The modularity of seed dispersal: differences in structure and robustness between bat– and bird–fruit networks

Mello, Marco A. R.; Marquitti, Flávia Maria Darcie; Guimarães, Paulo R.; Kalko, Elisabeth K. V.; Jordano, Pedro; Aguiar, Marcus A. M. de

doi:10.1007/s00442-011-1984-2

Cited by 123 publications

(105 citation statements)

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“…The number of modules and the level of modularity observed in pollination networks are found to be invariant to sampling efforts at different time (Dupont and Olesen 2012). Mello et al (2011) also noticed a high level of modularity in seed-dispersal networks. Little is known about the implication of modular structure to mutualistic network stability.…”

Section: Network Architecturementioning

confidence: 85%

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Complexity and stability of ecological networks: a review of the theory

et al. 2018

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Our planet is changing at paces never observed before. Species extinction is happening at faster rates than ever, greatly exceeding the five mass extinctions in the fossil record. Nevertheless, our lives are strongly based on services provided by ecosystems, thus the responses to global change of our natural heritage are of immediate concern. Understanding the relationship between complexity and stability of ecosystems is of key importance for the maintenance of the balance of human growth and the conservation of all the natural services that ecosystems provide. Mathematical network models can be used to simplify the vast complexity of the real world, to formally describe and investigate ecological phenomena, and to understand ecosystems propensity of returning to its functioning regime after a stress or a perturbation. The use of ecological-network models to study the relationship between complexity and stability of natural ecosystems is the focus of this review. The concept of ecological networks and their characteristics are first introduced, followed by central and occasionally contrasting definitions of complexity and stability. The literature on the relationship between complexity and stability in different types of models and in real ecosystems is then reviewed, highlighting the theoretical debate and the lack of consensual agreement. The summary of the importance of this line of research for the successful management and conservation of biodiversity and ecosystem services concludes the review.

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Section: Network Architecturementioning

confidence: 85%

“…Global (vs. local) stability implies that any (vs. small) perturbation from the equilibrium will be dampened. Global Ives et al (2000), Krause et al (2003), Thébault and Fontaine (2010) and Stouffer andBascompte (2011) Mutualism: Olesen et al (2007), Mello et al (2011) and Dupont and Olesen (2012) …”

Section: Network Stabilitymentioning

confidence: 99%

Complexity and stability of ecological networks: a review of the theory

et al. 2018

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“…The original network structure is lost, and the meaning of links is changed. In plant-pollinator networks, for example, links in the bipartite network represent pollination interactions, but in the projected networks a link between two species represents niche overlap (Ribeiro Mello et al 2011).…”

Section: Methodsmentioning

confidence: 99%

The architecture of weighted mutualistic networks

Gilarranz

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Galeano

2011

Oikos

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Several ecosystem services directly depend on mutualistic interactions. In species rich communities, these interactions can be studied using network theory. Current knowledge of mutualistic networks is based mainly on binary links; however, little is known about the role played by the weights of the interactions between species. What new information can be extracted by analyzing weighted mutualistic networks? In performing an exhaustive analysis of the topological properties of 29 weighted mutualistic networks, our results show that the generalist species, defined as those with a larger number of interactions in a network, also have the strongest interactions. Though most interactions of generalists are with specialists, the strongest interactions occur between generalists. As a result and by defining binary and weighted clustering coefficients for bipartite networks, we demonstrate that generalists form strongly-interconnected groups of species. The existence of these strong clusters reinforces the idea that generalist species govern the coevolution of the whole community.In the past few years, several studies have used complex network theory to unveil hidden secrets of nature. The patterns of interactions between species provide information about the stability of ecological communities ( One kind of ecological network, mutualistic networks, depicts the interactions of mutual benefit between species in a community. Here, a set of species A, generally animals, interacts with another set of species P, generally plants, but there are no interactions within sets. Such a network can also be referred to as a bipartite network. Species are represented as nodes, and the interactions between these species are represented by links. The information about interactions can be binary, where a link indicates just an interaction between two species, or can be weighted, where the weight represents how strong that interaction is (Bascompte and Jordano 2007).While the aforementioned works have analyzed the structural properties of mutualistic networks in their binary representation, a smaller but growing number of papers have analyzed the relevance of interaction weights. A seminal work by Bascompte and coworkers (Bascompte et al. 2006), found that the asymmetry of dependences (Jordano 1987) between species in an interaction allows for greater biodiversity. Scotti et al. (2007), analyzed how the rank of species importance, based on their position in the network, changes when considering interaction weights. Though the ranks where very different in food webs, they found smaller differences in plant-pollinator networks. Blüthgen et al. (2008), apply information theory measures to characterize the degree of specialization in quantitative mutualistic networks. Hwang et al. (2009), showed that species strength, defined as species' total number of visits, is correlated with species degree in six plant-pollinator networks. Despite these first studies, the complete structure of weighted mutualistic networks, and how interaction weights a...

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“…Although consensus on the structure of mutualistic networks has been reached (e.g. Bascompte et al 2003;Olesen et al 2007;Guimarães et al 2007;Thébault and Fontaine 2010;Mello et al 2011), there is still considerable debate with respect to antagonistic networks (e.g., on whether antagonistic networks are more compartmentalised than random expectation; e.g. Poisot 2013).…”

Section: Introductionmentioning

confidence: 99%

Defining invasiveness and invasibility in ecological networks

et al. 2016

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The success of a biological invasion is context dependent, and yet two key concepts-the invasiveness of species and the invasibility of recipient ecosystems-are often defined and considered separately. We propose a framework that can elucidate the complex relationship between invasibility and invasiveness. It is based on trait-mediated interactions between species and depicts the response of an ecological network to the intrusion of an alien species, drawing on the concept of community saturation. Here, invasiveness of an introduced species with a particular trait is measured by its per capita population growth rate when the initial propagule pressure of the introduced species is very low. The invasibility of the recipient habitat or ecosystem is dependent on the structure of the resident ecological network and is defined as the total width of an opportunity niche in the trait space susceptible to invasion. Invasibility is thus a measure of network instability. We also correlate invasibility with the asymptotic stability of resident ecological network, measured by the leading eigenvalue of the interaction matrix that depicts traitbased interaction intensity multiplied by encounter rate (a pairwise product of propagule pressure of all members in a community). We further examine the relationship between invasibility and network architecture, including network connectance, nestedness and modularity. We exemplify this framework with a trait-based assembly model under perturbations in ways to emulate fluctuating resources and random trait composition in ecological networks. The maximum invasiveness of a potential invader (greatest Electronic supplementary material The online version of this article

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The modularity of seed dispersal: differences in structure and robustness between bat– and bird–fruit networks

Cited by 123 publications

References 50 publications

Complexity and stability of ecological networks: a review of the theory

Complexity and stability of ecological networks: a review of the theory

The architecture of weighted mutualistic networks

Defining invasiveness and invasibility in ecological networks

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