Desert Uplands 1 Eddy Covariance and Meteorological Data Collection

Eddy covariance and meteorological measurements from the ALTAR Desert Uplands 1 flux tower in a woodland ecosystem. Data are processed using PyFluxPro to produce gap-filled Net Ecosystem Exchange (NEE) partitioned into Gross Primary Productivity (GPP) and Ecosystem Respiration (ER). The dataset is managed by the Terrestrial Ecosystem Research Network's Data Discovery platform and was last updated on 2026-05-16.

Use Cases

• Modeling carbon sequestration based on gap-filled Net Ecosystem Exchange (NEE) data.
• Analyzing ecosystem respiration and gross primary productivity dynamics in a regrowth woodland.
• Studying energy and mass exchange between the land surface and atmosphere using eddy covariance techniques.
• Investigating the impact of specific tree species on local microclimates based on the described woodland composition.

Strengths

• Data processing follows a published methodology described in Isaac et al. (2017).
• The final product is gap-filled, providing a continuous time series.
• The dataset includes partitioned carbon flux components (GPP and ER).
• The specific woodland ecosystem and dominant plant species are described in detail.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Access to the dataset is available on request subject to agreement, which may delay immediate use.

Provenance

Source

Terrestrial Ecosystem Research Network's Data Discovery

Collection Method

Collected via eddy covariance techniques at the ALTAR Desert Uplands 1 flux tower and processed with PyFluxPro.

Freshness

Last updated 2026-05-16 01:59:06.579083; freshness should be verified.

Geography

ALTAR Desert Uplands 1 site, a woodland in an unspecified location.