What this entity is
Canonical name: National Ecological Observatory Network (NEON). 1
Known alias: NEON. 1
Stable external identifier: Not reported in this document. 1
NEON is the dominant soil metagenome study represented in the analysis of eukaryotic signal in NMDC prokaryote-targeted metagenomes. 1
The NMDC context audit refines this usage distinction: kbase.nmdc_neon represents NEON, not the National Microbiome Data Collaborative (NMDC), making it a namesake collision rather than an NMDC resource. NEON is an NSF program, whereas NMDC is associated with DOE-BER. 2
Key facts from the document
The batch-controlled NEON analysis included 1,186 runs from one sampling program with a constant protocol and batch. 1
Within NEON, local vegetation (env_local_scale, with 11 levels) was associated with eukaryotic fraction, with Kruskal–Wallis H=119.1 and p=7.6×10⁻²¹. 1
Median eukaryotic fractions were 23% in sedge/forb herbaceous soil, 14% in emergent wetland, 13% in dwarf scrub, and 2% in evergreen forest, while deciduous forest, cropland, and pasture were approximately 0. 1
Geography also differed across 47 NEON sites, with Kruskal–Wallis H=310.4 and p=2.4×10⁻⁴⁶. 1
The highest median eukaryotic fractions occurred at Arctic tundra sites: Utqiaġvik had 30%, Caribou-Poker Creeks had 22%, and Toolik had 17%, compared with 2–8% in temperate forests. 1
A model using local environment and geography achieved within-study five-fold R²=+0.17 ± 0.06 in NEON, contrasting with cross-study out-of-study R²=−0.30. 1
The NEON result supports the interpretation that environmental metadata can predict eukaryotic signal when batch is held approximately constant, while remaining subject to possible sub-batch confounding within the study. 1
NEON had zero non-null sequencing-depth values, so the reported negative association between measured sequencing depth and eukaryotic fraction was a cross-study statistic and was not part of the batch-controlled within-study result. 1
The report cautions that env_local_scale and geography within NEON may track sub-batches such as sampling campaigns, making this analysis the best available control rather than a randomized design. 1
The audit’s identification of kbase.nmdc_neon supports treating NEON provenance and authority separately from NMDC when selecting or attributing resources; its inferred risk of misattribution is a provenance hazard, not a directly observed user error. 2
Related pages
The NEON findings are summarized in Metadata Correlates of Eukaryotic Contamination in NMDC Prokaryote-Targeted Metagenomes. 1
The resource-provenance distinction is summarized in NMDC Context Audit. 2
They contribute to environment-embedding-geography, which addresses how environmental metadata and geography relate to biological signals. 1
They also inform cross-tenant-data-bridging, because the analysis connected NMDC workflow results with biosample and study metadata. 1