Desert Uplands 1: Eddy Covariance Flux and Meteorological Data 2025

Australian woodland flux tower data measuring the exchange of energy and mass between the surface and the atmosphere. The dataset is processed with PyFluxPro to produce a final, gap-filled product including Net Ecosystem Exchange (NEE), Gross Primary Productivity (GPP), and Ecosystem Respiration (ER). It was last updated by the Terrestrial Ecosystem Research Network on 2026-05-21.

Use Cases

• Modeling Net Ecosystem Exchange (NEE) based on gap-filled eddy covariance data.
• Partitioning carbon flux into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER) using the PyFluxPro methodology.
• Studying energy balance and microclimatology based on meteorological measurements.
• Analyzing ecosystem dynamics in a regrowth woodland dominated by species like Silver-leaved Ironbark and Soft Spinifex.

Strengths

• Data is processed to a final, gap-filled state using the documented PyFluxPro software (Isaac et al., 2017).
• Includes derived carbon flux components: Net Ecosystem Exchange (NEE), Gross Primary Productivity (GPP), and Ecosystem Respiration (ER).
• Provides a specific ecological context for a regrowth woodland site in the Desert Uplands.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Access 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.

Freshness

Last updated 2026-05-21 19:53:14.663073; freshness should be verified.

Geography

Desert Uplands 1 site, Australia, a regrowth woodland.