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Biological surveys based on visual identification of the biota are challenging, expensive and time consuming, yet crucial for effective biomonitoring. DNA metabarcoding is a rapidly developing technology that can also facilitate biological surveys. This method involves the use of next generation sequencing technology to determine the community composition of a sample. However, it is uncertain as to what biological substrate should be the primary focus of metabarcoding surveys. This study aims to test multiple sample substrates (soil, scat, plant material and bulk arthropods) to determine what organisms can be detected from each and where they overlap. Samples (n = 200) were collected in the Pilbara (hot desert climate) and Swan Coastal Plain (hot Mediterranean climate) regions of Western Australia. Soil samples yielded little plant or animal DNA, especially in the Pilbara, probably due to conditions not conducive to long-term preservation. In contrast, scat samples contained the highest overall diversity with 131 plant, vertebrate and invertebrate families detected.Invertebrate and plant sequences were detected in the plant (86 families), pitfall (127 families) and vane trap (126 families) samples. In total, 278 families were recovered from the survey, 217 in the Swan Coastal Plain and 156 in the Pilbara. Aside from soil, 22%-43% of the families detected were unique to the particular substrate, and community composition varied significantly between substrates. These results demonstrate the importance of selecting appropriate metabarcoding substrates when undertaking terrestrial surveys. If the aim is to broadly capture all biota then multiple substrates will be required.

Anthropogenic disturbance is one of the most important forces shaping soil ecosystems. While organisms that live in the soil, such as arbuscular mycorrhizal (AM) fungi, are sensitive to disturbance, their response is not always predictable. Given the range of disturbance types and differences among AM fungi in their growth strategies, the unpredictability of the responses of AM fungi to disturbance is not surprising. We investigated the role of disturbance type (i.e., soil disruption, agriculture, host perturbation, and chemical disturbance) and fungus identity on disturbance response in the AM symbiosis. Using meta-analysis, we found evidence for differential disturbance response among AM fungal species, as well as evidence that particular fungal species are especially susceptible to certain disturbance types, perhaps because of their life history strategies.

Ecological restoration of landscapes is an integral part of the mining process. However, restoration is often constrained by a lack of consistent monitoring approaches. For example, the need for specialist techniques and trapping approaches often limits monitoring of fauna recovery. Application of molecular tools has made important contributions to understanding factors influencing restoration success. Here, we outline advances in next-generation sequencing methods, especially metabarcoding of environmental DNA. These have potential to revolutionize the practical contribution of genetics to the monitoring of fauna in a restoration context. DNA metabarcoding involves the simultaneous characterization of biota using DNA barcodes. It is a powerful method to assess the biodiversity contained within environmental samples (e.g. scats, bulk arthropods, soil, water, and sediment). This review outlines the challenges associated with current approaches to monitoring faunal biodiversity throughout ecological restoration. We also demonstrate how the emergence of DNA metabarcoding could recast monitoring capacity for improved ecological restoration outcomes, while discussing current limitations of a DNA-based approach to biodiversity assessment.

Invertebrate biomonitoring can reveal crucial information about the status of restoration projects; however, it is routinely underused because of the high level of taxonomic expertise and resources required. Invertebrate DNA metabarcoding has been used to characterize invertebrate biodiversity but its application in restoration remains untested. We use DNA metabarcoding, a new approach for restoration assessment, to explore the invertebrate composition from pitfall traps at two mine site restoration chronosequences in southwestern Australia. Invertebrates were profiled using two cytochrome oxidase subunit 1 assays to investigate invertebrate biodiversity. The data revealed differences between invertebrate communities at the two mines and between the different age plots of the chronosequences. Several characteristic taxa were identified for each age within the chronosequence, including springtails within the youngest sites (Order: Collembola) and millipedes within the oldest and reference sites (Order: Julida). This study facilitates development of a molecular “toolkit” for the monitoring of ecological restoration projects. We suggest that a metabarcoding approach shows promise in complementing current monitoring practices that rely on alpha taxonomy.

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Fauna monitoring often relies on visual monitoring techniques such as camera trapping, which have biases leading to underestimates of vertebrate species diversity. Environmental DNA (eDNA) metabarcoding has emerged as a new source of biodiversity data that may improve biomonitoring; however, eDNA‐based assessments of species richness remain relatively untested in terrestrial environments. We investigated the suitability of fallen log hollow sediment as a source of vertebrate eDNA, across two sites in southwestern Australia—one with a Mediterranean climate and the other semi‐arid. We compared two different approaches (camera trapping and eDNA metabarcoding) for monitoring of vertebrate species, and investigated the effect of other factors (frequency of species, timing of visits, frequency of sampling, and body size) on vertebrate species detectability. Metabarcoding of hollow sediments resulted in the detection of higher species richness in comparison (29 taxa: six birds, three reptiles, and 20 mammals) to metabarcoding of soil at the entrance of the hollow (13 taxa: three birds, two reptiles, and eight mammals). We detected 31 taxa in total with eDNA metabarcoding and 47 with camera traps, with 14 taxa detected by both (12 mammals and two birds). By comparing camera trap data with eDNA read abundance, we were able to detect vertebrates through eDNA metabarcoding that had visited the area up to two months prior to sample collection. Larger animals were more likely to be detected, and so were vertebrates that were identified multiple times in the camera traps. These findings demonstrate the importance of substrate selection, frequency of sampling, and animal size, on eDNA‐based monitoring. Future eDNA experimental design should consider all these factors as they affect detection of target taxa.