The growing concern about side-effects of policies focusing on economic growth or even technological innovations, as well as agriculture intensification leads more and more stakeholders to pay attention to the questions of monitoring and evaluation of agricultural practices. This step of evaluation is now essential in policy decision, in research and design of innovative solutions, in NGOs' development projects, as well as in improvement process in ISO certification. The aim of this article is to review steps in the evaluation of sustainability in agriculture, starting in a first section with the necessity to develop a conceptual indicator framework to precise evaluators' own vision of sustainability. In a second section, we address the necessity to answer preliminary questions that will guide the selection of a set of indicators or an assessment method. In a third section, after discussing the way to categorize indicators, we provide an overview of available indicators for two sustainability themes of the environmental dimension regarding respectively nitrogen management and biodiversity. In a fourth section, we highlight the diversity of evaluation methods of sustainability through six examples in France. Finally we conclude the article with a general discussion on questions that remain to address.
National audience ; Among agricultural activities, animal husbandry is one of the main sources of atmospheric pollutant emissions : 15% of the greenhouse gases and 80% of the ammonia emissions come from this sector.Today, at the international level, a major political objective is to decrease the emissions of greenhouse gases (Kyoto Conference) and also of ammonia (Göteborg Conference). It seems therefore necessary that the farmers become aware of the impact of their practices, especially of farmyard manure management, on air quality. The development of assessment tools would be useful to farmers. The aim of this study is to set up an assessment method for the impacts of farmers' practices on air quality. This method is based on three indicators, which assess the emissions of ammonia (NH3), methane (CH4), and nitrous oxide (N20). These gases are emitted during intestinal fermentation of livestock, housing, storing of farmyard manure (and composting), grazing, and manure spreading. The ammonia emission indicator (INH3) is presented in detail. It is calculated by assessing the impact of each practice on gas emission, and then combining the results to assess the global risk at the farm level. The final score lies between 0 (high risk) and 10 (lowest risk), thus assessing the emission of NH3 from the totality of practices concerning farmyard manure management. The methane emission indicator (ICH4) and the nitrous oxide indicator (IN2O) are calculated in the same way. Lastly, we show that the calculation of these indicators on two dairy farms makes it possible not only to diagnose their impacts on air quality, but also to highlight which of the polluting practices can be improved.
National audience ; Among agricultural activities, animal husbandry is one of the main sources of atmospheric pollutant emissions : 15% of the greenhouse gases and 80% of the ammonia emissions come from this sector.Today, at the international level, a major political objective is to decrease the emissions of greenhouse gases (Kyoto Conference) and also of ammonia (Göteborg Conference). It seems therefore necessary that the farmers become aware of the impact of their practices, especially of farmyard manure management, on air quality. The development of assessment tools would be useful to farmers. The aim of this study is to set up an assessment method for the impacts of farmers' practices on air quality. This method is based on three indicators, which assess the emissions of ammonia (NH3), methane (CH4), and nitrous oxide (N20). These gases are emitted during intestinal fermentation of livestock, housing, storing of farmyard manure (and composting), grazing, and manure spreading. The ammonia emission indicator (INH3) is presented in detail. It is calculated by assessing the impact of each practice on gas emission, and then combining the results to assess the global risk at the farm level. The final score lies between 0 (high risk) and 10 (lowest risk), thus assessing the emission of NH3 from the totality of practices concerning farmyard manure management. The methane emission indicator (ICH4) and the nitrous oxide indicator (IN2O) are calculated in the same way. Lastly, we show that the calculation of these indicators on two dairy farms makes it possible not only to diagnose their impacts on air quality, but also to highlight which of the polluting practices can be improved.
On estime que les productions animales, à travers les engrais de ferme, représentent 15% des émissions de gaz à effet de serre et 80% des émissions d'ammoniac. La réduction de ces émissions de gaz est devenue un objectif politique majeur. Pour que les agriculteurs prennent conscience de l'impact de leurs pratiques, notamment de gestion des engrais de ferme, il est indispensable de disposer d'outils d'évaluation. La méthode d'évaluation de l'impact des engrais de ferme sur la qualité de l'air présentée méthode repose sur la construction de 3 indicateurs évaluant les émissions d'ammoniac (NH3), de méthane (CH4) et de protoxyde d'azote (N2O). La démarche d'établissement de l'indicateur INH3 est présentée en détail : 1) calcul des émissions de NH3 dues aux déjections, 2) les quantités obtenues sont agrégées en une valeur globale à l'échelle de l'exploitation d'élevage, 3) cette valeur globale est transformée en une valeur entre 0 et 10 (risque nul). L'application de cette méthode à 2 élevages laitiers de montagne permet d'effectuer un diagnostic environnemental d'impact sur la qualité de l'air et de mettre en évidence les pratiques polluantes qui peuvent être améliorées ; Among agricultural activities, animal husbandry is one of the main sources of atmospheric pollutant emissions : 15% of the greenhouse gases and 80% of the ammonia emissions come from this sector.Today, at the international level, a major political objective is to decrease the emissions of greenhouse gases (Kyoto Conference) and also of ammonia (Göteborg Conference). It seems therefore necessary that the farmers become aware of the impact of their practices, especially of farmyard manure management, on air quality. The development of assessment tools would be useful to farmers. The aim of this study is to set up an assessment method for the impacts of farmers' practices on air quality. This method is based on three indicators, which assess the emissions of ammonia (NH3), methane (CH4), and nitrous oxide (N20). These gases are emitted during intestinal fermentation of livestock, housing, storing of farmyard manure (and composting), grazing, and manure spreading. The ammonia emission indicator (INH3) is presented in detail. It is calculated by assessing the impact of each practice on gas emission, and then combining the results to assess the global risk at the farm level. The final score lies between 0 (high risk) and 10 (lowest risk), thus assessing the emission of NH3 from the totality of practices concerning farmyard manure management. The methane emission indicator (ICH4) and the nitrous oxide indicator (IN2O) are calculated in the same way. Lastly, we show that the calculation of these indicators on two dairy farms makes it possible not only to diagnose their impacts on air quality, but also to highlight which of the polluting practices can be improved.
International audience ; Introduction During the last decades food production has increased thanks to intensive use of non-renewable and agrochemical inputs and simplification of landscapes (Therond et al., 2017). Yet, the present inefficient use of pesticides and fertilizers and the increasing prevalence of intensive and simplified cropping systems are leading to negative impacts on biodiversity and its associated ecosystems services (Rusch et al., 2016). Actually, these are the same systems that may push agriculture over a sustainability tipping point (Ray et al., 2012). Thus, it is a priority to develop innovative forms of agriculture that stabilizes both yields and farmers' profitability while developing ecosystem services (Therond et al., 2017). Cropping diversification is regarded as a key path for a strong sustainable development of multifunctional agroecosystems (Ponisio and Kremen, 2016). However, little is still known on the potential synergic and trade-off effects brought by the implementation of different crop diversification strategies at different spatial and temporal scales. Integrated Assessment and Modelling (IAM), a multicriteria and multilevel assessment based on modelling platforms and involvement of stakeholders may help to deal with this challenge. As part of the EU H2020 DiverIMPACTS project, this work uses MAELIA, an IAM platform of agricultural landscape (Therond et al., 2014), to perform on three contrasted European case studies (CSs), an assessment of the benefits and drawbacks brought by diversification from field and farm to landscape and agro-chain levels. Materials and Methods MAELIA is a high-resolution multi-agent platform, that allows to simulate at fine spatial resolution the daily dynamic and interactions between human activities (e.g. farming practices), ecological processes (e.g. crop growth), and governance systems (e.g. agricultural regulations). It is applied in three very different CSs used as pilot test for the implementation of different diversified agricultural strategies. A first CS is located in Germany, is composed by 25 farmers with a common goal of improving water quality in catchment basin trough new valuable and sustainable farming strategies based on diversified rotations, as well as to increase the cooperation and trade between local farmers. A second CS in Romany is composed by four very large farms (800 to 14000 ha each) in which the objective is to assess in an ex-ante way the effects of including in the rotation legumes and other winter crops on soil quality, yield stability and economic returns. The third CS, in France, corresponds to ten farmers where the challenge is to develop exchanges between cereal and livestock farmers, in order to offer diversification opportunities (e.g. forage production), while dealing with water quality and availability. The IAM process was structured in three main participatory steps. Firstly, data and knowledge were collected and integrated to develop in MAELIA a concrete model of the current functioning of each CS. Second, a participatory design process led by stakeholders was conducted to specify changes in the cropping systems. Thirdly, the integrated assessment of these scenarios was carried out with MAELIA, and results were analysed and discussed with stakeholders. Results A large set of pre-defined indicators (8 for the economic pillar, 19 for environmental sustainability, 2 for social dimension; see Canali et al. 2019) and stakeholder-oriented indicators (e.g. biological regulations issues) will be calculated to assess the direct and indirect effects of diversification over time (intra and inter year variabilities, rotation and long term) and space (field, cropping system, farm and territory). Based on outputs of scenarios simulations, this conference will provide opportunity to present and discuss the first key results of the IAM procedure. Discussion and Conclusions To support policy makers, it is necessary to define policies and strategies at the relevant levels at which impacts (e.g. biodiversity and economic return) are managed, such as farm or landscape. These impacts are also intrinsically linked with local biophysical processes, defined at very fine scales, such as soil-plant level. Here, we propose an IAM approach that allows simulating and assessing the main aspects of cropping systems, including social, environmental and economical, steering a transition to more sustainable food. Namely, the discussion is focused on the effects of cropping system diversification on a large range of generic and stakeholders oriented indicators. We will focus above all on the viability of agricultural holdings and the robustness/resilience to technical, climate and socioeconomic changes; stability of production and economic returns; soil (e.g. quality, erosion); GHG balance and non-renewable resources; water quality and availability; agricultural environmental impacts (e.g. nitrogen leaching); and, farmers' quality of life (e.g. workload).
Suite au Grenelle de l'Environnement et à l'évolution des politiques publiques, une réduction sensible de l'usage des produits phytosanitaires est attendue. Cette réduction passe non seulement par une meilleure efficience des intrants et par la substitution de techniques de lutte non chimique aux méthodes habituellement utilisées, mais aussi par des changements de systèmes de culture et l'exploration de stratégies ou d'innovations qui soient en réelle rupture avec les pratiques actuelles. Par ailleurs, il est nécessaire d'évaluer l'ensemble des impacts sociaux, économiques et environnementaux de tels changements car il peut y avoir contradiction entre ces différents aspects de la durabilité. Comment concevoir des innovations en réelle rupture et disposer néanmoins d'une évaluation multicritère de leurs performances la plus solide et la plus large possible ? L'outil d'évaluation ex ante multicritère DEXiPM a été développé à cette fin et permet de (i) pouvoir comparer, le plus en amont possible, les performances de systèmes innovants avec celles des systèmes actuels, (ii) sélectionner a priori les systèmes les plus prometteurs qui pourront alors être testés au champ (en station et/ou en fermes) et (iii) identifier les conditions facilitant l'adoption de ces systèmes innovants. L'aptitude à l'analyse et à la comparaison de ces systèmes innovants par l'utilisation de DEXiPM est précieuse pour l'estimation de la durabilité globale des systèmes, mais surtout par la mise en lumière de l'ensemble des critères analysés. Ainsi les améliorations proposées peuvent être discutées et testées sur la base des connaissances disponibles. Parce que le contexte (politique, social, économique…) est pris en compte dans le modèle, DEXiPM peut aussi aider à concevoir des systèmes innovants qui ne sont pas nécessairement viables économiquement, écologiquement performants ou socialement acceptables aujourd'hui mais qui pourraient l'être sous certaines conditions, comme des politiques publiques appropriées ou des stratégies de filière adaptées ; Pesticide use reduction in arable cropping systems has become a priority of public policies. To meet the objectives of reducing pesticide use by 50%, it is not only relevant to improve the efficiency of crop protection and to substitute non-chemical solution to pesticide but it is also necessary to consider redesigning cropping systems and exploring really innovative breakthroughs. It is equally important to assess all the economic, social and environmental impacts, be them direct or indirect, of proposed innovative systems. How can we design really innovative solutions and be able to assess them as completely as possible? DEXiPM is an ex ante multi-criteria assessment tool which make it possible (i) to compare, as early as possible, innovative systems with conventional systems, (ii) to select those systems which are the most promising ones and which would be further tested in-field, and (iii) to identify the conditions which could make their adoption easier. The ability to analyse and compare innovative systems using DEXiPM should prove valuable not only in estimating the overall sustainability of the systems but, more importantly, in shedding light on the value of all the criteria under analysis. Thus further improvements can be discussed and tested, resulting in better proposals for innovative systems. And because the context (political, social, economical etc) is taken into account in the model, DEXiPM can also assess those innovative systems which may not be feasible or efficient today, but which might be sustainable 'tomorrow' in a different context
For a selection of farms in the Farm Accountancy Data Network (FADN) of the European Union, the economic, environmental and social performance of farms is measured using farm level sustainability indicators based on FADN data and additiona data collected through the FLINT project. For each type of farming (TF), that is to say each main production specialisation, farms are then clustered on the basis of their economic performance and following this their environmental and social performances are assessed. The analysis addresses the question of whether top performing farms from an economic perspective can also be high-performing farms from an environmental and social perspective. The characteristics of the top performers are also investigated.Results suggest that economic sustainability and environmental sustainability are positively correlated for some farm types but not others, and this depends on the type of environmental indicator. By contrast, there are no tradeoffs between economic performance and (private) social performance. From a methodological perspective, the choice of the indicator, in particular the choice of the functional unit is crucial and may influence conclusions. In addition, some indicators never or almost never discriminate between clusters.
For a selection of farms in the Farm Accountancy Data Network (FADN) of the European Union, the economic, environmental and social performance of farms is measured using farm level sustainability indicators based on FADN data and additiona data collected through the FLINT project. For each type of farming (TF), that is to say each main production specialisation, farms are then clustered on the basis of their economic performance and following this their environmental and social performances are assessed. The analysis addresses the question of whether top performing farms from an economic perspective can also be high-performing farms from an environmental and social perspective. The characteristics of the top performers are also investigated.Results suggest that economic sustainability and environmental sustainability are positively correlated for some farm types but not others, and this depends on the type of environmental indicator. By contrast, there are no tradeoffs between economic performance and (private) social performance. From a methodological perspective, the choice of the indicator, in particular the choice of the functional unit is crucial and may influence conclusions. In addition, some indicators never or almost never discriminate between clusters.
Textes issus des travaux du programme Casdar "Innovation et Partenariat" de 2007 et présentés lors d'un colloque le 4 décembre 2012, sous l'égide du GIS Relance Agronomique ; Taking increasing account of the environmental dimension in policies of orientation of agricultural practices, in research and development in agricultural science has led since 15 years to many works on agri-environmental assessment, yielding, in many cases, in the design of indicators or even computer prototypes. These tools make it possible to estimate the impacts of agricultural practices with regard to the different dimensions of sustainable development and the environmental themes and, for some of them, to propose action plans at different scales of time and space. To face this diversity, a group of actors of research and agricultural development, designers or users of assessment tools, mobilized through the Plage 1 project to characterize the existing tools and the evaluation situations, to explain the variety of tools available from all stakeholders in the agricultural sector in order to facilitate their use, but also to pool the efforts of computer maintenance and tuning tools and database references. To achieve these various goals, project partners imagined to design a WEB platform and a platform of skills. Plage 1 project led to the development of the specifications of the WEB platform and the establishment of an open network of agricultural stakeholders in the agri-environmental assessment. ; La prise en compte croissante de la dimension environnementale dans les politiques d'orientation agricole, dans les travaux de recherche et de développement en agronomie a conduit depuis une quinzaine d'années à une multiplication de travaux sur l'évaluation agri-environnementale, aboutissant, dans de nombreux cas, à la conception d'indicateurs voire de prototypes informatiques. Ces outils permettent d'estimer les impacts des pratiques agricoles au regard des différentes dimensions du développement durable et des thématiques ...
