Desert Uplands 2: Eddy Covariance Flux and Meteorological Data for a Woodland Ecosystem

Flux tower measurements capture the exchange of energy and mass between a woodland surface and the atmosphere using eddy covariance techniques. Data are processed into a final, gap-filled product with Net Ecosystem Exchange partitioned into Gross Primary Productivity and Ecosystem Respiration by PyFluxPro software. The Terrestrial Ecosystem Research Network's Data Discovery platform released this dataset on 2026-05-21.

Use Cases

• Modeling Net Ecosystem Exchange (NEE) based on gap-filled flux tower data.
• Partitioning ecosystem carbon flux into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER) based on the described PyFluxPro methodology.
• Studying energy and mass exchange dynamics in a Silver-leaved Ironbark and Spinifex-dominated woodland based on the site description.
• Analyzing meteorological conditions alongside ecosystem fluxes for a regrowth woodland site.

Strengths

• Data are processed into a final, gap-filled product, which suggests completeness for time-series analysis.
• Processing follows a documented methodology using PyFluxPro as described in Isaac et al. (2017).
• The site ecology is specifically described, including dominant tree and ground layer species like Eucalyptus melanophloia and Tripodia pungens.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale modeling.
• Access to this dataset is available on request subject to agreement, which may create a barrier to immediate use.

Provenance

Source

Terrestrial Ecosystem Research Network's Data Discovery

Collection Method

Flux tower measurements using eddy covariance techniques, processed with PyFluxPro software.

Freshness

Last updated 2026-05-21 19:53:31.821299; freshness should be verified.

Geography

ALTAR Desert Uplands 2 site, a woodland in Australia (inferred from data_gov_au platform and site description).