SSN2: The next generation of spatial stream network modeling in R

The SSN2 R package provides tools for spatial statistical modeling, parameter estimation, and prediction on stream (river) networks. `SSN2` is the successor to the SSN R package, which was archived alongside broader changes in the R-spatial ecosystem that included 1) the retirement of rgdal, rgeos, and maptools and 2) the lack of active development of sp. SSN2 maintains compatibility with the input data file structures used by SSN but leverages modern R-spatial tools like sf  and provides many useful modeling features that were not available in SSN, including new modeling functions, updated fitting algorithms, and simplified syntax consistent with other R generic functions.

Impact/Purpose

Streams provide vital aquatic services that sustain wildlife, provide drinking and irrigation water, and support recreational and cultural activities.  Data are often collected at various locations on a stream network and used to characterize spatial patterns in stream phenomena. For example, a manager may need to know how the amount of a hazardous chemical changes throughout a stream network to inform mitigation efforts. SSN models use a spatial statistical modeling framework to describe unique and complex dependencies on a stream network resulting from a branching network structure, directional water flow, and differences in flow volume. SSN models relate a continuous or discrete response variable to one or more explanatory variables, a spatially independent error term (i.e., nugget), and up to three spatially dependent error terms: tail-down errors, tail-up errors, and Euclidean errors. We show how to fit these models in R and make relevant ecological inferences.

Citation

Dumelle, M., E. Peterson, J. Ver Hoef, A. Pearse, AND D. Isaak. SSN2: The next generation of spatial stream network modeling in R. Journal of Open Source Software, 9(99):6389, (2024). [DOI: 10.21105/joss.06389]

DOI: SSN2: The next generation of spatial stream network modeling in R