7 resultados para Q15 - Land Ownership and Tenure

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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This study investigates the changes in soil fertility due to the different aggregate breakdown mechanisms and it analyses their relationships in different soil-plant systems, using physical aggregates behavior and organic matter (OM) changes as indicators. Three case studies were investigated: i) an organic agricultural soil, where a combined method, aimed to couple aggregate stability to nutrients loss, were tested; ii) a soil biosequence, where OM chemical characterisation and fractionation of aggregates on the basis of their physical behaviour were coupled and iii) a soils sequence in different phytoclimatic conditions, where isotopic C signature of separated aggregates was analysed. In agricultural soils the proposed combined method allows to identify that the severity of aggregate breakdown affected the quantity of nutrients lost more than nutrients availability, and that P, K and Mg were the most susceptible elements to water abrasion, while C and N were mainly susceptible to wetting. In the studied Chestnut-Douglas fir biosequence, OM chemical properties affected the relative importance of OM direct and indirect mechanisms (i.e., organic and organic-metallic cements, respectively) involved in aggregate stability and nutrient losses: under Douglas fir, high presence of carboxylate groups enhanced OM-metal interactions and stabilised aggregates; whereas under Chestnut, OM directly acted and fresh, more C-rich OM was preserved. OM direct mechanism seemed to be more efficient in C preservation in aggregates. The 13C natural abundance approach showed that, according to phytoclimatic conditions, stable macroaggregates can form both around partially decomposed OM and by organic-mineral interactions. In topsoils, aggregate resistance enhanced 13C-rich OM preservation, but in subsoils C preservation was due to other mechanisms, likely OM-mineral interactions. The proposed combined approach seems to be useful in the understanding of C and nutrients fate relates to water stresses, and in future research it could provide new insights into the complexity of soil biophysical processes.

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Big data are reshaping the way we interact with technology, thus fostering new applications to increase the safety-assessment of foods. An extraordinary amount of information is analysed using machine learning approaches aimed at detecting the existence or predicting the likelihood of future risks. Food business operators have to share the results of these analyses when applying to place on the market regulated products, whereas agri-food safety agencies (including the European Food Safety Authority) are exploring new avenues to increase the accuracy of their evaluations by processing Big data. Such an informational endowment brings with it opportunities and risks correlated to the extraction of meaningful inferences from data. However, conflicting interests and tensions among the involved entities - the industry, food safety agencies, and consumers - hinder the finding of shared methods to steer the processing of Big data in a sound, transparent and trustworthy way. A recent reform in the EU sectoral legislation, the lack of trust and the presence of a considerable number of stakeholders highlight the need of ethical contributions aimed at steering the development and the deployment of Big data applications. Moreover, Artificial Intelligence guidelines and charters published by European Union institutions and Member States have to be discussed in light of applied contexts, including the one at stake. This thesis aims to contribute to these goals by discussing what principles should be put forward when processing Big data in the context of agri-food safety-risk assessment. The research focuses on two interviewed topics - data ownership and data governance - by evaluating how the regulatory framework addresses the challenges raised by Big data analysis in these domains. The outcome of the project is a tentative Roadmap aimed to identify the principles to be observed when processing Big data in this domain and their possible implementations.

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Turfgrasses are ubiquitous in urban landscape and their role on carbon (C) cycle is increasing important also due to the considerable footprint related to their management practices. It is crucial to understand the mechanisms driving the C assimilation potential of these terrestrial ecosystems Several approaches have been proposed to assess C dynamics: micro-meteorological methods, small-chamber enclosure system (SC), chrono-sequence approach and various models. Natural and human-induced variables influence turfgrasses C fluxes. Species composition, environmental conditions, site characteristics, former land use and agronomic management are the most important factors considered in literature driving C sequestration potential. At the same time different approaches seem to influence C budget estimates. In order to study the effect of different management intensities on turfgrass, we estimated net ecosystem exchange (NEE) through a SC approach in a hole of a golf course in the province of Verona (Italy) for one year. The SC approach presented several advantages but also limits related to the measurement frequency, timing and duration overtime, and to the methodological errors connected to the measuring system. Daily CO2 fluxes changed according to the intensity of maintenance, likely due to different inputs and disturbances affecting biogeochemical cycles, combined also to the different leaf area index (LAI). The annual cumulative NEE decreased with the increase of the intensity of management. NEE was related to the seasonality of turfgrass, following temperatures and physiological activity. Generally on the growing season CO2 fluxes towards atmosphere exceeded C sequestered. The cumulative NEE showed a system near to a steady state for C dynamics. In the final part greenhouse gases (GHGs) emissions due to fossil fuel consumption for turfgrass upkeep were estimated, pinpointing that turfgrass may result a considerable C source. The C potential of trees and shrubs needs to be considered to obtain a complete budget.

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The study defines a new farm classification and identifies the arable land management. These aspects and several indicators are taken into account to estimate the sustainability level of farms, for organic and conventional regimes. The data source is Italian Farm Account Data Network (RICA) for years 2007-2011, which samples structural and economical information. An environmental data has been added to the previous one to better describe the farm context. The new farm classification describes holding by general informations and farm structure. The general information are: adopted regime and farm location in terms of administrative region, slope and phyto-climatic zone. The farm structures describe the presence of main productive processes and land covers, which are recorded by FADN database. The farms, grouped by homogeneous farm structure or farm typology, are evaluated in terms of sustainability. The farm model MAD has been used to estimate a list of indicators. They describe especially environmental and economical areas of sustainability. Finally arable lands are taken into account to identify arable land managements and crop rotations. Each arable land has been classified by crop pattern. Then crop rotation management has been analysed by spatial and temporal approaches. The analysis reports a high variability inside regimes. The farm structure influences indicators level more than regimes, and it is not always possible to compare the two regimes. However some differences between organic and conventional agriculture have been found. Organic farm structures report different frequency and geographical location than conventional ones. Also different connections among arable lands and farm structures have been identified.

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Depending on the regulatory regime they are subject to, governments may or may not be allowed to hand out state aid to private firms. The economic justification for state aid can address several issues present in the competition for capital and the competition for transfers from the state. First, there are principal-agent problems involved at several stages. Self-interested politicians might enter state aid deals that are the result of extensive rent-seeking activities of organized interest groups. Thus the institutional design of political systems will have an effect on the propensity of a jurisdiction to award state aid. Secondly, fierce competition for firm locations can lead to over-spending. This effect is stronger if the politicians do not take into account the entirety of the costs created by their participation in the firm location race. Thirdly, state aid deals can be incomplete and not in the interest of the citizens. This applies if there are no sanctions if firms do not meet their obligations from receiving aid, such as creating a certain number of jobs or not relocating again for a certain amount of time. The separation of ownership and control in modern corporations leads to principal-agent problems on the side of the aid recipient as well. Managers might receive personal benefits from subsidies, the use of which is sometimes less monitored than private finance. This can eventually be to the detriment of the shareholders. Overall, it can be concluded that state aid control should also serve the purpose of regulating the contracting between governments and firms. An extended mandate for supervision by the European Commission could include requirements to disincentive the misuse of state aid. The Commission should also focus on the corporate governance regime in place in the jurisdiction that awards the aid as well as in the recipient firm.