Assessing the role of agri-environmental measures to enhance the environment in the Veneto Region, Italy, with a model-based approach

Many efforts have been made in Europe to improve the environmental quality of agro-ecosystems. Since the 2000s, agri-environmental measures (AEMs) have been financed and implemented in EU countries, although their beneficial effects are still questioned due to poorly targeted environmental issues and a lack of site-specific payments. Indeed, estimates of AEM outcomes at the territorial level require considerable efforts to consider simultaneously multiple environmental objectives with multiple targets. As a result, a DAYCENT model-GIS platform was developed that integrates multiple types of pedo-climatic and land management information. The aim was to provide a decision support system for spatially evaluating and selecting the best AEMs in terms of soil, water and air quality, when compared with a standard scenario without any adopted measure. Our modelled results showed that in the Veneto Region, north-eastern Italy, the AEMs applied from 2007 to 2013 improved the environmental value of the agro-ecosystems, especially in terms of soil and water quality. Continuous soil cover, reduction of soil disturbance through grasslands, conservation agriculture and cover crops were the best simulated strategies to increase soil organic matter content (+25%) and reduce nitrogen leaching (⿿90%). These strategies were also able to sharply reduce soil water erosion (⿿86%) and as a consequence P loss, in particular in the steep hilly and mountain areas, although their application to arable lands in those landscapes is still rare. In contrast, care should be taken in the long-term regarding an increase in P leaching, since predictions up to +0.15 kg ha⿿1 y⿿1 are reached compared to the standard scenario. Finally, greenhouse gas (GHG) emissions (N2O and CH4) were reduced mainly due to increased fertilisation efficiency. The proposed method can be a flexible decision support tool for a result-oriented and scientifically-based evaluation of AEMs that may help policy makers to evaluate the most effective measures for increasing the environmental value of agro-ecosystems.