One of the most critical studies on microbial ecology is to reveal microbial turnover patterns along spatial, temporal, or environmental gradients. In such studies, it is often necessary to select appropriate statistical methods based on the experimental design, especially when considering random effects. However, there are few tools that can be readily applied to such cases. In this study, we present a mecoturn R package, designed to support various statistical analyses of microbial turnover along gradients. The researchers’ study appeared 06 October, 2025 in Soil Ecology Letters.

Before this work, the Environmental Genomics Team at the College of Resources and Environment, Fujian Agriculture and Forestry University, had already released a series of R packages—such as microeco, file2meco, and meconetcomp—to facilitate downstream analysis of microbiome data. Nevertheless, investigating beta-diversity patterns and taxon-abundance changes in microbial communities along environmental or spatial gradients remains a major challenge. During a study published last year (DOI: 10.1007/s11104-024-06676-w), we encountered this very problem, which prompted us to develop the mecoturn package for convenient gradient-based data transformation and downstream analysis.

Professor Yao said, “The study of gradient-driven microbial community changes is an important direction in microbial ecology research, but currently lacks relevant data analysis tools. To address this, we have developed an R package called ‘mecoturnʼ specifically for studying microbial turnover. This package is suitable for analyzing beta diversity changes under gradients or the abundance change profiles of microbial groups. It includes a series of data transformation, statistical analysis, and visualization methods, particularly expanding the application of linear mixed-effects models in beta diversity analysis, filling a gap in this direction. To verify the effectiveness of the two classes and their methods, we conducted a multi-process comparative analysis on microbial community datasets of wheat bulk soil, rhizosphere soil, and root endophytes from different regions of China. The main analysis contents compared were the community turnover patterns (along the spatial gradient from bulk soil to the root interior) with and without considering the effects of different plant individuals, as well as the relative abundance changes of high-abundance phyla. The results showed that reasonable analysis considering the heterogeneity of plants can strengthen the reliability of statistical hypothesis testing. This R package has the advantages of being open-source and flexible in use, incorporating a variety of statistical methods to accommodate different data analysis scenarios, and can be used for ecological sampling surveys or complex controlled experiments. Since its first submission to CRAN, the package has been downloaded over 8000 times. We believe this package is highly beneficial for researchers in molecular ecology to analyze gradient-based omics data.”

DOI：10.1007/s42832-025-0355-6