SDesti: An R package for the analysis of aquatic benthos environmental studies’ data

Published: 26 October 2021| Version 4 | DOI: 10.17632/3h8347w6d9.4
Diogo Sayanda, Frederick Wrona,
, Christina Suzanne


Data analysis is one of the most relevant steps of aquatic benthic environmental monitoring and research studies, and should be a fundamental consideration in both the planning (i.e., defining appropriate sampling design strategies) and implementation phases (application of appropriate standardized sampling procedures). A common objective of these studies is to identify relationships between environmental stressors and benthic bioindicator metrics. However, assessing these relationships is a complex process. Multivariate regression model adjustment coupled with forward and backward model selection routines is an appropriate complementary statistical analysis tool to test for the existence of statistically significant associations between a non-autocorrelated biological response and each variable within a group of environmental covariates included in a model. With this in mind, we developed SDesti, a user-friendly R package to analyze benthos data (number of individuals, biomass, chlorophyll concentration, or biological indices, excluding beta diversity metrics). SDesti contains four user accessible functions. AnalysisDescriptives() and Estimation() give information on the quality, homogeneity and representativeness of the data for one sampling campaign for one site. TimeLineAnalysisDescriptives() performs the descriptive analysis that usually precedes the adjustment of a regression model. TimeLineAnalysis() automatically adjusts an adequate regression model (linear, Poisson, quasipoisson, or negative binomial) and also returns the necessary measures and graphics to evaluate the quality of the adjustment and verify the model assumptions. SDesti greatly simplifies the process of data analysis and can be easily used by non-statisticians. The analytical package includes a complete manual that provides detailed information: on the data structure requirements, on the variable nomenclature rules and program operating procedures, on the data analysis (complemented with examples) and on the interpretation of the results (type ??SDesti on R console). SDesti eliminates redundancy, reduces human error and, coupled with a suitable sampling design, standard sampling and sample treatment procedures, it contributes to improve the consistency of the results in environmental studies. SDesti binary for windows users and installation instructions can be found below.


Steps to reproduce

Citation - Sayanda, D., Lima, A. C., Suzanne, L.C., Wrona, F. (2021). SDesti: An R package for the analysis of aquatic benthos environmental studies’ data. Ecological Informatics. Copy zip file to some work folder on a PC. This is the binary file with the program SDesti for windows. The program is updated from time to time to make sure it is fully functional in the most recent R version. It imports some functions from the packages: grDevices, broom, car, faraway, graphics, MASS and stats that are available on CRAN. If necessary install these packages first (depending on the R version the installation of SDesti imports can be automatic or not.) Installation: 1 - On R: Open R -> Packages -> Install Packages from local file (browse and select filefile) -> OK. 2 - On RStudio: Open RStudio -> Tools -> Install packages -> Install from(select Package Archive File) -> Packages(browse and select file) -> OK. Run the examples in help(SDesti) and read pdf manual by typing ??SDesti on R console.


Statistics, Biomonitoring, Aquatic Invertebrates, Environmental Impact Assessment, Periphyton