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International audience; Although Sierra Leone aims to improve the livelihoods of its rice-farming households, the effect of specific policy changes on diverse households remains an open question. This study presents a household model that simulates strategies of production and consumption for rice-farming households in Sierra Leone. It accounts for non-separability between household production and consumption decisions, accounts for resource constraints, and uses a risk-adjusted measure of welfare. The model simulated the effects of three policy scenarios seeking to improve food consumption and calculated production, consumption and socio-economic indicators. The scenarios included: 1) subsidizing rice seed costs, 2) subsidizing palm oil production costs, and 3) subsidizing the conversion of lowlands into land suitable for rice production. The model was applied to four representative rice-farming households in northern Sierra Leone that differed in their land resources and rice consumption. The four household types included: 1) Upland_intensive, 2) Lowland_intensive, 3) Upland_extensive, and 4) Lowland_extensive. Results show that extensive lowland-based households had the lowest rice consumption (54 kg capita−1 year-1) and caloric intake (843 Kcal capita−1 day−1) in comparison with the other household types. Subsidizing rice seed costs in the lowlands, compared to the baseline scenario, improved rice consumption across the households by 15–34%, and farm income by 12–57%. Regardless of the scenario, differences in caloric intake, in comparison to the baseline scenario, were less than differences in rice consumption, thus indicating substitution effects between the different foods (vegetables, cereals, oils, and sweet potatoes). A maximum caloric increase of 16% was achieved by subsidizing palm oil production costs. Subsidizing lowland conversion for rice cultivation improved rice consumption mainly through the subsidy’s positive effect on rice production, which in turn effected self-consumption. Depending on the scenario, the increase in household income was mainly because of an increase in upland rice area, an increase in rice sowing rates, an increase in cash, or a specialization in lowland rice combined with planting a cash crop.

International audience; This study considers a quantitative approach for assessing the performance of Tunisian farming systems to face climate change. It is based on the resilience concept and the calculation, with a modelling chain, of three indicators: land stock, labour stock, and income flux. Two system states, ‘‘base’’ and ‘‘climate change’’, and a time horizon of 2010–2025, are developed and compared for representative farming systems. The study shows that 55% of the farming systems were identified as being resilient to climate change. They are diversified and mostly grow cereals, vegetables, and forage crops combined with livestock, increasing their capability to mitigate climate change by reorganizing crop activities. 35% of the farms identified as being non-resilient are dominated by orchards, or cereals and orchards. They showed an important drop in farm income (-45%), mainly due to their inability to adapt their cropping systems to water stress and soil salinity. Finally, only 10% were identified as being poorly resilient farming systems. Those farms have mainly intensified cereal cropping systems based on a strategy of purchasing land to increase the surface area of profitable activities (forage and livestock). Overall, the methodology can be adapted for other dry land areas in the Mediterranean region and help experts and policy-makers to propose and test strategies for adapting to climate change.

Le present travail applique a la Tunisie, part d'un double constat relatif, d'une part, a la gravite de l'erosion et, d'autre part, a l'importance des depenses publiques en matiere de conservation des eaux et du sol visant a attenuer ce phenomene. La contradiction de ce double constat et la divergence des resultats obtenus par l'adoption de ces amenagements de conservation constituent le determinant principal pour la remise en cause de l'efficacite de cette intervention publique. L'evaluation quantitative de l'impact de ces amenagements sur le rendement, le systeme de production et par la sur la rentabilite des capitaux investis ainsi que sur l'erosion constituent, donc, l'objectif primordial de ce travail. L'approche bio-economique qui couple l'emploi d'un simulateur biophysique a un modele d'optimisation economique est avancee comme une meilleure methode pour juger cette efficacite.

Une« fonction de production d'ingenieur », qui fait appel a la fois a un simulateur de croissance de plantes et a de la programmation lineaire sous contrainte de risque, est utilisee pour analyser les consequences de la reforme « Me Sharry » sur les revenus et sur l'environnement, dans une grande variete de types d'exploitations de « grandes cultures » (dont certaines avec elevage), a travers toute la France. Le modele est dynamique et recursif au sens de Day. Malgre la grande diversite des situations, la reforme, dans l'ensemble, semble devoir atteindre les objectifs qui etaient les siens, avec une tendance a l'extensification et au reequilibrage entre les regions. Cependant, l'incertitude majeure, susceptible de remettre en cause ces resultats, reste la perception des risques encourus par les agriculteurs.

Groundwater in Spain, as in other arid and semiarid countries worldwide, has been widely used in the expansion of irrigated agriculture. In the Spanish Mancha Occidental aquifer, the excessive, and sometimes illegal, water abstraction for irrigation has promoted outstanding socioeconomic development in the area, but it has also resulted in exploitation of the aquifer and degradation of valuable wetlands. Water policies implemented in the region have not yet managed to restore the aquifer and face strong social opposition. This paper uses a multi-scale modeling approach to explore the environmental and socio-economic impacts of alternative water conservation measures at the farm and basin levels. It also analyzes their comparative cost-effectiveness to help policy makers identify the least costly policy option for achieving the goal of the Mancha Occidental aquifer's sustainability. To conduct this analysis, a Mathematical Programming Model has been developed to simulate: the closing-up and taxed-legalization of unlicensed wells, uniform volumetric and block-rate water prices, water quotas, and water markets. Aggregate results show that net social costs are not substantially different across policy option, so none of the considered policy options will be clearly more cost-effective than the others. However, there are significant differences between private and public costs (at the farm and sub-basin levels), which will be critical for determining the application in practice of these policies. Results show that controlling illegal water mining (through the legalization of unlicensed wells) is necessary, but is not sufficient to recover the aquifer. Rather, effective water management in this area will require the implementation of other water management policies as well. Among them, uniform volumetric and block-rate water pricing policies will entail the lowest net social cost, but will produce important income losses in the smallest and most water-intensive farms, which might put at risk the viability of these farms and the social acceptance of the policies. Further investigations on social costs, policy enforcement capacity and public participation in water management are highly recommended.

International audience; The bio-economic modeling approach presented in this book is a result of two distinct developments: by one side, the improvement of bio-physical simulation models applied to agricultural systems and by the other, the evolution of agricultural policies demanding a kind of assessment that conventional economic models are not able to provide. Some economists began to realize that biophysical models could be considered as detailed engineering production functions, allowing to represent in a consistent manner the joint products of agricultural activities. The perspectives that this vision provides allow dealing with environmental and natural resources issues with an economic perspective in an efficient manner. Representing environmental impacts of agricultural activities measured in physical units allows performing cost-efficiency calculations of alternative policies, potentially able to attain specified policy targets. This capability permitted in recent years the development of applied research related with institutional demands from national and international public institutions. But this approach requires a multidisciplinary approach, with positive and negative effects. The positive one is, both for economists and biophysical scientists, to enlarge their vision of the world. The negative effects are the greater difficulty to get recognized in their specific discipline, the obstacles to obtain the necessary information for properly use these models, and the longer time to perform the research activity. The “productivity” for producing papers is lower for economists applying this approach compared with economists applying econometric methods, using available published data. In spite of these negative effects, as the demands from the real world for the assessment these models are able to provide is increasing, it is quite possible that there is a future for bio-economic models applied to agricultural systems. The challenges of Climate Change, the increase care for the preservation of natural resources and the environment will require further developments of this kind of approach.

Chapitre 5; The aim of this chapter is to present a bio-economic modelling framework established to provide insight into the complex nature of agricultural systems and to assess the impacts of agricultural and environmental policies and technological innovations. This framework consists of a Farm System Simulator (FSSIM) using mathematical programming that can be linked to a cropping system model to estimate at field level the engineering production and environmental functions. FSSIM includes a module for agricultural management (FSSIM-AM) and a mathematical programming model (FSSIM-MP). FSSIM-AM aims to define current and alternative activities and to quantify their input output coefficients (both yields and environmental effects) using a cropping system model, such as APES (Agricultural Production and Externalities Simulator) and other sources (expert knowledge, surveys, etc.). FSSIM-MP seeks to describe the behaviour of the farmer given a set of biophysical, socio-economic and policy constraints and to predict its reactions under new technologies, policy and market changes. The communication between these different tools and models is based on explicit definitions of spatial scales and software for model integration. The bio-economic modelling framework was designed to be sufficiently generic and flexible in order to be applied for all relevant farming systems across the European Union, easily transferable between different geographic locations, and reusable for different applications.; L’objectif de ce chapitre est de présenter un cadre de modélisation bioéconomique pour offrir un aperçu de la nature complexe des systèmes agricoles et pour évaluer les impacts des politiques agricoles et environnementales et des innovations technologiques. Ce cadre consiste en un modèle économique de ferme (FSSIM) basé sur la programmation mathématique qui peut être relié à un modèle biophysique pour estimer, au niveau parcellaire, les fonctions de production et d’externalité. FSSIM comprend un module de gestion des données (FSSIM-AM) et un modèle de programmation mathématique (FSSIM-MP). FSSIM-AM a pour but de définir les activités actuelles et alternatives et de quantifier leurs coefficients inputs-outputs (à la fois les rendements et les effets sur l'environnement) en utilisant un modèle biophysique, comme APES (Agricultural Production and Externalities Simulator), ainsi que d'autres sources (expertise, enquêtes, etc.). FSSIM-MP cherche à décrire le comportement de l'agriculteur en tenant compte d’un ensemble de contraintes biophysiques, socio-économiques et politiques et de prévoir ses réactions face à des changements de politiques et du marché ainsi que de nouvelles technologies. La communication entre ces différents outils et modèles est basée sur une définition explicite des échelles spatiales et des logiciels d'intégration. Le cadre de modélisation bioéconomique a été conçu suffisamment générique et flexible pour être appliqué à tous les systèmes de production en Europe, facilement transférables entre les différentes implantations géographiques, et réutilisables pour différentes applications.