Characterising Soil Eukaryotic Diversity From NEON Metagenomics Datasets

TL;DR

This study explores soil eukaryotic diversity using NEON data, revealing patterns linked to environmental factors like pH and land management.

Contribution

The study provides the first large-scale analysis of soil eukaryotes in NEON metagenomics data using a custom pipeline.

Findings

Eukaryotic richness was negatively correlated with soil pH.

Managed sites reduced eukaryotic richness by 47%.

Fire and biome differences significantly influenced eukaryotic community composition.

Abstract

Belowground eukaryotic diversity serves a vital role in soil ecosystem functioning, yet the composition, structure, and macroecology of these communities are significantly under‐characterized. The National Ecological Observatory Network (NEON) provides publicly available datasets from long‐term surveillance of numerous taxa and ecosystem properties. However, this dataset is not routinely evaluated for its eukaryotic component, likely because analyzing metagenomes for eukaryotic sequences is hampered by low relative sequence abundance, large genomes, poorer eukaryote representation in public reference databases, and is not yet mainstream. We mined the NEON soil metagenome datasets for 18S rRNA sequences using a custom‐built pipeline and produced a preliminary assessment of biodiversity trends in North American soil eukaryotes. We extracted ~800 18S rRNA reads per sample (~22,000 reads per site) from 1455 samples from 495 plots across 45 NEON sites in 11 biomes, which corresponded to 5183 genera in 35 phyla. To our knowledge, this represents the first large‐scale soil eukaryote analysis of NEON data. We asked whether taxonomic richness paralleled patterns previously established ecological trends and found that eukaryotic richness was negatively correlated with pH, managed sites lowered eukaryotic richness by 47%, most biomes had a distinct eukaryotic community, and fire decreased eukaryotic richness. These findings parallel generally accepted ecological trends and support the notion that NEON soil metagenome datasets can and should be used to explore spatiotemporal patterns in soil eukaryote diversity, its association with ecosystem functioning, and its response to environmental changes in North America.

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