A roadmap towards predicting species interaction networks (across space and time)
Autor: | Andrew Gonzalez, Timothée Poisot, Benjamin Mercier, Philippe Desjardins-Proulx, Dominique Caron, Laura J. Pollock, Norma R Forero-Muñoz, Michael D Catchen, Tanya Strydom, Francis Banville, Gabriel Dansereau, Gracielle Teixeira Higino, Dominique Gravel |
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Rok vydání: | 2021 |
Předmět: |
Structure (mathematical logic)
business.industry Computer science Ecology (disciplines) Deep learning Ecological forecasting Part IV: Novel Frameworks and Methodological Advances Variation (game tree) Biota Models Biological Data science General Biochemistry Genetics and Molecular Biology Host-Parasite Interactions Ecological network Spatio-Temporal Analysis Neural Networks Computer Artificial intelligence General Agricultural and Biological Sciences business Macroecology Global biodiversity |
Zdroj: | Philos Trans R Soc Lond B Biol Sci |
ISSN: | 1471-2970 0962-8436 |
DOI: | 10.1098/rstb.2021.0063 |
Popis: | 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’. |
Databáze: | OpenAIRE |
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