Bayesian analysis of three indices for lagoons ecological status evaluation

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• 作者：Alessio Pollice (1)
  Serena Arima (2)
  Giovanna Jona Lasinio (3)
  Alberto Basset (4)
  Ilaria Rosati (4)
  
  1. Dipartimento di Scienze Economiche e Metodi Matematici ; Universit脿 degli Studi di Bari Aldo Moro ; Largo Abbazia Santa scolastica 53 ; 70124聽 ; Bari ; Italy
  2. Dipartimento di Metodi e Modelli per l鈥橢conomia ; il Territorio e la Finanza ; Sapienza Universit脿 di Roma ; Via Castro Laurenziano 9 ; 00161聽 ; Rome ; Italy
  3. Dipartimento di Scienze Statistiche ; Sapienza Universit脿 di Roma ; P.le Aldo Moro 5 ; 00185聽 ; Rome ; Italy
  4. Dipartimento di Scienze e Tecnologie Biologiche ed Ambientali ; Universit脿 del Salento ; Prov.le Lecce-Monteroni ; 73100聽 ; Lecce ; Italy
  
• 关键词：Multivariate multiple regression ; Correlated responses ; Bayesian inference ; Ecosystem status
• 刊名：Stochastic Environmental Research and Risk Assessment (SERRA)
• 出版年：2015
• 出版时间：February 2015
• 年：2015
• 卷：29
• 期：2
• 页码：477-485
• 全文大小：462 KB
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  2. Barbone E, Rosati I, Reizopoulou S, Basset A (2012) Linking classification boundaries to sources of natural variability in transitional waters: a case study of benthic macroinvertebrates. Ecol Indic 12:105鈥?22 lass="external" href="http://dx.doi.org/10.1016/j.ecolind.2011.04.014" target="_blank" title="It opens in new window">CrossRef
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• 刊物类别：Earth and Environmental Science
• 刊物主题：Environment
  Mathematical Applications in Environmental Science
  Mathematical Applications in Geosciences
  Probability Theory and Stochastic Processes
  Statistics for Engineering, Physics, Computer Science, Chemistry and Geosciences
  Numerical and Computational Methods in Engineering
  Waste Water Technology, Water Pollution Control, Water Management and Aquatic Pollution
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1436-3259

文摘

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.