TY - JOUR T1 - Next generation restoration metrics: Using soil eDNA bacterial community data to measure trajectories towards rehabilitation targets JF - bioRxiv DO - 10.1101/2021.08.12.456018 SP - 2021.08.12.456018 AU - Craig Liddicoat AU - Siegfried L. Krauss AU - Andrew Bissett AU - Ryan J. Borrett AU - Luisa C. Ducki AU - Shawn D. Peddle AU - Paul Bullock AU - Mark P. Dobrowolski AU - Andrew Grigg AU - Mark Tibbett AU - Martin F. Breed Y1 - 2021/01/01 UR - http://biorxiv.org/content/early/2021/11/05/2021.08.12.456018.abstract N2 - In post-mining rehabilitation, successful mine closure planning requires specific, measurable, achievable, relevant and time-bound (SMART) completion criteria, such as returning ecological communities to match a target level of similarity to reference sites. Soil microbiota are fundamentally linked to the restoration of degraded ecosystems, helping to underpin ecological functions and plant communities. High-throughput sequencing of soil eDNA to characterise these communities offers promise to help monitor and predict ecological progress towards reference states. Here we demonstrate a novel methodology for monitoring and evaluating ecological restoration using three long-term (> 25 year) case study post-mining rehabilitation soil eDNA-based bacterial community datasets. Specifically, we developed rehabilitation trajectory assessments based on similarity to reference data from restoration chronosequence datasets. Recognising that many alternative options for microbiota data processing have potential to influence these assessments, we comprehensively examined the influence of standard versus compositional data analyses, different ecological distance measures, sequence grouping approaches, eliminating rare taxa, and the potential for excessive spatial autocorrelation to impact on results. Our approach reduces the complexity of information that often overwhelms ecologically-relevant patterns in microbiota studies, and enables prediction of recovery time, with explicit inclusion of uncertainty in assessments. We offer a step change in the development of quantitative microbiota-based SMART metrics for measuring rehabilitation success. Our approach may also have wider applications where restorative processes facilitate the shift of microbiota towards reference states.Competing Interest StatementThe authors have declared no competing interest. ER -