The ecodist package in R provides a set of dissimilarity-based methods for analyzing ecological data, including simple and partial Mantel tests, and a novel extension to the Mantel correlogram. These methods allow for the analysis of spatial structure in ecological data without requiring specific data distributions. The package includes functions for calculating various dissimilarity metrics, such as Euclidean, Bray-Curtis, and Jaccard distances. The Mantel test assesses the correlation between two dissimilarity matrices, while the partial Mantel test accounts for the effects of additional variables. The Mantel correlogram extends these methods to examine spatial patterns at different scales, allowing for the detection of nonlinear structures. The package also includes functions for permutation testing and confidence intervals, which are essential for statistical inference. The ecodist package is particularly useful for analyzing complex ecological data, such as plant community composition and environmental variables, and can be applied to a wide range of ecological studies. The methods are illustrated using both artificial data and real-world data from grazinglands in the northeastern United States. The package is designed to be flexible and user-friendly, with functions that can be easily extended or modified to suit specific research needs. The use of dissimilarity-based methods allows for the explicit inclusion of geographic distance, while requiring minimal assumptions about the nature of the data. The flexibility of these methods makes them suitable for a wide range of ecological analyses, including the identification of spatial patterns and the assessment of relationships between environmental variables and species composition. The package is recommended for researchers working with complex ecological data, as it provides a comprehensive set of tools for analyzing spatial structure and relationships in ecological datasets.The ecodist package in R provides a set of dissimilarity-based methods for analyzing ecological data, including simple and partial Mantel tests, and a novel extension to the Mantel correlogram. These methods allow for the analysis of spatial structure in ecological data without requiring specific data distributions. The package includes functions for calculating various dissimilarity metrics, such as Euclidean, Bray-Curtis, and Jaccard distances. The Mantel test assesses the correlation between two dissimilarity matrices, while the partial Mantel test accounts for the effects of additional variables. The Mantel correlogram extends these methods to examine spatial patterns at different scales, allowing for the detection of nonlinear structures. The package also includes functions for permutation testing and confidence intervals, which are essential for statistical inference. The ecodist package is particularly useful for analyzing complex ecological data, such as plant community composition and environmental variables, and can be applied to a wide range of ecological studies. The methods are illustrated using both artificial data and real-world data from grazinglands in the northeastern United States. The package is designed to be flexible and user-friendly, with functions that can be easily extended or modified to suit specific research needs. The use of dissimilarity-based methods allows for the explicit inclusion of geographic distance, while requiring minimal assumptions about the nature of the data. The flexibility of these methods makes them suitable for a wide range of ecological analyses, including the identification of spatial patterns and the assessment of relationships between environmental variables and species composition. The package is recommended for researchers working with complex ecological data, as it provides a comprehensive set of tools for analyzing spatial structure and relationships in ecological datasets.