The limited spatial scale of dispersal in soil arthropods revealed with whole-community haplotype-level metabarcoding.
2020
Soil arthropod communities are highly diverse and critical for ecosystem functioning. However, our knowledge of spatial structure and the underlying processes of community assembly is scarce, hampered by limited empirical data on species diversity and turnover. We implement a high-throughput-sequencing approach to generate comparative data for thousands of arthropods at three hierarchical levels: genetic, species and supra-specific lineages. A joint analysis of the spatial arrangement across these levels can reveal the predominant processes driving the variation in biological assemblages at the local scale. This multi-hierarchical approach was performed using haplotype-level-COI metabarcoding of entire communities of mites, springtails and beetles from three Iberian mountain regions. Tens of thousands of specimens were extracted from deep and superficial soil layers and produced comparative phylogeographic data for >1000 co-distributed species and nearly 3000 haplotypes. Local assemblage composition differed greatly between grasslands and forests, and within each habitat showed strong spatial structure and high endemicity. Distance-decay was high at all levels, even at the scale of a few kilometres or less. The local distance-decay patterns were self-similar for the haplotypes and higher hierarchical entities, and this fractal structure was similar in all regions, suggesting that uniform processes of limited dispersal determine local-scale community assembly. Our results from whole-community metabarcoding provide insight into how dispersal limitations constrain mesofauna community structure within local spatial settings over evolutionary timescales. If generalized across wider areas, the high turnover and endemicity in the soil locally may indicate extremely high richness globally, challenging our current estimations of total arthropod-diversity on Earth.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
55
References
14
Citations
NaN
KQI