When conserving native biodiversity, it is particularly important to consider invertebrates, a diverse and functionally important component of biodiversity. However, their inclusion in monitoring and conservation planning has lagged behind larger fauna because collecting, sorting and identifying invertebrates using conventional monitoring techniques is often expensive, time consuming and restricted by expertise in diagnostics. Emerging DNA metabarcoding techniques could potentially revolutionise monitoring of invertebrates by providing the ability to characterise entire communities from a single, easily collected environmental sample. We aimed to characterise the invertebrate fauna of an isolated, coastal forest fragment in New Zealand using the same level of financial investment for conventional invertebrate monitoring (pitfall and malaise traps) and a DNA metabarcoding approach applied to two alternative sample types (conventional invertebrate samples and soil samples). The bulk invertebrate and soil DNA metabarcoding methods were able to reproduce ecological patterns observed in the beetle community detected using conventional sampling. The soil DNA metabarcoding method detected a different beetle community and a more diverse array of invertebrate taxa than conventional sampling techniques. DNA metabarcoding offers conservation managers a practical, cost-effective technique for characterising whole invertebrate communities. However, increasing the taxonomic coverage of reference sequence databases (particularly for New Zealand invertebrates) through DNA barcoding efforts should be the focus of future research as it would improve the utility of metabarcoding methods for invertebrate monitoring, which would complement conventional techniques.
Abstract. Understanding the responses of biodiversity to different land use regimes is critical for managing biodiversity in the face of future land use change. However, there is still significant uncertainty around how consistent the responses of different taxonomic groups to land use change are. Here, we use a combination of high-throughput environmental DNA sequencing and traditional field-based survey methods to examine how patterns of richness and community composition correlate among four domains/kingdoms (bacteria, fungi, plants, and metazoans) and the four most-abundant animal taxonomic groups (arachnids, Collembola, insects, and nematodes) across five different land use types (natural forest, planted forest, unimproved grassland, improved grassland, and vineyards). Richness for each taxonomic group varied between land use types, yet different taxa showed inconsistent responses to land use, and their richness was rarely correlated. This contrasted with community composition of taxonomic groups, for which there was relatively good discrimination of land use types and there was strong correlation between group responses. We found little evidence for consistent drivers of taxonomic richness, yet identified several significant drivers of community composition that were shared across many groups. Drivers of composition were not the same as the drivers of diversity, suggesting diversity and composition are independently controlled. While land use intensification has been viewed as having generally negative effects on biodiversity, our results provide evidence that different taxa respond divergently across different land uses. Further, our study demonstrates the power of high-throughput sequencing of environmental DNA as a tool for addressing broad ecological patterns relating to landscape biodiversity.
Globally, wetlands are in decline due to anthropogenic modification and climate change. Knowledge about the spatial distribution of biodiversity and biological processes within wetlands provides essential baseline data for predicting and mitigating the effects of present and future environmental change on these critical ecosystems. To explore the potential for environmental DNA (eDNA) to provide such insights, we used 16S rRNA metabarcoding to characterise prokaryote communities and predict the distribution of prokaryote metabolic pathways in peats and sediments up to 4m below the surface across seven New Zealand wetlands. Our results reveal distinct vertical structuring of prokaryote communities and metabolic pathways in these wetlands. We also find evidence for differences in the relative abundance of certain metabolic pathways that may correspond to the degree of anthropogenic modification the wetlands have experienced. These patterns, specifically those for pathways related to aerobic respiration and the carbon cycle, can be explained predominantly by the expected effects of wetland drainage. Our study demonstrates that eDNA has the potential to be an important new tool for the assessment and monitoring of wetland health.
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