Comparison of traditional and DNA metabarcoding samples for monitoring tropical soil arthropods (Formicidae, Collembola and Isoptera)

Abstract

The soil fauna of the tropics remains one of the least known components of the biosphere. Long-term monitoring of this fauna is hampered by the lack of taxonomic expertise and funding. These obstacles may potentially be lifted with DNA metabarcoding. To validate this approach, we studied the ants, springtails and termites of 100 paired soil samples from Barro Colorado Island, Panama. The fauna was extracted with Berlese-Tullgren funnels and then either sorted with traditional taxonomy and known, individual DNA barcodes (“traditional samples”) or processed with metabarcoding (“metabarcoding samples”). We detected 49 ant, 37 springtail and 34 termite species with 3.46 million reads of the COI gene, at a mean sequence length of 233 bp. Traditional identification yielded 80, 111 and 15 species of ants, springtails and termites, respectively; 98%, 37% and 100% of these species had a Barcode Index Number (BIN) allowing for direct comparison with metabarcoding. Ants were best surveyed through traditional methods, termites were better detected by metabarcoding, and springtails were equally well detected by both techniques. Species richness was underestimated, and faunal composition was different in metabarcoding samples, mostly because 37% of ant species were not detected. The prevalence of species in metabarcoding samples increased with their abundance in traditional samples, and seasonal shifts in species prevalence and faunal composition were similar between traditional and metabarcoding samples. Probable false positive and negative species records were reasonably low (13–18% of common species). We conclude that metabarcoding of samples extracted with Berlese-Tullgren funnels appear suitable for the long-term monitoring of termites and springtails in tropical rainforests. For ants, metabarcoding schemes should be complemented by additional samples of alates from Malaise or light traps.

Illuminating arthropod diversity in a tropical forest: Assessing biodiversity by automatic light trapping and DNA metabarcoding

“…Regional and global metabarcoding‐based studies are currently widely applied. Metabarcoding of pollen loads from pollinators has allowed us to identify the plant species they visit (Bell et al., 2017; Tommasi et al., 2021), as well as to identify terrestrial arthropods from bulk soil samples (Basset et al., 2022; Clarke et al., 2021; Kirse et al., 2021). Further, some applications yield trophic information (Šigut et al., 2017; Toju & Baba, 2018), reveal migratory patterns (Suchan et al., 2019), and even facilitate arthropod monitoring in different tree species based on DNA from rainwater percolating from them (Macher et al., 2023).…”

DNA metabarcoding and morphological identification reveal similar richness, taxonomic composition and body size patterns among flying insect communities

“…In addition, our understanding of how well metabarcoding represents the composition of flying insect communities compared with conventional morphological methods is still incomplete. Several studies have shown that metabarcoding can perform similarly to morphological approaches (Elbrecht, Vamos, et al, 2017; Herrera‐Mesías et al, 2022; Liu et al, 2020), but the majority of studies come from aquatic ecosystems (Buchner, Macher, et al, 2021; Elbrecht & Leese, 2015; Groendahl et al, 2017; Mora et al, 2019; Steyaert et al, 2020; Zimmermann et al, 2015) or terrestrial soil fauna (Basset et al, 2022; Oliverio et al, 2018). Moreover, most studies only investigate a small subset of defined target species or higher taxonomic levels (e.g., family level or genus level), necessitating examinations of how well metabarcoding performs across the entire community at species level.…”

“…Moreover, most studies only investigate a small subset of defined target species or higher taxonomic levels (e.g., family level or genus level), necessitating examinations of how well metabarcoding performs across the entire community at species level. Furthermore, some studies do not compare identification methods using the same sample and specimens (e.g., Basset et al, 2022; Lobo et al, 2017; Mora et al, 2019; Schenk et al, 2020). Doing so can help to determine whether the same specimens identified by one method are also identified by the other.…”

Barcode 100K Specimens: In a Single Nanopore Run

“…2009, Von Cräutlein et al 2011, Antil et al 2023, Chac and Thinh 2023). Advances in high-throughput sequencing over this interval have enabled new approaches (eDNA, metabarcoding) which infer the species that contributed to DNA extracts prepared from environmental samples or bulk collections of specimens (Valentini et al 2016, Hallam et al 2021, Basset et al 2022, Cote et al 2023). However, these workflows require access to a reference library of barcode sequences constructed through the analysis of single specimens.…”