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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
________________________________________________________
Prof. Dr. Leonardo M. Versieux
Universidade Federal do Rio Grande do Norte
________________________________________________________
Prof. Dr. Daniel Marques de Almeida Pessoa (orientador)
Universidade Federal do Rio Grande do Norte
________________________________________________________
Natal, 27 de maio de 2019.
i
“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.
ii
Dedico esta dissertação a Ricardo Andreazze, sua
luz continua a me guiar pelos momentos mais
escuros.
iii
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
iv
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.
v
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.
vi
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
vii
Supplementary material 4. Illuminant of Caatinga and Restinga used in visual
modeling.....................................................................................................................................p. 85
viii
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
ix
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
10
1.INTRODUÇÃO
11
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,
12
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.
13
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
14
2. OBJETIVOS, HIPÓTESES E PREDIÇÕES
__________________________________________________________
15
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.
16
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.
17
3. ARTIGO 1
Painting the Roses Red: Temporal-spatial Patterns and the Evolution of
Flower Coloration
18
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
19
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).
0
1000
2000
3000
4000
5000
6000
7000
8000
1970-1979 1980-1989 1990-1999 2000-2009 2010-2019
Nu
mb
er o
f re
cord
s in
Web
of
Scie
nce
Dat
abas
e
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
21
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).
24
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.
26
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.
29
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 &
31
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).
33
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
34
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).
36
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.
40
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?
41
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51
4. ARTIGO 2
Pollination syndromes do not predict flower conspicuousness by different
pollinators
52
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.
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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
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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).
55
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
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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 category Description Includes
Number of flowers sampled
UV- UV+ Total
Red Pure red, unsaturated red, dark red, and
red with tints of yellow red, mauve,
orange, brown 4 4 8
Yellow Pure yellow, light yellow and muted
yellow cream, yellow, dull
beige 18 11 29
Green All greens, yellow with tints of blue, and
blues with tints of yellow green, greenish,
pale green 10 3 13 Blue pure blue and blues tinged red blue, pink, purple 13 3 16
white true white, off-whites and light grays white, dull white,
dull 25 5 30 Mottled irregular patches Mottled 0 0 0
59
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.
Animal model
Popular name
Photoreceptors’ peak 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
M Butterfly
390, 470, 555 nm2 S: 1; M: 1.5; L: 7.72 0.059 Drosophila
melanogaster House fly
345, 375, 437, 508 nm3 UV: 1; S: 2; M: 1; L: 2 6 0.1010 Sephanoides sephanoides
Humming 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.
62
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.
Modeled Spcies Color
∆S < 1 JND 1 JND < ∆S < 3 JND 3 JND < ∆S
Blue 3 13
Green 7 6
Yellow 6 23
Red 2 2 4
White 4 26
Blue 16
Green 1 12
Yellow 29
Red 3 3
White 30
Blue 16
Green 1 12
Yellow 29
Red 1 7
White 1 29
Blue 2 14
Green 4 9
Yellow 2 27
Red 1 7
White 3 27
Blue 16
Green 5 8
Yellow 2 27
Red 1 7
White 3 27S. sephanoides
Discriminability
A. mellifera
D. melanogaster
H. erato
H. erato
63
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.
65
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).
66
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).
67
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).
68
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.
73
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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,
J.I.M. Melo & E.M.P. Fernando Thorn Forest
Inflorescenc
e
Amaranthaceae Alternanthera tenella Colla Thorn Forest Leaf
Alternanthera brasiliana L. Thorn Forest Leaf
Anacardiaceae Anacardium occidentale L.
Atlantic
Forrest
(Restinga) Leaf
Annonaceae Guatteria schomburgkiana Mart.
Atlantic
Forrest
(Restinga) Leaf
Apocynaceae
Mandevilla moricandiana (A.DC.)
Woodson
Atlantic
Forrest
(Restinga) Leaf
Hancornia speciosa Gomes
Atlantic
Forrest
(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
Burmanniaceae
Gymnosiphon divaricatus (Benth.) Benth.
& Hook.f.
Atlantic
Forrest
(Restinga) Leaf litter
Burseraceae
Commiphora leptophloeos (Mart.) J.B.
Gillett Thorn Forest Leaf
Cactaceae
Tacinga inamoena (K.Schum.) N.P.Taylor
& Stuppy Thorn Forest Leaf litter
Melocactus violaceus Pfeiff.
Atlantic
Forrest
(Restinga)
Inflorescenc
e
Celastraceae Maytenus erythroxyla (Reissek) Biral
Atlantic
Forrest
(Restinga) Leaf
79
Chrysobalanacea
e
Hirtella racemosa (Willd. ex Roem. &
Schult.) Prance
Atlantic
Forrest
(Restinga) Leaf
Hirtella ciliata Mart. & Zucc.
Atlantic
Forrest
(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
Cyperaceae Rhynchospora cephalotes Ness
Atlantic
Forrest
(Restinga) Leaf
Erythroxylaceae Erythroxylum pungens O.E.Schulz Thorn Forest Leaf
Erythroxylum rimosum O.E.Schulz
Atlantic
Forrest
(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
Chamaecrista ramosa (Vogel) H.S.Irwin &
Barneby
Atlantic
Forrest
(Restinga) Leaf
Periandra mediterranea (Vell.) Taub.
Atlantic
Forrest
(Restinga) Leaf
Stylosanthes guianensis (Aubl.) Sw.
Atlantic
Forrest
(Restinga) Leaf
Desmodium barbatum (L.) Benth.
Atlantic
Forrest
(Restinga) Leaf
Stylosanthes capitata Vogel
Atlantic
Forrest
(Restinga) Leaf
80
Gentianaceae Voyria sp.
Atlantic
Forrest
(Forrest) Leaf litter
Voyria aphylla (Jacq.) Pers.
Atlantic
Forrest
(Restinga) Leaf litter
Schultesia sp.
Atlantic
Forrest
(Restinga) Leaf litter
Heliconiaceae Heliconia psittacorum L.f.
Atlantic
Forrest
(Forrest) Leaf
Krameriaceae Krameria tomentosa A.St.-Hil.
Atlantic
Forrest
(Restinga) Leaf
Lamiaceae Mesosphaerum suaveolens (L.) Kuntze Thorn Forest Leaf
Eplingiella fruticosa (Salzm. Ex Benth)
Atlantic
Forrest
(Restinga) Leaf
Lauraceae Cassytha filiformis L.
Atlantic
Forrest
(Restinga) Tree trunk
Leguminosae Zornia diphylla (L.) Pers.
Atlantic
Forrest
(Restinga) Leaf litter
Lentibulariaceae Utricularia sp.
Atlantic
Forrest
(Restinga) Sand
Loasaceae Mentzelia aspera L. Thorn Forest Sand
Loranthaceae Struthanthus syringifolius Mart.
Atlantic
Forrest
(Restinga) Leaf
Psittacanthus dichroos (Mart.) Mart.
Atlantic
Forrest
(Restinga) Leaf
Lythraceae Cuphea flava Spreng.
Atlantic
Forrest
(Restinga) Leaf
Malpighiaceae Stigmaphyllon paralias A.Juss.
Atlantic
Forrest
(Restinga) Leaf
Byrsonima crassifolia (L.) Kunth
Atlantic
Forrest
(Restinga) Leaf
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Byrsonima gardneriana A. Juss
Atlantic
Forrest
(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
Melastomataceae Comolia villosa (Aubl.) Triana
Atlantic
Forrest
(Restinga) Leaf
Miconia albicans (Sw.) Triana
Atlantic
Forrest
(Restinga) Leaf
Nyctaginaceae Guapira sp.
Atlantic
Forrest
(Restinga) Leaf
Ochnaceae Sauvagesia sprengelii A.St.-Hil.
Atlantic
Forrest
(Restinga) Sand
Ouratea hexasperma (A.St.-Hil.) Baill.
Atlantic
Forrest
(Restinga) Leaf
Orchidaceae Epidendrum cinnabarinum Salzm.
Atlantic
Forrest
(Restinga) Leaf
Vanilla bahiana Hoehne
Atlantic
Forrest
(Restinga) Green Petals
Peraceae Chaetocarpus echinocarpus (Baill.) Ducke
Atlantic
Forrest
(Restinga) Leaf
Polygalaceae Polygala longicaulis Kunth
Atlantic
Forrest
(Restinga) Sand
Asemeia violacea (Aubl.) J.F.B.Pastore &
J.R.Abbott
Atlantic
Forrest
(Restinga) Leaf
Polygonaceae Coccoloba ramosissima Wedd.
Atlantic
Forrest
(Restinga) Leaf
Portulacaceae Portulaca oleracea L. Thorn Forest Leaf
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Rubiaceae
Richardia grandiflora (Cham. & Schltdl.)
Steud. Thorn Forest Leaf
Psychotria bracteocardia (DC.) Müll.Arg.
Atlantic
Forrest
(Forrest) Leaf
Psychotria sp.
Atlantic
Forrest
(Restinga) Leaf
Staelia virgata (Link ex Roem. & Schult.)
K.Schum.
Atlantic
Forrest
(Restinga) Sand
Perama hirsuta Aubl.
Atlantic
Forrest
(Restinga) Sand
Salzmannia nitida DC.
Atlantic
Forrest
(Restinga) Leaf
Cordiera myrciifolia (K.Schum.)
C.H.Perss. & Delprete
Atlantic
Forrest
(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
Lantana radula Sw.
Atlantic
Forrest
(Restinga) Leaf
Lippia alba (Mill.) N.E.Br. ex P. Wilson Thorn Forest Leaf
Xyridaceae Xyris sp.
Atlantic
Forrest
(Restinga) Sand
83
Table S2. Description of flower color categories, proposed by Wilmer (2011), and the number of
flowers sampled in our study.
Color category Description
Number of flowers sampled
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
Orange Bright yellow tinged red or bright red tinged
yellow 1 3 4 Yellow Pure bright yellow 6 10 16 Cream Very light yellow 12 1 13
Green Low contrast between green leaves and
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
Dull white Off-white, white with a small tinge of any
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
84
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.
85
5. CONCLUSÃO GERAL
86
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.
87
6.0 APÊNDICES
MINISTÉRIO DA EDUCAÇÃO COMISSÃO DE ÉTICA NO USO DE ANIMAIS – CEUA
Av. Salgado Filho, S/N – CEP: 59072-970 – Natal / RNFone: (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 -
Número de Animais
Não haverá coletada ou manipulação de animais durante a pesquisa. Todas as informações que serão utilizadas na modelagem referentes a animais serão retiradas da literatura. Apenas espécies vegetais serão coeltadas.
Idade/Peso -
Sexo -
Coleta das espécies vegetais
Floresta Nacional de Assu – RN e Reserva Biológica Guaribas - PB
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 JúniorCoordenador da CEUA-UFRN
www.ceua.propesq.ufrn.br
