Lipophilicity matters - A new look at experimental plant uptake data from literature.

Peer-reviewed Transpiration Stream Concentration Factor (TSCF) values were analysed to elucidate whether pH-induced changes in lipophilicity can explain some of the variability in reported TSCF and whether a potential relationship between lipophilicity and TSCF can be described by a simple mathematical model. The data set for this investigation combined TSCF values of 42 non-ionisable and ionisable compounds from hydroponic tests with intact plants and publicly available lipophilicity data for the tested compounds. The data set was not homogenous in terms of molecular weight of the tested compounds, plant species used for testing and experimental conditions, but a strong effect of one of these factors on variation in reported TSCF was not detected. Variation in TSCF was high for the same or similar predicted octanol/water partitioning coefficient (log P) but could be reduced by considering octanol/water distribution coefficients (log D) instead. The TSCF data set was split into a training and a test data set in order to identify and test a best-fit model describing the relationship between log D and TSCF. Comparing different types of models (linear, sigmoidal, Gaussian), the Gaussian model fitted to the training data set after removal of two outliers was identified as best-fit model based on visual assessment and fit statistics (RMSE = 0.20, NSE = 0.57, R = 0.75 (p < 0.001)). The 95% confidence interval around the best-fit model contained about 70% of data points in the training set and the test set, respectively. In conclusion, compound lipophilicity expressed as log D is a more appropriate descriptor of uptake by plant roots and subsequent translocation than log P when ionisable compounds are considered. Furthermore, findings in this study suggest that a relationship exists between log D and TSCF for uptake tests with intact plants which can be described by a simple bell-shaped Gaussian model.

Evaluation of a novel test design to determine uptake of chemicals by plant roots.

A new hydroponic study design to determine uptake of chemicals by plant roots was tested by (i) investigating uptake of [14C]-1,2,4-triazole by wheat plants in a ring test with ten laboratory organizations and (ii) studying uptake of ten other radiolabelled chemicals by potato, tomato or wheat plants in two laboratories. Replicate data from the ring test were used to calculate plant uptake factor (PUF) values (uptake into roots and shoots) and transpiration stream concentration factor (TSCF) values (uptake into shoots). Average PUF for 1,2,4-triazole was 0.73 (n=39, 95% confidence interval (CI): 0.64, 0.82) and the corresponding TSCF value was 1.03 (n=49, 95% CI: 0.76, 1.3). Boxplots and subsequent classification tree analysis of PUF and TSCF values showed that potential outlier values were >1.38 and were observed for PUF replicates with low biomass increase (ratio of final to initial biomass ≤1.739) and small initial biomass (≤1.55g) and for TSCF replicates with an increase in biomass of <0.67g over a period of eight days. Considering only valid replicate data, average values of PUF and TSCF were 0.65 (n=33, 95% CI: 0.57, 0.73) and 0.64 (n=39, 95% CI: 0.58, 0.70). The additional experiments with ten chemicals and three plant species showed that uptake was low for polar substances of high molecular weight (≥394g/mol) and that TSCF values increased with log Kow values of the tested chemicals ranging from -1.54 to 1.88 (polynomial equation with R2=0.64). A cluster analysis for three of the compounds that were tested on wheat and tomato indicated that the plant uptake was mainly determined by the substance. Overall, the findings show that the hydroponic study design allows for reliable quantification of plant uptake over a range of compound/crop combinations.

The footprint of pesticide stress in communities--species traits reveal community effects of toxicants.

The predictive power of the current risk-assessment framework for pesticides remains uncertain. This is because any extrapolation towards landscape-level effects encounters considerable uncertainties: (i) when proceeding from the level of individual single-species tests to populations and communities, biological interactions are not considered; (ii) from mesocosms to field communities, environmental factors and stressors that determine the effects of pesticides in the field are not considered; and (iii) most monitoring investigations are restricted spatially and do not consider recolonisation, and lack an adequate means of distinguishing confounding factors from natural variation. We advocate using species traits as community descriptors, to determine quantitative links between pesticide toxicity and community alterations. Recently, a trait-based indicator system was developed to identify SPEcies At Risk (SPEAR) of being affected by pesticides, with reference to life-history and physiological traits. This SPEAR system has now been successfully employed to link pesticide exposure and effects in Finland, France and Germany. The effect of pesticides on the structure of communities described with SPEAR was independent of the biogeographical region. We then extrapolated and visualised the anticipated risk for aquatic communities in small agricultural streams within Europe in a risk map. With this information we identified a potential risk from pesticide runoff in a high proportion of streams. By focusing on the ecological effect of selected environmental factors, trait-based approaches offer an increased realism for risk assessment of toxicants on the ecosystem level.

Mapping ecological risk of agricultural pesticide runoff.

A screening approach for the EU-scale is introduced and validated that predicts pesticide runoff and related ecological risk for aquatic communities in small agricultural streams. The approach is based on the runoff potential (RP) of stream sites, by a spatially explicit calculation based on pesticide use, precipitation, topography, land use and soil characteristics in the near-stream environment. The underlying simplified model complies with the limited availability and resolution of data at larger scales. RP is transformed to ecological risk by means of a runoff-response relationship between RP and invertebrate community composition that results from a large-scale investigation and considers the influence of landscape-mediated recovery pools. Community composition is expressed as abundance of SPEcies At Risk (SPEAR) i.e. species that are potentially affected by pesticides because of physiological sensitivity to organic pollutants and ecological traits. The SPEAR concept was applied because it provides powerful community descriptors that are independent of habitat parameters and support comparison of pesticide effects between different geographical regions. Raster maps for the EU before the 2004 enlargement indicate that ecological risk from pesticide runoff is potentially low for streams in 34% of the grid cells with non-irrigated arable land (mostly northern countries, predicted effects at < or = 20% of the streams per cell). In contrast, ecological risk is very high in 19% of the grid cells (central and southern countries, predicted effects at >90% of the streams per cell). Field investigations showed that the screening approach produced appropriate estimates of ecological risk from pesticide runoff for selected regions in Finland, France and Germany.

Agricultural intensity and landscape structure: influences on the macroinvertebrate assemblages of small streams in northern Germany.

The present study aimed to relate aquatic macroinvertebrate community composition to agricultural intensity and landscape structure. A total of 360 streams were investigated within the Aller river basin in northern Germany. The study area is typical of central German arable agricultural regions, but the small streams were of low dilution potential. These streams were characterized for abiotic parameters (including modeled potential for diffuse inputs from agricultural sources) and macroinvertebrate communities, with data collected over a 17-year period. Spray drift potential did not correlate with community composition. In contrast, the relative index of runoff potential (RP) was negatively correlated with various measures of taxonomic richness and abundance. Community composition also was correlated with environmental parameters, including stream width, clay content of sediment, and presence of dead wood in sediment. The abundance of sensitive species decreased significantly during the main period of agrochemical use at sites of high RP but completely recovered by the following spring. Long-term decreased taxonomic richness and a shift to ecologically robust species also were observed at sites of high RP. The results suggest that long-term alterations in community measures probably were associated with factors related to runoff input. Nevertheless, the community composition remained reasonably rich and even. Landscape structure also appeared to influence community structure. Abundance of sensitive species remained significantly enhanced, even at sites of high RP, when forested reaches were present in upstream reaches. These probably provided a source of organisms for downstream recolonization and amelioration of effects at high RP.

Estimating pesticide runoff in small streams.

Surface runoff is one of the most important pathways for pesticides to enter surface waters. Mathematical models are employed to characterize its spatio-temporal variability within landscapes, but they must be simple owing to the limited availability and low resolution of data at this scale. This study aimed to validate a simplified spatially-explicit model that is developed for the regional scale to calculate the runoff potential (RP). The RP is a generic indicator of the magnitude of pesticide inputs into streams via runoff. The underlying runoff model considers key environmental factors affecting runoff (precipitation, topography, land use, and soil characteristics), but predicts losses of a generic substance instead of any one pesticide. We predicted and evaluated RP for 20 small streams. RP input data were extracted from governmental databases. Pesticide measurements from a triennial study were used for validation. Measured pesticide concentrations were standardized by the applied mass per catchment and the water solubility of the relevant compounds. The maximum standardized concentration per site and year (runoff loss, R(Loss)) provided a generalized measure of observed pesticide inputs into the streams. Average RP explained 75% (p<0.001) of the variance in R(Loss). Our results imply that the generic indicator can give an adequate estimate of runoff inputs into small streams, wherever data of similar resolution are available. Therefore, we suggest RP for a first quick and cost-effective location of potential runoff hot spots at the landscape level.