Comparative study of model prediction of diffuse nutrient losses in response to changes in agricultural practices.

This article presents a comparative study of modelled changes in nutrient losses from two European catchments caused by modifications in agricultural practices. The purpose was not to compare the actual models used, but rather to assess the uncertainties a manager may be faced with after receiving decision support from consultants using different models. Seven modelling teams were given the same data about two catchments and their management characteristics and were asked to model the same changes in management practices using the model of their own choice. This can potentially cause accumulated 'errors' due to differences in the modelling teams' interpretation of relevant processes and definitions of boundary conditions (inputs). The study was carried out within the framework of the EUROHARP project, which aimed at harmonising procedures for quantifying diffuse losses of nitrogen and phosphorus from agriculture. Models are important for assessing river basin management plans (RBMPs) as required e.g. under the EC Water Framework Directive and Action Plans under the EC Nitrates Directive. This article illustrates some challenges with respect to interpreting such modelling results. The selected management scenarios include changes in fertiliser application levels, changes in livestock numbers and changes in land-use and crop rotation systems. Seven models were applied for the same scenarios in the Enza catchment in Italy and the Zelivka catchment in the Czech Republic. All models had been calibrated and validated with respect to historical data of climatic conditions, water quality and discharge measurements. The modelling results reveal a variation in predicted effects of the management scenarios, causing different conclusions with respect to choice of best management practice for reducing nutrient losses. The study demonstrates that it is important that care is taken by modellers and involved decision makers throughout the entire modelling process, both with regard to a common understanding of the problem definition, understanding of boundary conditions, and uncertainty of outputs and interpretation of results.

Testicular cancer and parental use of fertilizers in agriculture.

Testicular cancer incidence is increasing rapidly in several countries. Environmental causes acting early in life are suspected but have not yet been identified. We conducted a cohort study to identify parental risk factors for testicular cancer among farmers' sons. Children born in 1952-1991 to parents who were farm holders at the time of the agricultural censuses in 1969-1989 were identified in the Central Population Register (Oslo, Norway). The resulting cohort of male offspring (n = 166,291) were followed up in the Cancer Registry of Norway (Oslo, Norway) for 1965-1991. Exposure indicators were derived from census information on activities on the farm. The cancer incidence was compared with that of the total rural population, and potential risk factors were analyzed by Poisson regression. In a follow-up of 2,924,663 person-years, 158 incident cases of testicular cancer were identified. The study population had a higher incidence of testicular cancer than did the total rural population, particularly at ages 15-19 years and in western Norway. Specific fertilizer regimens on the farm were associated with testicular cancer (rate ratio = 2.44; 95% confidence interval = 1.66-3.56), in particular nonseminoma (rate ratio = 4.21; 95% confidence interval = 2.13-8.32). The rate ratio estimates were highest for boys ages 15-19 years and for a subset of study subjects who were considered more likely to have grown up on a farm. Nondifferential misclassification and bias toward unity are likely because exposure information was available only at the farm level and only for census years. The fertilizer indicators were not available early in life for most subjects, and precise interpretations are difficult. A hypothesis worth considering is that excess nutrient run-off from agriculture constitutes a risk. However, inferences concerning the biological basis of our observations can scarcely be made.