SDesti: An R package for the analysis of aquatic benthos environmental studies’ data
Description
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.
Files
Steps to reproduce
Read 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. https://doi.org/10.1016/j.ecoinf.2021.101265 Copy zip file to some work folder on a PC. In R console or R Studio select install packages from local files. Select zip file and install it and all its dependencies. Call SDesti using library(SDesti) type ??SDesti to access the manual in pdf. Find all detailed instructions to use the program and interpret the results in the pdf manual file and associated peer reviewed paper.