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Spatial Distance and Climate Determine Modularity in a Cross-Biomes Plant–Hummingbird Interaction Network in Brazil

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Spatial Distance and Climate Determine Modularity in a Cross-Biomes Plant–Hummingbird Interaction Network in Brazil UC Berkeley UC Berkeley Previously Published Works Title Spatial distance and climate determine modularity in a cross-biomes plant–hummingbird interaction network in Brazil Permalink https://escholarship.org/uc/item/0bn4j06z Journal Journal of Biogeography, 45(8) ISSN 0305-0270 Authors Araujo, AC Martín González, AM Sandel, B et al. Publication Date 2018-08-01 DOI 10.1111/jbi.13367 Peer reviewed eScholarship.org Powered by the California Digital Library University of California DOI: 10.1111/jbi.13367 RESEARCH PAPER Spatial distance and climate determine modularity in a cross-biomes plant–hummingbird interaction network in Brazil Andrea Cardoso Araujo1 | Ana M. Martın Gonzalez 2,3 | Brody Sandel4 | Pietro K. Maruyama5,6 | Erich Fischer1 | Jeferson Vizentin-Bugoni7 | Francielle Paulina de Araujo 8 | Aline Goes Coelho9 | Rogerio Rodrigues Faria10 | Glauco Kohler11 | Flor Maria Guedes Las-Casas12 | Ariadna Valentina Lopes13 | Adriana O. Machado6 | Caio Graco Machado9 | Isabel Cristina Machado13 | Jimmy A. McGuire14 | Alan Cerqueira Moura9 | Genilda M. Oliveira15 | Paulo Eugenio^ Oliveira6 | Marcia Alexandra Rocca16 | Licleia da Cruz Rodrigues17 | Marcos Rodrigues17 | Ana Maria Rui18 | Ivan Sazima19 | Marlies Sazima20 | Isabela Galarda Varassin21 | Zhiheng Wang22 | Bo Dalsgaard2 | Jens-Christian Svenning23,24 1Instituto de Biociencias,^ Universidade Federal de Mato Grosso do Sul, Campo Grande, Mato Grosso do Sul, Brazil 2Centre for Macroecology, Evolution and Climate, Natural History Museum of Denmark, University of Copenhagen, Copenhagen, Denmark 3Pacific Ecoinformatics and Computational Ecology Lab, Berkeley, California 4Department of Biology, Santa Clara University, Santa Clara, California 5Departamento de Biologia Vegetal, Universidade Estadual de Campinas, Campinas, Sao~ Paulo, Brazil 6Instituto de Biologia, Universidade Federal de Uberl^andia -UFU, Uberl^andia, Minas Gerais, Brazil 7Department of Natural Resources and Environmental Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 8Universidade Estadual do Rio Grande do Sul, Unidade Sao~ Francisco de Paula, Assis Brazil, Rio Grande do Sul, Brazil 9Laboratorio de Ornitologia, Departamento de Ciencias^ Biologicas, Universidade Estadual de Feira de Santana, Feira de Santana, Bahia, Brazil 10Campus de Aquidauana, Universidade Federal de Mato Grosso do Sul, Aquidauana, Mato Grosso do Sul, Brazil 11Instituto Nacional de Pesquisas da Amazonia,^ Petropolis, Manaus, Amazonas, Brazil 12Departamento de Zoologia, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil 13Departamento de Botanica^ – CCB, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil 14Museum of Vertebrate Zoology, University of California, Berkeley, California 15Instituto Federal de Brasılia, Brasılia, Distrito Federal, Brazil 16Departamento de Ecologia, Centro de Ciencias^ Biologicas e da Saude, Universidade Federal de Sergipe, S~ao Cristov ~ao, Sergipe, Brazil 17Laboratorio de Ornitologia, Departamento de Zoologia, ICB, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil 18Laboratorio de Ecologia de Aves e Mamıferos, Departamento e Ecologia, Genetica e Zoologia, IB, Universidade Federal de Pelotas, Cap~ao do Le~ao, Rio Grande do Sul, Brazil 19Museu de Zoologia, Universidade Estadual de Campinas, Campinas, S~ao Paulo, Brazil 20Departamento de Biologia Vegetal, Instituto de Biologia, Universidade Estadual de Campinas, Campinas, S~ao Paulo, Brazil 21Laboratorio de Ecologia Vegetal, Departamento de Bot^anica, Universidade Federal do Parana, Curitiba, Parana, Brazil 22Department of Ecology and Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, College of Urban and Environmental Sciences, Beijing, China 23Section for Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus University, Aarhus C, Denmark 24Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Department of Bioscience, Aarhus University, Aarhus C, Denmark 1846 | © 2018 John Wiley & Sons Ltd wileyonlinelibrary.com/journal/jbi Journal of Biogeography. 2018;45:1846–1858. ARAUJO ET AL. | 1847 Correspondence Andrea C. Araujo, Instituto de Biociencias,^ Abstract Universidade Federal de Mato Grosso do Aim: We examined the effects of space, climate, phylogeny and species traits on Sul, 79070-900 Campo Grande, Mato Grosso do Sul, Brazil. module composition in a cross-biomes plant–hummingbird network. Email: [email protected] Location: Brazil, except Amazonian region. Methods: We compiled 31 local binary plant–hummingbird networks, combining Funding information CAPES/FUNDECT PAPOS, Grant/Award them into one cross-biomes metanetwork. We conducted a modularity analysis and ß~ Number: 23/200.638/2014; Fundacao de tested the relationship between species’ module membership with traits, geographi- Apoio ao Desenvolvimento do Ensino, Ciencia^ e Tecnologia do Estado de Mato cal location, climatic conditions and range sizes, employing random forest models. ß~ Grosso do Sul; Fundacao O Boticario de We fitted reduced models containing groups of related variables (climatic, spatial, Protecß~ao a Natureza; Coordenacßao~ de Aperfeicßoamento de Pessoal de Nıvel phylogenetic, traits) and combinations of groups to partition the variance explained Superior, Grant/Award Number: BEX 4556/ by these sets into unique and shared components. 13-5; European Research Council, Grant/ Award Number: ERC-2012-StG-310886- Results: The Brazilian cross-biomes network was composed of 479 plant and 42 HISTFUNC; Conselho Nacional de hummingbird species, and showed significant modularity. The resulting six modules Desenvolvimento Cientıfico e Tecnologico, Grant/Award Number: 309453/2013-5, conformed well to vegetation domains. Only plant traits, not hummingbird traits, dif- ß~ 311001/2012-2, 445405/2014-7; Fundacao fered between modules, notably plants’ growth form, corolla length, flower shape de Amparo aCiencia^ e Tecnologia do Estado de Pernambuco; Villum Fonden; The Nature and colour. Some modules included plant species with very restricted distributions, Conservancy; National Natural Science whereas others encompassed more widespread ones. Widespread hummingbirds Foundation of China, Grant/Award Number: 31522012; Fundacßao~ de Amparo a Pesquisa were the most connected, both within and between modules, whereas widespread do Estado da Bahia; Fundo de Apoio ao plants were the most connected between modules. Among traits, only nectar con- Ensino, a Pesquisa e Extensao,~ Universidade Estadual de Campinas; Fundacßao~ de Amparo centration had a weak effect on among-module connectivity. a Pesquisa do Estado de Minas Gerais; Main conclusions: Climate and spatial filters were the main determinants of module Fundacßao~ de Amparo a Pesquisa do Estado de S~ao Paulo, Grant/Award Number: 2015/ composition for hummingbirds and plants, potentially related to resource seasonal- 21457-4; Division of Environmental Biology, ity, especially for hummingbirds. Historical dispersal-linked contingency, or environ- Grant/Award Number: 0543556, 0724679; Michelin Brasil mental variations not accounted for by the explanatory factors here evaluated, could also contribute to the spatial component. Phylogeny and morphological traits Editor: Daniel Kissling had no unique effects on the assignment of species to modules. Widespread species showed higher within- and/or among-module connectivity, indicating their key role connecting biomes, and, in the case of hummingbirds, communities within biomes. Our results indicate that biogeography and climate not only determine the variation of modularity in local plant–animal networks, as previously shown, but also affect the cross-biomes network structure. KEYWORDS biogeography, module composition, ornithophily, phylogeny, pollination, range size, species roles, traits 1 | INTRODUCTION Horadam, 2016; Fortunato & Hric, 2016). Indeed, modularity appears as a common feature across a wide variety of ecological and biogeo- Knowledge about how biotic interactions are distributed within and graphical networks, i.e. networks based on species occurrence across between communities is crucial for understanding both species inter- large areas (Dalsgaard et al., 2013; Kougioumoutzis, Simaiakis, & dependence and community dynamics. For instance, biotic interac- Tiniakou, 2014; Martın Gonzalez et al., 2015; Olesen, Bascompte, tions are typically not evenly distributed within communities Dupont, & Jordano, 2007). In modular networks species tend to (Vazquez, 2005). Several tools have been used for the detection of interact intensively within subsets of species (modules), so that spe- community structure, with modularity being one of the most wide- cies in a given module interact more frequently with species in the spread techniques for describing network clustering (Alzahrani & same module than with species outside of it (Olesen et al., 2007). 1848 | ARAUJO ET AL. Several factors such as current and historical climate, species’ hummingbirds and their food plants should vary across this almost distributional ranges, morphological traits and phylogenetic relation- continental scale. In this study we evaluate the major drivers of ships may show associations with the level of modularity and mod- plant–hummingbird interactions at the cross-biomes scale, examining ule composition, and hence, with the specialization of plant– how interactions are distributed across space and which factors may hummingbird interactions (Dalsgaard et al., 2013; Martın Gonzalez, explain observed interaction
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