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DATASET
Alcoa-BASE-Metadata-April2018.xlsx (35.89 kB)
DATASET
AM_ContextualMetadata_iluka.xlsx (47.54 kB)
DATASET
AM_ContextualMetadata_south32.xlsx (49.17 kB)
DATASET
Bacteria.csv (331.58 MB)
TEXT
Iluka_otu_cluss_tax.txt (106.89 MB)
DATASET
south32_otu_cluss_tax.xlsx (30.78 MB)
DOCUMENT
File descriptions.docx (14.17 kB)
TEXT
resto-traject-R-code-final.R (1.31 MB)
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8 files

Code and data supporting: "Next generation restoration metrics: Using soil eDNA bacterial community data to measure trajectories towards rehabilitation targets"

dataset
posted on 2022-02-19, 22:56 authored by Craig LiddicoatCraig Liddicoat, Siegfried L. Krauss, Andrew BissettAndrew Bissett, Ryan J. Borrett, Luisa C. Ducki, Shawn PeddleShawn Peddle, Paul Bullock, Mark P. Dobrowolski, Andrew Grigg, Mark Tibbett, Martin BreedMartin Breed
R code and supporting data are provided here for the article: "Next generation restoration metrics: Using soil eDNA bacterial community data to measure trajectories towards rehabilitation targets" (see article link below).

Rehabilitation trajectory assessments have been developed for three case study minesites:
i) Alcoa - Huntly (sampled in 2016; 2-29 yr old rehab sites)
ii) Iluka - Eneabba (sampled in 2019; 7-38 yr old rehab sites)
iii) South32 - Worsley (sampled in 2019; 2-28 yr old rehab sites).

Please refer to the 'File descriptions' document for summary information on each file.

R code is also available at: https://github.com/liddic/resto_traj

History

Primary contact

craig.liddicoat@flinders.edu.au