ArticleEcology and evolution2025
Small Bugs, Big Data: Metagenomics for Arthropod Biodiversity Monitoring.
Article in Ecology and evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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
1 citing paper in PubMed.
- Small Bugs, Big Data: Metagenomics for Arthropod Biodiversity Monitoring.Ecology and evolution · 2025Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Obtaining genome-wide data from complex samples, such as environmental material or bulk species collections, is increasingly feasible, yet inferring species presence and population genomic insights remains challenging. We applied metagenomic sequencing to 40 arthropod bulk samples collected with Malaise traps across Sweden and compared results with metabarcoding of the same material. Using a custom genome database, we achieved genus-level classification largely consistent with metabarcoding. While metagenomics detected all genera identified by metabarcoding, conservative filtering thresholds designed to minimise false positives also excluded some true signals, particularly for low-abundance taxa. Taxonomic overlap between methods was further constrained by limited reference database representation. Beyond taxonomic assignment, metagenomic sequencing yielded genome-level information: we inferred haplotype diversity, heterozygosity and geographic population structure for several abundant species, including variable degrees of hybrid origin in red wood ants and the genetic distinctiveness of Gotland bumblebees. Finally, by-catch plant DNA present in the bulk samples revealed plausible arthropod-plant interactions, several of which align with known ecological associations. Together, these results demonstrate the potential of metagenomics for biodiversity monitoring and population genomics, while underscoring the importance of filtering criteria and comprehensive reference databases.
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