Small streams are important refuges for biodiversity. In agricultural areas, they may be at risk from pesticide pollution. However, most related studies have been limited to a few streams on the regional level, hampering extrapolation to larger scales. We quantified risks as exceedances of regulatory acceptable concentrations (RACs) and used German monitoring data to quantify the drivers thereof and to assess current risks in small streams on a large scale. The data set was comprised of 1 766 104 measurements of 478 pesticides (including metabolites) related to 24 743 samples from 2301 sampling sites. We investigated the influence of agricultural land use, catchment size, as well as precipitation and seasonal dynamics on pesticide risk taking also concentrations below the limit of quantification into account. The exceedances of risk thresholds dropped 3.7-fold at sites with no agriculture. Precipitation increased detection probability by 43%, and concentrations were the highest from April to June. Overall, this indicates that agricultural land use is a major contributor of pesticides in streams. RACs were exceeded in 26% of streams, with the highest exceedances found for neonicotinoid insecticides. We conclude that pesticides from agricultural land use are a major threat to small streams and their biodiversity. To reflect peak concentrations, current pesticide monitoring needs refinement.

Species reproduction is an important determinant of population dynamics. As such, this is an important parameter in environmental risk assessment. The closure principle computational approach test (CPCAT) was recently proposed as a method to derive a NOEC/LOEC for reproduction count data such as the number of juvenile Daphnia. The Poisson distribution used by CPCAT can be too restrictive as a model of the data-generating process. In practice, the generalized Poisson distribution could be more appropriate, as it allows for inequality of the population mean and the population variance . It is of fundamental interest to explore the statistical power of CPCAT and the probability of determining a regulatory relevant effect correctly. Using a simulation, we varied between Poisson distribution () and generalized Poisson distribution allowing for over-dispersion () and under-dispersion (). The results indicated that the probability of detecting the LOEC/NOEC correctly was provided the effect was at least 20% above or below the mean level of the control group and mean reproduction of the control was at least 50 individuals while over-dispersion was missing. Specifically, under-dispersion increased, whereas over-dispersion reduced the statistical power of the CPCAT. Using the well-known Hampel identifier, we propose a simple and straight forward method to assess whether the data-generating process of real data could be over- or under-dispersed.

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Background The European environmental risk assessment of plant protection products considers aquatic model ecosystem studies (microcosms/mesocosms, M/M) as suitable higher tier approach to assess treatment-related effects and to derive regulatory acceptable concentrations (RAC). However, it is under debate to what extent these artificial test systems reflect the risks of pesticidal substances with potential harmful effects on natural macroinvertebrate communities, and whether the field communities are adequately protected by the results of the M/M studies. We therefore compared the composition, sensitivity and vulnerability of benthic macroinvertebrates established in control (untreated) groups of 47 selected M/M studies with natural stream communities at 26 reference field sites. Results Since 2013 the number of benthic macroinvertebrate taxa present in M/M studies has increased by 39% to a mean of 38 families per study. However, there is only an average of 4 families per study that comply with the recommendations provided by EFSA (EFSA J 11:3290, 2013), i.e.: (i) allowing statistical identification of treatment-related effects of at least 70% according to the minimum detectable difference (here criteria are slightly modified) and (ii) belonging to insects or crustaceans (potentially sensitive taxa for pesticidal substances). Applying the criterion of physiological sensitivity according to the SPEARpesticides concept, the number of families decreases from 4 to 2.3 per study. Conclusions Most taxa established in recent M/M studies do not suitably represent natural freshwater communities. First, because their abundances are often not sufficient for statistical detection of treatment-related effects in order to determine an appropriate endpoint and subsequent RAC. Recommendations are given to improve the detectability of such effects and their reliability. Second, the taxa often do not represent especially sensitive or vulnerable taxa in natural communities in terms of their traits. The uncertainties linked to vulnerable taxa in M/M studies are especially high considering their representativity for field assemblages and the comparability of factors determining their recovery time. Thus considering recovery for deriving a RAC (i.e., ERO-RAC) is not recommended. In addition, this paper discusses further concerns regarding M/M studies in a broader regulatory context and recommends the development of alternative assessment tools and a shift towards a new paradigm.