Advances in DNA sequencing technology have revolutionized the field of molecular analysis of trophic interactions, and it is now possible to recover counts of food DNA sequences from a wide range of dietary samples. But what do these counts mean? To obtain an accurate estimate of a consumer's diet should we work strictly with data sets summarizing frequency of occurrence of different food taxa, or is it possible to use relative number of sequences? Both approaches are applied to obtain semi‐quantitative diet summaries, but occurrence data are often promoted as a more conservative and reliable option due to taxa‐specific biases in recovery of sequences. We explore representative dietary metabarcoding data sets and point out that diet summaries based on occurrence data often overestimate the importance of food consumed in small quantities (potentially including low‐level contaminants) and are sensitive to the count threshold used to define an occurrence. Our simulations indicate that using relative read abundance (RRA) information often provides a more accurate view of population‐level diet even with moderate recovery biases incorporated; however, RRA summaries are sensitive to recovery biases impacting common diet taxa. Both approaches are more accurate when the mean number of food taxa in samples is small. The ideas presented here highlight the need to consider all sources of bias and to justify the methods used to interpret count data in dietary metabarcoding studies. We encourage researchers to continue addressing methodological challenges and acknowledge unanswered questions to help spur future investigations in this rapidly developing area of research.

A plethora of pathogenic viruses colonize bats. However, bat bacterial flora and its zoonotic threat remain ill defined. In a study initially conducted as a quantitative metagenomic analysis of the fecal bacterial flora of the Daubenton’s bat in Finland, we unexpectedly detected DNA of several hemotrophic and ectoparasite-transmitted bacterial genera, including Bartonella. Bartonella spp. also were either detected or isolated from the peripheral blood of Daubenton's, northern, and whiskered bats and were detected in the ectoparasites of Daubenton's, northern, and Brandt's bats. The blood isolates belong to the Candidatus-status species B. mayotimonensis, a recently identified etiologic agent of endocarditis in humans, and a new Bartonella species (B. naantaliensis sp. nov.). Phylogenetic analysis of bat-colonizing Bartonella spp. throughout the world demonstrates a distinct B. mayotimonensis cluster in the Northern Hemisphere. The findings of this field study highlight bats as potent reservoirs of human bacterial pathogens.

To associate specimens identified by molecular characters to other biological knowledge, we need reference sequences annotated by Linnaean taxonomy. In this study, we (1) report the creation of a comprehensive reference library of DNA barcodes for the arthropods of an entire country (Finland), (2) publish this library, and (3) deliver a new identification tool for insects and spiders, as based on this resource. The reference library contains mtDNA COI barcodes for 11,275 (43%) of 26,437 arthropod species known from Finland, including 10,811 (45%) of 23,956 insect species. To quantify the improvement in identification accuracy enabled by the current reference library, we ran 1000 Finnish insect and spider species through the Barcode of Life Data system (BOLD) identification engine. Of these, 91% were correctly assigned to a unique species when compared to the new reference library alone, 85% were correctly identified when compared to BOLD with the new material included, and 75% with the new material excluded. To capitalize on this resource, we used the new reference material to train a probabilistic taxonomic assignment tool, FinPROTAX, scoring high success. For the full‐length barcode region, the accuracy of taxonomic assignments at the level of classes, orders, families, subfamilies, tribes, genera, and species reached 99.9%, 99.9%, 99.8%, 99.7%, 99.4%, 96.8%, and 88.5%, respectively. The FinBOL arthropod reference library and FinPROTAX are available through the Finnish Biodiversity Information Facility (www.laji.fi) at https://laji.fi/en/theme/protax. Overall, the FinBOL investment represents a massive capacity‐transfer from the taxonomic community of Finland to all sectors of society.

Diets play a key role in understanding trophic interactions. Knowing the actual structure of food webs contributes greatly to our understanding of biodiversity and ecosystem functioning. The research of prey preferences of different predators requires knowledge not only of the prey consumed, but also of what is available. In this study, we applied DNA metabarcoding to analyze the diet of 4 bird species (willow tits Poecile montanus, Siberian tits Poecile cinctus, great tits Parus major and blue tits Cyanistes caeruleus) by using the feces of nestlings. The availability of their assumed prey (Lepidoptera) was determined from feces of larvae (frass) collected from the main foraging habitat, birch (Betula spp.) canopy. We identified 53 prey species from the nestling feces, of which 11 (21%) were also detected from the frass samples (eight lepidopterans). Approximately 80% of identified prey species in the nestling feces represented lepidopterans, which is in line with the earlier studies on the parids' diet. A subsequent laboratory experiment showed a threshold for fecal sample size and the barcoding success, suggesting that the smallest frass samples do not contain enough larval DNA to be detected by high‐throughput sequencing. To summarize, we apply metabarcoding for the first time in a combined approach to identify available prey (through frass) and consumed prey (via nestling feces), expanding the scope and precision for future dietary studies on insectivorous birds.

A national crowdsourcing-based tick collection campaign was organized in 2015 with the objective of producing novel data on tick distribution and tick-borne pathogens in Finland. Nearly 20 000 Ixod...