Translating bioassay results to field population responses using a Leslie-matrix model for the marine amphipod Corophium volutator

Bioassays can be used for the assessment of sediment contamination. The response is classified based on a statistical scale indicating a certain effect percentage being significantly different from the controls (e.g. mortality classes of 0–10%, 10–20% etc.). The ecological relevance of this statistical scale is low. Extrapolating the observed mortality to population success could facilitate the development of a more ecological relevant scale. By incorporating the results of bioassays in population models, the consequences of the presence of contaminants can be studied at the population level. Based on a Leslie matrix combined with mathematical modelling of important biological processes, a population model is developed for Corophium volutator, a marine amphipod used in sediment bioassays. A literature review is carried out to specify reproduction, growth, mortality and predation and the way these factors depend on temperature and food availability. This resulted in a model describing the population development (population growth rate) of C. volutator. Field data of the C. volutator population in the Oesterput, a location in the Dutch Eastern Scheldt estuary, are applied to study the capability of the model to describe a field population. For populations tested in bioassays, without food limitation and predation, increasing population sizes (population growth rate (λ) >1) are predicted between +6.5 °C and +30.0 °C. Mortality observed in bioassays will reduce λ. Using a realistic temperature profile, a maximum allowable bioassay response of 30.5% reducing λ to a value of 1 was determined. However, also external factors like predation and food limitation will reduce the value of λ. This hampers the definition of a generic threshold based on population effects. The developed model forms a useful intermediate in the translation of bioassay effects to population effects for C. volutator. Not only does the model provide new information about the sensitivity of test organisms and thus contributes to reducing uncertainty in test results, but it provides a means to increase the ecological relevance of bioassays responses. These latter capabilities are valuable to the regulation authorities.