The Water Framework Directive (WFD) recognizes benthic macroinvertebrates as a good biological quality element for transitional waters as they are the most exposed to natural variability patterns characteristic of these ecosystems, due to their life cycles and space-use behavior. In this paper we consider the performance of three multimetric indices (namely M-AMBI, BITS and ISS) based on benthic macroinvertebrates abundances, aiming at assessing the ecological status of lagoons and likely to respond differently to different sources of stress and natural variability. In order to investigate the possible contrasting behavior of the three multimetric indices, we propose a Bayesian hierarchical model in which they are jointly modeled as functions of abiotic covariates, external anthropogenic pressure indicators and lagoon effects. The proposed model is applied to data from three lagoons in Apulia and assessed using multiple diagnostic tools. The joint sensitivity of lagoon quality evaluations to available covariates is thus investigated.

Bayesian analysis of three indices for lagoons ecological status evaluation

Rosati Ilaria
2015

Abstract

The Water Framework Directive (WFD) recognizes benthic macroinvertebrates as a good biological quality element for transitional waters as they are the most exposed to natural variability patterns characteristic of these ecosystems, due to their life cycles and space-use behavior. In this paper we consider the performance of three multimetric indices (namely M-AMBI, BITS and ISS) based on benthic macroinvertebrates abundances, aiming at assessing the ecological status of lagoons and likely to respond differently to different sources of stress and natural variability. In order to investigate the possible contrasting behavior of the three multimetric indices, we propose a Bayesian hierarchical model in which they are jointly modeled as functions of abiotic covariates, external anthropogenic pressure indicators and lagoon effects. The proposed model is applied to data from three lagoons in Apulia and assessed using multiple diagnostic tools. The joint sensitivity of lagoon quality evaluations to available covariates is thus investigated.
2015
Istituto di Ricerca sugli Ecosistemi Terrestri - IRET
Multivariate multiple regression
Correlated responses
Bayesian inference
Ecosystem status
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/310146
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