Ecological monitoring contributes to the understanding of complex ecosystem functions. The diets of fish reflect the surrounding environment and habitats and may, therefore, act as useful integrating indicators of environmental status. It is, however, often difficult to visually identify items in gut contents to species level due to digestion of soft‐bodied prey beyond visual recognition, but new tools rendering this possible are now becoming available. We used a molecular approach to determine the species identities of consumed diet items of an introduced generalist feeder, brown trout (Salmo trutta), in 10 Tasmanian lakes and compared the results with those obtained from visual quantification of stomach contents. We obtained 44 unique taxa (OTUs) belonging to five phyla, including seven classes, using the barcode of life approach from cytochrome oxidase I (COI). Compared with visual quantification, DNA analysis showed greater accuracy, yielding a 1.4‐fold higher number of OTUs. Rarefaction curve analysis showed saturation of visually inspected taxa, while the curves from the DNA barcode did not saturate. The OTUs with the highest proportions of haplotypes were the families of terrestrial insects Formicidae, Chrysomelidae, and Torbidae and the freshwater Chironomidae. Haplotype occurrence per lake was negatively correlated with lake depth and transparency. Nearly all haplotypes were only found in one fish gut from a single lake. Our results indicate that DNA barcoding of fish diets is a useful and complementary method for discovering hidden biodiversity.
In South Korea, the Eurasian otter (Lutra lutra (Linnaeus, 1758)), a semi-aquatic carnivore, is found mainly in lower order streams that tend to have a low abundance of preferred prey fish species. To investigate the relationship between resource use and availability, we used DNA barcoding to identify otter diet items in 24 otter spraints (faeces) from 16 sites along the Nakdong River basin from 4 to 6 June 2014. At these sites fish availability was assessed using scoop nets and casting nets. Fish formed the bulk of otter diet, which included also frogs, mammals, and reptiles. By DNA barcoding (success rate: 72.38%), we identified 79 prey items from 105 bone remains. The diet comprised mostly fish, but frogs, mammals, and reptiles were also identified. The fish fauna and otter diet composition differed significantly. Across the study sites, members of the Cyprinidae dominated in netted samples, but occurred less frequently in otter diet. Because most Cyprinidae are fast swimmers, otters also fed on benthic fishes and frogs, suggesting limited foraging flexibility in otters and specialization on more slowly moving prey.
We designed an experiment to analyze the gut content of Rotifera based on DNA barcoding and tested it on Asplanchna sp. in order to ensure that the DNA extracted from the rotifer species is from the food sources within the gut. We selected ethanol fixation (60%) to minimize the inflow effects of treated chemicals, and commercial bleach (the final concentration of 2.5%, for 210 s) to eliminate the extracellular DNA without damage to the lorica. Rotifers have different lorica structures and thicknesses. Therefore, we chose a pretreatment method based on Asplanchna sp., which is known to have weak durability. When we used the determined method on a reservoir water sample, we confirmed that the DNA fragments of Chlorophyceae, Diatomea, Cyanobacteria, and Ciliophora were removed. Given this result, Diatomea and cyanobacteria, detected from Asplanchna, can be considered as gut contents. However, bacteria were not removed by bleach, thus there was still insufficient information. Since the results of applying commercial bleach to rotifer species confirmed that pretreatment worked effectively for some species of rotifers food sources, in further studies, it is believed to be applicable to the gut contents analysis of more diverse rotifers species and better DNA analysis techniques by supplementing more rigorous limitations.
The complete mitochondrial genome of the freshwater bryozoan
Pectinatella magnifica
was sequenced. The circular mitochondrial genome is 17,539 bp and consists of 13 protein-coding, two ribosomal RNA, and 22 transfer RNA genes (GenBank accession no. MG546680). The Bayesian comparative analysis of molecular evolution rates revealed no acceleration of the mitochondrial DNA (mtDNA) evolution of
P. magnifica
. Results of maximum likelihood analysis showed that this species clustered with other species of the phylum Bryozoa.
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