Insights into the assembly rules of a continent-wide multilayer network

Mello, Marco A. R.; Félix, Gabriel M. F.; Pinheiro, Rafael Barros Pereira; Muylaert, Renata L.; Geiselman, Cullen; Santana, Sharlene E.; Tschapka, Marco; Lotfi, Nastaran; Rodrigues, Francisco A.; Stevens, Richard D.

doi:10.1038/s41559-019-1002-3

Cited by 70 publications

(87 citation statements)

References 55 publications

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“…In fact, the network's nestedness comes mostly from within than between the modules. Compound topologies have also been observed in other networks with high taxonomic diversity (Felix et al., 2017), composed of different kinds of interactions (Mello et al., 2019), or that contain mixed taxonomic groups (Genrich et al., 2017). As the studied network does also harbor mixed taxa, its compound topology might have emerged as a result of the constraints faced by taxonomically distant pollinators when using the resources offered by different plant families and genera.…”

Section: Discussionmentioning

confidence: 77%

“…Finally, we quantified node specialization using Blüthgen's d’ , which measures the specialization of a node to a set of other nodes and varies from 0 to 1 (Blüthgen, 2010). A more specialized node ( d’ → 1) is assumed to represent a species that makes a set of interactions different from those made by other species of the same network (Mello et al., 2019).…”

Section: Methodsmentioning

confidence: 99%

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Bats and hawkmoths form mixed modules with flowering plants in a nocturnal interaction network

Queiroz¹,

Diniz

Vázquez

et al. 2020

Biotropica

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Based on the conceptual framework of pollination syndromes, pollination networks should be composed of well-delimited subgroups formed by plants that diverge in floral phenotypes and are visited by taxonomically different pollinators. Nevertheless, floral traits are not always accurate in predicting floral visitors. For instance, flowers adapted to bat-pollination are larger and wider, enabling the exploitation by other nocturnal animals, such as hawkmoths. Thus, should an interaction network comprising bats and hawkmoths, the most important nocturnal pollinators in the tropics, be formed of mixed-taxon modules due to cross-syndrome interactions? Here, we analyzed such a network to test whether resource plants are shared between the two taxa, and how modules differ in terms of species morphologies. We sampled interactions through pollen grains collected from floral visitors in a Caatinga dry forest in northeastern Brazil. The network was modular yet interwoven by cross-syndrome interactions. Hawkmoths showed no restriction to visit the wider chiropterophilous flowers. Furthermore, bats represented a subset of a hawkmoth-dominated network, as they were restricted to chiropterophilous flowers due to constraints in accessing narrower sphingophilous flowers. As such, the bat-dominated module encompassed relatively wider flowers, but hawkmoths, especially long-tongued ones, were unrestricted by floral width or length. Thus, pollination of flowers with open architectures must be investigated with caution, as they are accessible to a wide array of floral visitors, which may result in mixed-pollination systems. Future research should continue to integrate different syndromes and pollinator groups in order to reach a better understanding of how pollination-related functions emerge from community-level interactions.

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Section: Discussionmentioning

confidence: 77%

Section: Methodsmentioning

confidence: 99%

Bats and hawkmoths form mixed modules with flowering plants in a nocturnal interaction network

Queiroz¹,

Diniz

Vázquez

et al. 2020

Biotropica

Self Cite

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“…Nested topologies are, thus, likely to occur in species interaction networks comprising low phylogenetic diversity (e.g., Flores et al, 2011), but unlikely in diverse networks (e.g., Flores et al, 2013). In diverse networks, topologies that include preferences, such as modular and compound, tend to predominate (Mello et al, 2019).…”

Section: Nestedness and Null Modelsmentioning

confidence: 99%

“…A nested matrix, according to our definition, cannot be modular at the same time, because it presents no preferences. However, nestedness and modularity are also not the opposite extremes of a continuum (Valverde et al, 2020) and, as in a modular network preferences are clustered, nestedness may still prevail within each module (Lewinsohn et al, 2006;Felix et al, 2017;Mello et al, 2019).…”

Section: Topologies Beyond Nestednessmentioning

confidence: 99%

Linking null models to hypotheses to improve nestedness analysis

Pinheiro

Dormann

Félix

et al. 2021

Preprint

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Aim: Nestedness is a common pattern in metacommunities and interaction networks, whose causes are still discussed. Nestedness inference is challenging because, beyond calculating an index, we need to compare observed values with values generated with a null model. There are different null models and the choice between them affects test outcomes. Furthermore, there is no established theoretical basis to guide this choice. Here, we propose a different look at the meaning of nestedness that improves our understanding of its causes and unveils the link between null models and hypotheses. Innovation: Nestedness of a matrix is a combination of marginal sum inequality and high overlap. The higher the overlap, the more predictable the cell values by marginal sums. Here, we show that nestedness actually measures how better one can predict cell values by marginal sums than by matrix dimensions and total sum alone. From this, we propose that two null models can be used to test for different topological hypotheses. The equiprobable model excludes all nestedness-generating mechanisms and provides the distribution of expected values for nestedness significance tests. The proportional model conserves nestedness-generating mechanisms and excludes nestedness-disrupting mechanisms, and thus, produces highly nested matrices. The proportional model provides the distribution of expected nestedness for nested matrices. Additionally, we evaluate the efficiency of several indices within this new perspective and illustrate our approach using an empirical plant-pollinator network. Main conclusions: Through a shift of perspective, our approach reconciliates contradictions in null model analysis and delimits the range of possible explanations for nestedness. The only way a process can increase nestedness in a matrix is by promoting marginal sum inequalities, without concomitantly introducing preferences. Consequently, in a species interaction network, explanations for nestedness should explain why some species interact more frequently than others.

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“…This model is hierarchical: a modular structure whose modules are internally nested. This compound topology is of special interest because it accords with common features of ecological and evolutionary scenarios [ 26 , 38 , 39 ]. To examine mutual information in these compound models, as before we set up square matrices with m internally nested modules.…”

Section: Complex Topologiesmentioning

confidence: 99%

Mutual Information as a General Measure of Structure in Interaction Networks

Corso

Ferreira

Lewinsohn

2020

Entropy

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Entropy-based indices are long-established measures of biological diversity, nowadays used to gauge partitioning of diversity at different spatial scales. Here, we tackle the measurement of diversity of interactions among two sets of organisms, such as plants and their pollinators. Actual interactions in ecological communities are depicted as bipartite networks or interaction matrices. Recent studies concentrate on distinctive structural patterns, such as nestedness or modularity, found in different modes of interaction. By contrast, we investigate mutual information as a general measure of structure in interactive networks. Mutual information (MI) measures the degree of reciprocal matching or specialization between interacting organisms. To ascertain its usefulness as a general measure, we explore (a) analytical solutions for different models; (b) the response of MI to network parameters, especially size and occupancy; (c) MI in nested, modular, and compound topologies. MI varies with fundamental matrix parameters: dimension and occupancy, for which it can be adjusted or normalized. Apparent differences among topologies are contingent on dimensions and occupancy, rather than on topological patterns themselves. As a general measure of interaction structure, MI is applicable to conceptually and empirically fruitful analyses, such as comparing similar ecological networks along geographical gradients or among interaction modalities in mutualistic or antagonistic networks.

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Insights into the assembly rules of a continent-wide multilayer network

Cited by 70 publications

References 55 publications

Bats and hawkmoths form mixed modules with flowering plants in a nocturnal interaction network

Bats and hawkmoths form mixed modules with flowering plants in a nocturnal interaction network

Linking null models to hypotheses to improve nestedness analysis

Mutual Information as a General Measure of Structure in Interaction Networks

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