Report on spatial sampling designs for long term biodiversity monitoring of soil biota

Soil biota are extremely diverse and spatially heterogeneous. Sampling strategies that target the soil biota through metabarcoding must incorporate existing ecological theory and explicitly consider technical constraints. This report synthesizes empirical research from large-scale projects (SpaceMic, PhytOakMeter) to evaluate how spatial sampling design—specifically sample extent, number, and size—influences metabarcoding-derived biodiversity estimates across a range of soil biota. We find that the practice of homogenizing several soil samples per plot into one composite sample results in linear increases in plot diversity with sample number (Spearman’s ρ > 0.96, p < 0.001), likely at the cost of sample completeness. Conversely, we found no effect of sample extent on plot-level diversity assessments, suggesting flexibility in plot sizing for monitoring programs but highlighting the importance of consistent plot sizing across a monitoring program. Finally, DNA extraction protocols, and their associated sample size, critically affect detectability: larger soil samples (10g vs. 0.5g) improved nematode diversity recovery, highlighting protocol-dependent biases. This study advocates for standardized, spatially explicit designs that take both a single and a composite sample per plot to ensure comparability in long-term datasets. Our insights provide actionable guidelines for enhancing the reproducibility and ecological relevance of soil metabarcoding in long-term monitoring initiatives.