A unified framework for quantifying holobiont-level redox resilience by integrating plant physiological traits, soil redox chemistry, and microbial community organization into a single interpretable index. The package implements the Redox Resilience Index (RRI), a weighted composite metric grounded in redox biogeochemistry, microbial ecology, and systems biology. Multivariate indicators from each domain are reduced to normalized one-dimensional latent scores using flexible dimension-reduction methods (e.g., PCA, factor analysis, nonlinear embeddings, or co-expression networks). Microbial resilience is represented as a blended latent component combining abundance or functional composition with network organization metrics derived from ecological graphs. RedoxRRI is designed for hypothesis-driven research rather than black-box prediction, enabling transparent comparison of alternative aggregation strategies, domain weights, and ecological contexts. The framework supports validation against ecosystem recovery, stress tolerance, and biogeochemical function across experimental and observational studies.

The importance of converting relative to absolute abundance in the context of microbial ecology: Introducing the user-friendly DspikeIn R package

The importance of converting relative to absolute abundance in the context of microbial ecology: Introducing the user-friendly DspikeIn R package

The importance of converting relative to absolute abundance in the context of microbial ecology: Introducing the user-friendly DspikeIn R package

The DspikeIn package supports both phyloseq and TreeSummarizedExperiment formats to streamline microbial quantification across diverse experimental setups. It accommodates either a single spike-in taxon or synthetic community taxa with variable or equal spike-in volumes and copy numbers. The package offers a comprehensive suite of tools for AA quantification, addressing challenges through ten core functions: 1) validation of spiked species, 2) data preprocessing, 3) system-specific spiked species retrieval, 4) scaling factor calculation, 5) conversion to absolute abundance, 6) bias correction and normalization, 7) performance assessment, and 8) taxa exploration and filtering 9) network topology assessment 10) further analyses and visualization.

From Microscale to Microbial Insights: Validating High-Throughput Microvolume Extraction Methods (HiMEx) for Marine Microbial Ecology

Coordinates are reprojected from WGS84 to UTM Zone 56S (EPSG:32756). Each plot is sampled independently and visualized in a faceted layout. Sampling favors spatial separation while preserving C3/C4 balance.

DspikeIn The DspikeIn package supports both phyloseq and TreeSummarizedExperiment formats to streamline microbial quantification across diverse experimental setups. It accommodates either a single spike-in taxon or synthetic community taxa with variable or equal spike-in volumes and copy numbers. The package offers a comprehensive suite of tools for AA quantification, addressing challenges through ten core functions: 1) validation of spiked species, 2) data preprocessing, 3) system-specific spiked species retrieval, 4) scaling factor calculation, 5) conversion to absolute abundance, 6) bias correction and normalization, 7) performance assessment, and 8) taxa exploration and filtering 9) network topology assessment 10) further analyses and visualization.

The DspikeIn package consolidates the process of converting relative abundance to absolute abundance using herpetofauna gut microbiomes as a model.

CCA on environmental factors and species as well as slope factor