What this entity is
Canonical name: Distance-based redundancy analysis. Known alias: db-RDA. No stable external identifier was reported in the source document. 1
Distance-based redundancy analysis is a multivariate method used in this study to isolate compartment centroid, or location, effects from dispersion effects in functional-distance data. 1
Key facts from the documents
Using a refined 17-marker panel and Jaccard distances across 607 root, rhizosphere, and phyllosphere species, db-RDA estimated a location-only R² of 0.060 with p = 0.001. 1
The location-only R² of 0.060 represented 84% of the total PERMANOVA R² of 0.071, while 16% was attributable to dispersion. 1
The db-RDA result therefore supports the conclusion that plant compartments have statistically significant but weak functional separation, with approximately 6% of variance associated with compartment location effects. 1
PERMDISP detected dispersion heterogeneity with F = 15.6 and p = 0.001; root species had a mean distance of 0.452 from their centroid, phyllosphere species had 0.503, and rhizosphere species had 0.528. 1
The db-RDA analysis refines the interpretation of the PERMANOVA result by showing that most of the explained variation reflected centroid shifts rather than dispersion differences. 1
The soil-metal analysis extends this method’s use from compartment functional distances to community COG profiles: its conditional model reported R² = 0.799 and p = 0.005 using 999 permutations after conditioning on batch and project effects, with metals explaining 80% of residual COG-profile variance. 2 This result is conditional rather than directly comparable to the plant location-only R², because the soil analysis removed project effects before fitting metal predictors; unconditional metal-only R² was not reported. 2
Related pages
This method is relevant to ecotype-environment-gene-content because it quantifies the compartment component of environmental differences in functional gene profiles. 1 The soil-metal result supports this broader environmental-gene-content connection by identifying biome-specific metal–COG relationships, while remaining observational. 2
It also contributes to environment-embedding-geography through the comparison of root, rhizosphere, and phyllosphere functional profiles. 1 The soil analysis refines that connection by showing that spatial and project conditioning affect interpretation of metal-associated profiles. 2
The source reports are summarized in Plant Microbiome Ecotypes — Compartment-Specific Functional Guilds and Their Genetic Architecture and Soil Metal Concentrations Drive Functional Gene Shifts. 1 2