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 as described by Isaac et al. (2017) for the quality control and post-processing steps. The final, gap-filled product containing Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER) has been produced using the ONEFlux software as described in Pastorello et al. (2020). This data set has been produced as part of the FLUXNET Shuttle project.
The Digby Plantation flux station is located in blue gum plantation in southwestern Victoria, approximately 300 km west of Melbourne.
Digby Plantation is a E. globulus plantation site near Digby, in Southwest Victoria, Australia, within the Glenelg River Basin. The plantation was established in August 2017, with a mean tree density of approximately 1000 trees-ha-1. The depth to the water table is between 5 to 10 m. Tree height at planting was between 150 mm and 300 mm, and trees were on average 11 m tall at the end of the monitoring period (July 2021).
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.
Purpose
The purpose of the Digby Plantation station was to monitor the fluxes in a blue gum (Eucalyptus globulus) plantation during the first few years after its establishment. The aim was to understand how the water efficiency of the plantation changes as trees rapidly grow in the years after being planted.
Lineage
Data collected using standard eddy covariance and meteorological instrumentation on a 15m tower at the Digby Plantation site. The data were quality controlled using the PyFluxPro software package, see Isaac et al (2017), which is available at
https://github.com/OzFlux/PyFluxPro. Gap filling and partitioning has been done using the ONEFlux software package, see Pastorello et al. 2020, which is available at
https://github.com/fluxnet/ONEFlux.
Procedure Steps1.
Data is measured using standard micro-meteorological instrumentation on a flux tower.
2.
Data is recorded on a data logger and is collected by the site PI.
3.
Data quality control including removal of data outside plausible ranges, removal of spikes, exclusion of particular date ranges and removal of data based on the dependence of one variable on another is done using PyFluxPro.
4.
Filtering for low-ustar conditions, gap filling and partitioning of NEE into GPP and ER are done using ONEFlux.