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This study uses PCR-derived marker systems to investigate the extent and distribution of genetic variability of 53 Garnacha accessions coming from Italy, France and

Our aim was to explore the adaptation choices to climate change in the grapevine regions of Spain from two points of view. First, what are the main reasons for concern? Second, how large is the adaptation effort in each region? We address the first question by measuring sensitivity to climate change with Huglin, Cold Night and Dryness Indices over the entire territory, providing information on the adaptation type (e.g. varieties, zoning, water allocation). We then estimate probabilistic projections across scenario, zone and sensitivity indices in the 56 Protected Designation of Origin areas to inform on the magnitude of the adaptation effort. Second, we propose an adaptation effort measure that is framed according to the local environmental context. Results suggest that most areas urgently need an adaptation plan due to the deterioration of production and quality indices as a result of climate change. Potential opportunities in many climate regions might be limited by current policy. The production objectives of quality and quantity trade-offs will probably need to be revised by analysing the sustainability of grapevine production.

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Abstract. We follow a user-based approach to examine how information supports operational drought management decisions in the Ebro basin and how these can benefit from additional information such as from remote sensing data. First we consulted decision-makers at basin, irrigation district and farmer scale to investigate the drought-related decisions they make and the information they use to support their decisions. This allowed us to identify the courses of action available to the farmers and water managers, and to analyse their choices as a function of the information they have available to them. Based on the findings of the consultation, a decision model representing the interrelated decisions of the irrigation association and the farmers was built. The purpose of the model is to quantify the effect of additional information on the decisions made. The modelled decisions, which consider the allocation of water, are determined by the expected availability of water during the irrigation season. This is currently informed primarily by observed reservoir level data. The decision model was then extended to include additional information on snow cover from remote sensing. The additional information was found to contribute to better decisions in the simulation and ultimately higher benefits for the farmers. However, the ratio between the cost of planting and the market value of the crop proved to be a critical aspect in determining the best course of action to be taken and the value of the (additional) information. Risk-averse farmers were found to benefit least from the additional information, while less risk-averse farmers stand to benefit most as the additional information helps them take better informed decisions when weighing their options.