Disentangling nestedness from models of ecological complexity

James, Alex; Pitchford, Jonathan W.; Plank, Michael J.

doi:10.1038/nature11214

Cited by 214 publications

(234 citation statements)

References 17 publications

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“…This pattern was not the result of sampling limitations, as both NODF and Weighted NODF values were relatively stable, with as low as half of the full sampling effort and thus not to be expected to change with a higher sample size, but likely driven by species abundances. Taken altogether our results question the ecological relevance of Nestedness indices (see also James, Pitchford, & Plank 2012). Modularity has been increasingly used in network studies as it is strongly related to Nestedness (Fortuna et al 2010).…”

Section: Network Propertiesmentioning

confidence: 59%

Sampling completeness in seed dispersal networks: When enough is enough

Costa

Silva

Ramos

et al. 2016

Basic and Applied Ecology

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Ecological networks are an increasingly popular tool to explore community assembly rules and frame practical conservation issues. However, most described networks vary largely in sampling effort, hampering the distinction of true biological patterns from artefacts caused by poor sampling. Identifying entire seeds in the droppings of mist-netted birds is generally considered a preferred sampling method for building unbiased, quantitative seed dispersal networks. We retrieved seeds from the droppings of 936 mist-netted birds captured during five days in seven sites in Portugal and estimated sampling completeness as the diversity of seed species, disperser species, and links detected with respect to those predicted by Chao 2 estimator. In one of those sites, sampling effort was extended to 25 days to evaluate the sensitivity of ten network structure descriptors to increasing sampling effort. After five sampling days we detected 93% of the seed species, 97% of the disperser species, and 79% of the links predicted by Chao 2, however sampling for 25 days resulted in the detection of more seeds, dispersers, and links than those estimated at day 5. Most network descriptors only began to stabilize around day 8, except for Connectance and Weighted Connectance that stabilized earlier. Similarly, only after 8 days most networks descriptors significantly departed from the confidence interval estimated by null models exclusively constrained by species abundances, thus reflecting independent ecological patterns. Nestedness was the only exception, as it never departed from the null models. We suggest that Chao 2 may slightly underestimate the real diversity and that in our case at least eight sampling days were needed to build a sound seed dispersal network as 67% of the seeds, 88% of the dispersers, and 71% of the links were detected. Our results have important implications for the interpretation of seed dispersal networks because under-sampled networks may produce biased descriptors that do not suitably characterize the focal communities. ZusammenfassungÖkologische Netzwerke werden immer beliebter als eine Methode, um die 'assembly rules' für Gemeinschaften zu untersuchen und praktische Naturschutzregeln zu entwerfen.

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Section: Network Propertiesmentioning

confidence: 59%

Sampling completeness in seed dispersal networks: When enough is enough

Costa

Silva

Ramos

et al. 2016

Basic and Applied Ecology

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“…This is seemingly at odds with the prevailing view that nestedness promotes the persistence of species in mutualistic systems 8,9 (although recent work has begun to question this proposition 28 ). As an approach to assessing system robustness, Table S1).…”

Section: Resultsmentioning

confidence: 90%

The ghost of nestedness in ecological networks

2013

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Ecologists are fascinated by the prevalence of nestedness in biogeographic and community data, where it is thought to promote biodiversity in mutualistic systems. Traditionally, nestedness has been treated in a binary sense: species and their interactions are either present or absent, neglecting information on abundances and interaction frequencies. Extending nestedness to quantitative data facilitates the study of species preferences, and we propose a new detection method that follows from a basic property of bipartite networks: large dominant eigenvalues are associated with highly nested configurations. We show that complex ecological networks are binary nested, but quantitative preferences are non-nested, indicating limited consumer overlap of favoured resources. The spectral graph approach provides a formal link to local dynamical stability analysis, where we demonstrate that nested mutualistic structures are minimally stable. We conclude that, within the binary constraint of interaction plausibility, species preferences are partitioned to avoid competition, thereby benefiting system-wide resource allocation.

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“…Recent progress in resolving the complexity-stability debate has involved exploring the causal relationship between the architecture and stability of many mutualistic (e.g., plantfrugivore and plant-pollinator), trophic (food web) and antagonistic (predator-prey and host-parasite/pathogen) networks (e.g. Memmott et al 2004;Eklöf and Ebenman 2006;Bascompte et al 2006;Burgos et al 2007;Estrada 2007;Bastola et al 2009;Kiers et al 2010;Thébault and Fontaine 2010;Brose 2011;de Visser et al 2011;Stouffer and Bascompte 2011;James et al 2012), and explaining emergent network structures using dynamic network models with adaptive and random species rewiring (van Baalen et al 2001;Kondoh 2003;Rezende et al 2007;Vacher et al 2008;Valdovinos et al 2010;Zhang et al 2011;Suweis et al 2013;Minoarivelo et al 2014;Nuwagaba et al 2015).…”

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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Disentangling nestedness from models of ecological complexity

Cited by 214 publications

References 17 publications

Sampling completeness in seed dispersal networks: When enough is enough

Sampling completeness in seed dispersal networks: When enough is enough

The ghost of nestedness in ecological networks

Defining invasiveness and invasibility in ecological networks

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