Parque Estadual da Serra do Mar – Núcleo Picinguaba (NP): it is located in the municipality of Ubatuba, São Paulo state, on the coastal plain (23o20’S, 44o50’W; 0 – 50 m a.s.l.). The climate is classified as tropical rainy without a dry season, Af according to Köppen-Geiger climate classification (Alvares et al. 2014) with a super-humid season from October to April (Figure S3 A). The annual precipitation is 2,519mm and the mean temperature is 21.9oC. The vegetation is classified as “typical” Atlantic rainforest with trees 15-25m high including a high diversity of species (Oliveira-Filho & Fontes 2000). The most species-rich tree families are Myrtaceae, Rubiaceae, Fabaceae and Lauraceae (Joly et al. 2012, Sanchez et al. 1999), and the understory contains shrubs and herbs predominantly from the families Rubiaceae, Myrtaceae, Melastomataceae, Amaranthaceae, Musaceae and Piperaceae (Morellato et al. 2000).

Parque Estadual da Serra do Mar – Núcleo Santa Virgínia (NSV): it is located in the municipality of São Luís do Paraitinga at the top of the Serra do Mar mountain ranges (23o20’S, 45o50’W; 870 to 1,100 m a.s.l). The regional climate is subtropical humid without a dry season and with temperate summer, Cfb according to Köppen-Geiger climate classification (Alvares et al. 2014); January and February are the wettest months and July and August the less rainy months (Figure S3 B). The annual precipitation is 1,193mm and the mean temperature is 20.0oC. The vegetation is also a “typical” Atlantic rainforest (Oliveira-Filho & Fontes 2000) and Myrtaceae, Lauraceae, Monimiaceae and Rubiaceae are the richest tree families (Padgurschi et al. 2011).

Parque Nacional da Serra da Canastra (PNC): it is located at the south-west portion of Minas Gerais state (20º00´ - 20º30´S; 46º15´ - 46º00´W, 800 to 1400 m a.s.l.). This study was conducted at the campo rupestre formation which has a humid subtropical climate with dry winter and a temperate summer, Cwb according to Köppen-Geiger climate classification (Alvares et al. 2014). November, December and January are the wettest months and June, July and August the driest ones (Figure S3 C). The annual precipitation is 1,574mm and the mean temperature is 20.4oC. The most important families vegetation are Fabaceae, Malpighiaceae and Myrtaceae (Romero & Nakajima 1999).

Espinhaço range – Serra do Cipó (SC): it is located at the southern portion of the Espinhaço Range, a mountain chain spanning 1000 Km in length in eastern Brazil with 10 altitudes varying between 900 and 1700m (19º17’22”S; 43º35’18”W; 1260 m a.s.l.) (Giulietti et al. 1997). The weather is subtropical wet with a dry winter and a temperate summer, Cwb according to Köppen-Geiger climate classification (Alvares et al. 2014). There are two well-defined seasons: a rainy season from October to April and a dry season from May to September (Figure S3 D). Fire is a recurrent phenomenon in this area during the dry season. The annual precipitation is 1,328mm and the mean temperature is 20.9oC. The vegetation is also characterized as campo rupestre with Asteraceae, Poaceae, Orchidaceae and Fabaceae as important families (Giulietti et al. 1997).

Parque Estadual do Guartelá (PEG): the park is located at Tibagi municipality, Paraná state (24°39’10”S e 50°15’25”W, 800 – 1150m a.s.l.). Climate is classified as subtropical wet with a temperate summer, Cfb according to Köppen-Geiger climate classification (Alvares et al. 2014), with November, December and January as the wettest month and July and August the dryest ones (Figure S3 E). The annual precipitation is 1,629mm and the mean temperature is 18.5oC. However, PEG is known by harbouring a vegetational mosaic including semideciduos forests, cerrado sensu stricto and specifically campo rupestre in high altitudes mainly because there is an microscale variation in climate and soil (Carmo et al. 2006). The vegetation sampled was predominantly campo rupestre, and Fabaceae and Myrtaceae are the most abundant families (Carmo et al. 2006). The dry season can last four months in the studied area (Fig S4 C).

Phenological sampling and reproductive system

Detailed phenological data for all areas were collected monthly for periods between 12 to 36 months (Table 1). The collection protocols differed among areas: at NP and NSV a random sample of individuals was observed each month, while at PNC, SC and PEG the same tagged individuals were observed throughout the sampling time. About 1200 adult individuals of 81 Melastomataceae species (Table S2) were observed over an average of 29.4 months (SD±10.14 months). The majority of common species and some rare species of each area were sampled and voucher specimens are deposited at the following herbaria: BHCB (Universidade Federal de Minas Gerais), UEC (Universidade Estadual de 11

Campinas), and UPCB (Universidade Federal do Paraná). Flowering (opened flowers) and fruiting (mature fruits) phenophases were monitored and quantified using two methods: qualitative (absence-presence) in SC and PEG, and semi-quantitative (4 interval classes; Fournier 1974) in NP, NSV and PNC (Table 1). We combined species phenology by vegetation type and per species, thus NSV and NP summed 34 Melastomataceae species occurring in Atlantic rainforest while PNC, SC and PEG summed 54 species in Cerrado; seven species co-ocurred in both vegetation type. Since the temporal sampling was not the same for all studies and number of species sampled in the first months was variable we just used the best time frame sampled to compare the phenology between vegetations: 27 months for NSV and NP (June 2011 to May 2013; 32 to 34 species) pooled (by monthly average) for a 12 month period, and 12 months for PEG (June 2011 to May 2012), SC (June 2009 to May 2010) and PNC (June 2005 to May 2006).

We described the breeding system of each species by accessing the fruit set from bagged and unbagged flowers and also checking the literature (adapted from Radford 1974). Then, we classified each species as dependent or independent of pollinators to set fruits (Table S2). In addition, we extrapolated the breeding system results for those species without information that were repeatedly sampled in different areas in our study (Table S2). The species were also classified by their fruit type based on the presence of pulp as resource to frugivores. The fruits of Miconieae were considered fleshy, while the fruits of Melastomeae, Microliceae and Bertolanieae were considered dry. We compared phenological pattern by reproductive system grouping the species by their breeding system (dependent or independent of pollinators to set fruits) or by the fruit dispersal system (biotic or abiotic). We also compared the phenology using the data for the 12 consecutive months with highest number of species sampled (86 to 88 taxa monthly observed). When the same species co-occurred in both vegetation types (Atlantic rainforest and Cerrado), we considered them as two different unities because the phenology could be affected by climate resulting in a different phenological strategy and, as a result, we have 88 taxa in this comparison instead of 81 species.

Seasonality

We used circular statistics to test the existence of seasonality in flowering and fruiting of Melastomataceae as described in Morellato et al. (2000, 2010). Circular statistics are useful when reproduction occurs continuously over the year with no logical starting point (Morellato et al. 2010). The year is represented as a 360 degrees circle with an arbitrary origin and each month corresponds to 30 degrees arcs. By convention, 01 January corresponds to 0 o or 360o (Zar 2010). We calculated the mean angle corresponding to the mean peak date, the angular deviation and the mean length of the mean (r vector) (Morellato et al. 2010). The r vector corresponds to the concentration around the mean angle and is considered a measure of the degree of seasonality varying from 0 (no seasonality) to 1 (when all the peaks occur in one date) as in Morellato et al. (2000). We performed Rayleigh test (Z) to test the significance of the mean angle and, as a correlate, the occurrence of seasonality (Morellato et al. 2000, 2010) using the percentage of species reproducing per month in two levels, first for each vegetation type (Atlantic rainforest or Cerrado) and second for each reproductive system. Species with undetermined pollination system were excluded from this analysis. The “Rayleigh´s z” is used to test the null hypothesis of no mean direction, which means that the percentages are uniformly distributed around the circle (Morellato et al. 2010).

Results

We followed the flowering and fruiting phenologies of ca. 1200 individuals in 81 species of Melastomataceae, including 37 species of the tribe Miconieae, 24 species of Melastomeae, 19 species of Microlicieae and 1 species of Bertolonieae. All the areas presented species with both pollination and seed dispersal systems, except PNC, in which all the species belong to Melastomeae or Microlicieae (Figure 2) which are dependent of pollinators to set their fruits and have abiotic seed dispersal system. Considering the common species in all the areas, the majority of species of the tribe Miconieae (64%) presented fruit set independent of pollinators, while in the tribe Melastomeae and Microlicieae we found the inverse pattern, with the majority of species presenting fruit set dependent on pollinators (61% and 65% respectively) (Figure 2). On the other hand, all the 13 species of Miconieae present fleshy fruits potentially dispersed by birds, while all species of Melastomeae and Microlicieae have dry fruits with abiotic dispersal system (Figure 2). The raw phenology data and climatic conditions during the period of study for each area is shown in Figure S4. We observed 40% to 70% of species in anthesis in any given month in Atlantic rainforest and 40 to 60% in Cerrado (Figure 3). Melastomataceae fruits were also available all year long with higher synchrony values among species recorded for Atlantic forest (70 to 90%), while in Cerrado, 50 to 75% of species produced fruits in any given month (Figure 3). The majority of the Melastomataceae species which depend on pollinators to set fruit (ca. 58-62%) flowered from March to May, while more than 50% of species independent of pollinators flowered throughout the year (Figure 4). When considering the fruit production, species showed high values of synchrony (more than 54%) during all the year regardless their dispersal system (fleshy or dry fruits; Figure 4). There was no seasonality for flowering in either the Atlantic forest (Z: 5.81, p=0.003, r=0.09, mean angle: 46.8°; Figure 5) or the Cerrado (Z: 0.08, p=0.9, r=0.01). Similarly, the fruiting pattern observed for the Atlantic forest was not seasonal (Z: 1.77, p=0.17, r=0.04) while Cerrado was weakly seasonal (Z: 3.6, p=0.027, r=0.07, mean angle: 268.9°; Figure 5). When considering the reproductive system, flowering patterns diverged: species dependent of pollinators were seasonal (Z: 16.69, p<0.001, r = 0.17, mean angle: 119.1°; Figure 6), while the species independent of pollinators did not present seasonality in the flowering pattern (Z: 0.95, p=0.3, r = 0.03; Figure 6). Dry and fleshy fruited species were not seasonal in the fruiting pattern, therefore species were reproducing all the time without a defined peak of activity (p>0.28; Figure 6).

Discussion Our results on the reproductive phenology of Melastomataceae indicate certain constancy in the production of flowers and fruits throughout the year, regardless the different environmental seasonality existing between Atlantic rainforest and Cerrado. This suggests that macroclimatic factors, which traditionally define vegetations, probably are not limiting Melastomataceae reproduction. However, future detailed analysis of correlation between historic climatic factors, such as temperature, rainfall and day length, and the reproductive phenology coould shed light in the abiotic factors influencing reproductions of Melastomataceae species in these areas. 14

The flowering of Melastomataceae that depend on pollinators to set their fruits was seasonal and occured mostly from February to June. These species belong mostly to Melastomeae and Miconieae and present anthers of different size (heteranthery) associated with herkogamy, which prevents self-pollination. Their poricidal anthers prevent the access of the pollen resource by non-vibratory animals, and the pollination process relies only on vibratory bees (Romero & Martins 2002, Brito & Sazima 2010). Therefore, interspecific relationships mediated for shared bees, like facilitation (Ratcke 1983, Waser & Real 1979), should have molded this pattern in flowering of these species. In fact, all Tibouchina species occurring at the NP flowered during the wet season and share the same species of pollinator Bombus morio (Brito, unpublished data). In this sense, flowering phenology of such species should be favoured in periods when the bee pollinators are more available (Freitas & Sazima 2006). On the other hand, species independent on pollinator to set their fruits showed no seasonality in their flowering time. Since pollinators are not necessary for fruit set, such species should be phenologically unconstrained, espetially in areas where the water supply is constant. This result is reinforced by the continuous flowering patterns found for eight species with pollinator-independent pollination systems, including the genera Clidemia, Leandra and Miconia regardless of their habitat. Melastomataceae fleshy fruits are primarily dispersed by birds but also various animals, including mammals like bats and monkeys (Renner 1989, Galetti & Stotz, 1996, de Figueiredo & Longatti 1997, Garcia et al., 2000, Lapenta & Procópio-de-Oliveira, 2008). The secondary seed dispersers of Miconieae are predominantely ants, but it could also be turtles, lizards and tapirs (Renner 1989, Silveira et al. 2013). Therefore, the fruiting phenology of animal-dispersed species should not be constrained along the year by the availability of biotic vectors. Our results are in accordance to this, since we found no fruiting seasonality for Miconiae species. Several studies have reported segregated fruiting pattern of fleshy fruit species of Melastomataceae (Snow 1965, Hilty 1980, Poulin et al. 1999). However, all these studies were conducted just with Miconia species in forested area with low climatic seasonality. On the other hand, a study conducted in the Andean forest, under marked climatic seasonality, indicates that the fruiting of Melastomataceae species is aggregated, resulting in high values of fruiting overlap (Kessler-Rios & Kattan 2012). In this sense, future overlap analysis including biotically and abiotically dispersed Melastomataceae should be conducted to unveil the fruiting patterns of Melastomataceae 15 species, grouping species by specific seed dispersal vectors. The same analyses should be carried out considering the flowering phenology of species which are dependent and independent on pollinator to set their fruits. The reproductive phenology of Melastomataceae species occurring in Atlantic rainforest and Cerrado seemed to be related to interactions with pollinators and dispersers. However, reproductive phenological patterns can also be affected by the evolutionary history of species sharing a common ancestors and may present some level of phylogenetic constraint (Kochmer & Handel 1986, Staggemeier et al. 2010). Closely related species should not be treated as statiscally independent units and the evolutionary information must be taken into account in phenological studies. However, the integration of phylogenies to investigate the phylogenetic constraints on plant phenology, in conjunction with other phenological predictors, is recent and still scarce (Staggemeier et al. 2010; Davis et al. 2010, 2013). Future analysis based in this database of Melastomataceae species, should take such phylogenetic information into account.

Acknowledgments

The authors thank the invaluable assistance of many friends in different periods of field work. VLGB and VGS were supported by FAPESP (grant # 2010/51494-5, # 2012/51425-5 and # 2014/13899-4). MS, LPCM, GWF receive a research productivity fellowship from CNPq.

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Table 1. Sources of phenological information for Melastomataceae in five areas of Brazilian ecosystems: Parque Estadual da Serra do Mar – Núcleo Picinguaba (NP), Parque Estadual da Serra do Mar – Núcleo Santa Virgínia (NSV), Parque Nacional da Serra da Canastra (PNC), Serra do Cipó (SC) and Parque Estadual do Guartelá (PEG). Sampling period, number of species and individuals observed and methods for quantifying phenophases are detailed. 0-4: Fournier with four classes (1: 1-25% of the crown in activity; 2: 26 to 50%; 3: 51 to 75%; and 4: 76 to 100%) and, 0-1: absence or presence of reproductive activity.

Phenological observations Area Sampling period Method N spp N ind

NP September 2010 to August 2013 0-4 20 200

NSV September 2010 to August 2013 0-4 16 160

PNC January 2005 to October 2007 0-4 10 100

SC June 2009 to May 2010 0-1 28 477

PEG March 2011 to August 2013 0-1 26 260

Figure 1. Reproductive systems in Melastomataceae species. In Microliceae and Melastomae the gene flow occurs mainly during the flowering phase when the pollen is carried among plants by insects. While in Miconiae tribe the gene flow occurs mainly during the fruiting phase when the biotic vectors disperse the seeds away from parental plant.

Figure 2. Porcentage of species in each area and in each Melastomataceae tribe showing different reproductive strategies. NA´s – data not available.

Figure 3. Percentage of species of Melastomataceae flowering (A) and fruiting (B) during the year in Atlantic rainforest and Cerrado.

Figure 4. Percentage of Melastomataceae species flowering (A) and fruiting (B) during the year according to their breeding and dispersal systems.

Figure 5. Seasonality patterns in the percentage of Melastomataceae species in flowering and fruiting grouped by area. The year is represented as a circle and each dot represents 5% of species presenting the phenophase. Arrow indicates the mean angle (date) of the phenophase when there was significance in the Rayleigh test for seasonality. 29

Figure 6. Seasonality patterns in the in the percentage of Melastomataceae species in flowering and fruiting grouped by the reproductive system. The year is represented as a circle and each dot represents 5% of species presenting the phenophase. Arrow indicates the mean angle (date) of the phenophase when there was significance in the Rayleigh test for seasonality. 30

Supplementary Material

Preliminary insights into the reproductive phenology of Melastomataceae species from two Brazilian biodiversity hotspots

*Correspondence: [email protected]

Running title: Reproductive phenology of Melastomataceae

Table S1. Source of climate data. Embrapa - Empresa Brasileira de Pesquisa Agropecuária; SIMEPAR – Sistema Meteorológico do Paraná; IBAMA - Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis. Studied areas: NP: Parque Estadual da Serra do Mar - Núcleo Picinguaba, NSV: Parque Estadual da Serra do Mar – Núcleo Santa Virgínia, PNC: Parque Nacional da Serra da Canastra, SC: Serra do Cipó, PEG: Parque Estadual do Guartelá.

Area Data Source Location Period

Historical Embrapa 23.45 S / 45.07 W 1960 – 1990 NP Study Local station 23.35 S / 44.85 W 2010 – 2013

Historical Embrapa 22.91 S / 45.98 W 1941 – 1970 NSV Study Local station 23.34 S / 45.15 W 2010 – 2013

Historical Embrapa 19.57 S / 46.93 W 1971 – 1990 PNC Study IBAMA 20.25 S / 46.62 W 2004 – 2007

Historical Embrapa 19.47 S / 44.25 W 1961 – 1990 SC Study Local station 19.34 S / 43.53 W 2008 – 2010

Historical Embrapa 24.33 S / 50.62 W 1971 – 1990 PEG Study SIMEPAR 24.33 S / 50.62 W 2011 – 2012

Table S2. Species, number of individuals observed for phenological sampling in each area, pollination system (PS; I – independent on pollinator to set fruit; D – dependent on pollinator to set fruit), fruit type (FT; D – dry; F – fleshy) and sources used to classify the pollination system of Melastomataceae species sampled in this study. NP: Parque Estadual da Serra do Mar, Núcleo Picinguaba; NSV: Parque Estadual da Serra do Mar, Núcleo Santa Virgínia; PNC: Parque Nacional da Serra da Canastra; SC: Serra do Cipó; PEG: Parque Estadual do Guartelá

Number of individuals PS Tribe Species PS FT NP NSV PNC SC PEG information

Bertolonieae Bertolonia sp. 1 Raddi 15-20 - - - - - D -

Tibouchina cf. langsdorffiana Melastomeae 5 - - - - D D This study (Bonpl.) Baill.

Melastomeae Acisanthera quadrata Pers. - - - - 10 - D -

Comolia sertularia (DC.) Melastomeae - - - 20 - - D - Triana

Melastomeae Comolia stenodon Triana - - - 15 - - D -

Santos et al. Melastomeae Macairea radula (Bonpl.) DC. - - 10 15 - D D 2012

Marcetia taxifolia (A.St.-Hil.) Santos et al. Melastomeae - - - 20 - D D DC. 2012

Tibouchina cardinalis (Humb. Melastomeae - - - 20 - - D - & Bonpl.) Cogn.

Tibouchina clavata (Pers.) Melastomeae 10-15 - - - - I D This study Wurdack

Tibouchina clinopodifolia Melastomeae - 10-15 - - - I D This study Cogn.

Melastomeae Tibouchina debilis Cogn. - - - - 10 - D -

Tibouchina fothergillae Melastomeae (Schrank & Mart. ex DC.) 5-10 10-15 - - 10 D D This study Cogn. 33

Table S1. Continuation Number of individuals PS Tribe Species PS FT NP NSV PNC SC PEG information Tibouchina frigidula (DC.) Santos et al. Melastomeae - - 10 - - D D Cogn. 2012

Tibouchina granulosa (Desr.) Melastomeae 5-10 - - - - D D This study Cogn.

Tibouchina hatschbachii Melastomeae - - - - 10 - D Maia 2013 Wurdack

Tibouchina herincquiana Melastomeae - - - - 10 - D - Cogn.

Tibouchina heteromalla Santos et al. Melastomeae 5-10 - 10 20 10 D D (D.Don) Cogn. 2012

Tibouchina martialis (Cham.) Melastomeae - - - - 10 - D - Cogn.

Brito & Melastomeae Tibouchina pulchra Cogn. 45 45 - - - D D Sazima 2012

Melastomeae Tibouchina reitzii Brade - 3 - - - D D This study

Melastomeae Tibouchina riedeliana Cogn. - - - - 10 - D -

Melastomeae Tibouchina sellowiana Cogn. - - - - 10 I D Maia 2013

Melastomeae Tibouchina sp. 1 Aubl. - 5-10 - - - I D This study

Tibouchina stenocarpa Melastomeae (Schrank & Mart. ex DC.) 2 - 10 - - D D This study Cogn.

Miconieae Clidemia biserrata DC. 10-15 - - - - I F This study

Miconieae Clidemia hirta (L.) D.Don 5-10 - - - - I F This study

Miconieae Clidemia urceolata DC. 5-10 - - 15 - I F This study

Miconieae Leandra aurea (Cham.) Cogn. - - - 15 10 I F Maia 2013

Table S1. Continuation Number of individuals PS Tribe Species PS FT NP NSV PNC SC PEG information Leandra australis (Cham.) Miconieae - - - - 10 I F Maia 2013 Cogn.

Leandra erostrata (DC.) Miconieae - - - - 10 - F - Cogn.

Miconieae Leandra microphylla Cogn. - - - - 10 I F Maia 2013

Leandra polystachya (Naudin) Miconieae - - - - 10 I F Maia 2013 Cogn.

Leandra purpurascens (DC.) Miconieae - - - - 10 I F Maia 2013 Cogn.

Miconieae Leandra reversa (DC.) Cogn. 5-10 - - - - - F -

Miconieae Leandra sp. 1 Raddi - 1 - - - - F -

Miconieae Leandra variabilis Raddi - 10-15 - - - I F This study

Leandra xanthocoma Miconieae - 10-15 - - - I F This study (Naudin) Cogn.

Miconieae Miconia albicans (Sw.) Triana 10-15 - - 20 10 I F This study

Miconieae Miconia alborufescens Naudin - - - 20 - - F -

Miconieae Miconia cabucu Hoehne - 10-15 - - - - F -

Miconia cf. nervosa (Sm.) Miconieae 5-10 - - - - D F This study Triana

Miconieae Miconia chartacea Triana - 5-10 - - - - F -

Miconieae Miconia cinerascens Miq. - - - - 10 - F -

Miconieae Miconia cipoensis R.Goldenb. - - - 15 - - F -

Miconieae Miconia corallina Spring - - - 15 - - F - 35

Table S1. Continuation Number of individuals PS Tribe Species PS FT NP NSV PNC SC PEG information

Miconieae Miconia dodecandra Cogn. 3 - - - - I F This study

Santos et al. Miconieae Miconia ferruginata DC. - - - 20 - I F 2012

Miconia hyemalis A.St.-Hil. & Miconieae - - - - 10 I F Maia 2013 Naudin

Miconia ibaguensis (Bonpl.) Miconieae 10-15 - - - - I F This study Triana

Miconieae Miconia irwinii Wurdack - - - 20 - - F -

Miconia ligustroides (DC.) Miconieae - - - - 10 I F Maia 2013 Naudin

Goldenberg & Miconieae Miconia petropolitana Cogn. - - - - 10 I F Varassin 2001

Miconieae Miconia prasina (Sw.) DC. 5-10 - - - - I F This study

Miconia pusilliflora (DC.) Miconieae 5-10 - - - - - F - Naudin

Miconieae Miconia sellowiana Naudin - - - - 10 D F Maia 2013

Miconieae Miconia sp. 1 Ruiz & Pav. 5-10 - - - - - F -

Goldenberg & Miconieae Miconia stenostachya DC. - - - 15 - I F Shepperd 1998

Miconia theizans (Bonpl.) Miconieae - 10-15 - - 10 I F Maia 2013 Cogn.

Miconieae Miconia tristis Spring - 5-10 - - - - F -

Ossaea amygdaloides (DC.) Miconieae 5-10 - - - - I F This study Triana

Miconieae Ossaea sp. 1 DC. - 5-10 - - - I F This study

Table S1. Continuation Number of individuals PS Tribe Species PS FT NP NSV PNC information Cambessedesia espora (A.St.- Santos et al. Microlicieae - - 10 - - D D Hil. ex Bonpl.) DC. 2012

Cambessedesia hilariana Fracasso & Microlicieae - - - 20 - D D (Kunth) DC. Sazima 2004

Chaetostoma armatum Microlicieae - - - 20 10 D D Maia 2013 (Spreng.) Cogn.

Lavoisiera campos-portoana Microlicieae - - - 17 - - D - Barreto

Lavoisiera confertiflora Rich. Microlicieae - - - 20 - - D - ex Naudin

Microlicieae Lavoisiera cordata Cogn. - - - 20 - - D -

Lavoisiera imbricata (Thunb.) Santos et al. Microlicieae - - 10 20 10 D D DC. 2012

Microlicieae Lavoisiera pulchella Cham. - - - - 10 I D Maia 2013

Microlicieae Lavoisiera subulata Triana - - - 20 - - D -

Microlepis oleifolia (DC.) Microlicieae - 10-15 - - - I F This study Triana

Microlicia fulva (Spreng.) Microlicieae - - - 15 - - D - Cham.

Santos et al. Microlicieae Microlicia inquinans Naudin - - 10 - - D D 2012

Microlicieae Microlicia sp. 1 - - - 20 - - D -

Microlicieae Microlicia tetrasticha Cogn. - - - 20 - - D -

Microlicia viminalis (DC.) Santos et al. Microlicieae - - 10 - - D D Triana 2012

Rhynchanthera Microlicieae - 5-10 - - - D D This study brachyrhyncha Cham.

Rhynchanthera grandiflora Santos et al. Microlicieae - - - 15 - D D (Aubl.) DC. 2012 37

Table S1. Continuation

Number of individuals PS Tribe Species PS FT NP NSV PNC information Svitramia hatschbachii Santos et al. Microlicieae - - 10 - - D D Wurdack 2012

Trembleya parviflora (D.Don) Santos et al. Microlicieae - 10-15 10 20 10 D D Cogn. 2012

Figure S1. Studied sites at Atlantic forest vegetation: Núcleo Picinguaba (A-B) and Núcleo Santa Virgínia (C-D), Parque Estadual da Serra do Mar, SP, Brazil. Photos: Vinícius L. G. Brito (A-D). 39

Figure S2. Studied sites at Campo rupestre formations in Brazilian cerrado: Parque Estadual do Guaterlá, Tibagi, Paraná (A-C); Parque Nacional da Serra da Canastra(D-E) and Serra do Cipó, Minas Gerais (F-I) Photos: F. R. Maia (A-C), R. Morokawa (D-E), F. Silveira (F-I)

Figure S3. Climatic diagrams of Núcleo Picinguaba (A), Núcleo Santa Virgínia (B), Parque Nacional da Serra da Canastra (C), Serra do Cipó (D) and Parque Estadual do Guaterlá (E). Month are represented on the x-axis from June to July. The left x-axis and the black line represent the temperature (oC) and the right y-axis and red line represent the rainfall (mm).

Figure S4. Flowering (yellow bars) and fruiting (red bars) patterns for two Atlantic rainforest areas: NP - Núcleo Picinguaba (A) and NSV - Núcleo Santa Virgínia (B) of Parque Estadual da Serra do Mar during the study period. Temperature (dashed line), rainfall (blue bars) and day length (continuous black line). Continue.

Figure S4 Continuation. Flowering (yellow bars) and fruiting (red bars) patterns for three Cerrado areas: PNC - Parque Nacional da Serra da Canastra (C), SC - Serra do Cipó (D) and PEG - Parque Estadual do Guartelá (E) during the study period. Temperature (dashed line), rainfall (blue bars) and day length (continuous black line).

Chapter II

The role of nectar production in the evolution of generalised pollination systems: a case study of Miconia theizans in Southeastern Brazil

Text edited for the journal Oikos

Vinícius Lourenço Garcia de Brito1*, André Rodrigo Rech1, Jeff Ollerton2 and Marlies Sazima1

1. Instituto de Biologia, Universidade Estadual de Campinas (Unicamp) – Rua Monteiro Lobato 255, CEP: 13083-970, Caixa Postal 6190, Campinas, Brazil 2. Landscape and Biodiversity Research Group, School of Science and Technology, The University of Northampton, Avenue Campus, Northampton, NN2 6JD, United Kingdom

*Correspondence: [email protected]

Running title: Nectar production in Miconia theizans

Abstract Generalist plant-pollinator interactions are prevalent in nature. However, there are few studies showing the adaptive value of a generalised pollination strategy or its secondary evolution from specialised ancestors. The evolution of generalist plant-pollinator interactions is often related to the paucity of specialized pollinators in some areas (e.g. islands) and generalization is considered a reproductive assurance in such places. In Miconia, the largest genus of the Melastomataceae, flowers of nectar producing species seem to be visited by a larger group of potential pollinators when compared to typical pollen rewarding flowers of the same genus. Here, we untangle the role of nectar production in the visitation and pollen release dynamics of Miconia theizans using a linear model selection approach. Flowers of Miconia theizans were visited by 97 insect species, including anther-buzzing and non-buzzing bees, wasps, flies, hoverflies, ants, beetles, hemipterans, cockroaches, and others. The nectar produced during anthesis explained the total visitation rate, and the visitation rate of pollinivorous was the best predictor explaining pollen release from the anthers. However, the visitation rates of pollinivorous, nectarivorous and insects collecting both pollen and nectar explain the dynamics of pollen deposition on stigmas. Therefore, nectar production may be related to high insect diversity and an increase of female success in this plant suggesting an adaptive character of generalised pollination systems in mainland areas with low specialised pollinator predictability.

Introduction Plant-pollinator interactions vary along a broad range of possibilities from obligate specialists, when a single species of pollinator depends on only one species of plant and vice-versa, to facultative generalists, when a flower or pollinator interacts with many species belonging to different functional, taxonomic or phylogenetic groups (Waser et al. 1996; Ollerton et al. 2007). Specialised interactions, in addition to the concept of pollination syndromes, have been the focus of pollination researchers since the concept was formalized (Faegri and van der Pijl 1979, Fenster et al. 2004). However, despite the wider prevalence of generalist systems in plant-pollinator interactions (Waser et al. 1996), their complexity and variability over time and space have limited their appreciation as case studies from an evolutionary perspective (Alarcón et al. 2008, but see Amorim et al. 2013, King et al. 2013, Zych et al. 2014). The degree of generalisation in pollination systems has been the subject of intense discussion among ecologists (Waser et al. 1996, Sahli and Conner 2011). Under the assumption of constant flower specialisation to the most effective pollinator, there was a general idea that highly specialised pollination systems could be evolutionary dead-ends and that transitions from generalist systems to specialist ones are more frequent than the reverse (Futuyma and Moreno 1988, but see Tripp and Manos 2008). This idea was partially corroborated by the fact that most of the reported transitions between pollination systems happened among functionally specialised ones (Chase and Hills 1992, Armbruster 1988; Kay et al. 2005; Wilson et al. 2007; Whitall and Hodges 2007; Tripp and Manos 2008; Martén-Rodrígez et al. 2010, Smith 2010). To the best of our knowledge, there are only two phylogeny-supported situations where transitions from specialised to generalised systems were described (Armbruster and Baldwin 1998, Martén-Rodríguez et al. 2010). These two cases were recorded on islands and explained as alternative strategies to the lack of specialized pollinators. Flowers of most members of the Melastomataceae have poricidal anthers, often offer just pollen as reward and are mainly pollinated by bees able to vibrate their wing muscles to release pollen grains ("buzz-pollination", Renner 1989, Fracasso and Sazima 2004, Luo et al. 2008, Franco et al. 2011, Pereira et al. 2011, Brito and Sazima 2012). Despite having a phenotypically specialised pollen-based pollination system, nectar production has been reported for some genera and is associated with high altitude 46 colonization where bees are supposed to be less predictable (Varassin et al. 2008, Kriebel and Zumbado 2014). However, the proposed new pollinator groups are often as specialised as vibrating bees (e.g. bats and hummingbirds). These discoveries increased the number of known transitions among specialised systems but still corroborate the ‘dead-end’ hypothesis. On the other hand, there are some reports of visitation of different insect orders for nectar in flowers of the genus Miconia (Goldenberg and Sheperd 1998, Varassin et al. 2008, Santos et al. 2010, Kriebel and Zumbado 2014). In this case, the changes in the pollination strategy from a pollen- to a nectar-based reward was associated with more opened anthers in small and white flowers, allowing animals that are unable to vibrate to release the pollen through the anther aperture (Goldenberg et al. 2008). Despite this recently reported mechanism, structure and location of nectar production in such Miconia flowers (Varassin et al. 2008, Kriebel and Zumbado 2014), little is known about the dynamics of the nectar production during anthesis and its relation to insect visitation and plant reproductive success. Nectar production could be another evolutionary strategy, other than heteranthery, to solve the “pollen dilemma” in Melastomataceae flowers, where the pollen must feed the visitors larvae and, at the same time, carry the plant male gamete (Luo et al. 2008, Vallejo-Marin et al. 2009). In addition, increased nectar availability may result in longer visit durations and in higher pollen removal and deposition (Ollerton et al. 2007). In this sense, we expect that the nectar production associated to the dynamics of pollen as a resource in a generalist flower would be related to the variation of its visitors and consequently the pollen removal from anthers and deposition on stigmas. This work focuses on Miconia theizans, a nectar producing Melastomataceae species with small, pale flowers that are visited by a varied suite of flower visitors, indicating a generalised pollination system. Here, we describe the dynamics of nectar production and relate it to the pollination system and reproductive success of this species. This data will be used to test the hypothesis that nectar production is an important factor improving flower visitation and reproductive success in Miconia theizans, favouring generalisation of this pollination system.

Materials and Methods Study area We carried out all field observations at the Núcleo Santa Virgínia (NSV), Serra do Mar State Park, in the municipality of São Luís do Paraitinga at the top of the Serra do Mar mountain range (23o20’S, 45o50’W). The local vegetation is classified as ombrophilous montane forest (Padgurschi et al. 2011). The altitude varies from 870 to 1100m above sea level, the mean monthly temperature is 16.1ºC and the mean monthly precipitation is 172.5 mm at the study site (CPTEC 2010). The regional climate is subtropical wet without a dry season (Joly et al. 2012, Alvares et al. 2014) and January - February are the wettest months while June - August are the driest (Tabarelli and Mantovani 1999).

Study species Miconia theizans (Bonpl.) Cogn. is a very common small tree ranging from 1.5m to 3.0m tall. Its flowers last less than one day and produce a weak perfume; the corolla is pale and less than 3 mm in diameter. Inflorescences are the visual unit (from a human perspective) and can carry more than 60 opened flowers per day at the peak of flowering time, when they are visited by a large number of insects from different orders (Table 1; Figure 1). They also produce large amounts of fleshy fruits, which are eaten by a diverse array of birds (Brito, personal observation). The genus Miconia Ruiz and Pav. is the largest in the Melastomataceae with more than 1050 species (Goldenberg et al. 2013). The clade Miconia III, in which M. theizans is placed, is mostly restricted to the Andes and Central America, with a few species widespread in South America. The phylogeny of the genus shows that nectar production is not monophyletic and M. theizans is neither basal nor much derived inside the genus (Goldenberg et al. 2008).

Sampling methods We observed and monitored 25 individuals of Miconia theizans individuals in flower during two flowering seasons: December 2012 - January 2013 and December 2013 – January 2014. Each individual was monitored from 07:00 to 13:00, after which most of the flowers wilted. During this interval, from hour to hour, we measured the amount of nectar in three different bagged and unbagged flowers to estimate the dynamics of nectar production and the nectar standing crop per flower. Nectar was measured using strips of 48 filter paper (Whatman no. 1), by touching the nectar on petal surface and marking the wet part of the strip with a pencil. Afterwards, the portion marked with nectar of each paper strip was weighed using a high precision weighing machine to estimate the availability of nectar in each treatment and in each time interval. As M. theizans produces minute amounts of nectar, we measured nectar sugar concentration from a subset of the samples from different individuals. Then, we prepared a sugar solution of the same concentration in the lab and collected drops from 1 to 10 uL of it using the same filter paper to build a relation curve between nectar volume and filter paper weight and estimate the nectar volume produced by flowers (Figure S1, Adjusted R2=0.8665, p<0.001). Adopting the same approach, we also collected two anthers (one representing each anther whorl) and one stigma from the same bagged and the same unbagged flower in each hour for each one of the individuals. Each anther was stored in an eppendorf tube of 1mL with 70% ethanol solution in the field. The anthers were broken up afterwards and the total number of pollen grains available was estimated in laboratory using a haemocytometer (Brito and Sazima 2012). The stigmas collected in the field were placed on glass microscope slides previously prepared with fuchsin jelly allowing a semi-permanent preparation to count the pollen grains in the laboratory (Dafni et al. 2005). As Miconia theizans has large pored anthers and may possibly self-pollinate, the bagged flowers gives us the amount of self-deposited and self-released pollen grains, while the unbagged flowers gives us the total pollen deposition and release adding the action of the flower visitors. Every half hour between 07:00 – 13:00, we recorded the visitation rate to flowers during 10 minutes in each one of the 25 individuals. Insects were categorized by the taxonomic group they belong and into one of three functional groups based on their flower visitation behaviour: a) those collecting exclusively nectar (N); b) those collecting exclusively pollen (P); and c) those collecting both pollen and nectar (B). We calculated the relative richness and abundance of each functional category during the study period. Samples of the most frequent visitor species were collected to posterior identification using an entomological net. Vouchers of these visitors were deposited in the collection of the Museu de Zoologia - Unicamp, L2B-DBA - Laboratório de Entomologia, Departamento de Biologia Animal – Unicamp and Museu de Entomologia - USP-Ribeirão Preto, and vouchers of the plant species in the herbarium UEC. During the data collection days and at 49 the same time intervals, we also recorded the local temperature and humidity using a digital termo-higrometer (Figure S2).

Nectar, pollen and visitation dynamics We performed an analysis of variance (ANOVA type 3 for unbalanced data) using linear models to understand the patterns of variation in nectar dynamics as well as the number of pollen grains released from the anthers and deposited on stigmas in each time interval. To examine the dynamics of nectar production and standing crop, we considered time and treatment (bagged and unbagged) as random effects and the picked flower as fixed effect and the nectar volume (estimated from the filter paper weight) as the response variable. In the pollen release analysis, we considered the time interval and the treatment (bagged and unbagged) as fixed effects, and the quadrant of the haemocytometer was considered a random effect, while the number of pollen grains was the response variable. In the pollen deposition analysis, we built a linear model considering the time interval and the treatment (bagged and unbagged) as factors and the number of grains deposited as the response variable. For the visitation dynamics, we built a linear model considering time interval and the functional categories as factors and the number of visits per flower as the response variable.

Visitation and pollen release and deposition by visitor action To predict the possible determinants of the visitation dynamic of M. theizans we built linear models with decrease complexity. We considered the time interval and day as random effects in all models. The fixed effects for each model were as follows: a) full: temperature, humidity, number of available pollen grains inside anthers of unbagged flowers and nectar standing crop; b) pollen: only the number of available pollen grains inside anthers of unbagged flowers; c) nectar: only the nectar standing crop; d) both: pollen and nectar available to visitors; e) weather: only temperature and humidity and; f) null: no fixed effects. We used linear models to understand the influence of visitation rate of each functional group on the number of pollen grains released from the anthers by visitor action (i.e. the number of pollen grains of unbagged flowers minus the number of pollen grains of bagged flowers). Using the same rationale, we calculated the number of pollen grains 50 deposited onto the stigma by visitor action and related it to the visitation rate of each functional group. Time intervals and days were considered random effects in all models while the fixed effects were as follows: a) full: sum of the visits by N, P and B; b) N: only the visitation dynamics of N; c) P: only the visitation dynamics of P; d) B: only the visitation dynamics of B; e) NB: the visitation dynamics of N and B; f) PB: the visitation dynamics of P and B; g) NP: the visitation dynamics of N and P and; h) null: no fixed effects. We used the Akaike information criterion (AIC) to evaluate the prediction ability of each model and the ΔAIC (the difference between the AIC for the ith model and the minimum AIC among all the models) to compare them and select the best fit. Values of ΔAIC within 0-2 have substantial support; delta within 4-7 are considerably less support; and delta greater than 10 has essentially no support (Burnham and Anderson 2002). All the analyses were carried out in R 2.15.0 language and environment (R Development Team Year).

Results Nectar, pollen and visitation dynamics The flowers of Miconia theizans produce minute amounts of high concentrated nectar (about 60%) that is continuously depleted during anthesis. In unbagged flowers the nectar availability was almost zero after 09:00 (dry crystals could remain on the petal surface due to the synergic action of reduction by visitors and elevated temperatures), while the nectar was available until the last time interval inside bagged flowers (Figure 2A). Time and treatment were both significant factors influencing nectar dynamics (time: F=54.679, p<0.01; treatment: F=36.348, p<0.01), and there was no interaction between these factors (F=2.071; p>0.05). Pollen grains from the anthers were also depleted during anthesis. In general, the largest amount of pollen grains was released before 09:00 and bagged flowers released fewer pollen grains than unbagged ones (Figure 2B). Time and treatment explained the pollen dynamics of the anthers (time: F=14.450, p<0.01; treatment: F=18.996, p<0.01), and there was no interaction between these factors (F=0.837; p>0.05). Pollen deposition on stigmas showed the inverse pattern, it increased during anthesis and the unbagged flowers received more pollen grains than bagged flowers (Figure 2C). Again, 51 there was an effect of time and treatment (time: F=8.397, p<0.01; treatment: F=43.758, p<0.01) and no interaction between factors (F=0.935; p>0.05). Over the two data collection seasons, we recorded 97 morpho-species of flower buzzing and non-buzzing bees, wasps, flies, hoverflies, ants, beetles, hemipterans, cockroaches, and others visitors to the flowers of Miconia theizans (Table 1; Figure 1). Visitation started in the morning at the sunrise and continued until around 14:00 when the flowers started to wilt. We recorded 10,885 visits, 17% of them performed by Apis mellifera, followed by an unidentified wasp species (13% of total visits) and an ant species (10% of total visits). The richest group was Dyptera with 40 morpho-species, followed by bees and wasps with 27 and 12 morph-species respectively (Figure 3). However, the most abundant group was wasp with 36.5%, followed by bees and ants with 35.8% and 13.0% of total visits, respectively (Figure 3). By categorizing the flower visitors according to the resource they collected, it was possible to see that nectarivorous insects are the main visitor group in terms of both morpho-species richness and abundance (Figure 4A). The visitation dynamics show that nectarivorous insects continued to visit the flowers long after the peak of visitation of the other groups (Figure 4B). There was a significant effect of time (F=1.949, p<0.03) and of the functional group considered (F=71.968, p<0.01), and no interaction between both factors (F=0.773; p>0.05).

Visitation and pollen release and deposition by visitor action The full model, which considers weather variables (temperature and humidity), the available resources (nectar and pollen) and the random effects (time and day) was the best fitted to the total flower visitation (ΔAIC=0.0, df=8, weight=0.44; Figure 5; Table S1). However, the model considering just the available pollen grains (pollen) and the one considering both pollen grains and nectar standing crop (both) were also below the threshold of substantial support (Pollen: ΔAIC=0.3, df=5, weight=0.38; Both: ΔAIC=1.8, df=6, weight=0.18; Figure 5; Table S1). The number of pollen grains released from the anthers by visitor action was better explained by the model that considered only the visitation dynamics of exclusively pollinivorous insects (ΔAIC=0.0, df=5, weight=0.96) with no other competing model below the substantial support threshold (Figure 6A; Table S2). The same result was found for the number of pollen grains deposited onto the stigma by visitor action, for which the 52 best fitted model was also the one that considers only the visitation of pollinivorous insects (ΔAIC=0.0, df=5, weight=0.28; Figure 6B; Table S2). However, models considering the dynamic of nectarivorous insects and the dynamic of insects that collected pollen and nectar were also scored below the threshold value of substantial support (model B: ΔAIC=1.1, df=5, weight=0.17; model PB: ΔAIC=1.4, df=5, weight=0.14; model NP: ΔAIC=1.9, df=5, weight=0.11; model N: ΔAIC=2.0, df=5, weight=0.11).

Discussion Miconia theizans offers minute amounts of nectar as well as pollen grains as rewards during anthesis. Nectar and pollen availability varies throughout the day, as well as the dynamics of the floral visitors. The flowers were visited by 97 morpho-species of insects feeding on nectar, pollen, or both. Although, we have sampled a large number of individuals of M. theizans, a simple richness estimator index suggest that this plants could be visited by more than 140 species (Chao richness estimator: species richness = 144.5 ± 20.5). This indicates that many more species should be expected with higher sampling effort, what would suggests that the pollination system of this species may be even more generalised than what we recorded. Our results support the idea that high richness and abundance of flower visitors is associated with nectar production, since the majority of visiting M. theizans insects feeds exclusively on nectar. The visitation rate curves suggests that nectarivorous visitors may remain visiting, and possibly depositing pollen on stigmas, long after pollinivorous ones have already stopped visiting the flowers. It is also worth mentioning that visitors classified as collecting both nectar and pollen (mostly bees) have switched from pollen collectors at early morning to nectar collectors after pollen availability have decreased (a time-structured behaviour). Hence, nectar production can also be seen as an effective strategy to stimulate some of the pollen collectors to keep visiting the flowers, and therefore improving female reproductive success. The importance of nectar in the evolution of new pollination systems, in this case from a buzz-pollinated typical flower (Endress 1994, Varassin et al 2008, Waser et al. 2011), is an example of an unusual transition from a functionally specialised to an ecologically generalised pollination system, confirming the previously suggested role of nectar in these transitions in the Melastomataceae (Varassin et al. 2008, Kriebel and Zumbado 2014). Moreover, nectar production in contrast to pollen is not ontogenetically 53 limited, thus plants can have more control on visitation, allowing visits of a larger suite of animals and enabling longer periods of visitation (Ollerton et al. 2007). In our study, we assumed a conservative estimate of the nectar role since our sampling method was likely underestimating the available volume of nectar in the flowers. The small amounts of exposed nectar reduced by visitors activity associated with elevated temperatures promoted the evaporation and increased the nectar concentration to levels that it could be seen on the flowers but no longer infiltrated the filter paper used to quantify its availability. Moreover, visitors such as flies and wasps kept visiting and collecting highly concentrated nectar or the remaining sugar crystals on the petals. The change from pollen- to nectar-based rewarded flowers could also be seen as a way to deal with the “pollen dilemma”. Since pollen-based rewarded flowers offer their own gametes for flower visitors, a strategy that diminishes the importance of pollen as a reward should be evolutionarily favoured. In Melastomataceae, an often-reported solution to this “pollen dilemma” is the presence of two sets of anthers with different size (heteranthery), with two different functions: feed the visitors’ larvae and carry the plant male gamete (Müller 1882, Luo et al. 2008, Vallejo-Marin et al. 2009). In this study, pollen removal from the anthers was explained by the visitation frequency of the exclusively pollen-feeding visitors. This was already expected since these visitors are the ones able to vibrate the anthers and take most of the pollen out of them (Buchmann 1983). However, as these bees have an optimized behaviour in order to produce their offspring, they could leave (next to) nothing for pollination, and, consequently, for fruit set (Hargreaves et al. 2009, Westerkamp and Claßen-Bockhoff 2007, Schlindwein et al. 2005). On the other hand, according to the pollen deposition curve, the pollen was deposited throughout the observation period. This trend can be confirmed by the model selection analysis since the model including nectarivorous and visitors collecting both nectar and pollen also explained the number of pollen grains deposited onto the stigmas. Therefore, these results suggests that nectar production could be another solution to the “pollen dilemma” in Melastomataceae flowers, since it would diminish the pressure of pollen consuption by bees on the female success. It can also be added that nectar probably helps to change the visitor attention when landing on the flower. When visitors are collecting nectar they frequently touch anthers and get pollen all over their bodies and the same should happen with stigmas when pollen is transferred. 54

A previous study at the same site of the present one had already indicated less predictability in pollination by buzzing-bees compared to the closest lowlands populations for another Melastomataceae species (Tibouchina pulchra, Brito and Sazima 2012). Our study corroborates this trend because buzzing-bees were a small proportion of flower visitors (14%). In high elevation, nectar production in M. theizans can contribute to enlarge the number of pollinators and therefore improve the whole system resistance to the loss of specialised buzz-pollinators. Hence, we provide support to Baker's rule, by including generalisation (mediated by nectar production) as another strategy to ensure plant establishment in places where specialised pollinator faunas are less predictable (Busch and Delph 2012, Cheptou 2012). The insurance strategy of the study species has not only more pollinators but also it can self-pollinate as shown by the number of pollen grains deposit on bagged stigmas. These pollen grains can also contribute to reproductive assurance as fruit were found in bagged inflorescences (Brito unpublished data). Although reproductive organs of M. theizans are very exposed and every visitor is likely to be a pollinator, a further study evaluating the visitors’ interspecific variation in effectiveness is required to ensure that the strategy is truly generalised (Niemirski and Zynch 2011). Once this is confirmed, we will be able to strengthen the evidence that specialisation by buzz-pollination is not a dead-end for pollination systems (Tripp and Manos 2008). Furthermore, our results suggests that the generalization of pollination systems may also be favoured in places other than islands (Armbruster and Baldwin 1998, Martén-Rodríguez et al. 2010). In this sense, high elevation mainland areas, where specialist pollinator predictability is also low, could favour the evolution of generalization from previously bee pollination specialised systems. Therefore, this study reinforces the evidences of the adaptive character of generalised pollination systems, not as an inexhaustible source of next generation specialists, but as effective reproductive strategies suitable and likely to evolve under certain conditions (Waser and Ollerton 2006, Tripp and Manos 2008).

Acknowledgement The authors kindly thank the help of our friends in the field and lab: Pedro J. Bergamo, Maraísa Braga, Priscila Veiga, Camila Oliveira, Rafael Pereira and specially Carine Carriere, Cristiano Silva and Maicon Grella. We thank FAPESP for the scholarship 55 provided to V.L.G.B. (Proc. Fapesp 2010/51494-5), A.R.R. (Proc. Fapesp 2009/54491-0) and the projects to M.S. (2012/50425-5 and 2013/14442-5), and CNPq for the grant to M.S.. JO is grateful to Fapesp for funding to allow his study visit to Brazil.

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Table 1. Number of morpho-species visiting Miconia theizans flowers at Parque Estadual da Serra do Mar (Santa Virgina station) São Paulo, Brazil. P: pollinivorous insects; N: nectarivorous insects; B: insectas collecting both pollen and nectar.

Order Number of morpho-species

P N B

Blattodea - 3 -

Coleoptera - 7 1

Diptera 1 25 14

Hemiptera - 2 -

Hymenoptera - bees 13 - 14

Hymenoptera – wasps - 12 -

Hymenoptera - ants - 4 -

Lepidoptera - 1 -

Total 14 54 29

Figure 1. Flower visitors of Miconia theizans at Parque Estadual da Serra do Mar (Santa Virgina station) São Paulo, Brazil. A-B. beetles (Coleoptera), C-D. Flies (Diptera: Tabanidae and Syrphidae), E-F. wasps (Hymenoptera: Vespidae) and G-I. bees (Hymenoptera: Apidae).

Figure 2. Nectar and pollen dynamics in Miconia theizans flowers at Parque Estadual da Serra do Mar - Núcleo Santa Virgínia, São Paulo, Brazil. (A) Nectar produced in bagged and in unbagged flowers (standing crop). (B) Estimated number of pollen grains from anthers in bagged and unbagged flowers. (C) Number of pollen grains deposited on stigmas of bagged and unbagged flowers. Bars indicate standard errors.

Figure 3. Morpho-species richness and relative abundance of each group of flower visitors of Miconia theizans flowers at Parque Estadual da Serra do Mar - Núcleo Santa Virgínia, São Paulo, Brazil.

Figure 4. Dynamics of visitation to flowers of Miconia theizans at Parque Estadual da Serra do Mar - Núcleo Santa Virgínia, São Paulo, Brazil. (A) Proportional morpho-species richness and abundance of the flower visitors grouped by the resource they were collecting from the flowers. (B) Visitation rate over time of each visitor functional group. Bars indicate standard errors.

Figure 5. Selection of the best fitted linear model for the visitation rate on Miconia theizans at Parque Estadual da Serra do Mar - Núcleo Santa Virgínia, São Paulo, Brazil. ΔAIC values below the dashed line (ΔAIC = 2) indicate competing models with substantial support based on Akaike information criteria. All models considered day and time as random effects. Model fixed factors are as follows: full: temperature, humidity, number of available pollen grains inside anthers of unbagged flowers and nectar standing crop; pollen: only the number of available pollen grains inside anthers of unbagged flowers; nectar: only the nectar standing crop; both: pollen and nectar available to visitors; weather: only temperature and humidity and; null: no fixed effects.

Figure 6. Selection of the best fitted linear model to pollen release and deposition by visitor action in Miconia theizans at Parque Estadual da Serra do Mar - Núcleo Santa Virgínia, São Paulo, Brazil. ΔAIC values below the dashed line (ΔAIC = 2) indicate competing models with substantial support based on Akaike information criteria. (A) Number of pollen grains released from the anthers by visitors action. (B) Number of pollen grains deposited on stigmas by visitors action. All models considered day and time as fixed effects. Model random factors are as follows: full: sum of the visits by N, P and B; N: only the visitation dynamics of N; P: only the visitation dynamics of P; B: only the visitation dynamics of B; NB: the visitation dynamics of N and B; PB: the visitation dynamics of P and B; NP: the visitation dynamics of N and P and; null: no random effects. N – nectarivorous insects; P – pollinivorous insects; B – insects collecting nectar and pollen. 66

Supplementary Material

The role of nectar production in the evolution of generalised pollination systems: case study of Miconia theizans in south eastern Brazil

Vinícius Lourenço Garcia de Brito1, André Rodrigo Rech1, Jeff Ollerton2 and Marlies Sazima1

*Correspondence: [email protected]

Running title: Nectar production in Miconia theizans

Table S1. Results of selection of the best fitted linear model to visitation rate on Miconia theizans at Parque Estadual da Serra do Mar - Núcleo Santa Virgínia, São Paulo, Brazil. Values of ΔAIC within 0-2 have substantial support; delta within 4-7 considerably less support; and delta greater than 10 essentially no support. df: degrees of freedom; weight is the probability of one model being in favor over the other.

ΔAIC Df weight

Full 0.0 8 0.44

Pollen 0.3 5 0.38

Both 1.8 6 0.18

Null 43.7 4 <0.001

Nectar 44.6 5 <0.001

Weather 45.3 6 <0.001

All models considered day and time as random effects. Model fixed effects were: Full: temperature, humidity, number of available pollen grains inside anthers of unbagged flowers and nectar standing crop; Pollen: only the number of available pollen grains inside anthers of unbagged flowers; Nectar: only the nectar standing crop; Both: pollen and nectar available to visitors; Weather: only temperature and humidity and; Null: no fixed effects.

Table S2. Results of selection of the best fitted linear model to pollen release and deposition by visitor action in Miconia theizans at Parque Estadual da Serra do Mar - Núcleo Santa Virgínia, São Paulo, Brazil. Values of ΔAIC within 0-2 have substantial support; delta within 4-7 considerably less support; and delta greater than 10 essentially no support. df: degrees of freedom; weight is the probability of one model being in favor over the other.

ΔAIC df Weight

Pollen release

P 0.0 5 0.962 PB 7.5 5 0.0224 Full 9.8 5 0.0072 NP 11.1 5 0.0038 B 12.9 5 0.0015 NB 13.3 5 0.0012 N 14.1 5 <0.001 Null 16.4 4 <0.001

Pollen deposition

P 0.0 5 0.2845 B 1.1 5 0.1660 PB 1.4 5 0.1406 NP 1.9 5 0.1096 N 2.0 5 0.1070 NB 2.2 5 0.0949 Full 2.2 5 0.0959 Null 10.4 4 0.0015

All models considered day and time as random effects. Model fixed factors were: Full: sum of the visits by N, P and B; N: only the visitation dynamics of N; P: only the visitation dynamics of P; B: only the visitation dynamics of B; NB: the visitation dynamics of N and B; PB: the visitation dynamics of P and B; NP: the visitation dynamics of N and P and; 69

Null: no fixed effects. N – nectarivorous insects; P – pollinivorous insects; B – insects collecting nectar and pollen.

Figure S1. The relationship between nectar volume and the filter paper weight used in the field to estimate the nectar volume produced by flowers of Miconia theizans at Parque Estadual da Serra do Mar (Santa Virgina station) São Paulo, Brazil. Adjusted R2=0.8665 and p<0.01.

Figure S2. Weather condition during field data collection of Miconia theizans at Parque Estadual da Serra do Mar (Santa Virgina station) São Paulo, Brazil. (A) Mean temperature. (B) Mean relative humidity. Bars indicate the 95% confidence interval for the 7 days of weather data collection.

Chapter III

Genetic structure and diversity of populations of Tibouchina pulchra Cogn. (Melastomataceae) under different pollination dynamics in extremes of an elevational gradient

Text edited to the Organisms Diversity and Evolution journal

Vinícius L. G. Brito*,a,b, Gustavo M. Morib,c, Bianca B. Z. Vignab,d, Marianne A. Silvae, Marlies Sazimaa and Anete P. Souzaa,b

a Department of Plant Biology, Institute of Biology, State University of Campinas , Campinas, São Paulo, Brazil; b Center for Molecular Biology and Genetic Engineering (CBMEG), State University of Campinas, Campinas, São Paulo, Brazil; c Agência Paulista de Tecnologia dos Agronegócios, Pólo Regional Centro Sul, Piracicaba, São Paulo, Brasil; d EMBRAPA Southeast Livestock, Brazilian Agricultural Research Corporation, São Carlos, São Paulo, Brazil; e Department of Animal Biology, Institute of Biology, State University of Campinas , Campinas, São Paulo, Brazil.

*correspondence: email: [email protected] phone number: +55(19) 3521-6170 fax number: +55(19) 3521-6184.

Key-Words: polyploidy; pollen flow; Atlantic rainforest; Serra do Mar; manacá-da-serra

Abstract The genetic structure and diversity of plants may change significantly in an elevational gradient because different elevations regulate different ecological conditions. Several factors may influence genetic variation, such as mutations, selection, the evolutionary history of each plant species and gene flow, which may be considered the most important factor. The aim of the present study was evaluate the genetic structure and diversity of populations of Tibouchina pulchra Cogn. (Melastomataceae) in two extremes of an elevational gradient experiencing different pollination dynamics: at the higher region, individuals are more pollinator limited than at the lower region. Nine polymorphic microsatellite loci were used to measure the genetic diversity of 14 adult populations, whose structure was evaluated using frequentist and Bayesian group analyses. To assess one possible current process leading to genetic structure, we also carried out progeny analysis comparing the relatedness of the progeny and the mother-plant and the relatedness within the progeny among sibblings. Group analyses indicated the existence of genetic differentiation between populations of each region, but with a contact interface between them. The populations from the higher region showed smaller genetic diversity when compared to the populations at the lower region. However, the pollen variability delivered to the stigmas at the higher region is not different from that of the lower region. These results may be explained by the dynamics of gene flow mediated by pollen, especially by the different amounts of cross-pollination events in each regions, as well as by Tibouchina pulchra distribution and reproduction characteristics through the Serra do Mar mountain range.

Introduction Plant populations are not a set of genotypes randomly structured in time and space. In general, there is a genetic organization among geographically distinct populations, within local plant groups or even in the progeny of individuals (Loveless and Hamrick 1984). In this sense, several factors may influence the amount of genetic structure and diversity of plant populations, such as mutations, selection, the biological context of each plant species and gene flow, which may be considered the most important one (Loveless and Hamrick 1984; Slatkin 1987). In plants, gene flow may occur only in two life history moments, during pollen and seed dispersal. Therefore, pollination and seed dispersion dynamics have direct implications on the genetic structure of populations and both processes have been considered the causes of high diversification of angiosperms (Bawa 1995). The lack of gene flow can decrease the effective size and genetic diversity in populations and generate inbreeding depression (Ellstrand 1992; Charlesworth and Charlesworth 1987). This reduction in diversity and increasing of inbreeding rates can limit the potential of natural populations to adapt to a changing world (Reis 1996). On the other hand, high levels of genetic diversity, generated by the movement of pollen and/or seeds and the consequent exchange of genes among populations, enable a great number of genotypic combinations, increasing the evolutionary potential of the species due to the greater adaptation capacities to possible environmental changes (Sebbenn et al. 2000). However, this intraspecific gene flow may also increase outbreeding depression, i.e. a reduction of fitness after outcrossing or hybridization, especially in rare species (Waser and Price 1989). The genetic structure and diversity of plants may change significantly in an elevational range since it results in different ecological conditions in a particular habitat, such as pollinator availability (Thomas et al. 2001; Semagn et al. 2000; Yan et al. 2009). Genetic differentiation between populations throughout an elevational gradient has been demonstrated for several species of plants, in which diversity can increase, decrease or even fluctuate with the increase of altitude (Yan et al. 2009; Ohsawa and Ide 2008; Zhao et al. 2006; Semagn et al. 2000). Some of these studies suggest that the restricted gene flow among populations and strong natural selection influences the genetic diversity of plant in such places (Thomas et al. 2001; Slatkin 1987). Therefore, plants that occur in elevational 76 gradients and rely on pollinator activity for their reproduction might be an ideal model to understand the role of pollen flow on genetic structure and diversity of populations. The Melastomataceae family comprises 4200-4500 species and they are well represented in tropical and subtropical ecosystems of the Americas, where around 3000 species are found (Renner 1993). There are 68 genera in Brazil, with estimations of over 1300 species (Goldenberg et al. 2012; Renner 1993). Their flowers are normally pollinated by bees which collect pollen from the often poricidal tubular anthers. During a flower visit, the bees embrace the anthers and perform vibration movements with their wing muscles. Pollen grains are expelled and adhere to the bee body, a place frequently touched by the flower stigmas. This type of pollination is called buzz pollination and is frequently found in the genus Tibouchina (Buchmann 1983; Franco et al. 2011; Brito and Sazima 2012). Consequently, in such systems, gene flow by pollen is almost restricted to the movement of the pollinators due to pronounced flower herkogamy (Renner 1989). On the other hand, because Tibouchina produces capsular fruits, seed dispersal in this genus restricted to wind or gravity (Silveira et al. 2013), which possibly reduces the effects of seed dispersal in gene flow. The aim of this study was to evaluate the genetic structure and diversity of populations of Tibouchina pulchra Cogn. (Melastomataceae) occurring at two extremes of an elevational gradient: at sea level and around 1000m above sea level in Parque Estadual da Serra do Mar. As populations at higher region (NSV) are more pollinator limited than populations occurring at the lower region (NP) (Brito and Sazima 2012), we expect to find: 1) genetic differentiation between both regions and 2) lower genetic diversity in the populations occurring at higher elevations. If the process generating such possible genetic structure and diversity pattern is the low pollen diversity delivered to the stigmas at NSV as compared to NP, we expect that 3) the relatedness between progeny and their mother plant, as well as, the relatedness among individuals from the same fruit (siblings), will be greater in the higher regions.

Materials and Methods

Study area The study was developed at the Parque Estadual da Serra do Mar, at Núcleo Santa Virgína (NSV) and Núcleo Picinguaba (NP), both situated in the Southeasthern Brazil (Fig. 1). The NSV is located in the region of scarps and reverse faults of the Serra do Mar mountain range, on the Paraitinga-Paraibuna plateau, close to the city of São Luís do Paraitinga - SP, with altitudes that vary between 870 m and 1,110m (Tabarelli and Mantovani 1999). According to Veloso et al. (1991), vegetation may be classified as montane Atlantic rainforest. According to the climatic classification by Köppen (1948), the regional climate is subtropical humid without a dry season and with temperate summer (Alvares et al. 2014). Average annual precipitation is 2,180 mm, and December, January and February are the wettest months, while June, July and August are the drier months. Average precipitation is never inferior to 60 mm per month (Tabarelli and Mantovani 1999). The NP is located on the coastal plain, in the municipality of Ubatuba - SP, covering the coastline and the foothills of the Serra do Mar mountain range. The vegetation in the area is classified as dense rainforest (Veloso et al. 1991). The climate is tropical rainy according to Köppen (1948) and presents a super humid season from October to April, with an average precipitation superior to 200 mm per month and a drier season from May to September, with an average monthly precipitation of 100 mm (Morellato et al. 2000). The average annual precipitation is 2,100 mm and the average annual temperature is around 22ºC (Bencke and Morellato 2002).

Study species The genus Tibouchina (tribe Melastomeae) is amply distributed in the Neotropics and has the greatest number of species within the group of capsular fruit Melastomataceae, with around 240 species (Renner 1993). It is found from Eastern Mexico to Northeast Argentina and Paraguay (Todzia and Almeida 1991; Guimarães and Martins 1997). Tibouchina pulchra Cong., is a pioneer polyploid tree species that has flowers displaying two colours: new white flowers presenting a pleasant and weak perfume, characteristic to melitophilous flowers (sensu Faegri and Van der Pijl 1979) and old pink flowers that are scentless and rarely receive visits (Pereira et al. 2011; Brito and Sazima 2012). The new 78 flowers possess five big stamens and five small ones, both presenting poricidal anthers. Pollen grains are the only reward offered by flowers and it is removed only by buzz pollination (Buchmann 1983). Tibouchina pulchra is self-compatible, but not self- pollinated and requires pollinators for reproduction. Its fruits are capsular and they set over then 3,000 seeds that germinate after 15 days (Brito and Sazima 2012).

DNA extraction, amplification and genotyping Young leaves from 210 adult individuals (105 individuals at each region) were collected using sterile scissors and stored in the Biofreezer at - 80°C. To avoid parentage bias, we chose individuals at least 10 m apart from each other occurring in seven distinct populations about 2 Km apart from each other within each region (Table 1, Fig. 1A, B). During fruiting season, we chose some of these adults to collect one or two fruits assigning the region, the population, the cardinal direction at the tree top and the mother for each one. From each fruit collected, we germinated their seeds and sampled from 10 to 21 progeny individuals when the seedlings reached a size enough to perform DNA extraction (Table 1). Total genomic DNA was extracted from the leaf tissues using the DNeasy Plant Mini Kit (QIAGEN) and individuals genotyped at nine polymorphic microsatellite loci previously developed (Brito et al. 2010). The loci were amplified using polymerase chain reaction (PCR) carried out in a final volume of 10 µL containing 1.5 ng of template DNA, 1 X PCR buffer, 3 mM magnesium chloride, 0.2 µM of each dNTP, 0.1 µM of each primer, 0.1 µM of 700 nm or 800 nm Infrared Dyes (Li-Cor Biosciences, Licoln, NE, USA) and 1 U Taq DNA polymerase. We followed three touchdown protocols (Don et al. 1999), according to the thermocycling conditions: 94°C for 4 min; 10x [94°C for 45 sec, 60°C (- 0,5°C/cycle) or 57°C (-0,5°C/cycle) or 63°C (-0,5°C/cycle) for 1 min and 72°C for 1 min 15 sec]; 25x [94°C for 45 sec, 50°C for 1 min and 72°C for 1 min 15 sec]; and 72°C for 10 min. In each forward primer a M13 tail (5'- CACGACGTTGTAAAACGAC - 3') was added at its 5’ end (Schuelke 2000), which enabled the amplified microsatellite fragments to be scored on 4300 DNA Analyzer (Li-Cor Biosciences, Licoln, NE, USA). Given the impossibility of determining the exact allele frequency in polyploids, we restricted our analysis to methods that considers such bias on the data.

Genetic structure and diversity of adult populations Analysis of Molecular Variance (AMOVA) (Excoffier et al. 1992) was performed using the ade4 1.6-2 R package (Dray et al. 2007) to estimate how genetic variation is partitioned between regions, among populations within regions, and within each population. The significance of the proportion of variation at each category was obtained by a Monte Carlo test with 1000 permutations. The genetic relation among all individuals and group formation was accessed through a discriminant analysis on principal components (DAPC) (Jombart et al. 2010) implemented in the adegenet R package (Jombart 2008). DAPC maximizes the variance between groups while minimizing the variance within groups, using as the input the principal components (PCs) generated from the genotypes of individuals (Jombart et al. 2010). As the number of retained PCs for the analysis can bias the fit of DAPC, we chose the number of principal components using the a-score function, which is the difference between the proportion of successful reassignment of the analysis (observed discrimination) and values obtained using random groups (random discrimination). We ran this analysis considering the region and the populations within each region as groups. The evaluation of the genetic structure of the populations was also made through Bayesian inference (Pritchard et al. 2000; Falush et al. 2007) performed with the Structure 2.2.3 software. The individuals were assigned to possible allelic pools, K, varying from two to ten. We used the model with admixed ancestry and correlated allele frequencies between populations without the locality informed a priori. Fifty independent Markov Chain Monte Carlo (MCMC) runs were carried out with 500,000 iterations following a burn-in period of 500,000 iterations for each value of the number of clusters (K). The best estimate of K was calculated from the ad hoc statistic delta K, proposed by Evanno et al. (2005). To deal with label switching and multimodality issues we used the software CLUMPP 1.1.2 (Jakobsson and Rosenberg 2007). The following estimators of the genetic diversity on each locus in populations occurring at the two regions were calculated through the FDASH program (Obbard et al. 2006): total number of alleles, average number of unshared alleles between pairs of individuals, average number of different alleles carried by each individual, total number of phenotypes, average Shannon-Weaver phenotype diversity, and average number of shared alleles between pairs of individuals. These estimations were calculated through the average 80 number of alleles by which pairs of individuals differ. These estimates are ideal to allopolyploids, as is possibly the case of T. pulchra (see discussion; Obbard et al. 2006). We performed an analysis of variance (ANOVA) at 95% confidence interval using each estimator as response and the regions, populations and locus as factors.

Progeny relatedness We conducted an analysis comparing the relatedness between each individual of the progeny and their mother-plant and the relatedness among siblings from the fruits collected in adults occurring in both regions (Table 1). We used two estimators of relatedness in polyploids, one based in method-of-moments (MOM) and the other based in maximum likelihood (ML) using the program POLYRELATEDNESS 1.5 (Huang et al. 2014). From the relatedness matrix based in each estimator, we calculated the relatedness between the progeny and the mother-plant and performed an ANOVA considering the relatedness as response, the region and the cardinal direction of the fruit at the tree top as fixed factors and the population, the mother and the fruit as random factors. The same rationally was applied to conduct an ANOVA considering the relatedness among siblings from the same fruit as response, the region and the cardinal directions of the fruit as fixed factors, and the population and mother as random factors. All analyses, except the Bayesian and the relatedness analyses, were carried out using the R 2.15.0 language and environment (R Development Team Year).

Results Although leaves from 105 adults were collected in each region, one adult from NP region was lost, resulting in a total of 209 trees and 562 progeny individuals genotyped. The progeny was collected from 31 fruits in 21 adults from different populations (Table 1). The total number of bands per locus varied from four to 25, while the number of bands per individual per locus varied from one to four, a multi-band pattern typical of polyploid organisms.

Genetic analysis of the adult populations AMOVA indicated that most of the variation (91.55%) is within populations, while 5.94% varies among populations and 2.51% between regions (Table 2). The Monte Carlo 81 test indicated that this variation within populations was less than expected by chance, while it was greater than expected by chance among populations and between regions (p<0.001 in each test). The DAPC discriminated 88% of the individuals from NSV and 86% of the individuals from NP, considering the region as groups and a retention of 24 PCs given by the a-score (Fig. 2). However, 26% of total individuals were associated to both regions indicating the existence of a contact interface between the populations from higher and lowers regions. A similar result was found using the populations as groups and a retention of 21 PCs as suggested by the a-score: the populations from each region grouped together but with a contact interface between them (Fig. 3). The allocation of individuals to populations, by utilizing the ancestry model without admixture with correlated allele frequency, showed that the best K is two, based on Evanno et al. (2005) estimation, and not considering the information on the location (Fig. 4). The majority of the individuals shared a common allelic pool in accordance to their occurrence at each region (blue: NSV; red: NP – Fig. 4). However, there are some individuals carrying most of their allelic pool corresponding to a different region, which supports the results from DAPC analysis. The genetic diversity estimators calculated by the FDASH program indicated that the individuals located at NSV region form a group genetically less diverse than the individuals occurring at NP (Table 3, Fig. 5). Only the average number of shared alleles between pairs of individuals was statistically not different between regions, but all the other measurements were lower at the higher region (Table 3, Fig. 5). The genetic diversity indexes, except for the total number of alleles, were not structured by the populations (Table 3). On the other hand, there was difference among locus in all genetic diversity indexes (Table 3).

Progeny relatedness The progeny analysis indicated that, regardless the kind of estimator used, the relatedness of the progeny and the mother were not different when considering the cardinal directions (MOM - direction: F = 0.7977, Df = 3, p = 0.51135; ML – direction: F = 0.72622, Df = 3, p = 0.5499) or the region from which the fruit was collected (Fig. 6; MOM - region: F = 4.4112, Df = 1, p = 0.06843; ML – region: F = 1.33899, Df = 1, p = 0.2752). 82

The same result was obtained for the relatedness among siblings from the same fruit: there was not an effect of the cardinal direction (MOM - direction: F = 0.88138, Df = 3, p = 0.4786; ML – direction: F = 1.22443, Df = 3, p = 0.3337) nor an effect of the region (Fig. 6; MOM - region: F = 0.00424, Df = 1, p = 0.9514; ML – region: F = 0.49495, Df = 1, p = 0.5013).

Discussion Polyploidy in T. pulchra has been observed before (Brito et al. 2010) and was confirmed by our results. However, the T. pulchra ploidy level still could not be inferred and should be investigated by more accurate cytogenetic methods since it cannot be inferred by banding patterns or electropherograms (Brochmann et al. 1992). Almeda and Chuang (1992) pointed out that tetraploidy is the most common condition in the genus Tibouchina, followed by diploidy and hexaploidy. Polyploidy has been considered one of the most predominant modes of speciation in plants (Otto and Whitton 2000) and can be classified into two types: allopolyploidy in which plants contain more than two distinct genomes and; autopolyploidy in which plants contain multiple identical genomes (De Silva et al. 2005). In allopolyploidy, as in diploidy, the formation of bivalents occurs during meiosis and inheritance, due to the movement of locus to opposite poles, is called disomic, producing genotyping gels with band patterns similar to diploid bands. Multivalents are formed in autopolyploids during meiosis and the inheritance is called polysomic, producing various combinations of bands per individual in microsatellite genotyping gels. However, these two inheritance types are often just extremes of a continuum in polyploids and several species present a combination of them in standard genotyping procedures. The presence of more than two alleles per individual associated to the complex inheritance patterns described above does not allow for the direct calculation of allele frequency in polyploids and impedes the utilization of traditional methods to measure genetic variability (De Silva et al. 2005). However, polymorphic markers, such as the ones presented here, can be utilized as dominant markers in ecological and evolutionary studies involving polyploids (Byrne et al. 2008; Caddah et al. 2009). For this study we used such approach for the AMOVA, DAPC and Structure analyses or programs developed for polyploids that considers the uncertainty in the allele frequency estimation (POLYRELATEDNESS) and 83 programs specifically developed for allopolyploids (FDASH), because most of the loci presented a disomic inheritance pattern (Obbard et al. 2006). Molecular variance analysis indicated that there is a low genetic difference between the group formed by the individuals occurring at the higher and lower sites. However, this difference was greater than expected by chance. This result was confirmed by the DAPC analysis which assigned the majority of the adult individuals to their actual region, even when we consider populations as groups. The Structure analysis also confirms this trend showing that the majority of individuals occurring in each region share the same allelic pool. In plants, an effective genetic isolation is caused by the restriction or lack of gene flow through pollen or seed dispersion (Yan et al. 2009). These could be the case of T. pulchra occurring in both regions but our analysis also suggests a genetic contact interface between individuals occurring in different regions. Therefore, we also suggest that the high reproductive and germinative capacities of T. pulchra (Zaia and Takaki 1998) associated with various reproductive events during its lifetime and the continuous distribution throughout the Serra do Mar, would cause such a contact interface between them. Differentiation among populations on a gradient can be understood by two possible processes influencing gene flow: isolation by distance or habitat differentiation (Bockelmann et al. 2003). In plants with short distance of pollen or seed dispersal, as probabily is the case of T. pulchra, long distance gene flow events may be very rare. Consequently, the increasing of geographic distance would lead to genetic isolation of the populations. On the other hand, drastic environmental differences in temperature, soil, luminosity and pollinator limitation may also restrict the establishment of seedlings and limit gene flow, leading to the differentiation between NSV and NP populations. Tibouchina pulchra is a pioneer species with a great area of distribution (Lorenzi 1992), its fruits produce thousands of seeds, dispersed by gravity and 10 to 30% are able to germinate in natural conditions (Brito, unpublished data). At the Serra do Mar mountain range, the distribution of this species is continuous, occurring from the restinga (sandbank) region to the more elevated regions (Lorenzi 1992). Although T. pulchra is widely distributed in the study area, the availability of pollinators varies drastically between both regions: at the more elevated region, the frequency of bees capable of collecting pollen from poricidal anthers is up to 200 times smaller than in the lower region (NP) (Brito and Sazima 2012). This may result in different pollen flow dynamics within populations, depending on the 84 elevation. Therefore, the differentiation between populations at NSV and NP seems to be mainly limited by gene flow by pollen and seed dispersal than by the capacity to establish seedlings. Moreover, the fact that these populations have some temporal shift in flowering and fruiting phenology (Brito and Sazima 2012) may also favour the genetic differentiation between populations (Hall et al. 1994). Genetic differentiation between populations on an elevational gradient has been demonstrated for several species of plants, in which diversity can increase, decrease or even fluctuate with the elevation in altitude (Yan et al. 2009; Zhao et al. 2006; Semagn et al. 2000). Specifically, the pattern of lower genetic diversity at higher regions, as we found for T. pulchra, was already described and attributed to genetic drift and bottlenecks occurring during range expansion from lowlands or clonal reproduction (Ohsawa and Ide 2008; Quiroga and Premoli 2007; Williams and Arnold 2001). Tibouchina pulchra does not reproduce vegetatively but, in our study, we cannot exclude neutral processes, as genetic drifts and bottlenecks, as the causes of genetic structure along the elevational gradient. However, ecological conditions, such as pollinator limitation, may also lead to the same genetic structure and diversity pattern and this should be stronger in plants exclusively pollinated by bees. Studies have already reported pollinator limitation at higher regions in the Andean and Alpine sites (Arroyo et al. 1985; Totland 1993), and the same was seen for T. pulchra occurring at the Serra do Mar mountain range (Brito and Sazima 2012). Nonetheless, our progeny analysis indicates that the relatedness of the progeny to the mother plant, as well as the relatedness among siblings from the same fruit, was not different between regions. These results refute our primary idea that low pollen variability delivered by bees to the stigmas is the main current cause for the lower genetic diversity at the higher region. Despite this result, the idea that the dynamic of pollen flow influences genetic diversity within the populations in each region still holds. If pollen has a better dispersal capacity than seeds, as seems to be the case for T. pulchra and most tropical trees (Loveless and Hamrick 1984), gene dispersal will depend almost exclusively on this component (Hardy et al. 2006). Therefore, we speculate that the pattern of genetic diversity found in T. pulchra populations is related to the different amount of cross-pollination events in each region. The lack of pollinators and the consequent pollen limitation observed in the higher region associated to the dependence on pollinators (due to pronounced herkogamy), would lead to a smaller fruit formation in higher areas, and a consequent low 85 input of new variants in this region. Even with greater flowering and greater germination rate of seeds produced by cross-pollination in NSV (Brito and Sazima 2012), the reduced number of bees does not ensure a mixture of allelic polls, as seems to happen in NP. The smaller values of genetic diversity measured by many indexes in NSV reinforce this idea. The lack of genetic variability within these populations would lead to an increase of inbreeding and decrease of the adaptive capacity (Reis 1996). However, to test the occurrence of inbreeding depression (Ellstrand 1992; Charlesworth and Charlesworth 1987) in these populations, studies with more comprehensive collections should be done in high elevation regions of Serra do Mar. Our study showed that T. pulchra populations occurring at two extreme regions of the elevational gradient of the Serra do Mar mountain range are genetically different and that the populations occurring at the higher region (NSV) have lower genetic diversity. However, despite the lack of genetic diversity differences among the populations within regions in the majority of the indexes considered, we also recorded genetic structure at this level, indicating that some processes not evaluated by this study are also determining these patterns. Spatial genetic structure in these populations was also stated, since geographically close population grouped together, and this should be considered in further studies. Our progeny analysis indicated that the variability of pollen grains delivered to stigmas was not the major process influencing the genetic diversity of T. pulchra in both regions. However, we suggest that the amount of cross-pollination events, which is much smaller at NSV, reduces the input of new mutations in this site. To specifically test this hypothesis, a further study comparing the structure and diversity of T. pulchra seedlings in both regions would be necessary.

Acknowledgements The authors kindly thank the help of our friends in the field and lab: Cristiano Silva, Marcelo M. Egea, Rafael S. Oliveira, Fernanda Piccolo and especially Desirée A. L. Meireles for intense dedication in lab work. We thank FAPESP for the scholarship provided to V.L.G.B. (Proc. Fapesp 2010/51494-5), the Fapesp grant to M.S. (2012/50425- 5) and CNPq grant to M. S..

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Table 1. Adult and progeny location and sample size (n) of progeny of Tibouchina pulchra situated in two regions: Núcleo Santa Virgínia (NSV) and Núcleo Picinguaba (NP), in the Parque Estadual da Serra do Mar. In each population, we collected total DNA for 15 adult individuals. 1 – Each number corresponds to the number of fruits collected from the same adults from the previous column, + signal is used to separate different adult origins. 2 – Each number corresponds to the number of seedlings collected from each fruit from the previous column, parenthesis indicates different adult origin and + signal indicates different fruit origins.

Designation Location of adults Fruits Seedlings from each Region Population (Latitude/Longitud with from each fruit (n)2 e) collected adult (n)1 fruits Santa Virgínia Entrada -23.35/-45.13 S146 + S157 2 + 2 (11 + 12) + (20 + 20) Santa Virgínia Fazenda -23.33/-45.13 S198 + S195 2 + 1 (20 + 20) + (15) Santa Virgínia Km 88 -23.37/-45.14 S138 1 (14) Santa Virgínia Km 86 -23.38/-45.16 S129 + S120 2 + 1 (20 + 20) + (20) Santa Virgínia Mirante -23.36/-45.12 S101 + S113 2 + 1 (21 + 21) + (21) Santa Virgínia Poço do Pito -23.34/-45.12 S183 + S189 1 + 1 (20) + (11) Santa Virgínia Posto II -23.34/-45.15 S169 1 (20) Picinguaba Almada -23.35/-44.87 P184 + P188 1 + 2 (10) + (20 + 14) Picinguaba Camburi -23.37/-44.80 P175 1 (20) Picinguaba Promirim -23.37/-44.96 P101 2 (20 + 20) Picinguaba Puruba -23.35/-44.94 P121 + P129 2 + 1 (20 + 19) + (20) Picinguaba Sede -23.36/-44.83 P202 1 (16) Picinguaba Ubatumirim -23.33/-44.92 P139 + P136 2 + 2 (20 + 20) + (20 + 17) Picinguaba Zero -23.35/-44.77 NA NA NA

Table 2. Results of the Analysis of Molecular Variance (AMOVA) for populations of Tibouchina pulchra situated in two regions: Núcleo Santa Virgínia (NSV) and Núcleo Picinguaba (NP), in the Serra do Mar State Park. Df – degrees of freedom.

Variation as Variation Variation Df Sum of Squares compared to a P value Source Percentage random process Within 195 1552.22857 91.554179 less < 0.001 populations Among populations 12 188.00751 5.938167 greater < 0.001 within regions Between regions 1 38.45291 2.507653 greater < 0.001

Total 297 2597.5906 100.000000

Table 3. ANOVA results for the analysis of genetic diversity indexes for Tibouchina pulchra occurring in higher (Santa Virgínia – NSV) and lower (Picinguaba – NP) regions. Df: degrees of freedom. Bold p values indicate significance at 95% confidence interval.

Total number of alleles F value Df p

Region 8.373 1 0.00464 Populations 1.848 12 0.04981 Locus 42.330 8 <0.001

Average number of unshared alleles between pairs of individuals F value Df p

Region 7.242 1 0.0083 Populations 1.093 12 0.3736 Locus 33.985 8 <0.001

Average number of different alleles carried by each individual F value Df p

Region 10.411 1 0.00168 Populations 1.138 12 0.33790 Locus 9.421 8 <0.001

Total number of phenotypes F value Df p

Region 8.283 1 0.00486 Populations 1.300 12 0.22984 Locus 30.473 8 <0.001

Average Shannon-Weaver phenotype diversity F value Df p

Region 7.442 1 0.00748 Populations 1.151 12 0.32811 Locus 28.480 8 <0.001

Average number of shared alleles between pairs of individuals F value Df p

Region 0.018 1 0.894 Populations 1.467 12 0.149 Locus 28.770 8 <0.001

Fig. 1 Map with population locations for Tibouchina pulchra in the Parque Estadual da Serra do Mar - SP. (A) Populations in the upper region at Núcleo Santa Virgínia (NSV). (B) Populations in lower region at Núcleo Picinguaba (NP). Each population was composed of 15 adult individuals.

Fig. 2 Density distribution of adult individuals of Tibouchina pulchra produced by the discriminant analysis after the retention of 24 PCs. Blue curve = Santa Virgínia (higher region, NSV) Red curve = Picinguaba (lower region, NP). The upper graph shows the retained PCs by the a-score.

Fig. 3 Discriminant analysis on principal components (DAPC) for adult individuals of Tibouchina pulchra considering 21 PCs retained by the a-score grouped by population. Blue: individuals collected in NSV region; red: individuals collected in NP region. Upper graph shows the retained PCs by the a-score. Lower graph shows the discriminant functions choose to produce the graph. Population names: Ent – Entrada; Faz – Fazenda; Kso – Km88; Kss – Km86; Mir – Mirante; Poc – Poço do Pito; Pos – Posto II; Alm – Almada; Cam – Camburi; Pro – Promirim; Pur – Puruba; Sed – Sede; Uba – Ubatumirim; Zer – Zero. Individuals are represented as dots linked to the centroid lines, populations are represented as inertia ellipses.

Fig. 4 Analysis performed by STRUCTURE 2.2.3 software for adult individuals of Tibouchina pulchra occurring in Santa Virgínia (higher region, NSV) and Picinguaba (lower region, NP). Grouping obtained by utilizing ancestry model with mixture and allele frequency correlated between populations without the population of each individual informed a priori showed the best K=2. Each color represents a group (K). Bars that present two colors indicate individuals that belong to more than one group. The size of each color bar represents the probability of the individual to belong to that group. In this graph, the individuals are grouped in accordance to the population in which they were collected. Population names: Alm – Almada; Cam – Camburi; Pro – Promirim; Pur – Puruba; Sed – Sede; Uba – Ubatumirim; Zer – Zero; Ent – Entrada; Faz – Fazenda; Kso – Km88; Kss – Km86; Mir – Mirante; Poc – Poço do Pito; Pos – Posto II.

Fig. 5 Comparison between genetic diversity indexes for Tibouchina pulchra occurring in higher (Santa Virgínia – NSV) and lower (Picinguaba – NP) regions. * indicates significance at 95% confidence interval. NS: non-significant.

Fig. 6 Boxplot showing the relatedness between progeny and the mother and among siblings individuals of Tibouchina pulchra occurring in higher (Santa Virgínia – NSV) and lower (Picinguaba – NP) regions. Boxplots show outliers as circles, the extreme of the lower and upper whisker as bars, the lower and upper hinges as the box extremes and the median as the darker line. NS: non-significant.

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Chapter IV

Trees as huge flowers and flowers as oversized floral guides: the role of floral color change and retention of old flowers in Tibouchina pulchra

Text edited and e submitted to Frontiers in Plant Science journal

Vinícius L. G. Brito1*, Kevin Weynans2,3, Marlies Sazima1 and Klaus Lunau2

1 Department of Plant Biology, Institute of Biology, State University of Campinas, Campinas, São Paulo, Brazil

2 Institut für Sinnesökologie, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany;

3 Institut für Genetik, Johannes Gutenberg Universität Mainz, Mainz, Germany

* Correspondence: MSc Vinícius L. G. Brito, State University of Campinas – Unicamp, Department of Plant Biology, Programa de Pós Graduação em Biologia Vegetal, P.O.Box: 6109, 13083-970, Campinas, SP, Brazil. [email protected]

Keywords: bumblebee, color preference, Atlantic Rainforest, flower-pollinator interaction, attractiveness, mass flowering

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Abstract

Floral color changes and retention of old flowers are frequently combined phenomena restricted to the floral guide or single flowers in few-flowered inflorescences. They are thought to increase the attractiveness over long distances and to direct nearby pollinators towards the rewarding flowers. In Tibouchina pulchra, a massively flowering tree, the whole flower changes its color during anthesis. On the first day, the flowers are white and on the next three days, they change to pink. This creates a new large-scale color pattern in which the white pre-changed flowers contrast against the pink post-changed ones over the entire tree. We describe the spectral characteristics of floral colors of T. pulchra and test bumblebees´ response to this color pattern when viewed at different angles (simulating long and short distances). The results indicated the role of different color components in bumblebee attraction and the possible scenario in which this flower color pattern has evolved. We tested bumblebees´ preference for simulated trees with 75% pink and 25% white flowers resembling the color patterns of T. pulchra, and trees with green leaves and pink flowers (control) in long-distance approach. We also compared an artificial setting with three pink flowers and one white flower (T. pulchra model) against four pink flowers with white floral guides (control) in short-distance approach. Bumblebees spontaneously preferred the simulated T. pulchra patterns in both approaches despite similar rewards. Moreover, in short distances, pollinator visits to peripheral, non-rewarding flowers occurred only half as frequently in the simulated T. pulchra when compared to the control. Thefore, this exceptional floral color change and the retention of old flowers in T. pulchra favors the attraction of pollinators over long distances in a deception process while it honestly directs them towards the rewarding flowers at short distances possibly exploring their innate color preferences.

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1. Introduction

Floral traits and their patterns in time and space are major keys to understanding plant- pollinator interactions and the diversification of angiosperms (Weiss 1991a; Lunau 2003; Schiestl and Johnson 2013). Traits like color, scent, size and shape mediate these interactions, advertising to the pollinators the amount and quality of resources and influencing their behavior (Schemske and Bradshaw 1999; Handelman and Kohn 2014). Particularly, flower color patterns are important to attract pollinators which are visually oriented at long and short distances, and may affect their flower constancy and preferences (Lunau, et al. 1996; Chittka et al. 1999).

Flower color changes during anthesis associated with retention of old flowers is a very common and widespread phenomenon in angiosperms. It occurs in at least 33 orders, 78 families and 253 genera (Weiss and Lamont 1997; Suzuki and Ohashi 2014). Previous studies have shown that this phenomenon creates new attractive units that directly influence the movement of pollinators, favouring both the optimization of the foraging behavior and plant reproduction (Delph and Lively 1989; Weiss 1991b). In general, there are two non- exclusive concerted hypotheses to explain flower color changes and the retention of old flowers in angiosperms. For pollinators at long distances, the size of the total floral display will be increased and, so will the number of pollinator visits (Gori 1983; Oberrath and Böhning-Gaese 1999). For pollinators at short distances, it is thought that their foraging efficiency will be improved, so that the number of superfluous visits decreases (Weiss 1995), because the floral color change honestly indicates rewarding flowers (Schaefer et al. 2004).

However, if the pollinators can discriminate the colors of new and old flowers at long distances, the effect of the increased floral display would be worthless, because they can learn to associate floral traits with the amount and quality of rewards (Lunau et al. 1996; Raine and Chittka 2007). Without attraction at long distances, the effects of floral color change at short distance could be achieved without the costs of the retention of old flowers because the flower visitors would not need to probe more flowers when their intention is to visit exclusively pre-changed flowers. Therefore, the old flowers should be similar to new 104 flowers at long distances, while the different floral colors should be discriminable to pollinators at short distances. If this is true, the effect of floral color change and retention of old flowers at long distances can be understood as a deception, while at short distances the same phenomena are honestly signalling the rewards to the visitors. Such an effect should be more evident in bee-pollinated flowers, because the spatial resolution of insect compound eyes is very poor and bees will recognize much less details of flower color patterns and see a rough color pattern or even a single mixed color dependent on distance (Vorobyev et al. 1997). Moreover, bees use different sets of photoreceptor inputs at long and short distances depending on the visual angle in which the target is viewed (Giurfa et al. 1996; Giurfa et al. 1997; Dyer 2006; Dyer et al. 2008). In this sense, different color attributes should also be important in the visual communication between flowers and pollinators in these plants when we consider long and short distances (Lamont 1985; Casper and La Pine 1984). Thus, we expect that green contrast (Chittka 1992) and spectral purity (Lunau et al. 1996), play different roles in the communication at long and short distances between plants retaining old flowers with an altered color and their pollinators.

Flower color change may be the consequence of a pollination event or be related to the natural senescence of the flower (Gori 1983; Gori 1989; Pohl et al. 2008). In most of angiosperms, and in several species of Melastomataceae) this change occurs just in some small parts of the flowers, e.g. the base of the petals, floral guides, filaments or ovaries, whereas color change in the entire corolla is more rare (Weiss 1991b). In Tibouchina pulchra Cogn., a common massively flowering tree of the Atlantic Rainforest, the color of the whole flower, including petals, stamens and style, changes from white on the first day of anthesis, when flowers are rewarding, to pink on the second to the fourth day, when they receive few or no visits (Pereira et al. 2011; Brito and Sazima 2012). This creates a color pattern that covers the entire crown of the tree, in which the newly opened white flowers are presented in a pink background of old flowers (Fig. 1a, b). On the other hand, other closely related Tibouchina species from the same phylogenetic clade (Michelangeli et al. 2013) change their color from white to red in a very small area at the centre of the purple corolla and these flowers are presented in inflorescences scattered in the green foliage. These differences among T. pulchra and its congeners highlights this system as a good 105 model to understand the evolutionary meanings of flower color change and retention of old flowers using an experimental design based on a natural condition.

Here we describe T. pulchra color patterns considering pollinator’s visual abilities, and add new insights on the phenomenon of floral color change and retention of old flowers in angiosperms. Our main goal is to describe the spectral characteristics of floral colors of T. pulchra, to test flower-visiting bumblebees´ response to this color pattern at different visual angles (as a proxy for distance), and to discuss the possible scenario in which this pattern has evolved. We specifically address the following questions: (i) how is the color change viewed when we consider the bee visual system? (ii) is this floral color change discriminable by the bee visual system? (iii) how do the relative spectral purity and the green contrast vary during anthesis? (iv) do these changes in color attributes favour the attraction of bees at long and short distances? (v) do naive bees prefer color patterns produced by T. pulchra viewed at long and short distance over the color patterns shown by congeneric species?

2. Materials and methods

2.1. Study species and site

Tibouchina pulchra is a common hermaphroditic flowering tree that occurs in disturbed sites and secondary forests in the Atlantic Rainforest of Brazil (Leitão-Filho et al. 1993). The large flowers are heterantherous and herkogamous, produce a weak scent and interact with bumblebees able to buzz the poricidal anthers and transfer the pollen to the stigmas of conspeciﬁc self-compatible ﬂowers (Pereira et al. 2011; Brito and Sazima 2012). This pioneer species produces many gravity-dispersed seeds with high germination rates and often quickly colonizes disturbed areas (Zaia and Takaki 1998).

The data collection of flower colors was made in the summer of 2012 at the Núcleo Picinguaba, Serra do Mar State Park, Ubatuba municipality, located on the northern coast 106 of São Paulo state, Brazil (23o20S, 44o50W). The climate is tropical and rainy, with a super-humid season from October to April (Morellato et al. 2000). The mean monthly temperature was 21.2oC and the mean monthly precipitation was 174.7mm between 2011 and 2013 (CPTEC 2013).

2.2. Floral colors

We took normal color and UV photographs of flowers in each of the 4 days of anthesis. Afterwards, we excluded the red information provided by normal photography and included the UV information as follows: we split the three color channels of normal photographs (blue, green and red) and replaced the blue channel by the red channel of UV photography (as the red sensor is UV-sensitive), the green channel by the blue channel of the normal photography and the red channel by the green channel of the normal photography. By this means, we could discern the floral color patterns of new and old flowers perceived by the visual system of a bumblebee. All this procedure employed the sofware Jasc Paint Shop Pro 9. The analysis of photographs in order to visualize bee-subjective colours has recently been advanced by Garcia et al. (2014) using digital images for representation of the spatio- chromatic signal variability. We also measured the spectral reflection of the bases and tips of petals from the 1st, 2nd, 3rd and 4th day flowers from 15 trees. These measurements were made using a USB4000 spectrophotometer (Ocean Optics, Inc.) coupled with a deuterium– halogen light source (D2H; World Precision Instruments, Sarasota, FL, USA) able to emit light between 215 nm and 1700 nm. All the measurements were taken at an angle of 45° to the petal surface and at the same direction relative to the petal (Chittka and Kevan 2005). We used barium sulphate as white standard and a black film can as black standard for recordings of the spectral reflection (Lunau et al. 2011). We used a standard background of green leaves and a standard daylight illumination (D65, Wyszecki and Stiles 1982), as well as the spectral sensitivity functions of bumblebee (Bombus terrestris) photoreceptors, to calculate the color locus of each measurement using the color hexagon, a model to understand the bee-subjective view of the flowers (Lunau et al. 2011; Chittka 1992).

To estimate the ability of bumblebees to discriminate flower colors, we performed a multivariate analysis of variance (MANOVA) using position of each flower color 107 measurement (base or tip) and days of anthesis as fixed factors and the values of x and y axis of the color hexagon as the response variable. We calculated the mean euclidian distance in hexagon units between the new white flowers and old pink flowers, and also among pink flowers of different age. As reference, bumblebees can distinguish correctly by 60 % between colors with 0.09 hexagon units of perceptual distance (Dyer 2006). From these color loci we also calculated the green contrast and the relative spectral purity of the base and tip of flowers from the first to the fourth day using the same color hexagon model (Chittka et al. 1994; Lunau et al. 2011). The green contrast is measured as the distance between the target color locus and the central point of the color hexagon representing the locus of the standard green background (Chittka 1992). On the other hand, the relative spectral purity is calculated as the proportion between the distance of the color locus from the center of the hexagon and the distance of the corresponding spectral locus representing the maximal spectral purity considering bumblebees' photoreceptor excitation from the same point (Lunau et al. 1996). We built generalised least-squares models considering the flower's day of anthesis and the positions of measurement as factors, to explore the differences in these components of floral color. We visually checked the standardized residuals vs the fitted values plot to conclude for the unnecessity of variance heterogeneity control in such models. The results of this analysis were compared a posteriori using the day of anthesis as factor in a pairwise t-test with false discovery rate (FDR)-controlling procedures (Benjamini and Hochberg 1995).

2.3. Bee preference experiments

We performed bumblebee preference tests using a Y-maze chamber in the laboratory for long- and short-distance color patterns using artificial paper trees and flowers built with colors simulating the actual colors of T. pulchra flowers. Each arm of the Y-maze was 140 cm long and the visual perception angle in each experiment was adjusted by moving the attraction units (artificial trees or flowers) back and forward in each arm (Giurfa et al. 1996). We used 2 neon tubes (OSRAM L58W/72-965 run with 30 kHz, providing about 2000 lux) above each arm of the Y-maze. As white flowers are kept on the tree during one day and pink flowers are kept during 3 days, we defined a color proportion of 25 % white and 75 % pink in all simulations of the color patterns of T. pulchra. All the artificial trees 108 and central flowers used were provided with a 50 % sucrose solution droplet at their center to serve as a reward. As control treatment we used a common color pattern that occurs in several congeneric Tibouchina species belonging to the same clade in Melastomae tribe phylogeny (clade J – Eartern Brazil, sensu Michelangeli et al. 2013) in which the base of the petals is white and the tip of the petals is purple (e. g. T. heteromalla, T. fothergillae, T. clavata, T. cf. langsdorffiana). In these species, the flowers change the color just in a very small area in the centre, from white to red, and, despite the retention of old flowers, they do not flower so massively as T. pulchra and present a number of discrete inflorescences among extensive green leaves. Thus we could test whether bees prefer the color pattern of T. pulchra produced by the massive flowering and retention of old post-change flowers to a common pattern produced by flowers with minimal (negligible) color change and no association to massive flowering. When developing the experimental setup we considered three behavioral responses of the bees towards the Tibouchina color patterns. Naive bees respond due to their innate preferences, but they lose their naivety as soon as they are rewarded; getting no reward is not regarded as a punishment for the bees since empty flowers are common in nature (Lunau et al. 1996). Experienced bees have learnt differences between rewarding and non-rewarding flowers and are supposed to change their preference accordingly (Niggebrügge and Hempel de Ibarra 2003; Spaethe, Tautz and Chittka 2001). A fundamental study about trained bees´ response to novel color stimuli showed that the bees chose novel colors according to their similarity to the trained color. Only if the tested colors were so different from the trained color that no generalization took place, choice behavior was not affected by the trained color but reflected innate preferences (Gumbert 2000). Recently it was demonstrated that trained bees show spontaneous color preferences only for disctint color attributes, e.g. colour purity, overriding learnt preferences for trained color stimuli, but not for other color attributes, e.g. dominat wavelength (Papiorek et al. 2013; Rohde et al. 2013). Here we assumed that these spontaneous preferences might be important for bees in guiding them to rewarding trees as well as to rewarding flowers irrespective of their experience and the amount of reward.

In the long-distance experiment, we used a visual perception angle of 3° (one paper square of 3 cm x 3 cm at 57.28 cm from the decision point). The artificial trees were built with 75 % of a pink background representing the old, changed flowers. This pink background was 109 spotted with 25 % of white representing the new flowers. The control trees were built with 75 % of green leaf background spotted with 25 % of pink flowers. In each chamber arm, the trees were presented against a green background simulating the forest where T. pulchra occurs (Fig. 2). With the visual angle of 3° we simulated the crown of a T. pulchra tree with 5 m diameter viewed from a distance of 95.5 m. For comparison, a single flower, 5 cm in diameter, can be viewed from a distance of 96 cm under a visual angle of 3°.

We used the same scenario to perform the short-distance experiment with a visual perception angle of 7° (3 cm diameter flowers at 24.52 cm from the decision point). Four T. pulchra flowers, one white central flower circled by 3 pink peripheral flowers, were presented against a green background simulating the green leaves. As control we used four identical flowers with 75 % pink on the periphery and 25 % white on the centre (Fig. 2). Thus we kept the same color proportion in the simulation of T. pulchra flowers and in the control treatment. In this setting, we also tested the number of approaches to peripheral flowers, because only the central flowers were rewarded with sugar solution in both treatments.

We made 12 consecutive trials with 10 naive workers of Bombus terrestris, trained once for each trial in the simulation or in the control and in the left or right side of the Y-maze chamber, totalling 120 approaches in long- and short-distance experiments. Therefore we used the treatment, the training simulation and the training side of the chamber as fixed factors and the bee identity as a random factor in generalised linear mixed-effects models with binomial error distribution . All the statistical tests were performed using the R 2.15.0 software using the packages stats, nlme and lme4 (http://www.r-project.org/).

3. Results

3.1. Floral colors

Tibouchina pulchra showed flowers change their color from white to pink during the four days of anthesis (Fig. 3). When we considered the bee-perceivable color spectrum, there 110 was a decrease in the reflection of green and the flowers become more bee-blue (without UV-reflection) (Fig. 3). This change was abrupt and occured simultaneously in the tip and the base of the petals. Although there was no difference between the color of the petals’ tip and base (MANOVA, F = 0.75, p = 0.47), the color of flowers of different days was different (MANOVA, F = 20.24, p < 0.01). The color of these petal parts on the first day occupied a different locus in the color hexagon when compared to the colors on the next days of the same petal parts (Fig. 4). The mean distance between the new white flowers and old pink flowers was 0.118 ± 0.032 color hexagon units, while the distance among pink flowers on different days was 0.065 ± 0.022 color hexagon units.

There was an interaction between the day of anthesis and the base and tip of petals when explaining the green contrast component of flower color (F = 9.98, p < 0.01) (Fig. 5a). The green contrast decreased during anthesis and the change was more pronounced in the base of petals. There was also a decrease in the relative spectral purity of flowers during anthesis (F = 4.09, p < 0.01), but there was no difference between the base and the tip of petals (ANOVA, F = 3.71, p > 0.05) and no interaction between these factors occured (ANOVA, F = 0.38, p > 0.05) (Fig. 5b).

3.2. Bee preference experiments

The naive bumblebees spontaneously preferred the simulated artificial tree with original colors of T. pulchra over the tree simulating the congeneric species (control) in the long distance experiments (86 approaches, z = 2.50, p < 0.05) (Fig. 6a). This result was not influenced by the tree to which the bee was trained (54 approaches to the same training tree, z = -1.38, p > 0.05) or the side of the Y-maze chamber on which the bee was trained (58 approaches to the same training side, z = 1.64, p > 0.05). We found a similar pattern for the short-distance experiments: the naive bumblebee preferred the simulation of T. pulchra flowers, in which 1 white flower was circled by 3 pink flowers, over the congeneric control flowers (78 approaches, z = -2.12, p < 0.05) (Fig. 6b). This result was not influenced by the training flowers (60 approaches to the same training flowers, z = 0.01, p > 0.05) or the the training side of the Y maze chamber (65 approaches to the same training side, z = 0.33, p > 111

0.05). Moreover, the bees approached only 28 peripheral flowers in the simulated setting of short distance experiments, while they approached 55 peripheral flowers in the control setting (t test, t = -2.12, p < 0.05).

4. Discussion

The floral color change in T. pulchra occurs during the four days of the anthesis and the whole flower changes its color from white to pink in the human visual system. However, when we consider the bee visual system the change occurs mostly at the base of the petals in the green range of wavelength, which becomes less prevalent in the flower color composition during the anthesis. The bees cannot easily discriminate old flowers from different days of anthesis due to the small perceptual distance between their color loci. However, the new white flowers are distinct from the old pink flowers when we consider the distance of 0.09 hexagon units as a bee discrimination threshold (Dyer 2006). This result indicates that T. pulchra post-changed flowers, when retained at the treetop, create a background different from that of green leaves, covering the whole tree where the new flowers are exposed to pollinators. This pattern should be even more conspicuous for the bees once the production of green leaves decreases during the flowering time in T. pulchra and the treetop is covered almost exclusively by the new and old flowers (Brito and Sazima 2012).

In general, the retention of old flowers has been suggested to be a strategy to attract more pollinators at long distances by increasing the floral display size (Gori 1983; Weiss 1991b; Kudo et al. 2007). On the other hand, bees are unable to resolve the distinct parts of the color pattern at long distances, which limits their capacity to discriminate fine color patterns from a uniformly colored area at long distances (Dafni et al. 1997; Hempel de Ibarra, Vorobyev and Menzel 2014). Thus, it should be assumed that at long distances the bees see a single mixed color composed by the colors of the color pattern and their ratio. The results of the long-distance experiment indicate that the bees prefer the T. pulchra over the hypothetical ancestral tree. In this sense, it is noteworthy that T. pulchra does not display red (or subjective bee black) as a post-change color as many other flowers including other Tibouchina species do (Weiss 1991a, Weiss and Lamont 1997), because bees have a 112 very limited ability to see red (Lunau and Maier 1995). Since all colors involved absorb ultraviolet light, white as well as pink is spectrally pure bee-bluegreen, whereas red would appear similar to the green background color to which the eyes of the bees are adapted. The spectral reflectance properties of white and (pale) pink are more similar than that of white and red, and this should increase the overall attractiveness of the mixed colors of the tree in the forest gaps. However, it is still no trivial question whether the progress in attractiveness was mediated by the color mixed of one quarter white and three quarters pink of T. pulchra over the hypothetical ancestral color mixed of one quarter pink and three quarters green or the increased display size of a colored target object or even an interaction of these factors.

The short-distance experiment also showed that bees prefer the simulated T. pulchra floral composition to the control, in which the same amount of white and pink colors was presented. Moreover, in this experiment the bees made fewer mistakes (approaches to peripheral flowers) in T. pulchra simulated flowers, as was foreseen by the short distance hypothesis to explain floral color change (Weiss 1995). When floral color change is associated with retention of old flowers, the color differences at short distances should be associated with differences in floral resources to encourage pollinator visits (Lamont 1985). Moreover, such colour pattern associated with differences in reward, should be strengthened by the differences in scent between new and old flowers (Pereira et al. 2011). In the nectarless T. pulchra flowers the pollen is almost depleted during visits to the new white flowers, and therefore, visits to old pink flowers are rewardless and thus rare or non- existent (Brito and Sazima 2012; Pereira et al. 2011). When pollinators restrict their visits to newly opened white flowers, they increase their efficiency by getting more pollen per visit, besides promoting pollination and avoiding pollen wastage (Weiss 1995). Moreover, the color pattern of T. pulchra should also favour the movement of bees to longer distances, promoting outcrossing among different trees (Harder and Barrett, 1995; Sun et al. 2005).

The phenomenon of floral color change in plants is closely linked to the pollinators´ ability to learn and associate color with the amount and quality of rewards (Lunau et al. 1996; Raine and Chittka 2007; Pohl et al. 2008). In T. pulchra, a species strictly dependent on large bees to set fruits (Brito and Sazima 2012), the floral color attributes should also be important for the functioning of the strategy of floral color change considering long and 113 short distances. In addition to the low spatial visual resolution, bumblees are unable to distinguish colors at long distances, because they use only the information from green photoreceptors when the visual angles are lower than 2.7° (Dyer et al. 2008). Other bee species might use a deviant critical visual angle, e.g. for the Western honeybee the critical visual angle is 15° (Dyer et al. 2008), which means that a bumblebee is able to detect a T. pulchra tree from a distance that is more than 5 times larger than that of a honeybee. Bumblebees detect stimuli containing both green-receptor-contrast and colour contrast at a visual angle of approximately 2.3°, whilst stimuli that contain only colour contrast are only detected at a visual angle of 2.7° (Dyer et al. 2008). On the other hand, the respective viewing angles for honeybees amount to 5° and 15°. The maximal detection distance for a T. pulchra tree possessing a crown of 5 m diameter for bumblebees via green contrast amounts 125 m and 106 m via colour contrast, whereas honeybee have to approch to 57 m to detect the tree via green contrast and up to 19 m to detect it via colour contrast. Therefore, the calculation of the maximal detection distance for T. pulchra trees presumes that bees would detect the grouped flowers better than single flowers. The grouping of flowers into patches, experimentally simulated by three spatially separated disks – similar to the the experimental design in our study – as compared to a single disk improved their detectability by bees and such improvement of detectability should be stronger for bumblebees than for honeybees (Wertlen et al. 2008). Thus, in a long-distance perspective the pattern composed by the new and old flowers in T. pulchra, as well as the retention of these flowers in the tree as a whole, provides a large, attractive and deceptive object in the gaps of the forest for the bees. The attractiveness of the whole tree should be given by the high spectral purity values of new and old flowers, which also favours the discrimination of the trees in the green forest background while it does not indicate the differences between new and old flowers. In fact, experienced bumblebees exhibit a preference for spectrally purer colors over trained colors even if the perceptual color distance is small (Rohde et al. 2013). When this stimulus is perceived at long distance and an approach is made, the bee vision changes automatically to a color vision in which all the photoreceptors are used (Giurfa et al. 1996; Giurfa et al. 1997; Giurfa and Lehrer 2001; Dyer et al. 2008). In this context, the new rewarding and the old rewardless flowers of T. pulchra can be honestly discriminated and dominant wavelength, associated with the differences in the green 114 contrast among flowers from different days, should be the major mediator of the bee attraction process at short distances.

In general, bees have an innate preference for high spectrally pure and contrasting colors and this may explain the color patterns of flower structures in angiosperms (Lunau et al. 1996; Lunau and Maier 1995). Mostly, the floral guides display large visual contrast against the corolla and higher spectral purity than the corollas. This set is more spectrally pure than the green leaves, creating a unidirectional color pattern of increase in spectral purity that may direct the pollinators to the rewarding sites and reproductive structures of the flower (Lunau 1996). Floral color change is also present in other Tibouchina species, in which this change occurs only in the white base of the petals, while the periphery remains with the same color, often purple (e. g. T. heteromalla, T. fothergillae, T. clavata, T. cf. langsdorffiana). This color pattern creates the unidirectional floral color disposition in new flowers that is suspended in the old ones. As this color pattern is very common along the Tibouchina Brazilian clade (clade J – Eastern Brazil, sensu Michelangeli et al. 2013), we stated that, in T. pulchra, the retention of old pink flowers together with massive flowering favoured an enlargement of the previous floral guide to the whole periphery of the corolla. In fact, some individuals do present a pink color in the petals´ tip of their new flowers, probably a vestige of a pink corolla. Therefore, T. pulchra trees completely covered by flowers function as a huge flower in forest gaps and the new white flowers function as oversized large floral guides, guiding the pollinators to the reward and the reproductive floral structures.

The floral color change of T. pulchra is exceptional in multiple aspects. Floral color change in most flowers is restricted to floral guides or small flowers in many-flowered inflorescences (Weiss 1991b), whereas T. pulchra has large flowers which change their color in the entire visually signalling apparatus. In some plants, the floral color change is triggered by pollination (Gori 1983; Van Doorn 2002), but in T. pulchra color change indicates senescence and is associated with flower duration. Moreover, flowers dominate the visual display of the entire plant of T. pulchra, whereas green leaves normally dominate it in other plants. This has enabled us to use T. pulchra as a model plant to test experimentally the sustainability of long distance attractiveness hypothesis for the first 115 time. However, it remains open whether the color pattern, the display size or a synergetic effect of both is responsible for this bee preference at long distances, because these parameters were combined in our experimental setup. Future experiments might disentangle which of these parameters have been important for the evolution of flower color change and retention of old flowers. Future studies also might show whether the special floral color change of T. pulchra was favoured by the scattered distribution of the plants in rare disturbed areas, once it would favor the attraction of the pollinators from very large distances matching the average distances between single trees. Since the visual attention in a complex search task differs between honeybees and bumblebees (Morawetz and Spaethe 2012), the long distance signalling of flowering T. pulchra trees might represent a strategy to selectively address bumblebees, solitary foragers that largely rely on their own experience, instead of mass-recruiting honeybees and stingless bees. Recent studies have highlighted different search strategies in bees depending of environmental consitions and intracolony-communication (Morawetz and Spaethe 2012, Bukovac et al. 2013); however, it is still unknown whether tropical bumblebees, the most frequent flower- visitors and pollinators, possess a distinct search strategy. In this regard it seems noteworthy that the nectarless flowers of T. pulchra are not attractive to honeybees that are not capable of buzzing the flowers for pollen reward. T. pulchra thus might benefit from adjusting their visual display for pollinating bumblebees.

In this study, the long-distance experiment demonstrated that naive bumblebees prefer the simulating trees with color change over the control model in which there was no color change or massive flowering. The same preference was found in the short-distance experiment demonstrating that both long- and short-distance hypotheses can explain this phenomenon in angiosperms, as previous studies have shown (Casper and La Pine 1984; Delph and Lively 1989; Weiss 1991b; Weiss and Lamont 1997, Ida and Kudo, 2003). Furthermore, we suggest that different attributes of floral colors play different roles in long and short distances regarding the attraction and direction of pollinators among flowers. Moreover, because we performed our experiments with naive bumblebees, the results reinforce the idea that floral color change creates color a patterns that increase unidirectionally the attractiveness from the greens leaves to the new flowers. In this sense, 116 floral color change when associated with retention of old flowers, could be favoured in angiosperms by exploring innate preferences of bees (Lunau 1996, Papiorek et al. 2013).

5. Acknowledgement

We thank the Instituto Florestal (Parque Estadual da Serra do Mar, Núcleo Santa Virginia and Núcleo Picinguaba) for permits to study in protected public land (license COTEC/SMA no. 260108-011-806/2010). We thank Sarah Papiorek for the flower photos, Leonardo R. Jorge and Carlos H. Tonhatti for statistical support, Pedro J. Bergamo, Ann Thorson and Prof. Kazuharu Ohashi for kindly review and improvement of previous versions of the manuscript. VLGB and MS received grants from FAPESP (2010/51494-5 and 2012/50425- 5) and the Conselho Nacional de Desenvolvimento Cientíﬁco e Tecnológico (303084/2011- 1).

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7. Figures

Figure 1. Floral color change and retention of old flowers in Tibouchina pulchra. (A) A T. pulchra tree in flowering peak, covered by old pink flowers and new white flowers. (B) Close-up showing the pink background made by old pink flowers spotted with new white flowers.

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Figure 2. Experimental settings of long-distance experiment (A) and short-distance experiment (B) to test the bee preferences in a Y-maze chamber.

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Figure 3. Color patterns of T. pulchra flowers from the first to the fourth day of anthesis. Photos are shown in conventional photography (red, blue and green channels) and replacing the blue channel by the red channel of the UV photography (as the red sensor is UV- sensitive), the green channel by the blue channel of the normal photography and the red channel by the green channel of the normal photography in order to reveal the bumblebee color vision perception. Average reflectance curves of the base (solid line) and tip (dotted line) are given for each day of anthesis. Shadow indicates the standard deviation. N = 15 individuals.

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Figure 4. Color hexagon coordinates showing the locus of base (B) and tip (T) colors of petals from T. pulchra flowers. Color measurements were taken on the first (1), second (2), third (3) and fourth (4) days of anthesis (graph model inspired by Suzuki & Ohashi 2014).

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Figure 5. Green contrast (A) and relative spectral purity (B) variation along the four days of anthesis in base and tip of petals of T. pulchra flowers. Bars indicate standard error. Letters indicate significant differences (p < 0.05) between the days after pairwise t-test with FRD-controlling procedures.

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Figure 6. Number of bee approaches in (A) long-distance experiment and (B) short- distance experiment simulating color patterns of T. pulchra. *** < 0.005 significance using a logistic regression model. (NS) non-significant.

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Appendix I

Ecologia cognitiva da polinização

Text edited and published as a chapter in Biologia da Polinização. Eds. Rech, AR, Agostini, K, Oliveira, PE & Machado, IC. Editora Projeto Cultural, Rio de Janeiro- RJ. ISBN: 978-85-68126-01-1.

Vinícius L. G. Brito1, Francismeire J. Telles2 e Klaus Lunau3

1. Programa de Pós-Graduacão em Biologia Vegetal, Instituto de Biologia, Universidade Estadual de Campinas. CEP: 13083-970 – Campinas-SP – Brasil – Caixa postal 6109 – e- mail: [email protected] 2. Estación Experimental de Zonas Áridas (EEZA/CSIC), Departamento de Ecología Funcional y Evolutiva, Ctra. de Sacramento s/n, La Cañada de San Urbano, 04120 Almería, España. 3. AG Sinnesökologie, Institut fur Neurobiologie, Heinrich-Heine-Universitat Düsseldorf, Universitätsstr. 1, 40225 Düsseldorf, Alemanha

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Resumo As características florais com as quais nos deparamos em nosso dia a dia podem atrair facilmente a nossa atenção e despertar nossos sentidos através dos estímulos que emitem, como cores e odores. Porém ditos atrativos não evoluíram em resposta a nosso sistema sensorial e capacidades cognitivas. O surgimento de determinados padrões florais, como cor, forma, tamanho, capacidade de emissão de odores, presença de estímulos táteis, térmicos, gustatórios etc., em cada grupo de plantas, é o resultado de um processo interativo entre plantas e seus visitantes. Assim, explorar o sistema sensorial e cognitivo de animais que buscam por fontes de energia como pólen e néctar é a chave para plantas que necessitam de vetores para facilitar o movimento de pólen entre indivíduos coespecíficos. Essa interação, que teve início há cerca de 150 milhões de anos, tem sido interpretada como a principal causa da alta diversidade das angiospermas. Então, para entender os processos evolutivos que levaram à diversidade dos sistemas de polinização em angiospermas é fundamental levar em consideração a capacidade sensorial e cognitiva de seus polinizadores. Neste capítulo pretendemos descrever o funcionamento dos principais sistemas sensoriais e as capacidades cognitivas dos visitantes florais, além de introduzir diferentes processos de interação entre estes e as características florais e apresentar a existência de outros mecanismos evolutivos, como a inércia filogenética, a exaptação e a deriva, que também podem ter contribuído para o surgimento dessa enorme diversidade floral que percebemos hoje nas angiospermas.

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Introdução Os animais polinizadores, ou visitantes florais em geral, reagem aos atrativos e recursos através do instinto e aprendizado. Os sinais florais e os sistemas sensoriais desses animais interatuam, selecionando e ativando diferentes mecanismos e rotas que, por sua vez, são dependentes da atividade que o visitante procura realizar. Não deveria ser difícil, portanto, imaginar ou ao menos nos permitir chegar à conclusão de que esses organismos usam, de maneira similar à nossa, as informações que estão disponíveis ao seu redor. Esse processo interativo com o mundo físico está modulado pela capacidade individual de cada organismo em captar, processar e armazenar os sinais através do uso de órgãos sensoriais e memória da mesma maneira como nós o fazemos. Visão, fragrâncias e sabores, tato, sensibilidade eletromagnética, noção de tempo, estimação de distâncias, medida de direção, estabelecimento de pontos de referências e, ainda, uma memória para armazenar e lembrar todas essas informações de maneira seletiva (Kevan & Menzel 2012) seriam parte dessa rede de comunicação entre as formas de vida e o ambiente físico, estando estruturados e adaptados de acordo com os ecossistemas aos quais pertencem. Desde os tempos de Darwin, a comunicação animal tem sido objeto de grande interesse e, mesmo depois de tantos anos de estudos, a tentativa de desvendar o mistério que circunda o tema em diferentes níveis funcionais continua. Ainda temos muito o que descobrir sobre a evolução dos sinais percebidos e emitidos por diferentes espécies e as respostas produzidas através do processamento dessa informação, que finalmente será refletida no comportamento do animal. Essa integração entre sinais e respostas comportamentais tende a ser modulada, ou facilitada, por processos cognitivos. As características cognitivas, como qualquer outra característica animal, são determinadas por combinações entre fatores genéticos e ambientais. Podemos imaginar que indivíduos de uma mesma espécie exibem uma ampla variação em fitness e que isto é determinado em parte pela variação hereditária em suas características cognitivas. Consequentemente, essas variações foram, são ou serão submetidas à evolução através do processo de seleção natural e, portanto, podemos contar com os conhecimentos ecológicos e evolutivos ao estudar cognição (Dukas & Ratcliffe 2009). O conceito de cognição, de maneira ampla, pode ser referido como a capacidade de adquirir, processar, reter e, posteriormente, utilizar a informação captada através dos sentidos. A cognição pode ser dividida em vários componentes inter-relacionados e talvez 132 indissociáveis: a) percepção – tradução dos sinais ambientais em representações neuronais; b) aprendizado – aquisição e retenção das representações neuronais obtidas; c) memória de trabalho – ou memória de curto prazo, constituída por um pequeno conjunto de representações neuronais – ou informações – ativas durante um curto período; d) memória de longo prazo – representações passivas armazenadas previamente, referentes à informação aprendida; e) atenção – ativação das representações neuronais quando o estímulo está disponível em um dado momento; e f) tomada de decisão – execução de uma ação de acordo com a informação disponível sobre as características ambientais relevantes e experiência prévia (Dukas 2004; Dukas & Ratcliffe 2009). Para entender por que a cognição é potencialmente importante no contexto da biologia da polinização faz-se essencial primeiramente o conhecimento de como esses animais percebem e respondem ao mundo que os rodeia. O que nós buscamos nas próximas páginas desse capítulo é fazer com que o leitor entre nesse universo sensorial e entenda como ele é percebido e discriminado por animais que dispõem de mecanismos e sensações como as nossas, algumas vezes em uma escala menos refinada e outras centenas de vezes mais precisas e detalhadas, mas com interações criticamente estabelecidas e baseadas em sua história ecológica e evolutiva, resultando na maioria das vezes em relações harmonicas e efetivas com o mundo físico.

Cor e sua percepção Entender o conceito de cor não é tarefa das mais fáceis e parte desse exercício consiste em interpretar as sensações humanas. Embora em nosso dia a dia muitas vezes nos guiemos pelas características visuais que os objetos apresentam – as mudanças nas cores do sinal de trânsito, um fruto maduro, um céu cinza ou ensolarado, entre outros –, não paramos para pensar que a cor, aparentemente apenas representando uma propriedade dos objetos, também está diretamente relacionada à capacidade de processamento visual e sensorial de um organismo. Para perceber e reconhecer diferenças entre cores muitas vezes recorremos a distintas propriedades das mesmas. Nós, seres humanos, temos a capacidade de discriminar entre elas através de mecanismos cromáticos (matiz e saturação) ou acromáticos (brilho). Ainda que soe estranho dizer que acromaticidade possa representar cor de alguma maneira, tomemos como exemplo pessoas com visão de cores dicromata, chamadas de daltônicas, 133 que podem discriminar entre tons de verde e vermelho considerando a diferença de brilho entre eles. No caso da visão em cores e não apenas discriminação entre cores, precisamos mais do que a habilidade de perceber diferenças acromáticas: devemos ser capazes de identificar um objeto ainda que seu par oposto ou o fundo no qual esteja sendo apresentado tenham a mesma quantidade de brilho (Kelber et al. 2003). Uma breve definição e a representação visual (Fig. 19.1) das propriedades de uma cor tornam-se necessárias então:  Matiz: é o que reconhecemos por “cor” propriamente dita; é o estado puro da cor sem o branco ou o preto agregado. Está associado com o comprimento de onda dominante e é o que nos permite distinguir ou nomear em que classe espectral se encontra um objeto – vermelho, azul, verde, etc.;  Saturação ou croma: refere-se à pureza ou intensidade da cor em particular, vivacidade ou palidez da mesma. Também pode ser definida pela quantidade de cinza que uma cor contém: quanto mais cinza ou neutra for, menos saturada é a cor. Por exemplo, partindo de um vermelho puro e rico, este seria menos saturado ao se adicionar algum valor de cinza;  Brilho: usado para descrever quão clara ou escura parece uma cor com respeito ao seu matiz original. A descrição clássica dos valores corresponde a claro (quando há determinadas proporções de branco), médio (quando há determinadas proporções de cinza) e escuro (quando há determinadas proporções de preto). Levando em conta todos esses parâmetros, podemos predizer que o conceito de cor não se refere apenas à quantidade de luz refletida por um objeto em cada comprimento de onda visível para o observador. Por exemplo: a cor percebida de um determinado verde de uma folha não seria apenas a refletância do comprimento de onda verde, mas também um componente abstrato e subjetivo (Willmer 2011), dependente da variação da iluminação natural ou artificial presente no ambiente e do contraste produzido entre o objeto e o plano de fundo (Faruq et al. 2013). É importante reconhecer que comprimentos de onda e cor não pertencem a um mesmo conceito. Comprimentos de onda, por si sós, são “incolores” e as cores que vemos são resultados subjetivos de nossa análise desses comprimentos de onda visualizados. Em uma linguagem mais filosófica, cores subjetivas (vermelho, verde, etc.) são frutos da nossa percepção pessoal (qualia), cuja natureza não pode ser demonstrada para outros. O espectro 134 visível para seres humanos e a maioria dos primatas não humanos, ou a faixa visível de longitudes de onda, está entre 400 e 700 nm, com alguma sensibilidade acima dos 800 nm. Para muitos outros animais, incluindo pássaros, peixes e muitos artrópodes, esse espectro se estende na faixa do ultravioleta, de 400 a aproximadamente 320 nm (UVA). Nas aranhas- saltadoras (Salticidae) essa distribuição abaixo dos 315 nm (UVB) e é utilizada no contexto de reprodução, incluindo o cortejo. Muitas flores possuem atrativos na faixa do ultravioleta (UVA), que, apesar de serem imperceptíveis aos nossos olhos, são distinguíveis pelos polinizadores (Land & Nilsson 2002). Objetos ao nosso redor refletem diferentes comprimentos de onda em diferentes proporções. Ser capaz de analisar de alguma maneira essa distribuição da luz que chega aos olhos provê vantagens e pode ser uma ferramenta útil para os animais identificarem e classificarem objetos que sejam relevantes em um determinado contexto. Levando isso em consideração, podemos utilizar as propriedades das cores para construir o que é conhecido como espaço de cores para um determinado animal, considerando as características de cada sistema visual. Para seres humanos que possuem células visuais (conhecidas como fotorreceptores e divididas em cones e bastonetes) que respondem aos comprimentos de onda na faixa do azul, verde e vermelho podemos construir um espaço de cor tridimensional, onde cada um dos eixos pertencentes ao espaço geométrico de cores estaria representando o valor de excitação de cada um dos fotorreceptores (para maiores detalhes sobre espaço de cores, ver Feitosa-Santana et al. 2006). Por previamente conhecer a capacidade perceptual do sistema visual humano e classificá-la como tricromática (pela presença de três tipos distintos de fotorreceptores), podemos criar uma representação geométrica de forma triangular para definir o matiz percebido, com base na estimulação relativa de cada fotorreceptor. Assim, um objeto de determinada cor, como, por exemplo, uma flor amarela, poderá ser representado em um local específico dentro deste espaço. Considerando, portanto, os tipos e a quantidade de fotorreceptores presentes nos olhos dos animais, podemos determinar a maneira com a qual as cores de diferentes comprimentos de onda emitidas por diferentes objetos estimulam as células visuais. Tendo a abelha-do-mel (Apis mellifera) como principal organismo ao se estudar a visão em insetos polinizadores, dada a sua longa relação com os homens e o interesse despertado desde épocas remotas, o primeiro modelo de percepção de cores foi elaborado para essa espécie (Backhaus 1991), seguido de um modelo aplicável aos himenópteros de maneira geral 135

(Chittka 1992) e, mais recentemente, de um modelo baseado em processos físicos de absorção da informação luminosa (Vorobyev & Osorio 1998). Esses modelos proporcionam informação sobre a detecção e discriminação de estímulos visuais e representam ditos estímulos dentro de um espaço de cores. A distância entre dois estímulos coloridos, ou entre um estímulo colorido e o plano de fundo no qual este está sendo apresentado, pode ser interpretado como a sua distância perceptual, de modo que valores mais próximos a zero (numa escala hipotética de 0 e 1) indicam maior dificuldade de discriminação entre a cor e seu plano de fundo, ou entre esta e uma segunda cor, enquanto valores mais próximos a 1 indicam uma discriminação superior a 75%. Para animais com visão tricromática, os valores de excitação dos três tipos de fotorreceptores são usados para se calcular a posição ocupada por um determinado estímulo que está sendo visualizado, dentro de um espaço geométrico de cores, como anteriormente mencionado no caso dos humanos. Diferentes modelos predizem diferentes posições e distâncias (Fig. 19.2) e cabe ao investigador aprofundar-se mais na hora de selecionar um deles e saber se suas premissas correspondem e se ajustam ao comportamento dos organismos testados (ver Vorobyev & Brandt 1997 para uma revisão dos modelos). Desse modo, podemos imaginar que, de forma geral, as flores disputam a atenção dos seus possíveis agentes polinizadores usando uma ampla gama de cores para gerar sensações e serem discriminadas. Esses agentes, por outro lado, estão equipados com pigmentos visuais capazes de decodificar a informação refletida pela superfície desses estímulos. Considera-se que todos os insetos polinizadores são sensíveis à faixa do ultravioleta e, apesar de não sermos capazes de enxergar nesse comprimento de onda, muitas flores de diversas famílias refletem nessa faixa do espectro (Guldberg & Atsatt 1975), permitindo que animais capazes de perceber esses comprimentos de onda explorarem um novo mundo de possibilidades visuais, como veremos adiante.

Visão em cores: um novo mundo de possibilidades A ciência da visão em cores e os processos psicofísicos associados ao seu estudo foram estabelecidos durante o século XIX para os seres humanos. A partir de então cientistas começaram a questionar se os demais animais também eram capazes de ver o mundo em cores (Kelber et al. 2003). Muitos dos conceitos e inferências utilizados atualmente ao se trabalhar com estes organismos provêm daqueles gerados através dos 136 estudos da visão humana. Após as observações pioneiras de Lubbock (1888) demonstrarem que o microcrustáceo Daphnia sp. era capaz de ver o mundo em cores e que as abelhas-do- mel são capazes de associar recompensas com cores, foi a vez do então ganhador do prêmio Nobel Karl von Frisch, em 1914, diferenciar o uso de sinais cromáticos e acromáticos por insetos usando também a abelha-do-mel como modelo. Nesse experimento, von Frisch alimentou abelhas operárias com solução de açúcar apresentada sobre um cartão azul durante a fase de treinamento. Após as abelhas aprenderem a associar o estímulo cromático com recompensa (solução de açúcar), elas passaram para a fase de teste, quando deveriam eleger o mesmo estímulo azul entre outros quinze cartões de vários tons de cinza, com pelo menos um deles contendo a mesma intensidade ou valor acromático daquele usado na fase de treinamento. Ele supôs que, se as abelhas fossem cegas para cores, elas confundiriam o cartão azul com os cartões cinza – ou pelo menos com aquele de mesmo valor acromático – , o que não aconteceu. Dessa maneira, von Frisch estabeleceu o uso da visão em cores pelas abelhas (Willmer 2011). De forma geral, o processo visual consiste basicamente em extrair a informação luminosa refletida pelos objetos e convertê-la em sinais neurais. Assim, para que haja visão em cores torna-se necessário, mas não suficiente, que o animal em questão tenha mais de um tipo de fotorreceptor ou pigmentos visuais em seus olhos, com diferentes sensibilidades espectrais. Isso se deve ao fato de que, com apenas um pigmento visual, comprimento de onda e intensidade não podem ser separados um do outro, sendo a visão em cores impossível. Esse processo começa uma vez que a luz chega a essas diferentes células fotorreceptoras – neurônios especializados em absorver a luz e convertê-la em sinais elétricos, processo conhecido como fototransdução –, gerando sinais neurais que passam ao longo e através de vários níveis estruturais, submetendo-se a um extensivo processamento da informação antes de a mesma ser retransmitida, depois de codificada. É esse caminho de processamento da informação que constitui a visão e a diferencia de processos fotossintéticos e outros, que são similarmente relacionados com absorção da luz (Fein & Szuts 1982). A diferença entre os fotorreceptores está principalmente na capacidade de excitação (Tab. 19.1) e na quantidade dos pigmentos visuais presentes nestas estruturas, variando entre organismos intra e interespecificamente. A maioria dos artrópodes e vertebrados possui ao menos dois deles. Entre os invertebrados a maioria é di ou tricromática, com 137 frequentemente um pigmento sensível na faixa do ultravioleta. Mas isso não quer dizer que não haja exceções: alguns insetos, como libélulas e borboletas, possuem cinco pigmentos, apresentando uma visão em cor complexa e sofisticada (Land & Nilsson 2002). De forma geral, abelhas têm visão tricromática, ou seja, possuem fotorreceptores com picos de excitação em três faixas diferentes do espectro visual: ultravioleta, azul e verde. A visão tricromática UV-azul-verde parece ser a condição ancestral de todos os insetos pterigota desde o Devoniano, existindo, porém, variações (Briscoe & Chittka 2001), como mencionado anteriormente. Outro grupo importante de polinizadores – as aves – possui visão tetracromática, isto é, quatro tipos de fotorreceptores em suas retinas, respondendo a comprimentos de onda na faixa do ultravioleta, azul, verde e vermelho (Finger & Burckhardt 1993). Isso faz com que a capacidade visual desse grupo seja inimaginável para nossa condição tricromática. Além disso, os cones das aves possuem pequenas gotas de óleo que filtram a luz, estreitando o espectro de cor que adentra estas células e diminuindo, provavelmente, a sobreposição nas respostas dos diferentes receptores presentes nos cones (Willmer 2011). Nos morcegos, de uma maneira geral, a visão desempenha um importante papel na detecção e prevenção dos predadores durante o forrageio e sobrevoo. Todavia, para aqueles que são polinizadores, o uso da visão dicromática poderia aumentar a capacidade de encontrar flores durante a noite, já que muitas flores noturnas apresentam refletância no ultravioleta (Müller et al. 2009). Existem dois tipos de fotorreceptores na retina dos mamíferos: os cones, utilizados durante o dia e capazes de detectar e diferenciar cores, e os bastonetes, especializados em visão noturna e contrastes. Apenas recentemente a visão em cores nos morcegos noturnos foi desvendada (Barton et al. 1995). A verdade é que dentro desse grupo existem mais de 1.100 espécies que podem ver cores, ainda que sua capacidade não seja tão excelente quando comparada com a de outros animais noturnos. O tipo de informação extraída do meio físico depende das necessidades específicas de cada organismo e da sua história evolutiva associada ao ambiente em que está inserido. Assim, ainda que os insetos pertençam a um grupo monofilético e que, partindo desse fato, poderíamos esperar que coleópteros, moscas, borboletas e mariposas teriam muito em comum com a capacidade visual das abelhas, o que realmente encontramos é um número imenso de diferenças inter e intrataxa (Weiss 2001). Além disso, indivíduos dentro de um mesmo grupo podem possuir capacidades distintas de perceber o meio que os cerca. 138

Portanto devemos considerar a existência de pequenas diferenças ou variações na sensibilidade com a qual um sinal é percebido pelo seu receptor (polinizadores) e considerar seus possíveis efeitos no fitness das plantas (Chittka et al. 2001). Essas considerações são fundamentais no entendimento das relações ecológicas e evolutivas entre plantas e seus polinizadores, já que estariam determinando a efetividade com a qual a transferência da informação genética estaria ocorrendo.

Preferência por cores Claramente a preferência por uma cor apenas pode existir se o organismo em questão possuir a capacidade de distinguir entre esta e o meio que a circunda. Em termos fisiológicos, essa capacidade de discriminação vem modulada pela presença de pigmentos visuais com diferentes sensibilidades espectrais, como vimos no item anterior. Além disso, devemos considerar que a distinção entre uma flor e o meio no qual ela se encontra também se dá por outros sinais visuais além da cor, como tamanho da flor, simetria, brilho, textura etc. Para seguirmos no entendimento da interação entre cores e o sistema visual dos polinizadores, devemos distinguir os termos “sensibilidade à cor” e “preferência de cor”. Sensibilidade à cor está relacionada com a capacidade de um sistema visual em detectar comprimentos de onda, enquanto preferência de cor apresenta uma base fisiológica e evolutiva. Por exemplo, uma mariposa pode responder a estímulos que refletem unicamente UV, mas isso não necessariamente significa que esta seja sua cor preferida quando em situação natural de forrageio. Basicamente, preferências de cor estão divididas em duas categorias: inatas e aprendidas, estando o aprendizado geralmente condicionado ao recurso floral oferecido (Lunau et al. 1996; Weiss 1997; Raine & Chittka 2007). Desta forma, assume-se que deve existir uma preferência inicial – inata – seguida de uma preferência associativa ou aprendida dos recursos disponíveis. Preferências aprendidas podem ser vistas como especializações temporárias dos indivíduos e são dependentes da capacidade de aprendizagem do organismo em questão. Não obstante, uma preferência aprendida pode ser perdida ou modulada em função da preferência inata ou da disponibilidade de novos recursos (Willmer 2011). A habilidade dos insetos em reconhecer flores com base na cor está geralmente descrita ao nível de ordem. Por exemplo, abelhas e vespas tendem a visitar flores violeta, 139 azuis, rosa, amarelas e, muito raramente, vermelhas. Besouros preferem flores brancas ou tons pastel, enquanto moscas apresentam atração por amarelo, vermelho fosco e marrom (Capítulo 7) (Miller et al. 2011). Porém, ainda que os insetos tenham uma preferência inata por determinadas cores, eles são frequentemente vistos forrageando em múltiplas espécies de plantas com diferentes características florais, o que se deve à capacidade visual desses organismos. Como vimos no item anterior, estes insetos podem identificar cores que vão desde a faixa do ultravioleta (320 nm) até próximo ao vermelho (600-650 nm), podendo reconhecer um leque amplo dessas e suas combinações. Além dos fatores relacionados com a capacidade visual, muitos outros podem modular a preferência de umas cores sobre outras. A facilidade de detecção de um estímulo contra o seu plano de fundo é, com certeza, um deles, uma vez que flores mais contrastantes podem ser mais facilmente detectadas e, portanto, receber mais visitas (Giurfa et al. 1997). De fato, um estudo demonstrou que os padrões contrastantes dos guias de néctar em relação à corola de Lapeirousia oreogena (Iridaceae) favorecem a polinização por moscas (Hansen et al. 2012). Essa detecção de um estímulo contra o seu plano de fundo a longa distância está modulada por processos acromáticos, no caso das abelhas e moscas. Estes insetos usam apenas os valores de estimulação do fotorreceptor verde, fazendo um contraste entre aqueles valores provocados pela cor da flor e aqueles pertencentes à habituação do plano de fundo. Uma vez que o estímulo é identificado, uma aproximação é feita e, quanto mais curta a distância, simultaneamente ocorre uma mudança automática no processo de identificação da flor, passando então ao uso das cores – canal cromático – para pouso e discriminação mais fina da mesma (Giurfa et al. 1996; Giurfa & Lehrer 2001). Um visitante floral que forrageia entre uma diversificada comunidade de plantas pode encontrar uma ampla variedade de flores, diferindo entre si em muitos aspectos. Então, como esse visitante seleciona uma flor para visitar consecutivamente no meio de tanta diversidade? Estudos experimentais sobre preferência por determinados padrões presentes nas flores podem responder a esta e muitas outras questões relacionadas a comportamento e escolhas feitas durante o forrageio dos visitantes florais. Para demonstrar preferências inatas, usualmente coloca-se o indivíduo à prova em experimentos conduzidos em situações controladas de laboratório, utilizando animais sem experiência prévia com cores. Por outro lado, para testar a preferência aprendida, ou mesmo a capacidade de aprendizagem de um polinizador, o mesmo dever ser treinado em 140 experimentos clássicos de associação entre cores e recompensas (Lunau & Maier 1995; Weiss 1997; Gumbert 2000). A maioria dos visitantes florais aprende rapidamente a associar estímulos coloridos com recompensas, como é o caso de abelhas e borboletas, convertendo-se assim em organismos modelo na hora de conduzir experimentos sobre capacidade visual. Assim, deve-se esperar que nem a taxa de visitação nem a taxa de eleições feitas por um visitante floral e observadas na natureza são provas de que existe uma preferência inata por determinadas cores, já que o suposto comportamento pode ser resultado de experiências prévias, com flores oferecendo recompensa floral de alta qualidade. Como resultado de um experimento em laboratório, podemos esperar que, se o processo de aprendizagem foi efetivo, as respostas comportamentais serão unicamente baseadas e moduladas pela recompensa prévia encontrda pelos visitantes nas flores. Dessa forma, um treinamento limitado pode afetar a preferência de cor nestes testes. Devido às dificuldades de se obterem estes tipos de dados, a maioria dos trabalhos que apresentam preferência de cor pelos polinizadores, principalmente aqueles associados às síndromes de polinização, não realizou os testes necessários para descobrir o tipo de preferência (Willmer 2011). Ainda que existam claras preferências determinadas e agrupadas por grandes classes taxonômicas e demonstradas através de experimentos comportamentais, algumas relações encontradas na natureza nem sempre estão demarcadas ou limitadas pelo processo de preferência por cores. Um bom exemplo que ilustra essa relação, ou a falta dela, é o trabalho desenvolvido por Lunau et al. (2011). Beija-flores não apresentam tipo algum de preferência floral inata quanto à cor, ainda que visitem frequentemente flores vermelhas. No processo de divisão e compartilhamento de recursos na natureza, uma hipótese foi criada tentando responder a esse comportamento: a de exclusão sensorial, que, no caso dos beija-flores, é aplicada quando assumimos que preferem flores vermelhas porque estas são acromáticas para abelhas (abelhas não possuem fotorreceptores que as permitam discriminar facilmente ou reconhecer “vermelho” através de mecanismos cromáticos, mas ainda assim são potenciais visitantes e competidores). Se essa hipótese estiver correta, devemos esperar que flores de outras cores polinizadas por beija-flores também sejam acromáticas para as abelhas. Para testar essa ideia, estes autores mediram as cores de flores vermelhas e brancas polinizadas por beija-flores com ajuda de um espectrofotômetro de refletância (um instrumento capaz de medir a curva de refletância para qualquer superfície). Para que uma flor vermelha seja 141 acromática para as abelhas, ela não deve apresentar refletância na faixa do ultravioleta. Por outro lado, para que uma flor branca seja acromática para as abelhas, ela deve refletir todos os comprimentos de onda de igual maneira. Nesse mesmo estudo também foi usado este mesmo procedimento para medir flores vermelhas e brancas polinizadas por abelhas. Neste caso, esperaríamos um padrão inverso: flores melitófilas vermelhas devem refletir também ultravioleta, enquanto as flores melitófilas brancas não devem refletir esse comprimento de onda. Esses foram justamente os resultados que eles encontraram, confirmando a hipótese de que as flores polinizadas por beija-flores exploram um nicho de cor que só os beija- flores, ou algum outro visitante floral com capacidade visual para tal, podem enxergar, como um canal privado de televisão!

Essências florais: vias de produção, mecanismos de percepção e polinização Flores de muitas espécies de plantas emitem essências capazes de atrair uma grande variedade de animais polinizadores, principalmente insetos (Dudareva & Pichersky 2000). Estas essências são tipicamente uma mistura de pequenos voláteis orgânicos produzidos por caminhos biossintéticos através de reações anabólicas e catabólicas, que variam quanto a seu peso molecular, polaridade e estado de oxidação. Devido à ampla diversidade de compostos voláteis e suas relativas abundâncias e interações, não existem duas essências florais que sejam exatamente iguais. Assim, essências florais são sinais que direcionam polinizadores a uma flor em particular, atuando principalmente como atrativos a longa distância, facilitando sua localização (Capítulo 7). Nos insetos, as antenas e, geralmente, partes da mandíbula possuem sensores olfatórios que são os responsáveis por interceptar as moléculas de odor. Cada um desses sensores apresenta entre dois a cinco neurônios que se conectam diretamente com o cérebro (Kaissling 1986). Já nos vertebrados como morcegos, aves e humanos, o epitélio nasal é o órgão responsável por interceptar as moléculas de odor (Lancet 1986). Deste epitélio, neurônios se projetam até os bulbos olfatórios no cérebro. Independente do animal em questão, essas moléculas de odor vão se ligar a proteínas específicas nessas regiões que desencadearão uma reação que culminará com a transmissão de um impulso nervoso até o cérebro, que posteriormente interpretará a mensagem como um odor específico (Dryer & Berghard 1999), inclusive indicando sua concentração. 142

Plantas tendem a sincronizar suas emissões máximas com os horários de pico de visitação de seus polinizadores, assegurando, assim, a atração dos mesmos numa escala temporal que favorecerá a visitação das flores que estarão prontas para serem exploradas. Plantas que maximizam seu potencial durante o dia são primariamente polinizadas por abelhas, moscas ou borboletas, enquanto morcegos e mariposas seriam os principais agentes de polinização para as flores que apresentam máximas emissões voláteis durante a noite. Um polinizador que reconhece um odor e pode voar seguindo um gradiente de concentração do mesmo poderá encontrar a próxima flor de uma mesma espécie mais facilmente. Além dos odores mais comumente presentes na natureza, como os adocicados e frutais, também há a ocorrência de odores que sugerem a presença de algo que de fato não é: moscas são atraídas por aromas considerados, segundo a percepção humana, putrefatos ou de fezes, produzidos por determinadas plantas para atrair visitantes e, assim, possíveis polinizadores. Até o momento, pouco é conhecido sobre como os insetos respondem a componentes individuais encontrados nas essências florais, mas está claro que eles são capazes de distinguir entre complexas misturas. Além de facilitar o processo de atração e indicação do recurso, os voláteis florais são essenciais para facilitar a discriminação entre flores de várias espécies ou até mesmo entre indivíduos dentro de uma mesma espécie. Por prover um sinal espécie-específico, as fragrâncias florais facilitam o aprendizado de um inseto visitante sobre um determinado recurso, aumentando sua eficiência de forrageio e a transferência de pólen, portanto a produção de buquês florais diferentes e únicos pode atuar como um mecanismo de isolamento entre as espécies de plantas, uma vez que cada mistura atrairá potencialmente diferentes visitantes florais. Os seres humanos são capazes de distinguir mais de 400 mil moléculas de odores e possuem trezentos receptores olfativos diferentes em seus epitélios nasais (Willmer 2011). Porém nós não somos os melhores perceptores de perfumes florais. Em um experimento realizado com 1.816 pares de odores florais, as abelhas-do-mel (Apis mellifera) foram capazes de distinguir 1.729 (Vareschi 1971). Além disso, as abelhas são capazes de diferenciar odores em concentrações que são imperceptíveis para nós e até mesmo diferentes concentrações de um mesmo odor. A disposição anatômica das duas antenas em diferentes locais na cabeça das abelhas, e provavelmente de todos os insetos polinizadores, permite uma percepção em “estéreo” dos odores no espaço, levando a uma percepção fina 143 de diferenças súbitas na concentração dos odores florais e auxiliando na movimentação desses insetos no espaço e localização do recurso em questão (Mafra-Neto & Cardé 1994; Willmer 2011). Devido à imensa quantidade de tipos e subtipos de moléculas relacionadas a essências florais, às diferentes misturas que podem ser produzidas entre elas e à complexidade dos sistemas olfatórios de cada um dos grupos de polinizadores, não existe, até o momento, um modelo que permita entender melhor a relação mediada pelo odor entre as flores e seus visitantes. De forma geral, técnicas de ordenação, como análises de componentes principais, permitem uma comparação entre diferentes odores e preferências por visitantes, mas nada que caracterize, especifique ou determine grupos unicamente a partir do sistema olfatório do polinizador, como ocorre no caso de modelos criados para estabelecer espaços visuais de percepção de cores, com base na relação entre fotorreceptores, sensibilidade espectral e capacidade de discriminação visual (Raguso 2001). De uma maneira geral, visitantes florais tendem a preferir flores que apresentam essências sobre aquelas sem nenhum tipo de atração volátil, o que nos dá uma pista sobre o papel desses compostos na biologia das plantas, sugerindo que essências florais podem ter um significativo impacto sobre as taxas de visitação às flores e a produção de sementes (Capítulo 7). Dito padrão associativo pode ter profundas implicações no nosso entendimento sobre a evolução de aromas florais mediada por polinizadores – ou vice-versa (Majetic et al. 2009). Há a possibilidade de que os sinais voláteis atuem de maneira crucial mediante situações mais complexas, como a busca de um recurso num dia nublado, identificação e reconhecimento de uma planta que pouco contrasta com o seu plano de fundo, ou, ainda, como possível chave na hora de identificar espécies dentro de uma relação mimética. Esse uso poderia desencadear interessantes questões sobre o peso dado aos distintos mecanismos sensoriais em diferentes e enigmáticas situações.

Interações entre canais sensoriais: ferramentas de comunicação entre plantas e polinizadores Ainda que as flores atraiam seus polinizadores, principalmente através de estímulos baseados na imensa gama de cores e nas distintas fragrâncias florais, devemos imaginar que as flores também “exploram” outros sistemas sensoriais além da visão e do olfato, como, por exemplo, o tato. Hoje sabemos que muitas flores melitófilas produzem uma epiderme 144 com células arredondadas que proporcionam estabilidade às abelhas no momento do pouso (Kevan & Lane 1985; Whitney et al. 2009; Whitney et al. 2011). Além disso, algumas flores possuem pelos ou filamentos que podem estar associados à estimulação tátil de seus polinizadores. Em vertebrados temos como exemplo a comunicação entre morcegos e flores quiropterófilas através do sistema de ecolocação, no qual essas flores produzem estruturas especialmente desenhadas para facilitar sua percepção em um espaço complexo. Em um experimento de campo foi observado que morcegos da família Glossophaginae são atraídos pelos ecos gerados a partir do estandarte da flor de Mucuna holtonii (Helversen & Helversen 1999). Esse estandarte possui um formato côncavo que reflete as ondas sonoras enviadas pelos morcegos. Quando estes estandartes foram preenchidos com um pedaço de algodão (não alterando a cor ou forma da flor), as visitas florais reduziram drasticamente. Além disso, esses pesquisadores demonstraram, utilizando sons artificiais, que a flor intacta é capaz de enviar de volta aos morcegos sinais sonoros mais fortes que botões florais ou flores modificadas experimentalmente (com pedaço de algodão no estandarte), demonstrando que a estrutura floral original é fundamental para a localização das flores pelos polinizadores. Existe também o caso de abelhas mamangavas que são capazes de distinguir variações no campo elétrico da flor através dos pelos que cobrem seu corpo (Clarke et al. 2013). Essa capacidade ajuda a abelha a perceber, no campo, quais flores de uma mesma espécie foram e quais não foram previamente visitadas, e quais, provavelmente, oferecem maior quantidade de recursos. Além disso, existem exemplos de interações entre flores e polinizadores a partir de estímulos termais (Raguso 2004) e também gustatórios (Kessler et al. 2008). Por exemplo, plantas como o café e os cítrus (laranja, limão, tangerina, etc.) produzem néctar com cafeína e esse composto aumenta a capacidade das abelhas de lembrarem um odor floral associado ao recurso e aprendido previamente (Wright et al. 2013). Desta forma, cada flor pode ser entendida como um verdadeiro mosaico sensorial, que produz diversos sinais perceptíveis pelos diferentes sistemas sensoriais e modulados pelo sistema cognitivo dos seus visitantes (Raguso 2004). Além disso, devemos considerar que cada flor, ou qualquer outra unidade de atração, configura uma diferente estratégia evolutiva que interage, através destes sinais, com seus visitantes, oferecendo-lhes em troca 145 alguma recompensa (na maioria dos casos, exceções na natureza existem, como no caso de plantas miméticas ou aquelas que emitem feromônios). Assim, de acordo com os pressupostos das síndromes de polinização, esperaríamos que cada uma destas estratégias estivesse bastante delimitada em “espaços cognitivos”, ou seja, que não houvesse sobreposição entre diferentes espécies de plantas na forma em que interagem com os sistemas cognitivos de seus polinizadores. Poderíamos pressupor também que essas diferentes estratégias são consequência de diferentes eventos de irradiação adaptativa entre flores e polinizadores ao longo do tempo evolutivo, o que explicaria a grande diversidade das angiospermas (Lunau 2004; Crepet & Niklas 2009). Esse não parece, porém, ser exclusivamente o caso (Schiestl & Dötterl 2012; Schäfﬂer et al. 2012). Tomando como exemplo a cor das flores, sabemos que a maioria delas está dentro do espectro visível de diversos visitantes florais, como ultravioleta, azul, branco (geralmente UV absorvente), rosa e amarelo (geralmente UV absorvente também) (Waser et al. 1996; Chittka et al. 2001). Assim, apesar do nosso entendimento comum de que sinais florais e a capacidade de identificação e percepção dos visitantes estão mutuamente sintonizados pela ação da seleção natural, devemos considerar também outras causas envolvidas nessas interações, como restrições filogenéticas, exaptação (um novo uso para atributos selecionados em um contexto evolutivo passado), pleiotropia (seleção através de atributos correlacionados) e processos evolutivos randômicos, como a deriva genética (Chittka et al. 2001). Um exemplo para esta questão é o caso anteriormente citado dos beija-flores e suas interações com flores vermelhas. Como vimos, a preferência dos beija- flores por estas flores se justifica mais pela hipótese de exclusão sensorial das abelhas do que pela hipótese de coevolução. Se os sinais florais como cor, odor, forma e tamanho são emitidos por duas espécies irmãs e posteriormente reconhecidos e não distinguidos entre si por visitantes florais dessas duas espécies, isso provavelmente não se deve, a priori, a uma adaptação às mesmas pressões seletivas nestas espécies. Imagine dois grandes gêneros ocorrentes na Mata Atlântica brasileira: Eugenia e Miconia. Estes dois grupos circunscrevem centenas de espécies que possuem flores bastante similares entre si, sendo que as diferenças taxonômicas são encontradas basicamente em suas características vegetativas. Assim, poderíamos supor que as características florais destas espécies sejam resultado de restrições filogenéticas, dada a rápida divergência dentro dos grupos, em vez de resultarem de 146 pressões de seleção nas características florais mediada pelo sistema cognitivo dos polinizadores. Essa hipótese permanece sem ser testada, mas abordá-la poderia ajudar no entendimento da conservação destas características florais nestes grupos. A coloração amarela UV absorvente apresentada geralmente pelos grãos de pólen é um exemplo que ilustra exaptação de sinais florais. Segundo Osche (1979), essa coloração já estava presente nos grãos de pólen dos ancestrais anemófilos e tinha por função a prevenção de mutações causadas pela radiação UV. Posteriormente, animais que puderam reconhecer esta coloração foram beneficiados, uma vez que o pólen é um valioso recurso protéico para os visitantes florais. Isso teria favorecido o surgimento de uma preferência inata por esta coloração. Muito tempo depois, Heuschen et al. (2005), analisando 162 espécies de plantas com flores e inflorescências multicoloridas, constataram que as cores predominantes nas regiões centrais dessas unidades atrativas eram menos variáveis que aquelas apresentadas na periferia e que estas cores, surpreendentemente, eram muito similares à cor dos grãos de pólen. Esse resultado sugere que a coloração de muitas flores pode ser explicada como uma forma de mimetismo batesiano, conhecida como mimetismo de pólen. Assim, a recorrente coloração amarelada encontrada em diversas flores teria sido selecionada pela preferência inata dos visitantes florais em busca de grãos de pólen, que, por sua vez, são amarelos apenas por causa da proteção conferida pelos carotenóides contra a radiação UV (Lunau & Maier 1995). Além disso, alguns autores sugerem que muitos dos pigmentos florais, ou mesmo as vias bioquímicas que levam à produção destes pigmentos, já existiam previamente como proteção contra herbívoros, radiação UV, congelamento ou outros eventos que poderiam interferir na sobrevivência das plantas (Levin & Brack 1995; Armbruster et al. 1997; Fineblum & Rausher 1997). Um exemplo de como a deriva genética poderia atuar na produção de novos padrões de sinais visuais pelas flores é o caso de Nigella arvensis, uma espécie que se distribui pelas penínsulas e ilhas do mar Egeu, ocorrendo tanto na Grécia quanto na Turquia. A diferença na localidade de ocorrência é acompanhada por diferenças no padrão floral, na forma e na coloração entre as diferentes populações das ilhas, e isso se deve provavelmente ao efeito gerado pelo processo de deriva genética, uma vez que as ilhas são pequenas e favoreceriam a fixação de alelos ao acaso (Chittka et al. 2001). 147

Apesar dos exemplos e sugestões citados, ainda existe uma enorme lacuna no entendimento dos processos, que não a seleção natural, os quais poderiam gerar a grande diversidade de flores dentro das angiospermas e as interações destas com seus visitantes.

Complexidade floral As flores utilizam uma grande variedade de sinais para atrair e indicar a presença de recompensas aos seus polinizadores. De forma geral, estes sinais frequentemente são transmitidos simultaneamente entre as múltiplas modalidades sensoriais, incluindo as visuais, olfatórias, gustatórias, táteis e, ainda, acústicas (Kaczorowski et al. 2012; Burger et al. 2012). Mantendo em mente a flor (ou qualquer outra unidade de atração dos polinizadores que esteja relacionada à reprodução das plantas) como um mosaico sensorial evolutivo que emite sinais para diferentes canais perceptuais dos polinizadores (Raguso 2004), podemos nos perguntar qual a funcionalidade dessa extrema complexidade floral. Segundo Leonard et al. (2011a), essa complexidade favoreceria evolutivamente a interação entre plantas e polinizadores através da capacidade de aprendizado e memória do último grupo. Do ponto de vista das plantas, há o favorecimento da transferência de pólen entre flores de uma mesma espécie e, consequentemente, a prevenção da perda de grãos de pólen em estigmas não coespecíficos (Waser 1978). Nesse contexto, visitantes florais incapazes de aprender e memorizar os estímulos apresentados pelas flores seriam inconstantes e, portanto, estariam diminuindo os níveis do recurso oferecido, interferindo no padrão de visitas daqueles polinizadores mais efetivos (Feinsinger 1987). Do ponto de vista dos polinizadores, a capacidade de aprender e memorizar permitiria uma identificação mais acurada das flores, promovendo uma maior eficiência no forrageio. Ao mesmo tempo, estes polinizadores estariam menos sujeitos à grande variação que existe na quantidade e qualidade das recompensas florais (Raine & Chittka 2007) e evitariam visitar flores que não oferecem recursos (Dafni 1984) ou que não sejam de igual ou superior qualidade ao que vinha sendo encontrado anteriormente. Junto a isso podemos entender que essa complexidade floral, em seus distintos níveis, atua como um filtro, repelindo, por um lado, interações com agentes antagonísticos (Junker & Blüthgen 2008) e favorecendo interações com mutualistas não polinizadores (Gonzálvez et al. 2013). Existem duas maneiras de se entender como o conjunto de sinais emitidos pelas flores influencia o aprendizado e a memória dos seus visitantes (Leonard et al. 2011a). O primeiro 148 deles é que cada sinal (como cor, odor, estímulos táteis etc.) atua de forma independente. Esse paradigma sem dúvida configura o arcabouço teórico em que a maioria dos estudos sobre ecologia cognitiva da polinização foi conduzida, uma vez que estes consideram a influência de apenas um estímulo e a resposta que o mesmo produz nos visitantes quando em situações experimentais (Leonard et al. 2011b). Para ilustrar como seria a ação independente dos estímulos florais vamos citar um exemplo teórico. Imagine uma flor que oferece uma recompensa ao seu visitante e que possui cor amarela e odor adocicado e outra flor que não oferece recompensa e que emite sinais diferentes, como cor azul e odor lavanda. Segundo a hipótese de ação independente dos estímulos florais, esperaríamos que os polinizadores fizessem escolhas mais acuradas quando estes dois estímulos ocorressem juntos do que quando ocorressem separados (como uma nova flor de cor amarela e odor lavanda). Assim, o componente adicional apenas provê mais informação sobre a identidade floral (Leonard et al. 2011a). Por outro lado, podemos imaginar que os estímulos florais interagem entre si e que o aprendizado de um facilita o aprendizado do segundo estímulo. De fato, abelhas mamangavas que aprenderam a discriminar flores artificiais com e sem recurso através da cor conjugada com a presença de algum odor fazem distinção entre essas flores artificiais mais corretamente que abelhas que aprenderam a discriminar as mesmas flores na ausência de odor (Leonard et al. 2011b). Como essa interação entre sinais pode facilitar o aprendizado e a memória dos polinizadores? Para responder a esta questão, primeiro devemos entender e diferenciar o que é aprendizado e o que é memória. Em um contexto cognitivo podemos definir aprendizado como a capacidade de adquirir novas informações e memória, como a capacidade de armazenar e posteriormente resgatar informações adquiridas (Leonard et al. 2011a). A memória dos animais pode ser dividida em dois tipos (mencionados anteriormente): memória de trabalho (muitas vezes também chamada de memória de curto prazo, que pode ser estocada por alguns segundos ou minutos) e memória de longo prazo (também chamada de memória de referência, que pode ser estocada por alguns dias ou mesmo por toda a vida do animal). Podemos imaginar como isso funciona em nós, humanos. Quando em determinadas situações precisamos guardar um número de telefone para em seguida o inserirmos em nossa agenda e não dispomos de algum outro recurso para fazê-lo naquele exato momento, durante essas frações de segundos entre o armazenar e o guardar estamos fazendo uso da nossa memória de trabalho. Quando procuramos um 149 edifício e nos equivocamos de número e logo alguém nos diz a numeração correta e saímos em busca do prédio até encontrar o número que buscamos também é outro exemplo do uso da memória curta, já que provavelmente não voltaremos àquele lugar ou não armazenaremos esta informação por não considerarmos relevante. Porém cada um de nós é capaz de se lembrar de números de telefone que talvez nem mais utilizemos (assim como o número da casa onde morávamos). Essa última é a nossa memória de longo prazo, determinada por eventos e informações que consideramos de suma relevância, independente da sua natureza. Os diferentes sinais emitidos pelas flores podem, quando recebidos em conjunto, facilitar o aprendizado e a memória dos polinizadores de três maneiras (Leornard et al. 2011a; Hebbets & Papaj 2005). Uma possibilidade é que um determinado estímulo previamente analisado atue como base ou fonte de informação na hora de descrever outro. Por exemplo, algumas espécies de beija-flores exibem coloração vermelha em suas plumagens e tendem a preferir, como vimos, flores vermelhas. As entradas de ninhos de abelhas muitas vezes são similares, em forma, tamanho e coloração, a flores comumente visitadas por elas. Assim, sinais florais podem atrair polinizadores explorando vieses sensoriais já existentes e, de fato, flores parecem usar essa estratégia mais comumente para enganar seus polinizadores do que para mimetizar outras flores (Schaefer & Ruxton 2010). Outra possibilidade é a conjunção de sinais florais, por meio da qual um deles aumenta a atenção dada pelo polinizador a um segundo sinal, ou seja, a detecção do primeiro sinal traz para a memória de trabalho a “imagem” do segundo sinal inicialmente associado a ele. Um experimento ilustra como isso ocorre em abelhas (Reinhard et al. 2004): na fase de treinamento, abelhas-do-mel foram alimentadas em bebedouros amarelos com odor de rosas e em bebedouros azuis com odor de limão. Na fase de teste, os bebedouros ficaram sem odor, mas as cores foram mantidas. Quando o odor previamente associado a um dos bebedouros foi novamente inserido (mas agora dentro da colmeia, estimulando as abelhas), as abelhas visitaram preferencialmente o bebedor da cor respectiva. Assim, os odores, além de serem usados para diferenciar entre flores de diferentes espécies (ver itens anteriores) podem também manter as abelhas focadas na procura de uma determinada fonte de recurso. A complexidade floral também pode facilitar o aprendizado e a memória por não permitir que outros estímulos sejam trazidos da memória de longo prazo para a memória de 150 curto prazo dos polinizadores. Por transmitir um estímulo múltiplo (que envolve cor, odor, forma, textura etc.), as flores garantem que seus polinizadores não se lembrarão de outros estímulos positivos que induzam a mudança de rota ou da espécie de flor aprendida. Isso aumenta as chances de que o polinizador permaneça fiel as suas flores, um fenômeno bastante conhecido e chamado de constância floral que será desenvolvido no próximo item.

Constância floral Quando um polinizador sobrevoa um campo à procura de recurso, geralmente ele se depara com muitas plantas em flor. Durante esta tarefa ele precisa comparar os sinais percebidos com sua memória prévia de outros sinais florais e dos recursos oferecidos outrora por essas flores, diferenciando flores entre aquelas que oferecem recursos adequados daquelas que são desconhecidas ou pouco recompensadoras (Waser 1986; Chittka et al. 1999). Assim, geralmente ele escolhe e restringe suas visitas a apenas poucas espécies de plantas, ignorando a existência de outras, ainda que estas sejam energeticamente iguais ou até mais recompensadoras (Hill et al. 1997). Dessa forma, podemos imaginar que ocorre constância floral quando existe preferência por parte de um dado polinizador por um ou múltiplos sinais emitidos pelas flores (como cor, forma, odor, estímulos táteis etc.), seja essa preferência inata ou aprendida. Essa constância floral interfere diretamente na reprodução das plantas por facilitar a transferência de pólen entre coespecíficos (Waser 1978). Além disso, como já vimos, visitantes inconstantes diminuiriam os níveis do recurso oferecido pelas flores, interferindo no padrão de visitas de polinizadores mais efetivos (Feinsinger 1987). Porém as vantagens do comportamento de constância para os polinizadores não estão totalmente claras. É importante aqui ressaltar a diferença entre visitantes florais constantes e visitantes florais oligoléticos. O primeiro termo é atribuído ao indivíduo de uma espécie, enquanto o segundo é um conceito relacionado à espécie como um todo, podendo envolver o comportamento de vários indivíduos. Existem várias explicações para a ocorrência de constância floral e por que esse tipo de comportamento seria favorável do ponto de vista dos polinizadores. A primeira delas, e talvez a mais debatida, é que constância floral ocorre basicamente porque existe uma limitação na capacidade de memorização dos polinizadores. Segundo Chittka et al. (1999), uma explicação simples, mas não suficiente, é a de que polinizadores (nesse caso 151 específico, insetos) seriam capazes de memorizar apenas uma simples tarefa como reconhecer ou manipular uma flor complexa e não muitas ao mesmo tempo, entretanto, pelo menos para as abelhas, esse parece não ser o caso. Abelhas possuem uma capacidade incrível de memorizar o espaço por onde transitam durante sua vida, podendo sempre retornar aos seus ninhos ou a fontes de recursos. Assim, a capacidade da memória de longo prazo parece ser bastante grande para, sozinha, explicar a constância floral das abelhas (Chittka et al. 1999). Por outro lado, abelhas treinadas em apenas uma tarefa são mais eficientes que aquelas que aprenderam mais de uma em um curto espaço de tempo. Elas cometem menos erros, apresentam um tempo menor de manuseamento das flores, corrigem erros rapidamente e as transições entre flores da mesma espécie são inicialmente mais rápidas (Chittka & Thomson 1997). Por exemplo, quando uma abelha é treinada a visitar um tipo de flor A, seguido de um segundo tipo B, e tem que voltar depois de um determinado tempo a eleger A outra vez, ela demorará muito mais tempo em reaprender a como visitar a flor A (Woodward & Laverty 1992). Além disso, se dois estímulos usados durante o treinamento (como cor e odor) são substituídos por dois novos estímulos da mesma natureza, a memória para os dois primeiros parece ser apagada (Menzel 1979), portanto dois novos estímulos não podem ser estocados simultaneamente na memória de trabalho das abelhas. Esse padrão também é comprovado em estudos de campo para abelhas: nos primeiros segundos de voo depois de uma visita floral, a probabilidade de a abelha visitar uma nova flor da mesma espécie é extremamente alta, mesmo quando flores de outras espécies estão presentes na mesma área (Chittka et al. 1997). O enfraquecimento, ou mesmo a completa eliminação, da memória de trabalho quando uma segunda tarefa é aprendida por um animal ficou conhecido como “hipótese de interferência”. Sua relação com a constância floral foi primeiramente atribuída ao próprio Darwin (Woodward & Laverty 1992; Goulson et al. 1997). Segundo ele, “É de grande importância para as plantas que insetos permaneçam visitando flores da mesma espécie... mas ninguém suporia que este comportamento é realizado para o benefício das plantas. A causa está, provavelmente, no aumento da capacidade dos insetos para trabalhar mais rápido. Eles apenas aprenderam como permanecer na melhor posição na flor, e quanto e em qual direção inserir suas probóscides. Eles agem com o mesmo 152 princípio de um artesão que precisa construir uma dúzia de engenhos e que poupa tempo fazendo primeiro cada uma das rodas e depois cada uma das outras partes.” Fica evidente que Darwin não se referiu à existência de uma interferência entre capacidades para executar tarefas simples, mas, sim, a que insetos são mais efetivos quando trabalhando em apenas uma tarefa. Chittka et al. (1999) argumentam que essa limitação na memória de trabalho poderia explicar por que abelhas se especializam em poucos tipos florais e propõem um cenário: depois de conhecer as flores, as abelhas são capazes de estocar mais de uma imagem floral e seus atributos cognitivos em sua memória de curto prazo. Mas a memória de flores familiares que não foram visitadas recentemente fica num estado de dormência na memória de longo prazo e seu acesso pode levar certo tempo. Assim, segundo esses autores, a constância floral pode ser mais um problema de processamento de informação do que da capacidade de armazenamento propriamente dita. Uma vez que toda informação estocada previamente não está continuamente disponível na natureza, as abelhas devem preferir flores que foram encontradas mais recentemente em sua história de vida. Além das limitações nas memórias de longo e curto prazos, também existem outras hipóteses que podem explicar o fenômeno da constância floral (Chittka et al. 1999). Por exemplo, o aprendizado de uma nova capacidade cognitiva, como manipular uma nova flor, pode ser desvantajoso pelo alto custo em tempo e energia. Outra possibilidade é que polinizadores constantes não procuram outras flores por não conhecerem os atributos qualitativos referentes aos recursos florais possíveis de serem encontrados. Assim, permanecer visitando uma flor que garante um retorno conhecido quanto aos seus recursos seria mais vantajoso que correr o risco da troca. Além disso, existe a ideia de que organismos sociais, como é o caso de algumas abelhas, evitariam competição entre indivíduos de uma mesma colônia, realizando visitas constantes em flores de diferentes espécies fazendo com que o retorno em recursos para a colônia como um todo seja maior já que seus indivíduos forrageiam e se especializam, temporalmente, em várias espécies. De fato, entre abelhas sociais, existem poucos indivíduos especializados em procurar novas fontes de recursos e estas serão informadas às operárias que forragearão constantemente naquela fonte de recurso para a qual foram recrutadas. Em biologia da polinização é comum o pensamento de que a morfologia floral está diretamente associada à morfologia de seus polinizadores, levando à ideia da especialização 153 como um fim evolutivo para tais sistemas (Futuyma & Moreno 1988; Tripp & Manos 2008). Essa é uma das consequências do paradigma das síndromes de polinização (Faegri & van der Pijl 1979), porém a compreensão das causas que levam à constância floral, ainda que em sua maioria estudada apenas em insetos, propõe um novo cenário explicativo para a enorme diversidade das angiospermas. Nesse sentido, formas florais complexas, por favorecer visitantes florais mais constantes, teriam vantagens sobre formas florais mais comuns em que os visitantes seriam menos constantes, levando a maior perda de gametas (Chittka et al. 1999). Esse cenário levaria a uma rápida irradiação adaptativa, o que de fato ocorreu na história evolutiva das plantas com flores (Lunau 2004; Crepet & Niklas 2009). Além disso, essa hipótese não reivindica que as interações plantas-polinizadores atuais ocorram par a par, que suas morfologias sejam complementares e que sejam resultado de adaptação darwiniana. Ainda, as especiações por favorecimento da constância floral poderiam ocorrer em simpatria, enquanto a especialização deve ocorrer mais provavelmente em alopatria (Wilson & Thomson 1996).

Conclusão Em um novo contexto de estudo em biologia da polinização, podemos entender que plantas e polinizadores (co) evoluíram a partir da capacidade sensorial e cognitiva desse último grupo (Shafir et al. 2003). Sabemos agora que o comportamento de preferência e de constância floral afetam o sucesso reprodutivo das plantas de forma significativa e que estes comportamentos são resultado das capacidades sensoriais (como visão, olfato, tato etc.) e processos (como memória e aprendizado) cognitivos dos polinizadores. Por outro lado, o sucesso reprodutivo dos polinizadores também está, direta ou indiretamente, relacionado a atratividade e recursos oferecidos pelas plantas. Assim, ditas capacidades e processos inerentes dos polinizadores atuam como um filtro subjetivo da realidade, mediando as possíveis interações e estipulando os diferentes níveis dentro dos quais elas podem ocorrer. Além disso, podemos agora imaginar que, assim como para nós, humanos (Varela et al. 1993), essas capacidades sensoriais estão incorporadas nos polinizadores e não há outra interação (ou outra realidade) além daquela que ocorre entre as características florais, as vias sensoriais e a capacidade cognitiva desses vetores de transferência de informação genética. Isso afeta sobremaneira a forma como o pesquisador descreve os padrões e os 154

processos geradores das interações planta-polinizador. O que importa, dentro da ecologia cognitiva da polinização, não é interpretar unicamente as características florais como o centro e a resposta a todos os processos evolutivos, mas, sim, como algo manifesto dentro de um espaço compartilhado entre plantas e visitantes florais. Assim, os estudos em biologia da polinização devem partir do princípio de que cada visitante floral possui uma capacidade de representação particular e complexa do mundo à sua volta. Conhecer ditas capacidades e entender como as características florais são representadas e interpretadas dentro desse espaço (seja visual, olfativo ou de qualquer outra natureza sensorial) é fundamental nos avanços em biologia da polinização.

Agradecimentos Aos mestres, por serem fonte infinita de inspiração em cada experiência particular apreendida através dos processos cognitivos, transformando ações, pensamentos e palavras em realidades libertadoras.

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Tabela 1. Diferentes espécies com seus respectivos fotorreceptores apresentando diferentes picos de sensibilidade espectral

Fotorreceptores (λmáx) Espécie UV Azul Verde Vermelho Bastonetes

Aranha-saltadora (Menemerus confusus) 360 490 520 580 – Abelha-do-mel (Apis mellifera) 344 436 556 – – Borboleta (Papilio xuthus) 360-400 440 520 600 – Peixe-dourado (Carrassius auratus) 356 447 537 623 522 Rãs (Ranna spp.) – – 502 562 430 Tartaruga (Pseudemys scripta) 360 450 518 620 – Galo (Gallus gallus) – 455 507 569 506 Golfinho (Tursiops truncatus) – – – 524 488

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Figura 19.1 Representação esquemática das diferentes propriedades das cores.

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Figura 19.2 Representação de três estímulos (flores) em dois espaços de cores de acordo com o sistema visual de Apis mellifera. (A) Modelo do hexágono de cores (Chittka 1992), esquinas representando fotorreceptores e as possíveis combinações entre eles de acordo com a refletância espectral do objeto que está sendo visualizado. (B) Modelo de oposição das cores (Backhaus 1991) e a distribuição relativa dos estímulos dentro deste espaço. 164

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Concluding remarks, caveats and future steps

This thesis has shown that solutions to the “pollen dilemma”, other than the heteranthery, should have arisen in Melastomataceae family as stable reproductive strategies. Moreover, these strategies may not just be the traditionally studied intra-floral traits, but also, traits varying in time and space in accordance to the cognitive abilities of the pollinators. In fact, the first chapter has preliminarly suggested that the reproductive strategies of Melastomataceae species as pollinator dependence or independence to set fruit, as well as, the dispersal system, may influence the flowering and fruiting and be more determinant than vegetation type in reproductive phenology. However, for a broader understanding of the phenology determinants of Melastomataceae species, we proposed to deep our study in the future with an overlap and phylogenetic analysis. The second chapter discussed the role of the nectar production in the generalisation of the pollination system of Miconia theizans. The nectar production and its association to an increasing number of visitor species, including non-vibratory insects, were already described for some Miconia species. However, we showed that the visitation rate of nectarivorous insects explains the amount of pollen grains reaching the stigmas, possible contributing to female reproductive success. This kind of strategy should have been favored in a scenario of low pollinator availability, which is probably the case of buzzing bees in elevated areas. In this sense, nectar production should be another reproductive strategy to deal with the “pollen dilemma”, a widespread fate of Melastomataceae species since their evolutionary history is very tied with bees. Future studies should track the geographical and phylogenetic occurrence of nectar producing species of Melastomataceae and clarify if the generalisation of pollination system from specialized ones could also occur in areas other than islands. The third chapter showed that different pollination dynamics may have create genetic structure and differences in genetic diversity among populations of plants that rely only on pollinator for their reproduction. This scenario is commonly found in melittophilous plants occurring in elevational gradients, where the richness and abundance of bees decrease with the elevation. In elevated areas, the reduced amount of cross- pollination events could lead to this genetic pattern in such plants. Moreover, our results 166 indicate that spatial structure should also occur in a fine scale and this should be tested with the same data in a future study using group spatial analysis. The major challenge of this study was to deal with the polyploidy condition of T. pulchra. In such case, there is much uncertainty in the estimation of allele frequency, which makes impossible the use of traditional techniques in population genetics, since almost all of them were developed just for diploid organisms. Therefore, this study may also encourage future population genetic studies using another polyploid plant models. The last chapter described the phenomena of floral colour change in Tibouchina pulchra considering the bee visual system. This, in addition to the experimental confirmation of the long and short distances hypotheses proposed to explain such phenomenon, enabled us to demonstrate that floral colour change may be related to specific colour properties and the innate visual abilities of bees. Specifically, we proposed that the process of floral colour change and retention of old flowers in T. pulchra creates a colour pattern where the tree is covered by old flowers in less spectral pure pink (bee blue) while the new flowers are shown in high pure white (bee blue-green). This unidirectional colour pattern gradient, with colours varying from a lesser to a greater purity from the periphery to the center (where the reward is available to visitors), is preferred by naïve bees and it is a common intra-flower trait in Angiosperms. However, we have shown that it can occur in a broader scale: the whole tree. Future studies should clarify if the preference by bees to the long distances artificial set, as showed by our study, was due to just the colour pattern, the display size utilized or a synergetic effect of both. Moreover, future studies also might show whether the special floral color change of T. pulchra was favoured by the scattered distribution of the plants in rare disturbed areas of the rainforest. As an annex to this chapter, we reviewed the major concepts of cognitive ecology of pollination, calling the attention of pollination Brazilian researchers to the fact that plants and pollinators interact by a sensorial channel that is experientially inaccessible for human raw cognition and, most important, that the interaction in such dimensions is the backstage for co-evolutionary processes for both interactors. Therefore, we recommended that future studies in pollination biology consider such natural bias, since each flower visitor has a complex and single representation of the world around it. The Melastomataceae family is widespread in the tropics where the largest amount of possible interacting animal species also occurs. Their typical poricidal anthers are highly 167 associated with buzzing bees, which in turn consume their pollen grains. This would create an evolutionary force that favours reproductive strategies to deal with this “pollen dilemma”. This study has described and discussed some of these strategies and their consequences but the variability of such possible systems is far from be exhausted in literature and their histories could fascinate an entire academic life.