The conventional view of pollution monitoring is that any choice is a trade-off between realism and precision, as the control over confounding variables decreases with the increasing degree of organization of the test system. Dublin Bay is subject to considerable anthropogenic pressures and there have been many attempts to quantify the status of the system at organizational levels from DNA strand breaks (Comet) to the system itself (Ecological Network analysis, ENA). Using Dublin Bay as an example, the data show there was considerable variability at all levels of organization. At intracellular level, Lysosome Membrane Stability (LMS, assessed by Neutral Red Retention, NRR) varied almost 4-fold with season and individual condition, while the community level AZTI Marine biotic Index (AMBI) had a similar range within a single, supposedly homogeneous, site. Overall, there was no evidence that biomarkers of the lower levels of organisation reduced the variability of the measure, despite the extra control over influencing variables, nor was there any evidence that variability was additive at higher levels of organisation. This poses problems for management, especially given the fixed limits of Ecological Quality Standards (EQSs). Clearly while the integrated approach to pollution monitoring does offer the potential to link effects across the organizational range, it should also be possible to improve their capability by widening the database for reference values, particularly at the higher level of organization, and by process models, including the confounding variables found in the field, for those at lower level.
Keywords: Biomarkers; Dublin Bay; Ecological status; Pollution; Variability.
Copyright © 2014. Published by Elsevier Ltd.