No abstract

Agricultural activities are co-responsible for the emission of the most important greenhouse gases: carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). Development of methodologies to improve monitoring techniques for N2O are still needful. The LIFE+IPNOA project aims to improve the emissions monitoring of nitrous oxide from agricultural soils and to identify the agricultural practices that can limit N2O production. In order to achieve this objective, both a mobile and a stationary instrument were developed and validated. Several experimental field trials were set up in two different sites investigating the most representative crops of Tuscany (Central Italy), namely durum wheat, maize, sunflower, tomato and faba bean. The field trials were realized in order to test the effect on N2O emissions of key factors: tillage intensity, nitrogen fertiliser rate and irrigation. The field trial on durum wheat was set up in 2013 to test the effect of tillage intensity (minimum and conventional tillage) and nitrogen fertilisation rate (0, 110, 170 kg N ha -1 ) on soil N2O flux. Monitoring was carried out using the IPNOA mobile prototype. Preliminary results on N2O emissions for the durum wheat growing season showed that mean daily N2O fluxes ranged from -0.13 to 6.43 mg m -2 day -1 and cumulative N2O-N emissions over the period ranged from 827 to 2340 g N2O-N ha -1 . Tillage did not affect N2O flux while increasing nitrogen fertilisation rate resulted to significantly increase N2O emissions. The IPNOA mobile prototype performed well during this first year of monitoring, allowing to catch both very low fluxes and peaks on N2O emissions after nitrogen supply, showing a good suitability to the field conditions.

The dataset presented in this paper is based on data gathered from several countries within the West Mediterranean area at the highest detailed scale regarding official statistics, with the aim of investigating land and food systems dynamics in the Mediterranean. Characterizing land and food systems dynamics is critical to reveal insights regarding interactions between current dynamics of agricultural practices, species diversity and local food systems. These interactions were analyzed, at multiple spatial scales, on a large part of the Mediterranean basin within the DIVERCROP Project (https://divercropblog.wordpress.com/).An harmonized dataset with the desired characteristics was not readily available from official sources and, therefore, it was necessary to build an ad hoc database that could: (1) cover the Mediterranean areas of seven countries, namely Algeria (DZ), France (FR), Italy (IT), Malta (MT), Portugal (PT), Spain (ES) and Tunisia (TN); (2) contain data referred to the most disaggregated level of administrative units for which data is available in each country; (3) contain data referred to at least two time points, including the latest available data, in each country; (4) contain data on number of farm holdings, on the physical areas covered by the main annual and permanent crops and on livestock (number of heads); (5) contain a primary key that allows joining the census and surveys database to a geographical dataset of administrative units covering the entire area; (6) have an associated complete geographical dataset of administrative units, to allow spatial data analyses.

The study aims to describe and interpret the agricultural system dynamics on the Western Mediterranean areas in terms of occupied land and crop specialization, by using the available data from the two last agricultural censuses. From the spatial point of view, we chose to adopt the most detailed level available, by using the smallest land administrative unit (LAU) for every involved country (Spain, Portugal, France and Italy). The resulting database was made of about 16k records and seven fields for a total of 112k single data. The considered variables were: total farm area (TFA), utilized agricultural area (UAA), irrigated area (IA), arable lands (AL), permanent crops (PC), permanent grassland (PG) and remaining surface (RS). The LAU data analysis was carried out following the four steps: (i) level of land occupation by agricultural systems; (ii) patterns of crop groups in UAA composition; (iii) attribution to each LAU of an agricultural typology (AT), resulting from the combination of the two previous features and iv) calculation of two synthetic indices to evaluate the expansion and specialization level for each LAU. Finally, an analysis of the spatial distribution of the two indices was proposed. Results showed a lowering over time of the TFA, UAA and PG areas and an increase of IA and RS. The number of identified ATs was rising at the expense of their extension. This phenomenon led to a fragmentation in ATs spatial distribution within the same geographical region. These changes prove that farmers’ responses to the driving forces acting on agricultural systems have been more differentiated than in the past. The prevailing strategy seems to aim at a reduction in the level of specialization of the agricultural systems whereas less marked was the lowering of their level of expansion.