ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2024
Combining environmental DNA and remote sensing for efficient, fine-scale mapping of arthropod biodiversity.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Environmental DNA (eDNA) Technology in Biodiversity and Ecosystem Health Research: Advances and Prospects.Ecology and evolution · 2026Review
- High-throughput biodiversity surveying sheds new light on the brightest of insect taxa.Proceedings. Biological sciences · 2025Article
- Combining environmental DNA and remote sensing for efficient, fine-scale mapping of arthropod biodiversity.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Article
- Towards a toolkit for global insect biodiversity monitoring.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Arthropods contribute importantly to ecosystem functioning but remain understudied. This undermines the validity of conservation decisions. Modern methods are now making arthropods easier to study, since arthropods can be mass-trapped, mass-identified, and semi-mass-quantified into 'many-row (observation), many-column (species)' datasets, with homogeneous error, high resolution, and copious environmental-covariate information. These 'novel community datasets' let us efficiently generate information on arthropod species distributions, conservation values, uncertainty, and the magnitude and direction of human impacts. We use a DNA-based method (barcode mapping) to produce an arthropod-community dataset from 121 Malaise-trap samples, and combine it with 29 remote-imagery layers using a deep neural net in a joint species distribution model. With this approach, we generate distribution maps for 76 arthropod species across a 225 km
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