Network embedding unveils the hidden interactions in the mammalian virome

Poisot, Timothée; Ouellet, Marie-Andrée; Mollentze, Nardus; Farrell, Maxwell J.; Becker, Daniel; Brierley, Liam; Albery, Gregory F.; Gibb, Rory; Seifert, Stephanie; Carlson, Colin J.

doi:10.1016/j.patter.2023.100738

Cited by 9 publications

(4 citation statements)

References 56 publications

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“…Similarly, predictive approaches are also increasingly used with other interaction types to highlight interaction hotspots on global scales (e.g. mapping geographical hotspots of predicted host-virus interactions between bats and betacoronaviruses [72], predicting the distribution of hidden interactions in the mammalian virome [73]). Our workflow offers the potential to bring these global predictions down to the local scale where they can be made more actionable, and vastly increases the diversity of ecological networks that can be projected in space.…”

Section: Discussionmentioning

confidence: 99%

Spatially explicit predictions of food web structure from regional-level data

Dansereau,

Barros,

Poisot

2024

Phil. Trans. R. Soc. B

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Knowledge about how ecological networks vary across global scales is currently limited given the complexity of acquiring repeated spatial data for species interactions. Yet, recent developments in metawebs highlight efficient ways to first document possible interactions within regional species pools. Downscaling metawebs towards local network predictions is a promising approach to using the current data to investigate the variation of networks across space. However, issues remain in how to represent the spatial variability and uncertainty of species interactions, especially for large-scale food webs. Here, we present a probabilistic framework to downscale a metaweb based on the Canadian mammal metaweb and species occurrences from global databases. We investigated how our approach can be used to represent the variability of networks and communities between ecoregions in Canada. Species richness and interactions followed a similar latitudinal gradient across ecoregions but simultaneously identified contrasting diversity hotspots. Network motifs revealed additional areas of variation in network structure compared with species richness and number of links. Our method offers the potential to bring global predictions down to a more actionable local scale, and increases the diversity of ecological networks that can be projected in space. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

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Section: Discussionmentioning

confidence: 99%

Spatially explicit predictions of food web structure from regional-level data

Dansereau,

Barros,

Poisot

2024

Phil. Trans. R. Soc. B

Self Cite

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show abstract

“…Similarly, predictive approaches are also increasingly used with other interaction types to highlight interactions hotspots on global scales (e.g. mapping geographical hotspots of predicted host-virus interactions between bats and betacoronaviruses, Becker et al 2022; predicting the distribution of hidden interactions in the mammalian virome, Poisot et al 2023). Our workflow offers the potential to bring these global predictions down to the local scale where they can be made more actionable, and vastly increases the diversity of ecological networks that can be projected in space.…”

Section: Discussionmentioning

confidence: 99%

Spatially explicit predictions of food web structure from regional level data

Dansereau,

Barros,

Poisot

2023

Preprint

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Knowledge about how ecological networks vary across global scales is currently limited given the complexity of acquiring repeated data for species interactions. Yet, recent developments of metawebs highlight efficient ways to first document possible interactions within regional species pools. Downscaling metawebs towards local network predictions is a promising approach to use current data to investigate the variation of networks across space. However, issues remain in how to represent the spatial variability and uncertainty of species interactions, especially for large scale food webs. Here, we present a probabilistic framework to downscale a metaweb based on the Canadian mammal metaweb and species occurrences from GBIF. We investigate how our approach can be used to represent the variability of networks and communities between ecoregions in Canada. Our results highlighted mismatches in the distribution of species richness and interactions, especially in their within-ecoregion variability, indicating that interactions vary differently than species distributions over continental-scale gradients. Results summarized by ecoregion showed non-constant variation within and between ecologically meaningful biogeographic boundaries and identified contrasting diversity hotspots. Our method offers the potential to bring global predictions down to a more actionable local scale, and increases the diversity of ecological networks that can be projected in space.

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“…Branco et al, 2015). In a recent large-scale imputation of interactions in the mammal-virus networks, Poisot, Ouellet, et al (2021), for example, estimated that 93% of interac-…”

Section: What Are the Baseline Values Of Performance Measures?mentioning

confidence: 99%