This release consists of flux tower measurements of the exchange of energy and mass between the surface and the atmospheric boundary-layer using eddy covariance techniques. Data were processed using PyFluxPro (v3.4.15) as described by Isaac et al. (2017). PyFluxPro produces a final, gap-filled product with Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER).
Wombat State Forest site is a secondary re-growth forest that was last harvested in 1980. Dominant tree species are Eucalyptus obliqua (messmate stringybark), Eucalyptus radiata (narrow leaf peppermint) and Eucalyptus rubida (candlebark) with an average canopy height of 25 m. The understorey consists mainly of patchy grasses and the soil is a silty-clay overlying clay. The forest is managed by the Department of Sustainability and Environment and management includes selective harvesting and prescribed burning regimes. The climate of the study area is classified as cool-temperate to Mediterranean with cold and wet winters (May-August) and warm and dry summers (December-February) with temperatures between 1 and 30 °C and mean annual air temperature of 12.1 °C. Annual rainfall is approximately 871 mm (142 year long-term average). Coherent automated measurements of soil greenhouse gas fluxes (CO2, CH4 and N2O) were collected using a trailer-mounted mobile laboratory - Fourier transform infra-red (FTIR) spectrometer from 2010 to 2016. Measurement height was originally 30 m but increased to 33 m in January 2017.
Credit
We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging.
The site is managed by The University of Melbourne in collaboration with Monash University and the Department of Sustainability and Environment of Victoria. Data collection is funded by TERN.
Purpose
Wombat Forest research site facilitates the investigation of complex ecosystem processes of carbon, water and nutrient cycles in a dry-sclerophyll forest that are commonly found in Australia. This research will help to assess the impact of future environmental change on forest ecosystems in Australia. The Wombat Forest research site will:
- quantify the carbon sink/source strength of a dry sclerophyll forest and identify the contribution of such forests to the Australia's National Carbon Inventory
- quantify the emission and/or uptake of non-CO2 greenhouse gases, such as nitrous oxide and methane of the forest
- assess the role of climate variability and drought on ecosystem processes
- assess the impact of disturbances (such as fire) on ecosystem processes
- provide a database of microclimate and ecological parameters for use in carbon and water modelling projects.
Data Processing
File naming convention
The NetCDF files follow the naming convention below:
SiteName_ProcessingLevel_FromDate_ToDate_Type.nc
- SiteName: short name of the site
- ProcessingLevel: file processing level (L3, L4, L5, L6)
- FromDate: temporal interval (start), YYYYMMDD
- ToDate: temporal interval (end), YYYYMMDD
- Type (Level 6 only): Summary, Monthly, Daily, Cumulative, Annual
- Summary: This file is a summary of the L6 data for daily, monthly, annual and cumulative data. The files Monthly to Annual below are combined together in one file.
- Monthly: This file shows L6 monthly averages of the respective variables, e.g. AH, Fc, NEE, etc.
- Daily: same as Monthly but with daily averages.
- Cumulative: File showing cumulative values for ecosystem respiration, evapo-transpiration, gross primary productivity, net ecosystem exchange and production as well as precipitation.
- Annual: same as Monthly but with annual averages.
Lineage
All flux raw data is subject to the quality control process OzFlux QA/QC to generate data from L1 to L6. Levels 3 to 6 are available for re-use. Datasets contain Quality Controls flags which will indicate when data quality is poor and has been filled from alternative sources. For more details, refer to Isaac et al. (2017).