Farmland expansion and intensification do not foster local food self-sufficiency. Insights from the Mediterranean area.

Bridging the gap between the micro and the macro scale in modelling food security to inform context-specific regionalised policies remains a major scientific challenge. A better understanding of the relations between global and local drivers impacting local food self-sufficiency (LFSS) is essential. We applied to the whole Mediterranean environmental area (Southern and Northern) a modelling framework for structural estimates (PLS-PM) using qualitative and quantitative methods to combine local-level information from field surveys and participatory workshops with global-level data. Our findings show that farmland expansion and intensification spatially disconnected from urban consumption areas do not appear to foster LFSS. On the other hand, public policies appear key to enhancing LFSS in the Mediterranean area if appropriate to the particular regional context. We outline how this multi-level modelling methodology can contribute to a place-based approach by informing context-specific regionalised policies aimed at food security.

The Role of Different Types of Actors In The Future of Sustainable Agriculture In a Dutch Peri-urban Area.

Peri-urban areas support a broad range of multifunctional demands for public goods. In northwest Europe, peri-urban areas tend to overlap with intensive agricultural land, resulting in conflicts between agricultural use and the public good demands of residents. Sustainable intensification (SI) of agriculture might help reconcile agricultural and well-being goals, but it is unclear how the mix of actors in a peri-urban setting can trigger or restrain SI. In a Dutch case study, we explored how SI of agriculture can contribute to making peri-urban areas more sustainable, and which actors are key enabling factors for implementing SI. We used interviews, surveys, workshops, and empirical analysis to obtain insight into the stakeholder's vision of a sustainable future for the case study area, the farming system and actor network. We integrated these insights in a Bayesian Belief Network, where we linked the actor network to implementation of three SI measures (farm-level efficiency measures, small landscape elements, and direct sales), and used sensitivity analysis to model effects of support for implementation by different groups of actors. The case study has a dense stakeholder network, where, dependent on the SI measure, farmers are triggered by all actors to implement SI, or have a stronger role in uptake themselves. The sensitivity analysis suggested that the future preferred by the stakeholders requires broad support of all actors involved, with local actors without a formal role being essential for uptake. Overall, trade-offs among public goods are almost inevitable when taking up SI measures.

A spatial dataset about short-term land system dynamics (2005-2015) in the Mediterranean basin.

Mediterranean land systems are undergoing significant changes in terms of agricultural land use and practices. The location and nature of agricultural areas in the Mediterranean basin are changing following a set of tensions and opportunities taking place both locally and in the entire basin. This dataset presents the main short-term land system dynamics (2005-2015) and their location on the whole Mediterranean basin. The dataset is based on existing land use map and available data about agricultural surface distribution, and it is obtained through a classification process of the land systems on the two analyzed data (2005 and 2015) and a subsequent change detection between the two obtained maps. It covers all the Mediterranean bioclimatic area in pixels of 2 km spatial resolution, harmonizing information from the northern and southern side of the basin. We identified different types of changes, and the most relevant in terms of surfaces are: (1) from mixed agriculture to specialized fruit groves; (2) from agricultural areas to urban and/or periurban areas; (3) from agroforestry to arable systems, and (4) from predominantly bare soils to agricultural areas. This data can be used for further analysis to assess underlying trajectories, and the impact of the observed dynamics on biodiversity and the provision of ecosystem services, as well as on the organization of the food system.

Early intra-intensive care unit psychological intervention promotes recovery from post traumatic stress disorders, anxiety and depression symptoms in critically ill patients.

INTRODUCTION: Critically ill patients who require intensive care unit (ICU) treatment may experience psychological distress with increasing development of psychological disorders and related morbidity. Our aim was to determine whether intra-ICU clinical psychologist interventions decrease the prevalence of anxiety, depression and posttraumatic stress disorder (PTSD) after 12 months from ICU discharge. METHODS: Our observational study included critical patients admitted before clinical psychologist intervention (control group) and patients who were involved in a clinical psychologist program (intervention group). The Hospital Anxiety and Depression Scale (HADS) and Impact of Event Scale-Revised questionnaires were used to assess the level of posttraumatic stress, anxiety and depression symptoms. RESULTS: The control and intervention groups showed similar demographic and clinical characteristics. Patients in the intervention group showed lower rates of anxiety (8.9% vs. 17.4%) and depression (6.5% vs. 12.8%) than the control group on the basis of HADS scores, even if the differences were not statistically significant. High risk for PTSD was significantly lower in patients receiving early clinical psychologist support than in the control group (21.1% vs. 57%; P < 0.0001). The percentage of patients who needed psychiatric medications at 12 months was significantly higher in the control group than in the patient group (41.7% vs. 8.1%; P < 0.0001). CONCLUSIONS: Our results suggest that that early intra-ICU clinical psychologist intervention may help critically ill trauma patients recover from this stressful experience.

An open dataset about georeferenced harmonized national agricultural censuses and surveys of seven mediterranean countries.

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.