INTERACTIONS, PERSISTENCE ANDCOEXISTENCE MECHANISMS OFNECTARIVOROUS BATS AND THE PLANTS THEYFEED ON, IN A SEASONALLY DRY TROPICALFOREST IN NORTHEASTERN BRAZILEugenia Cordero SchmidtOrientador: Dr. Eduardo Martins VenticinqueCo-orientador: Dr. Bernal Rodríguez Herrera

INTERAÇÕES, MECANISMOS DE PERSISTÊNCIA E COEXISTÊNCIA DE

MORCEGOS NECTARÍVOROS E DAS PLANTAS DAS QUAIS SE

ALIMENTAM EM UMA FLORESTA TROPICAL SAZONAL SECA NO

NORDESTE BRASILEIRO

INTERACTIONS, PERSISTENCE AND COEXISTENCE MECHANISMS OF

NECTARIVOROUS BATS AND THE PLANTS THEY FEED ON, IN A

SEASONALLY DRY TROPICAL FOREST IN NORTHEASTERN BRAZIL

Eugenia Cordero Schmidt

Orientador: Dr. Eduardo Martins Venticinque

Universidade Federal do Rio Grande do Norte

Coorientador: Dr. Bernal Rodríguez Herrera

Universidad de Costa Rica

Tese apresentada ao Programa de Pós

Graduação em Ecologia da Universidade

Federal do Rio Grande do Norte, como parte do

requerimento para obtenção do título de Doutora

em Ecologia.

Natal, Março 2020

3

Schmidt, Eugenia de Jesus Cordero. Interações, mecanismos de persistência e coexistência demorcegos nectarívoros e das plantas das quais se alimentam emuma floresta tropical sazonal seca no Nordeste brasileiro /Eugenia de Jesus Cordero Schmidt. - Natal, 2020. 160 f.: il.

Tese (Doutorado ) - Universidade Federal do Rio Grande doNorte. Centro de Biociências. Programa de Pós-graduação emEcologia. Orientador: Prof. Dr. Eduardo Martins Venticinque. Coorientador: Prof. Dr. Bernal Rodríguez Herrera.

1. Caatinga - Tese. 2. Chiroptera - Tese. 3. Dieta - Tese. 4.Fenologia - Tese. 5. Pólen - Tese. 6. Reprodução - Tese. I.Venticinque, Eduardo Martins. II. Herrera, Bernal Rodríguez.III. Universidade Federal do Rio Grande do Norte. IV. Título.

RN/UF/BSCB CDU 574

Universidade Federal do Rio Grande do Norte - UFRNSistema de Bibliotecas - SISBI

Catalogação de Publicação na Fonte. UFRN - Biblioteca Setorial Prof. Leopoldo Nelson - -Centro de Biociências - CB

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

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AGRADECIMENTOS

Que fase doida, incrível, intensa, pesada e leve. Muito aprendizado, autoconhecimento e muito pra agradecer!

Juank, mi persona favorita! Comenzamos esto juntos y lo terminamos juntos. GRACIAS por tu amor, compañía, comida, cuidados (en los varios problemas aleatorios que me han pasado) y por tu increíble paciencia. GRACIAS por tu fuerte trabajo en campo, las manejadas, las carreras, las embarcadas, por tu compañerismo y por tus fotos INCREIBLES (95% das fotos desta tese foram tiradas por ele!). ¡GRACIAS por equilibrarme y por hacerme reír todos los días! ¡GRACIAS POR EXISTIR!

Familia, ma, pa, Gaby y todos mis hermanos y sobrinos perros. ¡GRACIAS por el apoyo IN-CON-DI-CIO-NAL! GRACIAS por todos los viajes, cenas, cajitas sorpresas por correo… Que bárbaros, sin ustedes y sus miles de ayudas emocionales, espirituales y económicas no hubiera logrado esto. ¡Me hace muy feliz saber que están orgullosos de mi! GRACIAS tíos, primos y abuelitos, me han hecho mucha falta, pero nunca he dejado de sentirlos cerca.

GRACIAS a mis queridos amigos ticos biologeos, Sol, Marce, Cristin (¡MIL GRACIAS SIEMPRE por tu disponibilidad y ayuda para revisar mis cosas!), Jose, Moritzio, Jenny, Kathe, Maggie, Elena y Adri (¡¡da Silva!! Te volviste brasileña! Gracias por el cariño!). A mis queridos termitas peruanas Adri, Bala y Bompe, los extraño muchísimo!

OBRIGADA Bernal e Dadão. Formamos uma equipe de trabalho muito forte e completa, baseada em amizade e carinho. Obrigada por todos esses muitooos anos de trabalho juntos, aprendi muito com vocês e agradeço sua paciência! Bernal, muchas gracias por abrirme la puerta hacia Brasil, donde fui tan bien recibida por Dadāo, los quiero mucho! Ragde e Marina, por associações acadêmicas e conjugais, acabei fazendo duas grandes amigas! Ragde, sos um ser de luz! Marina, mulherão cheia de criatividade e força (vou sentir falta das nossas conversas pós-reunião!!).

OBRIGADA amigos da alma e irmãos brasileiros! Marin (aprendi muito de você, obrigada pela amizade pura), Caro (gracias por las comiditas, risaditas e por ser um exemplo de força!), vocês são mis hermanas favoritas! Pocas (MULHERÃO incrível! Exemplo de pessoa!) Dante (mi amigo, chegou pra nos

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alegrar a vida mais ainda!), Caramujo (figuraaaaaaaaa! Valeu pelas risadas!), Ricard (tua paz e transparência são muito legais!), Dardo (que falta hacés!!!!!!!!!), Isa (queridaaaaaaaaa você é uma pessoa MUITO legal e única, saudade!!), Juanpi, Tamara, Dri, Guiga, JB, Gustav, Helder, Carol, Dukin saudades dos churrascos e risadas com vocês! OBRIGADA a todos os cachorros que me ajudaram com minha carência e saúde mental, Tucumā obrigada por ter me proporcionado tanta felicidade, Pretis (você é incrível!), Lampião, Judith, Paçoca, Malú e Nina.

OBRIGADA Vermiculitas, vocês viraram elementos fundamentais da minha vida! Obrigada pelas risadas SEMPRE, pelos conselhos e momentos de “lua na sinceridade”. Obrigada pelas constantes manifestações de afeto disfarçadas de bullying (saibam que meu nível de português é intermediário por causa de vocês). Helo obrigada por tua leveza!!!! Estar com você sempre me recarrega com energias positivas e isso é muito difícil de achar! Eli, minha querida leonina, campeã do bullying, professora de yoga, artista, a minha amiga mais descolada... vou sentir falta de te-incomodar e rir com você! Julia, sempre vou te agradecer por ter trazido a Tucumā na minha vida! Você é uma das pessoas mais confiáveis que conheço, corazón peludo pero no mucho! Tenho muito carinho e admiração por todas vocês!

“Lab” 2020 OBRIGADA pelas risadas e conselhos! Foi muito bom compartilhar com vocês os sofrimentos e conquistas!!! OBRIGADA Palito pela força sempre, pelos vários campos juntos com conversas super legais, por me transmitir uma paixão fortíssima pela Caatinga. Você é um pesquisador exemplar e dedicado, te admiro muito! Você vai longe e com certeza vai levar a Caatinga junto! OBRIGADA Virginita pela tua energia sempre legal e leve! Obrigada pelas ajudas em campo, você fez com que essa última fase de coleta em campo fosse muito mais legal e engraçada, obrigada pelas conversas, conselhos e parceria, você é uma pessoa muito especial! Fer, obrigada pelos dados de precipitação, pelas palhaçadas e pelas imitações incrivelmente semelhantes à realidade haha. Continua com essa perseverança e dedicação, você vai longe! Ellen, te conheci pouco, mas o que sei é que você é uma mulher muito forte e perseverante, vai que vai!

OBRIGADA ao Programa de Pós-graduação em Ecologia da UFRN. Agradeço a todos os professores que se tornaram grandes amigos: Carlinhos, Gis, Márcio, Liana, Serginho, Ádrian e Marília (que não foi muito minha professora, mas sim uma amiga muito querida! Vou sentir falta das tretas nas jogatinas!).

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OBRIGADA ao Laboratório de Investigação de Matrizes Vegetais Energéticas (LIMVE), a Elaine, ao pessoal do Herbário da UFRN. Obrigada ao Laboratório de Micromorfologia Vegetal - LAMIV UEFS, MUITO obrigada Francisco, Paulino, Vivi, Luis, Camila (rainha das Acanthaceae todas!) vocês são proffesionais de primeira e muito queridos!

OBRIGADA aos morcególogos queridos, grandes pesquisadores e pessoas: Enrico, muito obrigada pelo apoio e confiança sempre. Você foi fundamental na nossa caminhada com morcegos no nordeste brasileiro! Eder, Marília, Marianita, Julia, Marlon, Messi, Patrício, Valeria foi sempre um prazer compartilhar e trocar ideias com vocês nos congressos, reuniões e suas respetivas festas!

OBRIGADA meus fiéis companheiros ao longo de este processo todo: Deus, música, praia, meditação, exercício, café e demais plantas que alimentaram meu corpo e espírito!

OBRIGADA Caatinga. Ela foi a minha principal educadora neste enorme processo de aprendizado. Ela me ensinou a ser humilde e respeitosa. Me mostrou paisagens deslumbrantes e imagens duras e inesquecíveis. Me permitiu estudar parte da sua riqueza e me apresentou o povo mais forte, resiliente e generoso que já conheci! OBRIGADA Seu João (meu pai no mato, forte, sorridente e conhecedor!), Darquinha (obrigada pela tua amizade e comidas incríveis), Jusara (<3), Pedrinho (ajuda firme e conversas no mato), dona Das Dores (e seus cafés milagrosos), seu Lorival (e seus abraços e sorrisos apaziguadores), obrigada por me deixarem ser parte da sua família, vocês são incríveis! OBRIGADA dona Creusa, seu Cícero, Laysa e Irene, obrigada por sempre ter um lugar pra nos acolher, comida deliciosa e conversas gostosas!! OBRIGADA a todos nossos companheiros, guias e amigos de campo: Juninho (ainda estou impressionada com tua força!), Edinho (teu sorriso, tua energia positiva e tranquilidade são admiráveis), Valtenci (tuas risadas e histórias sempre surpreendentes! E tua família acolhedora e querida!), Iatagan (outro pai! Obrigada pelo cuidado, conselhos, bolachas, goiabada com açúcar, água gelada, risadas, e por compartilhar sempre teu conhecimento interminável!), Veio, Titico, Mario, Geilson e Geison.

OBRIGADA aos funcionários das Unidades de Conservação que nos acolheram e facilitaram nosso trabalho: Lucia (uma mulher forte, centrada, e muito querida!!!), Rielson (e sua agradável família!), e Leonardo do Parque Nacional Furna Feia; Mauro dos Anjos gestor da FLONA de Açu; George e

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Geraldo da ESEC do Seridó. Diego Bento (grande parceria!) do Centro de Pesquisa e Conservação de Cavidades (CECAV).

Um agradecimento especial a uma pessoa que se tornou fundamental na reta final do doutorado, Fabiana Lopes (a querida Bia!). Obrigada pela grande confiança depositada em mim e pelo apoio, forca e paciência. Vamos fazer grandes coisas juntas!

OBRIGADA morcegos!! Animais fascinantes, incríveis e interessantíssimos! Obrigada por me permitir invadir sua vida, sua casa e sua privacidade! Amo vocês! Obrigada as mais de 600 pessoas que participaram nas oficinas de educação ambiental com morcegos, obrigada pelo interesse em conhece-los um pouquinho melhor!

A ciência definitivamente não é gasto, é investimento!

O presente trabalho foi realizado com apoio da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Código de Financiamento 001; também com o apoio fundamental do CNPq (Pesquisador Visitante Especial-PVE - Projeto de Ecologia e Conservação de Morcegos na Caatinga Potiguar: 401467 / 2014-7), The Rufford Small Grants Foundation, e finalmente obrigada Wildlife Conservation Society Brasil pelo apoio na logística de campo.

“Se nada ficar destas páginas, algo, pelo menos, esperamos que permaneça: nossa confiança no povo. Nossa fé nos homens e na criação de um mundo em

que seja menos difícil amar”- Paulo Freire.

1 2 3 4

GENERAL

10 About this doctorate

11 What we found

12 General introduction

Chapter I. SHEDDING LIGHT ON NECTARIVOROUS BAT – PLANT NETWORKS:

INTERACTIONS FROM CAATINGA REVEALS HIGHLY GENERALIZED

ASSOCIATIONS AND TEMPORAL STABILITY

19 Abstract

21 Introduction

23 Methods

29 Results

30 Discussion

35 References

47 Figures and tables

52 Supporting information

Chapter II. MECHANISMS MEDIATING NECTAR-FEEDING BATS COEXISTENCE AND

PERSISTENCE THROUGH THE SEASONAL RHYTHM OF CAATINGA

64 Abstract

66 Introduction

69 Methods

76 Results

82 Discussion

93 References

105 Figures and tables

115 Supporting information

Chapter III. FEMALE REPRODUCTION PATTERNS IN CAATINGA ARE INFLUENCED

BY PRECIPITATION AND CACTACEAE RESOURCE AVAILABILITY

120 Abstract

122 Introduction

125 Methods

129 Results

134 Discussion

139 References

146 Figures and tables

151 Supporting information

SUMMARY

158 What we learned about nectar-feeding bats in Caatinga

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5

Coletamos os dados principalmente no município de Lajes, no estado do Rio Grande do Norte, mas para representar melhor a heterogeneidade da Caatinga desse pouco explorado estado, incluímos outros seis municípios (amostrados em menor escala). Coletamos dados em sete tipos diferentes de habitat: 1) Carnaubais, 2) Enclaves de floresta úmida, 3) Caatinga média, 4) Pomares, 5) Caatinga ripária, 6) Afloramentos rochosos e 7) Caatinga arbustiva.

Em diferentes períodos entre maio de 2015 e fevereiro de 2019, cobrindo a sazonalidade tão característica da Caatinga.

Usamos redes de neblina para capturar os morcegos nectarívoros. Anotamos: a hora de captura, espécie, sexo, medidas eco-morfológicas (peso, antebraço, focinho e asas). Coletamos dois tipos de amostras: fezes e pólen de seus pelos (com cubos de gelatina glicerinada). Para caracterizar a dieta das espécies: identificamos os tipos de pólen e itens alimentares complementares ao néctar. Também coletamos dados fenológicos de floração de nove espécies de árvores, arbustos e cactos para saber quais recursos estavam disponíveis para os morcegos e quando.

Nos aprofundamos na vida de quatro espécies de morcegos nectarívoros: Glossophaga soricina (Phyllostomidae: Glossophaginae), Lonchophylla inexpectata, Lonchophylla mordax e Xeronycteris vieirai (Phyllostomidae: Lonchophyllinae). Descrevemos suas redes de interações com plantas (capítulo 1), exploramos seus mecanismos de persistência e coexistência ao longo do tempo e estações do ano (capítulo 2) e, finalmente, descrevemos os padrões de reprodução dos morcegos nectarívoros (capítulo 3).

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Anoura geoffroyi, G. soricina, Linexpectata, L. mordax e X. vieirai interagiram com 31 espécies de plantas. A rede mostrou um padrão altamente generalizado de interações, consistente ao longo das estações e anos. Os morcegos apresentaram alta sobreposição nas interações, o que contribuiu para a generalização ecológica (baixa especialização e modularidade) e padrão não aninhado. Os padrões de interação generalizados podem ser uma condição necessária para a persistência de morcegos nectarívoros e de suas plantas especializadas em ambientes variáveis como a Caatinga.

Glossophaga soricina, L. inexpectata, L. mordax e X. vieirai coexistem e persistem ao longo do tempo (anos e estações) mediados por uma mistura de mecanismos: 1) Particionamento temporal (diferenças nas capturas ao longo da noite). 2) Diferenças eco-morfológicas (peso, antebraço, focinho e proporções das asas). 3) Particionamento de recursos (flexibilidade da dieta consumindo pelo menos 20 espécies de plantas além de pólen, insetos e tecidos vegetais). A persistência temporal dos morcegos foi facilitada pela continuidade e complementaridade dos recursos florais disponíveis ao longo do ano. No entanto, as Cactaceae são um recurso fundamental na Caatinga, espécies de cactos foram usadas em alta frequência por todos os morcegos.

Dois padrões reprodutivos foram observados para as espécies de morcegos nectarívoros na Caatinga, padrão bimodal em G. soricina e aparentemente em L. inexpectata (poucos dados reprodutivos) e multimodal em L. mordax e X. vieirai. A precipitação afetou positivamente a probabilidade de ocorrência de gravidez em L. mordax e X. vieirai. Nenhuma das variáveis testadas influencia a gravidez de G. soricina. A disponibilidade de recursos florais de Cactaceae do mês anterior, afetaram positivamente a probabilidade de ocorrência de lactação para todos os morcegos nectarívoros, com algumas diferenças para determinadas espécies de cactos.

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7 GENERAL INTRODUCTION 8

Seasonally dry tropical forest (SDTF) are considered a harsh environment 9

due to their high temperature, scarce and variable rainfall that cause seasonal 10

restrictions on the availability of water and food resources (Dirzo et al., 2011). 11

SDTFs are distribuited in disjunct patches throughout the world. They vary greatly 12

physiognomically influenced by local climate, soil and topography (Pennington et 13

al., 2009) which has hampered the overall definition of SDTFs and the 14

delimitation of the biomes and ecosystems within them. In Neotropics the majority 15

of SDTFs occurs in South America with the largest and most continuous 16

fragments in Bolivia and Brazil (Sánchez-Azofeifa and Portillo-Quintero, 2011). 17

Animals and plants that occur in SDTFs developed adaptations to deal 18

with these conditions. For example, most of the plants are facultative or obligatory 19

deciduous species. Thorny species are abundant and their flowering and fruiting 20

phenologies are markedly seasonal with a shorter growing period (Murphy and 21

Lugo, 1986; Pennington et al., 2000). In the case of mammals, several 22

mechanisms about how they cope with and survive in SDTFs were synthesized 23

by Stoner and Timm (2011). Broadly, they divided the mechanisms in 24

physiological (changes in body temperature, seasonal torpor or hibernation, 25

water conservation, and delayed reproduction), and behavioral adaptations 26

(dietary flexibility, long and short distance migrations, activity patterns, 27

seasonality of reproduction). 28

It has been proven that bats can occupy arid and semiarid forests mainly 29

due to long distance migrations strategies and short distance habitat shifts 30

(Fleming et al., 2003), diet flexibility (Heithaus et al., 1975; Soriano et al., 1991; 31

Tschapka et al., 2008) and presenting a close relationships with keystone plants 32

which are regular resources, such as cactus and agaves (Sosa and Soriano 33

1996; Valiente-Banuet et al., 1996, 1997, Stoner et al., 2003). 34

Nectar-feeding bats are found frequently in dry areas and are the main 35

agents of pollination for hundreds of plant species, some of which are completely 36

13

dependent on them for reproduction (Bolzan et al., 2015). They are known to 37

pollinate over 528 species of plants worldwide (Kunz et al., 2011) and are 38

responsible for the pollination of 13.1% of the plants present in a Caatinga region 39

(Machado and Lopes, 2004). This percetage is considered a high when 40

compared to other ecosystems ( 3% in Cerrado and humid forests Silberbauer-41

Gottsberger and Gottsberger,1988; Bawa et al., 1985). 42

Caatinga is the largest continuous SDTF area in northeastern Brazil, with 43

around 800,000 km2, covering 11% of the country (Silva et al., 2018). It is a 44

mosaic of vegetation types, ranging from habitats with non-thorny arboreal 45

habitats to xeric habitats, where thorny shrubs, cactus and bromeliads 46

predominate (Andrade-Lima, 1981). Caatinga is the most populated semiarid 47

region in the world, harboring over 28.6 million people (Silva et al., 2018). 48

Unfortunately, Caatinga experience gradual but persistent degradation 49

processes (Ribeiro et al., 2015). Caatinga harbors a high diversity and endemism 50

in both flora and fauna with outstanding adaptations to the extreme abiotic 51

conditions (Coe and de Sousa, 2014; Ribeiro et al., 2015). It is home to about 52

5000 species of angiosperms, 300 of which are endemic (Giulietti et al., 2004) 53

and 153 species of mammals with ten endemic species (Paglia et al., 2012; 54

Gutierrez and Marinho-Filho, 2017). More than a half of the mammalian diversity 55

in the Caatinga is represented by bats, a total of 90 species (59% of all mammals 56

occurring in the Caatinga) have been recorded of which nine are known to be 57

nectar-feeding bats (belonging to Glossophaginae and Lonchophyllinae 58

subfamilies) (Carvalho-Neto et al., 2016; Gutierrez and Marinho-Filho, 2017). 59

In this thesis I seek to understand the ecology of the ensemble of 60

nectarivorous bats and their persistence, coexistence and reproduction patterns 61

in the northeastern part of Caatinga, at the Rio Grande do Norte (RN) state. In 62

the first chapter I describe how the network of interactions between nectarivorous 63

bats and the plants they feed on is structured and evaluate its temporal dynamics 64

across seasons. In the second chapter, I test for three possible coexistence 65

mechanisms for the nectar-feeding bats: 1) Temporal partitioning 2) 66

Ecomorphological differences and 3) Resource partitioning in a Caatinga 67

fragment in the municipality of Lajes. In the third chapter, I described the female 68

reproductive patterns of nectar-feeding bats and inspect the effects of 69

precipitation and Cactaceae resource availability. 70

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Stoner, K. E., Karla, A. S., Roxana, C. F., & Quesada, M. (2003). 139 Population dynamics, reproduction, and diet of the lesser long-nosed bat 140 (Leptonycteris curasoae) in Jalisco, Mexico: implications for conservation. 141 Biodiversity & Conservation, 12(2), 357-373. 142

Stoner, K. E., & Timm, R. M. (2004). Tropical dry-forest mammals of Palo 143 Verde: Ecology and conservation in a changing landscape. University of 144 California Press, Berkeley. 145

Sosa, M., & Soriano, P. J. (1993). Solapamiento de dieta entre 146 Leptonycteris curasoae. Rev. Biol. Trop, 41(3), 529-532. 147

Stoner, K. E., & Timm, R. M. (2011). Seasonally dry tropical forest 148 mammals: Adaptations and seasonal patterns. In Seasonally Dry Tropical 149 Forests (pp. 85-106). Island Press, Washington, DC. 150

Tschapka, M., Sperr, E. B., Caballero-Martínez, L. A., & Medellín, R. A. 151 (2008). Diet and cranial morphology of Musonycteris harrisoni, a highly 152 specialized nectar-feeding bat in western Mexico. Journal of Mammalogy, 89(4), 153 924-932. 154

van Schaik, C. P., Terborgh, J. W., & Wright, S. J. (1993). The phenology 155 of tropical forests: adaptive significance and consequences for primary 156 consumers. Annual Review of ecology and Systematics, 24(1), 353-377 157

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Valiente-Banuet, A., Arizmendi, M. D. C., Rojas-Martínez, A., & 158 Domínguez-Canseco, L. (1996). Ecological relationships between columnar cacti 159 and nectar-feeding bats in Mexico. Journal of Tropical Ecology, 12(1), 103-119. 160

Valiente-Banuet, A., Rojas-Martínez, A., Arizmendi, M. D. C., & Dávila, P. 161 (1997). Pollination biology of two columnar cacti (Neobuxbaumia mezcalaensis 162 and Neobuxbaumia macrocephala) in the Tehuacan Valley, central 163 Mexico. American Journal of Botany, 84(4), 452-455. 164 165 166

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168 169

Shedding light on nectarivorous bat-plant networks: interactions from 170

Caatinga reveals highly generalized associations and temporal stability 171

172

Eugenia Cordero-Schmidt1, Pietro Kiyoshi Maruyama2, Juan Carlos Vargas-173 Mena1, Paulino Pereira Oliveira3, Francisco de Assis R. Santos3, Rodrigo A. 174 Medellín4, Bernal Rodriguez-Herrera5 and Eduardo M. Venticinque1 175 176 177 1Departamento de Ecologia, Universidade Federal do Rio Grande do Norte, 178 59078900 Lagoa Nova Natal, RN, Brazil; E-mail: ecordero.s@gmail.com 179 2 Centro de Síntese Ecológica e Conservação, Departamento de Genética, 180 Ecologia e Evolução - ICB, Universidade Federal de Minas Gerais, Belo 181 Horizonte, MG, Brazil. 182 3 Laboratório de Micromorfologia Vegetal, Universidade Estadual de Feira de 183 Santana, 44036-900, Novo Horizonte, BA, Brazil 184 4 Instituto de Ecología, Universidad Nacional Autónoma de México, 70-275, 185 04510 México D. F., México 186 5 Escuela de Biología, Universidad de Costa Rica, 2060 Montes de Oca, San 187 José, Costa Rica 188 189

19

ABSTRACT 190

Seasonally Dry Tropical Forests have low and variable precipitation regimes 191 causing a seasonal pattern in the supply of feeding resources, controlling species 192 composition and plant–animal interactions. Vertebrates, especially nectarivorous 193 bats are important pollinators in STDFs and other tropical ecosystems, including 194 the Brazilian Caatinga. Nevertheless, community-level interaction network 195 studies considering nectarivorous bats are scarce in the literature, which hinders 196 a more comprehensive understanding of plant-pollinator interactions. Here, we 197 describe a nectarivorous bat-plant interaction network from the Caatinga and 198 evaluated its temporal dynamics across seasons and years, considering the 199 highly variable environmental conditions in this ecosystem. To do so, we mist-200 netted nectarivorous bats from 2015 to 2019, sampled pollen loads on their 201 bodies and built a pollen transportation network between bats and plants. Five 202 species of nectar-feeding bats interacted with 31 plant species. This network 203 showed a highly generalized pattern of interactions, which was consistent across 204 repeated seasons and years. Most commonly sampled nectarivorous bat species 205 showed high levels of interaction overlap, which contributed to ecological 206 generalization (low specialization and modularity) and lack of nestedness. 207 Specialized chiropterophilous plants and plants that do not show specialized bat 208 pollination traits were equally important components of the interaction network. 209 The ecologically and phenotypically generalized interaction patterns found may 210 be a necessary condition for the persistence of nectarivorous bats and their 211 specialized plants in the environmentally harsh and variable environments of 212 Caatinga. Studying neglected groups of pollinators and their interaction networks 213 may shed new insights into our general understating of plant-pollinator 214 relationships, and more studies considering bats and other nocturnal pollinators 215 need to be conducted. Specifically, the underappreciated generalization on 216 interaction with plants call for studies testing for the effectiveness of bats in 217 pollinating specialized and non-specialized plants they visit. 218 219 220 Key words: Chiropterophily; Pollen transport; Pollination; Pollination syndrome; 221

Seasonal Dry Tropical Forest; Temporal variation 222

223

20

GRAPHICAL ABSTRACT 224

21

INTRODUCTION 225

Many vertebrates are key pollinators, especially birds and bats (Fleming & 226

Muchhala 2008; Ratto et al. 2018). Recently, the field of pollination ecology has 227

greatly benefited from the use of interaction network approaches when 228

characterizing plant and pollinator interactions at the community level (Knight et 229

al. 2018). Despite many advances that the interaction networks theory and 230

methods brought, the literature in plant-pollination networks has shortcomings, 231

for instance, neglecting some functional group of pollinators from tropical regions 232

(Vizentin-Bugoni et al. 2018). Bats are involved in frugivory and nectarivory 233

interactions with plants throughout the Neotropics (Mello et al. 2019). However, 234

bat-plant pollination interactions have been poorly explored, especially when 235

compared to birds which have been more frequently studied using the network 236

approach (Zanata et al. 2017). Bat-flower interactions at the community scale are 237

largely absent in the network literature (Vizentin-Bugoni et al. 2018). To our 238

knowledge, only two recent studies have evaluated Old-World nectarivorous bats 239

and their interaction networks (Stewart & Dudash 2017; Sritongchuay, Hughes & 240

Bumrungsri, 2019). However, Old-World (Pteropodidae) and New-World 241

nectarivorous bats (Phyllostomidae) have different evolutionary histories, even 242

though they show many convergent traits and ecological similarities (Fleming, 243

Geiselman & Kress, 2009). 244

Conversely, bat pollination has evolved independently many times in 245

different lineages of tropical and subtropical plants (Fleming, Geiselman & Kress, 246

2009), and includes hundreds of ecological and economically important plant 247

species (Kunz, Braun de Torrez, Bauer, Lobova & Fleming., 2011). Nectar-248

feeding bats are typically associated with large robust flowers or inflorescences, 249

22

with light-colored flowers with long and numerous stamens, copious amounts of 250

nectar, large quantities of pollen, and sometimes producing unpleasant odors that 251

attract nectarivorous bats (Tschapka & Dressler, 2002). This set of floral traits 252

characterizes the pollination syndrome of chiropterophily (Fægri & van der Pijl 253

1979), and specialized bat-pollinated plants seem to be especially dependent on 254

their pollinators for sexual reproduction (Ratto et al. 2018). 255

Considering the importance of bats as pollinators in the Tropics, and 256

especially in some ecosystems, studies on nectarivorous bat-plant networks 257

could bring new insights for the understanding of plant-pollinator interactions. 258

Seasonally Dry Tropical Forests (SDTF) are endangered ecosystems (Janzen 259

1988) with a remarkable diversity of lifeforms and functional groups of both flora 260

and fauna (Dirzo, Young, Mooney & Ceballos, 2011). Low and variable rainfall 261

patterns in SDTFs means that in most cases plant-related resources are found in 262

temporal pulses (Chesson et al. 2004). This seasonal pattern of resource 263

availability seems to be a key factor controlling species composition and therefore 264

influencing niche dynamics and coexistence patterns of consumer populations 265

(Kneitel & Chase, 2004). Despite this irregularity, plants from STDFs present high 266

levels of dependence on biotic vectors for their pollination and seed dispersal 267

(Quesada et al. 2009; Leal, Lopes, Machado & Tabarelli, 2017), indicating a tight 268

plant-animal relationship controlling ecosystem dynamics. 269

Caatinga is the largest SDTF ecosystem in South America with over 800 270

000 km2 located in northeastern Brazil, which harbors a rich biota with high level 271

of endemism (Silva, Leal & Tabarelli, 2018). Here, the proportion of bat-pollinated 272

plants in communities are outstandingly high, representing 11-13.1% of the flora; 273

which is much higher than in other tropical plant communities (Machado & Lopes, 274

23

2004; Quirino & Machado, 2014). Caatinga is home to 9 nectar-feeding bat 275

species including two endemic species (Moratelli & Dias, 2015; Carvalho-Neto et 276

al. 2017), but information about their interactions with plants is scarce (Cordero-277

Schmidt et al. 2017; Silva, Neves, Guedes, Almeida & Brasil-Sato, 2019). 278

In this study, we describe community-level nectarivorous bat-plant 279

interaction networks from the Neotropics and evaluate its dynamics across time 280

in two scales: (1) seasons and (2) years. Because of marked seasonality, plant–281

animal interactions in SDTFs are probably much more sensitive to phenological 282

patterns, including potential changes in the structure of interactions networks 283

(Souza et al. 2018). Although studies evaluating temporal dynamics in pollination 284

networks are not very common, previous studies with bat (Sritongchuay et al. 285

2019) and multi-taxa pollination networks (Souza et al. 2018) from seasonal 286

tropical areas have shown that interaction networks are more specialized in the 287

dry season when floral resources are less abundant. Hence, we also expected 288

variation according to seasons in bat-plant networks from Caatinga, with higher 289

specialization in the dry season. In contrast, pollination networks may show 290

surprisingly similar structural properties from year to year (Alarcón et al. 2008), 291

and we expected our networks to also maintain the same general structural 292

patterns across the years. Finally, considering the high number of 293

chiropterophilous plants in Caatinga (Machado & Lopes 2004), we expected that 294

bats would rely on their diet primarily on the species of plants with 295

chiropterophilous syndrome characteristics (Fleming et al. 2009). 296

297

METHODS 298

Study site 299

24

We conducted the study in the state of Rio Grande do Norte, Brazil, with sampling 300

mostly conducted in the municipality of Lajes, and also in six other municipalities: 301

Cerro Corá, Assu, Felipe Guerra, Baraúna, Martins and Serra Negra do Norte 302

(Supporting Information Figure S1). We spread our samples across these 303

different municipalities to encompass the heterogeneity of Caatinga vegetation, 304

composed of seven habitat types (Supporting Information Table S1, Figure S2): 305

Riparian (7 sampling sites), Shrubby Caatinga (7), Medium Caatinga (6), Rocky 306

outcrops (3), Copernicia groves (2), Humid forest enclave (1), and Orchards (1). 307

For surveyed sites we recorded general environmental characteristics and noted 308

the dominant plant species to classify them into habitat types described by Mares, 309

Willig, Streilein & Lacher (1981) and Prado (2003) (Supporting Information Figure 310

S2 and Table S3). 311

The climate type in the region is semi-arid (Köppen’s BSh), with the wet 312

season lasting approximately six months from January to June and the dry 313

season from July to December (following Oliveira, Silva & Lima, 2017, Northern 314

semiarid subregion). We collected data during two periods, between May and 315

October 2015, and between May 2017 and June 2019. 316

Nectar-feeding bat captures 317

We sampled bats for 151 nights, placing 80 m to 120 m of mist nets per night 318

over six hours from sunset to midnight. All mist nets were placed at ground level 319

and along preexisting trails and near flowering plants or known/ suspected roosts. 320

The total netting effort was 310.8925 m2h (Straube & Bianconi, 2002). We 321

identified the species in the field using systematic keys and species diagnosis 322

(Díaz, Solari, Aguirre, Aguiar & Barquez, 2016). All bats were released after data 323

collection except for the individuals that were impossible to identify in the field or 324

25

that represented a new report for the area, which were deposited in the Adalberto 325

Varela Mammalogy Collection (CMAV) of the Universidade do Rio Grande do 326

Norte. All procedures for capture, handling and collection of bats met the 327

guidelines of the American Society of Mammalogists for the use of wild mammals 328

in research (Sikes et al., 2016), and the legal Brazilian requirements of 329

conservation and animal welfare. Fieldwork was authorized by 330

MMA/ICMBio/SISBIO under permits 48325-2. To recognize recaptured 331

individuals during the same sampling period, bats were marked by cutting a small 332

portion of fur (1 cm) from the lower back of each individual with a curved 333

dissecting scissor. 334

Pollen collection and identification 335

We collected pollen samples from each captured bat’s fur, wings, legs and 336

uropatagium using a single glycerin jelly cube (3-4 mm) per individual, which was 337

later mounted on glass microscope slides. Jelly were prepared with glycerin and 338

phenol for preservation and safranin for staining (Voigt, Kelm, Bradley & 339

Ortmann, 2009). To avoid cross-contamination from one sample to another, 340

special care was taken by cleaning the worktable, hands and tweezers with 341

alcohol after finishing the handling of each bat. Besides, the cloth bags in which 342

the bats were held after capture were always clean and never reused until they 343

were washed. 344

We identified pollen under a light microscope (magnification 400-1000x, 345

Leica DM500) to the lowest possible taxonomic level through comparison with 346

reference collections. To identify the pollen types, we used a collection 347

specialized on the pollen of the Caatinga vegetation from the Palynotheca of the 348

LAMIV, UEFS (Plant Micromorphology Laboratory, Universidade Estadual de 349

26

Feira de Santana), and a reference collection that we made from local plants in 350

bloom during our fieldwork. We also used pollen catalogs for additional reference 351

(Palacios-Chávez, Ludlow-Wiechers & Villanueva, 1991; Roubik & Moreno 1991; 352

Santos, Watanabe & Hamburgo-Alves, 1997; Carreira & Barth 2003; Melhem et 353

al. 2003; Silva, Santos & Lima, 2016). 354

We scored the presence/absence of each pollen type on individual bats 355

and used the number of times each pollen type was found in a specific bat 356

species as a measure of interaction frequency (Sazatornil et al. 2016). To 357

minimize the effects of possible contaminations, i.e., pollen grains placed in the 358

flowers by other pollinators before the visit of the bats, we established a minimum 359

number of pollen grains according to size categories (following Heithaus, Fleming 360

& Opler, 1975). In the present study, we established three criteria based on pollen 361

size and count (Supporting Information Table S4). 362

We then gathered information from the literature for the following plant and 363

floral traits to characterize the floral biology and pollination syndromes of plants 364

sampled: Flowering season, flower opening (day, night or crepuscular), blossom 365

class (according Fægri & van der Pijl, 1971), corolla color, flower size, flower size 366

categories (according to Machado & Lopes, 2004), and pollen size (according to 367

Erdtman, 1952) (Supporting Information Table S5). 368

Network analyses 369

We built networks for seasons (dry - July to December, wet - January to June), 370

years of sampling (2015, 2017, 2018, each year from June to October) and only 371

for the municipality of Lajes. We calculated four network metrics that characterize 372

distinct aspects of the interaction patterns. We calculated (1) connectance, the 373

ratio of observed and possible links in the network, which is an estimate of how 374

27

interactions are constrained within the community (Jordano, 1987); (2) 375

complementary specialization (H2') that measures how species restrict their 376

interactions from those randomly expected based on the availability of partners 377

(Blüthgen et al. 2006); (3) nestedness using NODF index (Almeida-Neto, 378

Guimaraes, Guimaraes, Loyola & Ulrich, 2008), which quantifies how interactions 379

of specialized species are subsets of the interactions of the more generalist 380

species in the networks; (4) modularity (Q) using the DIRTLPA+ algorithm 381

(Beckett 2016), which quantifies the tendency of species forming subgroups of 382

interacting species. Due to the stochastic nature of the optimization algorithm, we 383

repeated the analysis 30 times and kept the highest Q value as the optimal 384

solution (Beckett, 2016). To assess the significance of these network-level 385

metrics, we contrasted the observed values to those generated by null models. 386

For NODF, we used the r1 model from the vegan package, which uses the 387

column (bats) marginal frequencies as probabilities to distribute the presence of 388

interactions (Oksanen et al. 2019). For quantitative indices, including H2' and Q, 389

we used the r2dtable model from the bipartite package (Dormann et al. 2008) that 390

constrains the marginal totals and network size. We considered a metric 391

significant by assessing whether the observed value was greater than 95% of the 392

simulated values from the null models (p<0.05). 393

We also calculated three species-level indices from the interaction 394

network: (1) plant degree, which is the number of bat species each plant species 395

interacted with; (2) species strength, quantified as the sum of the proportions of 396

interactions performed by a given species across all its interacting partners, 397

measuring the extent to which bat species depend on a specific plant species 398

(Bascompte, Jordano & Olesen, 2006); (3) species-level specialization d', which 399

28

quantifies how interaction frequencies of a given species deviate concerning the 400

availability of interaction partners in the network, defined by their marginal totals 401

(Blüthgen, Menzel & Blüthgen, 2006). Calculations of all network-related indices 402

were conducted with the bipartite package version 2.13 (Dormann, Gruber & 403

Fruend, 2008). We used these indices to contrast plants showing characteristics 404

in accordance with chiropterophily syndrome, to those showing characteristics 405

associated with other pollination syndromes, e.g., diurnal flower opening. We 406

used the three species level indices as response variables in three distinct 407

Generalized Linear Models (GLMs) for each index, with a categorical predictor 408

assigning plant species as chiropterophilous or not. We assumed a Poisson 409

distribution of data for the GLM with degree, and Gaussian distribution for GLMs 410

with species strength and specialization (Zuur et al. 2009). We only used the 411

pollen types that were identified to species level in this analysis. To attain 412

significance values for each model, we used the function Anova in car package 413

version 3.0-4 (Fox and Weisberg, 2011). 414

Finally, we also estimated the sampling completeness of the networks 415

(Chacoff et al. 2012; Vizentin-Bugoni et al. 2016). We took each combination of 416

a bat and plant species as an equivalent of ‘species’ and the frequency of each 417

pairwise interaction as their ‘abundances’, and then calculated the ratio between 418

observed and estimated interaction diversity (Vizentin-Bugoni et al. 2016). We 419

used the Chao 1 estimator from the iNEXT package to estimate the richness of 420

pairwise interactions from the observed data (Hsieh, Ma & Chao, 2014). All 421

analysis was conducted in R, version 3.6.1 (R Core Team, 2019). 422

423

RESULTS 424

29

Nectar-feeding bats 425

Five species of nectar-feeding bats were captured (Figure 1), with a total of 650 426

captures (Supporting Information Table S6). Glossophaga soricina was the most 427

abundant (n= 252) and found in most localities (L=6) and Habitat Types (HT=6) 428

during both seasons, followed by Lonchophylla mordax (n= 173 L=5, HT=4). The 429

two species that had the lowest occurrence were Xeronycteris vieirai (n= 134, 430

L=1, HT= 2) and Lonchophylla inexpectata (n= 103, L=1, HT=2); while Anoura 431

geoffroyi was the least abundant (n= 6, L=2, HT=2) during both seasons. 432

Bat-plant interactions 433

We collected a total of 608 glycerin jelly samples, from which 121 did not contain 434

any pollen grain. From the remaining 487 samples, 54% belonged to the dry 435

season and 46% to the rainy season (A. geoffroyi n= 5; G. soricina n=178; L. 436

mordax n= 137; L. inexpectata n= 76; X. vieirai n=91). A total of 31 pollen types 437

(Figure 2) were recorded in the bats from 19 genera and 14 plant families (Figure 438

3). In average, we recorded 2.56 ± 1.70 pollen types (min. = 1, max. = 10), per 439

sample. Cactaceae (eight pollen types) was the most frequent plant family, 440

followed by Acanthaceae and Fabaceae (four each). We were unable to identify 441

three pollen types; however, they were only rarely recorded (1.6% of samples). 442

Three additional pollen types were identified only up to the family level (Fabaceae 443

type, Sapindaceae type and Malpighiaceae type), and two pollen types up to the 444

genus level (Pseudobombax type, and Ipomoea type). 445

The interaction network comprised of 1250 interactions between bat and 446

plant species (pollen types). The overall network showed a highly generalized 447

interaction pattern, with a high value of connectance, and low but significant 448

values of specialization and modularity. Thus, although there is a non-random 449

30

pattern on how interactions are organized, there is very little partitioning of 450

interactions between species. Moreover, because most bats are equally 451

generalist, we did not find significant nestedness in the network (Table 1). The 452

two seasonal networks comprised a slightly smaller number of plant species (26 453

in the dry and 27 in the rainy season), indicating some but not strong seasonality 454

in flowering species richness. These networks showed similar structure to the 455

overall network, and no strong variation between the seasons (Table 1). 456

Moreover, there was no strong variation among the distinct years of sampling, 457

and the network considering only the most sampled locality, Lajes, showed a 458

similar pattern as the overall network (Table 1). 459

When comparing chiropterophilous plants to other plants used by bats, 460

there was no difference in any of the three species level indices (Figure 4). 461

Finally, we found that our networks were all reasonably well sampled, with 462

sampling completeness from 65% to 87% (Table 1). 463

464

DISCUSSION 465

The nectarivorous bat-plant network from Caatinga showed a highly generalized 466

pattern of interactions, which was consistent across the seasons and years. Most 467

commonly sampled nectarivorous bat species showed high levels of interaction 468

overlap, which contributed to ecological generalization (low specialization and 469

modularity) and lack of significant nestedness. Some plant species that do not 470

show characteristics in accordance with chiropterophily syndrome were equally 471

important in the interaction network to those that were more specialized. This 472

implies bats may also be generalists regarding floral traits of the plants they 473

31

interact with, characterizing these pollinators as phenotypic and functional 474

generalists (Ollerton, Killick, Lamborn, Watts & Whiston, 2007; Armbruster 2017). 475

Generalization in pollination interactions is regarded as conferring 476

resilience to both plants and pollinators to fluctuation on their respective 477

resources (Waser et al. 1996). Flowering phenology in Caatinga is highly 478

variable, dependent on somewhat unpredictable rainfall (Machado & Barros, 479

1997), hence generalization may be favored. Within bats, generalist species may 480

opportunistically switch their diet temporarily according to availability of mass 481

flowering plants, in contrast to more specialist ones that remain loyal to plants 482

with longer flowering periods (Stewart & Dudash 2018). When considering the 483

five most important plants for each nectar-feeding bat (>10% of samples with 484

pollen type), we found all bats interacting with plants showing distinct flowering 485

phenologies, i.e. both plants with continuous and short flowering pulses. So, 486

nectarivorous bats were all similarly generalized and do not seem to show 487

differences in feeding strategy regarding plant phenologies. 488

Differences in rostrum and tongue size have been linked to differences in 489

nectar extraction efficiency among bat species, but this does not necessarily lead 490

to floral niche partitioning (Gonzalez-Terrazas et al. 2012). Although there may 491

be some exceptions with extreme morphological specialists (Muchhala & 492

Thomson, 2009), long rostrum/tongue in bats may have evolved so that species 493

get efficient access to the broadest range of the local flower resources in the 494

community (Gonzalez-Terrazas et al. 2012). In our bat community, X. vieirai has 495

the longest (11.9 ± 0.7 mm) and G. soricina the shortest snout (7.3 ± 0.6 mm), 496

but both species show high interaction overlap (Fig. 1). Morphological matching 497

can be an important mechanism generating niche partitioning and resource 498

32

specialization in ecological networks (Vázquez et al. 2009, Sonne et al. 2020). 499

While nectar acquisition trade-offs lead to the partitioning of interactions among 500

species in plant-hummingbird (Maruyama et al. 2014, Maglianesi et al. 2015), 501

and -hawkmoth networks (Sazatornil et al. 2016), this might not the case in 502

nectarivorous bats. Nevertheless, detailed studies on eco-morphology between 503

pollinators and plants in the Caatinga are still missing and are of great interest as 504

it may show distinct mechanisms structuring their interactions according to 505

pollination systems. 506

Our study adds many new records of interactions between bats and 507

flowers for Caatinga (Bredt et al. 2012; Cordero-Schmidt et al. 2017; Silva et al. 508

2019). Most of the new plant records and around 30% of the plants in the pollen 509

transport network overall present floral traits associated typically to bird and bee 510

pollination (van der Pijl, 1961). These non-chiropterophilous plants were similarly 511

important in the network as were plants showing characteristics in accordance 512

with chiropterophily syndrome, a trend also described previously for plant-513

hummingbird interactions networks in Caatinga (Las-Casas et al. 2012) and the 514

neighboring Cerrado’s savanna ecosystem (Maruyama et al. 2013). Interestingly, 515

such generalization may ensure the persistence of pollinator populations in 516

climatically less stable environments (Waser et al. 1996). 517

Moreover, such seldom-appreciated opportunistic use of generalist 518

flowers by bats may provide the opportunity for new evolutionary paths in some 519

groups of plants. Many closely related plant species are pollinated by bats and 520

birds, and some even have both as pollinators with distinct contribution to plant 521

reproduction (Sazima et al. 1994; Muchhala, 2007). Additionally, the transition 522

from bird to bat pollination seems the most common evolutionary pathways in 523

33

distinct groups (Tripp & Manos, 2008, Abrahamczyk, Souto-Vilarós, Renner 524

2014). In this sense, that some of the sampled non-chiropterophilous plants are 525

commonly used by bats, such as M. zehntneri (ornithophily) which comprised 526

22.8% of the samples in total, emphasizes the ability of bats to include plants in 527

their diet opportunistically. Species of Melocactus have short diurnal anthesis, 528

with flowers lasting only some hours until the end of the day (Romão, Hughes, 529

Vieira & Fontes, 2007; Locatelli & Machado, 1999). For bats to use the 530

nectar/pollen resources of these plants, visits to flowers must occur right after 531

they start foraging (17:30-18:30). Melocactus flowers are abundant year-round in 532

Caatinga, associated with distinct floral visitors such as birds, lizards and insects 533

(Taylor, 1991; Leal, Lopes & Machado, 2006), and now we also include bats in 534

this list. The opportunistic use of plants we recorded suggest that studies focusing 535

on the floral biology of diurnal flowers may find “surprises” by potentially including 536

crepuscular and nocturnal observation, as these may uncover novel and 537

unexpected interactions. Because the methodology we used does not allow us to 538

characterize effective pollination, experiments and observations on visitation 539

rates are necessary to better understand the role of nectar-feeding bats in the 540

reproduction and evolutionary paths of the non-chiropterophilous plants. 541

Cactaceae, is often regarded as closely linked to New World bats, and 542

two species, Pilosocereus pachycladus and P. gounellei with specialized bat 543

flowers and relatively extended flowering phenology (E. Cordero-Schmidt pers. 544

obs.) were important component of the network. Species in the family are well 545

adapted to arid and semiarid environments, and its predictability in providing 546

resources contribute to the persistence of fauna (Anderson, 2001). Many cacti 547

species from STDFs in the New World depend heavily on pollination by one or 548

34

more species of Phyllostomid bats (Valiente-Banuet, Arizmendi, Rojas-Martínez 549

& Domínguez-Canesco, 1996; Nassar, Beck, Sternberg & Fleming, 2003), and 550

the same pattern seems to occur in the Brazilian Caatinga. Some species of bats 551

are even defined as obligate cactophilic species (Fleming & Valiente-Banuet 552

2002). The overlapping geographic range between some nectar-feeding bats and 553

cactus-rich environments is an important aspect indicating the importance of this 554

interaction (Simmons and Wetterer, 2002). One of our bat species, Xeronycteris 555

vieirai, has recently been classified as endemic to the dry diagonal crossing the 556

central portion of Brazil, including Caatinga and Cerrado (Dias & Oliveira, 2019), 557

and was also the species that most frequently interacted with Cactaceae species 558

in both dry and rainy seasons, suggesting it is potentially a cactophilic species. 559

In conclusion, the observed generalized and temporarily stable interaction 560

patterns indicated that bat-plant interactions may be somewhat robust to current 561

human-driven disturbance impacting Caatinga (González-Varo et al. 2013, Silva, 562

Leal & Tabarelli, 2017). However, our studied interactions also include some 563

endemic species (X. vieirai and L. inexpectata), which may be more threatened. 564

Considering the relative scarcity of bat-flower networks and the importance of 565

bats as pollinators for native and crop plants (Ratto et al. 2018, Sheherezade et 566

al. 2019; Tremlett et al. 2019) we urge that more networks studies be conducted 567

with bat pollination, so that insights on the mechanisms structuring this and other 568

pollination interactions may be uncovered. As reported here, there is still much to 569

be learned and we think more unexpected findings, such as the importance of 570

non-chiropterophilous plants, might happen. Given the deep links between plants 571

and bats in this ecosystem, Caatinga should be considered a top priority for 572

conservation efforts. 573

35

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844

Table 1. Network properties of plant – bat pollination networks from Caatinga of Rio Grande do Norte state, northeast Brazil. * indicates 845 significant network metrics in comparison to null models (see Methods for detail). 846 847

Network Bat Plant Interactions Connectance Specialization

(H'2)

Nestedness

(NODF)

Modularity

(Q)

Sampling Completeness

(%)

All 5 31 1250 0.66 0.08* 63.5 0.13* 84.3 Dry 5 26 675 0.6 0.11* 62.1 0.16* 77.6

Rainy 5 27 574 0.56 0.09* 67.0 0.15* 64.9 Lajes 4 24 1117 0.88 0.05* 47.2 0.11* 80.9 2015 4 16 151 0.61 0.16* 62.4 0.19* 76.4 2017 4 17 188 0.72 0.15* 69.3 0.20* 87.2 2018 4 21 244 0.73 0.11* 65.8 0.17* 70.4

848

849

850

Figure 1. Interaction network between plants and nectar-feeding bats from 851 Caatinga of Rio Grande do Norte state, northeast Brazil. The size of the lines and 852 the thickness of the boxes indicate the interaction frequency. Plant species not 853 shown (less frequent ones) are, in order: Jatropha mollissima, Bauhinia 854 cheilantha, Melocactus ernestii, Coursetia rostrata, Pilosocereus piauhyensis, 855 Fabaceae sp1, Harpochilus neesianus, Sapindaceae sp., Undetermined2, 856 Combretum leprosum, Aloe vera, Malpighiaceae sp1., Monocot sp, Pilosocereus 857 tuberculatus and Undetermined4. 858 859 860 861 862

49

863 Figure 2. Pollen types found in bat body and fur samples in Caatinga. 864 Acanthaceae: A Dicliptera ciliaris; B Harpochilus neesianus; C Haporchilus 865 paraibanus; D Ruellia asperula; Bignoneaceae: E Tabebuia aurea; 866 Bromeliaceae: F Encholirium spectabile; Cactaceae: G Cereus jamacaru; H 867 Melocactus ernestii; I Melocactus zehntneri; J Pilosocereus chrysostele; K 868 Pilosocereus gounellei; L Pilosocereus pachycladus; M Pilosocereus 869 piauhyensis; N Pilosocereus tuberculatus; Capparaceae: O Cyanophalla hastata; 870 Cleomaceae: P Tarenaya spinosa; Combretaceae: Q Combretum leprosum; 871 Convolvulacae: R Ipomoea type. Euphorbiacae: S Jatropha mollissima; 872 Fabaceae: T Bauhinia cheilantha; U Bauhinia pentandra; V Fabaceae type; 873 Malvaceae: W Helicteris baruensis; X Pseudobombax type. (Scale bar 10 µm) 874

50

875 Figure 3. Flowers of some of the bat-visited plants. Chiropterophilous species A-876 L: A. Cyanophalla hastata; B. Tareyana spinosa; C. Bauhinia cheilantha (Photo: 877 Rubens Teixeira de Queiroz); D. Bauhinia pentandra (Photo: Carmen Paixão); E. 878 Helicteris baruensis (Photo: Francisco Farriols Sarabia), F. Harpochilus 879 neesianus (Photo: Mario Adelmo Varejão Silva); G. Haporchilus paraibanus 880 (Photo: Emanoel Messias); H. Pilosocereus piauhyensis; I. Pilosocereus 881 chrysostele; J. Pilosocereus gounellei; K. Pilosocereus pachycladus; L. 882 Pilosocereus tuberculatus (Photo: Victor Lima). Melittophilous species M-Q: M. 883 Tabebuia aurea; N. Combretum leprosum (Photo: M. B. I. Lojola); O. Coursettia 884 rostrata (Photo: Domingos Cardoso); P. Aloe vera (Photo: Jamie Morrow); Q. 885 Jatropha mollissima. Ornithophilous species R-V: R. Dicliptera ciliaris (Photo: 886 Olivier Gaubert), S. Ruellia asperula; T. Melocactus zehntneri; U. Melocactus 887 ernestii. Phalaenophilous species: V. Cereus jamacaru. Mixed: W. Encholirium 888 spectabile with Lonchophylla mordax visiting its flowers. 889

51

890

Figure 4. Comparison of species-level network indices between chiropterophilous 891 plants (N= 12 species) and plants showing other pollination syndromes (N=9). 892 The boxplots depict the median and the quartiles for all the metrics. None of the 893 comparisons were significant. 894 895

52

SUPPORTING INFORMATION 896 897

898 Figure S1. A) Map of the sampling sites in Rio Grande do Norte state, 899 northeastern Brazil. B) Area of occurrence of Caatinga ecosystem in Brazil. 900

901

53

Table S1. Sampling sites of bat captures in Caatinga of Rio Grande do Norte from 902 2015-2019. *Conservation Units, other sites were located in unprotected private 903 properties 904 905

Municipality Sampling Site Latitude Longitude Habitat Assu FLONA de Açu - Sitio cables -5.576278 -36.954722 Shrubby Caatinga *Açu National Forest FLONA de Açu - Sitio carnaubal -5.537781 -36.962528 Copernicia groves

FLONA de Açu - Sitio medio -5.562993 -36.956627 Shrubby Caatinga

Baraúna Sitio Coqueiros (Buffer area) -5.022500 -37.447583 Orchards *Furna Feia National Park PARNA Furna Feia - Atolados -5.045963 -37.510515 Medium Caatinga PARNA Furna Feia - Sitio 1 -5.038146 -37.559421 Medium Caatinga PARNA Furna Feia - Sitio letreiro -5.055785 -37.537123 Medium Caatinga Cerro Corá Sitio Araras do Bala, velho -6.080221 36.317938 Riparian Caatinga Serra São João -6.045830 -36.287671 Shrubby Caatinga Felipe Guerra Sitio Passagem Funda -5.572606 -37.675224 Copernicia groves Lajedo do Rosario -5.561032 -37.663018 Rocky outcrops Lajedo do Urubu -5.572894 -37.652178 Rocky outcrops Sitio Barra -5.577348 -37.574361 Riparian Caatinga Lajes Açude Santa Rosa -5.831779 -36.202887 Riparian Caatinga Fazenda Santo Antonio -5.798484 -36.240754 Shrubby Caatinga Sitio Amarante -5.798667 -36.139528 Riparian Caatinga Serra do Feiticeiro-Minas -5.747957 -36.174944 Shrubby Caatinga

Sitio Juazeiro -5.765694 -36.215472 Riparian Caatinga Sitio Bom Fim -5.810528 -36.120556 Riparian Caatinga Sitio Tapuá -5.818944 -36.201389 Shrubby Caatinga Martins Casa de pedra -6.071420 -37.885478 Medium Caatinga Brejo -6.063889 -37.936472 Humid forest enclave Serra ESEC do Seridó - Açude e trilha -6.580697 -37.255378 Riparian Caatinga *Seridó Ecological Station ESEC do Seridó - Junco -6.599227 -37.249024 Medium Caatinga ESEC do Seridó - Lajedo -6.575139 -37.267417 Rocky outcrops ESEC do Seridó - Pe da serra -6.565667 -37.264667 Medium Caatinga ESEC do Seridó - Savana -6.573081 -37.256470 Shrubby Caatinga

906

54

Figure S2. Sampled habitat types. A. Copernicia groves, palm stands dominated 907 by Copernicia prunifera (carnauba) of 10-20m high near river courses, lagoons 908 or lakes. B. Humid forest enclave, evergreen and semideciduous forest enclaves 909 found on mountains (>500m altitude) surrounded by Caatinga vegetation with a 910 canopy of 10-20m with abundant trees, vines and epiphytes. C. Medium 911 Caatinga, xerophytic trees of 7-15m tall with a close canopy during rainy season 912 and with a variable density in the arboreal layers. D. Orchards with non-native 913 species like Mangifera indica, Musa sp., and Artocarpus heterophyllus 914 surrounded by Caatinga vegetation. E. Riparian Caatinga, alongside rivers, 915 lakes, lagoons and artificial dams. F. Rocky outcrops, outcroppings of calcareous 916

55

or granitic rocks with patches of Caatinga vegetation. G. Shrubby Caatinga, with 917 dispersed trees (3-8m tall) in a matrix of bushes and open areas with annual 918 herbs and grasses, cacti and also bromeliads. 919 920 Table S3. Description of the sampled Caatinga habitat types 921 Habitat Description Medium Caatinga forest Xerophytic trees of 7-15m tall with a close canopy during rainy season and

with a variable density in the arboreal layers. Common plant species are Poincianella pyramidalis, Mimosa tenuiflora, Ziziphus joazeiro, Myracrodruon urundeuva, Auxemma oncocalyx, Jatropha mollissima, Bauhinia forficata, Cereus jamacaru, Bromelia laciniosa. These forests are rare in RN and restricted to hillsides or canyons and in protected areas.

Shrubby Caatinga Dispersed trees (3-8m tall) of Aspidosperma pirifolium, Tabebuia aurea, Amburana cearensis in a matrix of bushes of Poincianella pyramidalis, Mimosa tenuiflora, Jatropha mollissima, Ruellia asperula, and Cnidosculus urens, and open areas with annual herbs and grasses like Aristida sp. Cacti are the most common components, Cereus jamacaru, Melocactus zehtneri, Tacinga inamoena, T. palmadoura, Pilosocereus gounellei, P. chrysostele and P. pachycladus, the latter a tree-like cacti found in large densities in some localities (e.g. Lajes); also terrestrial bromeliad Bromelia laciniosa and Encholirium spectabile are found.

Riparian Caatinga Plant composition varies among localities but, in general, riparian caatingas in RN are a mixture of Shrubby Caatinga with components of Medium Caatinga forest. However, it presents typical plant species associated to water bodies that are found alongside rivers, lakes, lagoons and artificial dams such as Licania rigida, Tabebuia aurea, Cleome spinosa. Trees of P. pyramidalis, M. tenuiflora, Prosopis juliflora, Z. joazeiro, shrubs as Jatropha mollissim., Ruellia asperula, and cacti C. jamacaru, P. gounellei and P. pachycladus can be found as well.

Copernicia Forest Palm stands dominated by Copernicia prunifera (carnauba) of 10-20m high near river courses, lagoons or lakes with a varzea characteristic during the rainy season. During the rainy season the understory is covered with herbaceous species.

Rocky outcrops Outcroppings of calcareous or granitic rocks that varies in complexity from simple unbroken rock faces to a complex of many fissured rock faces studded with patches of Caatinga vegetation including cacti (Pilosocereus gounellei), terrestrial bromeliads (Encholirium spectabile, Bromelia lacinosa), Senna sp and C. urens shrubs, and dispersed trees of P. pyramidalis and Tabebuia aurea trees are commonly found.

Brejo de Altitude Evergreen and semideciduous forest enclaves found on mountains (>500m altitude) surrounded by Caatinga vegetation with a canopy of 10-20m with trees of Ficus sp., Brosium sp., Copaifera sp., Senegalia polyphylla, Hymenaea sp., Contortisiliquum sp., Anacardium occidentale, Entherolobium sp., Psidium guajava, Spondias sp., Annona squamosa; Syagrus coronata palms, Ruellia sp. bushes, Cereus jamacaru cacti, with Cayoponia sp., Ipomea sp., and Mucuna sp vines and epiphyte bromeliads and orchids with non-native species like Mangifera indica, Musa sp., and Artocarpus heterophyllus are found.

922

923

56

Table S4. Criteria established to consider pollen contamination in the samples 924 Criteria *Pollen grains Family/Genus Observation Anemophilous or autogamous

1-2 Poaceae, Asteraceae and Amaranthaceae were disregarded

Sigle pollen in single sample

1 Malvaceae sp1., Bromeliaceae sp1., and Justicia rubrobracteata, were disregarded

Attention should be paid to these plants as possible resources for bats in future studies

**Small pollen grains

≤10 Tarenaya spinosa (Jacq.) Raf. (basionym Cleome spinosa Jacq. Criteria used by Sperr et al. 2011

Not applied to samples of individuals captured during the first half hour of sampling (1730 h-1800 h), we considered that the few pollen grains present in their fur was from the previous night and not contamination.

**Medium pollen grains

≤5 Combretum, Coursetia, Cynophalla, Dicliptera and Tabebuia

**Large and very large pollen grains

≤ 5 Bauhinia, Cereus, Encholirium, Harpochilus, Jatropha, Melocactus, Pilosocereus and Pseudobombax

*Number of pollen grains per sample that were considered contamination 925 **Size categories in Erdtman 1952 926 927

57

Table S5. Trait information about the 23 plant species used by nectar-feeding bats in the Caatinga was gathered from published and 928 grey literature obtained from Google scholar (https://scholar.google.com), self-archived ResearchGate (https://www.researchgate.net) 929 and The Brazilian Flora 2020 project (http://floradobrasil.jbrj.gov.br/). Pollen size categories L: Large, M: Medium, VL: Very Large. 930 931

Family Plant species Flowering season

Flower oppening

Flower type

Blossom class Corolla color

Flower size (mm)

Flower size category Pollination syndrome

Pollen size category References

Acanthaceae Dicliptera ciliaris Rainy Day Close Flag Violet 20 M Ornithophily M 5, 22

Harpochilus neesianus Year-round Night close Gullet Green/yellow 70-90 VL Chiropterophily B 6, 30, 31, 39

Harpochilus paraibanus Transition Night close Gullet Pale yellow 40 VL Chiropterophily B 6, 8, 18

Ruellia asperula Dry Day close Gullet Red 25,5 ± 3,2 VL Ornithophily B 8, 14

Bignoneaceae Tabebuia aurea Dry Day Open Bell-funnel Yellow 65 VL Melittophily M 3,4, 17, 35

Bromeliaceae Encholirium spectabile Transition Crepuscular open Brush

Light green/yellow 24 M Mixed B 10, 29, 32

Cactaceae Cereus jamacaru Rainy Night close Tube White 200-300 VL Phalaenophily VB 2,12, 29

Melocactus ernestii Year-round Day close Tube

Dark pink/magenta 19.5-29 M Ornithophily B 2, 8, 12, 25

Melocactus zehntneri Year-round Day close Tube Pink 13,5 ± 2,2 M Ornithophily B 2, 14, 15, 30

Pilosocereus chrysostele Transition Night close Tube

Light pink/brown 45 ± 2,7 VL Chiropterophily B 2, 8, 40

Pilosocereus gounellei Year-round Night close Tube

Light pink/white 71,8 ± 7,1 VL Chiropterophily B 2, 8, 40

Pilosocereus pachycladus Year-round Night close

Bell-funnel White 67,4 ± 3,9 VL Chiropterophily B 2, 8, 40

Pilosocereus piauhyensis . Night close

Bell-funnel White 55-75 VL Chiropterophily B 2, 8

Pilosocereus tuberculatus Year-round Night close Tube White/green 60-67 VL Chiropterophily B 2, 30

Capparaceae Cynophalla hastata Dry Day Open Brush Cream 30 L Chiropterophily M 1, 16, 34

Cleomaceae Tarenaya spinosa Year-round Crepuscular Open Dish White 10 M Chiropterophily S 16, 28, 33

58

Combretaceae Combretum leprosum Rainy Day Open Dish White 6 S Melittophily M 2, 8, 21

Euphorbiaceae Jatropha mollissima Year-round Day open Dish Yellow 5 S Melittophily/Psychophily VB 7, 27, 30, 37

Fabaceae Bauhinia cheilantha Transition Night close Flag White 50-60 VL Chiropterophily VB 9, 28, 30

Bauhinia pentandra Rainy Night close Flag White/green 40-50 VL Chiropterophily VB 2, 8

Coursetia rostrata Rainy Day close Flag White 30-35 VL Melittophily M 2, 8, 13, 19

Malvaceae Helicteres baruensis Rainy Crepuscular close Flag White-green 30 L Chiropterophily M 2, 8, 11, 38

Xanthorrhoeaceae Aloe vera Dry Day close Tube Yellow 26-34 L Melittophily/Ornithophily B 2, 8, 36 932 1. Aguirre De la Hoz, A. C., & Ruiz Zapata, T. (2017). Capparaceae Juss. from Atlántico deparment, Colombia. Ciencia

en Desarrollo, 8(1), 51-69.

2. Anderson, E. F., & Brown, R. (2001). The cactus family (Vol. 776). Portland: Timber press.

3. Barros, M. G. (2001). Pollination ecology of Tabebuia aurea (Manso) Benth. & Hook. and T. ochracea (Cham.) Standl.(Bignoniaceae) in Central Brazil cerrado vegetation. Brazilian Journal of Botany, 24(3), 255-261.

4. Barbosa-Filho, J. M., Lima, S. A., Camorim, E. L., de Sena, K. X. F., Almeida, J. R. G., da-Cunha, V. L., ... & Braz-Filho, R. (2004). Botanical study, phytochemistry and antimicrobial activity of Tabebuia aurea:(with 1 table & 1 figure). Phyton (Buenos Aires), 73, 221-228.

5. Côrtes, A. L. A., & Rapini, A. (2013). Justicieae (Acanthaceae) do semiárido do estado da Bahia, Brasil. Hoehnea, 40(2), 253-292.

6. Costa-Lima, J. L., & Chagas, E. C. D. O. (2019). A revision of Harpochilus sheds light on new combinations under Justicia (Acanthaceae). Phytotaxa, 393(2), 119-130.

7. Diogo, I. J. S., Martins, F. R., Verola, C. F., & Costa, I. R. D. (2016). Variation in plant-animal interactions along an elevational gradient of moist forest in a semiarid area of Brazil. Acta Botanica Brasilica, 30(1), 27-34.

8. Erdtman, G. (1952). Pollen morphology and plant taxonomy. New York, 6-24.

9. Fonseca Vaz, A. M. S., & Azevedo Tozzi, A. M. G. (2003). Bauhinia ser. Cansenia (Leguminosae: Caesalpinioideae) no Brasil. Rodriguésia, 54(83), 55-143.

10. Forzza, R. C., & Zappi, D. (2011). Side by side: two remarkable new species of Encholirium Mart. ex Schult. & Schult. f.(Bromeliaceae) found in the Cadeia do Espinhaço, Minas Gerais, Brazil. Kew Bulletin, 66(2), 281.

11. Goldberg, L. (2009). Patterns of nectar production and composition, and morphology of floral nectaries in Helicteres guazumifolia and Helicteres baruensis (Sterculiaceae): two sympatric species from the Costa Rican tropical dry forest. Revista de Biología Tropical, 57, 161-177.

12. Gomes, V. G. N., Quirino, Z. G. M., & Machado, I. C. (2014). Pollination and seed dispersal of Melocactus ernestii Vaupel subsp. ernestii (Cactaceae) by lizards: an example of double mutualism. Plant Biology, 16(2), 315-322.

13. Lavin, M. (1988). Systematics of Coursetia (Leguminosae-Papilionoideae). Systematic Botany Monographs, 1-167.

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14. Leal, F. C., Lopes, A. V., & Machado, I. C. (2006). Polinização por beija-flores em uma área de caatinga no Município de Floresta, Pernambuco, Nordeste do Brasil. Revista Brasileira de Botânica, 29(3), 379-389.

15. Locatelli, E., & Machado, I. C. S. (1999). Comparative study of the floral biology in two ornithophilous species of Cactaceae: Melocactus zehntneri and Opuntia palmadora. Bradleya, 1999(17), 75-86.

16. Machado, I. C., Lopes, A. V., Leite, A. V., & de Brito Neves, C. (2006). Cleome spinosa (Capparaceae): Polygamodioecy and pollination by bats in urban and Caatinga areas, northeastern Brazil. Botanische Jahrbücher, 127(1), 69-82.

17. Mendes, D. O. F., L. F. P. Mendes, E. O. Souza & C. Aoki, 2017. Flores de paratudo (Tabebuia aurea) (Bignoniaceae) como recurso alimentar para aves no Pantanal Sul, Brasil. Boletim do Museu Paraense Emílio Goeldi. Ciências Naturais 12(2): 295-299.

18. Monteiro, F. K. S., Fernando, E. M. P., Lucena, M. D. F. D. A., & Melo, J. I. M. (2018). A new species of northeastern Brazilian endemic genus Harpochilus (Acanthaceae). Phytotaxa, 358(3), 289-294.

19.Queiroz, L. P., & Lavin, M. (2011). Coursetia (Leguminosae) from Eastern Brazil: nuclear ribosomal and chloroplast DNA sequence analysis reveal the monophyly of three Caatinga-inhabiting species. Systematic Botany, 36(1), 69-79.

20. Queiroz, J. A., Quirino, Z. G. M., Lopes, A. V., & Machado, I. C. (2016). Vertebrate mixed pollination system in Encholirium spectabile: a bromeliad pollinated by bats, opossum and hummingbirds in a tropical dry forest. Journal of Arid

21. Quirino, Z. G. M., & Machado, I. C. (2001). Biologia da polinização e da reprodução de três espécies de Combretum Loefl.(Combretaceae). Revista Brasileira de Botânica, 24(2), 181-193.

22. Quirino, Z. G. M., & Machado, I. C. (2014). Pollination syndromes in a Caatinga plant community in northeastern Brazil: seasonal availability of floral resources in different plant growth habits. Brazilian Journal of Biology, 74(1), 62-71.

23. Rathod, A. H., Parmar, S. K., Vaghela, P. O., Sheikh, W. A., Shinde, A. S., & Kalaskar, S. R. (2014). Floral and reproductive phenology of Aloe vera. Bioscan, 9(2), 723-726.

24. Rede de catálogos polínicos online. disponível em: < http://chaves.rcpol.org.br/ >. acesso em: 1/11/2019 25. Romão, R. L., Hughes, F. M., Vieira, A. M. C., & Fontes, E. C. (2007). Autoecologia de Cabeça-de-frade (Melocactus ernestii Vaupel) em duas áreas de

afloramentos na Bahia. Revista Brasileira de Biociências, 5(1), 738-740.

26. Rocha, E. A., Machado, I. C., & Zappi, D. C. (2007). Floral biology of Pilosocereus tuberculatus (Werderm.) Byles & Rowley: a bat pollinated cactus endemic from the “Caatinga” in northeastern Brazil1. Bradleya, 2007(25), 129-145.

27. Santos, M. J., Machado, I. C., & Lopes, A. V. (2005). Biologia reprodutiva de duas espécies de Jatropha L.(Euphorbiaceae) em Caatinga, Nordeste do Brasil. Revista Brasileira de Botânica, 28(2), 361-373.

28. Santos, F. A. R., Novaes, D., & de Queiroz, L. P. (2012). Pollen of Bauhinia L. and Phanera Lour.(Leguminosae-Caesalpinioideae) from the Brazilian Caatinga. American Journal of Plant Sciences, 3(07), 909.

29. Silva, T. D. S., Felix, L. P., & Melo, J. I. M. D. (2015). Bromeliaceae and Orchidaceae on rocky outcrops in the Agreste Mesoregion of the Paraíba State, Brazil. Hoehnea, 42(2), 345-365.

30. Silva, F. H. M., Santos, F. A. R., & Lima, L. C. L. (2016). Flora Polínica das Caatingas: Estação Biológica de Canudos (Canudos, Bahia, Brasil). Feira de Santana: Micron.

31. Silva Monteiro, F. K., Pinto, A. S., da Costa, F. C. P., & de Melo, J. I. M. (2018). A Taxonomic Synopsis of Acanthaceae Juss. Native to Paraíba State, Brazil. Harvard Papers in Botany, 23(2), 189-204.

32. Silva, J., Rocha, L. H. S., Jorge, J. P. S., Sousa, P. H. P., Santos, R. L., & Freire, E. M. X. (2018). Floral visitors and potential pollinators of a rupicolous bromeliad (Pitcairnioideae) in the Brazilian semiarid. Neotropical Biology and Conservation, 13(2), 101-110.

33. Soares Neto, R. L., Magalhães, F. Á. L., Tabosa, F. R. S., Moro, M. F., Costa e Silva, M. B., & Loiola, M. I. B. (2014). Flora of Ceará state, Brazil: Capparaceae. Rodriguésia, 65(3), 671-684.

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34. Soares Neto, R. L., & Jardim, J. G. (2015). Capparaceae in the state of Rio Grande do Norte, Brazil. Rodriguésia, 66(3), 847-857.

35. Souza, C. N., Rezende, A. A., & Gasparino, E. C. (2019). Pollen morphology of Bignoniaceae from Brazilian forest fragments and its systematic significance. Palynology, 43(2), 333-347.

36. Velásquez-Arenas, R., & Imery-Buiza, J. (2008). Fenología reproductiva y anatomía floral de las plantas Aloe vera y Aloe saponaria (Aloaceae) en Cumaná, Venezuela. Revista de biología tropical, 56(3), 1109-1125.

37. Viana, B. F., Neves, E. L. D., & MachadoI, I. C. (2011). Sistemas de polinização e de reprodução de três espécies de Jatropha (Euphorbiaceae) na Caatinga, semi-árido do Brasil.

38. von Helversen, O., & Voigt, C. C. (2002). Glossophagine bat pollination in Helicteres baruensis (Sterculiaceae). Polinización mediante murciélagos Glossophaginae en Helicteres baruensis (Sterculiaceae). Ecotropica., 8(1), 23-30.

39. Vogel, S., Machado, I.C., Lopes, A.V., (2004). Harpochilus neesianus and other novel cases of chiropterophily in neotropical Acanthaceae. Taxon 53, 55e60.

40. Rocha, E. A., Domingos-Melo, A., Zappi, D. C., & Machado, I. C. Reproductive biology of columnar cacti: are bats the only protagonists in the pollination of Pilosocereus, a typical chiropterophilous genus?. Folia Geobotanica, 1-18.

933

61

Table S6. Nectar-feeding bat captures throughout the study period 934 935

(a) Captures per year Year (Sampling effort) Anoura

geoffroyi Glossophaga

soricina Lonchophylla inexpectata

Lonchophylla mordax

Xeronycteris vieirai

Total

2015 (44163,75 m2h) 1 48 12 27 33 121 2017 (103646,25 m2h) . 72 26 49 29 176 2018 (143623,75 m2h) 4 99 50 81 55 289 2019 (15663,75 m2h) 1 27 9 15 12 64

TOTAL 6 246 97 172 129 650

(b) Captures per season Season (Sampling

effort) Anoura

geoffroyi Glossophaga

soricina Lonchophylla inexpectata

Lonchophylla mordax

Xeronycteris vieirai

Total

Rainy (140717,5 m2h) 1 99 45 97 62 304 Dry (166380 m2h) 5 147 52 75 67 346

(c) Captures per municipality and habitat type

Municipality (sampling effort)

Habitat type Anoura geoffroyi

Glossophaga soricina

Lonchophylla inexpectata

Lonchophylla mordax

Xeronycteris vieirai

*Açu (14198,75 m2h) Copernicia groves

. . . 1 .

Copernicia groves

. 10 . . .

*Baraúna(21220 m2h) Medium . 7 . . . Orchards . . . . . Shrubby . . . . .

Cerro Corá (5086,25 m2h)

Riparian . 2 . . .

Shrubby . . . . . Felipe Guerra (30907,5

m2h) Copernicia

groves 1 . . .

Medium . 5 . . . Riparian . 5 . 3 . Rocky

outcrops 18 . 13 .

Lajes (202600 m2h) Riparian 1 79 43 47 10 Shrubby 109 54 100 119

Martins (14267,5 m2h)

Humid forest enclave

5 10 . . .

Medium . . . 1 . *Serra Negra do Norte

(22612,5 m2h) Medium . . . . .

Riparian . . . . . Rocky

outcrops . . . 7 .

Shrubby . . . . . *Protected areas

936 937

62

938

939

63

940

941 942

Mechanisms mediating nectar-feeding bats coexistence and persistence 943

through the seasonal rhythm of Caatinga 944

945

Eugenia Cordero-Schmidt1, Juan Carlos Vargas-Mena1, Paulino Pereira-946 Oliveira2, Francisco de Assis R. Santos2, Bernal Rodriguez-Herrera3 and 947 Eduardo M. Venticinque1 948 949 950 1 Departamento de Ecologia, Universidade Federal do Rio Grande do Norte, 951 59078900 Lagoa Nova Natal, RN, Brazil; E-mail: ecordero.s@gmail.com 952 2 Laboratório de Micromorfologia Vegetal, Universidade Estadual de Feira de 953 Santana, 44036-900, Novo Horizonte, BA, Brazil 954 3 Escuela de Biología, Universidad de Costa Rica, 2060 Montes de Oca, San 955 José, Costa Rica 956 957

64

ABSTRACT 958

Species coexistence is mediated by ecological differences in space, time 959 and/or complementarity of food resources and these attributes are linked to each 960 species physiology, morphology, and behavior. Coexisting nectar-feeding bats 961 have been observed in most neotropical regions and up to eight species have 962 been observed in a single locality, and up to five species co-occur in Caatinga. 963 We tested three coexisting mechanisms between nectar-feeding bat species: a) 964 Temporal partitioning by comparing differences in capture rates between years, 965 seasons and between hours within the same nights. b) Ecomorphological 966 differences by measuring body weight, forearm size, snout length and wing 967 morphology. c) Resource partitioning by identifying pollen in fur samples and 968 determining the composition of their feces. We studied a nectar-feeding bat 969 ensemble in an area of Caatinga in Rio Grande do Norte state for over two years 970 and collected phenological data on nine plant species to document resource 971 availability through time. We capture a total of 443 individuals belonging to four 972 nectar-feeding bat species: Glossophaga soricina, Lonchophylla inexpectata, L. 973 mordax and Xeronycteris vieirai. The mechanisms detected are complementary 974 and seem to be explained by temporal partitioning (differences in captures 975 throughout the night), by ecomorphological differences (size, weight, snout 976 length, wing aspect ratio) and by resource partitioning (diet flexibility feeding on 977 at least 20 plant species, and insects). The temporal persistence of nectar bats 978 was facilitated by the continuity and complementarity of floral resources 979 availability during both seasons. Cactaceae is a keystone resource in Caatinga 980 since it was the most used family (five cacti species used in a high frequency) by 981 all nectar-feeding bats. 982 983

984

Keywords: Eco-morphology; Keystone resources; Phenology; Resource-985

partitioning; Seasonally Dry Tropical Forest; Night-sharing 986

987

65

GRAPHICAL ABSTRACT 988

989

990

Nectar-feeding bats persist and coexist year-round both in thewet season & dry season by:

Ecomorphological:- Weight and size

- Snout length

- Wing Aspect ratio

Temporal partitioning:

- Differences in captures throughout

the hours of the night

Diet flexibility:- 24 plant species- Insects- Pollen- Plant tissues

Keystone resource:- Cactaceae- Pilosocereus pachycladus

Glossophaga soricina

Lonchophylla mordax

Xeronycteris vieirai

Lonchophylla inexpectata

9

8

76

10

Res

ourc

e pa

rtitio

ning

1112

66

INTRODUCTION 991

Tropics are packed with coexisting species, and understanding the mechanisms 992

enabling this have interested ecologists for decades. Coexistence may be even 993

more intriguing between species performing same ecological roles, such as 994

pollinators (Palmer, Stanton & Young, 2003). Pianka (1974) noted that species 995

coexistence is mediated by ecological differences in space, time and/or 996

complementarity of food resources and these attributes are linked to each 997

species physiology, morphology, and behavior (Jorgensen & Fath, 2014). Bats 998

have been an ideal group to deepen the understanding of coexistence and 999

competition mechanisms, as suites of evolutionary sister species may commonly 1000

be encountered in the same locality (Findley, 1993). 1001

The known fauna of nectar-feeding bats (hereafter ‘nectar bats’) in the 1002

Neotropics is composed of 55 species (Solari & Martínez-Arias, 2014, Moratelli 1003

& Dias, 2015), divided in the subfamilies Lonchophyllinae (19 species) and 1004

Glossophaginae (36 species). Coexisting nectar bats have been observed in 1005

most neotropical regions and up to eight species have been observed in a single 1006

locality (Fleming & Muchhala 2008). There are several adaptations linked to 1007

nectar feeding species and small differences among them can mediate 1008

mechanisms of coexistence between the species of nectar bats (Gonzales-1009

Terrazas et al., 2012). 1010

Nectar bats present long narrow snouts with reduced dentition coupled 1011

with long tongue with hair-like papillae in the tip of the tongue (in Glossophaginae) 1012

or deep lateral grooves along the entire length of the tongue (in Lonchophyllinae) 1013

(Tschapka, Gonzalez-Terrazas, & Knörnschild, 2015). Nectar bats are generally 1014

light weighted and have specific proportions in their wings that aid in hovering 1015

67

while feeding (Findley, Studier & Wilson, 1972). The mentioned morphological 1016

characteristics limits access to certain floral resources and nectar extraction 1017

efficiency contributing to coexistence by resource partition (Gonzales-Terrazas 1018

et al., 2012). 1019

Physiologically, nectar bats possess high basic metabolic rates and high 1020

daily energy requirements, likewise they are able to digest and metabolize nectar 1021

and pollen quickly (Datzmann, von Helversen & Mayer, 2010). In nature nectar 1022

bats encounter a wide variety of resources with different energetic cost-benefits. 1023

Bats mostly feed on chiropterophilous flowers (nocturnal, robust with light colors 1024

and strong scent), but have been reported to use non-chiropterophilous as well 1025

(Vogel, Lopes & Machado, 2005; Fadini et al., 2018; Cordero-Schmidt in prep.). 1026

It has been proven that the resource selection is not random and that it is highly 1027

influenced by flower attraction, access and rewards (amounts of nectar and 1028

pollen and nectar sugar concentrations) (Tschapka, & Dressler, 2002) and that 1029

the use of certain resources could be species-specific (Winter & von Helversen, 1030

1998; Tschapka et al., 2008; Sperr et al., 2011; Gonzales-Terrazas et al., 2012), 1031

once again contributing with nectar bats coexistence. 1032

Diet plasticity has proven to be another important mechanism of 1033

coexistence and persistence of populations of nectar bats in areas with resource 1034

seasonality (Heithaus et al., 1975; Soriano et al., 1991; Tschapka et al., 2008). 1035

Certain nectarivorous species can also feed on insects and fruits at times of low 1036

availability of floral resources (Reid, 2009). Finally, species turnover has also 1037

been documented for coexistence in bats (Fleming, Muchala & Ornelas, 2005). 1038

Though, a mixture of all the mentioned mechanisms is what generally explains 1039

the coexistence of the species. 1040

68

Testing coexistence is a challenging task, especially in the highly 1041

diversified tropics. Mechanisms modeling nectar bat co-occurence have been 1042

fairly well documented in arid and semi-arid areas (Valiente-Banuet et al., 1996; 1043

Petit, 1996; Nasar et al., 2003). Nine species of nectar-feeding bats are known to 1044

inhabit Caatinga, the largest Seasonal Tropical Dry Forest in America located in 1045

northeastern Brazil, but information about these species is scarce. 1046

The coexistence of nectar bat species in the highly variable environment 1047

of Caatinga is particularly puzzling considering the low and variable precipitation 1048

regulating plant phenologies (Machado, Barros & Sampaio, 1997; Lima & Rodal, 1049

2010) and thus species composition and behavior. The present study is the first 1050

to focus on Caatinga nectar bat ensemble using an ecological approach of 1051

coexistence and persistence of species over time. We tested three coexisting 1052

mechanisms between nectar bat species: a. Temporal partitioning (between 1053

years, seasons and between hours within the same nights). b. Ecomorphological 1054

differences (snout length and wing morphology). c. Resource partitioning (diet 1055

composition). 1056

In markedly seasonal ecosystems, climatic variables are good predictors 1057

of population behavior (Janzen, 1973). Hence, considering Caatinga’s temporal 1058

variability reflected in the seasonality of the availability of food resources, our 1059

hypothesis was that we would find seasonal differences both in the number of 1060

nectar bat species coexisting as well as in the resources used by them. We 1061

expected that at times of less resources available (driest months) the composition 1062

of the ensemble would be different, and the remaining species would have a more 1063

similar diet among them. On the contrary, in periods with more resources (wettest 1064

months) there would be more co-existing nectar bats which would have a more 1065

69

differentiated diet (considering used plant species and complementing items) and 1066

the use of resources would be explained by ecomorphological differences among 1067

the bat species. 1068

METHODS 1069

Study site 1070

The study was carried out in the Caatinga in the municipality of Lajes, Rio Grande 1071

do Norte (RN) state, northeastern Brazil (5°48'46.95"S 36°10'34.60"W). Our three 1072

sampling sites were located within the largest (53,500 ha; 200–400 mamsl) 1073

continuous fragment of Caatinga vegetation in the RN state. Lajes is located in 1074

the Northern semiarid region (following Oliveira et al., 2017) with an average 1075

rainfall of 399.31 mm (precipitation data from 2009 to 2019). The wet season is 1076

from January to June and the dry season from July to December. 1077

During our study, the sum of the accumulated rainfall was 313.2 mm in 1078

2017, the rainiest month was February (111.9 mm) and the driest months were 1079

August to November with zero precipitation. In 2018 the accumulated rainfall was 1080

351.65 mm in 2018 (rainiest April with 108 mm and the driest August, September 1081

and November with zero precipitation). All precipitation data were extracted from 1082

the EMPARN (acronym in Portuguese Rio Grande do Norte Agricultural 1083

Research Corporation) database. Vegetation in Lajes is Hyperxerophilous 1084

Caatinga type, a dry vegetation, with large Cactaceae presence and smaller and 1085

scattered plants. Presenting a predominance of deciduous herbaceous and 1086

shrubby plant species (Farias, 2016). 1087

Bat sampling 1088

Bat captures was conducted monthly, in a total of 57 mist-netting nights 1089

(approximately 3 nights per month), between February 2017 and February 2019 1090

70

(except November 2017 and May 2018), including 30 nights in the dry season 1091

and 27 in the wet season. Mist nets were placed for over six hours (from sunset 1092

to midnight), using 80 to 120 m of mist nets per night. Total sampling effort was 1093

155991.25 m2h (total area of the mist-nets multiplied by the by the time they were 1094

set; Straube and Bianconi, 2002). We identified the species in the field using 1095

systematic keys and species diagnosis (Díaz et al., 2016). All procedures for 1096

capture, handling and collection of bats met the guidelines of the American 1097

Society of Mammalogists for the use of wild mammals in research (Sikes, 2016), 1098

and the legal Brazilian requirements of conservation and animal welfare. 1099

Fieldwork was authorized by MMA/ICMBio/SISBIO under permits 48325-2. Bats 1100

were marked by cutting a small portion of fur from the back of each individual to 1101

recognize recaptured individuals during the same sampling period. 1102

a. Temporal partition and species turnover 1103

The time of capture was recorded for each bat individual; this information was 1104

used as a proxy for differences in the species activity as a coexistence 1105

mechanism. We tested for significant differences in the capture rates between 1106

years, seasons and hours within the night. For this analysis we considered 20 1107

sampled periods (9 months for the wet season, 11 for the dry). First, we did a 1108

Non-Metric Multidimensional Scaling (NMDS) over a Bray Curtis dissimilarity 1109

matrix of the nectar bat species. Prior to the analysis the bat capture data was 1110

corrected by effort as follows: [Captures N / (mist netting hours * meters2) * 1000]. 1111

The ordering adjustment was measured by stress value. The temporal species 1112

composition of the nectar bat ensemble between years, seasons and hours was 1113

tested by applying a MANOVA to the NMDS first and second axis scores values. 1114

71

After MANOVA, one-way ANOVAs were applied to identify in which axes the 1115

variation was significant. 1116

Differences between years, seasons and hours within the nights were 1117

tested for statistical significance using a one-way ANOVA followed by Tukey’s 1118

Honest Significant difference test. We additionally performed a MANOVA to see 1119

significant differences across all variables using Wilks's Lambda Test. 1120

b. Eco-morphological differences 1121

-Body weight and size 1122

We sexed each captured nectar bat, weighed all adult individuals (except 1123

pregnant females) with a dynamometer (precision: 1 g), and measured their 1124

forearm length using calipers (precision: 0.1 mm). 1125

-Snout length 1126

The length of the snout is an indication of specialization in nectarivorous diet, the 1127

longer, the more specialized (Freeman, 1995). A ruler (precision: 0.5 mm) was 1128

used to measure the distance between the center of the eye and the tip of the 1129

lower lip (Tschapka, 2004). 1130

-Wing morphology 1131

To explore if the coexistence mechanisms of nectar bats are related to 1132

differences in their flight style (maneuverability and hovering) and foraging 1133

behavior (ability to fly longer distances in search of resources), we collected three 1134

wing measurements following Tschapka (2004). 1135

We measured the length of the 3rd and 5th finger by using a ruler 1136

(precision: 0.5 mm). Wing proportions were quantified using Aspect Ratio Index 1137

(ARI) and Wing Tip Index (WTI). Following the morphologic properties of bat 1138

wings (Findley, Studier & Wilson, 1972), migratory and high-speed species have 1139

72

high ARI and WTI. These characteristics favors long distance foraging. On the 1140

other hand, species with good ability to maneuver and hover have a low ARI. 1141

Both indices are independent of body size and of each other. 1142

Differences in morphological variables (weight, forearm, ARI, WTI and 1143

snout) between nectar bat species were tested for statistical significance using a 1144

one-way ANOVA followed by Tukey’s Honest Significant difference test. 1145

c. Resource Partition 1146

-Resource availability 1147

To detect the availability of floral resources for one year (December 2017-1148

November 2018, except for May 2018), we followed monthly the phenology of 1149

152 individuals of 9 species (Supporting Information Table S1). Plant species 1150

selection was based on previous field observations of resource use by bats. We 1151

established 15 transects of 100 x 5 m following pre-existing trails, where the 1152

species of trees, shrubs, cacti and bromeliads were identified, and individuals of 1153

each species were counted for abundance estimation in each transect. We 1154

selected at least two adult individuals of each species and tagged them with 1155

fluorescent flagging tape and numbered aluminum plates. Data collected for each 1156

individual were presence or absence of flowers (both buds and open flowers were 1157

considered). 1158

Botanical samples of the species were collected for proper identification 1159

and deposited in the herbarium of the Universidade Federal do Rio Grande do 1160

Norte. Pollen samples were collected directly from flowers available during the 1161

sampling period with jelly-glycerin cubes in order to make a reference pollen 1162

collection. 1163

A matrix of presence and absence of flowering species by month was 1164

73

developed; we summed the number of species flowering in each month. The 1165

dates of the observations were converted into angles, the day 01 / January = 0°, 1166

and sequentially until December 31=360 °, with intervals of approximately 30°. 1167

The flowering phenophase was analyzed using circular statistics using the R 1168

program with the packages Circular (Lund, Agostinelli & Agostinelli, 2017), and 1169

CircStats (Lund and Agostinelli, 2018). The mean angle (M) or average date is 1170

the time of the year around which the dates of flowering occurred for most 1171

species. The Rayleigh (p) test was performed to verify flowering seasonality for 1172

data with unimodal or uniform distribution, whereas Rao’s Spacing Test was 1173

performed when data showed bi or multimodal patterns. The vector ‘r’ indicates 1174

the temporal concentration of events and vary from 0 (when phenological activity 1175

is distributed uniformly throughout the year) to 1 (when phenological activity is 1176

concentrated around one single date or time of year). 1177

- Flower visits 1178

We constructed species accumulation curves on nectar bats captured and the 1179

pollen types found in the samples of the individuals to establish whether the diet 1180

sampling was completed, or otherwise, to know its representativeness of the total 1181

estimated plant species (Moreno and Halffter, 2001). 1182

We collected pollen samples from each captured bat’s fur, wings, legs and 1183

uropatagium using a single glycerin jelly cube (Voigt et al., 2009) per individual, 1184

which were later mounted on glass microscope slides. To avoid cross-1185

contamination from one sample to another, special care was taken by cleaning 1186

the worktable, hands and tweezers with alcohol after finishing the handling of 1187

each individual bat, additionally, cloth bags used to keep the nectar bats were 1188

always clean. 1189

74

We identified pollen types under a light microscope (magnification 40-1190

100x, Leica DM500) to the lowest possible taxonomic level through comparison 1191

with reference collections. To identify the pollen types, we used a collection 1192

specialized on pollen of the Caatinga vegetation from the Palynotheca of the 1193

LAMIV, UEFS (Plant Micromorphology Laboratory, Universidade Estadual de 1194

Feira de Santana, and a reference collection that we made from local plants in 1195

bloom during our fieldwork. We also used pollen catalogues for additional 1196

reference (Palacios-Chávez, Ludlow-Wiechers & Villanueva, 1991; Roubik & 1197

Moreno 1991; Santos, Watanabe & Hamburgo-Alves, 1997; Carreira & Barth 1198

2003; Melhem et al., 2003; Silva, Santos & Lima, 2016). 1199

We noted the identity of the pollen types and number of times each pollen 1200

type was found in a specific bat species as a measure of the frequency of 1201

resource use. Small amounts of pollen can contaminate the samples; thus, we 1202

established a minimum number of pollen grains according to size categories 1203

(Erdtman, 1952; Heithaus, Fleming & Opler, 1975). Medium, large and very large 1204

pollen types (Combretum, Coursetia, Cynophalla, Dicliptera and Tabebuia, 1205

Bauhinia, Cereus, Encholirium, Harpochilus, Jatropha, Melocactus, Pilosocereus 1206

and Pseudobombax) represented in a sample by less than five pollen grains were 1207

considered contamination. For small pollen types (Tareyana spinosa) less than 1208

10 pollen grains were considered contamination. 1209

To detect possible patterns of associations and differences within the 1210

plants used by nectar bat species in the dry and wet season, we performed a 1211

Correspondence Analysis (CA). The CA is an analysis for displaying the rows 1212

and columns of a matrix as points in dual low dimensional vector space 1213

(Greenacre, 1984). The graphical representation of data generated by CA allows 1214

75

visual examination of the correlations among the plant species (row labels) and 1215

bat species (column labels) in the dry and wet season. On the plot, the closer two 1216

rows are to each other, the more similar their residuals, additionally, the closer 1217

the labels are to the origin (where the x- and y-axes are both at 0), the less 1218

distinct they probably are. The length of the lines connecting row/column label to 1219

the origin indicates the association between nectar bats species and one or more 1220

plant species (longer lines indicates higher associations). Finally, the angle 1221

formed between the two lines indicate association, where angles <90 indicate 1222

higher association, 90 degrees angle indicate no relationship and 180 degrees 1223

indicate negative associations. 1224

We performed an analysis of similarity (ANOSIM) to test if there were 1225

significant differences in the diet between species. To measure the similarity, we 1226

used the Bray Curtis dissimilarity index. Significance levels were adjusted by a 1227

Bonferroni sequential correction. To help with the interpretation of the results 1228

obtained with the ANOSIM, we performed a Similarity Percentages (SIMPER) 1229

analysis using the Bray-Curtis method. This analysis breaks down the 1230

contribution of each species of plant to the observed dissimilarity between the 1231

nectar-feeding bat species diets. It allows to identify the species that are most 1232

important in creating the observed pattern of dissimilarity. Analyses were 1233

performed in PAST 3.0. 1234

-Diet composition 1235

To infer if diet plasticity of the different nectar bat species could be 1236

considered as a mechanism of persistence and coexistence, we collected fecal 1237

samples and characterized their contents using a microscope (magnification 40-1238

100x, Leica DM500). We categorized the contents of each fecal sample by the 1239

76

presence or absence of pollen, insect fragments, and “plant tissue” which are 1240

unidentified elements that appear to be of plant origin such as leaves, pericarp, 1241

hairs of cactus areolas, trichomes, etc. 1242

All the individuals captured were fed with sugar water at different times 1243

throughout the handling process, to maintain their energy requirements and 1244

reduce the risk of death due to stress. Additionally, it promotes the production 1245

and excretion of feces while collecting the data, since bats have a fast transit time 1246

of food ingestion-defecation (Muscarella and Fleming, 2007). Fecal samples 1247

were placed in micro tubes for preservation and subsequent analysis. 1248

As mentioned before, snout length is a proxy of specialization, the longer 1249

the snout, the less force in the bite, thus limiting the ability to consume harder 1250

food items, such as insects and fruits (Heithaus, 1982). We correlated the snout 1251

length (mm) of the four nectar bat species and established a Fecal Composition 1252

Index grouping fecal sample in three categories A. Pollen: samples with ≥ 1 pollen 1253

types; B. Pollen & insects: with both ≥ 1 pollen types and insect fragments and/or 1254

moth scales; C Mix: with ≥ 1 pollen types, insect fragments and plant tissues. The 1255

Fecal Composition Index is the score of the first axe of an NMDS analysis with 1256

the percentages of fecal composition by species. In the NMDS ordination we 1257

used the Bray Curtis dissimilarity index to calculate the distance between fecal 1258

species composition. 1259

RESULTS 1260

Nectar-feeding bat ensemble 1261

We captured a total of 443 nectar bats. The local nectar bat ensemble consisted 1262

of four resident species (present year-round) (Figure 1), one Glossophaginae 1263

species, Glossophaga soricina (dry n= 87, wet n=53), and three Lonchophyllinae 1264

77

species, Lonchophylla mordax (dry n=57, wet n=63), Xeronycteris vieirai (dry 1265

n=46, wet n=50) and Lonchophylla inexpectata (dry n=44, wet n=43). 1266

Temporal partitioning 1267

-Changes in species composition and temporal partitioning between seasons and 1268

years 1269

There were no significant differences between the captures rates for all species 1270

(F = 0.710; DF = 3,72; P = 0.548), between seasons (F = 0.655; DF = 1,72; P = 1271

0.420) and the interaction between species * season (F = 0.470; DF = 3.72; P = 1272

0.703) (Supporting Information Table S2). 1273

The time dynamics of capture rates were strongly correlated between X. 1274

vierai and L inexpectata (r = 0.83), between L. mordax and L. inexpectata (r = 1275

0.71) and between X. vierai and L. mordax (r = 0.69). Glossophaga soricinia 1276

presented a capture dynamic uncoupled with L. inexpectata and L. mordax 1277

(Supporting Information Table S3). There were no significant differences among 1278

the community composition within the years (MANOVA with Wilks's 1279

Lambda=0.96393; F=0.29939; df=2,16; p=0.74533) and the seasons (MANOVA 1280

with Wilks's Lambda=0.91777; F=0.76156; df=2,17; p=0.48222) (Respectively, 1281

Supporting Information Table S4A and S4B and Figure 2A and 2B). 1282

-Temporal partition between hours within the night 1283

There were significant differences (MANOVA with Wilks's Lambda=0.44649; 1284

F=2.15177; df=12,52; p=0.02883) among the community composition between 1285

the hours of the nights (Figure 3A). Some subtle differences are observed 1286

between the number of the different species (Figure 3B). However, after 21:00 1287

the captures of all species remain low but stable. In the univariate ANOVA, the 1288

first axis from the NMDS over a Bray Curtis dissimilarity matrix of the nectar bat 1289

78

species captured within the night showed a significant difference between the bat 1290

community over the hours (F=4.301; df=6,27; p=0.00362), but the second axis 1291

showed no significant difference (F=0.47422; df=6,27; p=0.82138). The first axis 1292

was related to a decrease in activity of all species. Xeronycteris vierai showed a 1293

less pronounced peak in early evening activity (Supporting Information Table S5). 1294

a. Ecomorphological measurements 1295

Significant differences were found in the morphology of the four nectar bat 1296

species Table 1). Body size: Considering weight and forearm, the biggest species 1297

is X. vieirai (respectively x̄=11.87 ± 1.77 g; x̄=38.47 ± 0.96 mm), followed by G. 1298

soricina (x̄=9.98 ± 1.29 g; x̄=35.89 ± 1.26 mm), and finally L. mordax (x̄=8.73 ± 1299

1.21 g; x̄=35.38 ± 1,67 mm), and L. inexpectata (x̄=8.47 ± 1.10 g; x̄=35.06 ± 1.46 1300

mm). 1301

Wing morphology: Wing Tip Index (WTI) was the only morphological 1302

measurement that was not significantly different between species, and Aspect 1303

Ratio Index (ARI) was significantly different for X. vieirai when compared to the 1304

other species. 1305

Snout length: The four nectar bat species could be grouped into three size 1306

categories with significant differences, X. vieirai (x̄=11.99 ± 0.55 mm) has the 1307

longest snout of all, followed by the two species with intermediate size, L. mordax 1308

(x̄=8.84 ± 0.66 mm) and L. inexpectata (x̄=8.99 ± 0.70 mm), finally G. soricina 1309

with the snout significantly shorter (x̄=7.33 ± 0.56 mm). 1310

Resource Partition 1311

-Resource availability 1312

The studied plant community of this Caatinga area presented a constant and 1313

complementary resource offer throughout the year (Figure 4, Table 2). All the 1314

79

nine species included in this phenological analysis were used as a feeding 1315

resource by nectar bats. Considering the number of species and the intensity of 1316

resources availability, the months with the greatest supply are December, 1317

January and February. Cereus jamacaru and Jatropha mollissima flower only in 1318

the wet season. Lowest resource availability occurred in the driest period in 1319

September, October and November. Phenological complementarity is observed 1320

throughout the year (Figure 4, Supplementary Material Table S1). 1321

- Flower visits 1322

We identified pollen types in a total of 443 samples, of which 140 were from G. 1323

soricina, 120 from L. mordax, 96 of X. vieirai and 87 from L. inexpectata. The diet 1324

of the four nectar bats studied was fairly well represented in our samples 1325

(Supporting Information Figure S6). They are feeding on at least 24 plant species 1326

belonging to 11 families. The used plant species show different flower size, 1327

blossom class (flower shape), nectar’s volume and sugar concentration (Table 1328

3). 1329

The nectar bats used more species of the Cactaceae family (5 species), 1330

followed by Acanthaceae and Fabaceae, each with four species. Although most 1331

of the plants were used by all species of nectar bats, differences in the frequency 1332

of use of resources were found (Table 3). The most similar diets were between 1333

L. mordax and L. inexpectata in both seasons and between L. inexpectata and 1334

G. soricina in the wet season (Table 4). Lonchophylla mordax used 23 species 1335

(except J. mollissima), 21 species used by G. soricina (except: Ipomoea sp., H. 1336

neesianus and J. mollissima), likewise X. vieirai used 21 species (except B. 1337

cheilantha, A. vera and an unidentified pollen type), finally the species that fed 1338

80

on fewer plant species was L. inexpectata that used 20 species (except H. 1339

neesianus, A. vera and two unidentified pollen types). 1340

Correspondence analysis separated our nectar-feeding bat species 1341

according to their diet per season. Axis1 accounted 54.2% of the variance (Table 1342

5) and separated bat species by season, additionally, Axis2 (13.4%) separated 1343

X. vieirai from the other bat species (Figure 5). There are several plant species 1344

located in the middle (i.e., near the origin) of the two-dimension space, these 1345

plants are used by all bat species during both seasons. The longest lines in the 1346

different seasons indicate seasonality of resource availability of the plant species, 1347

and/or the importance of the resource for a specific bat species in each season. 1348

Ipomoea type was mostly used by L. inexpectata, while R. asperula was 1349

mostly used by L. mordax in the dry season. On the other hand, H. neesianus 1350

was mostly used by L. mordax and an unidentified leguminosae species 1351

(Fabaceae type) was mostly used by X. vieirai. Glossophaga soricina’s diet 1352

variated greatly seasonally. In the dry season G. sorcina was associated with 1353

most of the commonly used plant species (closer to the origin) T. spinosa and J. 1354

mollissima, in the wet season the G. soricina was the only bat species to use A. 1355

vera, C. rostrata and C. hastata. 1356

The differences between the diet of the nectar-feeding bat species are 1357

better represented in the Axis2 (13.4%) and Axis3 (12.1%) (Figure 6). The four 1358

nectar bat species were divided by genus into three groups and not by sub 1359

families that would be expected by their tongue characteristics. Lonchophylla 1360

sister species have a more similar diet between them, especially during the wet 1361

season and differed more in the dry season. The diet of Xeronycteris differs 1362

greatly from the other nectar-feeding bat species in both seasons (Figure 5 and 1363

81

6). Xeronycteris vieirai’s diet diverges the most with L. mordax in the dry season, 1364

and with G. soricina in the wet season. The ANOSIM (Table 6) revealed 1365

differences in the diet between the four species of nectar-feeding bats (R = 0.036, 1366

p = 0.035). 1367

The contribution of each plant species (%) to the dissimilarity between the 1368

diet of each nectar-feeding bat species in each season are summed in Table 7 1369

(SIMPER). The first eight species of consumed plants explain a little more than 1370

50% of the dissimilarity in the diet of the nectarivores. Season related 1371

dissimilarities in the use was observed in C. jamacaru and H. neesianus (mostly 1372

used in the wet season) and H. baruensis and E. spectabile (in the dry season). 1373

Bat taxonomic related dissimilarities in resource use was observed in P. 1374

pachycladus, P. gounellei and T. spinosa (Supporting Information S7). Where P. 1375

gounellei and P. pachycladus (Cactaceae) were the only two species that were 1376

used year-round with the highest frequency of use by all nectar bat species. 1377

Nonetheless, P. gounellei was mostly used by Lonchophyllinae species and P. 1378

pachycladus mostly by X. vieirai. Tareyana spinosa was also used year-round 1379

but was used differently by nectar bat species in the different seasons 1380

-Diet composition 1381

We collected 125 fecal samples (G. soricina n=23; L. inexpectata n=33; L. 1382

mordax n=29 and X. vieirai n=40) (Figure7). The four species of nectar bat 1383

species are feeding on the same elements (pollen, insects and plant tissue) 1384

during both seasons. However, G. soricina in addition to these elements also 1385

consumed cactus fruits. We found P. pachycladus seeds in the body of two 1386

individuals (fruits were not included in the analysis since the seeds were not found 1387

in the fecal samples but in the bats fur near the anus). Fecal samples of all 1388

82

species presented pollen, however for most species we found pollen mixed with 1389

insect fragments and/or plant tissues (which could be leaves, pericarp, pulp, 1390

cactus areolas hairs and/or trichomes). The large amount of pollen, insects and 1391

plant tissues present in several samples indicates that the species are consuming 1392

these items to complement their diet. A higher proportion of fecal samples with 1393

insect fragments (mostly Lepidoptera scales) were documented in the wet 1394

season for all nectar bat species. 1395

There are significant differences between the snout length of the different 1396

nectar bat species and fecal composition (Figure 8). The fecal composition of 1397

G.soricina (shortest snout) was dominated by pollen and insects. No fecal 1398

samples of G. soricina contained exclusively pollen, contrary to X. vieirai (longest 1399

snout) who presented the highest percentage of samples composed exclusively 1400

of pollen, which could be considered a suggestion for its diet specialization in 1401

nectarivory/pollinivory (Figure 7, 8). The Lonchophylla species, with their 1402

intermediate snout size, presented fecal composition more similar to G. soricina. 1403

DISCUSSION 1404

The nectar-feeding bat ensemble in this Caatinga area consists of four resident 1405

species coexisting and persisting year-round, thus flowing with the seasonal 1406

rhythm of Caatinga’s resources offer. The nectar bat species exhibit similar 1407

ecologies in sympatry yet showing subtle but significant differences in 1408

morphological attributes (weight, forearm, snout and wing aspect ratio), in 1409

capture rates within the night and also differences in resource use. The studied 1410

nectar bat ensemble presents some sort of specialization on a ‘primary’ food type 1411

(nectar and pollen of Cactaceae) while retaining omnivorous capabilities to 1412

83

exploit in different frequency supplementary food items such as insects, plant 1413

tissues and nectar of ‘secondary’ plant species. 1414

Nectar-feeding bat ensemble 1415

The nectar bat ensemble in the Caatinga of Lajes is species rich when compared 1416

to other Caatinga areas. Previous studies on the structure of bat communities in 1417

Caatinga reported ensembles of nectar bats mostly comprised by two species 1418

(Silva, Guedes & Peracchi, 2001; Gregorin et al., 2008; Beltrão et al., 2015; 1419

Soares et al., 2018a; 2018b; Feijó & Rocha 2017), three species (Sá-Neto & 1420

Marinho-Filho, 2013; Rocha et al., 2015; Silva et al., 2015) and less frequently by 1421

four (Rocha, Ruiz-Esparza & Ferrari, 2017) and five species (Cordero-Schmidt et 1422

al., 2017). 1423

The studied ensemble is mainly conformed by Lonchophyllinae species (L. 1424

mordax, L. inexpectata and Xeronycteris vieirai) and a single Glossophaginae 1425

species (Glossophaga soricina). Anoura geoffroyi (Glossophaginae) is another 1426

nectar bat species reported for several localities in Caatinga (Gregorin et al., 1427

2008; Silva et al., 2015; Rocha et al., 2017; Feijó & Rocha, 2017; Soares et al., 1428

2018b) including our study site (Cordero-Schmidt et al., 2017), withal, A. geoffroyi 1429

captures are generally low. We considered this species as "occasional" or rare 1430

species of our studied nectar bat ensemble, but due to the lack of captures during 1431

the study period our discussion of this species is limited. 1432

Glossophaga soricina is one of the most commonly encountered nectar 1433

bat species in the Neotropics (Fleming, Muchhala & Ornelas, 2005) and so it was 1434

in our study. Its flexible diet, generalized habitat requirements and its ability to 1435

defend feeding territories is what makes G. soricina successful and widespread 1436

in both preserved and highly modified habitats (Lemke, 1985; Clare et al., 2014). 1437

84

This species is the second biggest (weight and forearm) in our ensemble, it has 1438

the shortest snout and their wings showed the lowest ARI and WTI. 1439

Lonchophylla inexpectata is a recently described poorly known Caatinga 1440

endemic species (Moratelli & Dias, 2015). Moratelli & Dias (2015) stated this 1441

species was for many years misidentified as L. mordax due to their morphological 1442

resemblance, therefore we could expect that its distribution and abundance have 1443

been underestimated in other areas. Lonchophylla mordax despite being a 1444

relatively common species in Caatinga (Sá-Neto & Marinho-Filho, 2013; Rocha 1445

et al., 2015), there is little information on its biology and diet (Bredt, Uieda & 1446

Pedro, 2012). The morphological similarities between both Lonchophylla species 1447

were confirmed with our data on the species weight, forearm, ARI, WTI and snout 1448

length. However, some differences in the use of resources were observed mainly 1449

during the wettest months (higher resource availability). 1450

Xeronycteris vieirai has recently been classified as endemic to the dry 1451

diagonal crossing central Brazil including Caatinga and Cerrado (Dias & Oliveira, 1452

2019). Information on the natural history of X. vieirai has been compiled by 1453

Cordero-Schmidt et al., (2017) and Gomes et al., (2018). Its recent increase in 1454

distribution may indicate that this species is widely distributed, however it seems 1455

to be a locally rare species in some areas of Caatinga and relatively common in 1456

others (Cordero-Schmidt et al. in prep.). In comparison with the other species of 1457

nectar bats, this species is the largest (weight and forearm), it also has the 1458

longest snout and the highest ARI. This species can be classified as “obligate 1459

cactophile” (sensu Simmons & Wetterer, 2002) due to their predominantly 1460

dependence on cactus products (nectar and pollen) through the year. 1461

85

Palmer, Staton & Young (2003) stated that the mechanisms allowing 1462

species coexistence should be considered as a set of mechanisms and not as 1463

individual ones. We discuss three non-exclusive mechanisms potentially 1464

facilitating coexistence and persistence of G. soricina, L. inexpectata, L. mordax 1465

and X. vieirai in Caatinga. 1466

Temporal persistence mediated by resource availability and keystone 1467

plants 1468

Seasonal changes in the composition of nectar bats have been observed in 1469

different types of habitats in the tropics, with altitudinal or latitudinal migrations 1470

(Sosa & Soriano, 1993; Tschapka, 2004), some species behave as common 1471

persistent residents (core) and others that come and go (satellite) related to 1472

resource availability (Fleming, Muchala & Ornelas, 2005). In Caatinga, Rocha et 1473

al. (2015) observed that two species (G. soricina and L. mordax) were captured 1474

year-round, nonetheless, they were significantly more abundant in the wet 1475

season. Authors linked nectar bats year-round presence to the local abundance 1476

of specific chiropterophilic resources. We did not observe any seasonal changes 1477

in the composition and abundance of nectar bats in our studied Caatinga area. 1478

In the same way we observed available floral resources throughout the year. 1479

The continuity of the floral resources offered by plants in Caatinga has 1480

been suggested to be a plant strategy to maintain pollinator populations year-1481

round (Machado, Barros & Sampaio, 1997; Lima & Rodal, 2010; Quirino & 1482

Machado, 2014). This has been verified for populations of hummingbirds (Las-1483

Casas, Azevedo & Dias, 2012) and for bees (Novais, Absy & Santos, 2014) and 1484

now our study confirms it for nectar bats. In other semiarid areas of the 1485

neotropics, Cactaceae and Agavaceae species have been pointed as keystone 1486

86

species for maintaining nectar-feeding bat populations in lean times (Fleming, 1487

Nuñez, & Sternberg,1993; Sosa & Soriano, 1993; Petit, 1996). In our study site 1488

Pilosocereus pachycladus (Cactaceae), displayed floral resources throughout 1489

the year (though with higher resource availability in the wet season) and was the 1490

most used plant species by the four nectar bat species, besides, this cactus is 1491

one of the most abundant plant species in the area. Species of the genus 1492

Pilosocereus have been highlighted by having close relations with bats in 1493

Caatinga (Rocha, Machado & Zappi, 2007; Rocha et al., 2019). Together with P. 1494

pachycladus other additional four Cactaceae species (P. gounellei, P. 1495

chrysostele, C. jamacaru and M. zehntneri) were central plant species in the diet 1496

of the nectar bat ensemble during both seasons. We suggest that the Cactaceae 1497

family, with particular emphasis on P. pachycladus, are keystone plant resources 1498

in Caatinga. Peres (2010) described keystone species attributes such as local 1499

abundance, temporarily reliable availability of resources and extreme generalism. 1500

Most of the consumed Cactaceae present local abundance (except for C. 1501

jamacaru and P. chrysostele), year-to-year predictable phenology (comparing 1502

this study data to personal observations in the field for the past four years), plus 1503

they are consumed by all nectar bat species, in addition to other vertebrate 1504

species (Leal et al., 2017). 1505

Temporal partitioning within the night and bat mobility 1506

Temporally based resource niche partitioning, such as differences in the hours of 1507

activity in the exploration of resources is expected for bats that feed on quickly 1508

renewable resources (Aguiar & Marinho-Filho, 2004), such as nectar in the 1509

flowers. This behavior has been observed in nectar bats (Solmsen, 1998). In our 1510

study while we captured the four species of nectar bats throughout the night, 1511

87

some differences were observed suggesting that time partitioning could be a 1512

coexisting mechanism in our ensemble. Xeronycteris vieirai was the species that 1513

presented a more differentiated pattern. This species showed a low but constant 1514

capture rate throughout the night, this could be related to its size and therefore 1515

to its energy requirements and the characteristics of the nectar they are feeding 1516

off. 1517

Foraging modes and habitat use in bats are mainly determined by wing 1518

shape and size (Findley, Studier & Wilson, 1972) and by body size (Norberg, 1519

1994). A big body size and faster flight can be considered as an asset when less 1520

resources are available and sparse, (Norberg, 1994), such might be the case for 1521

X. vieirai. This species is the largest species in our study and it is also the most 1522

specialist in nectar/pollen diet. Nectar specialists are forced by flowering plants 1523

to continuously search for new nectar sources since nectar rewards are barely 1524

large enough to satisfy bats energetic requirements (Voigt & Speakman, 2007). 1525

The sugar concentration of the consumed nectar must be taking into 1526

consideration when understanding the energetics involved in increased foraging 1527

time (Ayala-Berdon et al., 2011), such as the presented by X. vieirai. Pilosocereus 1528

pachycladus was the most used plant species by X. vieirai (present in 67.54% of 1529

the samples), this species has a diluted nectar (11-17 % of sugar concentration 1530

Rocha et al., 2019). Our results are in accordance with Ayala-Berdon et al. (2011) 1531

where the volumetric intake of low sugar concentrated nectars (5-15 %) explains 1532

the increase in the total nightly feeding time. 1533

Xeronycteris vieirai showed the highest ARI (longer and slender wings), 1534

this characteristic has been discussed for other nectar-feeding bat species as the 1535

ability to fly faster and respond quickly to season changes in local resource 1536

88

availability (Sperr et al., 2011). During the dry season (less resource available) in 1537

our study, X. vieirai was the species that fed the most on H. neesianus and 1538

Pseudobombax type, these plant species were not observed within our 1539

phenology transects, nor close to our sampling sites (˜5 km), suggesting X. vieirai 1540

is capable of flying longer distance looking for resources. 1541

The lower ARI (shorter and wider wings) presented by G. soricina, L. 1542

inexpectata and L. mordax may promote lift at low speeds and ease maneuvering 1543

(Findley, Studier & Wilson, 1972). Even small differences in wing proportions 1544

between nectar bats have proven to be particularly important in the energy 1545

demanding foraging efficiency (Tschapka, 2004). Melocactus zehntneri, D. ciliaris 1546

and R. asperula are ornithophilic species with smaller and more delicate flowers 1547

when compared to a typical chiropterophilus species with big and robust flowers. 1548

Feeding on these small flowered species probably would require better hovering 1549

aptitudes (Fleming and Muchhala, 2008) such as the observed in G. soricina, and 1550

the Lonchophylla species inferred by their ARI values. Moreover, capture rate of 1551

these species is higher during the first hour after sunset (18:00 hrs.); to be able 1552

to feed on the nectar of the mentioned ornithophilic species, bats must visit them 1553

right after they start foraging. The nectar of these plant species could be the right 1554

intake nectar bats need to get their night started. Welch & Suarez (2008) found 1555

that G. soricina can use recently ingested sugars to provide ∼78% of the fuel 1556

required for oxidative metabolism during their energetically expensive hovering 1557

flight. 1558

Although studies on the energy requirements and foraging of each species 1559

in relation to the spatial and temporal availability of resources are necessary, the 1560

nightly temporal partitioning together with morphological differences (weight size 1561

89

and wing indexes) observed in the four nectar bat species could be supporting 1562

another mechanism of coexistence for nectar bats in Caatinga. 1563

Resource partitioning and use mediated by ecomorphological differences 1564

Ecomorphological patterns between plant-pollinator reflects at least two 1565

processes: interspecific competition and mutualistic coevolution (Palmer, Stanton 1566

& Young, 2003). These processes are common among coexisting hummingbird 1567

species and have been proven to be rare or absent for nectar bat species (von 1568

Helversen & Winter, 2005). Yet, small morphological differences may allow 1569

sympatric nectar bats to exploit different microhabitats, resulting in the 1570

consumption of different food items and resource partitioning (Tschapka, 2004; 1571

Gonzales-Terrazas et al., 2012). In our study bats are feeding on pollen, insects 1572

and other unidentified plant tissues with regularity along the different seasons 1573

and some species-specific differences in use of these items were observed 1574

indicating a possible resource partitioning strategy, 1575

-Snout length and diet composition 1576

Lonchophylla inexpectata, L. mordax and X. vieirai included more insects during 1577

the wet season coinciding with the insect’s maximum abundance in Caatinga 1578

(Vasconcellos et al., 2010). On the other hand, G. soricina consumed similar 1579

proportion of insects during both seasons. Clare et al. (2014) determined that G. 1580

soricina’s diet flexibility is explained by both morphology (shorter snout and high 1581

maneuverability ease by low wing ARI) and sensory characteristics (low-intensity 1582

echolocation). Species with shorter snout vary their diet the most contrary to 1583

longer snouts with a more nectar restricted diet (Solmsen, 1998). 1584

The diet and snout of X. vieirai differentiated the most when compared to 1585

the other nectar bat species. Even though X. vieirai also feeds on insects, it does 1586

90

so in a smaller proportion as the other nectar bat species, also explained by the 1587

extremely reduced dentition (Nogueira et al., 2014) in comparisson to the other 1588

studied nectar bat species. Further, it seems to be the most specialized in nectar 1589

feeding which coincides with the inference made by Gregorin and Ditchfield 1590

(2005) and Cordero-Schmidt et al. (2017). Xeronycteris vieirai was also the 1591

species that included pollen in its diet the most (in 63.63% of the samples) and 1592

through the year. Pollen is an important source of proteins, vitamins, and 1593

minerals, but the efficiency digestion of pollen contents is different within bat 1594

species (Herrera & Martínez, 1998). Authors stated that bat species that regularly 1595

include pollen in their diet, as the case of X. vieriai in our study, should be more 1596

efficient at extracting pollen contents than species that ingest pollen only 1597

seasonally presenting another hint of resource partitioning as a coexistence 1598

facilitator. 1599

Glossphaga soricina complemented its nectar-feeding diet with pollen, 1600

insects and other plant tissues, it was the only species that fed on P. pachycladus 1601

fruits. We expected to find more evidence of fruit use as it is a resource commonly 1602

used by nectarivorous bats when nectar resources are scarce (Fleming, Nuñez 1603

& Sternberg, 1993; Godínez-Alvarez & Valiente-Banuet, 2000), but since there is 1604

nectar and pollen are available through the year, it seems that nectar bat species 1605

can rely on a flower-resource based diet. 1606

-Nectar sugar concentration and resource use 1607

Tschapka, Gonzales-Terrazas & Knörnschild (2015) proposed that differences in 1608

nectar efficiency extraction linked to different tongue morphologies between 1609

species belonging to Glossophaginae and Lonchophyllinae could mediate other 1610

coexistence mechanism; where Glossophaginae species would feed more on 1611

91

high sugar concentration nectar extracted more efficiently with ‘viscous dipping’ 1612

mechanism, contrary to Lonchophyllinae feeding on low sugar concentration 1613

nectar using a ‘pumping-tongue’ mechanism. Our data does not demonstrate a 1614

clear pattern with respect to this taxonomic mediated coexistence mechanism, 1615

since most plant species with different sugar concentration are used by both 1616

subfamilies with a similar frequency. Nonetheless, when looking into species-1617

specific capacity to reach energetic balance it can be elucidated by the resources 1618

the nectar bat species are feeding on considering the nectar’s sugar 1619

concentration and composition (Ayala-Berdon et al., 2011). Authors highlighted 1620

two mechanisms to obtain energy balance ‘Compensatory feeding’ where 1621

species maintain a constant energy intake in spite of food quality. The species 1622

with this type of energetic balance generally feeds on high sugar concentrated 1623

nectar but also present a wider nectar niche. This could be the case of L. mordax 1624

who feeds the most on the two plant species that presented the highest sugar 1625

concentration (C. jamacaru 30%, and R. aperula 29.25%), at the same time L. 1626

mordax also feeds on more plant species (23) when compared to the other nectar 1627

bats (20-21 plant species). 1628

The uncoupled observed activity dynamic of G. soricina with L. inexpectata 1629

and L. mordax, together with the fact that is the nectar bat species that feed 1630

mostly of low sugar concentrated plant species, might be in accordance to 1631

‘Physiological constrains’ mechanism proposed by Ayala-Berdon & Schondube 1632

(2011). Physiological constrains occurs when species limit the amount of energy 1633

they obtain when feeding on dilute nectars (i.e. less than 15% sugar 1634

concentration). Authors explained that species feeding on dilute nectar must visit 1635

more flowers but at the same time they should also reduce their flight time, finding 1636

92

this way an energetic balance. It would be expected that species with this 1637

physiological constrains will forage in smaller areas with high resource 1638

abundance (Ayala-Berdon et al., 2011). To further conclude energy-mediated 1639

coexisting mechanisms, future studies should focus on better characterizing the 1640

plant specie’s nectar concentration and composition, as well as exploring the 1641

physiological constrains such as gut size, sugar absorption and digestion rates 1642

and water absorption. This energetic characterization of resource use, as well as 1643

observations on foraging behavior would give us valuable information about the 1644

role of nectar bat species in pollen movement and pollination in Caatinga. 1645

Pollination focused studies are urgent since Caatinga suffers from intense 1646

and chronic degradation and vegetation destruction since it is inhabited by 1647

approximately 28.6 million people (Silva et al., 2018). The destruction of the 1648

native vegetation results in the decrease in food resources for different animal 1649

populations, and consequently have a dramatical effect in the environmental 1650

services provided by them (Kearns & Inouye, 1997). 1651

CONCLUSIONS 1652

With this study we were able to have the first insight on the mechanisms of 1653

persistence and coexistence of four species of nectar bats in Caatinga. The 1654

mechanisms detected are complementary and seem to be explained by temporal 1655

partitioning (differences in captures throughout of the night), by ecomorphological 1656

differences (size, weight, snout length, wing aspect ratio) and by resource 1657

partitioning (diet flexibility). The four species of nectar bats present a flexible diet, 1658

consuming more than 20 species of plants with different concentrations of sugar 1659

and with both, chiropterophilic and non-chiropterophilic characteristics. They also 1660

include pollen, insects and other plant tissues. On the other hand, contrary to our 1661

93

expectations, there were no changes in species composition mechanism in the 1662

period of least available resources. Additionally, no evidence of an evolutionary 1663

mediated mechanism (differences in nectar concentration linked to nectar bat 1664

subfamily) was found. 1665

The temporal persistence of nectar bats was facilitated by the continuity 1666

and complementarity of floral resources available during both seasons, however 1667

we highlight the importance of the Cactaceae family in Caatinga. Cacti should be 1668

considered keystone resources and therefore conservation initiatives should 1669

consider sites with high abundance and diversity of Cactaceae as a conservation 1670

priority. 1671

1672

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105-111. 1941

1942

105

1943 1944 Figure 1. Local nectar-feeding bat guild: A. Glossophaga soricina; B. 1945 Lonchophylla inexpectata; C. Lonchophylla mordax; D. Xeronycteris vieirai. 1946 1947 1948

1949 1950 Figure 2. Graphic representation of the first two axes of a NMDS performed for 1951 all species of nectar-feeding bats captures between years (A) and seasons (B) 1952 first axis retained 68.6% of the total variation and second axis 45.3% 1953 Stress=0.096. 1954 1955

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1956 1957 Figure 3. Capture rates from 18:00 to 24:00. A. Nectar-feeding bat capture 1958 composition per hour, and B. Captured individuals for each species. 1959

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Table 1A. Morphological measurements (W= Weight, FA= Forearm, ARI=Aspect 1960 Ratio Index, WTI=Wing Tip Index and snout) of the four nectar-feeding bat 1961 species. N= individuals with data, B. ANOVA of morphological measurements of 1962 the four nectar-feeding bat species. 1963 1964

A. Glossophaga soricina Lonchophylla inexpectata W (g) FA (mm) ARI WTI Snout W (g) FA (mm) ARI WTI Snout N 117 126 126 126 126 65 69 69 69 69 Minimum 5.00 30.00 1.26 1.34 6.00 5.00 31.00 1.26 1.37 8.00 Maximum 17.00 39.50 2.27 2.23 10.00 13.00 38.00 2.31 2.16 10.00 Mean 9.98 35.89 2.11 1.83 7.33 8.47 35.06 2.11 1.84 8.99 SD 1.29 1.26 0.12 0.09 0.56 1.10 1.46 0.12 0.10 0.70

Lonchophylla mordax Xeronycteris vieiriai W (g) FA (mm) ARI WTI Snout W (g) FA (mm) ARI WTI Snout N 90 107 107 107 107 68 74 74 74 74 Minimum 5.00 23.30 1.76 1.32 7.00 6.50 35.50 2.08 1.69 11.00 Maximum 11.50 38.00 2.33 2.88 11.00 16.00 40.50 2.45 2.06 14.00 Mean 8.73 35.38 2.12 1.85 8.84 11.87 38.47 2.17 1.90 11.99 SD 1.21 1.67 0.07 0.13 0.66 1.77 0.96 0.05 0.05 0.55

1965

B. Type III SS df Mean

Squares F-ratio p-value R2 Parwise difference

Weight 579.99 3 193.33 78.42 <0.001 0.39 Xv > Gs > Li =Lm Error 917.13 372 2.47

Forearm 551.08 3 183.69 96.50 <0.001 0.44 Xv > Gs > Li =Lm Error 708.15 372 1.90

ARI 0.20 3 0.07 7.64 <0.001 0.06 Xv > Lm = Li = Gs Error 3.29 372 0.01

WTI 0.07 3 0.02 1.22 0.31 0.01 Equal Error 7.09 372 0.02

Snout 1018.92 3 339.64 896.38 <0.001 0.88 Xv > Li = Lm > Gs Error 140.96 372 0.3789

1966 1967

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1968 D 1969

1970 1971 Figure 4. Circular histogram of monthly (except May 2018) flowering phenology. 1972 The height of the bars represents the number of species in bloom per month. A. 1973 All studied plant species. B. Four chiropterophilous plant species: Pilosocereus 1974 chrysostele, P. gounellei, P. pachycladus and Tareyana spinosa. C. Five non-1975 chiropterophilous species: R. asperula, T. aurea, C. jamacaru, M. zehntneri and 1976 J. mollissima. D. Linear representation of flowering phenology of nine plant 1977 species in Caatinga. The solid line indicates the moments where > 50% of the 1978 monitored individuals had flowers; Dotted line indicates moment where < 50% of 1979 individuals had flowers; Blank sections indicate individuals with no observed 1980 available flowers. 1981 1982 Table 2. Circular statistical analyses testing for the occurrence of seasonality on 1983 flowering phenological behavior of nine plant species in Caatinga. The average 1984 date (angle) is the time of the year around which the dates of flowering occurred 1985 for most species. Rayleigh test was performed for significance of the mean angle. 1986 1987

Plants N Average date (Angle) r Z Rayleigh

(p) Rao (p)

Chiropterophilous 33 86.21 0.120 0.475 . <0.001

Non-chiropterophilous 30 6.97 0.124 0.467 0.630 .

All 63 47.93 0.094 0.559 0.571 . 1988 1989

Chiropterophilous Dec17 Jan18 Feb18 Mar18 Apr18 May18 Jun18 Jul18 Aug18 Sep18 Oct18 Nov18

Tareyana spinosaPilosocereus chrysostele

Pilosocereus gounellei Pilosocereus pachycladus

Non-Chiropterophilous

Ruellia asperulaTabebuia aurea

Cereus jamacaruMelocactus zehntneri

Jatropha mollissima

109

1990

Family Plant species G. soricina

n=140 L. inexpectata

n=87 L. mordax

n=120 X. vieirai

n=96 Flower

size (mm) *Blossom

class Nectar volume

(μl) Sugar

concentration (%) Reference

Acanthaceae Dicliptera ciliaris 19.29 8.05 8.33 2.08 20 Flag . . Gomes, Quirino & Machado, 2014

Harpochilus neesianus . . 2.50 3.13 70-90 Gullet 46-72 26-29 Vogel, Machado & Lopes, 2004

Harpochilus paraibanus 25.71 12.64 15.00 4.17 40 Gullet . . Monteiro, Fernando, Lucena& Melo, 2018 Ruellia asperula 2.14 4.60 13.33 . 22.3-28.7 Gullet . 25-33,5 Leal, Lopes & Machado, 2006

Bignoneaceae Tabebuia aurea 11.43 9.20 15.00 7.29 65 Bell-funnel 3.2-5.0 25.9-27 Barros, 2001

Bromeliaceae Encholirium spectabile 20.00 8.05 17.50 16.67 24 Dish-bowl 190.3 ± 98.5 16.58 ± 8.56 Queiroz, Quirino, Lopes & Machado, 2016

Cactaceae Cereus jamacaru 25.00 27.59 35.00 18.75 200-300 Tube . 30 Anderson & Brown, 2001 Melocactus zehntneri 13.57 27.59 25.00 16.67 11.5-15.5 Tube 41 ± 1,18 27 ± 0,57 Locatelli & Machado, 1999

Pilosocereus chrysostele 22.86 12.64 13.33 27.08 45 ± 2,7 Tube 755 19 ± 7 Rocha et al., 2019 Pilosocereus gounellei 27.86 50.57 47.50 47.92 71,8 ± 7,1 Tube 365 23 ± 11 Rocha et al., 2019

Pilosocereus pachycladus 47.85 42.53 56.67 63.54 67,4 ± 3,9 Bell-funnel 1643 14 ± 4 Rocha et al., 2019 Cynophalla hastata 6.43 2.30 8.33 1.04 30 Head-brush . . Soares Neto & Jardim, 2015

Cleomaceae Tarenaya spinosa 33.57 29.89 28.33 18.75 10 Dish-bowl 116.9 ± 25.95 15.56% ± 4.75 Machado, Lopes, Leite & de Brito Neves, 2006

Convolvulaceae Ipomea sp. 1.43 9.20 8.33 4.17 . . . . . Euphorbiaceae Jatropha mollissima . 3.45 1.67 1.04 5 Dish-bowl 107 ± 36,8 24,85 ± 1,07 Viana, Neves & MachadoI, 2011

Fabaceae Bauhinia cheilantha 4.29 4.60 5.00 5.21 50-60 Flag . . Fonseca & Azevedo Tozzi, 2003

Bauhinia pentandra 0.71 5.75 9.17 3.13 40-50 Flag . . Fonseca & Azevedo Tozzi, 2003

Coursetia rostrata 4.29 1.15 . 1.04 30-35 Flag . . Lavin, 1988

Fabaceae sp1 0.71 2.30 0.83 3.13 . . . . . Malvaceae Helicteres baruensis 23.57 28.74 25.00 15.63 30 Flag 77.3 ± 64.99 10.1-16 Goldberg, 2009

Pseudobombax sp. 3.57 5.75 7.50 13.54 . . . . . Xanthorrhoeaceae Aloe vera 0.71 . 0.83 . 26-34 Tube 37 13.6-20.9 Velásquez-Arenas & Imery-Buiza, 2008

. Indeterminada 2 0.71 . . 1.04 . . . . .

. Monocot sp1 0.71 . 0.83 . . . . . . *Following Fægri, K. & van der Pijl, L. 1971. The Principles of Pollination Ecology. Pergamon Press, Oxford.

Table 3. Percentage of samples of each nectar bat species that contained each plant species, plus flower and nectar characteristics of the used plant species.

110

Table 4. Bray-Curtis dissimilarity matrix comparing diet between nectar-feeding 1991 bat species based on pollen samples. Darker blue and highest value indicate the 1992 most dissimilar diets, whilst darker red and lowest value indicate the most similar 1993 diets. GS: Glossophaga soricina, LI: Lonchophylla inexpectata, LM: Lonchophylla 1994 mordax and XV: Xeronycteris vieirai. 1995 1996

1997 1998 1999 Table 5. Results of Correspondence Analysis of the relationships between four 2000 species of nectar-feeding bat and the 24 plants species they feed on in the dry 2001 and wet season. 2002 2003

2004 2005

GS_DRY LI_DRY LM_DRY XV_DRY GS_WET LI_WET LM_WETGS_DRYLI_DRY 0.41LM_DRY 0.33 0.22XV_DRY 0.37 0.32 0.32GS_WET 0.47 0.58 0.46 0.53LI_WET 0.47 0.41 0.38 0.45 0.29LM_WET 0.52 0.54 0.54 0.59 0.33 0.29XV_WET 0.53 0.49 0.43 0.41 0.37 0.31 0.36

Axis 1 2 3 4 5 6 7Eigenvalue 0.21 0.05 0.05 0.03 0.03 0.01 0.01% of total 54.25 13.46 12.15 8.04 6.91 3.48 1.71

Cumulative 54.25 67.71 79.86 87.91 94.81 98.30 100.00

111

2006

Figure 5. Axes 1 and 2 of Correspondence Analysis of matrix of nectar-feeding 2007 bats and the 24 plant species they feed on in the dry and wet season. Axis 1 2008 explains 54.2% and axis 2 explains 13.4%. Gs: Glossophaga soricina; Li: 2009 Loncophylla inexpectata; Lm: Lonchophylla mordax and Xv: Xeronycteris vieirai. 2010 Numbers refer to plant species used by bats: 1. Aloe vera, 2. Bauhinia cheilantha, 2011 3. Bauhinia pentandra, 4. Cereus jamacaru, 5. Coursetia rostrata, 6. Cynophalla 2012 hastata, 7. Dicliptera ciliaris, 8. Encholirium spectabile, 9. Fabaceae sp1, 10. 2013 Harpochilus neesianus , 11. Harpochilus paraibanus, 12. Helicteres baruensis, 2014 13. Indeterminada2, 14. Ipomoea sp1, 15. Jatropha mollissima, 16. Melocactus 2015 zehntneri, 17. Monocot sp1, 18. Pilosocereus chrysostele, 19. Pilosocereus 2016 gounellei, 20. Pilosocereus pachycladus, 21. Pseudobombax sp, 22. Ruellia 2017 asperula, 23. Tabebuia aurea, and 24. Tarenaya spinosa. 2018 2019

-2 2EX1

-2

-1

1

2EX2

Gs_DRYLi_DRY

Lm_DRY

Xv_DRY

Gs_WET

Lm_WET

Xv_WET

1

23

4

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6

7

8

9

1011

12

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15 16

17

18

19 20

21

22

23 24

Li_WET

Used plantsBat_WET seasonBat_DRY season

112

Figure 6. Axes 2 and 3 of Correspondence Analysis of matrix of nectar-feeding 2020 bat and the 24 plants species they feed on in the dry and wet season. Axis 2 2021 explains 13.4% and axis 3 explains 12.1%. Gs: Glossophaga soricina; Li: 2022 Loncophylla inexpectata; Lm: Lonchophylla mordax and Xv: Xeronycteris vieirai. 2023 Numbers refer to plant species used by bats: 1. Aloe vera, 2. Bauhinia cheilantha, 2024 3. Bauhinia pentandra, 4. Cereus jamacaru, 5. Coursetia rostrata, 6. Cynophalla 2025 hastata, 7. Dicliptera ciliares, 8. Encholirium spectabile, 9. Fabaceae sp1, 10. 2026 Harpochilus neesianus , 11. Harpochilus paraibanus, 12. Helicteres baruensis , 2027 13. Indeterminada2, 14. Ipomoea sp1, 15. Jatropha molíssima, 16. Melocactus 2028 zehntneri, 17. Monocot sp1, 18. Pilosocereus chrysostele, 19. Pilosocereus 2029 gounellei, 20. Pilosocereus pachycladus, 21. Pseudobombax sp, 22. Ruellia 2030 asperula, 23. Tabebuia aurea, and 24. Tarenaya spinosa. 2031 2032 Table 6. ANOSIM for differences in diet composition among the different nectar-2033 feeding bat species. 2034

2035 G. soricina L. inexpectata L. mordax

L. inexpectata 0.3293 L. mordax 0.1622 0.3658 X. vieirai 0.1687 0.0553 0.0124

2036

-2 1 2EX2

-2

2

3EX3

Gs_DRY

Li_DRY

Lm_DRY

Xv_DRY

Gs_WET

Li_WET

Lm_WET

Xv_WET

1

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3

4

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6

78

9

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Used plantsBat_WET seasonBat_DRY season

113

Table 7. Plant species consumed by the nectar-feeding bats and its relative contribution to the Bray-Curtis dissimilarity index; values 2037 calculated by the SIMPER Method. Values for each species are mean abundances. First eight species (grey background) explains 2038 54.3% of the dissimilarity in the bat species. 2039 2040

2041

Pollen type Av. dissim Contrib. %

Cumulative %

Mean Gs_DRY

Mean Li_DRY

Mean Lm_DRY

Mean Xv_DRY

Mean Gs_WET

Mean Li_WET

Mean Lm_WET

Mean Xv_WET

Cereus jamacaru 2.61 8.23 8.23 5.58 4.76 6.61 3.47 13.70 12.40 14.40 10.80Pilosocereus pachycladus 2.61 8.23 16.46 14.50 11.40 16.30 19.40 19.20 16.30 16.60 27.50Helicteres baruensis 2.29 7.23 23.69 7.43 9.52 5.73 6.25 0.00 0.00 0.00 0.00Pilosocereus gounellei 2.11 6.65 30.33 9.29 15.20 13.20 16.70 9.59 18.30 14.40 18.30Encholirium spectabile 1.98 6.24 36.57 8.92 5.71 5.73 7.64 0.69 1.31 0.54 1.67Tarenaya spinosa 1.95 6.16 42.74 13.80 9.52 11.00 9.03 6.85 10.50 4.81 4.17Harpochilus paraibanus 1.88 5.93 48.67 8.92 2.86 3.52 2.08 8.90 9.80 9.09 5.00Harpochilus neesianus 1.79 5.64 54.30 0.00 0.00 0.00 0.69 8.22 5.23 5.35 0.83Pilosocereus chrysostele 1.62 5.11 59.41 7.06 3.81 3.96 9.72 8.90 4.58 3.74 10.00Pseudobombax sp. 1.54 4.87 64.28 1.86 4.76 3.52 7.64 0.00 0.00 0.54 1.67Tabebuia aurea 1.52 4.81 69.08 4.83 6.67 6.17 4.86 2.05 0.65 2.14 0.00Ipomea sp. 1.51 4.76 73.84 0.74 7.62 4.41 2.78 0.00 0.00 0.00 0.00Melocactus zehntneri 1.35 4.24 78.08 3.72 7.62 5.73 4.86 6.16 10.50 9.09 7.50Ruellia asperula 1.21 3.81 81.89 1.12 2.86 7.05 0.00 0.00 0.65 0.00 0.00Dicliptera ciliaris 1.20 3.78 85.67 6.69 1.90 2.64 0.69 2.74 0.65 4.28 4.17Cynophalla hastata 1.02 3.23 88.90 2.60 0.95 3.08 0.69 6.16 3.27 2.14 0.83Bauhinia pentandra 0.99 3.14 92.03 0.00 1.90 0.44 0.00 0.69 1.96 5.35 2.50Bauhinia cheilantha 0.94 2.95 94.99 0.00 0.00 0.88 0.69 4.11 2.61 2.14 3.33Coursetia rostrata 0.47 1.47 96.45 2.23 0.95 0.00 0.69 1.37 0.65 1.60 0.00Fabaceae sp1 0.39 1.23 97.68 0.00 0.00 0.00 0.69 0.00 0.00 1.60 1.67Jatropha mollissima 0.38 1.21 98.89 0.00 1.90 0.00 0.69 0.00 0.65 1.07 0.00Aloe vera 0.13 0.42 99.31 0.00 0.00 0.00 0.00 0.69 0.00 0.54 0.00Indeterminada 2 0.12 0.38 99.68 0.37 0.00 0.00 0.69 0.00 0.00 0.00 0.00Monocot sp1 0.10 0.32 100.00 0.37 0.00 0.00 0.00 0.00 0.00 0.54 0.00

114

2042 Figure 7. Percentage of fecal samples of each nectar-feeding bat species 2043 with different contents. Gs: Glossophaga soricina Ndry=9, Nwet=14; Li: Lonchophylla 2044 inexpectata Ndry=11, Nwet=22; Lm: Lonchophylla mordax Ndry=8, Nwet=21; 2045 Xeronycteris vieirai Ndry=22, Nwet=18. Examples of each category type A. Sample 2046 with at least three pollen types. B. At least two pollen types, insect fragments and moth 2047 scales. C. One pollen type and unidentified green plant tissue. D. Pollen types, moth 2048 scales and unidentified plant tissue. 2049 2050

2051 Figure 8. Relationship between the snout length of the four nectar-feeding bat species 2052 and their diet considering fecal contents. Fecal composition index included three 2053 categories (A. Pollen; B. Pollen & Insects; C. Mix). 2054

115

SUPPORTING INFORMATION 2055 2056 Table S1. Plant species with flowering data (N), growth habit and the relative 2057 abundance of each species in the 15 transects in Lajes, RN. 2058 2059

2060 2061 Table S2. Comparison between capture rates between seasons (dry and wet) and the 2062 four species of nectarivorous bat in the municipality of Lajes RN 2063 2064

Source Type III SS df Mean Squares F-ratio p-value

Season 0.32837 1 0.32837 0.65581 0.42071 Bat species 1.06774 3 0.35591 0.71083 0.54869 Season*Bat

species 0.70723 3 0.23574 0.47083 0.70356

Error 36.05082 72 0.50071 2065 Table S3. Pearson correlation of the capture rates of each nectarivorous bat species 2066 in the municipality of Lajes, RN. Bold values represent significant correlations after the 2067 Bonferroni criterion is applied 2068 2069

G. soricina L. inexpectata L. mordax L. inexpectata 0.50

L. mordax 0.53 0.71

X. vieirai 0.57 0.83 0.69 2070 2071

Family Species Pollination syndrome N AbundanceAcanthaceae Ruellia asperula (Mart. ex Nees) Lindau Ornithophily 2 20Bignoniaceae Tabebuia aurea (Silva Manso) Benth. & Hook.f. ex S.Moore Melittophily 2 5Cactaceae Cereus jamacaru DC. Phalaenophily 9 17

Pilosocereus gounellei (F.A.C.Weber) Byles & Rowley Chiropterophily 40 341Pilosocereus pachycladus F.Ritter Chiropterophily 64 369Pilosocereus chrysostele (Vaupel) Byles & G.D.Rowley Chiropterophily 6 20Melocactus zehntneri (Britton & Rose) Luetzelb. Ornithophily 12 53

Cleomaceae Tarenaya spinosa (Jacq.) Raf. Chiropterophily 5 236Euphorbiaceae Jatropha mollissima (Pohl) Baill. Melittophily/Psychophily 12 302

116

Table S4. MANOVA of the bat composition between years (A) and seasons (B) at 2072 Caatinga in Lajes, Northeast Brazil. 2073 2074

A. Years 2075

2076 B. Seasons 2077

2078 2079 Table S5. Spearman Correlation Matrix between nectar bats captured within the night 2080 2081 Species NMDS I NMDS II G. soricina -0.784 0.122 L. inexpectata -0.669 0.137 L. mordax -0.704 -0.080 X. vieirai -0.448 0.409 Total -0.774 0.163

2082 2083 2084 2085

Source Type III SS df Mean Squares F-ratio p-value

NMDS I 0.01335 1 0.01335 0.43946 0.51627 Error 0.51639 17 0.03038

NMDS II 0.00294 1 0.00294 0.16821 0.68683 Error 0.29733 17 0.01749

Wilks's Lambda=0.96393; F=0.29939; df=2,16; p=0.74533

Source Type III SS df MS F-ratio p-value

NMDS I 0.00952 1 0.00952 0.31455 0.58182 Error 0.54486 18 0.03027

NMDS II 0.01999 1 0.01999 1.25251 0.27779 Error 0.28729 18 0.01596

Wilks's Lambda=0.91777; F=0.76156; df=2,17; p=0.48222

117

2086 Figure S6. Accumulation curve of pollen types present in the diet of each nectarivorous 2087 bat species. 2088 2089

2090 Figure S7. Percentage of resource used by Glossophaginae (G. soricina) and 2091 Lonchophyllinae (L. inexpectata, L. mordax and X. vieirai) species organized by the 2092 plant’s nectar sugar concentration ranging from the highest 30% to the lowest 13% .2093 2094 2095

118

2096

119

2097

C H A P T E R 3 2098

2099

Female reproduction patterns in Caatinga are influenced by precipitation and 2100

Cactaceae resource availability 2101

2102

Eugenia Cordero-Schmidt1, Juan Carlos Vargas-Mena1, Bernal Rodriguez-Herrera3 2103

and Eduardo M. Venticinque1 2104 2105 1Departamento de Ecologia, Universidade Federal do Rio Grande do Norte, 59078900 2106

Lagoa Nova Natal, RN, Brazil; E-mail: ecordero.s@gmail.com 2107 2Escuela de Biología, Universidad de Costa Rica, 2060 Montes de Oca, San José, 2108

Costa Rica 2109

2110

120

ABSTRACT 2111 2112 The life history strategies of animals are significantly determined by the frequency and 2113 timing of their reproductive events (Crichton & Krutzsch, 2000), but reproduction is not 2114 an easy task or cheap one and it is influenced by abiotic and biotic factors. Considering 2115 that sympatric species with similar adaptations and food habits provide ideal models 2116 for comparative studies in reproduction, in this study we aim to describe the 2117 reproductive patterns of G. soricina, L. inexpectata, L. mordax and X. vieirai, and 2118 answer three main questions: 1. What is the effect of: A. precipitation and B. 2119 Cactaceae flowers availability on the reproductive patterns of the species? 2. Do they 2120 affect differently the four nectar bat species? 3. Will the diet composition (pollen types 2121 load and other items in fecal samples) be different among nectar-feeding female bats 2122 according to the reproductive status in which they are found? We detected two types 2123 of reproductive patterns for the nectar bat species in Caatinga, bimodal pattern in G. 2124 soricina and apparently L. inexpectata and polymodal in L. mordax and X. vieirai. 2125 Precipitation positively affected the probability of occurrence of pregnancy for L. 2126 mordax and X. vieirai, but not for G. soricina (none of the tested variables influenced 2127 the pregnancy of G. soricina. The availability of floral resources of Cactaceae from the 2128 previous month, positively affected the probability of occurrence of lactation for all 2129 nectar bat species, with some differences of significance for certain cacti species. The 2130 fate of both nectar bats and Cactaceae in Caatinga are closely linked and so are the 2131 other animals that also depended on these keystone resources, including people. 2132 Conservation initiatives should consider areas with high abundance and diversity of 2133 Cactaceae as a priority. 2134 2135

Keywords: Chiroptera; Diet; Phenology; Seasonal Dry Tropical Forest; Resource 2136

partitioning 2137

121

GRAPHICAL ABSTRACT 2138

BIMODAL- Glossophaga soricina- Lonchophylla inexpectata

POLYMODAL- Lonchophylla mordax

- Xeronycteris vieirai

Wet season only

Mostly wet season, few dry months

Year-round

FLO

WER

ING

Pregnancy - P Lactation - L

DRYWET

122

INTRODUCTION 2139

Essentially all species have the same purpose in life, to reproduce and pass their genes 2140

from generation to generation, but this is not an easy task, nor a cheap one. Bats life-2141

history is characterized by longevity, multiple reproductive events, delayed sexual 2142

maturity and small litters with one to two well developed (up to 43% of maternal body 2143

mass) offspring (Kurta & Kunz, 1987). 2144

After decades of study on animal reproduction, scientists identified the factors 2145

triggering reproductive periods, and also the ones limiting them. For bats, calcium (for 2146

skeletal growth), nitrogen (protein) and energy (carbohydrates and fat) are three 2147

fundamental factors during pregnancy but mainly during lactation considering it is the 2148

most energetically costly phase of the reproductive cycle (Barclay, 1994; Racey et al., 2149

2000; Voigt, 2003). From a nutritional and physiological perspective, nectar-feeding 2150

bat’s reproduction is noteworthy as their main diet is composed by carbohydrates and 2151

for them to meet the nutritional constrains, they are required to ingest more food and 2152

complement it with protein rich pollen and insects (Herrera et al., 2001; Tschapka, 2153

2005). 2154

Bat reproduction triggering factors vary according to latitude and habitat types 2155

(Racey & Entwistle, 2000). In temperate areas, photoperiod and temperature are 2156

determinant aspects, in the tropics precipitation is fundamental, but in all regions, 2157

parturitions are synchronized with periods of greater resource availability (Fleming, 2158

Hooper & Wilson, 1972; Sperr et al., 2011). This synchrony is expected to be even 2159

more strong in habitats where food resources vary seasonally (Fleming, Hooper & 2160

Wilson, 1972), such as in Caatinga (Machado, Barros & Sampaio, 1997). 2161

Willig (1985) first described the reproduction patterns of bats in Caatinga and 2162

noted that the long-term pattern of rainfall seems to be the dominant factor molding 2163

123

bats reproductive patterns. In other Seasonally Dry Tropical Forests (SDTF) 2164

reproduction of nectar-feeding bats (hereafter ‘nectar bats’) have been intimately 2165

linked to cactus resources (nectar, pollen and fruits) availability (Sosa & Soriano, 1996; 2166

Petit, 1997; Martino, Arends & Aranguren, 1998). Authors highlighted the dependence 2167

on nectar bats reproduction on cactus and vis versa. 2168

Cactaceae is a family endemic to America (Anderson, 2001) and Brazil stands 2169

out as one of the countries with greatest cactus diversity. It has 270 species (70.4% 2170

are endemic) of which 97 species occur in Caatinga (43.2% are endemic) (Taylor and 2171

Zappi, 2002; Ortega-Baes and Godínez-Alvarez, 2006). Cactaceae reproductive 2172

phenology in SDTFs is known to be affected by precipitation both negative or positive, 2173

or even neutrally for different cacti species (Petit, 2001; Cruz & Pavón, 2013), but this 2174

information about Caatingas’ cacti is scarce. 2175

Four basic reproductive patterns have been stablished characterizing the 2176

number of peaks in the proportion of pregnant (hereafter ‘P’) females in a population 2177

of a species or ensemble and the associated lactating (hereafter ‘L’) peaks, if more 2178

than one peak is observed they can be classified as primary and secondary as 2179

suggested by Durant et al. (2013). The patterns are: Amodal (absence of peaks in 2180

pregnancy or lactation); Unimodal (one annual P peak followed by one L peak); 2181

Bimodal (two P peaks associated with two L peaks); and Polymodal (≥ 3 P peaks 2182

accompanied by L peaks). To date, most information on the reproductive patterns of 2183

Neotropical nectar bats have been gathered for SDTFs and provided information for 2184

four genus Glossophaga, Leptonycteris and on less stand for Anoura and 2185

Musonycteris (Fleming et al., 1972; Ramirez-Pulido et al., 1993; Sosa & Soriano, 2186

1996; Petit 1997; Martino et al. 1998; Sperr et al., 2011; but see Zortea, 2003; 2187

Tschapka, 2005 for other habitat type). Most nectar bats present seasonal bimodal 2188

124

polyestrous pattern. Willig (1985) presented pioneering data on G. soricina 2189

reproduction in Caatinga, and only little information has been recently added for the 2190

Vieira’s flower bat (Cordero-Schmidt et al., 2017). 2191

Glossophaga soricina, Lonchophylla inexpectata, Lonchophylla mordax and 2192

Xeronycteris vieiria has been documented to persist and coexist in an area of Caatinga 2193

in the state of Rio Grande do Norte (RN) in northeast Brazil (Cordero-Schmidt et al., 2194

in prep. here Chapter 2). Their diet is composed by at least 31 plant species belonging 2195

to 14 families. Withal, the most used plant family for the four nectar-feeding bats 2196

species was Cactaceae. In this same Caatinga area, at least seven species of cacti 2197

coexist, Cereus jamacaru DC, Pilosocereus chrysostele (Vaupel) Byles & 2198

G.D.Rowley, Pilosocereus gounellei (F.A.C.Weber) Byles & Rowley, Pilosocereus 2199

pachycladus F.Ritter, Melocactus zehntneri (Britton & Rose) Luetzelb and other two 2200

Tacinga Britton & Rose species not used by nectar bats. Cordero-Schmidt et al., (in 2201

prep. here Chapter 1 and 2) have stressed the importance of Cactaceae floral 2202

resources (both pollen and nectar) for the persistence over time of local nectar-feeding 2203

bat ensemble. But is this tight relationship strong enough to influence reproduction 2204

patterns of nectar-feeding female bats in Caatinga? 2205

Considering that sympatric species with similar adaptations and food habits 2206

provide ideal subjects for comparative studies in reproduction, in this study we aim to 2207

describe the reproductive patterns of G. soricina, L. inexpectata, L. mordax and X. 2208

vieirai, and answer three main questions: 1. What is the effect of: A. precipitation and 2209

B. Cactaceae flowering on the female reproductive patterns of the species? 2. Do 2210

they affect differently the four nectar bat species? 3. Will the diet composition (pollen 2211

types load and other items in fecal samples) be different among nectar-feeding female 2212

bats according to the reproductive status in which they are found? 2213

125

In bats energetic investment in offspring is optimized in relation to food 2214

abundance (Racey & Entwistle, 2000), we expect that the reproductive patterns, as in 2215

other SDTFs (Petit, 1997; Martino et al., 1998) will be influenced by both precipitation 2216

and higher resource abundance. Pregnancies will be better explained by precipitation 2217

as a predictor to synchronize their lactation parturition/lactation with the periods of 2218

maximum cacti resource availability to increase their reproductive success. 2219

Nonetheless we expect to find subtle differences between the nectar-feeding bat 2220

species as a way to avoid competition for resources. Additionally, we expect pregnant 2221

and lactating females to have a diet more similar to each other and that will be different 2222

from the diet of non-reproductive females since foraging behavior efficiency can be 2223

impaired by the extra weight of either the final phase of pregnancy or females that 2224

usually fly with their young (Norberg & Rayner, 1987). 2225

METHODS 2226

Study site and climate 2227

This study was conducted in Caatinga, in the municipality of Lajes in the Rio Grande 2228

do Norte (RN) state, located in northeastern Brazil (5°48'46.95"S 36°10'34.60"W). 2229

Vegetation in Caatinga is very diverse for climatic, edaphic, topographic, and anthropic 2230

reasons (Silva, Leal & Tabarelli, 2018). It is characterized by deciduous leaves during 2231

the dry season and frequent or abundant presence of thorny shrubs and Cactaceae. 2232

In a 10-year time series (2009-2019) of the precipitation of the municipality of 2233

Lajes there was a great monthly and year-to-year variation of precipitation (Supporting 2234

Information Figure S1). In Lajes the mean accumulated rainfall was 399.31 mm; 2009 2235

was the rainiest year with a cumulative total of 984.1 mm and 2012 the driest year with 2236

a cumulative total of 99 mm. All precipitation data were extracted from the EMPARN 2237

126

(acronym in Portuguese Rio Grande do Norte Agricultural Research Corporation) 2238

database. 2239

Bat data 2240

We captured bats on 3-day monthly fieldtrips from May to October 2015 for a total of 2241

31 nights (netting effort 43920 m2h) and from February 2017 to February 2019 (except 2242

for November 2017 and May 2018) for a total of 58 mist-netting nights (netting effort 2243

150175 m2h). We mist-netted from 17:30 to midnight and to increase the proportion of 2244

nectar bats caught we set the mist-nets near available flowering plants when possible. 2245

We identified bats to species level using systematic key and species diagnosis 2246

(Gregorin & Ditchfield, 2005; Moratelli & Dias, 2015; Díaz et al. 2016). We determined 2247

age following Brumet-Rossinni & Wilkinson (2009), looking into the epiphyseal-2248

diaphyseal fusion, pelage coloration and tooth wear. 2249

Reproduction data 2250

We externally inspected females to identify the reproductive status. They were 2251

categorized as: non-reproductive – NR: with flat abdomen, nonapparent nipples (post-2252

lactating females with no milk produced and new fur growth surrounding the nipples 2253

were included in the NR category); pregnant – P: pregnancy was detected by lower 2254

abdominal palpation and general body shape); lactating- L: enlarged nipples with no 2255

hair surrounding them, with milk secretion verified by light pressure on the nipples. 2256

All procedures for capture, handling and collection of bats met the guidelines of 2257

the American Society of Mammalogists for the use of wild mammals in research 2258

(Sikes, 2016), and the legal Brazilian requirements of conservation and animal 2259

welfare. Fieldwork was authorized by MMA/ICMBio/SISBIO under permits 48325-2. 2260

Prior to the analysis the bat capture data was corrected by effort as follows: 2261

! !"#%&'()*"+,-./-*0,**/012%"+-∗#!" ∗ 1000 2262

127

Diet 2263

Dietary information on the nectar bat species were obtained from pollen samples 2264

collected from the fur, wings, legs and uropatagium using a single glycerin jelly cube 2265

(3-4 mm) per individual (Voigt, Kelm, Bradley & Ortmann, 2009), which were later 2266

mounted on glass microscope slides. Pollen types were identify to the lowest possible 2267

taxonomic level using a light microscope (magnification 40-100x, Leica DM500) by 2268

comparing our samples with a reference pollen collection from the study sites and with 2269

other pollen catalogues (Palacios-Chávez, Ludlow-Wiechers & Villanueva, 1991; 2270

Roubik & Moreno 1991; Santos, Watanabe & Hamburgo-Alves, 1997; Carreira & Barth 2271

2003; Melhem et al., 2003; Silva, Santos & Lima, 2016). Additionally, we collected 2272

fecal samples and characterized their contents using a microscope (magnification 40-2273

100x, Leica DM500). We categorized the contents of each fecal sample by the 2274

presence or absence of pollen, insect fragments, and “plant tissue” which are 2275

unidentified elements that appear to be of plant origin such as leaves, pericarp, hairs 2276

of the areolas of the cactus, trichomes, etc. 2277

Cactaceae flower resources 2278

We established 15 transects of 100 * 5 m following pre-existing trails, where we tagged 2279

110 randomly chosen reproductive individuals of three species of Cactaceae (nine 2280

Cereus jamacaru - Mandacaru, 40 Pilosocereus gounellei - Xique-xique and 61 2281

Pilosocereus pachycladus - Facheiro). We recorded the individuals with flowers (both 2282

buds and open flowers) available at the time we were mist-netting for bats and the 2283

abundance of each species in the transects. Availability of resource per hectare was 2284

calculated as follows: 2285

Resourceavailabilitypermonth = 5Floweringindv.Observedindv. < ∗ 5Sppabundance

Aream! ∗ 10.000ha. < 2286

2287

128

Studied Cacti species 2288

-Cereus jamacaru DC, commonly known as Mandacaru (Supporting Information 2289

Figure S2). Is a widely distributed Caatinga endemic species, present both in natural 2290

and anthropic areas. It is a columnar cactus with many erect branches forming dense 2291

crowns, individuals can have a height of up to 10 m with distinct trunks to 60 cm in 2292

diameter (Anderson, 2001). Flowers are tubular and very large with 20-30 cm long and 2293

18-20 cm in diameter, solitary, nocturnal and white colored. Individuals can produce 1 2294

to 87 flowers, the opening of all the buds is given over 3 days, once a month during 2295

the rainy period (Zanina, 2013), the blooming of this species is considered massive. 2296

Its pollination syndromes involve sphingophily and chiropterophily (Quirino, 2006). 2297

- Pilosocereus gounellei (F.A.C.Weber) Byles & Rowley, commonly known as Xique-2298

xique (Supporting Information Figure S3). It is a widely distributed Caatinga endemic 2299

species, mostly common on sandy soil and rocky outcrops (Rocha and Agra, 2002). It 2300

is a shrubby cactus, rarely treelike, 0.5-4 m high with numerous erect, inclined and 2301

even horizontal stems (Anderson, 2001). Flowers are tubular and have a narrower and 2302

longer flower-tube the other Pilosocereus species with 7.18 cm long and 2.31cm in 2303

diameter. Individuals have seven to 17 open flowers per night and their flowers last 2304

one day (Rocha et al., 2019). Its pollination syndromes involve sphingophily (Rocha 2305

et al., 2019) and probably chiropterophily (Zappi, 1994; Cordero-Schmidt et al., 2017). 2306

- Pilosocereus pachycladus F.Ritter, commonly known as Facheiro (Supporting 2307

Information Figure S4). It is widely distributed Caatinga endemic species, occurs more 2308

frequently in the top of the mountains (Lucena et al., 2015a). It is a columnar cactus 2309

with many erect branches, individuals can have a height of 2 to 10 m or more 2310

(Anderson, 2001). The flower’s shape is bell/funnel and have a size of approximately 2311

6.74 cm and a diameter of 2.7 cm. Individuals have one to nine open flowers per night 2312

129

and their flowers last one day (Rocha et al., 2019). Its pollination syndromes involve 2313

chiropterophily (Quirino, 2006). 2314

Analysis 2315

We applied simple and multiple logistic regression models to estimate the probability 2316

of occurrence of pregnant and lactating females of G. soricina, L. mordax and X. vieirai 2317

(L. inexpectata was excluded from the analysis due to lack of data on captured 2318

reproductive females). Candidate models included the following variables: 2319

precipitation (Precip.), one month anticipated precipitation (T-1), and the availability of 2320

floral resources of three Cactaceae species P. pacycladus (Pp), Pilosocereus 2321

gounellei (Pg), and Cereus jamacaru (Cj), and one month anticipated the availability 2322

of floral resources of this species (t-1). Model selection was performed using Akaike 2323

Information Criterion (AIC) (Williams et al., 2002). The normalized likelihood that a 2324

model fits the data better (Akaike weights) was used to choose which model was most 2325

likely to be the best to explain the observed data. The lower the value of AIC scores 2326

(∆AIC < 2), the more plausible the model adjustment is to the data. Analysis were 2327

performed in the software SYSTAT version 12. 2328

After selecting the best models, we used the estimative of parameter for 2329

selected logistic models to explain the effect in both pregnancy and lactation of the 2330

studied nectar bat species. 2331

RESULTS 2332

Precipitation 2333

Among the three sampled years, 2015 was the driest with a cumulative total of 277.6 2334

mm, followed by 2017 with 313.2 mm and 2018 with 351.6 mm (Figure 1). The rainiest 2335

months were February (x̄=75.03 mm), March (x̄= 62.06 mm) and April (x̄= 84.90 mm). 2336

The driest months were August, September and November with zero mm. 2337

130

Cactaceae resource availability 2338

The months of greatest flower availability of the three species of cactus coincides with 2339

the months with the highest rainfall (Figure 1). The primary flowering peak of the three 2340

species is overlapped and occurs in February. Pilosocereus pachycladus and C. 2341

jamacaru presented a secondary peak in April, contrary to P. gounellei that kept the 2342

number of individuals blooming similarly from April to September. Cereus jamacaru is 2343

the most seasonal species blooming only in the rainiest period (January-July). 2344

Pilosocereus gounellei bloom during the rainy season and extends its flowering during 2345

few dry months (August-September) and P. pachycladus is the only species that 2346

remains blooming throughout the year. 2347

Reproductive patterns and diet 2348

Glossophaga soricina 2349

We captured a total of 14 pregnant females, nine lactating and 76 non-2350

reproductive females (Table 1). 2351

Reproductive pattern 2352

Glossophaga soricina presented a seasonal bimodal pattern (Figure 2A). The primary 2353

pregnancy peak is observed in May (late rainy period) and the second peak in 2354

December (end of the dry period). Lactation peaks occurred approximately two 2355

months after each pregnancy peak, the primary peak occurred in July. 2356

None of the tested variables (precipitation, nor Cactaceae resource availability with 2357

their respective month anticipation) had an effect on pregnancies of G. soricina 2358

(Supplementary information Table S5). Cactaceae flower resource availability of the 2359

previous month (t-1) had a positive effect on lactating females of G. soricina (Pp(t-1) 2360

Estimate=0.004; Pg(t-1) Estimate=0.002; Cj(t-1) Estimate=0.12; ΔAIC= 0.66; 2361

131

wAIC=13.06; Table 2). Cereus jamacaru had a marginally more significant effect than 2362

the other cacti species (Table S5). 2363

Diet 2364

The females of G. soricina fed on 18 plant species including five species of cactus 2365

(Supporting Information Table S8). This species used P. pachycladus in a similar 2366

proportion in its different reproductive status. During lactation (L), 80% of the samples 2367

included the five species of cacti, with M. zehntneri and P. pachycladus being the most 2368

used resource and they supplemented their diet with two species, 30% of the samples 2369

contained Harpochilus paraibanus (Acanthaceae) and 10% Encholirium spectabile 2370

(Bromeliaceae). 2371

We can observe that either pregnant, lactating or non-reproductive females 2372

used the same complementary resources (pollen, insects and plant tissues) and the 2373

use of these food items does not seem to be determined by precipitation (Figure 4). 2374

However, due to the low number of fecal samples of each reproductive status it is 2375

difficult to draw any conclusions regarding the use of complementary food items. 2376

Lonchophylla inexpectata 2377

We captured a total of five pregnant females, one lactating and 51 non-2378

reproductive (Table 1). 2379

Reproductive pattern 2380

The first peak of pregnancy was observed in February (Figure 2B). The few pregnant 2381

captured females might suggest a seasonal bimodal pattern, nonetheless, all 2382

observed peaks are based on small samples and thus not robust enough to conclude 2383

a pattern. 2384

Diet 2385

132

More than 60% of their samples were composed by Cactaceae pollen and 2386

complemented their diet with 12 other plant species (Figure 3; Supporting Information 2387

Table S8). Lonchophylla inexpectata also complemented their diet with pollen, insects 2388

and plant tissues and it seems that the species included both pollen and insects in the 2389

drier periods in June and August (Figure 4). Due to the low capture of reproductively 2390

active females we cannot have proper conclusions about the diet of this species in the 2391

different reproductive status. 2392

Lonchophylla mordax 2393

We captured a total of 17 pregnant females, 19 lactating and 51 non-2394

reproductive females (Table 1). 2395

Reproductive pattern 2396

Lonchophylla mordax presented a polymodal pattern (Figure 2C) with one primary 2397

pregnancy peak in April (second precipitation peak), a secondary peak in December-2398

January (transition between dry and rainy period) and occasional pregnancies in June 2399

and August (beginning of the dry period). 2400

Precipitation had a strong significant effect in pregnancy of L. mordax (Precip. 2401

Estimate=0.02; ΔAIC= 0; wAIC=36.12) (Table 2). Cactaceae flower resource 2402

availability of the previous month (of the three species) had a positive significant effect 2403

on lactation in L. mordax but was most significantly influenced by P. pachycladus 2404

previous month flowering availability (Pp(t-1) Estimate=0.004; ΔAIC= 0; wAIC=42.64) 2405

(Table 2). 2406

Diet 2407

Females of L. mordax fed on 20 plant species including five species of cactus 2408

(Supporting Information Table S8). Lonchophylla mordax is the nectar bat that used 2409

higher proportion of non-cacti species, still, Cactaceae predominates in the diet mainly 2410

133

of pregnant females (80%) and lactation (60%). During lactation L. mordax used a 2411

similar proportion of C. jamacaru, P. gounellei and P. pachycladus. 2412

Fecal samples of pregnant females presented feces with exclusively pollen in 2413

August and April (Figure 4). Females diet included a higher proportion of insects in the 2414

rainiest periods and used higher proportion of pollen and other plant tissues in the 2415

driest period. 2416

Xeronycteris vieirai 2417

We captured a total of seven pregnant females, eleven lactating and 48 non-2418

reproductive females (Table 1). 2419

Reproductive pattern 2420

Xeronycteris vieirai seems to have a polymodal pattern based on the three lactation 2421

peaks in March, May (primary peak) and July. Pregnancy peaks are not as discernible 2422

as lactation peaks (Figure 2D). 2423

Precipitation had a significant positive effect on pregnancy in X. vieirai (Precip. 2424

Estimate=0.01; ΔAIC= 0; wAIC=20.19) (Table 2). Previous month flower availability of 2425

C. jamacaru had a significant positive effect on lactating females (Cj(t-1) Estimate=0.12; 2426

ΔAIC= 0; wAIC=24.87) (Table 2) the second most significant model was flower 2427

availability of P. gounellei of the previous month (Pg(t-1) Estimate=0.01; ΔAIC= 0; 2428

wAIC=12.97;) (Table 2). 2429

Diet 2430

Females of X. vieirai fed on 14 plant species including five species of cactus 2431

(Supporting Information Table S8). Xeronycteris vieirai was the nectar bat the used a 2432

higher proportion of cactus (≥80%) in their diet in all reproductive status, the higher 2433

proportion was used by pregnant females (>90%) where they only complemented their 2434

diet with Bauhinia pentandra present in 14% of the samples. During lactation the most 2435

134

used cactus species was C. jamacaru (30%), followed by approximately 20% of P. 2436

pachycladus and P. gounellei, and used only two species of non-cacti plants, 2437

Encholirium spectabile (18%) and B. pentandra (9%). Pregnant and non-reproductive 2438

females used a similar proportion of P. pachycladus and P. gounellei (around 30%), 2439

M. zehntneri (10%) and P. chrysostele (10%). 2440

Fecal samples from the driest months (January, June and August to December) 2441

included almost exclusively pollen, independently of their reproductive status (Figure 2442

4). In February (rainiest month) pregnant, lactating and non-reproductive females 2443

complemented their diet with insects and pollen. 2444

The diet of the females of the four studied nectar bats, we can see that regardless of 2445

their reproductive status, more than 50% of female’s diets are composed of 2446

Cactaceaea (Figure 3). 2447

DISSCUSSION 2448

The life history strategies of animals are significantly determined by the 2449

frequency and timing of their reproductive events (Crichton & Krutzsch, 2000). We 2450

detected two types of reproductive patterns for the nectar bat species in Caatinga, 2451

bimodal pattern in G. soricina and polymodal in L. mordax and X. vieirai. Precipitation 2452

positively affected the probability of occurrence of pregnancy for L. mordax and X. 2453

vieirai. None of the tested variables (precipitation nor Cactaceae resources 2454

availability) influenced the pregnancy of G. soricina. On the other hand, the availability 2455

of floral resources of Cactaceae from the previous month, positively affected the 2456

probability of occurrence of lactation for all nectar bat species, with some differences 2457

of significance for certain cacti species. 2458

The phenological flowering patterns of sympatric cactus species have been 2459

studied in various SDTFs where both synchronous and asynchronous, inter and intra-2460

135

specific blooms have been observed (Soriano et al., 1991; Silvius, 1995; Locatelli & 2461

Machado, 1996b; Sosa & Soriano 1996; Petit, 1997; Petit, 2001; Ruiz et al., 2000; 2462

McIntosh, 2002). Authors have mentioned that this phenological variation throughout 2463

the year favors the maintenance of pollinators and dispersers, mainly in environments 2464

with high seasonality. Also, the periods of flowering overlap can favor pollination, since 2465

an increase in resources could also be reflected pollinators abundance (Kudo, 2006). 2466

The studied cacti species seem to present both strategies since their flotation peaks 2467

overlap in the rainy season furthermore each species showed a different flowering 2468

frequency throughout the year (C. jamacaru-rainy season only; P. gounellei - mainly 2469

rainy season and extends during the first months of the dry season; P. pachycladus 2470

year-round availability). This phenological variability is influencing not only the 2471

persistence of the species in the area over time (Cordero-Schmidt in prep. Chapter 2), 2472

but also influencing the occurrence of lactation events. 2473

Pregnancy and rainfall 2474

Caatinga is an environment dominated by seasonal changes, where resources 2475

vary according to precipitation fluctuations (Lima & Rodal, 2010) thus creating more 2476

suitable periods to reproduce. The long period of gestation of bats limits their ability 2477

to react quickly to short-term fluctuations but respond to predictable seasonal changes 2478

by which to optimize their time of reproduction (Heideman, 2000). Bimodal and 2479

polymodal polyestry patterns have shown a clear relationship in enviroments 2480

presenting unimodal rainfall (Heideman, 2000) as observed in our studied Caatinga 2481

area. Lonchophylla mordax and X. vieirai presented most of their pregnancy events 2482

within the propitious rainy season and lower pregnancy events and non-breeding 2483

during suboptimal dry seasons. Differently, none of the variables used in our models 2484

were able to explain the patterns in pregnancy of G. soricina, maybe this is due to its 2485

136

generalist’s behavior (Estrada & Coates-Estrada, 2001). Glossophaga soricina is the 2486

nectar bat species with more information gathered about its reproductive patterns in 2487

different habitats. This species has a bimodal pattern independent of habitat type 2488

(Fleming 1972; Willig, 1985; Ramirez-Pulido et al., 1993; Stoner 2001; Zortea, 2003; 2489

Tschapka, 2005), but the time when the pregnancy and lactation peaks occurs can 2490

vary geographically (Durant et al., 2013), our data corroborates this. In the Caatinga 2491

of RN state G. soricina shows a bimodal pattern, with a peak pregnancy peaks in May 2492

(rainy season) and December (dry season) followed by two lactation peaks in February 2493

(rainy season) and July (transition between rainy to dry season). In other SDTFs G. 2494

soricina’s reproductive patterns have been explained according to the availability of 2495

resources and their great flexibility in the diet (Sperr et al., 2011). 2496

Lactation and Cactaceae resource availability 2497

As mentioned before, lactation is the most energetically costly reproductive status, 2498

hence seems logic that the most important factor in determining the timing of this 2499

event’s occurrence is resource availability (Racey & Entwistle, 2000). Lactation 2500

overlap occurred year-round; but the primary peaks of L. mordax and X. vieirai do not 2501

overlap and are separated by approximately one month (Figure S9). Such a difference 2502

in the timing of reproduction emphasizes the importance of diet in determining 2503

reproductive timing, and reinforce that food availability, rather do climatic factors, 2504

ultimately underlies the timing of reproductive events in tropical bat species (Racey & 2505

Entwistle, 2000). July is the only month where the lactation of the three studied nectar 2506

bat species seems to overlap the most. July is also the last month where there is 2507

flowering overlap of the three cacti species and the month where a last peak in rain is 2508

observed (Figure 1). The fact that there is no overlap of the main lactation peaks of 2509

the three species seems to indicate a mechanism to avoid competition (Ramirez-2510

137

Pulido et al., 1993). Considering that all cacti species were equally available for all bat 2511

species, another possible evidence of competition avoidance is the distinct influence 2512

of the different cacti species on the different nectar bat species. Glossophaga soricina 2513

lactation events were better explained by C. jamacaru, L. mordax by P. pachycladus 2514

and X. vieirai by C. jamacaru and P. gounellei. It seems that the nectar bat species 2515

are partitioning resources during the delicate phase of lactation. 2516

Bats generally give birth to well-developed large infants, about 26.6% of the 2517

mother’s body mass in phyllostomids (Kurta and Kunz, 1987). Females of G. soricina 2518

and X. vieirai were caught several times carrying their young, this behavior was never 2519

observed in the Lonchophylla species; this behavior probably affects the species 2520

foraging behavior and dislocation capacity and thus the diet composition (Kurta and 2521

Kunz, 1987). Lonchophylla mordax included more species of plants during lactation 2522

(14 plant species) than G. soricina and X. vieirai, this might be explained by greater 2523

access to different flowers because they are not carrying their young while foraging. 2524

But at the same time L. mordax lactating females may be obligated to forage where 2525

most resources are concentrated or forage near the maternity roosts (Sperr et al., 2526

2011). However, it is necessary to study this in more detail and in other areas to see 2527

if it is a repeating pattern for these species. 2528

Fecal contents of X. vieirai females seem to show some sort of seasonality, 2529

where regardless of their reproductive status the females include more insects in their 2530

diet during the rainy season and include more pollen in the dry season. In Caatinga, 2531

the rainiest months of the year are the months with the greatest abundance of insects 2532

(Vasconcellos et al., 2010) and this could explain the increase in the frequency of this 2533

item in the diet of X. vieirai. Cordero-Schmidt (in prep. Chapter 2) found that X. vieirai 2534

is the most specialized nectar/pollen-feeding bat in this Caatinga area, especially 2535

138

when compared to G. soricina which is the most generalist species, capable to actively 2536

look for insect preys (Clare et al., 2014). In general we can affirm that the females of 2537

the species of nectar bats complement their diet mainly with pollen, which is an 2538

important source of tyrosine, an amino acid found in abundance in the milk of small 2539

mammals and acts as growth stimulant (Howell, 1974), followed by insects and plant 2540

tissues, thus obtaining the inputs of protein, nitrogen among others, necessary for the 2541

different reproductive states. But the low number of fecal samples does not allow us 2542

to have any robust conclusions about the way the species are supplementing their diet 2543

according to their reproductive status. 2544

Conservation concerns 2545

Both abiotic (precipitation) and biotic resources availability (Cactaceae) influence the 2546

reproduction events in nectar-feeding bats in Caatinga. Sadly both factors are 2547

threatened by climate change. Predictive models about the potential impact of climate 2548

change in the Caatinga indicate that precipitation will decrease 22% by 2100 and that 2549

drier sites show impoverished plant assemblages that are more sensitive to chronic 2550

disturbances such as wood extraction, cattle ranching and subsistence agriculture 2551

(Rito et al., 2017). In other SDTFs the range reductions of particular species, lower 2552

abundance, extirpation, extinction, and increased competition in environments altered 2553

by humans are having severe negative consequences on the structure and 2554

composition of mammal communities (Dirzo et al., 2011). Moreover, changes in 2555

flowering phenology caused by habitat fragmentation have shown to change bat 2556

pollination patterns and to negatively affect the reproductive outcome of the plants 2557

they pollinate (Quesada et al. 2004). 2558

Cactaceae have intrinsic characteristics that make them vulnerable to habitat 2559

fragmentation, loss of habitat quality, mining, trade and illegal collection (Zappi et al., 2560

139

2011). Their life cycle is slow and only small proportion of the annual seed production 2561

will germinate and survive (Ortega-Baes et al., 2010). Cacti resources are very 2562

important not only for wildlife but for humans as well. Cactaceae species are widely 2563

used by human populations in Caatinga, its uses vary and range from construction (for 2564

making doors, windows, boards,laths, etc), food for cattle, goats and sheep, religious, 2565

medicinal, ornamental and veterinary use, among others (Lucena et al., 2015b). 2566

The fate of both nectar bats and Cactaceae in Caatinga are closely linked and 2567

so are the other animals that also depended on this keystone resources including 2568

people. The loss of cacti species could certainly affect the supply of important 2569

environmental services such as pollination and seed dispersal by animals (Zappi, et 2570

al., 2011). Conservation initiatives should consider areas with high abundance and 2571

diversity of Cactaceae as a priority. 2572

2573

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& Aona, L. (2011). Plano de ação nacional para conservação das cactáceas. 2708

Instituto Chico Mendes de Conservação da Biodiversidade, Brazil. 2709

Zortéa, M. (2003). Reproductive patterns and feeding habits of three nectarivorous 2710

bats (Phyllostomidae: Glossophaginae) from the Brazilian Cerrado. Brazilian 2711

Journal of Biology, 63(1), 159-168. 2712

2713

2714 2715

146

2716

2717

2718 Figure 1. Monthly flowering individuals per hectare of the sampled three Cactaceae 2719 species and monthly precipitation. 2720 2721

147

Table 1. Monthly sampling effort, monthly and average precipitation during the sampling periods and the captured individuals 2722 categorized in five reproductive status: NRF- Non-Reproductive Females; P- Pregnant; L-Lactating. Cells are filled with the number 2723 of captured individuals, · accounts for zero. 2724 2725

2726

148

2727 Figure 2. Reproductive pattern of the four nectar bat species synthesized from 2 2728 sampling periods: May-October 2015 and February 2017 to February 2019 (except for 2729 November 2017 and May 2018). The patterns are based on monthly proportions of: 2730 Pregnant, Lactating and Non-Reproductive females; all corrected by monthly sampling 2731 effort. I. Female reproduction patterns in relation to mean monthly precipitation. II. 2732 Females reproductive pattern in relation to three Cactaceae species flowering 2733 phenologies (P.p: Pilosocereus pachycladus; C.j: Cereus jamacaru; P.g: Pilosocereus 2734 gounellei). 2735

2736

149

Table 2. Selected models parameters for explaining A. Pregnancy and B. Lactation 2737 patterns in the different nectar-feeding bat species: Gs: Glossophaga soricina (no 2738 tested variables influenced pregnancy of Gs); Lm: Lonchophylla mordax and Xv: 2739 Xeronycteris vieirai. 2740 2741

2742

A. Pregnancy

Species_Status Parameter Estimate SE Z p-value Odds Ratio

Standard Error

IC 95% Lower

IC 95% Upper

Lm_Pregnant Constant -3.14364 0.54072 -5.81382 0Precip. 0.02744 0.00654 4.197 0.00003 1.02782 0.00672 1.01473 1.04108G=21.5989; df=1; p-value=0

Constant -4.02936 0.92048 -4.37744 0.00001Precip. 0.03941 0.02078 1.89683 0.05785 1.04019 0.02161 0.99869 1.08342Pp 0.00517 0.00312 1.65683 0.09755 1.00519 0.00314 0.99905 1.01136Pg -0.00653 0.00812 -0.80401 0.42139 0.99349 0.00807 0.97779 1.00944Cj -0.08366 0.10822 -0.77309 0.43947 0.91974 0.09953 0.74396 1.13706G=26.76662; df=4; p-value=0.00002

Constant -3.00891 0.63888 -4.70966 0Precip. 0.0271 0.00655 4.13465 0.00004 1.02747 0.00673 1.01436 1.04076

Precip.(T-1) -0.00387 0.01079 -0.35896 0.71963 0.99613 0.01075 0.97529 1.01742G=21.73156; df=2; p-value=0.00002

Xv_Pregnant Constant -3.52222 0.82406 -4.27421 0.00002Precip. 0.01516 0.00854 1.77592 0.07575 1.01527 0.00867 0.99843 1.0324G=3.18926; df=1; p-value=0.07412

Constant -3.30563 0.76559 -4.31776 0.00002Cj 0.08357 0.05691 1.46836 0.14201 1.08716 0.06187 0.97241 1.21545G=2.13002; df=1; p-value=0.14444

B. Lactation

Species_Status Parameter Estimate SE Z p-value Odds Ratio

Standard Error

IC 95% Lower

IC 95% Upper

Gs_Lactant Constant -3.81076 0.9788 -3.89327 0.0001

Pp(t-1) 0.00414 0.00311 1.33 0.18352 1.00414 0.00312 0.99804 1.01028

Pg (t-1) 0.00221 0.00786 0.28125 0.77852 1.00221 0.00788 0.98689 1.01777

Cj (t-1) 0.12597 0.07535 1.67191 0.09454 1.13425 0.08546 0.97853 1.31475G=8.80279; df=3; p-value=0.03203

Lm_lactant Constant -6.14157 1.9662 -3.12358 0.00179

Pp(t-1) 0.01148 0.00509 2.25614 0.02406 1.01155 0.00515 1.00151 1.02169

Pg (t-1) -0.01267 0.01217 -1.04081 0.29796 0.98741 0.01202 0.96413 1.01125

Cj (t-1) 0.26575 0.1298 2.04741 0.04062 1.30441 0.16931 1.01142 1.68229G=14.90147; df=3; p-value=0.0019

Constant -2.57998 0.49926 -5.16757 0

Pp(t-1) 0.00451 0.00183 2.46438 0.01373 1.00452 0.00184 1.00092 1.00812G=6.11659df=1p-value=0.01339

Xv _Lactant Constant -2.81719 0.51379 -5.48311 0

Cj (t-1) 0.12362 0.04852 2.54758 0.01085 1.13158 0.05491 1.02892 1.24448G=6.19254: df=1; p-value=0.01283

Constant -2.75725 0.51761 -5.32684 0

Pg (t-1) 0.01204 0.00536 2.2477 0.0246 1.01212 0.00542 1.00154 1.0228G=4.888; df=1; p-value=0.02704

150

2743 Figure 3. Females’ diet composition observed in the pollen samples of the four nectar 2744 bat species different reproductive status. NR- Non-Reproductive; P- Pregnant; L-2745 Lactating. The proportion of each non-cacti species used is represented in each grey 2746 compartment. Number inside ( ) is the number of samples from each reproductive 2747 status. 2748

Figure 4. Monthly females’ diet composition observed in the fecal samples of the four 2749 nectar bat species different reproductive status. Glossophaga soricina N= 14 (Non-2750 reproductive-NR= 9; Pregnant-P=2; Lactating-L=3). Lonchophylla inexpectata N=15 2751 (NR= 14; P= 1). Lonchophylla mordax N=17 (NR= 7; P=6; L= 4). Xeronycteris vieirai 2752 N=22 (NR= 11; P=2 L= 9). 2753

2754

151

SUPPORTING INFORMATION 2755 2756 2757 2758

2759 2760 Figure S1. Mean monthly precipitation from 2009 to 2019 (shaded light-blue area) in 2761 the municipality of Lajes in northeastern Brazil. Rainiest year was 2009 (blue dashed 2762 line), driest year 2012 (black dashed line), sampled years precipitation are 2763 represented by continuous colored lines. 2764

152

Figure S2. Cereus jamacaru DC, common name Mandacarú, Cactaceae 2765

153

Figure S3. Pilosocereus gounellei (F.A.C.Weber) Byles & Rowley, common name 2766 Xique- xique Cactaceae 2767

154

Figure S4. Pilosocereus pachycladus F.Ritter, common name Facheiro, Cactaceae 2768

155

Table S5. Selection models of logist regressions for Glossophaga soricina pregnancy 2769 and lactation. AIC - Akaike Information Criterion value; ΔAIC - difference in the Akaike 2770 Information Criterion between each model and the best model; W AIC - Akaike weight 2771 and w AIC um - cumulative weight of AIC. 2772 2773

2774

Glossophaga soricinaA. Pregnancy models AIC Δ AIC w AIC w AIC cumNull model 61.33866 0 18.18 18.18Precip.(T-1) 62.00041 0.66175 13.06 31.23Cj (t-1) 62.00947 0.67081 13.00 44.23Pp 62.8168 1.47814 8.68 52.91Pg 63.27697 1.93831 6.90 59.81Cj 63.29118 1.95252 6.85 66.66Precip. 63.32209 1.98343 6.74 73.40Pp(t-1) 63.3276 1.98894 6.72 80.12Pg (t-1) 63.33841 1.99975 6.69 86.81Precip. + Precip.(T-1) 63.93893 2.60027 4.95 91.77Pp(t-1) + Pg(t-1) + Cj(t-1) 64.34065 3.00199 4.05 95.82Precip.(T-1) + Pp(t-1) + Pg(t-1) + Cj(t-1) 65.27891 3.94025 2.53 98.35Pp + Pg + Cj 66.80748 5.46882 1.18 99.53Precip. + Pp + Pg + Cj 68.65995 7.32129 0.47 100.00

B. Lactation models AIC Δ AIC w AIC w AIC cumPp(t-1) + Pg(t-1) + Cj(t-1) 49.34502 0 74.77 74.77Cj (t-1) 54.22654 4.88152 6.51 81.28Pp(t-1) 54.85174 5.50672 4.76 86.05Cj 55.44522 6.1002 3.54 89.59Pg 55.57414 6.22912 3.32 92.91Precip. 56.66901 7.32399 1.92 94.83Precip. + Precip.(T-1) 57.21488 7.86986 1.46 96.29Null model 58.2465 8.90148 0.87 97.16Pg (t-1) 58.47649 9.13147 0.78 97.94Precip.(T-1) 58.7374 9.39238 0.68 98.62Pp + Pg + Cj 58.86454 9.51952 0.64 99.26Pp 59.42353 10.07851 0.48 99.75Precip. + Pp + Pg + Cj 60.7285 11.38348 0.25 100.00Precip.(T-1) + Pp(t-1) + Pg(t-1) + Cj(t-1) **** unsatisfactory solution

156

Table S6. Selection models of logist regressions for Lonchophylla mordax pregnancy 2775 and lactation. AIC - Akaike Information Criterion value; ΔAIC - difference in the Akaike 2776 Information Criterion between each model and the best model; W AIC - Akaike weight 2777 and w AIC um - cumulative weight of AIC. 2778 2779

2780 2781

Lonchophylla mordaxA. Pregnancy models AIC Δ AIC w AIC w AIC cumPrecip. 71.02498 0 36.12 36.12Precip. + Pp + Pg + Cj 71.85726 0.83228 23.82 59.94Precip. + Precip.(T-1) 72.89232 1.86734 14.20 74.14Pp(t-1) + Pg(t-1) + Cj(t-1) 73.08742 2.06244 12.88 87.02Precip.(T-1) + Pp(t-1) + Pg(t-1) + Cj(t-1) 74.92053 3.89555 5.15 92.17Pp + Pg + Cj 75.48289 4.45791 3.89 96.06Pp 75.76236 4.73738 3.38 99.44Pg 79.68772 8.66274 0.47 99.91Pg (t-1) 84.29037 13.26539 0.05 99.96Cj 85.8122 14.78722 0.02 99.98Pp(t-1) 86.72477 15.69979 0.01 100.00Null model 90.62388 19.5989 0.00 100.00Precip.(T-1) 92.1174 21.09242 0.00 100.00Cj (t-1) 92.59177 21.56679 0.00 100.00

B. Lactation models AIC Δ AIC w AIC w AIC cumPp(t-1) 87.1826 0 42.64 42.64Precip. 90.29003 3.10743 9.02 51.65Pp(t-1) + Pg(t-1) + Cj(t-1) 90.60521 3.42261 7.70 59.36Precip. + Precip.(T-1) 90.79375 3.61115 7.01 66.37Cj 91.01386 3.83126 6.28 72.64Null model 91.29919 4.11659 5.44 78.09Pg (t-1) 91.53587 4.35327 4.84 82.92Precip.(T-1) 91.95728 4.77468 3.92 86.84Precip.(T-1) + Pp(t-1) + Pg(t-1) + Cj(t-1) 92.33949 5.15689 3.24 90.08Cj (t-1) 92.41795 5.23535 3.11 93.19Pg 92.81246 5.62986 2.55 95.74Pp 92.88179 5.69919 2.47 98.21Pp + Pg + Cj 94.69184 7.50924 1.00 99.21Precip. + Pp + Pg + Cj 95.15429 7.97169 0.79 100.00

157

Table S7. Selection models of logist regressions for Xeronycteris vieirai pregnancy 2782 and lactation. AIC - Akaike Information Criterion value; ΔAIC - difference in the Akaike 2783 Information Criterion between each model and the best model; W AIC - Akaike weight 2784 and w AIC um - cumulative weight of AIC. 2785 2786 2787

2788

Xeronycteris vieiraiA. Pregnancy models AIC Δ AIC w AIC w AIC cumPrecipitation 37.27039 0 20.19 20.19Cj 38.32964 1.05925 11.89 32.07Null model 38.45965 1.18926 11.14 43.21Pg (t-1) 38.76249 1.4921 9.57 52.79Precip. + Precip.(T-1) 38.94167 1.67128 8.75 61.54Pp 39.01898 1.74859 8.42 69.96Pg 39.34525 2.07486 7.15 77.12Pp(t-1) 39.84975 2.57936 5.56 82.68Precip.(T-1) 40.23503 2.96464 4.58 87.26Cj (t-1) 40.23887 2.96848 4.58 91.84Pp + Pg + Cj 41.20642 3.93603 2.82 94.66Pp(t-1) + Pg(t-1) + Cj(t-1) 41.41201 4.14162 2.55 97.20Precip. + Pp + Pg + Cj 42.04871 4.77832 1.85 99.05Precip.(T-1) + Pp(t-1) + Pg(t-1) + Cj(t-1) 43.39088 6.12049 0.95 100.00

B. Lactation models AIC Δ AIC w AIC w AIC cumCj (t-1) 55.45911 0 24.87 24.87Pg (t-1) 56.7636 1.30449 12.96 37.83Pp(t-1) + Pg(t-1) + Cj(t-1) 56.84886 1.38975 12.42 50.25Pp + Pg + Cj 57.55236 2.09325 8.73 58.98Precip. + Pp + Pg + Cj 57.69148 2.23237 8.15 67.13Precip.(T-1) 57.89418 2.43507 7.36 74.49Cj 58.52586 3.06675 5.37 79.86Precip.(T-1) + Pp(t-1) + Pg(t-1) + Cj(t-1) 58.78662 3.32751 4.71 84.57Precip. + Precip.(T-1) 59.06233 3.60322 4.11 88.68Null model 59.65166 4.19255 3.06 91.73Pp(t-1) 59.84916 4.39005 2.77 94.50Pp 59.97883 4.51972 2.60 97.10Precip. 60.92345 5.46434 1.62 98.72Pg 61.39118 5.93207 1.28 100.00

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Table S8. Plants species used by females of each nectar bat species in the different 2789 reproductive status. NR- Non-Reproductive Females; P- Pregnant; L-Lactating. The 2790 single lactating pollen sample of L. inexpectata did not contained any pollen types. 2791 2792

2793 2794

2795

2796

Figure S9. Proportion of lactating females of the three nectar-feeding bats. The 2797

underlined months indicate the primary lactation peak for the different bat species. 2798

2799

Family Plant species G. soricina L. inexpectata L. mordax X. vieiraiAcanthaceae Harpochilus paraibanus NR | P | L NR NR | P | L NR

Dicliptera ciliaris NR | P NR NR | P | L NRRuellia asperula NR NR NR | L NRHarpochilus neesianus ・ ・ NR ・

Bignoneaceae Tabebuia aurea NR NR NR | L NRBromeliaceae Encholirium spectabile NR | P | L NR NR | P | L LCactaceae Pilosocereus pachycladus NR | P | L NR | P NR | P | L NR | P | L

Pilosocereus gounellei NR | P | L NR | P NR | P | L NR | P | LMelocactus zehntneri NR | P | L NR | P NR | P | L NR | P | LCereus jamacaru NR | P | L NR | P NR | P | L NR | P | LPilosocereus chrysostele NR | P | L P NR | P | L NR | P

Capparaceae Cynophalla hastata NR ・ NR | P ・

Cleomaceae Tareyana spinosa NR | P NR NR ・

Convolvulaceae Ipomoea sp. ・ NR NR | L ・

Euphorbiaceae Jatropha mollissima ・ NR ・ NRFabaceae Bauhinia cheilantha NR | P NR NR | P ・

Bauhinia pentandra NR ・ NR | L P | LCoursetia rostrata NR ・ ・ ・

Fabaceae sp. ・ NR NR ・

Malvaceae Helicteres baruensis NR | P NR | P NR | P | L NRPseudobombax ・ NR NR | L NR

Xanthorrhoeaceae Aloe vera NR ・ ・ ・

. Monocot sp. NR ・ NR ・

Total used plant species 18 17 20 14

159

- At 2800 2801 At least five species can co-occur:

- Anoura geoffroyi, the rarest. Mostly captured in the humid forest enclave and one individual was captured in a riparian Caatinga. This species feeds on at least eight plant species.

- Glossophaga soricina, the most common and abundant. Captured in all sampled localities and types of habitat. It feeds on 26 plant species and complements its diet mostly with insects, but also with pollen and plant tissues.

- Lonchophylla inexpectata, a Caatinga endemic, this species had the second lowest occurrence. Only captured in the locality of Lajes in riparian and shrubby Caatinga. It feeds on 20 plant species and complements its diet with insects, pollen and plant tissues.

- Lonchophylla mordax, the second most common and abundant species. Captured in Copernicia groves, Medium, Shrubby and Riparian Caatinga and in Rocky outcrops. It feeds on 28 plant species and complements its diet with insects, pollen and plant tissues.

- Xeronycteris vieirai, endemic to the dry diagonal crossing central Brazil. Captured only in Lajes, in riparian and shrubby Caatinga. It feeds on 21 plant species and complements its diet mainly with pollen but also with insects and plant tissues.

- The interaction networks between nectar bats and plants is highly generalized and showed high overlap. This associations are stable through the seasons and years.

- Nectar bats showed ecological and phenotypical generalization in the plants they include in their diets.

- The species coexisted and persisted year-round in Caatinga by presenting temporal partitioning within the hours of the night, resource partitioning facilitated by ecomorphological differences and diet flexibility.

- Temporal persistence of nectar bats was facilitated by the continuity and complementarity of floral resources available through the year and the high use of keystone resources.

- Female reproduction patterns of the studied nectar-feeding bats are bimodal (G. soricina and apparently L. inexpectata) and polymodal (L. mordax and X. vieirai).

- Pregnancy was influenced by precipitation in L. mordax and X. vieirai but not for G. soricina.

- Lactation was influenced by Cactaceae resource availability of the previous month for the three nectar bat species.

- Cactaceae are keystone resources for nectar bats in Caatinga. At least five species were widely used, but Pilosocereus pachycladus stood out. Conservation initiatives should consider sites with high abundance and diversity of Cactaceae as a conservation priority.

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