SSNbayes: An R package for Bayesian spatio-temporal modelling on stream networks

TL;DR

SSNbayes is an R package that enables Bayesian spatio-temporal modeling and prediction on stream networks, incorporating flow connectivity and stream distance for ecological and epidemiological applications.

Contribution

The paper introduces SSNbayes, a novel R package that models spatial dependence on stream networks using flow connectivity and stream distance within a Bayesian framework.

Findings

Successfully applied to stream temperature data in Idaho.

Provides probabilistic habitat estimates and exceedance probabilities.

Supports predictions across entire stream networks.

Abstract

Spatio-temporal models are widely used in many research areas from ecology to epidemiology. However, most covariance functions describe spatial relationships based on Euclidean distance only. In this paper, we introduce the R package SSNbayes for fitting Bayesian spatio-temporal models and making predictions on branching stream networks. SSNbayes provides a linear regression framework with multiple options for incorporating spatial and temporal autocorrelation. Spatial dependence is captured using stream distance and flow connectivity while temporal autocorrelation is modelled using vector autoregression approaches. SSNbayes provides the functionality to make predictions across the whole network, compute exceedance probabilities and other probabilistic estimates such as the proportion of suitable habitat. We illustrate the functionality of the package using a stream temperature dataset collected in Idaho, USA.