Computational Provenance & Reproducibility Record Diversity Analysis and PERMANOVA · v1.1.0
Computational Provenance & Reproducibility Record
RAISINS · Diversity Analysis Module
This Computational Provenance Record documents the statistical computing environment, software dependencies, computational provenance, and bibliographic references associated with the RAISINS Diversity Analysis module. It is intended to support computational reproducibility and software transparency. Detailed statistical methodology, mathematical derivations, and user guidance are provided separately in the official module documentation.
1 Module Metadata
| Parameter | Specification |
|---|---|
| Module | Diversity Analysis |
| Module Version | Diversity v1.1.0 |
| Document Type | Computational workflow |
| Statistical Engine | R |
| R Version | 4.5.0 |
| Reproducibility | Execution Environment: Posit Connect · GCR · renv-locked |
2 Statistical Dependency Manifest
| Package | Version | Repository | Core Statistical Functions |
|---|---|---|---|
| vegan | 2.7-5 |
CRAN | diversity(), specnumber(), vegdist(), decostand(), adonis2(), betadisper(), anosim() |
| fossil | 0.4.0 |
CRAN | chao1() |
| car | 3.1-5 |
CRAN | leveneTest() |
| FSA | 0.10.1 |
CRAN | dunnTest() |
| stats | 4.5.0 |
Base R | aov(), shapiro.test(), kruskal.test(), pairwise.t.test(), anova(), hclust(), dist(), scale() |
3 Statistical Function Registry
| Analytical Role | Primary Function(s) |
|---|---|
| Alpha diversity indices | vegan::diversity(), vegan::specnumber(), fossil::chao1() |
| Assumption checks | stats::shapiro.test(), car::leveneTest() |
| Omnibus group comparison | stats::aov(), stats::kruskal.test() |
| Post-hoc multiple comparison | stats::pairwise.t.test(), FSA::dunnTest() |
| Community dissimilarity | vegan::vegdist(), vegan::decostand() |
| Multivariate group testing | vegan::adonis2() |
| Dispersion homogeneity | vegan::betadisper(), stats::anova() |
| Similarity testing | vegan::anosim() |
| Clustering / ordination | stats::hclust(), stat::dist() |
4 RAISINS Native Statistical Framework
RAISINS integrates native statistical components for analytical workflow management, computational validation, automated reporting, and module-specific statistical procedures. This document intentionally discloses only the statistical computing environment required for computational reproducibility. Descriptions of RAISINS-native statistical functions, together with their scientific basis and validation, are available for independent scientific review upon reasonable request to the developers, subject to applicable intellectual property and licensing provisions.
5 Package References
R Core Team. (2025). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/
Oksanen, J., Simpson, G. L., Blanchet, F. G., Kindt, R., Legendre, P., Minchin, P. R., O’Hara, R. B., Solymos, P., Stevens, M. H. H., Szoecs, E., Wagner, H., Bedward, M., Bolker, B., Borcard, D., Carvalho, G., De Caceres, M., Durand, S., Evangelista, H. B. A., Hannigan, G., Hill, M., Lahti, L., Martino, C., Ouellette, M., Ribeiro Cunha, E., Smith, T., Stier, A., Ter Braak, C. J. F., & Weedon, J. (2026). vegan: Community Ecology Package (R package version 2.7-5). https://doi.org/10.32614/CRAN.package.vegan
Vavrek, M. J. (2011). fossil: Palaeoecological and palaeogeographical analysis tools. Palaeontologia Electronica, 14(1), 1T.
Fox, J., & Weisberg, S. (2019). An R Companion to Applied Regression (3rd ed.). Sage.
Ogle, D. H., Doll, J. C., Wheeler, A. P., & Dinno, A. (2026). FSA: Simple Fisheries Stock Assessment Methods (R package version 0.10.1). https://doi.org/10.32614/CRAN.package.FSA
Allaire, J. J., Xie, Y., Dervieux, C., McPherson, J., Luraschi, J., Ushey, K., Atkins, A., Wickham, H., Cheng, J., Chang, W., & Iannone, R. (2026). rmarkdown: Dynamic Documents for R (R package version 2.31). https://github.com/rstudio/rmarkdown