LBA-ECO CD-02: Stable Isotope Ratios in Brazilian Forest and Pasture Organic Material
Updated 1mo ago
6filesBIN
Available on 2 platforms
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Description
Stable carbon, nitrogen, and oxygen isotope ratios and elemental concentrations were measured in plant, litter, and soil samples from forest canopy profiles and pastures across multiple sites in Brazil. The sampling design captured temporal rainfall variation over several years, enabling the use of isotope ratios as proxies for interpreting carbon and nitrogen cycles in Amazonian rainforests. Data are provided in three comma-delimited ASCII files.
Use Cases
Modeling carbon and nitrogen cycling dynamics in Amazonian ecosystems based on stable isotope proxies.
Analyzing temporal variation in plant and soil biogeochemistry in response to rainfall patterns.
Comparing isotopic signatures and nutrient concentrations between forest canopy and pasture ecosystems.
Calibrating or validating remote sensing products for vegetation characteristics using ground-truth isotope data.
Strengths
Cross-platform presence on Data.gov and NASA EarthData signals importance and curation.
Sampling design captured temporal variation over the course of several years, providing a time-series dimension.
Data includes multiple sample types (plant, litter, soil) and ecosystems (forest, pasture) from several sites.
Limitations
Column names and exact row counts are unknown, limiting immediate analytical utility.
Conflicting 'last updated' dates (2004 on NASA vs. 2026 on Data.gov) create uncertainty about data freshness.
License is specified only as 'other-license-specified', requiring further investigation for reuse.
Provenance
Source
National Aeronautics and Space Administration (NASA)
Collection Method
Field measurements of stable isotope ratios and tissue concentrations in organic material samples.
Time Range
Sampling occurred over several years (exact range not specified).
Freshness
Last updated dates conflict: 2004-08-31 (NASA EarthData) and 2026-04-10 (Data.gov).
Geography
Multiple sites across Brazil, focusing on the Amazon rainforest region.
License details are unclear ('other-license-specified'); users must investigate terms before reuse. Data is split across three files.