Search

Phenology reflect the influences of climate change on individual plant biodiversity. Meteorological factors (temperature, precipitation, sunshine period) are reported to have major influence for determining variation of time phenophases through changes in biological activities.Functional traits are morphological, physiological, and phenological features that show the plant functional response to a specific environmental condition. Traits are therefore connected to physiological functions and mechanisms that allow species to face the climatic changes.Phenological traits can help explaining variation in plant growth strategies as it is closely associated with carbon gain and nutrient conservation. The beginning of leaf emergence and senescence can maximize plant survival and productivity, as the duration of stages are closely related to resource acquisition and distribution. Intraspecific trait variation, complementarity, and environmental stress are investigated at several hierarchical levels with the final goal of identify the mechanisms through which individuals and species interact and coexist for the use of resources. Therefore, it is fundamental to understanding how species modulate their phenological traits.In this work, phenological traits for 12 forest species are monitored and studied. The research was conducted on an experimental site in Sardinia, Italy. A selection of monocultures and mixed communities, with different levels of species richness and functional diversity, were under observation over a 2-years period.Phenological traits were investigated by using automated monitoring systems for recording high-resolution digital images in the visible spectrum. Start and duration of the growing season were monitored to acquire information regarding the plant status in relation to environmental conditions (temperature/drought). The images were collected at daily interval during the period 2017-2019. Six systems were set-up and installed on a metal pole, at 2.5 m height above ground.The phenological traits for each individual were determined by analysing images visually. Moreover, a digital image processing, for deriving colour vegetation indices, was performed using a routine specifically developed under the software application MATLAB. RGB color channel information were recorded as digital numbers (DN) in a region of interest (ROI). To reduce the effects of scene illumination, the DNs are converted in to chromatic coordinates. Daily values of vegetation indices (ExG, REI, GRVI, etc) were then calculated.The pattern of vegetation indices during the growing season were analysed for each species, showing how the color index performance works in capturing vegetation phenological change, and the performance of species growing under different levels of richness and functional diversity.Information from this study can provide a valid contribution to a more detailed understanding on how plant responds to different environmental conditions, in particular in relation to phenological behaviour in response to climatic changes in Mediterranean regions.

Heat waves (HWs) and wildfires are potentially considered highly correlated hazards with dramatic impacts on ecosystems and society. However, previous studies focused only on one single hazard leaving out potential compounding and cascading effects. The aim of this work is thus to investigate spatio-temporal patterns for both hazards in Mediterranean Europe and assess the potential influence of HWs on fire regime.The historical wildfire dataset was derived from the Global Wildfire Information System (GWIS). This dataset corresponds to georeferenced polygons detected between 2000 and 2021 by MODIS. To understand the relationship between fires and HWs, we extracted several fire regime metrics accounting for density, seasonality and severity. All the metrics were computed at the scale of 12 km square grid.Then, we characterised the HWs in terms of frequency, duration, seasonality and intensity for the same period based on a high resolution meteorological dataset (ERA5-land from Copernicus Climate Data Store). A HW was defined as a period of at least 6 days with temperatures greater than the 90th percentile whereas intensity was calculated as the total amount of degrees exceeding that percentile during the HW. Finally, we compared HWs occurrence with information about fire events. Compound and cascading events were analysed through hazard maps to identify simultaneous occurrences of the two hazards and look at different combinations of hazard sequences. Finally, multiple linear regression models were applied to explore the complex influence of HWs characteristics on fire metrics.The results highlighted the hotspot areas in Mediterranean countries where the common hazard occurrences were identified, and the role of HWs in the compound and cascading fire hazard events. The findings of this study could support the assessment of hazard patterns and, in turn, prevention and monitoring activities to support disaster risk reduction.

In the context of the Circular Economy, the enhancement of raw wool in new bioproducts represents an important challenge. Wool is the main by-product of sheep, although its production has decreased largely during the last decades. In addition, wools with coarse fiber diameter have little economic value since they are not adequate to be used in the textile sector and, when not transformed, wool needs to be treated as a special waste.Wool is by its nature a circular fiber. Due to its complex chemical composition, physical structure and mechanical properties, it represents a biodegradable renewable resource and can find various value-added applications beyond the textile industry. The technological characteristics make wool particularly suitable for different applications such as thermo-acoustic insulation, agricultural amendment, biomedical polymers, etc.Furthermore, it absorbs harmful pollutants, becoming a specific chemical indicator. In fact, it has been shown that wool fibers are good bio-indicators of the environmental status (soil, water and air pollution). The concentration of pollutants reflects either the feed and nutrition quality and the general health status of sheep as well as the climatic and environmental conditions. The sustainable and innovative alternative uses of this livestock waste could reduce and minimise keratinous waste disposal, reduce environmental impact and increase commercial process sustainability and circular economy.The aim of this research was to investigate the degree of contamination of Sarda sheep wool to understand if wool fiber can be a contamination source for both the environment and human health.Chemical analyses were carried out through Liquid chromatography Orbitrap mass spectrometry and Inductively coupled plasma mass spectrometry. Both analytical techniques were targeted for a wide range of micropollutants including pesticides, veterinary drugs and heavy metals. The results obtained in this study represent the first step for developing a new wool valorization chain.Wool analysis can be an important strategy for the biomonitoring of human exposure to pesticides and for evaluating the quality of wool-based products.

Viticulture in recent decades is particularly affected by reduction of water availability due to rising temperatures, drought and heat waves. Climate change projections towards global warming and drought set grape production at risk. Vineyards are largely located in semi-arid areas, such as Mediterranean regions, where the intensity of the drought season largely affect the final yield and quality of production. In order to complete its vegetative cycle, the vine needs large quantities of water. However, an optimal use of irrigation water is imperative for performing a sustainable cultivation, and this can only be achieved through a number of cultural practices, including regulated deficit irrigation and soil management. Moreover, robust techniques to accurately detect plant water stress are necessary.The development of new technologies related to proximal sensing are assuming great importance in vineyard management. Among them, are non-invasive methodologies based on infrared thermography for assessing plant water status, and supporting tools for irrigation scheduling. Moreover, proximal sensing techniques based on digital images are becoming a valuable tool for detecting crop physiological status.In this study, thermal and visible images of three varieties of grapevine, under two deficit irrigation regimes, were analysed and evaluated as a tool for supporting crop irrigation management. The experiment was conducted in two vineyards located in Sardinia, Italy, and consisted of two regulated deficit irrigation (RDI-1 moderate and RDI-2 severe) treatments and two reference treatments maintained under stress and well-watered conditions. Digital images were acquired daily, during the entire growing season, using Campbell CC5MPx digital cameras. Thermal images were acquired using the InfRec R500Pro thermal camera (Nippon Avionics Co., Ltd.). Artificial surfaces were used as target reference for wet and dry temperature. Vegetation indices from thermal and digital images, i.e. Crop water stress index (CWSI) and green and red chromatic indices (ExG, GRVI, REI), were then calculated for each observation day.The analysis of thermal images gave an accurate estimation of the differences in the water status of the vineyard over the RDI treatments. This technique proves to be able to well-differentiate different regimes in water management, confirming its good performance. The differences in CWSI values between moderate or severe water deficit treatments (RDI-1 and RDI-2) were in almost all cases (sites and varieties) statistically significant. These results were also confirmed by the seasonal pattern of both green and red chromatic indices (RGBs indices: ExG, GRVI, REI).The development of non-destructive, cost-effective and easy-to-use methods for continuous monitoring of grapevine water status is a challenge to be faced in the future. In this context, proximal sensing techniques tested in this study, can provide useful information to develop tools and models for irrigation management.

Three million sheep raised on 10 000 active farms operating in traditional and innovative farming systems in Sardinia, Italy, account for 13% of sheep milk production in the European Union (EU). Almost all of the milk delivered is processed to sheep cheese and is destined for world trade. The Sardinian dairy sheep sector also emits approximately 1600 kt CO2eq/year, approximately 60% of regional livestock greenhouse gas (GHG), prompting the need for regional mitigation plans. The SheepToShip LIFE project (EU-LIFE Climate Change Action 2014-2020) is a regional case study to test emission mitigation strategies. Based on the SheepToShip LIFE findings, this paper presents a systems perspective against the backdrop of the Sustainable Development Goals (SDGs) framework, with the aim of underlining system interlinkages between environmental, societal, and economic objectives. The project included (i) a life cycle thinking approach featuring environmental and socioeconomic traits of 18 sheep farms, (ii) on-farm implementation and demonstration of eco-innovative mitigation techniques indicating the most viable actions to reduce impact, (iii) focus groups discussing beliefs and reactions of the main stakeholders, and (iv) group model building producing a causal loop diagram from a systems thinking approach and exploring insights for regional policy-making that aligns with the SDGs. Causal links connect public interventions and stakeholder interaction (SDG 17) to boost farm eco-innovations (SDGs 9 and 8) and education and farmer training (SDG 4), and they foster efficient production (SDG 12) and high-quality food provisioning (SDG 2). These benefits contribute to climate change mitigation (SDG 13), water quality (SDG 6), and farm ecosystem services (SDG 15).

We implemented a fine-scale fire modeling approach to assess wildfire exposure in the highly valued resources and assets (HVRAs) of Ardabil Province (18,000 km(2)), northwestern Iran. For this purpose, we used the minimum travel time algorithm and simulated 60,000 wildfires under wildfire season most frequent weather scenarios. Wildfire exposure was analyzed on different vegetation types and municipalities using burn probability (BP), conditional flame length (CFL), and fire size (FS) modeling outputs. Also, we obtained the fire potential index (FPI) and source-sink ratio metrics to assess wildfire transmission across the study area. The BP ranged from 0.0003 to 0.013 (mean = 0.0008) and varied substantially among and within the HVRAs of the study area. While the lowest BP values located in broadleaf forests, the highest BP values concentrated on flashy fuel areas, including cereal crops, mountain meadows, and grazed pastures. The average CFL was 0.3 m, with the highest values peaking in cereal crops and wooded pastures located on slopes. FS ranged from about 1-1700 ha, with an average value of 225 ha. Fires ignited in the northern part of the study area resulted in the most significant FS values, due to the large contiguous patches of high fuel loads. High FPI values were associated with large fire ignition areas and anthropic fire occurrence hotspots in the northern and southern parts of the study area. Cereal crops and grazed pastures behaved as relevant wildfire sources of fires exposing rural communities. The results of this study may help support the development of an improved wildfire risk management policy in the study area. The methods from this study could be replicated in neighboring areas and other cultural landscapes of the Middle East, where wildfires pose a threat to human assets and natural values.

Forest stands plays an important role in Western Mediterranean ecosystems, their characterization it is needed for a whole comprehension of natural dynamics and for an efficient forestry management. The definition of the structural parameters of forest vegetation is a useful information for different environmental applications, such as studies on carbon dynamics, sustainable forest management, ecological studies, forest fuel studies and fire risk management. A precise description of the forest is particularly important for fire hazard mitigation planning because allows predictions of the potential fire behavior and its destructive effects. Obtaining detailed information on forest stand and canopy variables requires extensive, difficult, and laborious field campaigns. Remote and proximal sensing techniques for forest monitoring have become popular in recent decades. Specifically, Terrestrial Laser Scanner (TLS), based on Lidar technology, has demonstrated its potential to overcome the limitations of the conventional ground-based forest inventory techniques, but the accuracy and applicability of TLS techniques for estimation of tree attributes and canopy characterization, presupposes a correct separation between points representing shrubs, woody material, leaves and small branches and needs further investigations. In this work we developed and tested an automatic procedure based on the point density algorithms DBSCAN, to correctly separate points representing shrubs, woody material, leaves, and small branches at plot level, in order to identify woody material volumes, tree density and canopy cover on a forest stand. The study was carried out in several areas located in Sardinia, Italy, mainly covered by pine forest, mixed forest, and oak forest with different understory types. Destructive and non-destructive measurements were done inside circular plots of 10 m radius. TLS data sets were collected in field by multiple scanning of the plots. The 3D point clouds were processed for isolating trees, ground and understory and subsequently for separating wood from foliage. Cloud points were partitioned in cubic volumes (voxels) that were used as input to separate stand components (by applying principal component analysis) and to generate wood and no-wood clusters (by applying the point density algorithm DBSCAN). The first results obtained show that the proposed method allows to correctly identify foliage, trunk and main branches especially when the underlying layer is dominated by low herbaceous vegetation. However, further studies are needed to assess the ability of this method in forest stands characterized by high and dense undergrowth and with different species of trees.

International audience; The measures taken to contain the spread of COVID-19 in 2020 included restrictions of people's mobility and reductions in economic activities. These drastic changes in daily life, enforced through national lockdowns, led to abrupt reductions of anthropogenic CO2 emissions in urbanized areas all over the world. To examine the effect of social restrictions on local emissions of CO2, we analysed district level CO2 fluxes measured by the eddy-covariance technique from 13 stations in 11 European cities. The data span several years before the pandemic until October 2020 (six months after the pandemic began in Europe). All sites showed a reduction in CO2 emissions during the national lockdowns. The magnitude of these reductions varies in time and space, from city to city as well as between different areas of the same city. We found that, during the first lockdowns, urban CO2 emissions were cut with respect to the same period in previous years by 5% to 87% across the analysed districts, mainly as a result of limitations on mobility. However, as the restrictions were lifted in the following months, emissions quickly rebounded to their pre-COVID levels in the majority of sites.

The measures taken to contain the spread of COVID-19 in 2020 included restrictions of people's mobility and reductions in economic activities. These drastic changes in daily life, enforced through national lockdowns, led to abrupt reductions of anthropogenic CO

A next-generation sequencing (NGS)-based taxonomic analysis was carried out on airborne bacteria sampled at ground level in two periods (May and September) and two opposite locations on the north–south axis of the island of Sardinia. Located in a central position of the Mediterranean basin, Sardinia constitutes a suitable outpost for revealing possible immigration of bacterial taxa during transcontinental particle discharge between Africa and Europe. With the aim of verifying relative effects of dust outbreaks, sampling period, and sampling site on the airborne bacterial community composition, we compared air collected during dust-carrying meteorological events to that coming from wind regimes not associated with long-distance particle lifting. Results indicated that (a) higher microbial diversity and richness (118 vs. 65 orders) and increased community evenness were observed in the campaign carried out in September in comparison to the one in May, irrespective of the place of collection and of the presence or absence of dust outbreaks; (b) during the period of standard wind regimes without transcontinental outbreaks, a synchronous concerted turnover of bacterial communities across distant locations of the same island, accompanied as mentioned by a parallel rise in bacterial diversity and community evenness, appears to have occurred; (c) changes in wind provenance could transiently change community composition in the locality placed on the coast facing the incoming wind but not in the one located at the opposite side of the island, and for this reason the community changes brought from dust outbreaks of African origin are observed only in the sampling station exposed to the south; (d) the same winds, once proceeding over land, appear to uplift bacteria belonging to a common core already present over the region, which dilute or replace those that were associated with the air coming from the sea or conveyed by the dust particulates, explaining the two prior points; and (e) the hierarchy of the variables tested in determining bacterial assemblages composition results is as follows: sampling period≫ongoing meteorological events>sampling location within the island.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-flled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the frst time in this paper. In addition, 206 of these sites are for the frst time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible., European Union (EU), United States Department of Energy (DOE)

Climate change scenarios together with the increasing request for sustainable crop farming push the irrigation sector toward a more efficient use of natural resources. This is particularly relevant for the wine industry in Mediterranean areas, where there is a growing interest for technologies and knowledge devoted to save water resources while maintaining wine production and quality. In this work, a set of plant water status related variables were continuously monitored using an automated platform and compared with stem water potential values measured with pressure chambers. The preliminary results showed a good potential for these new automated sensors for a real time monitoring of the vine water status.

An NGS-based taxonomic analysis was carried out on airborne bacteria sampled at ground level in two periods (May and September) and two opposite localities on the North-South axis of the Sardinia Island. Located in a central position of the Mediterranean basin, Sardinia constitutes a suitable outpost to reveal possible immigration of bacterial taxa during transcontinental particle discharge between Africa and Europe. With the aim of verifying relative effects of dust outbreaks, sampling period and sampling site, on the airborne bacterial community composition, we compared air collected during dust-carrying meteorological events to that coming from wind regimes not associated to long-distance particle lifting. Results indicated that: (a) a higher microbial diversity (118 orders vs 65) and increased community evenness were observed in the campaign carried out in September in comparison to the one in May, irrespective of the place of collection and of the presence or absence of dust outbreaks. (b) During the period of standard wind regimes without transcontinental outbreaks a synchronous, concerted succession of bacterial communities across distant locations of the same island, accompanied as mentioned by a parallel rise in bacterial diversity and community evenness appears to have occurred. (c) changes in wind provenance could transiently change community composition in the locality placed on the coast facing the incoming wind, but not in the one located at the opposite side of the island; for this reason the community changes brought from dust outbreaks of African origin are observed only in the sampling station exposed to south; (d) the same winds, once proceeding over land appear to uplift bacteria belonging to a common core already present over the region, which dilute or replace those that were associated with the air coming from the sea or conveyed by the dust particulate, explaining the two prior points. (e) the hierarchy of the variables tested in determining bacterial assemblages composition results: sampling period >> ongoing meteorological events > sampling location within the island.

With an approach combining crop modelling and biotechnology to assess the performance of three durum wheat cultivars (Creso, Duilio, Simeto) in a climate change context, weather and agronomic datasets over the period 1973–2004 from two sites, Benatzu and Ussana (Southern Sardinia, Itay), were used and the model responses were interpreted considering the role of DREB genes in the genotype performance with a focus on drought conditions. The CERES-Wheat crop model was calibrated and validated for grain yield, earliness and kernel weight. Forty-eight synthetic scenarios were used: 6 scenarios with increasing maximum air temperature; 6 scenarios with decreasing rainfall; 36 scenarios combining increasing temperature and decreasing rainfall. The simulated effects on yields, anthesis and kernel weights resulted in yield reduction, increasing kernel weight, and shortened growth duration in both sites. Creso (late cultivar) was the most sensitive to simulated climate conditions. Simeto and Duilio (early cultivars) showed lower simulated yield reductions and a larger anticipation of anthesis date. Observed data showed the same responses for the three cultivars in both sites. The CERES-Wheat model proved to be effective in representing reality and can be used in crop breeding programs with a molecular approach aiming at developing molecular markers for the resistance to drought stress.

The fire danger (FD) defines the conditions less or more favourable for a fire ignition success and its propagation. FD indexes, that integrates environmental variables related to FD in more or less complex equations and systems, are widely used in wildfire prone countries for both scientific and operational purposes. Assessing the performance of FD indexes is challenging and this issue is quite debated within the fire community, which has been trying to apply several methodologies to evaluate FD indexes. The main aim of this work is to give a contribution to this effort. The analysis was conducted using data from a fire-prone Mediterranean area (Sardinia island, Italy), where 8 FD indexes were evaluated and compared using different statistical approaches. We calculated the daily FD values for the period 2000-2007 over the study area. A set of statistical tools (namely Spearman rank correlation, Index Value Distribution and Percentile Analysis, and Logistic Regression) were applied to evaluate the performance of each FD index by comparing FD values with fire occurrence indicators. The statistical tests revealed a large variability in FD indexes performance, depending also on fire activity conditions. Our results showed that two of the tested FD indexes reached a good overall performance. Findings from this study can help both the scientific community and local fire managers, supporting the evaluation of early warning systems and fire prevention strategies in the Mediterranean Basin.

Wildfire spread and behavior can be limited by fuel treatments, even if their effects can vary according to a number of factors including type, intensity, extension, and spatial arrangement. In this work, we simulated the response of key wildfire exposure metrics to variations in the percentage of treated area, treatment unit size, and spatial arrangement of fuel treatments under different wind intensities. The study was carried out in a fire-prone 625 km2 agro-pastoral area mostly covered by herbaceous fuels, and located in Northern Sardinia, Italy. We constrained the selection of fuel treatment units to areas covered by specific herbaceous land use classes and low terrain slope (

© 2017 Elsevier B.V. Deforestation and forest degradation cause the deterioration of resources and ecosystem services. However, there are still no operational indicators to measure forest status, especially for forest degradation. In the present study, we analysed the thermal response number (TRN, calculated by daily total net radiation divided by daily temperature range) of 163 sites including mature forest, disturbed forest, planted forest, shrubland, grassland, savanna vegetation and cropland. TRN generally increased with latitude, however the regression of TRN against latitude differed among vegetation types. Mature forests are superior as thermal buffers, and had significantly higher TRN than disturbed and planted forests. There was a clear boundary between TRN of forest and non-forest vegetation (i.e. grassland and savanna) with the exception of shrubland, whose TRN overlapped with that of forest vegetation. We propose to use the TRN of local mature forest as the optimal TRN (TRNopt). A forest with lower than 75% of TRNopt was identified as subjected to significant disturbance, and forests with 66% of TRNopt was the threshold for deforestation within the absolute latitude from 30° to 55°. Our results emphasized the irreplaceable thermal buffer capacity of mature forest. TRN can be used for early warning of deforestation and degradation risk. It is therefore a valuable tool in the effort to protect forests and prevent deforestation.

Despite the significant role of small ruminant sector in the global trends of livestock productions, little research has been conducted on the environmental implications of dairy sheep production systems. Dairy sheep systems are relevant for the economy of many areas of the Mediterranean Basin and the environmental and economic optimization of their productive factors is considered an effective strategy for promoting the innovation and increasing the competitiveness of Mediterranean dairy sheep systems. Therefore, scientific studies are needed in order to propose specific greening strategies and to improve the environmental performances of dairy sheep systems. The main objective of this study was to define a preliminary characterization of the environmental profile of sheep milk (“Pecorino”) cheese chain in Sardinia (Italy), using a Life Cycle Assessment (LCA) approach, with the following specific goals: i) comparing the environmental impacts caused by both the artisanal and the industrial manufacturing processes of "Pecorino” cheese and ii) identifying the hotspots to reduce the environmental impacts of the Sardinian dairy sheep sector. The analysis was based on the functional unit of 1 kg of artisanal “Pecorino di Osilo” cheese, and 1 kg of the industrial manufacturing cheese “Pecorino Romano PDO” cheese. The LCA highlighted that the GHG emissions of the two cheeses were similar, with an average value equal to 17 kg CO2-eq, largely due to enteric fermentation. The main differences between the two environmental profiles were found for human toxicity, ecotoxicity and eutrophication potential impact categories. Enteric methane emissions, feed supply chain, electricity, equipment and wastewater management seemed to be the hotspots where the environmental performances can be improved.

High severity wildfires can have many negative impacts on ecosystems. In this work, we coupled wildfire spread and erosion prediction modelling to evaluate the effects of fuel reduction treatments in preventing soil runoff in Mediterranean ecosystems. The study was carried out in a 68,000-ha forest area located in Northern Sardinia, Italy. We treated 15% of the study area, and compared no-treatment conditions vs alternative strategic fuel treatments. We estimated pre- and post-treatment fire behaviour by using the Minimum Travel Time (MTT) fire spread algorithm. For each fuel treatment scenario, we simulated 25,000 wildfires replicating the historic weather conditions associated with severe wildfires in the area. Sediment delivery was then estimated using the Erosion Risk Management Tool (ERMiT). Our results showed how post-fire sediment delivery varied among and within the fuel treatment scenarios tested. The treatments realized nearby roads were the most efficient. We also evaluated the effects of other factors such as exceedance probability, time since fire, slope, fire severity and vegetation type on post-fire sediment delivery. This work provides a quantitative assessment approach to inform and optimize proactive risk management activities aimed at reducing post-fire erosion in Mediterranean areas.

In a 3-year study, the chemical compositions of extra virgin olive oils (EVOO) of Bosana variety deriving from three different growing areas in Northern Sardinia were characterized, together with the pedo-climatic conditions of the three different growing areas, to gauge any differences at the chemical level. The main chemical differences in the oils from the three-studied areas were recorded in the fatty acid profiles [palmitic, oleic, and linoleic acid; sum of saturated (SFA), monounsaturated (MUFA), and polyunsaturated (PUFA) fatty acids]: these dissimilarities were ascribable to the environmental characteristics of the Alghero area, while others analytical parameters such as tocopherols, pigments, phenolic, and volatile compounds were not affected by production area. Fatty acids profile revealed a clear relation with temperature at a mesoclimate level, allowing a clusterization of the production areas. Our study provided evidences that pedo-climatic factors affect the quality of EVOO; in particular, in the case of Bosana cultivar the acidic fraction resulted one of the main traits differentiating the olive growing areas.

Wildfires represent a major threat to Mediterranean ecosystems and are responsible for relevant impacts to environmental, economic and social values. In the period 2010-2016, the cross-border Interreg Italy-France Maritime territory, which includes Sardinia, Corsica, Tuscany, Liguria and PACA Regions, had about 20,000 wildfire ignitions and a total burned area of about 122,000 ha. In the face of social and environmental conditions and risks of the Maritime Regions, strengthening and developing innovative common guidelines and systems of wildfire management, from the monitoring and forecast to suppression, can provide more effective solutions to the wildfire problem, and can help strengthen cross-border cooperation in case of days with high risk. This work is devoted to introduce the MED-Star project, and to describe his main activities and results, with a focus on the tasks and activities coordinated by the National Research Council of Italy, Institute of BioEconomy (CNR-IBE) of Sassari. MED-Star is a 3-years strategic project supported by the Interreg Italy-France Maritime Program 2014-2020, which is co-financed by the European Regional Development Fund (ERDF). MED-Star is closely linked to 4 joint simple projects (Intermed; Med-Coopfire; Med-Foreste; Med-PSS), which mainly focus on investments in small infrastructures for wildfire risk prevention and support to wildfire suppression operations. The MED-Star project aims to share and discuss fire management policies and the most advanced strategies that can reduce the risk associated with wildfires, also through the combination of joint action plans and pilot / demonstration actions. The partnerships of MED-Star and the related 4 simple projects include the main actors competent at the administrative, technical and scientific level on the wildfire topic in the Maritime area of cooperation, and are able to meet the abovementioned challenges, contributing to 1) the reduction of wildfire risk in the five Regions involved, 2) the definition of strategic and operational solutions, 3) the implementation of operational actions and investments for wildfire prevention, monitoring, forecast and suppression, and 4) the strengthening of joint early warning and risk monitoring systems.

Wildland fires represent a major threat to Quercus suber L. ecosystems, which provide relevant socioeconomic and ecological services in the Mediterranean Basin. In this work, we analyzed recent wildland fire dynamics in cork oak woodlands along the fire-prone areas of Sardinia (Italy), Corsica (France) and Catalonia (Spain). We first characterized geographic extent and main characteristics of cork oak woodlands in these regions and analyzed how environmental (climate and elevation) and socioeconomic factors (population and land uses) vary in the areas covered by Quercus suber L. We then evaluated how wildfires affected cork oak stands and, by logistic regression analysis, to what extent wildfires in cork oak areas were related to the above set of environmental and anthropic explanatory variables. Results revealed specific variations across study areas in cork oak characteristics as well as in environmental and social factors. We highlighted the spatial and temporal patterns of wildfires on cork oak woodlands, in terms of extent, seasonality, frequency and main driving factors. In the period 2003–2015, the percentage of cork oak woodlands burned ranged from 3.42% in Corsica to 11.30% in Sardinia. A few large and severe wildfires accounted for most of the area burned in cork oak woodlands. The most significant predictive variable that explained the spatial variation in wildland fire ignitions inside or nearby cork oaks was summer precipitation, while the weight of other factors varied depending on the region. This study provides evidence on recent fire dynamics in cork oak woodlands and gives valuable information and insights for the implementation of forest management and planning strategies in the Mediterranean area. This work was supported by the Sardinia Region under the project “Multifunzionalità delle foreste a quercia da sughero in Sardegna” (Multifunctionality of cork oak forests in Sardinia) funded within L.R. n. 7/2007 “Promozione della ricerca scientifica e della innovazione tecnologica in Sardegna,/Tender no. 2″, and by the “Proterina-2” Project funded by the Italia Francia-Marittimo Programme.

The development of comprehensive fire management and risk assessment strategies is of prominent concern in Southern Europe, due to the expanding scale of wildfire risk. In this work, we applied simulation modeling to analyze fine-scale (100-m resolution) wildfire exposure and risk transmission in the 24,000 km2 island of Sardinia (Italy). Sardinia contains a variety of ecological, cultural, anthropic and touristic resources that each summer are threatened by wildfires, and represents well the Mediterranean Basin environments and conditions. Wildfire simulations based on the minimum travel time algorithm were used to characterize wildfire exposure and risk transmission in terms of annual burn probability, flame length, structures exposed and type and amount of transmission. We focused on the historical conditions associated with large (>50 ha) and very large (>200 ha) wildfires that occurred in Sardinia in the period 1998–2016, and combined outputs from wildfire simulation modeling with land uses, building footprint locations, weather, and historical ignition data. The outputs were summarized for weather zones, main wind scenarios and land uses. Our study characterized spatial variations in wildfire spread, exposure and risk transmission among and within weather zones and the main winds associated with large events. This work provides a novel quantitative approach to inform wildfire risk management and planning in Mediterranean areas. The proposed methodology can serve as reference for wildfire risk assessment and can be replicated elsewhere. Findings can be used to better understand the spatial dynamics and patterns of wildfire risk and evaluate expected wildfire behavior or transmission potential in Sardinia and neighboring regions.

Several studies have demonstrated that Monteith's approach can efficiently predict forest gross primary production (GPP), while the modeling of net ecosystem production (NEP) is more critical, requiring the additional simulation of forest respirations. The NEP of different forest ecosystems in Italy was currently simulated by the use of a remote sensing driven parametric model (modified C-Fix) and a biogeochemical model (BIOME-BGC). The outputs of the two models, which simulate forests in quasi-equilibrium conditions, are combined to estimate the carbon fluxes of actual conditions using information regarding the existing woody biomass. The estimates derived from the methodology have been tested against daily reference GPP and NEP data collected through the eddy correlation technique at five study sites in Italy. The first test concerned the theoretical validity of the simulation approach at both annual and daily time scales and was performed using optimal model drivers (i.e., collected or calibrated over the site measurements). Next, the test was repeated to assess the operational applicability of the methodology, which was driven by spatially extended data sets (i.e., data derived from existing wall-to-wall digital maps). A good estimation accuracy was generally obtained for GPP and NEP when using optimal model drivers. The use of spatially extended data sets worsens the accuracy to a varying degree, which is properly characterized. The model drivers with the most influence on the flux modeling strategy are, in increasing order of importance, forest type, soil features, meteorology, and forest woody biomass (growing stock volume).