Since 1988, biomarkers in female perch (Perca fluviatilis) have been analyzed at a reference site on the Swedish Baltic coast. Strong time trends toward increasing hepatic ethoxyresorufin-O-deethylase (EROD) activity and reduced gonadosomatic index (GSI) have been observed. This could be caused by pollutants as well as other factors, such as increasing water temperature or reduced mean age of sampled fish. Correlation analyses were used to find the most probable explanation for the time trends. The time trends were still significant for EROD (p < 0.001) and GSI (p < 0.001) when the correlations were controlled for age. Furthermore, increasing water temperature could not explain the time trends. Exposure to pollutants through runoff from land was found to be probable, because mean flow rate in a nearby river during the last 20 d before sampling correlated to EROD activity (p < 0.01). In addition, the sum of EROD activities during the life time of the perch (ERODlife) correlated significantly with GSI (p < 0.001). This suggests that perch exposed to more EROD-inducing chemicals during their lifetime have reduced or delayed gonad development. The time trend in GSI and the correlation between ERODlife and GSI were supported by data from a site in the Bothnian Bay (northern Baltic Sea; p < 0.05). The results indicate that increased rain fall (climate change) can affect the distribution and bioavailability of chemicals in coastal areas. The link between EROD and gonad size supports the common assumption that biochemical biomarkers can act as early warning signals for effects on higher levels, which commonly is difficult to show. The significant results can probably be attributed to the unique 20-year data set.

Ecological risk assessments (ERA) of chemicals are often based on mortality and reproduction of individuals. To protect populations, fixed safety factors are applied to the data. However, the relationship between individuals and populations cannot easily be described by predefined numbers. The use of population models may reduce uncertainty and, hence, the risk for erroneous assessments. However, introducing models also introduces additional complexity. Therefore, it is desirable to keep the models as simple as possible. The objective of the present study was to determine whether simple risk equations or matrix models can improve ERA compared to traditional endpoints. To examine this, complex models that included environmental stochasticity and density dependence were used to simulate population level risk based on dose-response data for five chemicals. The risk, measured as probability for pseudo extinction and recovery time, was then compared to risk estimates based on individual level data (acute and chronic), risk equations, and simple matrix models. The results showed that the simple matrix models reduced uncertainty by more than 88% and 76% compared to acute and chronic data, respectively. Also the simple risk equation reduced uncertainty considerably (80% and 61% compared to acute and chronic data, respectively).

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Traditionally, ecological risk assessments (ERA) of pesticides have been based on risk ratios, where the predicted concentration of the chemical is compared to the concentration that causes biological effects. The concentration that causes biological effect is mostly determined from laboratory experiments using endpoints on the level of the individual (e.g., mortality and reproduction). However, the protection goals are mostly defined at the population level. To deal with the uncertainty in the necessary extrapolations, safety factors are used. Major disadvantages with this simplified approach is that it is difficult to relate a risk ratio to the environmental protection goals, and that the use of fixed safety factors can result in over- as well as underprotective assessments. To reduce uncertainty and increase value relevance in ERA, it has been argued that population models should be used more frequently. In the present study, we have used matrix population models for 3 daphnid species (Ceriodaphnia dubia, Daphnia magna, and D. pulex) to reduce uncertainty and increase value relevance in the ERA of a pesticide (spinosad). The survival rates in the models were reduced in accordance with data from traditional acute mortality tests. As no data on reproductive effects were available, the conservative assumption that no reproduction occurred during the exposure period was made. The models were used to calculate the minimum population size and the time to recovery. These endpoints can be related to the European Union (EU) protection goals for aquatic ecosystems in the vicinity of agricultural fields, which state that reversible population level effects are acceptable if there is recovery within an acceptable (undefined) time frame. The results of the population models were compared to the acceptable (according to EU documents) toxicity exposure ratio (TER) that was based on the same data. At the acceptable TER, which was based on the most sensitive species (C. dubia), the maximum reduction in population size was 13% and the maximum time to recovery was 4 d (both for D. magna). This information is clearly more informative for risk management than a risk ratio. For one of the species, D. pulex, a more complex model, which included sublethal effects on reproduction, was set up. The results of this model were in good agreement with a previous microcosm study and indicated that a traditional TER was overprotective.