Uncovering indirect interactions in bipartite ecological networks

AbstractIndirect interactions play an essential role in governing population, community and coevolutionary dynamics across a diverse range of ecological communities. Such communities are widely represented as bipartite networks: graphs depicting interactions between two groups of species, such as plants and pollinators or hosts and parasites. For over thirty years, studies have used indices, such as connectance and species degree, to characterise the structure of these networks and the roles of their constituent species. However, compressing a complex network into a single metric necessarily discards large amounts of information about indirect interactions. Given the large literature demonstrating the importance and ubiquity of indirect effects, many studies of network structure are likely missing a substantial piece of the ecological puzzle. Here we use the emerging concept of bipartite motifs to outline a new framework for bipartite networks that incorporates indirect interactions. While this framework is a significant departure from the current way of thinking about networks, we show that this shift is supported by quantitative analyses of simulated and empirical data. We use simulations to show how consideration of indirect interactions can highlight ecologically important differences missed by the current index paradigm. We extend this finding to empirical plant-pollinator communities, showing how two bee species, with similar direct interactions, differ in how specialised their competitors are. These examples underscore the need for a new paradigm for bipartite ecological networks: one incorporating indirect interactions.

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Extinction models of robustness for weighted ecological networks

10.1101/186577 ◽

2017 ◽

Cited By ~ 1

Author(s):

Miranda S. Bane ◽

Michael J. O. Pocock ◽

Richard James

Keyword(s):

Network Structure ◽

Structural Heterogeneity ◽

Ecological Networks ◽

List Type ◽

Bipartite Networks ◽

Opposing Effects ◽

The Impact ◽

Plant Pollinator ◽

Binary Networks ◽

New Framework

AbstractAnalysis of ecological networks is a valuable approach to understanding the vulnerability of systems to environmental change. The tolerance of ecological networks to co-extinctions, resulting from sequences of primary extinctions, is a widely-used tool for modelling network ‘robustness’. Previously, these ‘extinction models’ have been developed for and applied mostly to binary networks and recently used to predict cascades of co-extinctions in plant-pollinator networks. There is a need for robustness models that can make the most of the weighted data available and most importantly there is a need to understand how the structure of a network affects its robustness.Here, we developed a framework of extinction models for bipartite ecological networks (specifically plant-pollinator networks). In previous models co-extinctions occurred when nodes lost all their links, but by relaxing this rule (according to a set threshold) our models can be applied to binary and weighted networks, and can permit structurally correlated extinctions, i.e. the potential for avalanches of extinctions. We tested how the average and the range of robustness values is impacted by network structure and the impact of structurally-correlated extinctions sampling non-uniformly from the distribution of random extinction sequences.We found that the way that structurally-correlated extinctions are modelled impacts the results; our two ecologically-plausible models produce opposing effects which shows the importance of understanding the model. We found that when applying the models to networks with weighted interactions, the effects are amplified and the variation in robustness increases. Variation in robustness is a key feature of these extinction models and is driven by the structural heterogeneity (i.e. the skewness of the degree distribution) of nodes (specifically, plant nodes) in the network.Our new framework of models enables us to calculate robustness with weighted, as well as binary, bipartite networks, and to make direct comparisons between models and between networks. This allows us to differentiate effects of the model and of the data (network structure) which is vital for those making ecological inferences from robustness models. The models can be applied to mutualistic and antagonistic networks, and can be extended to food webs.

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A continuum of specialists and generalists in empirical communities

10.1101/009985 ◽

2014 ◽

Author(s):

Timothée Poisot ◽

Sonia Kéfi ◽

Serge Morand ◽

Michal Stanko ◽

Pablo Marquet ◽

...

Keyword(s):

Research Question ◽

Biotic Interactions ◽

Theoretical Studies ◽

Ecological Communities ◽

Bipartite Networks ◽

Physical Constraints ◽

Animal Hosts ◽

Plant Herbivore ◽

Plant Pollinator ◽

Different Levels

Understanding the persistence of specialists and generalists within ecological communities is a topical research question, with far-reaching consequences for the maintenance of functional diversity. Although theoretical studies indicate that restricted conditions may be necessary to achieve co-occurrence of specialists and generalists, analyses of larger empirical (and species-rich) communities reveal the pervasiveness of coexistence. In this paper, we analyze 175 ecological bipartite networks of three interaction types (animal hosts-parasite, plant-herbivore and plant-pollinator), and measure the extent to which these communities are composed of species with different levels of specificity in their biotic interactions. We find a continuum from specialism to generalism. Furthermore, we demonstrate that diversity tends to be greatest in networks with intermediate connectance, and argue this is because of physical constraints in the filling of networks.

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bmotif: a package for motif analyses of bipartite networks

10.1101/302356 ◽

2018 ◽

Cited By ~ 2

Author(s):

Benno I. Simmons ◽

Michelle J. M. Sweering ◽

Maybritt Schillinger ◽

Lynn V. Dicks ◽

William J. Sutherland ◽

...

Keyword(s):

Scale Structure ◽

Individual Species ◽

Mathematical Framework ◽

List Type ◽

Bipartite Networks ◽

Diverse Range ◽

Wide Range ◽

Macro Scale ◽

Plant Pollinator ◽

Meso Scale

AbstractBipartite networks are widely-used to represent a diverse range of species interactions, such as pollination, herbivory, parasitism and seed dispersal. The structure of these networks is usually characterised by calculating one or more metrics that capture different aspects of network architecture. While these metrics capture useful properties of networks, they only consider structure at the scale of the whole network (the macro-scale) or individual species (the micro-scale). ‘Meso-scale’ structure between these scales is usually ignored, despite representing ecologically-important interactions. Network motifs are a framework for capturing this meso-scale structure and are gaining in popularity. However, there is no software available in R, the most popular programming language among ecologists, for conducting motif analyses in bipartite networks. Similarly, no mathematical formalisation of bipartite motifs has been developed.Here we introduce bmotif: a package for counting motifs, and species positions within motifs, in bipartite networks. Our code is primarily an R package, but we also provide MATLAB and Python code of the core functionality. The software is based on a mathematical framework where, for the first time, we derive formal expressions for motif frequencies and the frequencies with which species occur in different positions within motifs. This framework means that analyses with bmotif are fast, making motif methods compatible with the permutational approaches often used in network studies, such as null model analyses.We describe the package and demonstrate how it can be used to conduct ecological analyses, using two examples of plant-pollinator networks. We first use motifs to examine the assembly and disassembly of an Arctic plant-pollinator community, and then use them to compare the roles of native and introduced plant species in an unrestored site in Mauritius.bmotif will enable motif analyses of a wide range of bipartite ecological networks, allowing future research to characterise these complex networks without discarding important meso-scale structural detail.

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Reconstruction of plant–pollinator networks from observational data

10.1101/754077 ◽

2019 ◽

Author(s):

Jean-Gabriel Young ◽

Fernanda S. Valdovinos ◽

M. E. J. Newman

Keyword(s):

Food Webs ◽

Observational Data ◽

Network Structure ◽

Rare Species ◽

Statistical Technique ◽

Ecological Networks ◽

Statistical Analyses ◽

Published Data ◽

Statistical Errors ◽

Plant Pollinator

Empirical measurements of ecological networks such as food webs and mutualistic networks are often rich in structure but also noisy and error-prone, particularly for rare species for which observations are sparse. Focusing on the case of plant–pollinator networks, we here describe a Bayesian statistical technique that allows us to make accurate estimates of network structure and ecological metrics from such noisy observational data. Our method yields not only estimates of these quantities, but also estimates of their statistical errors, paving the way for principled statistical analyses of ecological variables and outcomes. We demonstrate the use of the method with an application to previously published data on plant–pollinator networks in the Seychelles archipelago, calculating estimates of network structure, network nestedness, and other characteristics.

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Motifs in bipartite ecological networks: uncovering indirect interactions

Oikos ◽

10.1111/oik.05670 ◽

2018 ◽

Vol 128 (2) ◽

pp. 154-170 ◽

Cited By ~ 11

Author(s):

Benno I. Simmons ◽

Alyssa R. Cirtwill ◽

Nick J. Baker ◽

Hannah S. Wauchope ◽

Lynn V. Dicks ◽

...

Keyword(s):

Ecological Networks ◽

Indirect Interactions

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The Structure of Ecological Networks Across Levels of Organization

Annual Review of Ecology Evolution and Systematics ◽

10.1146/annurev-ecolsys-012220-120819 ◽

2020 ◽

Vol 51 (1) ◽

pp. 433-460 ◽

Cited By ~ 1

Author(s):

Paulo R. Guimarães

Keyword(s):

Food Webs ◽

Ecological Systems ◽

Ecological Networks ◽

Ecological Communities ◽

Ecological Interactions ◽

Biological Organization ◽

Architectural Patterns ◽

Fundamental Challenge ◽

Spatiotemporal Scales ◽

Multiple Levels

Interactions connect the units of ecological systems, forming networks. Individual-based networks characterize variation in niches among individuals within populations. These individual-based networks merge with each other, forming species-based networks and food webs that describe the architecture of ecological communities. Networks at broader spatiotemporal scales portray the structure of ecological interactions across landscapes and over macroevolutionary time. Here, I review the patterns observed in ecological networks across multiple levels of biological organization. A fundamental challenge is to understand the amount of interdependence as we move from individual-based networks to species-based networks and beyond. Despite the uneven distribution of studies, regularities in network structure emerge across scales due to the fundamental architectural patterns shared by complex networks and the interplay between traits and numerical effects. I illustrate the integration of these organizational scales by exploring the consequences of the emergence of highly connected species for network structures across scales.

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On the temporally flexible structure of plant-pollinator interaction networks

10.1101/2020.04.11.037366 ◽

2020 ◽

Author(s):

Paul J. CaraDonna ◽

Nickolas M. Waser

Keyword(s):

Temporal Variation ◽

Network Structure ◽

Species Interactions ◽

Interspecific Interactions ◽

Activity Period ◽

Individual Species ◽

Ecological Communities ◽

Short Term ◽

Temporal Flexibility ◽

Plant Pollinator

AbstractEcological communities consist of species that are joined in complex networks of interspecific interaction. The interactions that networks depict often form and dissolve rapidly, but this temporal variation is not well integrated into our understanding of the causes and consequences of network structure. If interspecific interactions exhibit temporal flexibility across time periods over which organisms co-occur, then the emergent structure of the corresponding network may also be temporally flexible, something that a temporally-static perspective would miss. Here, we use an empirical system to examine short-term flexibility in network structure (connectance, nestedness, and specialization), and in individual species interactions that contribute to that structure. We investigated weekly plant-pollinator networks in a subalpine ecosystem across three summer growing seasons. To link the interactions of individual species to properties of their networks, we examined weekly temporal variation in species’ contributions to network structure. As a test of the potential robustness of networks to perturbation, we also simulated the random loss of species from weekly networks. We then compared the properties of weekly networks to the properties of cumulative networks that aggregate field observations over each full season. A week-to-week view reveals considerable flexibility in the interactions of individual species and their contributions to network structure. For example, species that would be considered relatively generalized across their entire activity period may be much more specialized at certain times, and at no point as generalized as the cumulative network may suggest. Furthermore, a week-to-week view reveals corresponding temporal flexibility in network structure and potential robustness throughout each summer growing season. We conclude that short-term flexibility in species interactions leads to short-term variation in network properties, and that a season-long, cumulative perspective may miss important aspects of the way in which species interact, with implications for understanding their ecology, evolution, and conservation.

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Macroevolutionary imprints on the assembly of frugivory networks

10.1101/2020.04.15.042754 ◽

2020 ◽

Author(s):

Gustavo Burin ◽

Paulo R. Guimarães ◽

Tiago B. Quental

Keyword(s):

Interaction Network ◽

Ecological Networks ◽

Species Number ◽

Ecological Communities ◽

Biological Interactions ◽

Deep Time ◽

Interacting Species ◽

History Of ◽

Current Interaction ◽

Biodiversity Changes

Biological interactions are a key aspect of ecological communities (Delmas et al., 2018). Current interaction network structures are snapshots of dynamic processes of community assembly (Thompson, 2005), and represent the product of the evolutionary history of interacting species over millions of years. Thus, assessing the deep time mechanisms affecting the assembly of ecological networks are key to better understand biodiversity changes in broader time scales (Jablonski, 2008). Here we integrate tools from macroevolutionary studies with network science to show that more central species in frugivory networks belong to lineages with higher macroevolutionary stability. This association is more pronounced in warmer, wetter, less seasonal environments, which highlights the role of environmental factors in shaping ecological networks. Furthermore, our results suggest that these environments possess a more diverse (either in species number or ecology) assemblage of species that can be sorted during network assembly. Lastly, we found evidence that the macro-evolutionary contribution to network stability changes in geographical space. This reinforces the idea that the macroevolutionary sorting mechanism acts at the regional pool of species, rather than selecting absolute paces of diversification. Hence our results suggest an interplay between ecological roles and diversification regimes in shaping the fate of lineages of plants and seed dispersing birds.

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Experimental evidence of the importance of multitrophic structure for species persistence

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2023872118 ◽

2021 ◽

Vol 118 (12) ◽

pp. e2023872118

Author(s):

Ignasi Bartomeus ◽

Serguei Saavedra ◽

Rudolf P. Rohr ◽

Oscar Godoy

Keyword(s):

Experimental Evidence ◽

Plant Species ◽

Trophic Level ◽

Species Interactions ◽

Trophic Levels ◽

Ecological Communities ◽

Mathematical Approach ◽

Species Persistence ◽

Factors Affecting ◽

Plant Pollinator

Ecological theory predicts that species interactions embedded in multitrophic networks shape the opportunities for species to persist. However, the lack of experimental support of this prediction has limited our understanding of how species interactions occurring within and across trophic levels simultaneously regulate the maintenance of biodiversity. Here, we integrate a mathematical approach and detailed experiments in plant–pollinator communities to demonstrate the need to jointly account for species interactions within and across trophic levels when estimating the ability of species to persist. Within the plant trophic level, we show that the persistence probability of plant species increases when introducing the effects of plant–pollinator interactions. Across trophic levels, we show that the persistence probabilities of both plants and pollinators exhibit idiosyncratic changes when experimentally manipulating the multitrophic structure. Importantly, these idiosyncratic effects are not recovered by traditional simulations. Our work provides tractable experimental and theoretical platforms upon which it is possible to investigate the multitrophic factors affecting species persistence in ecological communities.

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LifeWebs: A (global) database of bipartite ecological interaction networks

Biodiversity Information Science and Standards ◽

10.3897/biss.5.75626 ◽

2021 ◽

Vol 5 ◽

Author(s):

Philip Butterill ◽

Leonardo Jorge ◽

Shuang Xing ◽

Tom Fayle

Keyword(s):

Interaction Network ◽

Community Level ◽

Interaction Networks ◽

Sampling Effort ◽

Ecological Communities ◽

Bipartite Networks ◽

Data Types ◽

User Friendliness ◽

Global Database ◽

Machine Readable

The structure and dynamics of ecological interactions are nowadays recognized as a crucial challenge to comprehend the assembly, functioning and maintenance of ecological communities, their processes and the services they provide. Nevertheless, while standards and databases for information on species occurrences, traits and phylogenies have been established, interaction networks have lagged behind on the development of these standards. Here, we discuss the challenges and our experiences in developing a global database of bipartite interaction networks. LifeWebs*1 is an effort to compile community-level interaction networks from both published and unpublished sources. We focus on bipartite networks that comprise one specific type of interaction between two groups of species (e.g., plants and herbivores, hosts and parasites, mammals and their microbiota), which are usually presented in a co-occurrence matrix format. However, with LifeWebs, we attempt to go beyond simple matrices by integrating relevant metadata from the studies, especially sampling effort, explicit species information (traits and taxonomy/phylogeny), and environmental/geographic information on the communities. Specifically, we explore 1) the unique aspects of community-level interaction networks when compared to data on single inter-specific interactions, occurrence data, and other biodiversity data and how to integrate these different data types. 2) The trade-off between user friendliness in data input/output vs. machine-readable formats, especially important when data contributors need to provide large amounts of data usually compiled in a non-machine-readable format. 3) How to have a single framework that is general enough to include disparate interaction types while retaining all the meaningful information. We envision LifeWebs to be in a good position to test a general standard for interaction network data, with a large variety of already compiled networks that encompass different types of interactions. We provide a framework for integration with other types of data, and formalization of the data necessary to represent networks into established biodiversity standards.

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