Coloração De Flores Na Visão De Polinizadores

Universidade Federal do Rio Grande do Norte Centro de Biociências Programa de Pós-graduação em Psicobiologia

Coloração de flores na visão de polinizadores

Marilia Fernandes Erickson

2019

Marilia Fernandes Erickson

Coloração de flores na visão de polinizadores

Essa dissertação foi desenvolvida no Laboratório de Ecologia Sensorial do Departamento de Fisiologia e Comportamento da Universidade Federal do Rio Grande do Norte, sob orientação do Prof. Dr. Daniel Marques de Almeida Pessoa e co-orientação do Professor Carlos Roberto Sorensen Dutra da Fonseca

Natal 2019

Universidade Federal do Rio Grande do Norte - UFRN Sistema de Bibliotecas - SISBI Catalogação de Publicação na Fonte. UFRN - Biblioteca Setorial Prof. Leopoldo Nelson - •Centro de Biociências - CB

Erickson, Marília Fernandes. Coloração de flores na visão de polinizadores / Marília Fernandes Erickson. - Natal, 2019. 92 f.: il.

Dissertação (Mestrado) - Universidade Federal do Rio Grande do Norte. Centro de Biociências. Programa de Pós-graduação em Psicobiologia. Orientador: Prof. Dr. Daniel Marques de Almeida Pessoa.

1. Angiospermas - Dissertação. 2. Visão de cores - Dissertação. 3. Modelagem visual - Dissertação. 4. Visitantes florais - Dissertação. 5. Polinização - Dissertação. I. Pessoa, Daniel Marques de Almeida. II. Universidade Federal do Rio Grande do Norte. III. Título.

RN/UF/BSE-CB CDU 582.5/.9

Elaborado por KATIA REJANE DA SILVA - CRB-15/351

Título

Coloração de flores na visão de polinizadores

Banca examinadora

Prof. Dr. Felipe Gawryszewski Universidade de Brasília

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Prof. Dr. Leonardo M. Versieux Universidade Federal do Rio Grande do Norte

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Prof. Dr. Daniel Marques de Almeida Pessoa (orientador) Universidade Federal do Rio Grande do Norte

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Natal, 27 de maio de 2019.

“Que terra mais pachorrenta!” comentou a Rainha. “Pois aqui, como vê, você tem de correr o mais que pode para continuar no mesmo lugar. Se quiser ir a alguma outra parte, tem de correr no mínimo duas vezes mais rápido!” Alice no País das Maravilhas, Lewis Carroll.

Dedico esta dissertação a Ricardo Andreazze, sua luz continua a me guiar pelos momentos mais escuros.

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AGRADECIMENTOS Agradeço às minhas irmãs Biny e Becky que, embora não fizeram nenhum bolo de cenoura para mim, estavam sempre com o Ifoods na mão. Aos meus pais, Sandra e Glenn, para os quais poderia escrever uma dissertação inteira dizendo tudo que fizeram por mim, mas, por hora, vou apenas dizer que, junto com o CNPQ, financiaram minha pesquisa. Ao Diogo, que foi “troxa” o suficiente para me emprestar suas pernas, cabeça, e tempo para me ajudar com esse projeto, seja emocionalmente, conceitualmente ou fisicamente. Tenho absoluta certeza que não teria conseguido sem sua ajuda em todos esses aspectos. Ao Daniel pela orientação, confiança e incentivo desde a graduação. Aos meus colegas de laboratório, cujo apoio foi indispensável. A Mariana por todas as semanas juntas em Assu, cheias de intrigas, pokemons e brigadeiro. A Sofia, Holda e Raiane, as flores mais preciosas que encontrei nesse mestrado. A Joaquim, Vinicius, Bia, Thiago, Geovan, Felipe, Elder, André, Larissa, Amanda e Kleytone. Obrigada por cada um carregar um pedacinho do trabalho do outro deixando tudo mais leve. À UFRN, Centro de Biociências, Departamento de Fisiologia e Comportamento, e todos os seus funcionários. Ao ICMbio pela manutenção das reservas e permissão de coleta, e alojamento durante a pesquisa. Ao Mauro, “Irmão”, Chiquinho, Luiz, e todo pessoal da FLONA de ASSU e da REBIO Guaribas. Ao Anderson, Alan e todo o herbário do Parque das Dunas e UFRN, por me cederem material, tempo e apoio. Ao Felipe, Letícia, Andréia e Ana Cecília, amigos maravilhosos que o mestrado me presenteou. Especialmente a “Terceiro” por me ceder a cadeira no ônibus e ótimos papos de calçada. À Rayane, Eva e Rizia por me fazerem companhia nas horas inacabáveis de laboratório. À minha melhor amiga Camila, e todos os meus amigos que tentaram me distrair da vida acadêmica (ou não), das mais diversas formas, Laila, Juh, Thaís, Ana Luíza, Pocati, Pablo, Daniel, Allan, Gabi, Sarah, Rodolfo e Valéria. À Larissa por ser a melhor motorista anti- bolsonaro e à Aninha por todas as dicas maravilhosas. Ao Fábio, Gabriel, David, Rafael e Guilherme amigos que nem o mestrado conseguiram separar. Ao CNPq pela concessão da bolsa. O presente trabalho foi realizado com apoio da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Código de Financiamento 001

Resumo A coloração das flores é tão intrigante quanto os fatores ecológicos e ambientas por trás delas. Desde os primórdios dos estudos de biologia floral, o porquê da coloração das flores vem sendo questionado. Muitos autores têm atribuído a coloração floral à seleção sexual e pressão exercida por polinizadores. Isso pode ser bem exemplificado pela ideia de síndromes de polinização; espécies de flores com certas características semelhantes, como a cor, são visitadas por grupos similares de polinizadores. Porém, colorações diversas raramente são explicadas por um único fator. Nesse estudo, procuramos entender quais são os fatores ambientais, ecológicos e fisiológicos responsáveis pela coloração das flores, com ênfase em testar se espécies previstas por síndromes de polinização realmente são conspícuas para seus polinizadores. Utilizamos como modelo Apis mellifera (abelha), Drosophila melanogaster (mosca), Heliconius erato (borboleta) e Sephanoides sephanoides (beija-flor) para entender como polinizadores diferentes enxergam flores. As flores foram mais conspícuas para polinizadores tetracromatas (mosca, borboleta fêmea, e beija-flor) e menos conspícuas para polinizadores tricromatas (borboleta macho, abelha). Dessa maneira, flores não foram mais conspícuas para seus polinizadores, e cores atribuídas as síndromes de polinização não possuem bases empíricas. Provavelmente diferentes fatores interagem para moldar a coloração das flores ao longo do tempo e síndromes de polinização são apenas um recorte de uma figura mais complexa. Palavras chave: Angiospermas, visão de cores, modelagem visual, visitantes florais, polinização.

Abstract Flower coloration is as intriguing as the ecological and environmental factors behind it. Since the beginning of studies in floral biology, the question of the reasons behind floral coloration has been asked. Many authors have attributed flower colors to sexual selection and pollinator pressure. This is well exemplified by the idea of pollination syndromes: flowers with certain similar characteristics, such as color, are visited by similar groups of pollinators. Such a diverse array of coloration, however, is hardly ever explained by one factor alone. In this study, we aimed at understanding which environmental, ecological and physiological pressures are behind flower coloration, emphasizing, in testing, if flowers predicted by pollination syndromes are in fact conspicuous to their pollinators. We used Apis mellifera (honeybee), Drosophila melanogaster (housefly), Heliconius erato (butterfly) and Sephanoides sephanoides (hummingbird) as models to study how different pollinators see flowers. Flowers were more conspicuous to tetrachromat (housefly, female butterfly and hummingbird) than to trichromat (honeybee and male butterfly) pollinators. Therefore, flowers were not more conspicuous for their respective pollinators, and colors attributed by pollination syndromes do are not supported by empirical data. Probably different factors have shaped the coloration of flowers across time, and pollination syndromes are a piece of the whole picture. Keywords: Angiosperms, color vision, flower color, floral visitors, pollination.

Lista de Figuras

Estudo 1- Painting the roses red: Temporal-spatial patterns and the evolution of flower coloration

Figura 1. Number of articles in web of science regarding flower coloration in the last decades……………………...... p. 20

Figura 2. Diagram exemplifying how flower color is affected by different factors discussed in this review...... p. 40

Estudo 2- Pollination syndromes do not predict conspicuousness by different floral visitors

Figura 1. Boxplot showing distribution of chromatic contrast values between flowers and background elements, comparison is within pollinators, and flowers are grouped by syndrome...... p. 64

Figura 2. Boxplot showing distribution of chromatic contrast values between flowers and background elements, comparison is within pollinators, and flowers are grouped by color...... p. 66

Figura 3. Boxplot showing distribution of chromatic contrast values between flowers and background elements, comparison is between pollinators, and flowers are grouped by syndrome...... p.67

Figura 4. Boxplot showing distribution of chromatic contrast values between flowers and background elements, comparison is between pollinators, and flowers are grouped by color...... p. 68

Supplementary material 3. Compared reflectance of flowers measured with Ocean Optics RPH- 1 probe holder and our custom-made 3D printed probe holder...... p. 85

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Supplementary material 4. Illuminant of Caatinga and Restinga used in visual modeling...... p. 85

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Lista de Tabelas

Estudo 2- Pollination syndromes do not predict conspicuousness by different floral visitors

Tabela 1. New color categories with description and number of flowers in each group...... p. 59

Tabela 2. Parameters used in our visual modeling...... p. 61

Tabela 3. Number of flowers, of different colors, that are cryptic, barely detectable, and detectable……………………………...... p. 63

Supplementary material 1. List of species used, locations found, and which backgrounds were used for the visual modeling...…………………………………………………………………p. 79

Supplementary material 2. Description of flower color categories, proposed by Wilmer (2011), and the number of flowers sampled in our study………...... p. 84

Sumário 1. Introdução 1.1 Introdução geral...... p. 11 1.2 Referencias ...... p. 13 2. Objetivos, hipóteses & predições...... p. 14 2.1 Objetivos...... p. 15 2.1.1 Objetivo geral...... p. 15 2.1.2 Objetivos específicos...... p. 15 2.2 Hipóteses e predições...... p. 16 3. Artigo 1: Painting the roses red: Temporal-Spatial patterns and the evolution of flower coloration ...... p. 17 3.1 Abstract...... p. 18 3.2 Introduction...... p. 19 3.3 Pigment and flower coloration...... p. 21 3.4 The visual system of pollinators...... p. 23 3.5 Floral syndromes...... p. 26 3.6 Phylogenetic constraint...... p. 29 3.7 Floral age...... p. 31 3.8 Seasonal changes in flower color...... p. 33 3.9 Biogeographical changes...... p. 34 3.10 Sensory drive...... p. 37 3.11 Conclusion...... p. 39 3.12 References...... p. 42 4. Artigo 2: Pollination syndromes do not predict conspicuousness by different floral visitors...... p. 51 4.1 Abstract...... p. 52 4.2 Introduction...... p. 53 4.3 Materials and methods...... p. 56 4.3.1 Data colection...... p. 56 4.3.2 Flower characterization...... p. 57 4.3.3 Visual modeling...... p. 59 4.3.4 Analysis...... p. 60 4.4 Results...... p. 61 4.5 Discussion...... p. 68 4.6 Conclusion...... p. 72 4.7 References...... p. 73 4.8 Supplementary Material...... p. 78 5. Conclusão geral...... p. 85 6. Apêndices...... p. 89 6.1 Aprovação do comitê de ética...... p. 88

1.INTRODUÇÃO

1.1 Introdução geral

Angiospermas são os organismos autótrofos de maior diversidade que há na Terra. Seu sucesso reprodutivo é constantemente relacionado com a presença de flores (Armbruster 2014), seus órgãos reprodutivos. Para angiospermas se reproduzirem, seus gametas precisam ser transportados por vetores (polinizadores), que podem ser abióticos, como a água e o vento, ou bióticos, empregando animais. Entre os animais polinizadores, pode-se destacar abelhas, borboletas, moscas, morcegos e aves. As plantas disponibilizam recursos (que podem ser pólen, néctar, óleo e fragrâncias) para seus polinizadores que estão forrageando e durante o processo de forrageio transportam os gametas realizando a polinização (Westerkamp 1996). Para assegurar sua reprodução, as plantas precisam se comunicar com diferentes animais utilizando, principalmente, sinais visuais e químicos.

Plantas obtém sua coloração através de pigmentos, que além de servir para atração de polinizadores, funcionam como defesa química contra herbívoros, proteção contra radiação solar, entre outras funções. Além disso, plantas estão competindo por polinizadores, o que pode levar a divergência ou convergência de cores, dependendo do ambiente. Mesmo levando em consideração somente pressão exercidas por polinizadores, muitos animais apresentam preferências inatas por cores, e aprendem rapidamente a associar cores com recompensas, o que os influencia diretamente durante o forrageio.

Os sinais florais mais importantes são os visuais (Waser, Chittka, Prince, Williams &

Ollerton 1996). A coloração é percebida a mais longa distância, em comparação a outros sinais como cheiro e padrões (Chittka & Menzel 1992). Adicionalmente, a cor é um dos principais promotores de constância floral (Waser 1986, Chittka & Menzel 1992), isso é, a tendência de polinizadores restringirem suas visitas a um número limitado de morfotipos de flores (Chittka,

Thomson & Waser 1999). A coloração de flores é diversa e intrigante no espectro visível da nossa espécie. Contudo, adicionalmente, a maioria dos polinizadores ainda conseguem enxergar luz ultravioleta (UV), revelando padrões nas flores que são imperceptíveis a humanos.

A presente dissertação está dividida em dois artigos. O primeiro artigo é uma revisão bibliográfica que visa entender quais diferentes fatores podem afetar a coloração das flores.

Começa abordando como diferentes pigmentos e fatores intracelulares causam a coloração das flores, exemplifica como é o sistema visual de diferentes grupos de polinizadores, e como a pressão por polinização pode ter moldado a coloração das flores. Então, examina como a coloração das flores esta sujeita a restrições filogenéticas e como diferentes fatores (e.g. idade, estação do ano e posição geográfica) podem atuar no direcionamento da evolução da coloração das flores. Por

último, discute como a teoria do direcionamento sensorial pode ajudar a explicar padrões biogeográficos de coloração de flores. O segundo artigo é um empírico e busca testar se as cores atribuídas às síndromes de polinização estão relacionadas às capacidades visuais encontradas em diferentes grupos de polinizadores.

1.2 Referências

Armbruster, W. S. (2014). Floral Specialization and Angiosperm Diversity: Phenotypic Divergence, Fitness Trade-Offs and Realized Pollination Accuracy. Annals of Botany, 6. https://doi.org/doi:10.1093/aobpla/plu003

Chittka, L., & Menzel, R. (1992). The Evolutionary Adaptation of Flower Colours and the Insect Pollinators’ Colour Vision. Journal of Comparative Physiology, 171(2), 171–181. https://doi.org/doi:10.1007/bf00188925

Chittka, L., Shmida, A., Troje, N., & Menzel, R. (1999). Flower Constancy, Insect Psychology, and Plant Evolution. Naturwissenschaften, 86(8), 361–377. https://doi.org/10.1007/s001140050636

Waser, N. M. (1986). Flower Constancy: Definition, Cause, and Measurement. The American Naturalist, 127(5), 593–603. https://doi.org/DOI: 10.1086/284507

Waser, N. M., Chittka, L., Prince, M. V., Williams, N. M., & Ollerton, J. (1996). Generalization in Pollination Systems, and Why it Matters. Ecology, 77(4), 1043–1060. https://doi.org/DOI: 10.2307/2265575

Westerkamp, C. (996). Pollen in Bee‐Flower Relations Some Considerations on Melittophily*. Botanica Acta, 109, 325–332. https://doi.org/10.1111/j.1438-8677.1996.tb00580.x

2. OBJETIVOS, HIPÓTESES E PREDIÇÕES

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2.1. Objetivos

2.1.1.Objetivo geral

Investigar o papel da visão de polinizadores na evolução da coloração floral.

2.1.2.Objetivos específicos

I- Revisar a literatura sobre fatores que influenciam na evolução da coloração das flores. II- Examinar o papel da visão de cores de diferentes visitantes florais no estabelecimento de síndromes de polinização.

2.2. Hipóteses e predições

I. Hipótese 1: Flores apresentam maior contraste de cor entre a pétala e seu background para

seu respectivo polinizador

a. Predição 1: Flores melitofilas (polinizadas por abelhas) terão maior contraste de cor, com

relação à folhagem, quando visualizadas por abelhas; flores psicofilas (polinizadas por

borboletas) terão contraste maior para borboletas, flores miofilas (polinizadas por moscas)

terão contraste maior para moscas e flores ornitófilas (polinizadas por aves) terão contraste

maior para aves.

b. Predição 2: Flores azuis, que seriam preferencialmente utilizadas por abelhas, terão maior

contraste de cor, quando comparadas à vegetação, quando visualizadas por abelhas, em

comparação à visão de outro polinizadores; flores vermelhas terão contraste maior para

aves e borboletas; flores brancas terão contraste maior para moscas e abelhas; flores verdes

terão contraste maior para moscas; flores amarelas terão contraste maior para abelhas,

moscas e borboletas (Wilmer 2011).

II. Hipótese 2: Polinizadores terão uma melhor detecção de cores daquelas flores que se

encaixam em suas síndromes de polinização.

a. Predição 3: Abelhas irão enxergar melhor flores melitofilas, quando comparadas a flores

das demais síndromes florais; aves irão enxergar melhor ornitófilas, moscas irão enxergar

melhor flores psicofilas, e borboletas irão enxergar melhor flores psicofilas.

b. Predição 4: Abelhas irão enxergar melhor flores azuis, amarelas e brancas; aves irão

enxergar melhor flores vermelhas; moscas irão enxergar melhor flores brancas, verdes e

amarelas; borboletas irão enxergar melhor flores amarelas e vermelhas.

3. ARTIGO 1

Painting the Roses Red: Temporal-spatial Patterns and the Evolution of

Flower Coloration

Painting the Roses Red: Temporal-spatial Patterns and the Evolution of Flower Coloration

Marilia Erickson1 and Daniel M. A. Pessoa

Laboratory of Sensory Ecology, Department of Physiology and Behavior, Universidade Federal do Rio Grande do Norte. Natal – RN, Brazil. CEP 59078-970

1- MSc student; E-mail: [email protected]

3.1 Abstract

The diversity of flower color has always been puzzling. Though flower coloration has been extensively studied, many unanswered questions remain. Studies on the coloration of flowers focus extensively on pollination. Flower coloration, however, has multiple functions, such as protecting against herbivory and other harmful visitors, and preventing ultraviolet damage. Here we review different factors affecting coloration in flowers by using a visual communication perspective, since recent studies have shown many similarities between strategies of animal and plant coloration, such as aposematism, camouflage, mimicry and private communication channels. We begin by looking at how plants produce pigment and how various receivers process coloration. Then we explore the ultimate (e.g. pollinator pressures and phylogenetic restraints) and proximate (e.g. effects of ontogeny on coloration, a bewildering phenomenon known as flower color change) causes of flower coloration, as well as the temporal and spatial patterns in flower communities. Finally, we look at how sensory drive could have framed the evolution of flower color. In short, we aim to contribute to ongoing research by underlining the main current topics in flower coloration studies, indicating perspectives for future studies of floral color. Keywords: Pigments, color vision, pollination ecology, flower ontogeny

3.2 Introduction

There are an estimated 308,000 plant species in the world that depend on animals for pollination (Ollerton, Winfree & Tarrant 2011) and hence need to overcome communication barriers between different species in order to reproduce. Plants are also subject to herbivory, nectar robbing and other antagonistic behavior from animals who can often explore the same sensory modalities of pollinators. These pressures can lead flowers to diverge or converge in color with flowers in their community. In general, having a distinct coloration from neighbors helps with flower constancy and is a favorable strategy (Waser 1986, Chittka, Thomson & Waser 1999,

Schaefer, Schaefer & Levey 2004). Yet this is not always the case, insofar as some mimetic plants depend on similar colors for pollination (Peter & Johnson 2008). Pollinator preference may also play a role in determining coloration (Dyer et al. 2012). Additionally, protection against herbivory

(Irwin, Strauss, Storz, Emerson & Guibert 2003, Johnson, Berhow & Dowd 2008), UV light

(Kootstra 1994; Mori et al. 2005), seasonal change (Stace & Fripp 1977, Hensel & Sargent 2012) and habitat (Gumbert, Kunze & Chittka 1999; Arnold, Savolainen & Chittka 2009; Shrestha, Dyer,

Bhattarai & Burd 2014) can all play a selective role in coloration.

Nonetheless, plants have been widely overlooked by researchers as communicating organisms.

Although the science of floral coloration is a growing topic, there is a strong bias towards the publication of pollination studies (13,400 records in web of science – from 1970 to 2019), leaving other research topics largely underexplored, such as: flower color change (80 records in Web of

Science Database – from 1970 to 2019), camouflage (30 – from 1970 to 2019), aposematism (17

– from 1970 to 2019), private communication channels (9 – from 1970 to 2019) and sensory drive

(7 – from 1970 to 2019) (Fig 1). The good news are that plant signaling have growingly received more attention in the past years, dealing with concepts that have only been thoroughly researched

20 in animals, such as mimetism (Lunau & Wester 2017), aposematism (Lev-Yadun & Gould 2007,

Lev-Yadun, Ne'eman & Keasar 2017), camouflage (Shuttleworth & Johnson 2009; Niu, Sun &

Stevens 2018), signal honesty (Makino & Ohashi 2017), private communication channels

(Shuttleworth & Johnson 2009; Lunau, Papiorek, Eltz & Sazima 2011) and sensory drive

(Schaefer, Schaefer & Levey 2004).

8000

7000

6000

5000

4000

3000

2000

1000

0 1970-1979 1980-1989 1990-1999 2000-2009 2010-2019 Number of records in Web of Science Database Science of Web in of records Number time period

flower OR floral colo* AND pollination flower OR floral colo* AND pigment flower OR floral colo* AND herbivory flower OR floral colo* AND mimetism or deception or mimicry flower OR floral colo* AND phylogenetic constraint flo* colo* change flower OR floral colo* AND camuflage or criptic or crypsis flower OR floral colo* AND aposematism OR "warning colo*" flower OR floral colo* AND "private niche" or "private channel" flower OR floral colo* AND sensory drive

Figure 1. Number of articles in web of science regarding flower coloration on the last decades.

The terms were inputted on the web of science main collection on June of 2019. Keywords used are presented in the figure labeled by different colors.

In this paper, we aim to review different factors that affect coloration in flowers (Fig 2). We start by looking at how plants produce color and how different receivers process visual information. Then we explore the ultimate and proximate causes of flower coloration, which include pollinators pressure, flower age, season and habitat as well as phylogeny. Finally, we discuss how sensory drive could explain convergent evolution in flower communities. We end this paper with some prospects of future studies regarding flower coloration.

3.3 Pigment and flower coloration

Pigments are molecules that absorb some wavelengths of light and reflect others. The reflected wavelengths give color to objects; and so, pigment determines the reflectance of flowers (Chittka,

Shmida, Troje & Menzel 1994). There are three major group of plant pigments: flavonoids, carotenoids and betalains. Their core structures differ in light absorption properties and can also be attached to other chemical groups to form more variable flower colorations (Wilmer 2011).

Different concentration of pigment can affect most of the parameters used for studying color vision, including dominant wavelength, spectral purity, green contrast and color contrast

(Papiorek, Rohde & Lunau 2013).

The diversity of flower color is often attributed to pollination pressure and sexual selection

(Schiestl & Johnson 2013). Selection for pigment coloration, however, goes beyond pollinator choice. Some pigments are also associated with chemical defenses against herbivory, this being one of the hypotheses as to why there are different color morphs in the same species. In the wild radish, Raphanus sativus L., pollinators prefer white and yellow morphs, which have a lower

22 concentration of anthocyanins, in comparison to bronze and pink color morphs that have a high concentration of pigment (Stanton 1987). The color morphs with lower anthocyanin concentration, however, are less resistant to herbivory, which can provide a selective pressure to maintain high pigment morphs (Irwin, Strauss, Storz, Emerson & Guibert 2003). In star-patterned petunia,

Petunia hybrida Vilm., flowers are multicolored, having a white star pattern at the middle of the corolla that can have multiple colors surrounding it. The colored part has a higher concentration of anthocyanins and was found to slow the development of lepidopteran larvae (Johnson, Berhow

& Dowd 2008). Thus, it is possible that herbivores avoid plants colored by anthocyanins because they indicate presence of defensive compounds (Schaefer & Rolshausen 2006), a tendency that, perhaps, should also be regarded as aposematism (Lev-Yadun & Gould 2007).

Pigments can also block UV radiation and prevent DNA damage (Kootstra 1994; Mori et al.

2005). Accumulation of protective anthocyanins caused by UV radiation produce red to purple colors in exposed tissue (Burger & Edwards 1996), as seems to be the case in Delachampia and

Acer, in which flower color seems to be associated with the presence of anthocyanin in vegetative tissue (Armbruster 2002). Plant pigments have also been associated with other functions such as drought resistance, temperature resistance, heavy metal resistance, and antioxidative capabilities

(Chalker-Scott 1999, Gould 2004, Pourcel, Routaboul, Cheynier, Lepiniec & Debeaujon 2007).

Presence of pigment alone, however, does not determine flower color. Cellular pH and cellular architecture may have a major role in determining flower coloration (Grotewold 2006). Varieties of Antirrhinum majus L. are perceived differently by their pollinators when having equal pigment concentration but differing cell shape (Glover & Martin 1998). Flowers can also reflect iridescent light due to structural mechanisms (Whitney et al 2009, Glover & Whitney 2010). Likewise, purple and blue flower variants of Ipomoea nil (L.) Roth do not differ in pigment concentration, but in

23 sap pH (Fukada-Tanaka, Inagaki, Yamaguchi, Saito & Iida 2000). Hence, biochemistry of flower coloration can be either determined by pigments, pH and cellular structure and influenced by external factors.

3.4 The visual system of pollinators

Among the many functions of pigments, signaling is the most important (Schiestl & Johnson

2013). Through color, flowers attract or repel visitors (Fig 2). Plants have little plasticity in signaling capacities, signals being seen by mutualist and antagonist (animals that visit plants or flowers and have harmful interactions with them) alike (Schaefer, Schaefer & Levey 2004). How these signals are interpreted, however, depends on the receiver’s sensory capacity. Communication through color requires animals to have a visual system that detects and interprets flower color. The main flower visitors are insects, mostly because of their function as pollinators, but also because they are quite vicious herbivores, florivores, nectar-robbers, pollen thieves, sapsuckers, and parasites. Hence, animals with very similar visual systems can be either beneficial or harmful to the same plant. We will, however, focus this review on pollinator’s visual ecology, inasmuch as pollinator choice is seen as the primary function of flower color (Schiestl & Johnson 2013), and since very few studies have considered eavesdroppers as a selective pressure for color (Cuthill et al 2017).

Insects have varied visual systems. Yet most insects seem to be trichromats with preserved photoreceptors that detect light in the UV, blue and green part of the electromagnetic spectrum

(Briscoe & Chittka 2001). Hymenoptera (e.g. ants, bees and wasps) have had their visual pigments extensively studied (Peitish et al. 1992) and follow, with few exceptions, the UV-blue-green receptor pattern found in most other insects. Bees are very visually oriented and can use achromatic and chromatic color vision for the detection of flowers (Giufa, Vorobyev, Kevan & Menzel 1996).

They are quick to associate flower color and reward and can maintain flower constancy, that is, the habit of a flower visitor to effectively restrict their visits to a few flower species or morphs

(Chittka, Thomson & Waser 1999). Flower constancy is very important for plants, insofar as it ensures the pollen will go to another individual of the same species without misplacement of pollen

(Muchhala & Thomson 2012) or development of infertile hybrids (Heinrich 1975). Leaves, stones and other general background components are achromatic to bees (Chittka, Shmida, Troje &

Menzel 1994), making bees ideal for detecting flowers (Chittka 1997).

Hoverflies usually have four photoreceptor varieties (Lunau 2014). Yet their color vision has been interpreted as relatively poor, since they would be able to distinguish only four color categories (Troje 1993), with scents being more important than colors (Roy & Rasugo 1997).

However, recently, objections to this model have appeared (White, Dalrymple, Herberstein &

Kemp 2017), as Drosophila melanogaster (housefly) has been able to distinguish flowers within the same category (Brembs & de Ibarra 2006). The visual ecology of flies is still poorly understood

(Lunau 2014).

The most common change in receptors within insects was the addition of a red receptor, which has happened independently many times within Lepidoptera (Briscoe & Chittka 2001). Butterflies may have from as few as three to as many as fifteen kinds of photoreceptors, though most butterflies have six different spectral sensitivities (Arikawa 2017). It is often assumed that the number of classes of photoreceptors determines the dimension of color vision, but this is not always the case (Cuthill et al 2017). Butterflies, despite usually having six different kinds of photoreceptors, have tetrachromatic vision using the UV, blue, green and red receptors (Arikawa

2017). They are capable of seeing the entire color spectrum, leading to great color discrimination, usually associated with sexual selection and foraging (Kelber 2016). Moths, like bees, have UV,

25 blue and green receptors that may be used for color vision even at night (Kelber, Balkenius &

Wattant 2003).

Some vertebrates can also play a key role in pollination and visitation of flowers. For instance, bats are common vertebrate pollinators for nocturnal flowers. Although bats are known for echolocation, they also have dichromatic color vision, in the UV and green range (Müller et al.

2009). Hummingbirds are mainly diurnal visitors and have four receptor types: UV, blue, green and red (Herrera et al 2008), so are able to detect the entire color spectrum, like butterflies. It is a misconception that birds prefer red flowers, as studies have shown birds not to have innate color preferences (Lunau, Papiorek, Eltz & Sazima 2011). Birds rely little on smell, and largely use visual cues for detection of flowers, which makes them excellent models to study the evolution of floral color due to pollinator preference.

Although flowers are visited by animals with different visual systems, Chittka & Menzel

(1992) and Dyer et al. (2012) argue that hymenoptera are the main drivers for the evolution of flower coloration. Luckily, bees have one of the most studied color vision systems, second only to primates (Wilmer 2011). Different methods can be used to study color vision such as visual modeling (Stevens, Stoddard & Higham 2009, Renoult, Kelber & Schaefer 2017, Gawryszewski

2018, Olsson, Lind, & Kelber, 2018), comparing the raw reflectance of flowers (Chittka, Shmida,

Troje & Menzel 1994; Arnold, Comber & Chittka 2009) and using behavioral experiments Dyer

(2012). Studies that investigate the role of more than one visual system are still relatively scarce

(Schaefer, Schaefer & Levey 2004) and should be encouraged, especially considering those investigating antagonistic interactions.

3.5 Floral syndromes

Different groups of floral visitors may have differential pollinator efficiency, which can be measured by seed production. In Calathea sp., Hesperiidae butterflies account for 21% of visits but for less than 1% of seed set. Bombus medius (bumblebee) and Rhathymus sp (bee), however, only had 5% of visits but were responsible for 22% of seed set. The reproductive success of a plant, therefore, is dependent on the kind of visitor it attracts (Schemske & Horvitz 1984). For a long time, flowers were grouped by their morphological characteristics in a pollination syndrome according to which pollinator it was supposedly meant to attract. The classical pollination syndromes are anemophily (wind), hydrophily (water), cantharophily (beetles), myophily (flies), sapromyophily (carrion and dung flies), psychophily (butterflies), phalaenophily (moths), melittophily (bees), ornitophily (birds) and chiropterophily (bats). Flower syndromes are based on the idea that some characteristics are overrepresented in flowers pollinated by certain agent. So, as a result of pollinator pressure, flowers will lead to convergent evolution of flower traits. Thus, for instance, a flower that has anthesis during the day, red or orange coloration, no scent or nectar guides, conceals nectar in high volume and low sugar concentration, and has low amounts of pollen and radial or bilateral symmetry, with short to medium corolla tube length, will likely be pollinated by birds (Wilmer 2011).

Trait convergence is often used as a predictive characteristic for a plant’s pollinator. Floral characteristics of color, flower type, corolla width, and presence of nectar, correctly identified 86% of bird pollinated species, 78% of fly pollinated species and 69% of bee pollinated species in

Australian heath Styphelioideae (Johnson 2013). In snapdragons, Antirrhineae, flower morphology, which included flower color and 7 other characteristics, had an overall positive

27 predictive value (PPV) of 65.95% for pollinators and flower visitors (Guzmán, Gómez & Vargas

2017).

Even though studies have shown some potential for the use of floral syndromes in the study of the evolution of flower traits, recently the idea of pollinator syndromes has fallen under lots of criticism. First, there are far more distinct flower morphologies than types of pollinators (Heinrich

1975). Second, most animal floral visitors visit more than one plant species, and most plant species receive visits from more than one animal group, both animals and plants alike being opportunistic about pollination (Waser, Chittka, Prince, Williams & Ollerton 1996). Third, pollinators are foraging for food while plants use them as a vector for gamete transportation and hence, reproduction, what some authors better describe as a mutual exploitation system rather than a mutualistic relationship (Westerkamp 1996). Fourth, the tendency in nature seems to be generalization of plant-pollinator systems (Waser, Chittka, Prince, Williams & Ollerton 1996).

And fifth, floral constancy favors diversity of signal (Waser 1986, Schaefer, Schaefer & Levey

2004), which does not support to the convergent notion of pollination syndromes (Fig 2).

Indeed, floral color does not always seem to be associated with pollinator syndrome. Kuniyasu et al (1998) associated flowers of a lowland dipterocarp forest in Sarawak (Malaysia) with pollination syndromes and found that pollination syndromes do relate with certain flower characteristics, such as reward, shape and flowering time, but not with color. Opomopsis aggregate

(Pursh) V. E. Grant is morphologically a bird-pollinated flower (red with tubular corolla tube), and indeed most its visits are from hummingbirds. Bumblebees, however, outperform hummingbirds in cross pollen deposition by three times, and induce four times more seed production in O. aggregata (Mayfield, Waser & Prince 2001). In the genus Ichoroma, though species with high nectar reward and large floral display were more likely to be pollinized by

28 hummingbirds, corolla length and flower color were not found to be associated with pollinator groups (Smith, Ané, Baum 2008).

A different view from the traditional pollination syndromes is that visitors cluster in functional groups of pollinators (e.g. long-tongued flies). Functional groups will exercise similar evolutionary pressures causing correlation among floral traits (Fenster, Armbruster, Wilson, Dudash &

Thomson 2004). Using the idea of functional groups, Fenster et al. (2004) reanalyzed the same data as used by Waser, Chittka, Prince, Williams, & Ollerton (1996) and found that 75% of species exhibited specialization in terms of functional groups. Functional groups are not, however, a clear- cut solution to the criticism of pollinator syndromes. Ollerton et al. (2009) surveyed flowers from three different continents and tried to test if floral syndromes, using functional groups, could predict the most common pollinator of different flowers. They found that even though floral syndrome characteristics formed a cluster in a phenotypical space, they were mostly unoccupied.

The minority of species fell into clusters formed by the pollination syndrome’s characteristics, as most species were located between clusters. These results further the understanding that real species do not comply to the long-established notion of pollination syndromes.

Another explanation for convergence of certain flower traits is that plants can evolve characteristics to exclude certain visitors (Heinrich 1975). That is well within the idea of private communication channels, that is, a communication system that involves a signal to which an eavesdropper is insensitive (Stevens 2013). That might explain the ornithophily syndrome, which states bird flowers are usually red. Bees are generally insensitive to longer wavelengths (Peitsch et al. 1992), which serves to generate a private communication channel for hummingbirds (Lunau,

Papiorek, Eltz & Sazima 2011), excluding bee visitors that can be nectar robbers in hummingbird pollinated species (Irwin & Brody 2000). Other ways to exclude unwanted visits, is by camouflage.

Flowers of Eucomis autumnalis (Mill.) Chitt. and Eucomis comosa (Houtt.) H. R. Wehrh. are visually cryptic by having similar color to leaves, attracting pollinators solely by smell

(Shuttleworth & Johnson 2009).

Accordingly, it appears that even though pollination syndromes were not developed to be diagnostic (Wilmer 2011), the predictive power of pollination syndromes is limited and frequently overstated. Interestingly, pollinators seem to prefer a certain flower color, but flower color does not determine pollinator assemblage, supporting the notion that generalization seems to be a more frequent flower strategy (Reverté, Retana, Gómez & Bosch 2016). In Erysimum, lilac flowers were related to a pollinator niche comprised of large long-tonged bees, but it seems that the development of lilac flowers pre-dates pollinator preference and is probably related to other environmental factors which eventually led to bee pollination (Gómez, Perfectti & Lorite 2015). The evidence for the hypothesis that plants develop certain colors to attract certain animals is controversial, as pollinator preference may lead to divergence of floral color rather than convergence (Schaefer,

Schaefer & Levey 2004, Arnold, Comber & Chittka 2009). Furthermore, the visual system of pollinator does not seem to be adapted to specific color preferences, as suggested by pollination syndromes (M. Erickson, D. J. A. Silva & D. M. A. Pessoa, in preparation). Overall, pollinators still provide a strong selective pressure as they will strongly impact reproductive success (Fig 2).

3.6 Phylogenetic constraints

Phylogeny might explain flower coloration in different ways (Fig 2). First, flowers are dependent on their genetic make-up to determine their pigments and color possibilities (Chittka

1997). The lack of bee white flowers has been associated with phylogenetic restrains (Chittka,

1999, Koski & Asman 2016). Second, related flowers can have a similar color because of their ancestral state, if there is not enough pressure to diverge from it. Some plant families tend to have

30 similar colors such as Apicaceae, whose flowers vary mostly in brightness rather than hue (Chittka

1997). Evolutionary history may also affect color because it allows for similar plants to withstand similar environmental factors, and hence to bloom close to each other. In Nepal, monocots are more present in lower elevations, and there is more color diversity in higher elevations (Shrestha,

Dyer, Bhattarai & Burd 2014).

The phylogenetical color signal is dependent on the biochemical pathways which determine coloration. In A. majus, single gene mutations may lead to color change in flowers (Dyer, Whitney,

Arnold, Glover & Chittka 2007). In Solanacea, biochemical pathways leading to red flowers by anthocyanin or double production of anthocyanin and carotenoids seem to possess phylogenetical signal (Ng & Smith 2015). More studies of floral genes should clarify whether there is convergence or divergence in floral signals (Schiestl & Johnson 2013).

Even though some studies corroborate the importance of phylogenetic signal for flower coloration (Reverté, Retana, Gómez & Bosch 2016; Ng & Smith 2015; Shrestha, Dyer, Bhattarai

& Burd 2014), a consensus is far from being achieved, since many studies found no effect of phylogenetic constraints on floral color, meaning that flower color and the phylogeny are not associated (Smith, Ané, Baum 2008; Arnold, Savolainen, Chittka 2009; McEwen & Vamosi 2010;

Gómez, Perfectti & Lorite 2015; Weber et al 2018). Many examples show that plant species are able to produce numerous colors in their lifetimes. For example, flower color change by pollination or age has been found in 77 families of plants that are taxonomically distinct (Weiss 1995). Plants can also produce fruits in different coloration than flowers, which exemplify that plants can allocate different pigments to serve desired functions (Chittka 1997). Additionally, some cultivated flowers can come in a wide variety of colors associated with different pigments and cell structure.

Roses, for example, can be red, pink, yellow, orange, white, violet and even green (Eugster &

Märki-Fischer 1991). Adaptative radiation can also exemplify how closely related flowers can easily diverge in color. In columbines (Aquilegia) single loss of one enzyme in the biopathway of some anthocyanins can cause blue to red transitions in flower color (Hodges & Dering 2009). All this indicates that given enough selective pressure, flowers are capable of rapid change in color

(Chittka 1997).

3.7 Floral age

Flower age can also affect flower color, as many plants show a dramatic color change, different from senescence (Weiss 1995). Byrsonima variabilis A. Juss., for instance, changes standard petal color during anthesis from yellow to orange and finally red, and bees preferentially visits flowers with yellow standard petals when foraging for pollen (Melo, Mota, Schlindwein,

Antonini & Oliveira 2018). The retention of old flowers increases display size and, by so doing, increases attraction of pollinators (Ishii & Sakai 2001). In fact, prolonged longevity of flowers can increase pollination even without color change (Texido et al 2019). It seems, however, that the retention of old flowers without color change might come with a cost, because it leads to plant- level avoidance by pollinators that have spatial memory (Makino & Ohashi 2017).

Flower color change has been extensively associated with directing pollinators to rewarding flowers, since flowers are unrewarding after color change (Weiss 1995). Indeed, at close range, flower color change can direct pollinators to rewarding flowers (Sun, Liao, Xia, Guo 2005), and is often considered an honest signal (Schaefer, Schaefer & Levey 2004, Makino & Ohashi

2017). Nevertheless, when considering long-distance attraction, it seems pollinators struggle to differentiate the amount of rewarding or unrewarding flowers (Oberrath and Böhning-Gaese 1999,

Kudo, Ishii, Hirabayashi & Ida 2007). For this reason, flower color change may attract pollinators at a distance via deception, by maintaining an increased display that includes unrewarding color

32 changed flowers that cannot be differentiated; once pollinators approach, however, it provides an honest signal, as to which flowers are rewarding (Brito, Weynans, Sazima, Lunau 2015).

There are other benefits to the retention of old-color changed flowers as, even without increased attraction, floral color change can decrease the amount of geitonogamous pollination

(when pollen is transferred from one flower to another flower of the same plant) (Ida & Kudo

2003, Sun, Liao, Xia, Guo 2005, Ida & Kudo 2010). In fact, flower color change seems to be such a huge advantage that some wonder why it is not prevalent among angiosperms (Ruxton &

Schaefer 2016). Flower color change is, however, more common than it gets credit for, and often we find new reports of color-changing flowers, even in the UV range (Ohashi, Makino & Arikawa

2015). Flower color change has evolved many times (Weiss 1995), and this outcome could be due to simple mechanisms. Pollinators have been shown to recognize old flowers as is the case in Rosa virginiana P.Mill., where second day flowers are paler, and bee preferentially visit younger flowers

(MacPhial, Kevan & Fuss 2007). Pigments are altered by sunlight, especially anthocyanins

(Grotewold 2006). Though color change can happen in any pigment, most color change seems to be associated with a change in anthocyanins (Weiss 1995, Lippi, Giuliani, Gonnelli, Bini 2011).

In Viola cornuta L. flowers, changes in color are due to anthocyanins; when flowers are grown in the dark, they do not show color change, as opposed to the white to purple change that occurs under light conditions (Farzad, Griesbach & Weiss 2002). Evidently, flower color change has evolved many times in relation to the natural reaction of anthocyanins to sunlight. Natural selection would refine this natural change, inasmuch as flower color change benefits plants by attracting more pollinators (Ishii & Sakai 2001, Ida & Kudo 2010) and diminishing geitonogamous pollination (Ida & Kudo 2003, Sun, Liao, Xia, Guo 2005, Ida & Kudo 2010), and pollinators, by diminishing foraging time (Kudo, Ishii, Hirabayashi & Ida 2007).

We discussed one pathway that could have led to flower color change, but there is likely to have more than one explanation. Flower color change can be a step into transitioning flowers from one pollinator to another, being ephemeral in evolutionary time (Ruxton & Schaefer 2016). In

Quisqualis indica (L.) DeFilipps, white flowers are mostly visited by moths and red flowers are visited by butterflies (Yan, Wang, Sui, Wang & Zhang 2016). Phylogeny and bee-pollination can also be major factors underlining the color change phenomenon (Ohashi, Makino & Arikawa 2015,

Makino & Ohashi 2017). There are many areas in flower color change that remain unexplored, such as the relation of color change to cost of pigments productions, evolutionary potential, and genetics (Ruxton & Schaefer 2016). Overall, flower color change is a phenomenon about which much is still to be learned.

3.8 Seasonal changes in flower color

A recurring theme in the literature is that flowers of certain colors bloom at certain seasons

(Wilmer 2011). Some insects change their color preference throughout the year (Kevan 1983), and so, flowers may bloom with the preferred color of the insects at a given time. The abundance of insects with color preference can also change throughout the year (Kevan 1983). In Australia,

Epacris impressa Labill. (common heath) has different color morphs that vary across seasons. The white morph is found in spring and the red flower on winter. This occurrence seems to be related to abundance of pollinators, because birds are present in winter when the red morph blooms, and white morphs occur in spring when insects are more plentiful (Stace & Fripp 1977).

Temperature might be a driving factor in determining floral color in polymorphic plants.

Mu, Li and Sun (2010) found that during the early flowering season when temperature was lower and the photoperiod shorter, the white color morph of the Tibetan herb Gentiana leucomelaena

Maxim. was much more abundant that the blue morph; latter in the season, when the temperature rose, the blue color morph became more abundant.

Flowers of darker color will be warmer than light colored flowers. Some pollinators, such as bees, can associate color difference with warmer flowers and preferentially forage on warmer flowers (Dyer, Whitney, Arnold, Glover & Chittka 2006). This makes for interesting pollination systems where heat is offered as a reward. In Oncocyclus irises, pollinators do not get any nectar or pollen reward, instead, flowers warm up quickly in the morning and so male bees who sleep inside flowers will start foraging earlier the next day (Sapir, Shmida & Ne'eman 2005).

There is some evidence of a convergence of flower color depending on the season, but that effect varies according to the population studied. Though the flower color of spring flowers does not seem to be white, as previously stated (Molten 1986), the corolla color of flowers in temperate deciduous forest, which flower in spring, tend to be lighter than non-spring flowers (Hensel &

Sargent 2012). In Germany, flower color was studied across a year period, and there was no relationship between floral color and blooming time using bee's color category, but there was a difference in the human color categories, showing that importance of using an ecologically relevant visual system to analyze color (Arnold, Comber & Chittka 2009). More research, emphasizing the pollinators perspective and accessing different populations, are needed in order to reach a better understanding of the effects of seasons on flower coloration.

3.9 Biogeographical changes

Because different communities have different selective pressures it is also important to study if there is a selection for specific colors depending on the habitat. Microclimates could help explain UV patterns of flowers. Habitats with high UV-B irradiance were more likely to have UV- absorbing flowers (Koski & Asman 2016). Another hypothesis is that flower color can vary with

35 different altitudes, because the amount of ambient light varies with altitude (Kevan 1983) and since higher altitudes will have different insect visitors. When the flora of Dovrefjell–Sunndalsfjella

National Park (Germany) was studied, at different altitudes, with regard to flower coloration and according to bee and fly vision, the results showed no effect of altitude on color (Arnold,

Savolainen, Chittka 2009). Yet, this is not always the case, as, in Nepal, flowers found in higher altitudes show more diversity of colors than in lower ones (Shrestha, Dyer, Bhattarai & Burd

2014).

Neutral factors can also contribute to the spatial distribution of plant color morphs. The iris

Iris lutescens Lam. has two color morphs, with different distributions across Spain and France.

Different processes seem to be acting in the two regions. Spain has monomorphic populations of either yellow or purple flowers that have little to no gene flow between them, and genetic drift seems to be the likely factor determining the polymorphism. In France, however, there is gene flow between populations and so, most populations are polymorphic composed of both colors

(Wang, Talavera, Min, Flaven & Imbert 2016). Similarly, in the milk thistle Silybum marianum

(L.) Gaertn., neutral process such as the founding effect and genetic drift, seem to explain the variation of color morphs along the Mediterranean (Keasar, Gerchman & Lev-Yadum 2016).

Another factor that may yield selection for different colors is the abundance of different kinds of pollinators across habitats. Indeed, flower coloration in Australia (Dye et al 2012) and

Israel (Chittka & Menzel 1992) seems to be shaped by Hymenoptera vision. Bees are important pollinators in Europe, as they do not have many bird pollinators. The abundance of red flowers in the tropics is often attributed to hummingbird pollination (Wilmer 2011). Blue-purple flowers in the artic seem to be related to species richness of bumblebees showing a coevolution between flower color and pollinator species (Eidesen, Little, Müller, Dickinson & Lord 2017).

Pollinators can also have differential color preferences between habitats. Bumblebees usually have a UV-violet preference, but some populations have an additional red preference

(Raine, Ings, Dornhaus, Saleh & Chittka 2006). Hence, plants can have local adaptations depending on pollinators. The mimetic Orchid Disa ferruginea Sw., is pollinated by a single species of butterfly. This orchid has two color morphs occurring in different geographical regions.

The red morph occurs when there are red rewarding flowers around, and butterflies shows preference for red flowers. Likewise, the orange morph occurs when there are orange rewarding flowers and butterflies show orange preference (Newman, Anderson & Johnson 2012).

Some studies have tried to associate habitat with flower color, showing that there can be a convergence of floral color, divergence in floral color, or just a random distribution. Chittka (1997) has shown that the color distribution of flowers in a German grassland was not found to be different from chance, but in the Brazilian rainforest flowers seemed to cluster around bee-blue. another study, conducted in Brazil, showed that in the Restinga (a sandy area near the coast with poor soil, the predominant vegetation is medium sized trees and shrubs) region there was a prevalence of white flowers and in the Caatinga (a semi-arid region characterized by small thorny trees and shrubs that shed their leaves in the summer) region most flowers were yellow (Machado & Lopes

2003). Moreover, subalpine communities in Canada show evidence divergent evolution of floral color (McEwen & Vamosi 2010). In another study, Gumbert, Kunze and Chittka (1999) analyzed five different habitats, within Germany, for trends in flower color. When only considering common flowers, they did not find any prevalent color; but when rare flowers were included, the results varied across locations, since in dry meadow and hazel shrub, plant colors were more divergent than expected by chance. On the other hand, the same study found that in the humid meadow, colors were more similar than expected by chance, and that in the maple forest and roadside, colors

37 did not differ from a random distribution. Until now, literature shows that, depending on the habitat, there can be selection for either divergence or convergence of floral color. There are many pressures in a given habitat that will make up their color diversity (Fig 2). In order to determine biogeographical patterns in floral color, the evaluation of other habitats, using a pollinators perspective, should be encouraged.

3.10 Sensory drive

According to Endler’s theory of sensory drive, the environmental bias, noise and receiver’s sensory capabilities tend to shape the evolution of signals, by selecting signals and receivers that better overcome noise in a given environment, selecting more conspicuous signals and more efficient receivers (Endler 1992). In general, flower coloration is an interesting context to study sensory drive (Schaefer, Schaefer & Levey 2004), because flowers are present in several different environments and, since they cannot move, are restricted to the signaling conditions of the given location. Predictively, bees prefer to forage in flowers that are more conspicuous in their background (Forrest & Thomson 2009). We should expect the same for other pollinators inasmuch as conspicuousness diminishes search time. More conspicuous flowers, however, would also be more readily perceived by antagonists; and thus, natural selection against herbivory could balance flower sexual selection for more conspicuous flowers (Fig 2).

Bees have been shown to detect changes in ambient light and use these as contextual cues

(Lotto & Chittla 2005). Filtering of ambient light in areas of abundance of woody long-lived plants, in relation to herbaceous species, might explain why some flowers appear to have lighter corollas

(Hensel & Sargent 2012). Ambient light also varies across seasons, especially in deciduous or semi-deciduous forests, in which the falling of the leaves will cause a different light filtering

(Endler 1993). In the understory of a green forest, we expect to have many yellow flowers, since

38 the canopy filters most of the red and blue light, while on the treetops, in which the broad spectrum of the sun is found, we should expect no difference in abundance of flowers of different colorations, except for green flowers, which would not contrast well against the green dappled foliage.

Depending on the background contrast, the same flower may be perceived as bearing different colors, so that pressure to overcome background noise might be crucial to development of conspicuous colors (Bukovac, Shrestha, Garcia, Burd, Dorin & Dyer 2017). Plants that develop dense foliage might overcome visual background noise (Bukovac, Shrestha, Garcia, Burd, Dorin

& Dyer 2017), helping bees, for instance, to forage under more visually uniform conditions

(Forrest & Thomson 2009). For flower species that occur in more than one environment (e.g. one with dense foliage and another with thin leaves), and/or for backgrounds that go through seasonal changes (e.g. falling leaves and leaf color changing), flower signals would also have to overcome different background noises, that could act as important selective pressures on the evolution of flower coloration and pollinator visual system. Nevertheless, in forests and grasslands of Germany, according to the honeybee visual system, flowers seem to have similar colors (Binkenstein &

Schaefer 2015). The importance of background coloration to the evolution of flower visual signals is well exemplified by a study conducted in the Eastern Mediterranean, by Dafni et al. (1999).

These authors found that there is an abundance of red flowers in the region, which are visited by beetles (with poor red-green discrimination), not by birds (with good red-green discrimination), because flowers bloom before the green foliage develops, enhancing the red flower contrast against the sandy background (Wilmer 2011).

Sensory drive can play an important role explaining the convergent evolution of coloration across seasons and habitats, as environmental noise can make flowers of a certain color less

39 conspicuous, and thus less visited by pollinators. According to sensory drive, we should expect flowers in similar signaling environments to evolve towards similar colors. This is not considered in many of the studies trying to determine floral coloration in different localities and seasons, as they do not attempt to control different background colors or light environments. How sensory drive affects the evolution of color is an increasingly popular topic, however, only recently we have been observing the use of plant models to study concepts used, almost, exclusively in animal communication.

3.11 Prospects

As we have seen, several different factors affect flower coloration (Fig 2), and different environmental pressures will determine if it is best to diverge or converge signals with their neighbors. While, plant coloration is dependent on available pigments, a direct pigment-pollinator link, is unlikely. Pigments are determined by phylogeny (Chittka, Shmida, Troje & Menzel 1994), but small mutations on plant pigments may cause perceptual change in flower color (Dyer,

Whitney, Arnold, Glover & Chittka 2007) and plant linages often display transition in color

(McEwen & Vamosi 2010). Flower colors are determined by natural selection, which favors colors which increase plant fitness against multiple selective pressures, but neutral selection such as genetic drift and founding effect can also explain certain patterns in flower color. Flower coloration offers a unique perspective in interspecific communication. Yet studies that account for other visitors other than pollinators are rare, and it is a growing field where there is much to be done.

Figure 2. Diagram exemplifying how flower color is affected by different factors discussed in this review.

Studies involving geographical and temporal patterns need to be conducted in more environments so we can better understand the relationship between location and flower color.

Sensory drive in flower coloration can be an interesting topic that has much to be explored. It is important to conduct research in relation to the coloration of flowers across forest canopy. In future studies of plant coloration, it is also important to consider herbivory and other antagonistic interactions and how they shape the evolution of flower color. Future studies in the field can focus on many questions. How are eavesdroppers shaping the evolution of flower color? How often do plants use color signals to repel visitors? Should we still use floral syndromes as the bases of flower-pollinator interactions? If not, how does pollinator preference shape the evolution of floral signals? Which biochemical pathways lead to flower color change? What environmental pressures shape color in flowers? Are flowers converging or diverging in color in a given habitat? How are all these factors related to the evolutionary history of these plants?

3.12 References

Arikawa, K. (2017). The Eyes and Vision of Butterflies. Journal of Physiology, 595(16), 5457– 5464. https://doi.org/10.1113/JP273917

Armbruster, W. S. (2002). Can Indirect Selection and Genetic Context Contribute to Trait Diversification? A Transition-Probability Study of Blossom-Colour Evolution in Two Genera. Journal of Evolutionary Biology, 15(3), 468–486. https://doi.org/10.1046/j.1420-9101.2002.00399.x

Arnold, S., Le Comber, S., & Chittka, L. (2009). Flower Color Phenology in European Grassland and Woodland Habitats, Through the Eyes of Pollinators. Israel Journal of Plant Sciences, 57, 211–230. https://doi.org/10.1560/IJPS.57.3.211

Arnold, S., Savolainen, V., & Chittka, L. (2009). Flower Colours Along an Alpine Altitude Gradient, Seen Through the Eyes of Fly and Bee Pollinators. Arthropod-Plant Interactions, 3, 27–43. https://doi.org/10.1007/s11829-009-9056-9

Binkenstein, J., & Schaefer, H. M. (2015). Flower Colours in Temperate Forest and Grassland Habitats: A Comparative Study. Arthropod-Plant Interactions, 3(9), 289–299. https://doi.org/10.1007/s11829-015-9369-9

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4. ARTIGO 2

Pollination syndromes do not predict flower conspicuousness by different pollinators

Marilia Erickson1 , Diogo Jackson de Aquino Silva & Daniel M. A. Pessoa

Laboratory of Sensory Ecology, Department of Physiology and Behavior, Universidade Federal do Rio Grande do Norte. Natal – RN, Brazil. CEP 59078-970

2- MSc student; E-mail: [email protected]

4.1 Abstract

Pollination syndromes have long been used to categorize and study flowers. Recently, this idea came into question as, it seems, most pollinators and flowers are generalist. There is a debate about whether we should continue to use pollination syndromes to study pollination. Little empirical data has been adduced to explain why pollinators prefer characteristics described by pollination syndromes. The aim of this study is to contribute to the ongoing debate, by investigating if flower conspicuousness, through the eyes of bees, flies, butterflies and hummingbirds, can explain color preferences described by traditional pollination syndromes. We used the Receptor Noise Limited model to calculate chromatic contrast between flowers and background. First, we tested if pollinators could discriminate better flowers of their own syndrome when compared with other floral syndromes. Second, we tested if flowers with colors associated with pollination syndromes were more conspicuous to their pollinators. And finally, we compared if pollinators could detect better flowers or colors of their own syndromes when compared with other pollinators. We found that pollinators do not see flowers of their own syndrome as more conspicuous, when compared to flowers of other syndromes, and that the colors of the most conspicuous flowers were not those predicted by pollination syndromes. On average, animals with tetrachromatic vision had a higher color contrast that trichromatic animals. Pollinators, however, could detect well all flower colors, with the exception that bees saw red poorly, as previously described in the literature. Overall, our findings support the idea that flowers are generalist regarding pollinators. This does not, however, mean that color preferences do not exist, as preferences could be explained by other mechanisms, such as innate preference, hue or brightness. Key words: Color vision; floral biology; flower color; Apis mellifera; Drosophila melanogaster; Heliconius erato; Sephanoides sephanoides.

4.2 Introduction

Pollinator pressure and sexual selection are considered to be the main factors driving the evolution of floral characteristics (Schiestl & Johnson 2013). Since pollinators with similar morphology exercise similar pressures on flowers, there is a tendency for flowers to converge towards certain traits (Fenster, Armbruster, Wilson, Dudash & Thomson 2004). Flower species often converge to characteristics associated with groups of pollinators giving rise to the idea of pollination syndromes, which is often used to predict pollinators of given flowers (Wilmer 2011).

By looking at flower morphology, it would then be possible, on this account, to characterize its pollinator, and, indeed, some papers have been able to show that pollination syndromes have compelling predictive power. Rosas-Guerrero et al (2014) conducted a meta-analysis of pollination data, finding pollinators that matched floral syndromes to be more effective pollinators. In

Australian epacrids, pollination syndromes characteristics correctly identified bird pollinated species in 86% of cases, fly pollinated species in 78% of cases and bee pollinated species in 69% of cases (Johnson 2013). While in South African flora, floral syndromes correctly predicted pollinators in 82% of the time (Johnson & Wester 2017). This is not, however, always the case, for many researchers have shown little support for pollination syndromes (Waser, Chittka, Prince,

Williams & Ollerton 1996; Ollerton et al 2009; Hernández-Yáñez, Lara-Rodríguez, Díaz-

Castelazo, Dáttilo & Rico-Gra 2013).

For one thing, pollination syndromes have been criticized on the grounds that the relationship between flower and pollinator is neither as peaceful nor as clear-cut as previously supposed (Waser, Chittka, Prince, Williams & Ollerton 1996). In fact, flowers employ pollinators to transport their gametes while pollinators are foraging for resources, which relationship could be described, at best, as mutual exploitation (Westerkamp 1996). Furthermore, most flowers receive

54 visits from multiple pollinators, and pollinators often visit more than one flower, consequently most flowers tend to be generalist regarding pollinators (Waser, Chittka, Prince, Williams &

Ollerton 1996). Regardless of the widespread use of pollination syndromes, it is still unknown how well syndromes describe phenotypic variation for plant-pollinator interaction (Ollerton, Rech,

Waser & Prince 2015), such as flower shape, nectar amount, color, time of anthesis, presence of nectar guides, among others (Wilmer 2011).

Color is one of the main characteristics attributed to pollinator syndromes (Faegri & Van der Pijl 1979), and it assures long distance attraction and flower constancy (Chittka & Menzel

1992). Flowers that are more conspicuous are preferred by pollinators because they diminish search time and increase foraging efficiency (Forrest & Thomson 2009). Red flowers, for example, have been shown to be more conspicuous for hummingbirds than white, yellow or orange ones

(Herrera et al 2008). Attracting naive pollinators due to their innate color preferences can limit the evolution of flower color and lead to convergent evolution as explained by pollination syndromes

(Lunau & Maier 1995). Bumblebees have innate preference for flowers in the violet-blue range

(Briscoe & Chittka 2001). Innate preference can also reflect adaptation to pollen feeding, as is the case with the hoverfly Eristalis tenax, which shows the innate reaction of extending their proboscis in response to yellow stimulus (Lunau & Wacht 1994). Reverté, Retana, Gómez & Bosch (2016) found that pollinators groups prefer to visit flowers of similar color (i.e; bees visit purple flowers, butterflies visit pink flowers). The relationship between innate preferences of pollinators is often used to justify the convergence of floral signals, but this supposition often lacks empirical data

(Schiestl & Johnson 2013). For instance, bee flowers come in almost all possible colors, not only pink, purple, blue, white and yellow, as predicted by their pollination syndrome (Wilmer 2011).

Perhaps this is due to pollinators ready capacity to associate flower color and reward, not being limited by innate preferences (Weiss 1997, Gumbert 2000).

Flower syndrome colors are attributed considering human vision, even though flowers can reflect ultraviolet (UV) light. This poses a problem, since humans and pollinators differ regarding their color vision. Bees are trichromats with photoreceptors in the UV, blue and green range

(Peitsch et al 1992). Flies, butterflies and hummingbirds often see the full electromagnetic spectrum with receptors on the UV, blue, green, and red region; but even within these groups, peak receptor sensitivities vary (Briscoe & Chittka 2001; Herrera et al 2008; McCulloch, Osorio &

Briscoe 2016). Although it is stated that bees prefer flowers that reflect UV light, all major groups of pollinators can also see UV light. The preference for UV reflecting flowers depends on context.

Red flowers pollinated by orchid bees usually reflect UV while white orchid flowers pollinated by bees usually lack UV reflection; the opposite is true for hummingbirds (Lunau, Papiorek, Eltz &

Sazima 2011).

The investigation of flower coloration from the perspective of multiple color visual systems has been largely underexplored (Schaefer, Schaefer & Levey 2004). Considering this, here we test if the color preference observed in pollination syndromes is sustained by certain flower colors being more conspicuous to pollinators. First, we test the hypothesis that pollinators detect flowers of their own syndrome better than flowers of other syndromes. Then, we investigate what color is more conspicuous to each pollinator (bees, flies, butterflies and hummingbirds). We predict that bees will see blue, yellow and white flowers best; birds will see red flowers best; butterflies will see red and yellow flowers best; while flies will see green and white flowers best, since these are the colors associated with each pollination syndrome (Wilmer 2011). Third, we want to compare conspicuousness between pollinators. We expect that, for instance, the bees’ visual system should

56 find bee flowers more conspicuous than flowers pollinated by flies, butterflies and hummingbirds, and so on. We also expect that certain flower colors should be more conspicuous to a given pollinator, according to color preferences described in each pollination syndrome. As in, bees should outperform birds in the detection of blue, and birds should outperform bees in the detection of red. To test these hypotheses, we calculate the chromatic contrast between flowers and their backgrounds, according to the visual system of each pollinator, using the Receptor Noise Limited model (Osorio & Vorobyev 1996).

4.3 Materials and methods

4.3.1. Data collection

We collected flowers between February of 2018 and January of 2019, in two different sites in Northeast of Brazil: the Floresta Nacional de Assu (-5,579745;-36,942139), which corresponds to a Caatinga (xeric shrubland/thorn forest) region, and the Reserva Biologica de Guaribas (-

6,74117;-35,138377), which corresponds to an Atlantic forest region. We collected flowers at the understory vegetation, that were up to 1.5m of the ground, which comprised mostly herbs and shrubs. After collection, flowers (Table S1) were transported, as quick as possible (maximum delay of one and a half hours), to an improvised laboratory. We used a USB4000-UV-VIS spectrometer connected to a DH-2000-BAL light source and a bifurcated QR450-7-XSR fiber (all by Ocean Optics Inc.), and software SpectraSuite (Ocean Optics Inc.), to measure the flowers and their respective backgrounds (leaves, sand, tree trunks, and modified leaves of the inflorescence,

Table S1). In order to measure flowers that were, at least, one millimeter in diameter, we attached a custom-made probe holder at the end of the fiber, to taper the measurable surface area to 1 mm.

Reflectance spectra registered with the custom-made probe holder, 3D printed in black plastic, were very similar to those registered with a RPH-1 probe holder (Ocean Optics Inc.) (Fig S1). All

57 stimuli were measured at with the probe holder in direct contact to the object surface, allowing measurements to be taken at a 90° angle, with a constant distance of 5mm from the probe. To calibrate the equipment, we used a Spectralon Reflectance Standard WS-1-SL (Ocean Optics Inc.) as the white standard, then turned the light source off and obstructed the probe holder orifice with a black cloth, for determining the black standard. In total, we measured 44 species from the

Caatinga and 50 species from the Atlantic forest habitat. Since two of the flowers from the

Caatinga were polymorphic regarding color (Croton sp. and Jacquemontia pentanthos) we set the total number of targets at 96 flower specimens. For those species whose flowers changed color, we used the pre-change color to characterize the species (i.e. for Lantana camara we used yellow flowers which precede orange and red floral phases). All flowers were mounted in Exsiccatae, deposited in the herbarium of Parque das Dunas (RN), and were identified by a professional botanist.

To measure the ambient light, we used the same spectrophotometer described above, attached to an QP450-2-XSR optic fiber (Ocean optics), with a cosine corrector (CC-3-UV-S,

Ocean Optics, Inc.). The apparatus was calibrated using a LS-1-CAL calibration lamp (Ocean

Optics, Inc.). The optic fiber was pointed upwards towards the sky, at each of the desired areas, to acquire illuminance measurements (Fig S2). For forest flowers we did not measure the illuminant, but instead used the forest shade illuminant, available in “pavo2” package.

4.3.2. Categorization of flower pollination syndrome and flower coloration

To categorize each flower as belonging to a pollination syndrome, we used the characters described by Wilmer (2011), that could be assessed either visually or olfactorily (“main color”,

“nectar guides”, “scent”, “shape”, “nectar site” and “pollen deposited”). Our flowers fell into five

58 syndromes: melittophily- Bee pollinated (51), psychophily – butterfly pollinated (23), myophily- fly pollinated (19), ornithophily – bird pollinated (2) and anemophily – wind pollinated (1).

Flower color was categorized based on Wilmer (2011) categories, to which we created individual descriptions (Table S2). Because of the reduced sample size of each category, we grouped the categories of Table 1 in new ones (Table 1). For the tests we used these new categories.

To characterize if flowers had UV, we created a standardized method by comparing different techniques (Percentage of reflectance between 300nm and 400nm compared to reflectance at exactly the wavelength 350nm in different ratios 5%, 8% and 10%). The criteria we found more reliable (matched the noticeable peaks in the spectrum) was if reflectance had at least 10% of reflectance in the Wavelength 350nm, so we used it to characterize flowers in our study. Therefore for each color category we had flowers without reflectance on UV (UV-), flowers with reflectance on the UV (UV +) and flowers with and without together (Total) to represent how humans have categorized flowers in syndromes.

Table 1. New color categories with description and number of flowers in each group.

Color Number of flowers sampled category Description Includes UV- UV+ Total Pure red, unsaturated red, dark red, and red, mauve, Red red with tints of yellow orange, brown 4 4 8 Pure yellow, light yellow and muted cream, yellow, dull Yellow yellow beige 18 11 29 All greens, yellow with tints of blue, and green, greenish, Green blues with tints of yellow pale green 10 3 13 Blue pure blue and blues tinged red blue, pink, purple 13 3 16 white, dull white, white true white, off-whites and light grays dull 25 5 30 Mottled irregular patches Mottled 0 0 0

4.3.3. Visual modeling

To calculate the color difference between the background and each flower petal we used the Receptor Noise Limited (RNL) model (Osorio & Vorobyev 1996), which gives the chromatic contrast (S) in Just Noticeable Difference (JND) units. For the RNL model, the detectability threshold is 1 JND, which means that targets contrasting, solely in color, from background elements in less than 1 JND should not be distinguishable by the visual system taken into consideration. Different pollinators might have different detectability thresholds, however, since these data are not available for most species (Olsson, Lind, & Kelber, 2018), we used the standard threshold of 1 JND for all models. The higher the chromatic contrast (measured in JND units), the higher the color difference between surfaces (Ham & Osorio 2007) and hence they would be more easily detected. We classified flowers as cryptic (S < 1 JND), barely detectable (S between 1 and 3 JND) and detectable (S > 3 JND).

We used the software R studio and the “pavo2” package (Maia, Bitton, Doucet & Shawkey

2018) for all the visual modeling analyses. The input from each visual system is described in Table

2. All spectral reflectance was smoothed in ‘pavo2’ package with a spawn of 0.12 prior to modeling. The illuminant spectra were chosen according to the habitats in which each flower was most frequently found. We used forest shade illuminant, available in “pavo2” package, for flowers found inside the forest. For flowers found in the Caatinga, or outside the forest (in the Restinga), we used illuminants that we previously gathered at each area.

Regarding the proportion of photoreceptors, we attributed a value of one to the least frequent photoreceptor, while scaling the other frequencies accordingly (i.e; 1:1:3 for bees). Since the frequency of receptors for short (S) and middle (M) wavelenghts are known to vary in bees

(Chittka & Raine 2006), we assumed each type had equal proportions. For S. sephanoides

60 hummingbirds, since this information is unavailable, we used the average proportion of photoceptors found in passerines (Heart & Hunt 2007). H. erato butterflies exhibit a visual sexual dimorphism (McCulloch, Osorio & Briscoe 2016), so we modelled female (F) and male (M) vision separately

Table 2. Parameters used in our visual modeling.

Popular Photoreceptors’ peak Animal model name sensitivities Photoceptor proportion Weber fraction Apis mellifera Honey bee 328, 436, 532 nm1 S: 1; M: 1; L: 35 0.128

Heliconius erato F Butterfly 355, 390, 470, 555 nm2 UV: 1.3; S: 1; M: 2.4; L: 14.32 0.059 Heliconius erato Butterfly M 390, 470, 555 nm2 S: 1; M: 1.5; L: 7.72 0.059 Drosophila House fly melanogaster 345, 375, 437, 508 nm3 UV: 1; S: 2; M: 1; L: 2 6 0.1010 Sephanoides Humming sephanoides bird 371, 444, 508, 560 nm4 UV: 1; S: 1,9; M: 2,8; L: 3,3 7 0.1010 1- Peitschet al 1992; 2- McCulloch, Osorio & Briscoe 2016; 3- Salcedo et al. 1999; 4- Herrera et al 2008; 5- Chittka & Raine 2006; 6- Kirschfeld & Franceschini 1978; 7- Heart & Hunt 2007; 8- Hempel de Ibarra, Giurfa & Vorobyev 2001; 9- Koshitaka, Kinoshita, Vorobyev & Arikawa 2008; 10- Vorobyev, Osorio, Bennett, Marshall, & Cuthill 1998.

4.3.4. Statistical Analysis

We used grouped flowers in previously described color and syndrome categories to test compare color contrast of flower within a specific visual system, and between different pollinators visual systems. For comparisons within a pollinator visual system, we tested if pollinator groups could detect better flowers bellowing to a syndrome (i.e; bees saw mellitiphilous flowers better than psychofilous flowers and myophilous flowers) and if in each of the syndrome categories flowers were more conspicuous to the respective pollinator of each category (i.e, melittophily flowers more conspicuous for Apis melifera, myophily flowers more conspicuous to Drosophila melanogaster). Comparisons between visual systems were made in three ways. First, in order to

61 compare if any specific pollinator saw all flowers as more conspicuous than other pollinators we checked if the color contrast of all flowers together was higher to a specific pollinator (i.e; If overall flowers were more conspicuous to bees, flies, butterflies or birds). Second, we tested which color had higher color contrast by each pollinator (i.e; If bees see blue flowers better than red flowers).

Third, which pollinator saw each color better (i.e; If birds saw red flowers better than bees). To test our hypothesis, we used the software R studio. To do this we first check the distribution of the data. Most data did not have a normal distribution (Shapiro-Wilk, p-valor < 0.05), so we used a

Kruskal-Wallis analysis, with Dunn’s test as a post-hoc analysis, adjusting the P value through

Bonferroni’s correction. Some of the groups had fewer than 5 species per category and therefore statistics would be unreliable, so we only show statistical results for samples higher than five.

Considering the UV reflection made little difference in the overall results, probably because it lowers the number of flowers in each category, so we only present the summed results of each color category (UV- plus UV+).

4.4. Results

For flies, butterflies (either males and females) and hummingbirds all chromatic contrasts

(S) between flowers and backgrounds were above the predetermined detection treshhold (JND >

1), meaning all flowers were detectable for the visual systems of these pollinators. (Table 4) Yet, for bees, two flowers (from a total of 96) of the red category (one mauve and one orange) felt below the detection threshold, meaning that these two flowers would not be distinguished from their background by the visual system of bees (Table 4).

Table 3. Number of flowers, of different colors, that are cryptic (S < 1 JND), barely detectable

(S between 1 and 3 JND) and detectable (S > 3 JND), according to the visual system of bees, flies, butterflies (males and females) and hummingbirds.

Modeled Spcies Color Discriminability ∆S < 1 JND 1 JND < ∆S < 3 JND 3 JND < ∆S Blue 3 13 Green 7 6 Yellow 6 23 Red 2 2 4 A. mellifera White 4 26 Blue 16 Green 1 12 Yellow 29 Red 3 3 D. melanogaster White 30 Blue 16 Green 1 12 Yellow 29 Red 1 7 H. erato White 1 29 Blue 2 14 Green 4 9 Yellow 2 27 Red 1 7 H. erato White 3 27 Blue 16 Green 5 8 Yellow 2 27 Red 1 7 S. sephanoides White 3 27

Statistically, considering the visual system of flies (x2 =2.67, df =2, P = 0.26), female butterflies (x2 =2.86, df =2, P = 0.23), male butterflies (x2 =2.46, df =2, P = 0.29), hummingbirds

(x2 =2.37, df =2, P = 0.3), and bees (x2 =4.27, df =2, P = 0.11) flowers of different pollination syndromes were not significantly different. In other words, flowers from each pollination syndrome were equally conspicuous, irrespective of the visual system considered (Figure 1). The sample size of bird pollinated flowers was to small to be compared statistically.

Figure 1. Boxplot showing distribution of chromatic contrast values between flowers and background elements, comparison is within visual system of pollinators where flowers are grouped

64 by syndrome A) flies, B) Female Butterfly, C) Bee, D) Male butterfly, E) Hummingbird. Different letters indicate statistical difference between groups. (α= 0.05).

Regarding flowers of different color categories (Fig 2)., bees saw better white and red was the least conspicuous color (x2 = 17.34, df =4, P < 0.05). Flies also detected white flowers better and detected red and green flowers worst (x2 =16.68, df =4, P < 0.05). For female butterflies, even if our analysis showed there was a difference in chromatic contrast between colors (x2 = 11.14, df

=4, P = 0.03), the post hoc failed to detect where is the difference and we will treat these results as all colors being equally conspicuous. For male butterflies, however, yellow was the most conspicuous color, and white and green were least conspicuous (x2 =13.58, df =4, P = 0.01).

Lastly, for humming-birds yellow was the most conspicuous color and red was the least conspicuous (x2 =11.6, df =4, P = 0.02).

When comparing chromatic contrasts of all flowers as seen by different pollinators, D. melanogaster and female H. erato had the highest chromatic contrasts, followed by S. sephanoides, male H. erato and A. mellifera (x2 = 100.17, df = 4, P < 0.05).

Continuing comparisons between pollinators, flowers predicted by each syndrome were not better viewed by their assumed Pollinators (Fig 3). Bee pollinated flowers were best vied by flies and female butterflies, rather than by bees (x2 = 63.92, df =4, P < 0.05). Fly pollinated flowers

(x2 = 16.55, df =4, P < 0.05) and Butterfly pollinated flowers (x2 = 30.8, df =4, P < 0.05) were best viewed by both D. melanogaster and female H. erato as seems to be the regular pattern. Samples sizes of both ornotophilous (2) and anemophilous (1) flowers were too small to allow statistical comparison, however, we identified a pattern suggesting that ornotophilous flowers could be best seen by S. sephanoides.

Figure 2. Boxplot showing distribution of chromatic contrast values between flowers and background elements, comparison is within visual system of pollinators where flowers are grouped by color. A) flies, B) Female Butterfly, C) Bee, D) Male butterfly, E) Hummingbird. Different letters indicate statistical difference between groups. (α= 0.05).

Figure 3. Boxplot showing distribution of chromatic contrast values between flowers and background elements, comparison is within pollination syndrome where data are grouped by visual system of pollinators. Abbreviations are the following AM) A.mellifera, DM) D. melanogaster,

HE♀) Female H. erato, HE♂) Male Heliconius erato SS) S. sephanoides. Different letters indicate statistical difference between groups. (α= 0.05).

Figure 4. Boxplot showing distribution of chromatic contrast values between flowers and background elements, comparison is within flower coloration where data are grouped by visual system of pollinators. Abbreviations are the following AM) A. mellifera, DM) D. melanogaster,

HE♀) Female H. erato, HE♂) Male H. erato SS) S. sephanoides. Different letters indicate statistical difference between groups. (α= 0.05).

When comparing colors between pollinators, color categories blue: (x2 = 22.51 , df =4, P <

0.05), green (x2 = 11.02 , df =4, P = 0.02), white ( x2 = 51.38 , df =4, P < 0.05), yellow (x2 =

34.587 , df =4, P < 0.05) followed the general trend of having a higher chromatic contrast for D. melanogaster and Femle H. erato followed by Male H. erato and S. sephanoides, with A. mellifera having the lowest contrast in all cases (Fig 4). Although red was not statistically significant (x2 =

8.62, df =4, P = 0.07), still followed the trend graphically (Fig 4).

4.5. Discussion

Comparison within pollinators showed that pollinators could not identify flowers of their own syndrome better, so the first hypothesis was not corroborated. Flowers signaling equally to all pollinators would be good evidence that they are generalist regarding pollination as previously stated (Waser, Chittka, Prince, Williams & Ollerton 1996).

Isolating the color factor of pollination syndrome could also not support color preferences previously described in the literature. White flowers would be the most conspicuous to flies, but not green. Previous studies have shown some flies have innate reactions to yellow (Lunau & Wacht

1994), but these results do not show much relation with color contrast. there are little evidential bases to explain why flies would prefer colors stated in pollination syndromes.

For female butterflies all colors were highly conspicuous and tests failed to see where the difference in color detection is. For male butterfly, however, there was a clear difference between the detection of yellow and other colors. In fact, male butterflies could detect yellow flowers as well as tetrachromats. In Heliconius butterflies, color vision likely evolved due to sexual selection and the need to find mates (Briscoe et al 2010). Many butterflies in this genus have yellow wing patterns, and yellow and ultraviolet are important mating colors for Heliconius (Finkbeiner,

Fishman, Osorio & Briscoe 2017). Remarkably, even butterflies that do not visit flowers have

69 innate preferences for yellow flowers (Weiss 1997; Balamrali, Edison, Somanathan &

Kodandaramaiah 2019). So, the preference for yellow could be linked to the role that coloration has in sexual selection. Hence, yellow flowers could be exploiting these butterflies’ sensory bias in order to assure their pollination. Reverté, Retana, Gómez & Bosch (2016), however, found butterfly preference for pink flowers, while Weiss (1997) found secondary innate bias for blue and purple flowers, which colors are typically associated with bee pollinated flowers.

For birds, our results show that red was the least conspicuous color, which is unexpected considering that red is the color typically associated with bird pollinated flowers. The red in the ornithophily syndrome, however, has been associated with avoidance by bees, not by a specific preference for red by birds (Lunau, Papiorek, Eltz & Sazima 2011), and according to our model, bees indeed would have difficulty detecting red flowers. As they could not differentiate two of the red flowers from their background colors. There result also contrast with the ones found by

Herrera et al (2008), where red was the most conspicuous color to S. sephanoides. This could be related to our reduced sample size or due to the fact that we did not find any purely red flowers.

Lastly, for bees red was the least contrasting color, but still does not corroborate the previously described bee colors as green was also relatively conspicuous. According to the literature, bees have an innate color preference for UV-blue and blue-green flowers (Giufa, Núñez,

Chittka & Menzel 1995). White flowers were, however the most conspicuous to bees, so bee preference for UV does not seem to be related with conspicuousness. When comparing which colors were most conspicuous to each pollinator, pattern did not follow the one described in pollination syndromes Therefore, our second hypothesis is not corroborated.

When comparing between species, D. melanogaster (housefly) was consistently the animal model with highest chromatic contrast, and therefore would better detect flowers. Fly color vision

70 is still not well studied and understood, and only a few species were tested in regard to color vision

(Lunau 2014). Hoverflies seem to have a categorical visual system being able to discriminate colors between categories, but not within categories (Troje 1993). There is, however, criticism to this model due to insufficient research (White, Dalrymple, Herberstein & Kemp 2017). For instance, D. melanogaster, the species we chose to use in our models, has been shown to detect colors within the same category (Brembs & de Ibarra 2006). The visual ecology of flies is still a growing topic (Lunau 2014) and hence chromatic contrast might not be the most appropriate tool to be used. Females Butterflies had a higher chromatic contrast than males, which is expected, because males are trichromats. Despite being tetrachromat, hummingbirds had an intermediate color vision between flies and female butterflies, and bees and male butterflies, which are trichromats. This could be due to the model parameters used to compare between pollinators, as small changes in parameters can cause big changes in JND (Olsson, Lind, & Kelber, 2018). It is often stated that the evolution of flower color is shaped by pollinator preference exercised by bees

(Dyer et al 2012). Yet we found that bees had the poorest color vision among all flower visitors modelled. Bees only use color vision to detect flower at close range, using the achromatic channels at a distance (Giufa, Vorobyev, Kevan & Menzel 1996), so there is little need for a higher color contrast at a distance. General background materials cluster in the perceptual space of bees and are all achromatic, appearing gray to bees (Chittka, Shmida, Troje & Menzel 1994). That facilitates the detection of color targets independent on the chromatic contrast.

Regarding pollination syndromes; fly flowers were best seen by flies, but flies saw all other flowers better as well. Psychophily flowers were best seen by female butterflies, but not by males.

Bird flowers (Ornithophylous) were more conspicuous for hummingbirds, but a larger sample size is required for evaluating this hypothesis statistically. Bee flowers were less conspicuous for bees,

71 as the general pattern was for bees to have lowest chromatic contrast. Color conspicuousness also followed the general trend of tetrachromats having a higher contrast than trichromats. Since both divisions by pollination syndromes and by color followed the general pattern of flies having higher chromatic contrast followed by female butterflies, hummingbird, male butterflies and bees; we do not consider the hypothesis that pollinators would detect flowers of their respective syndrome better than other pollinators or that pollinators would detect colors related to their syndrome better than other pollinators corroborated.

In this study, we did not find any empirical evidence that sustains pollination syndromes.

Colors in pollination syndromes could be explained by other mechanisms, such as innate preference. Yet pollinators can easily associate color and reward, overcoming their initial biases

(Giufa, Núñez, Chittka & Menzel 1995, Weiss 1997). Innate preferences may also be adapted to local flora (Raine & Chittka 2007). Therefore, it is difficult for innate color preferences to play a key role in pollination syndromes. Reverté, Retana, Gómez & Bosch (2016) found that, despite pollinator’s preference for flowers of certain colors, flower color does not dictate pollinator assembly. Other works has shown no association between colors and pollination syndromes

(Kuniyasu et al 1998, Hernández-Yáñez, Lara-Rodríguez, Díaz-Castelazo, Dáttilo, Rico-Gray

2013).

Despite pollination syndromes importance in pollination studies, they might not be an accurate way to group flowers (Ollerton et al 2009). And overall, our results show that plants seem to be generalist when signaling for pollinators and pollinators can easily detect most flowers, corroborating that generalization is the rule and not the exception in pollination systems (Waser,

Chittka, Prince, Williams & Ollerton 1996, Hernández-Yáñez, Lara-Rodríguez, Díaz-Castelazo,

Dáttilo, Rico-Gray 2013, Reverté, Retana, Gómez & Bosch 2016). In order to maintain flower

72 constancy, flowers are under pressure to diverge in color (Waser 1986, Schaefer, Schaefer & Levey

2004). That could explain the limited number of existing pollinator groups, and a much greater diversity of flower colors and morphologies (Heinrich 1975), divergence seems to be the prevailing strategy. Furthermore, pollinator abundancy also varies across time, so pollination networks are opportunistic rather than pre-determined by plant morphology (Alarcón, Waser &

Ollerton 2008), so maintaining ambiguous characteristics would assure attraction of secondary pollinators.

4.6. Conclusion

Flowers were not more conspicuous to their pollinators and more conspicuous flower colors were not the ones prescribed by pollination syndromes. Tetrachromat pollinators detected flowers better than trichromat pollinators. Accordingly, the question of why pollination syndromes are associated with flower colors remains. Contrast is only one method for analyzing color; and it is possible that other elements such as hue or brightness also play a key role in determining pollinator’s preference for colors. An analysis with a larger sample could further help determine how conspicuousness plays a role in flower-pollinator interactions.

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4.8. Supplementary Material

Table S1. List of species used, locations found, and which backgrounds were used for the visual modeling.

Family Species Biome Background Acanthaceae Ruellia asperula (Mart. ex Nees) Lindau Thorn Forest Leaf Harpochilus paraibanus F.K.S. Monteiro, Inflorescenc J.I.M. Melo & E.M.P. Fernando Thorn Forest e Amaranthaceae Alternanthera tenella Colla Thorn Forest Leaf Alternanthera brasiliana L. Thorn Forest Leaf Atlantic Forrest Anacardiaceae Anacardium occidentale L. (Restinga) Leaf Atlantic Forrest Annonaceae Guatteria schomburgkiana Mart. (Restinga) Leaf Atlantic Mandevilla moricandiana (A.DC.) Forrest Apocynaceae Woodson (Restinga) Leaf Atlantic Forrest Hancornia speciosa Gomes (Restinga) Leaf Asteraceae Blainvillea dichotoma (Murray) Stewart Thorn Forest Leaf Bignoniaceae Handroanthus impetiginosus Thorn Forest Tree trunk Fridericia dichotoma (Jacq.) L.G.Lohma Thorn Forest Leaf Boraginaceae Varronia leucocephala (Moric.) J.S.Mill. Thorn Forest Leaf Varronia globosa Jacq. Thorn Forest Leaf Atlantic Gymnosiphon divaricatus (Benth.) Benth. Forrest Burmanniaceae & Hook.f. (Restinga) Leaf litter Commiphora leptophloeos (Mart.) J.B. Burseraceae Gillett Thorn Forest Leaf Tacinga inamoena (K.Schum.) N.P.Taylor Cactaceae & Stuppy Thorn Forest Leaf litter Atlantic Forrest Inflorescenc Melocactus violaceus Pfeiff. (Restinga) e Atlantic Forrest Celastraceae Maytenus erythroxyla (Reissek) Biral (Restinga) Leaf

Atlantic Chrysobalanacea Hirtella racemosa (Willd. ex Roem. & Forrest e Schult.) Prance (Restinga) Leaf Atlantic Forrest Hirtella ciliata Mart. & Zucc. (Restinga) Leaf Commelinaceae Commelina erecta L. Thorn Forest Leaf Convolvulaceae Jacquemontia pentanthos (Jacq.) G.Don Thorn Forest Leaf Ipomoea bahiensis Willd. ex Roem. & Schult. Thorn Forest Leaf Cucurbitaceae Cayaponia tayuya (Vell.) Cogn. Thorn Forest Leaf Ceratosanthes palmata (L.) Urb. Thorn Forest Rock Atlantic Forrest Cyperaceae Rhynchospora cephalotes Ness (Restinga) Leaf Erythroxylaceae Erythroxylum pungens O.E.Schulz Thorn Forest Leaf Atlantic Forrest Erythroxylum rimosum O.E.Schulz (Restinga) Leaf Euphorbiaceae Croton sp. Thorn Forest Leaf Croton hirtus L'Hér. Thorn Forest Leaf Ditaxis desertorum (Müll.Arg.) Pax & K.Hoffm. Thorn Forest Leaf Dalechampia sp. Thorn Forest Leaf Jatropha mollissima (Pohl) Baill. Thorn Forest Leaf Sebastiania sp. Thorn Forest Leaf Fabaceae Indigofera sp. Thorn Forest Leaf Canavalia brasiliensis Mart. ex Benth. Thorn Forest Leaf Trischidium molle (Benth.) H.E.Ireland Thorn Forest Leaf Atlantic Chamaecrista ramosa (Vogel) H.S.Irwin & Forrest Barneby (Restinga) Leaf Atlantic Forrest Periandra mediterranea (Vell.) Taub. (Restinga) Leaf Atlantic Forrest Stylosanthes guianensis (Aubl.) Sw. (Restinga) Leaf Atlantic Forrest Desmodium barbatum (L.) Benth. (Restinga) Leaf Atlantic Forrest Stylosanthes capitata Vogel (Restinga) Leaf

Atlantic Forrest Gentianaceae Voyria sp. (Forrest) Leaf litter Atlantic Forrest Voyria aphylla (Jacq.) Pers. (Restinga) Leaf litter Atlantic Forrest Schultesia sp. (Restinga) Leaf litter Atlantic Forrest Heliconiaceae Heliconia psittacorum L.f. (Forrest) Leaf Atlantic Forrest Krameriaceae Krameria tomentosa A.St.-Hil. (Restinga) Leaf Lamiaceae Mesosphaerum suaveolens (L.) Kuntze Thorn Forest Leaf Atlantic Forrest Eplingiella fruticosa (Salzm. Ex Benth) (Restinga) Leaf Atlantic Forrest Lauraceae Cassytha filiformis L. (Restinga) Tree trunk Atlantic Forrest Leguminosae Zornia diphylla (L.) Pers. (Restinga) Leaf litter Atlantic Forrest Lentibulariaceae Utricularia sp. (Restinga) Sand Loasaceae Mentzelia aspera L. Thorn Forest Sand Atlantic Forrest Loranthaceae Struthanthus syringifolius Mart. (Restinga) Leaf Atlantic Forrest Psittacanthus dichroos (Mart.) Mart. (Restinga) Leaf Atlantic Forrest Lythraceae Cuphea flava Spreng. (Restinga) Leaf Atlantic Forrest Malpighiaceae Stigmaphyllon paralias A.Juss. (Restinga) Leaf Atlantic Forrest Byrsonima crassifolia (L.) Kunth (Restinga) Leaf

Atlantic Forrest Byrsonima gardneriana A. Juss (Restinga) Leaf Malvaceae Waltheria rotundifolia Schrank Thorn Forest Leaf Herissantia crispa (L.) Brizicky Thorn Forest Leaf Sida galheirensis Ulbr. Thorn Forest Leaf Herissantia tiubae (K.Schum.) Brizicky Thorn Forest Leaf Pavonia cancellata (L.) Cav. Thorn Forest Sand Corchorus argutus Kunth Thorn Forest Leaf Melochia sp. Thorn Forest Leaf Atlantic Forrest Melastomataceae Comolia villosa (Aubl.) Triana (Restinga) Leaf Atlantic Forrest Miconia albicans (Sw.) Triana (Restinga) Leaf Atlantic Forrest Nyctaginaceae Guapira sp. (Restinga) Leaf Atlantic Forrest Ochnaceae Sauvagesia sprengelii A.St.-Hil. (Restinga) Sand Atlantic Forrest Ouratea hexasperma (A.St.-Hil.) Baill. (Restinga) Leaf Atlantic Forrest Orchidaceae Epidendrum cinnabarinum Salzm. (Restinga) Leaf Atlantic Forrest Vanilla bahiana Hoehne (Restinga) Green Petals Atlantic Forrest Peraceae Chaetocarpus echinocarpus (Baill.) Ducke (Restinga) Leaf Atlantic Forrest Polygalaceae Polygala longicaulis Kunth (Restinga) Sand Atlantic Asemeia violacea (Aubl.) J.F.B.Pastore & Forrest J.R.Abbott (Restinga) Leaf Atlantic Forrest Polygonaceae Coccoloba ramosissima Wedd. (Restinga) Leaf Portulacaceae Portulaca oleracea L. Thorn Forest Leaf

Richardia grandiflora (Cham. & Schltdl.) Rubiaceae Steud. Thorn Forest Leaf Atlantic Forrest Psychotria bracteocardia (DC.) Müll.Arg. (Forrest) Leaf Atlantic Forrest Psychotria sp. (Restinga) Leaf Atlantic Staelia virgata (Link ex Roem. & Schult.) Forrest K.Schum. (Restinga) Sand Atlantic Forrest Perama hirsuta Aubl. (Restinga) Sand Atlantic Forrest Salzmannia nitida DC. (Restinga) Leaf Atlantic Cordiera myrciifolia (K.Schum.) Forrest C.H.Perss. & Delprete (Both) Leaf Sapindaceae Cardiospermum corindum L. Thorn Forest Leaf Allophylus sp. Thorn Forest Leaf Talinaceae Talinum triangulare Willd. Thorn Forest Leaf Turneraceae Turnera subulata Sm. Thorn Forest Leaf Turnera cearensis Urb. Thorn Forest Leaf Verbenaceae Lantana camara L. Thorn Forest Leaf Atlantic Forrest Lantana radula Sw. (Restinga) Leaf Lippia alba (Mill.) N.E.Br. ex P. Wilson Thorn Forest Leaf Atlantic Forrest Xyridaceae Xyris sp. (Restinga) Sand

Table S2. Description of flower color categories, proposed by Wilmer (2011), and the number of flowers sampled in our study.

Color Number of flowers sampled category Description Without UV With UV Total Red Pure bright red 0 0 0 Mauve Dark muted red 2 1 3 Pink Very light red 0 1 1 Bright yellow tinged red or bright red tinged Orange yellow 1 3 4 Yellow Pure bright yellow 6 10 16 Cream Very light yellow 12 1 13 Low contrast between green leaves and Green flowers 1 1 2 Greenish Yellow with a small tinge of blue 8 2 10 Pale green Low saturated green 1 0 1 Blue Bright or pale blue 4 0 4 Purple A mixture between pink and blue 9 2 11 White Not tinted by other colors 10 3 13 Off-white, white with a small tinge of any Dull white other color 15 2 17 Dull beige Muted brownish cream 0 0 0 Dull Light and unsaturated any color 0 0 0 Brown Dark, unsaturated orange or red 1 0 1 Mottled Irregular patches 0 0 0

Figure S1 Compared reflectance of flowers measured with Ocean Optics RPH-1 probe holder and our custom-made 3D printed probe holder. a) Petal of Delonix regia b) Petal of Catharanthus roseus c) Petal of Plumeria pudica.

Figure S2. Illuminant of Caatinga (a) and Restinga (b) used in visual modeling.

5. CONCLUSÃO GERAL

Conclusão geral

Embora os estudos de coloração floral têm crescido ao longo das décadas, ainda existem várias lacunas a serem preenchidas. Estudos que levam em consideração a visão de cores de diferentes animais precisam ser realizados, especialmente animais que podem ser prejudiciais as flores (herbívoros, florívoros, ladrões de néctar e pólen). Além disso existe uma escassez de estudos que avaliam padrões biogeográficos, sendo a maioria realizados na Europa. São necessários mais estudos que utilizam a história evolutiva para quantificar vias bioquímicas que podem levar a mudança de coloração em flores, seja ao longo da história evolutiva ou ao longo do tempo de vida de indivíduos. No geral, coloração floral é uma área que ainda tem muito a ser explorado.

Síndromes de polinização tem sido uma ferramenta importante nos estudos de coloração floral, porém, falta bases empíricas que expliquem o porquê certas características estão associadas com certos polinizadores. Quando comparando qual coloração é mais conspícua para diferentes polinizadores os padrões que encontramos não seguem os descritos por síndromes de polinização.

Além disso, polinizadores não detectam melhor flores de sua própria síndrome quando comparado com flores de outras síndromes. Quando comparando polinizadores, flores são mais conspícuas para polinizadores tetracromatas do que para polinizadores tricromatas. flores não são mais conspícuas para polinizadores previstos por síndromes, e a coloração das flores não determinou qual animal a detectava melhor. Mais estudos são necessários para entender por que polinizadores tendem a visitar flores de certas colorações.

6.0 APÊNDICES

MINISTÉRIO DA EDUCAÇÃO COMISSÃO DE ÉTICA NO USO DE ANIMAIS – CEUA Av. Salgado Filho, S/N – CEP: 59072-970 – Natal / RN Fone: (84) 9229-6491 / e-mail: [email protected]

CERTIFICADO

Natal (RN), 24 de abril de 2018.

Certificamos que a proposta intitulada “Comparação da coloração floral entre a caatinga e a mata atlântica”, protocolo 009/2018, CERTIFICADO nº 089.009/2018 , sob a responsabilidade de Daniel Marques de Almeida Pessoa - que envolve a produção, manutenção e/ou utilização de animais pertencentes ao filo Chordata, subfilo Vertebrata (exceto o homem), para fins de pesquisa científica (ou ensino) - encontra-se de acordo com os preceitos da Lei n.º 11.794, de 8 de outubro de 2008, do Decreto n.º 6.899, de 15 de julho de 2009, e com as normas editadas pelo Conselho Nacional de Controle da Experimentação Animal (CONCEA), foi aprovada, após adequações, pela COMISSÃO DE ÉTICA NO USO DE ANIMAIS da Universidade Federal do Rio Grande do Norte – CEUA/UFRN.

Vigência do Projeto Maio 2019 RELATÓRIO JUNHO 2019 Espécie/Linhagem - Não haverá coletada ou manipulação de animais durante a pesquisa. Todas as informações que serão utilizadas na Número de Animais modelagem referentes a animais serão retiradas da literatura. Apenas espécies vegetais serão coeltadas. Idade/Peso - Sexo - Coleta das espécies Floresta Nacional de Assu – RN e Reserva Biológica Guaribas - PB vegetais

Informamos ainda que, segundo o Cap. 2, Art. 13, do Regimento Interno desta CEUA, é função do professor/pesquisador responsável pelo projeto a elaboração de relatório de acompanhamento que deverá ser entregue tão logo a pesquisa seja concluída. O descumprimento desta norma poderá inviabilizar a submissão de projetos futuros.

José de Castro Souza Neto Júnior Coordenador da CEUA-UFRN