Next-Generation Global Biomonitoring: Large-scale, Automated Reconstruction of Ecological Networks
Open accessAbstract
We foresee a new global-scale, ecological approach to biomonitoring emerging within the next decade that can detect ecosystem change accurately, cheaply, and generically. Next-generation sequencing of DNA sampled from the Earth's environments would provide data for the relative abundance of operational taxonomic units or ecological functions. Machine-learning methods would then be used to reconstruct the ecological networks of interactions implicit in the raw NGS data. Ultimately, we envision the development of autonomous samplers that would sample nucleic acids and upload NGS sequence data to the cloud for network reconstruction. Large numbers of these samplers, in a global array, would allow sensitive automated biomonitoring of the Earth's major ecosystems at high spatial and temporal resolution, revolutionising our understanding of ecosystem change.
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There has been much recent work on applying ILP in ecology.
“There has been much recent work on applying ILP in ecology (Bohan et al., 2011; Tamaddoni-Nezhad et al., 2014; Bohan et al., 2017).”
From Inductive Logic Programming At 30: A New Introduction (2022) · cites this paper as Bohan et al., 2017
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References 73 · Cited by 200
Research works printed but not linked: 9
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- Authors
- Bohan, D. A., Vacher, C., Tamaddoni-Nezhad, A., Raybould, A., Dumbrell, A. J., & Woodward, G.
- Affiliations
- Université de Bourgogne (FR)
- Université de Bordeaux (FR)
- Syngenta (France) (FR)
- University of Essex (GB)
- University of Trieste (IT)
- Corresponding author
- Bohan, David A.
- Venue
- Trends in Ecology & Evolution
- Publisher
- Elsevier BV
- Published
- 2017-07
- Volume
- 32
- Issue
- 7
- Pages
- 477-487
- ISSN
- 0169-5347 (ISSN-L)
- OpenAlex
- W2601528672
- Cited by
- 200
- References
- 73
- Citations by year
- 2026: 10 · 2025: 12 · 2024: 19 · 2023: 28 · 2022: 26 · 2021: 30 · 2020: 18 · 2019: 29 · 2018: 19 · 2017: 8
- FWCI
- 1.70
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Trends in Ecology & Evolution (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Open Access at Essex (University of Essex) (acceptedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by-nc-nd)
- HAL (submittedVersion)
- Oskar-Bordeaux (Universite de Bordeaux) (submittedVersion, cc-by-sa)
- Spiral (Imperial College London) (submittedVersion, other-oa)
- Funders
- Imperial College London
- Agence Nationale de la Recherche (ANR-15-SUSF-0002)
- Institut National de la Recherche Agronomique
- Natural Environment Research Council (NE/M02086X/1, NE/M020843/1)
- Topics
- Physical Sciences › Environmental Science › Ecology › Environmental DNA in Biodiversity Studies
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Ecology and Vegetation Dynamics Studies
- Keywords
- next-generation sequencing, environmental DNA, operational taxonomic units, machine learning, ecosystem change detection, ecological interactions
- MeSH terms
- Machine Learning, DNA, Ecology, Environmental Monitoring, Sequence Analysis, DNA, Ecosystem, Biodiversity, High-Throughput Nucleotide Sequencing
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