Higher than … or lower than ….? Evidence for the validity of the extrapolation of laboratory toxicity test results to predict the effects of chemicals and ionising radiation in the field.

Single species laboratory tests and associated species sensitivity distributions (SSDs) that utilise the resulting data can make a key contribution to efforts to prospective hazard assessments for pesticides, biocides, metals and ionising radiation for research and regulatory risk assessment. An assumption that underlies the single species based toxicity testing approach when combined in SSD models is that the assessments of sensitivities to chemical and ionising radiation measured across a range of species in the laboratory can inform on the likely effects on communities present in the field. Potential issues with the validity of this assumption were already recognised by Van Straalen and Denneman (1989) in their landmark paper on the SSD methodology. In this work, they identified eight major factors that could potentially compromise the extrapolation of laboratory toxicity data to the field. Factors covered a range of issues related to differences in chemistry (e.g. bioavailability, mixtures); environmental conditions (optimal, variable), ecological (compensatory, time-scale) and population genetic structure (adaptation, meta-population dynamics). This paper outlines the evidence pertaining to the influence of these different factors on toxicity in the laboratory as compared to the field focussing especially on terrestrial ecosystems. Through radiological and ecotoxicological research, evidence of the influence of each factor on the translation of observed toxicity from the laboratory to field is available in all cases. The importance of some factors, such as differences in chemical bioavailability between laboratory tests and the field and the ubiquity of exposure to mixtures is clearly established and has some relevance to radiological protection. However, other factors such as the differences in test conditions (optimal vs sub-optimal) and the development of tolerance may be relevant on a case by case basis. When SSDs generated from laboratory tests have been used to predict chemical and ionising radiation effects in the field, results have indicated that they may often seem to under-predict impacts, although this may also be due to other factors such as the effects of other non-chemical stressors also affecting communities at polluted sites. A better understanding of the main factors affecting this extrapolation can help to reduce uncertainty during risk assessment.