Philippe Girardin

Use of agro-ecological indicators for the evaluation of farming systems

For the development of integrated arable farming systems (IAFS), tools are needed to evaluate the achievement of agronomic and environmental objectives, in order to optimize the systems. A set of agro-ecological indicators (AEI) is proposed. These indicators estimate the impact of cultivation practices on the agrosystem and its environment. AEI are aimed, first of all, at being used as decision aid tools, to help farmers to adapt their cultivation practices to IAFS requirements, from one cropping year to the next. So far, seven indicators have been elaborated for the evaluation of farming systems: crop diversity, crop succession, pesticide, nitrogen, phosphorus, organic matter and irrigation. The calculation method for the organic matter and pesticide indicators is presented. Possibilities for use of the AEI at the farm and field level, for farmers and decision makers are given with data from a network of 17 commercial arable farms. The elaboration of a single aggregated indicator is discussed.

Agri-Environmental Indicators to Assess Cropping and Farming Systems: A Review

Environmental impacts of agriculture cannot be always assessed by using direct measurements. Since the 1990s, numerous agri-environmental indicators were developed to assess the adverse effects of cropping and farming systems in the environment, such as water pollution, soil erosion, and emission of greenhouse gases. Here we present the different types of indicators developed during the last decade and review the progress of the methods used for their development. The application of different groups of indicators is discussed and illustrated by examples in the fields of nitrogen losses and pesticide risk: (1) indicators based on a single or a combination of variables related to farmer practices, (2) indicators derived from operational or more complex simulation models assessing emissions of pollutants, and (3) measured indicators linked directly to environmental impacts. The nitrogen indicator (IN) of the INDIGO method and the MERLIN indicator will be presented and used to illustrate the methodological discussion. We show that a good identification of the end-users, of the practical objectives of the indicator, and of the spatial and temporal scales is essential and should be done at a preliminary step before designing the indicator itself. The possibilities of deriving an indicator from a model and of setting a reference value are discussed. Several methods are also presented to study the sensitivity and the validity of agri-environmental indicators. Finally, several practical recommendations are made. As only few data are usually available at the regional level, several simple indicators should be used for assessing a given impact at this level. When more detailed information is available, indicators based on operational models can be useful to analyse the effects of several factors related to soil, climate, and cropping system on an environmental impact. In experimental studies, we suggest using both measured indicators and model-based indicators.

Comparison of methods to assess the sustainability of agricultural systems. A review

Since the 1990s, numerous agri-environmental indicators and indicator-based methods have been developed to assess the adverse effects of cropping and farming systems such as water pollution by nitrates and pesticides, and gaseous emissions due to nitrogen inputs. This wealth of environmental indicators and assessment methods based on indicators raises issues on the quality of the methods and of the indicators, and on the relevancy of results. Evaluation and comparative studies are therefore needed to answer such issues. Here, we present four recent comparative studies selected for their illustrative value, first, to analyse the methodologies used for comparison of methods, and second, to highlight the main results of the four comparisons. The first study involves 23 indicators to address nitrate leaching. The second study involves 43 indicators to address pesticide risk. The third and fourth studies compare environmental assessment methods based on 4–5 indicators used in French and Upper Rhine plains (France, Germany and Switzerland). Both studies also compare the outputs of the methods and highlight the low degree of convergence between them. The approach proposed in the last study is the most elaborate among the four case studies. It could be used to develop a generic evaluation and comparison methodology. The review of those four case studies shows the need to formalise the methodology underlying any comparison work of indicators or evaluation methods.

Sorting cropping systems on the basis of their impact on groundwater quality

Abstract In this paper is described the implementation of a multi-criteria analysis in order to answer a question of researchers of the Institut National de la Recherche Agronomique (INRA) who assess the impact of agricultural practices on the environmental components. They were particularly interested in differentiating cropping systems (CSs) as a function of their impact on groundwater quality. In order to give effect to this differentiation, members of the Laboratoire d’Analyse et de Modelisation de Systemes pour l’Aide a la Decision (LAMSADE) proposed a way of sorting CSs using the ELECTRE TRI method. Four categories of impact were defined and three families of criteria were built up. The main debate was about the nature of criteria: if basic data are used, the number of the criteria is high; if aggregated data are used, exchanges of information are tedious. In spite of difficulties, the study has been of important value for the agronomic researchers. Firstly, it helps them to work with decision-makers, such as the Water Agency: it allows farmers to be given concrete examples of CSs which preserve groundwater quality. Secondly, the multi-criteria methodology used seems to fit their researches: they are indeed now using the same approach to differentiate CSs on the basis of their impact on wild fauna or landscape quality.

Assessment of the contribution of land use pattern and intensity to landscape quality: use of a landscape indicator.

Abstract The objective of this research work is the evaluation of the impact of landuse pattern and intensity on landscape by means of an indicator. The method used to calculate a ‘landscape indicator’ ( I land ) allows to take into account the objective as well as the subjective approach of landscape. I land corresponds to the degree of agreement between landscape supply by farmers and landscape demand by the social groups. The supply and the demand are evaluated through four criteria: ‘diversity’, ‘upkeep’, ‘openness’ and ‘heritage’. The landscape supply is calculated from data of landscape objects (punctual, linear and spatial) for each criterion recorded at the field level. The values of the four criteria for the landscape demand are allocated by the user(s) of the indicator (decision makers, regional council, social groups…) into five classes (0–4). The value of the landscape indicator is the least favourable difference between supply and demand for the four criteria. An example of calculation of the ‘landscape indicator’ for an arable farm is given. The collection of data needs 2 h with the farmer and 2 h for a survey of the farm land.

Alkaloids in Meadow Saffron, Colchicum autumnale L.

ABSTRACT The alkaloids colchicine and colchicoside contained in meadow saffron (Colchicum autumnale L.) seeds are used, respectively, in drugs to treat gout and relax muscles. A two year study at two sites demonstrated the concentration and yields of these two seed constituents involves the transformation of colchicine into colchicoside during plant growth. The optimum harvest date for meadow saffron could be selected for the highest total alkaloid or colchicoside content and for the highest dry matter, and alkaloid yields. Differences in alkaloid yields and concentrations in different plant parts strongly suggest that alkaloids can be translocated in the plant.

Use of mean square error of prediction for crop model evaluation : the case of leaf area estimation

Abstract Several models for leaf area (LA) estimation in foxtail millet ( Setaria italica (L.) P. Beauv.) are proposed. The models were evaluated by using the mean squared error of prediction (MSEP), estimated by the cross-validation method. With this criterion, the predictive value of a model, and comparison between alternative models, was investigated. A coefficient of 0.67, by which measured dimensions are multiplied, can be used for the estimation of the leaf area of all the cultivars of Setaria italica . But this method is time consuming. It can only be used when many cultivars and few plants per cultivar are measured. Where a large number of plants from few genotypes are being studied, a more rapid method, taking into account the blade lengths of odd numbered leaves or even numbered leaves only, also provides an accurate estimate of leaf area. However in this case, a leaf area coefficient must be developed for each genotype (main culms and tillers).