Uncertainty analysis along the ecological quality status of water bodies: The response of the Posidonia oceanica multivariate index (POMI) in three Mediterranean regions

• Published in: Marine pollution bulletin Vol. 64; no. 5; pp. 926 - 931
• Main Authors: Mascaró, Oriol, Bennett, Scott, Marbà, Núria, Nikolić, Vedran, Romero, Javier, Duarte, Carlos M., Alcoverro, Teresa
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.05.2012
• Subjects: Alismatales - physiology; Balearic Islands; Biological indicators; bodies; Coastal environments; coasts; Croatia; data collection; Ecological monitoring; Environmental Monitoring - methods; Environmental Monitoring - standards; Fresh Water - chemistry; Islands; Marine; meadows; Mediterranean; Mediterranean Region; Monitoring; Multivariate Analysis; Pollution abatement; Posidonia oceanica; risk; Sampling; Seagrass; surface water; Uncertainty; uncertainty analysis; Water Framework Directive; Water Pollutants - analysis; water pollution; Water Pollution - statistics & numerical data; MED, Spain, Cataluna; MED, Croatia; Europe, Mediterranean Region; MED, Spain, Balearic Is; Mediterranean; Uncertainty; Seagrass; Water Framework Directive; Biological indicators
• ISSN: 0025-326X; 1879-3363
• DOI: 10.1016/j.marpolbul.2012.03.007

► Uncertainty estimation is a central element in WFD-compliant classification methods. ► Uncertainty associated to POMI index changes depending on the region of application. ► Uncertainty associated to POMI depends on the quality status of water bodies. ► Monitoring programmes design must respond to the specific conditions of water bodies. Uncertainty analyses allow the identification and quantification of the factors that contribute to the potential misclassification of the ecological status of water bodies, helping to improve the sampling design used in monitoring. Here we used a Posidonia oceanica multivariate index (POMI) bio-monitoring dataset covering a total of 81 sites distributed throughout 28 water bodies from the coast of Catalonia, Balearic Islands and Croatia to determine the levels of uncertainty associated with each region and how they change according to the quality status of water bodies. Overall, variability among sites (meadows) within water bodies was the factor that generated the greatest risk of misclassification among the three regions, within which the Balearic Islands had the lowest uncertainty, followed by Croatia and Catalonia. When water bodies classified in good/high quality were separated from those in moderate/poor status classes, we found that the latter displayed higher levels of uncertainty than the former.