Christian Bockstaller

Bio: Christian Bockstaller is an academic researcher from Nancy-Université. The author has contributed to research in topics: Sustainability & Cropping system. The author has an hindex of 11, co-authored 39 publications receiving 1028 citations. Previous affiliations of Christian Bockstaller include Institut national de la recherche agronomique.

MASC, a qualitative multi-attribute decision model for ex ante assessment of the sustainability of cropping systems

Abstract: Realistic assessments of sustainability are often viewed as typical decision-making problems requiring multi-criteria decision-aid (MCDA) methods taking into account the conflicting objectives underlying the economic, social and environmental dimensions of sustainability, and the different sources of knowledge representing them. Some MCDA-based studies have resulted in the development of sustainable agricultural systems, but the new challenges facing agriculture and the increasing unpredictability of their driving forces highlight the need for faster ex ante ('Before-the-event') assessment frameworks. These frameworks should also (i) provide a more realistic assessment of sustainability, by integrating a wider range of informal knowledge, via the use of qualitative information; (ii) address alternative scales, such as cropping system level, improving granularity for the handling of sustainability issues and (iii) target a larger panel of decision-makers and contexts. We describe here the MASC model, which is at the center of a framework addressing these objectives. The MASC model has at its core a decision tree that breaks the sustainability assessment decisional problem down into simpler units as a function of sustainability dimensional structure (economic, social and environmental), generating a vector of 32 holistic 'mixed' (quantitative and qualitative) elementary criteria rating cropping systems. The assessment process involves the calculation of these criteria, their homogenization into qualitative information for input into the model and their aggregation throughout the decision tree based on 'If-Then' decision rules, entered by the user. We present the model and describe its first implementation for the evaluation of four cropping systems generated from expert knowledge, and discuss its relevance to the objectives cited above. The MASC model has several advantages over existing methods, due to its ability to handle qualitative information, its transparency, flexibility and feasibility.

Pesticide Exposure, Safety Issues, and Risk Assessment Indicators

Abstract: Pesticides are widely used in agricultural production to prevent or control pests, diseases, weeds, and other plant pathogens in an effort to reduce or eliminate yield losses and maintain high product quality. Although pesticides are developed through very strict regulation processes to function with reasonable certainty and minimal impact on human health and the environment, serious concerns have been raised about health risks resulting from occupational exposure and from residues in food and drinking water. Occupational exposure to pesticides often occurs in the case of agricultural workers in open fields and greenhouses, workers in the pesticide industry, and exterminators of house pests. Exposure of the general population to pesticides occurs primarily through eating food and drinking water contaminated with pesticide residues, whereas substantial exposure can also occur in or around the home. Regarding the adverse effects on the environment (water, soil and air contamination from leaching, runoff, and spray drift, as well as the detrimental effects on wildlife, fish, plants, and other non-target organisms), many of these effects depend on the toxicity of the pesticide, the measures taken during its application, the dosage applied, the adsorption on soil colloids, the weather conditions prevailing after application, and how long the pesticide persists in the environment. Therefore, the risk assessment of the impact of pesticides either on human health or on the environment is not an easy and particularly accurate process because of differences in the periods and levels of exposure, the types of pesticides used (regarding toxicity and persistence), and the environmental characteristics of the areas where pesticides are usually applied. Also, the number of the criteria used and the method of their implementation to assess the adverse effects of pesticides on human health could affect risk assessment and would possibly affect the characterization of the already approved pesticides and the approval of the new compounds in the near future. Thus, new tools or techniques with greater reliability than those already existing are needed to predict the potential hazards of pesticides and thus contribute to reduction of the adverse effects on human health and the environment. On the other hand, the implementation of alternative cropping systems that are less dependent on pesticides, the development of new pesticides with novel modes of action and improved safety profiles, and the improvement of the already used pesticide formulations towards safer formulations (e.g., microcapsule suspensions) could reduce the adverse effects of farming and particularly the toxic effects of pesticides. In addition, the use of appropriate and well-maintained spraying equipment along with taking all precautions that are required in all stages of pesticide handling could minimize human exposure to pesticides and their potential adverse effects on the environment.

Global Water Pollution and Human Health

Abstract: Water quality issues are a major challenge that humanity is facing in the twenty-first century. Here, we review the main groups of aquatic contaminants, their effects on human health, and approaches to mitigate pollution of freshwater resources. Emphasis is placed on chemical pollution, particularly on inorganic and organic micropollutants including toxic metals and metalloids as well as a large variety of synthetic organic chemicals. Some aspects of waterborne diseases and the urgent need for improved sanitation in developing countries are also discussed. The review addresses current scientific advances to cope with the great diversity of pollutants. It is organized along the different temporal and spatial scales of global water pollution. Persistent organic pollutants (POPs) have affected water systems on a global scale for more than five decades; during that time geogenic pollutants, mining operations, and hazardous waste sites have been the most relevant sources of long-term regional and local water pollution. Agricultural chemicals and wastewater sources exert shorter-term effects on regional to local scales.

The Soil Management Assessment Framework

Abstract: Erosion rates and annual soil loss tolerance (T) values in evaluations of soil management practices have served as focal points for soil quality (SQ) research and assessment programs for decades. Our objective is to enhance and extend current soil assessment efforts by presenting a framework for assessing the impact of soil management practices on soil function. The tool consists of three steps: indicator selection, indicator interpretation, and integration into an index. The tool's framework design allows researchers to continually update and refine the interpretations for many soils, climates, and land use practices. The tool was demonstrated using data from case studies in Georgia, Iowa, California, and the Pacific Northwest (WA, ID, OR). Using an expert system of decision rules as an indicator selection step successfully identified indicators for the minimum data set (MDS) in the case study data sets. In the indicator interpretation step, observed indicator data were transformed into unitless scores based on site-specific algorithmic relationships to soil function. The scored data resulted in scientifically defensible and statistically different treatment means in the four case studies. The efficacy of the indicator interpretation step was evaluated with stepwise regressions using scored and observed indicators as independent variables and endpoint data as iterative dependent variables. Scored indicators usually had coefficients of determination (R2) that were similar or greater than those of the observed indicator values. In some cases, the R2 values for indicators and endpoint regressions were higher when examined for individual treatments rather than the entire data set. This study demonstrates significant progress toward development of a SQ assessment framework for adaptive soil resource management or monitoring that is transferable to a variety of climates, soil types, and soil management systems.