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• W2593276489 abstract "Ecological restoration is a globally important and well-financed management intervention used to combat biodiversity declines and land degradation. Most restoration aims to increase biodiversity towards a reference state, but there are concerns that intended outcomes are not reached due to unsuccessful interventions and land-use legacy issues. Monitoring biodiversity recovery is essential to measure success; however, most projects remain insufficiently monitored. Current field-based methods are hard to standardize and are limited in their ability to assess important components of ecosystems, such as bacteria. High-throughput amplicon sequencing of environmental DNA (metabarcoding of eDNA) has been proposed as a cost-effective, scalable and uniform ecological monitoring solution, but its application in restoration remains largely untested. Here we show that metabarcoding of soil eDNA is effective at demonstrating the return of the native bacterial community in an old field following native plant revegetation. Bacterial composition shifted significantly after 8 years of revegetation, where younger sites were more similar to cleared sites and older sites were more similar to remnant stands. Revegetation of the native plant community strongly impacted on the belowground bacterial community, despite the revegetated sites having a long and dramatically altered land-use history (i.e. >100 years grazing). We demonstrate that metabarcoding of eDNA provides an effective way of monitoring changes in bacterial communities that would otherwise go unchecked with conventional monitoring of restoration projects. With further development, awareness of microbial diversity in restoration has significant scope for improving the efficacy of restoration interventions more broadly." @default.
• W2593276489 created "2017-03-16" @default.
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• W2593276489 date "2017-04-08" @default.
• W2593276489 modified "2023-10-14" @default.
• W2593276489 title "Revegetation rewilds the soil bacterial microbiome of an old field" @default.
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• W2593276489 doi "https://doi.org/10.1111/mec.14081" @default.
• W2593276489 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28261928" @default.
• W2593276489 hasPublicationYear "2017" @default.
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