Lachlan River ecosystem metabolism data

River ecosystem metabolism and ancillary data accompanying Giling <i>et al. </i>(in press). This data is used to perform the Bayesian spatio-temporal model (Santos-Fernandez <i>et al. </i>2022).The dataset includes:<b>'lsn.ssn'. </b>ssn object containing spatial information on the stream network (Ver Hoef <i>et al. </i>2006, Peterson and Ver Hoef 2014).<b>'sites_df_with_obs.csv' and associated metadata</b>. The metabolism estimates were modelled from diel dissolved oxygen, water temperature, and PAR data collected as part of the Commonwealth Environmental Water Holder’s flow monitoring programs. Raw dissolved oxygen data are publically available (CEWH 2023). Discharge, water level, and water temperature data were sourced from the NSW Department of Planning, Industry and Environment (http://www.bom.gov.au/waterdata/, accessed 29/07/2021). Gridded daily solar exposure data were sourced from the Bureau of Meteorology. Note that the ecosystem metabolism rates presented here are not identical to the rates published from the broader Flow-MER program (available at https://data.gov.au/data/dataset/flow-mer-metabolism-base-model) due to the setting of site-specific constraints on reaeration rates in the current work, as described in the Supplementary Information of Giling <i>et al. </i>(under review).<b>'preds_spatial_df.csv' and associated metadata</b><b>. </b>Data containing prediction coordinates and ancillary data for predicting ecosystem metabolism rates at new sites.<br><br><b>References</b>CEWH. 2023. Metabolism oxygen logger data. Flow-MER Program. Commonwealth Environmental Water Holder, Australian Government Department of Climate Change, Energy, the Environment and Water. Sourced from https://data.gov.au/data/dataset/flow-mer-oxygen-logger. Last accessed 23/08/2023).Peterson EE, Ver Hoef JM. 2014. Stars: An ArcGIS toolset used to calculate the spatial information needed to fit spatial statistical models to stream network data. Journal of Statistical Software 56:1–17.Santos-Fernandez E, Ver Hoef JM, Peterson EE, McGree J, Isaak DJ, Mengersen K. 2022. Bayesian spatio-temporal models for stream networks. Computational Statistics &amp; Data Analysis 170:107446.Ver Hoef JM, Peterson E, Theobald D, Hoef JMV, Peterson E, Theobald D. 2006. Spatial statistical models that use flow and stream distance. Environ Ecol Stat 13:449–64.<br><br><br>