GUYASOILeDNA: a trans-kingdom and functional eDNA dataset on soil biodiversity from diverse land-cover types in French Guiana
Abstract
Soil biodiversity represents approximately 60% of all described species on Earth and plays a critical role in terrestrial ecosystem functioning. However, knowledge of tropical soil biota and their roles remains highly fragmentary, especially in hyperdiverse tropical regions that remain largely undersampled relative to their temperate counterparts. Recent non-invasive methods, such as environmental DNA (eDNA) metabarcoding, have enabled large-scale data collection across kingdoms of life and habitats, including understudied compartments such as soils. Here, GUYASOILeDNA is presented as the first large-scale eDNA metabarcoding dataset of tropical soil Bacteria (16S), Eukaryota (18S), Fungi (ITS1), and Insecta (16S) from French Guiana. This dataset describes the distribution of 69,881 operational taxonomic units (OTUs) in 1,410 soil samples collected across a variety of forest types, savannas, pastures, and urban areas. In addition, functional annotations based on trophic guild assignments are provided for 51% of the OTUs. This dataset can be used for meta-analyses, exploring soil taxonomic and functional diversity in relation to environmental factors, studying spatial associations among soil groups, and informing protected area management, among other applications. While this dataset represents an important first step toward understanding soil biodiversity in the region, it also reveals key gaps that may guide future research.
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BibTeX
@article{calderonsanou2026guyasoiledna,
title = {{GUYASOILeDNA: a trans-kingdom and functional eDNA dataset on soil biodiversity from diverse land-cover types in French Guiana}},
author = {Irene Calderón-Sanou and Finn Piatscheck and Anne-Sophie Benoiston and Jérôme Chave and Fabian Fischer and Marilou Hircq and Amaia Iribar and Eliane Louisanna and Frédéric Petitclerc and Jérémy Raynaud and Gaétan Rongier and Uxue Suescun-Darias and Shengli Tao and Valérie Troispoux and Lucie Zinger and Jérôme Murienne and Jérôme Orivel and Heidy Schimann},
journal = {Metabarcoding and Metagenomics},
year = {2026},
month = sep,
doi = {10.3897/mbmg.10.188340},
url = {https://hal.science/hal-05780412v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - GUYASOILeDNA: a trans-kingdom and functional eDNA dataset on soil biodiversity from diverse land-cover types in French Guiana
AU - Irene Calderón-Sanou
AU - Finn Piatscheck
AU - Anne-Sophie Benoiston
AU - Jérôme Chave
AU - Fabian Fischer
AU - Marilou Hircq
AU - Amaia Iribar
AU - Eliane Louisanna
AU - Frédéric Petitclerc
AU - Jérémy Raynaud
AU - Gaétan Rongier
AU - Uxue Suescun-Darias
AU - Shengli Tao
AU - Valérie Troispoux
AU - Lucie Zinger
AU - Jérôme Murienne
AU - Jérôme Orivel
AU - Heidy Schimann
PY - 2026
DA - 2026/09/29
JO - Metabarcoding and Metagenomics
DO - 10.3897/mbmg.10.188340
UR - https://hal.science/hal-05780412v1
AB - Soil biodiversity represents approximately 60% of all described species on Earth and plays a critical role in terrestrial ecosystem functioning. However, knowledge of tropical soil biota and their roles remains highly fragmentary, especially in hyperdiverse tropical regions that remain largely undersampled relative to their temperate counterparts. Recent non-invasive methods, such as environmental DNA (eDNA) metabarcoding, have enabled large-scale data collection across kingdoms of life and habitats, including understudied compartments such as soils. Here, GUYASOILeDNA is presented as the first large-scale eDNA metabarcoding dataset of tropical soil Bacteria (16S), Eukaryota (18S), Fungi (ITS1), and Insecta (16S) from French Guiana. This dataset describes the distribution of 69,881 operational taxonomic units (OTUs) in 1,410 soil samples collected across a variety of forest types, savannas, pastures, and urban areas. In addition, functional annotations based on trophic guild assignments are provided for 51% of the OTUs. This dataset can be used for meta-analyses, exploring soil taxonomic and functional diversity in relation to environmental factors, studying spatial associations among soil groups, and informing protected area management, among other applications. While this dataset represents an important first step toward understanding soil biodiversity in the region, it also reveals key gaps that may guide future research.
SN - 2534-9708
ER -