PREDICTING THE ECOLOGICAL EFFECTS OF HERBICIDES

One purpose of the science of ecotoxicology is to provide information for protecting ecosystems. Understanding the hazards of chemicals is e ssential to wise decision making, and it is now clear that community s tructure changes are closely linked to altered ecosystem function. Unc ertainty is high when decisions are made from a small biological (toxi cological) database. Individual bioassays provide little insight into biological interactions that are important in sustaining ecosystems. A rtificial ecosystem experiments with herbicides demonstrate the limite d predictive power of bioassays and ecological risk assessment methods that are heavily dependent on animal testing. Many herbicides interfe re with unique pathways in photosynthetic organisms but are not very t oxic to animals. For example, the herbicide atrazine is not considered toxic to fishes, because atrazine interferes with electron transport in photosystem II. But, adding atrazine at low levels (3-100 mu g/L) t o aquatic microcosms demonstrated significant increases in algal bioma ss, concurrent enhancement of nutrient recovery systems, and increases in the detectable number of heterotrophic microbial species. Higher l evels of atrazine (100-300 mu g/L) produced general collapse of these laboratory ecosystems. Low levels of atrazine capable of producing eco system-level effects can occur from days to weeks in streams of midwes tern agricultural areas. Conversely, the herbicide diquat is rapidly i mmobilized in the field if fine sediments are present. Laboratory bioa ssays tend to overestimate diquat toxicity if sediments are not presen t because the material rarely persists in the water column. A variety of measures of ecosystem condition are available for assessment of che mical effects. Community structure changes (especially of nontarget gr oups) and changes in ecosystem process variables have technical import ance and are not assessed in current risk assessment paradigms. Regula tors need to draw on a more comprehensive data set than is presently u sed to make risk assessment decisions. Sometimes, this may require usi ng methods other than those considered standard for data development.