This paper compares the performance of econometric land use models based on three proxies for agricultural land rent: farmers' revenues, land prices, and shadow land prices derived from a mathematical programming model. We consider different land use classes (agriculture, pasture, forest, urban, and other), different determinants (economic, physical, and demographic) of land use shares, and different spatial econometric specifications. It is found that the inclusion of spatial components significantly improves the quality of predictions. In terms of economic interpretation, the shadow land prices provide the most stable and intuitive results.

Interaction between mitigation and adaptation is a key question for the design of climate policies. In this paper, we study how land use adaptation to climate change impacts land use competition in the agriculture, forest and other land use (AFOLU) sector and how a mitigation policy in agriculture might affect this competition. We use for this purpose two sector-specific bio-economic models of agriculture and forest combined with an econometric land use shares model to simulate the impacts of two climate change scenarios (A2 and B1, 2100 horizon), and a greenhouse gas emissions from agriculture policy consisting of a tax of between 0 and 200 e/tCO 2 equivalent. Our results show that both climate change scenarios lead to an increase in the area devoted to agriculture at the expense of forest which could have a negative impact on reducing greenhouse gas emissions responsible for climate change. The mitigation policy would curtail agricultural expansion, and thus could counteract the effects of land use adaptation to climate change.In other words, accounting for land use competition results in a reduction of the abatement costs of the mitigation policy in the agricultural sector.

Pressures on freshwater ecosystems are mainly human-induced and driven by land use and climate change. We develop an empirical framework to estimate the impacts of land use (agriculture, forest, pasture, urban) and climate change on freshwater biodiversity, measured by a fish-based index, in France. Our estimation results reveal that rivers in areas with more intensive agriculture and steep pasture are associated to lower freshwater biodiversity compared to forest areas. Our simulations show that climate change will exacerbate these negative impacts through land-use adaptation. We discuss how two command-and-control policies could help improving freshwater biodiversity and cope with the adverse effects of land use and climate change.

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Les pressions actuelles exercées sur la ressource en eau et la menace potentielle du changement climatique devraient fortement influencer sa disponibilité et, de façon corrélative, la demande d'irrigation. Nous développons dans cet article une approche centrée sur l'eau comme facteur de production agricole et sur la demande française en eau d'irrigation. La méthode repose sur le couplage du modèle d'offre agricole AROPAj avec le modèle de culture STICS ainsi que sur l'obtention de cartes à haute résolution. Nous proposons d'illustrer la capacité du modèle à enrichir l'analyse spatiale de la demande d'irrigation et des disparités régionales. Focalisée sur les principales de cultures de vente, l'étude montre l'importance des cultures très consommatrices d'eau d'irrigation dans les zones fortement irriguées à l'ouest et au sud-est de la France. Elle montre également dans quelle mesure le modèle pourra traiter de l'importance que pourrait prendre l'irrigation dans d'autres régions dans un contexte de changement climatique prononcé.ABSTRACT. Present pressures on the water resource and the potential threat of climate change should strongly impact water availability and, consequently, irrigation demand. In order to help public decision-makers, we develop an approach where water is modeled as an input, and assess water demand in France. The method combines the economic model AROPAj, the STICS crop model, and the generation of high-resolution maps. As an illustration of the possible outputs of our modeling approach, we propose an application based on the spatial analysis of irrigation demand and regional disparities. This study reveals highly irrigated areas in the west and south-east of France, explained by the establishment of water-intensive crops like maize and sunflower. More importantly, it highlights the model capacity to enlighten the complex linkage between climate change and the demand for irrigation water even in regions where crops are not strongly water-intensive.

The spatial differentiation of input-based pollution fees should in theory decrease compliance costs in the case of nitrate pollution of water bodies from agriculture because both the damage and the compliance costs vary over space. However, the empirical evidence in the literature does not agree on the extent of the potential savings from differentiation. We address this issue in the case of France, using a mathematical programming model of agricultural supply (AROPAj). The modeling approach used accounts for the spatial diversity of nitrate pollution and the heterogeneity of farming systems. Our results reveal the efficiency gains from differentiating pollution fees among polluters and water bodies. For instance, firm-specific and water body-specific taxes represent respectively 5.8% and 32.5% of farmers' gross margin in terms of compliance costs, whereas a uniform policy at the river-basin district or national level leads to major economic losses and abandonment of the agricultural activity. These results stem from the lower tax rates faced by farmers in less polluted areas, for scenarios based on spatial differentiation. Our estimates suggest that realistic regulation via input-based pollution fees should be differentiated in order to significantly reduce the financial burden on farmers of conforming to predefined pollution levels. Some potential adverse effects related to input-based taxation and land use change call for additional fine-scale nitrogen pollution regulation (e.g. limitations on crop switching).

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Mineral nitrogen (N) application in agriculture has significantly increased food production over the past century. However, the intensive use of N-fertilizers also impacts negatively the environment, notably through greenhouse gas emissions and biodiversity loss and remains a major challenge for policymakers. In this paper, we explore the effects of a public policy aiming at halving agricultural mineral nitrogen use across the European Union (EU). We investigate the impacts on food security, climate mitigation, and biodiversity conservation and we analyse the potential trade-offs and synergies between them. Despite the uncertainties associated with monetary valuation and the choice of modeling approach, our results show that climate-and-biodiversity-related benefits of halving N use in EU agriculture more than offset the decrease in agricultural benefits.