ReviewPhilosophical transactions of the Royal Society of London. Series B, Biological sciences2021
A roadmap towards predicting species interaction networks (across space and time).
Review in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Construction of a potential ecological network based on public datasets: a case study in Tuscany.Data in brief · 2026Article
- Shaping research in marine functional connectivity for integrated and effective marine science and management.Biological reviews of the Cambridge Philosophical Society · 2026Review
- Biotic interactions biogeography: A framework for understanding how species interactions shape biodiversity patterns across scales.PLoS biology · 2026Review
- A comprehensive, multi-method dataset of plant-frugivore interactions in a Mediterranean hotspot.Scientific data · 2026Article
- Predicting missing links in food webs using stacked models and species traits.Nature communications · 2026Article
- Impacts of warmer temperatures on secondary seed dispersal byCurrent research in insect science · 2026Article
- Network theory predicts ecosystem robustness across environmental conditions.Proceedings. Biological sciences · 2025Article
- Deciphering Probabilistic Species Interaction Networks.Ecology letters · 2025Review
- Community density patterns estimated by species distribution modeling: The case study of an insect virus interaction.PloS one · 2025Article
- Understanding ecological systems using knowledge graphs: an application to highly pathogenic avian influenza.Bioinformatics advances · 2025Article
- Spatially explicit predictions of food web structure from regional-level data.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Article
- What constrains food webs? A maximum entropy framework for predicting their structure with minimal biases.PLoS computational biology · 2023Article
- Predicting the potential impacts of climate change on the endangered endemic annonaceae species in east africa.Heliyon · 2023Article
- Mismatch between IUCN range maps and species interactions data illustrated using the Serengeti food web.PeerJ · 2023Article
- Infectious disease macroecology: parasite diversity and dynamics across the globe.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021Article
- Phanerozoic parasitism and marine metazoan diversity: dilution versus amplification.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021Article
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Networks of species interactions underpin numerous ecosystem processes, but comprehensively sampling these interactions is difficult. Interactions intrinsically vary across space and time, and given the number of species that compose ecological communities, it can be tough to distinguish between a true negative (where two species never interact) from a false negative (where two species have not been observed interacting even though they actually do). Assessing the likelihood of interactions between species is an imperative for several fields of ecology. This means that to predict interactions between species-and to describe the structure, variation, and change of the ecological networks they form-we need to rely on modelling tools. Here, we provide a proof-of-concept, where we show how a simple neural network model makes accurate predictions about species interactions given limited data. We then assess the challenges and opportunities associated with improving interaction predictions, and provide a conceptual roadmap forward towards predictive models of ecological networks that is explicitly spatial and temporal. We conclude with a brief primer on the relevant methods and tools needed to start building these models, which we hope will guide this research programme forward. This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.