1. DNA metabarcoding is a cost-effective species identification approach with great potential to assist entomological ecologists. This review presents a practical guide to help entomological ecologists design their own DNA metabarcoding studies and ensure that sound ecological conclusions can be obtained.2. The review considers approaches to field sampling, laboratory work, and bioinformatic analyses, with the aim of providing the background knowledge needed to make decisions at each step of a DNA metabarcoding workflow.3. Although most conventional sampling methods can be adapted to DNA metabarcoding, this review highlights techniques that will ensure suitable DNA preservation during field sampling and laboratory storage. The review also calls for a greater understanding of the occurrence, transportation, and deposition of environmental DNA when applying DNA metabarcoding approaches for different ecosystems.4. Accurate species detection with DNA metabarcoding needs to consider biases introduced during DNA extraction and PCR amplification, cross-contamination resulting from inappropriate amplicon library preparation, and downstream bioinformatic analyses. Quantifying species abundance with DNA metabarcoding is in its infancy, yet recent studies demonstrate promise for estimating relative species abundance from DNA sequencing reads. 5. Given that bioinformatics is one of the biggest hurdles for researchers new to DNA metabarcoding, several useful graphical user interface programs are recommended for sequence data processing, and the application of emerging sequencing technologies is discussed.
We sequenced nearly the entire mitochondrial genome of Argyroneta aquatica, a wholly underwater‐living spider, thereby enhancing the available genomic information for Arachnida. The confirmed sequences contained the complete set of known genes present in other metazoan mitochondrial genomes. However, the mitochondrial gene order of A. aquatica was distinctly different from that of the most distant Chelicerata Limulus polyphemus (Xiphosura), probably because of a series of gene translocations and/or inversions. Comparison of arachnid mitochondrial gene orders for the purpose of phylogenetic inference is only minimally useful, but provides a strong signal in closely related lineages. To test the basal relationships and the evolutionary pattern of tRNA gene rearrangements among Arachnida, phylogenetic analyses using amino acid sequences of the 13 protein‐coding genes were performed. An interesting feature, the five 135‐bp tandem repeats and two 363‐bp tandem repeats, was identified in the putative control region. Although control region tandem repeats have been reported in many other arachnid and metazoan species, this is the first time it has been described in spiders.
DNA metabarcoding is an emerging approach for monitoring biodiversity, but uncertainties remain about its capacity to detect subtle differences in invertebrate community composition comparable to those achievable based on conventional morphological identification. In this study, DNA metabarcoding and morphology-based approaches were compared as tools for investigating whether logging history impacted beetle communities in Tasmanian wet eucalypt forests. We compared 12 unlogged mature forest sites with 12 neighboring regeneration sites that had been logged approximately 55 years previously. The number of species identified based on morphology (173) was close to the number of zero-radius operational taxonomic units (ZOTUs) identified by DNA metabarcoding of cytochrome c oxidase subunit I (COI, 176) and 16S ribosomal RNA (16S, 156) markers. Subtle but significant differences in beetle species composition between regeneration and unlogged mature forests were captured by both morphology-based and COI DNA metabarcoding approaches, but not by 16S DNA metabarcoding. Our results support the suitability of mitochondrial COI for studying invertebrate biodiversity. A slight loss of signal compared to the morphology-based approach may be resolved by developing more comprehensive DNA reference databases. While confirming forest recovery of 48-58 years did not fully restore mature forest beetle communities, we suggest that DNA metabarcoding can be used for monitoring biodiversity and probing subtle differences in community composition.
Existing quantitative syntheses on how biodiversity responds to anthropogenic habitat change appear to sometimes mix different biodiversity metrics in drawing inferences. This “mixing metrics” practice, if prevalent, would considerably bias our understanding of biodiversity responses and render uninterpretable conclusions. However, the prevalence of this practice remains unknown, and the bias it potentially renders has not been empirically assessed. We fill this gap by conducting a systematic literature assessment of existing syntheses on biodiversity responses to habitat change, along with an analysis of a global database specifically on forest restoration. We found that the “mixing metrics” practice was used in almost a quarter of existing syntheses across a wide range of ecosystem and habitat change types. This practice predictably altered the quantitative, and frequently even the qualitative, inferences on biodiversity responses to forest restoration, in ways contingent on the composition of metrics mixed. We call on future syntheses to be cognizant of the difference in metric meaning and behaviors, and to avoid mixing different metrics in studying biodiversity responses to habitat change.
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