Two Statistical Methods for the Detection of Environmental Thresholds

A nonparametric method and a Bayesian hierarchical modelling method are proposed in this paper for the detection of environmental thresholds. The nonparametric method is based on the reduction of deviance, while the Bayesian method is based on the change in the response variable distribution parameters. Both methods are tested using macroinvertebrate composition data from a mesocosm experiment conducted in the Everglades wetlands, where phosphorus is the limiting nutrient. Both methods resulted a TP concentration threshold slightly above 11 μg/L, using the percent of phosphorus tolerant species and a dissimilarity index as the response variables. Key Terms: Bray-Curtis dissimilarity, changepoint, deviance, Everglades, Gibbs sampling, macroinvertebrate, nonparametric, wetlands