AUTHOR=García-García Luz María , Sivyer Dave , Devlin Michelle , Painting Suzanne , Collingridge Kate , van der Molen Johan 

TITLE=Optimizing Monitoring Programs: A Case Study Based on the OSPAR Eutrophication Assessment for UK Waters

JOURNAL=Frontiers in Marine Science

VOLUME=Volume 5 - 2018

YEAR=2019

URL=https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2018.00503

DOI=10.3389/fmars.2018.00503

ISSN=2296-7745

ABSTRACT=The data and results of the UK second application of the OSPAR Common Procedure (COMP) for eutrophication were used as a case study to develop a generic system i) to assess an observational network from a multi-variable point of view, ii) to introduce additional datasets in the assessment and iii) to help reduce the cost of the monitoring programme. The method consisted of tools to analyse, by means of simple statistical techniques, if any reduction of the available datasets could correspond to the published assessments, with reduced costs (and limited loss in confidence). The data reduction scenarios included the removal of an existing dataset or the inclusion of freely available third-party data (ferrybox, satellite observations) combined with a subset of existing datasets. Merging different datasets was problematic due to the heterogeneity of the techniques, sensors, scales, and a cross validation was carried out between the different datasets out to assess possible biases between the different datasets.
The analysis of the results showed that there was little margin to remove any of the available datasets and that the use of extensive datasets, such as satellite data, has an important effect, leading very often to a change in the results of the assessment with respect to the thresholds, generally in the sense of moving from threshold exceedance to the opposite.This suggested that the results of the original assessment might be biased to the sampling location and time and emphasized the importance of monitoring programmes covering extensive spatial and temporal scales, and the opportunity to improve assessments by combining observations, satellite data and model results.