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Global biodiversity is declining at an ever-increasing rate. Yet effective policies to mitigate or reverse these declines require ecosystem condition data that are rarely available. Morphology-based bioassessment methods are difficult to scale, limited in scope, suffer prohibitive costs, require skilled taxonomists, and can be applied inconsistently between practitioners. Environmental DNA (eDNA) metabarcoding offers a powerful, reproducible and scalable solution that can survey across the tree-oflife with relatively low cost and minimal expertise for sample collection. However, there remains a need to condense the complex, multidimensional community information into simple, interpretable metrics of ecological health for environmental management purposes. We developed a riverine taxon-independent community index (TICI) that objectively assigns indicator values to amplicon sequence variants (ASVs), and significantly improves the statistical power and utility of eDNA-based bioassessments. The TICI model training step uses the Chessman iterative learning algorithm to assign health indicator scores to a large number of ASVs that are commonly encountered across a wide geographic range. New sites can then be evaluated for ecological health by averaging the indicator value of the ASVs present at the site. We trained a TICI model on an eDNA dataset from 53 well-studied riverine monitoring sites across New Zealand, each sampled with a high level of biological replication (nD16). Eight shortamplicon metabarcoding assays were used to generate data from a broad taxonomic range, including bacteria, microeukaryotes, fungi, plants, and animals. Site-specific TICI scores were strongly correlated with historical stream condition scores from macroinvertebrate assessments (macroinvertebrate community index or MCI; R² = 0:82), and TICI variation between sample replicates was minimal (CV = 0.013). Taken together, this demonstrates the potential for taxon-independent eDNA analysis to provide a reliable, robust and low-cost assessment of ecological health that is accessible to environmental managers, decision makers, and the wider community. [ABSTRACT FROM AUTHOR]

The application of DNA metabarcoding to dietary analysis of trophic generalists requires using multiple markers in order to overcome problems of primer specificity and bias. However, limited attention has been given to the integration of information from multiple markers, particularly when they partly overlap in the taxa amplified, and vary in taxonomic resolution and biases. Here, we test the use of a mix of universal and specific markers, provide criteria to integrate multi‐marker metabarcoding data and a python script to implement such criteria and produce a single list of taxa ingested per sample. We then compare the results of dietary analysis based on morphological methods, single markers, and the proposed combination of multiple markers. The study was based on the analysis of 115 faeces from a small passerine, the Black Wheatears (Oenanthe leucura). Morphological analysis detected far fewer plant taxa (12) than either a universal 18S marker (57) or the plant trnL marker (124). This may partly reflect the detection of secondary ingestion by molecular methods. Morphological identification also detected far fewer taxa (23) than when using 18S (91) or the arthropod markers IN16STK (244) and ZBJ (231), though each method missed or underestimated some prey items. Integration of multi‐marker data provided far more detailed dietary information than any single marker and estimated higher frequencies of occurrence of all taxa. Overall, our results show the value of integrating data from multiple, taxonomically overlapping markers in an example dietary data set. [ABSTRACT FROM AUTHOR]

DNA metabarcoding of food in animal scats provides a non-invasive dietary analysis method for vertebrates. A variety of molecular approaches can be used to recover dietary DNA from scats; however, many of these also recover non-food DNA. Blocking primers can be used to inhibit amplification of some non-target DNA, but this may not always be feasible, especially when multiple distinct non-target groups are present., We have developed scat collection protocols to optimise the detection of food DNA in vertebrate scat samples. Using shy albatross Thalassarche cauta as a case study, we investigated how DNA amplification success and the proportion of food DNA detected are influenced by both environmental and physiological parameters. We show that both the amount and type of non-target DNA vary with sample freshness, the collection substrate, fasting period and developmental stage of the consumer., Fresh scat samples yielded the highest proportion of food sequences. Collecting scats from dirt substrates reduced the proportion of food DNA and increased the proportion of contaminating DNA. Food DNA detection rates changed throughout the albatross breeding season and related to the time since feeding and the developmental stage of the animal. Fasting albatross produced scats dominated by parasite amplicons in universal PCR analysis, with little food DNA recovered. Samples from very young animals also produced reduced food DNA proportions., Based on our observations, we recommend the following procedures for field scat collections to ensure high-quality samples for dietary DNA metabarcoding studies. Ideally, (i) collect fresh scats; (ii) from surfaces with minimal contamination (e.g. rock or ice); (iii) collect scats from animals with minimum time since feeding and avoid fasting animals; (iv) avoid young animals that are not feeding directly (e.g. not weaned or fledged) or target larger/older individuals. The optimised field sampling protocols that we describe will improve the quality of dietary data from vertebrates by focusing on samples most likely to contain food DNA. They will also help minimise contamination issues from non-target DNA and provide standardised field methods in this rapidly expanding area of research. [ABSTRACT FROM AUTHOR]

We applied DNA-based faecal analysis to determine the diet of female Australian sea lions (n = 12) from two breeding colonies in South Australia. DNA dietary components of fish and cephalopods were amplified using the polymerase chain reaction and mitochondrial DNA primers targeting the short (~100 base pair) section of the 16S gene region. Prey diversity was determined by sequencing ~50 amplicons generated from clone libraries developed for each individual. Faecal DNA was also combined and cloned from multiple individuals at each colony and fish diversity determined. Diets varied between individuals and sites. Overall, DNA analysis identified a broad diversity of prey comprising 23 fish and five cephalopod taxa, including many species not previously described as prey of the Australian sea lion. Labridae (wrasse), Monacanthidae (leatherjackets) and Mullidae (goat fish) were important fish prey taxa. Commonly identified cephalopods were Octopodidae (octopus), Loliginidae (calamary squid) and Sepiidae (cuttlefish). Comparisons of fish prey diversity determined by pooling faecal DNA from several samples provided a reasonable but incomplete resemblance (55-71%) to the total fish diversity identified across individual diets at each site. Interpretation of diet based on the recovery of prey hard-parts identified one cephalopod beak ( Octopus sp.) and one fish otolith ( Parapriacanthus elongatus). The present study highlights the value of DNA-based analyses and their capabilities to enhance information of trophic interactions. [ABSTRACT FROM AUTHOR]