Reconstruction of plant–pollinator networks from observational data

Young, Jean-Gabriel; Valdovinos, Fernanda S.; Newman, M. E. J.

doi:10.1101/754077

Cited by 10 publications

(12 citation statements)

References 54 publications

(86 reference statements)

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“…For instance, the map equation assumes complete data and, when networks are sparse and may contain missing links, the optimal solution is distorted (Smiljanić et al, 2020). To overcome these obstacles, further investigation should consider the use of improved flow-based community detection algorithms in development (Smiljanić et al, 2020;Young et al, 2020Young et al, , 2021.…”

Section: Appendix 3: Sampling Coverage Of Caracoles (2020)mentioning

confidence: 99%

Multilayer diffusion networks as a tool to assess the structure and functioning of fine grain sub-specific plant-pollinator networks

Allen‐Perkins

Hurtado

García‐Callejas

et al. 2021

Preprint

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Ecological networks are a widely used tool to understand the dynamics of ecological communities in which plants interact with their pollinator counterparts. However, while most mutualistic networks have been defined at the species level, ecological processes, such as pollination, take place at the individual level. This recognition has led to the development of individual-based networks, yet current approaches only account for individuals of a single plant species due to conceptual and mathematical limitations. Here, we introduce a multilayer framework designed to depict the conspecific and heterospecific pollen flows mediated by floral visitors among plant individuals belonging to different species. Pollen transfer is modeled as a transport-like system, where an ensemble of conspecific plant-pollinator “circuits” are coupled through pollinators. With this physical conceptualization of ecological processes, we investigate how the reproductive success of plant individuals is affected by the overall dynamics of the whole multilayer network (macrostructure), as well as by their local position within the network (mesostructure). To illustrate this multiscale analysis, we apply it to a dataset of nine well-resolved individual plant-pollinator interaction networks from annual plant grasslands. Our results show that the resulting individual-based networks are highly modular, with insect visitors effectively connecting individuals of the same and different plant species. We also obtain empirical evidence that network structure is critical for modulating individual plant reproduction. In particular, the mesoscale level is the best descriptor of plant reproductive success, as it integrates the net effect of local heterospecific and conspecific interactions on seed production of a given individual. We provide a simple, but robust set of metrics to scale down network ecology to functioning properties at the individual level, where most ecological processes take place, hence moving forward the description and interpretation of multitrophic communities across scales.

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Section: Appendix 3: Sampling Coverage Of Caracoles (2020)mentioning

confidence: 99%

Multilayer diffusion networks as a tool to assess the structure and functioning of fine grain sub-specific plant-pollinator networks

Allen‐Perkins

Hurtado

García‐Callejas

et al. 2021

Preprint

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“…As is the case with most empirical networks, sampling of interactions in biological surveys is incomplete in our dataset. Studies show that sampling bias tends to strongly underestimate the number of interactions and overestimate the degree of specialization Young et al, 2019). To obtain a more reliable picture of pollination interactions across the AF, we applied a method of network reconstruction based on stochastic blockmodels to our metanetwork.…”

Section: Interaction Network Reconstructionmentioning

confidence: 99%

“…Network inference techniques developed in the domain of Network Science can help in the reconstruction of incomplete data (e.g. Peixoto 2018, Young et al 2019, allowing us to capture patterns at a large scale, gain further insight into ecosystem functioning, and hopefully build better conservation strategies.…”

Section: Introductionmentioning

confidence: 99%

Reconstruction and variability of tropical pollination networks in the Brazilian Atlantic Forest

Pereira

Ribeiro

Jordán³

et al. 2021

Preprint

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Loss of biodiversity comprehends not only the extinction of individual species, but also the loss of the ecological interactions among them. Survival of species, continuation of ecosystem functioning in nature, and ecosystem services to humans depend on the maintenance of well-functioning networks of species interactions (e.g. plant-pollinator networks and food webs). Analyses of ecological networks often rely on biased and incomplete survey data, especially in species-rich areas, such as the tropics.We used a network inference method to reconstruct pollination data compiled from a large tropical rainforest habitat extent. To gain insight into the characteristics of plant-pollinator interactions across the region, we combined the reconstructed pollination network with species distribution modeling to obtain local pollination networks throughout the area. We explored how global network properties relate to natural forest cover and land cover heterogeneity.We found that some network properties (the sum and evenness of link weights, connectance and nestedness) are positively correlated with forest cover, indicating that networks in sites with more natural habitat have greater diversity of interactions, stability and resilience. Modularity was not related to forest cover, but seemed to reflect habitat heterogeneity, due to the broad spatial scale of the study.We believe that the methodology suggested here can facilitate the use of incomplete network data in a reliable way, and allow us to better understand and protect networks of species interactions in high biodiversity regions of the world.

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“…Studies based on empirical observations of mutualism have revealed recurrent network patterns of these many-to-many interactions 12 , 13 . In a synthesis of these studies, Fernanda Valdovinos 28 , 29 highlighted five structural properties shared by mutualistic networks:…”

Section: Introductionmentioning

confidence: 99%

Socio-semantic networks as mutualistic networks

St-Onge

Renaud-Desjardins²,

Mongeau

et al. 2022

Sci Rep

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Several studies have shown that discourse and social relationships are intertwined and co-evolve. However, we lack theoretical models to explain the phenomenon. Inspired by recent work in ecology, we propose to model socio-semantic networks as an interaction between two intermingled data generating processes: a social community process and a document-based process. We consider the link between semantic and social ties as analogous to the interactions found in pollination networks whereby agents visit hidden topics in a similar way that insects visit specific plants for pollination. We use the ENRON socio-semantic email network to investigate if it exhibits properties that characterize mutualistic networks, namely moderate connectance, heterogeneous degree distribution, moderate modularity and high nestedness. To do so, we build a plant-pollinator matrix where “insect species” are communities detected via block modelling, “plant species” are latent topics detected with topic modelling, and the interaction between the two is the total number of visits a community makes to specific topics. Our results show that the ENRON socio-semantic interaction matrix respects the aforementioned criteria of mutualism paving the way for the development of a relevant framework to better understand the dynamic of human socio-semantic interactions.

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Reconstruction of plant–pollinator networks from observational data

Cited by 10 publications

References 54 publications

Multilayer diffusion networks as a tool to assess the structure and functioning of fine grain sub-specific plant-pollinator networks

Multilayer diffusion networks as a tool to assess the structure and functioning of fine grain sub-specific plant-pollinator networks

Reconstruction and variability of tropical pollination networks in the Brazilian Atlantic Forest

Socio-semantic networks as mutualistic networks

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