Modeling the effects of different fuel treatment mosaics on wildfire spread and behavior in a Mediterranean agro-pastoral area.

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 (<10%). We treated 2%, 5% and 8% of the landscape area, and identified priority sites to locate the fuel treatment units for all treatment alternatives. The fuel treatment alternatives were designed create diverse mosaics of disconnected treatment units with different sizes (0.5-10 ha, LOW strategy; 10-25 ha, MED strategy; 25-50 ha, LAR strategy); in addition, treatment units in a 100-m buffer around the road network (ROAD strategy) were tested. We assessed pre- and post-treatment wildfire behavior by the Minimum Travel Time (MTT) fire spread algorithm. The simulations replicated a set of southwestern wind speed scenarios (16, 24 and 32 km h-1) and the driest fuel moisture conditions observed in the study area. Our results showed that fuel treatments implemented near the existing road network were significantly more efficient than the other alternatives, and this difference was amplified at the highest wind speed. Moreover, the largest treatment unit sizes were the most effective in containing wildfire growth. As expected, increasing the percentage of the landscape treated and reducing wind speed lowered fire exposure profiles for all fuel treatment alternatives, and this was observed at both the landscape scale and for highly valued resources. The methodology presented in this study can support the design and optimization of fuel management programs and policies in agro-pastoral areas of the Mediterranean Basin and herbaceous type landscapes elsewhere, where recurrent grassland fires pose a threat to rural communities, farms and infrastructures.

Corrigendum to "The wildland-anthropic interface raster data of the Italy-France maritime cooperation area (Sardinia, Corsica, Tuscany, Liguria, and Provence-Alpes-Côte d'Azur)" [Data in Brief Volume 38 (2021) Article 107355].

[This corrects the article DOI: 10.1016/j.dib.2021.107355.].

Performance Prediction of Durum Wheat Genotypes in Response to Drought and Heat in Climate Change Conditions.

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.

Sustainability in the Sardinian sheep sector: A systems perspective, from good practices to policy.

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 CO2 eq/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). Integr Environ Assess Manag 2022;18:1187-1198. © 2022 SETAC.

Direct observations of CO2 emission reductions due to COVID-19 lockdown across European urban districts.

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 wildland-anthropic interface raster data of the Italy-France maritime cooperation area (Sardinia, Corsica, Tuscany, Liguria, and Provence-Alpes-Côte d'Azur).

We applied a geographical information system analysis to reclassify and characterize anthropic buildings based on structure density and area covered, land type, and proximity to wildlands able to originate intense wildfires and spot fires. The methodology was carried out in the 93,000 km2 Italy-France Maritime cooperation area (which includes the Regions of Sardinia, Tuscany, and Liguria, in Italy, and Corsica, and Provence-Alpes-Côte d'Azur, in France). We produced a 100-m raster dataset that characterizes and maps medium-high anthropic presence, wildland-anthropic areas, dispersed anthropic areas, and non-anthropic zones, in the whole study area. The study allowed to highlight variations in wildland anthropic interfaces among and within Regions as a function of anthropic presence and types and the surrounding wildlands. The spatial dataset provided with this work represents a valuable contribution to support landscape and urban planning and inform strategies to limit wildfire impacts nearby anthropic areas.

Quantifying deforestation and forest degradation with thermal response.

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.

Microbial immigration across the Mediterranean via airborne dust.

Dust particles lifting and discharge from Africa to Europe is a recurring phenomenon linked to air circulation conditions. The possibility that microorganisms are conveyed across distances entails important consequences in terms of biosafety and pathogens spread. Using culture independent DNA-based analyses via next generation sequencing of the 16 S genes from the airborne metagenome, the atmospheric microbial community was characterized and the hypothesis was tested that shifts in species diversity could be recorded in relation to dust discharge. As sampling ground the island of Sardinia was chosen, being an ideal cornerstone within the Mediterranean and a crossroad of wind circulation amidst Europe and Africa. Samples were collected in two opposite coastal sites and in two different weather conditions comparing dust-conveying winds from Africa with a control situation with winds from Europe. A major conserved core microbiome was evidenced but increases in species richness and presence of specific taxa were nevertheless observed in relation to each wind regime. Taxa which can feature strains with clinical implications were also detected. The approach is reported as a recommended model monitoring procedure for early warning alerts in frameworks of biosafety against natural spread of clinical microbiota across countries as well as to prevent bacteriological warfare.