• Energy Research

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.

In July 2016 the SheepToShip LIFE project was financed by the EU LIFE Programme Climate Action 2014-2020 with the aim to reduce the greenhouse gas emissions from the dairy sheep sector in Sardinia, an absolute leader on dairy sheep raising [4]. In particular, the main objective of the project is to reduce by 20% in 10 years GHG emissions (nitrous oxide, methane and carbon dioxide) from the Sardinian dairy sheep supply chain. The immediate goals of the project are to encourage the environmental improvements of production systems in the sheep sector and to demonstrate the environmental, economic and social benefits deriving from eco-innovation in the dairy industry and sheep farming sector. Additionally, its actions promote the implementation of environmental policies and rural development, guided by the Life Cycle Thinking approach, and aimed at enhancing the environmental quality of local sheep's milk and cheese supply chains. Furthermore, one of the project scopes is to increase the level of knowledge and awareness of stakeholders and the general public regarding the environmental sustainability of products made from sheep's milk and their contribution to the mitigation of climate change. With this approach, the project expects to achieve the development of a common methodology for analysing the life-cycle of sheep's milk supply chains. This procedure will be used to determine the environmental impact of the sheep's milk business in Sardinia, including the environmental hotspots of the life-cycle of Sardinian Protected Designation of Origin (PDO) sheep's cheese, and will be tested in several cases study (sheep farms and sheep dairy businesses) through the introduction of low-input techniques compatible with maintaining quality standards of products.

The eddy covariance method is a viable method to measure evapotranspiration from tree and vine crops. However, one must be careful to measure properly the energy balance components and to apply corrections to the heat flux data to obtain good results. Based on several years of experience with energy balance measurements, we have found that failure to achieve the energy closure is often attributable to inaccurate soil heat flux density data. In addition, interference by wind blowing past the mounting tower can lead to spurious results. Although the benefit was small in our experiments, applying the corrections for air temperature and density changes (WPL) are recommended to eliminate errors in sensible and latent heat flux density. This is especially true for high elevations and for locations with extreme temperatures. We found that locating the net radiometer and the eddy covariance instruments above or between the rows seems to have little influence on the measurement as long as the sensors are not too close to the canopy elements indicating that the 'footprints' were not an important factor. In this paper, these aspects of measuring ET with the eddy covariance method and some results will be discussed.

The IPCC Fifth Assessment Report (AR5) accounts an increase of the total annual anthropogenic GHG emissions between 2000 and 2010 that directly came from the transport sector. In 2010, 14% of GHG emissions were released by transport and fossil-fuel-related CO2 emissions reached about 32 GtCO2 per year. The report also considers adaptation and mitigation as complementary strategies for reducing the risks of climate change for sustainable development of urban areas. This paper describes the on-road traffic emission estimated in the framework of a Sardinian regional project [1] for the town of Sassari (Sardinia, Italy), one of the Sardinian areas where the fuel consumption for on-road transportation purposes is higher [2]. The GHG emissions have been accounted (a) by a calculation-based methodology founded on a linear relationship between source activity and emission, and (b) by the COPERT IV methodology through the EMITRA (EMIssions from road TRAnsport) software tool [3]. Inventory data for annual fossil fuel consumption associated with on-road transportation (diesel, gasoline, gas) have been collected through the Dogane service, the ATP and ARST public transport services and vehicle fleet data are available from the Public Vehicle Database (PRA), using 2010 as baseline year. During this period, the estimated CO2 emissions accounts for more than 180,000 tCO2. The calculation of emissions due to on-road transport quantitatively estimates CO2 and other GHG emissions and represents a useful baseline to identify possible adaptation and mitigation strategies to face the climate change risks at municipal level.

Although in many countries lightning is the main cause of ignition, in the Mediterranean Basin the forest fires are predominantly ignited by arson, or by human negligence. The fire season peaks coincide with extreme weather conditions (mainly strong winds, hot temperatures, low atmospheric water vapour content) and high tourist presence. Many works reported that in the Mediterranean Basin the projected impacts of climate change will cause greater weather variability and extreme weather conditions, with drier and hotter summers and heat waves. At long-term scale, climate changes could affect the fuel load and the dead/live fuel ratio, and therefore could change the vegetation flammability. At short-time scale, the increase of extreme weather events could directly affect fuel water status, and it could increase large fire occurrence. In this context, detecting the areas characterized by both high probability of large fire occurrence and high fire severity could represent an important component of the fire management planning. In this work we compared several fire probability and severity maps (fire occurrence, rate of spread, fireline intensity, flame length) obtained for a study area located in North Sardinia, Italy, using FlamMap simulator (USDA Forest Service, Missoula). FlamMap computes the potential fire behaviour characteristics over a defined landscape for given weather, wind and fuel moisture data. Different weather and fuel moisture scenarios were tested to predict the potential impact of climate changes on fire parameters. The study area, characterized by a mosaic of urban areas, protected areas, and other areas subject to anthropogenic disturbances, is mainly composed by fire-prone Mediterranean maquis. The input themes needed to run FlamMap were input as grid of 10 meters; the wind data, obtained using a computational fluid-dynamic model, were inserted as gridded file, with a resolution of 50 m. The analysis revealed high fire probability and severity in most of the areas, and therefore a high potential danger. The FlamMap outputs and the derived fire probability maps can be used in decision support systems for fire spread and behaviour and for fire danger assessment with actual and future fire regimes.

The assessment of fuel moisture content on a large spatial scale requires several observations and estimates and is often time consuming and costly due to labour and transportation expenses. Therefore, various models based on empirical functions of weather variables have been developed and applied to determine the amount of moisture in fuel. In this paper, a fuel dryness index (Fd) based on biophysical principles associated with energy exchange is presented and applied to monitor fuel moisture content for annual grasslands. Daily values of Fd were determined as the ratio of sensible heat flux density to the available energy using high-frequency temperature data and the surface renewal (SR) method in combination with net radiation and soil heat flux values. The SR method was evaluated by comparing with sensible and latent heat flux densities from eddy covariance data measured in a fire-vulnerable annual grassland. The Fd values and trends were compared with three well-known slow response fire-danger indices including the Keetch-Byram drought index, two modified versions of the drought factor in the McArthur forest fire-danger meter, and the fast response fine fuel moisture code of the Canadian fire weather index. Moreover, Fd index was compared with the McArthur grassland fire-danger meter. The Fd index was more responsive to daily changes than most of the other indices, providing accurate information on fuel dryness condition of a live vegetation grassland. In addition, it can potentially eliminate the need for calibrated empirical weather models and fuel stick measurements.

The CERES-Wheat crop model was used to simulate grain yields, kernel weights and anthesis dates for three Italian durum wheat varieties (Creso, Duilio and Simeto) under climate change projections at two typical Mediterranean environments (Ussana and Benatzu sites) located in Southern Sardinia (Italy). The model was calibrated and validated in a previous modelling study using long-term weather data from the same experimental sites and agronomic data-sets of the same sites and varieties over the period 1973-2004. To assess the responses of durum wheat varieties to climate changes, 48 synthetic climates based on the combination of increasing temperature and decreasing rainfall were used to represent paths of possible future climate change. The simulated impacts of climate projections on durum wheat varieties at both sites were: grain yield reduction, slightly increasing kernel weight, and earlier anthesis dates. The late variety Creso showed a larger grain yield reduction compared to the early genotypes Duilio and Simeto. Anticipation of time to flowering was larger at Ussana (medium-low fertility soil) than at Benatzu (high fertility soil) with no differences between varieties. Earlier anthesis response was due to temperature increase rather than rainfall reduction, since in the CERES-Wheat model as well as in the majority of crop growth models water availability has no effect on crop development rate. Predictions for kernel weight were more uncertain with a slightly increasing trend in response to increasing temperatures and decreasing rainfall. The CERES-Wheat crop model seems to capture fairly well the greater resilience shown by early genotypes in Mediterranean rainfed conditions. In general, the CERES-Wheat model showed results in line with the findings from real experiments in different pedoclimatic conditions. For these reasons, CERES-Wheat appeared to be reliable when used to evaluate plant responses to projected climate change conditions and can represent a useful tool for developing adaptation strategies and measures such as the choice and selection of adapted genotypes to tackle the negative impact of climate change.

The project CYCAS-MED: Crop yield and climate change impacts on agriculture: adaptation strategies to desertification processes in the Mediterranean areas, aimed at the development of tools and methodologies for the assessment of the response of three major crops in Morocco to climatic change. Results for durum wheat are here presented.

Abstract There is significant concern about the potential impacts of climate change and its variability on agricultural production worldwide. A good case study for analyzing vulnerability to climate change is represented by the Mediterranean area, which accounts for most of the global olive oil and more than 10% of the total cereal production. Considerable efforts have been recently expended on analyzing the effects of climate variability on agricultural crops using the scenario approach. The general goal of this work is to conduct a land suitability analysis for selected Mediterranean crops (wheat and olive) in Italy and to assess the impact of climate change on yield. © 2008, Page Press Publications. All rights reserved.