A model-based approach to lagoon ecosystem classification

The EU Water Framework Directive recognizes benthic macroinvertebrates as good biological indicators of the quality of transitional waters as they are mainly exposed to natural variability patterns characteristic of these ecosystems, due to their life cycles and space-use behavior. Here, we address the classification of the ecological status of three lagoons in Apulia (I), using three multimetric indices based on benthic macroinvertebrates (namely M-AMBI, BITS and ISS), that are likely to respond differently to different sources of stress and natural variability. Lagoon classification is usually based on the discretization of such indices by standard classification boundaries with only partial consideration of the natural variability of ecosystem properties and possible inaccuracies of the classification procedures. We first consider a Bayesian hierarchical model to study the effects of abiotic covariates and external anthropogenic pressure indicators on the multimetric indices, taking into account their correlation structure. In order to further investigate the possible contrasting behavior of the three indices in terms of lagoon classification, we propose a cumulative proportional odds model for the discretized version of the indices as function of the same explanatory ecological variables. This model allows to understand how abiotic variables and anthropogenic pressures affect the classification into different ecological status and to evaluate the agreement between indices in terms of classification. Both models have been estimated in a fully Bayesian framework by a Monte Carlo Markov Chain posterior simulation algorithm.