Hunt, J. & Laubach, J. (2026). Ashley Dene Wet FLUXNET Release 2025_r1. Version 2025_r1. Terrestrial Ecosystem Research Network. Dataset. https://dx.doi.org/10.25901/e446-yc27
Ashley Dene Wet FLUXNET Release 2025_r1
Ver: 2025_r1
Status of Data: completed
Update Frequency: annually
Security Classification: unclassified
Record Last Modified: 2026-03-25
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Dataset Created: 2025-12-11
Dataset Published: 2026-03-25
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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 (v3.4.21) 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.
Ashley Dene is a paired site, growing irrigated and non-irrigated lucerne & #40;Medicago sativa L.& #41; until 2020, then converted to dairy pasture with rotational grazing. It is located on a research dairy station on the Mid-Canterbury plains, South Island, New Zealand, owned and managed by Lincoln University. The lucerne crops and the pivot-irrigation system were established in spring 2015. The flux sites began operating in 2015/16. The research is supported by the Endeavour Fund and the Strategic Science Investment Fund from New Zealand’s Ministry of Business, Innovation and Employment, and for the pasture phase also from the New Zealand Agricultural Greenhouse Gas Research Centre.
Ashley Dene is a paired site, growing irrigated and non-irrigated lucerne & #40;Medicago sativa L.& #41; until 2020, then converted to dairy pasture with rotational grazing. It is located on a research dairy station on the Mid-Canterbury plains, South Island, New Zealand, owned and managed by Lincoln University. The lucerne crops and the pivot-irrigation system were established in spring 2015. The flux sites began operating in 2015/16. The research is supported by the Endeavour Fund and the Strategic Science Investment Fund from New Zealand’s Ministry of Business, Innovation and Employment, and for the pasture phase also from the New Zealand Agricultural Greenhouse Gas Research Centre.
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 Ashley Dene Dry flux station is to examine the impact of land management practices on:
- soil carbon stores
- leaching of nitrates from the soil
- net greenhouse gas emissions
- ecosystem water use
Lineage
Data collected using standard eddy covariance and meteorological instrumentation on a 4m tower at the Ashley Dene Wet 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.
Method DocumentationPastorello, G., Trotta, C., Canfora, E. et al. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. Sci Data 7, 225 (2020).Isaac P., Cleverly J., McHugh I., van Gorsel E., Ewenz C. and Beringer, J. (2017). OzFlux data: network integration from collection to curation, Biogeosciences, 14: 2903-2928PyFluxProONEFlux
Procedure Steps
1.
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.
Spatial Description
The Ashley Dene Wet flux tower was located at 30 km south-west of the city of Christchurch.
Temporal Coverage
From 2015-07-01 to 2018-07-01
Spatial Resolution
Data not provided.
Vertical Extent
Data not provided.
Data Quality Assessment Scope
Isaac P., Cleverly J., McHugh I., van Gorsel E., Ewenz C. and Beringer, J. (2017). OzFlux data: network integration from collection to curation, Biogeosciences, 14: 2903-2928The data have been quality controlled using the PyFluxPro software. Quality control checks applied to the data include:
Specific checks applied to the sonic and IRGA data including rejection of points based on the sonic and IRGA diagnostic values and on either automatic gain control (AGC) or CO2 and H2O signal strength, depending upon the configuration of the IRGA.
If the data quality is poor, the meteorological data is filled from ERA5 reanalysis data and fluxes are filled using the Marginal Distribution Sampling method. Filled data can be identified by the Quality Controls flags in the dataset.
The ONEFlux software used to gap fill and partition this data set also applies a Median Absolute Deviation (MAD) filter to the carbon dioxide, latent heat and sensible heat before the gap filling step.
- range checks for plausible limits
- spike detection and removal
- dependency on other variables
- manual rejection of date ranges
Specific checks applied to the sonic and IRGA data including rejection of points based on the sonic and IRGA diagnostic values and on either automatic gain control (AGC) or CO2 and H2O signal strength, depending upon the configuration of the IRGA.
If the data quality is poor, the meteorological data is filled from ERA5 reanalysis data and fluxes are filled using the Marginal Distribution Sampling method. Filled data can be identified by the Quality Controls flags in the dataset.
The ONEFlux software used to gap fill and partition this data set also applies a Median Absolute Deviation (MAD) filter to the carbon dioxide, latent heat and sensible heat before the gap filling step.
Data Quality Assessment Outcome
No anomalous data detected after quality control.
ANZSRC - FOR
GCMD Sciences
Horizontal Resolution
Parameters
Temporal Resolution
User Defined
FLUXNET ID
NZ-ADw
Contact Point
Principal Investigator
Terrestrial Ecosystem Research Network
80 Meiers Road, Indooroopilly, Queensland, 4068, Australia.
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