Environmental assessment tools for the evaluation and improvement of European livestock production systems

Different types of assessment tools have been developed in Europe with the purpose of determining the environmental impact of various livestock production systems at farm level. The assessment tools differ in terms of which environmental objectives are included and how indicators are constructed and interpreted. The paper compares typical tools for environmental assessment of livestock production systems, and recommends selected indicators suitable for benchmarking. The assessment tools used very different types of indicators ranging from descriptions of farm management and quantification of input to estimates of emissions of, e.g., nitrate and ammonia. The indicators should be useful in a benchmarking process where farmers may improve their practices through learning from farms with better agri-environmental performance. An example of this is given using data on P-surplus on pig farms. Some indicators used the area of the farm as the basis of the indicator — e.g. nitrogen surplus per hectare — while others were expressed per unit produced, e.g. emission of greenhouse gasses per kilogram milk. The paper demonstrates that a comparison of organic vs. conventional milk production and comparison of three pig production systems give different results, depending on the basis of the indicators (i.e. per hectare or per kilogram product). Indicators linked to environmental objectives with a local or regional geographical target should be area-based — while indicators with a global focus should be product-based. It is argued that the choice of indicators should be linked with the definition of the system boundaries, in the sense that area-based indicators should include emissions on the farm only, whereas product-based indicators should preferably include emissions from production of farm inputs, as well as the inputs on the actual farm. The paper ends with recommendations for choice of agri-environmental indicators taking into account the geographical scale, system boundary and method of interpretation

Eco-efficiency of tomato from Rwamagana district in Rwanda: From field constraints to statistical significance

On the request of decision-makers, the Life Cycle Assessment (LCA) framework is increasingly applied in agri-food value chains in developing countries under particularly demanding constraints. Based on the cradle-to-farm-gate LCA results of the tomato in Rwamagana district in Rwanda commissioned by the European Union, the main objectives of the paper were to validate statistically the differences in environmental impacts among expert-based types for this crop based on location and season and identify the key-drivers of these impacts. The study was developed thanks to two intensive field visits and a survey of 15 plots. The functional unit was one kg of tomato at farm-gate. Combining several statistical analyses allowed identifying three groups of plots with contrasting input profile and eco-efficiency. For most impact categories, the first group with mainly plots in marshland during wet season had the lowest impacts and the third group with plots in hillside showed the highest impacts. The yield of tomato being significantly different between marshland and hillside plots was an important driver of these results. The second group composed of plots in marshland during the dry season generally showed intermediate impacts due to the withdrawing of water for irrigation. The second group obtained a higher freshwater ecotoxicity due to a more intensive use of toxic insecticides. The factorial analysis for mixed data (FAMD) confirmed the importance of the location and the season for the eco-efficiency of tomato plots and the hierarchical clustering on principle components (HCPC) separated the tomato plots into three clusters. The generalized linear models (GLMs) validated the differences in the environmental impacts per kg of tomato between the clusters. The principal component analysis (PCA) combined to GLM revealed that only the use of water was significantly different between the three groups. Compared to existing datasets, all groups showed high freshwater ecotoxicity impacts due to the use of toxic insecticides and the excessive use of mancozeb. The third group also showed a high freshwater eutrophication in relation to P losses due to erosion and low yield. From a methodological point of view, we demonstrated in this paper that using expert-based typologies combined with adapted statistical analyses constituted a relevant approach under such circumstances