The idea of adopting ERA as a fundamental component in the management of ecosystems has gained an increased recognition due to the fact that it is impossible to eliminate all environmental effects of human activities and that decisions must be made on the basis of incomplete data and incomplete scientific knowledge (Suter, 1993). Therefore, it is necessary to reach a compromise between acceptable risks levels and the costs of reducing these risks. This becomes even more relevant when different stressors, i.e. physical, chemical and biological, are involved which is typically the case of aquatic ecosystems.
The existence of several spatio-temporal scales when assessing the risks in ecosystems and several levels of ecological organization from organism, population to food web, etc. provokes the existence of a gap between what is feasible to measure and what is interesting to assess. Being organisms the easiest unit to measure and ecosystem the relevant level for protection. It is for this reason that models are frequently used to fill this gap and provide meaningful extrapolation across time, space and biological organization scales (Suter, 1993).
Concerning chemical stressors to aquatic ecosystems, eutrophication and contamination with pollutants have been subject to intensive modelling research during the past decades (Cloern, 2001). Unfortunately, they have been mainly treated separately under the assumption that changes in trophic state cause negligible feedback on the fate of pollutants and their effects, and that toxicity of chemical produced negligible feedback on the physicochemical processes that determined the fate of pollutants (Koelmans et al., 2001). Of course, these assumptions are not always true and it has been seen that heavy metals (Sanders and Cibik, 1988, Kuwabara et al., 1989), chlorinated hydrocarbons as DDT and PCBs (Mosser et al., 1972) and herbicides such as atrazine and diuron inhibit selectively some species of
algae promoting population growth of the less-sensitive taxa. Furthermore, nutrient enrichment leads sometimes to enhanced accumulation of contaminants (Gunnarsson and Sköld, 1999) or may cause dilution of contaminants, e.g. nutrient enhanced algal production may cause change in the overall toxicity by increased transformation of contaminants though algal metabolism (Breitburg et al., 1999).
The main objective of this work is to assess the different types of models, e.g. population models, ecosystem models, with and without spatial components, chemical fate and transport models, bioaccumulation models and food web exposure models, from the thresholds perspective; and to assess how an integrated fate and effect model should be developed to consider the occurrence of points at which there is an abrupt change in an ecosystem quality produced by a small change in an environmental driver. The main objective is the increased concern about preventing dramatic state changes in ecosystems and our modelling approach should help in determining critical pollutant loads.
The focus of this study will be on coastal ecosystems which is the main focus of the IP Thresholds of environmental sustainability. The results of this analysis will then be incorporated in Stream 4 (S4: Thresholds of contaminants) where specific studies are being conducted and models developed.