RISK ASSESSMENT OF AGROCHEMICALS ON IRRIGATION WATER QUALITY
Pesticides used for crop protection in agriculture may enter irrigation canals, drainage ditches, ponds, lakes and rivers in numerous ways such as direct overspray, spray drift, leaching to surface and ground water, run-off from land, and/or accidental spills. To protect the biological integrity of these waters it is important to assess the po¬tential risks associated with the pesticide stress to aquatic ecosystems. To date Eco¬logical Risk Assessment (ERA) has focused on investigating the impacts of chemicals on individuals, but future focus should be on the protection of populations and communities in the field. The understanding of how population, communities and ecosystems are affected by for instance pesticides could be increased by integrating the fields of toxicology, chemistry, ecology and bioinformatics at different levels of biological organisation into the field of chemical stress ecology. How species and ecosystems react to pesticide stress, is governed by their intrinsic species sensitivity, interactions between species and communities and the recovery potential of popula¬tions. We present how a better understanding of these aspects could improve the scientific foundation and ecological justification of the ERA of pesticides. One of the major other challenges in ERA is to develop methodologies, models, rules of thumb among others that can be used to extrapolate effects and recovery patterns observed or modelled for one specific situation to another situation. For instance, can a sensitivity value for a Northern-European species be used in a Mediterranean risk assessment? This paper will reflect only on three types of extrapolation that we consider to be important for the ERA of pesticides, viz., extrapolation across exposure patterns, ecosystem complexity and geography.
Daam, M.A. and Van den Brink , P.J. (2011). RISK ASSESSMENT OF AGROCHEMICALS ON IRRIGATION WATER QUALITY . Acta Hortic. 922, 41-47
environmental risk assessment, pesticides, model ecosystems, species sensitivity distributions, traits, extrapolation