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Perego, A., Sanna, M., Giussani, A., Chiodini, M. E., Fumagalli, M., Pilu, S. R., et al. (2014). Designing a high-yielding maize ideotype for a changing climate in Lombardy plain (northern Italy). Science of The Total Environment, 499, 497–509.
Abstract: The expected climate change will affect the maize yields in view of air temperature increase and scarce water availability. The application of biophysical models offers the chance to design a drought-resistant ideotype and to assist plant breeders and agronomists in the assessment of its suitability in future scenarios. The aim of the present work was to perform a model-based estimation of the yields of two hybrids, current vs ideotype, under future climate scenarios (2030-2060 and 2070-2100) in Lombardy (northern Italy), testing two options of irrigation (small amount at fixed dates vs optimal water supply), nitrogen (N) fertilization (300 vs 400 kg N ha(-1)), and crop cycle durations (current vs extended). For the designing of the ideotype we set several parameters of the ARMOSA process-based crop model: the root elongation rate and maximum depth, stomatal resistance, four stage-specific crop coefficients for the actual transpiration estimation, and drought tolerance factor. The work findings indicated that the current hybrid ensures good production only with high irrigation amount (245-565 mm y(-1)). With respect to the current hybrid, the ideotype will require less irrigation water (-13%, p<0.01) and it resulted in significantly higher yield under water stress condition (+15%, p<0.01) and optimal water supply (+2%, p<0.05). The elongated cycle has a positive effect on yield under any combination of options. Moreover, higher yields projected for the ideotype implicate more crop residues to be incorporated into the soil, which are positively correlated with the SOC sequestration and negatively with N leaching. The crop N uptake is expected to be adequate in view of higher rate of soil mineralization; the N fertilization rate of 400 kg N ha(-1) will involve significant increasing of grain yield, and it is expected to involve a higher rate of SOC sequestration.
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Perego, A., Sanna, M., Giussani, A., Chiodini, M. E., Fumagalli, M., Pilu, S. R., et al. (2014). Designing a high-yielding maize ideotype for a changing climate in Lombardy plain northern Italy. Science of the Total Environment, 499, 497–509.
Abstract: • ARMOSA model simulated a maize ideotype with drought adaptation under climate change. • The ideotype needs less water for higher yield compared to current hybrids. • Higher production involves more crop residues that enhance soil C sequestration. • Soil organic C may generally decrease and N leaching will increase in sandy soil. The expected climate change will affect the maize yields in view of air temperature increase and scarce water availability. The application of biophysical models offers the chance to design a drought-resistant ideotype and to assist plant breeders and agronomists in the assessment of its suitability in future scenarios. The aim of the present work was to perform a model-based estimation of the yields of two hybrids, current vs ideotype, under future climate scenarios (2030–2060 and 2070–2100) in Lombardy (northern Italy), testing two options of irrigation (small amount at fixed dates vs optimal water supply), nitrogen (N) fertilization (300 vs 400 kg N ha− 1), and crop cycle durations (current vs extended). For the designing of the ideotype we set several parameters of the ARMOSA process-based crop model: the root elongation rate and maximum depth, stomatal resistance, four stage-specific crop coefficients for the actual transpiration estimation, and drought tolerance factor. The work findings indicated that the current hybrid ensures good production only with high irrigation amount (245–565 mm y− 1). With respect to the current hybrid, the ideotype will require less irrigation water (− 13%, p < 0.01) and it resulted in significantly higher yield under water stress condition (+ 15%, p < 0.01) and optimal water supply (+ 2%, p < 0.05). The elongated cycle has a positive effect on yield under any combination of options. Moreover, higher yields projected for the ideotype implicate more crop residues to be incorporated into the soil, which are positively correlated with the SOC sequestration and negatively with N leaching. The crop N uptake is expected to be adequate in view of higher rate of soil mineralization; the N fertilization rate of 400 kg N ha− 1 will involve significant increasing of grain yield, and it is expected to involve a higher rate of SOC sequestration.
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Piontek, F., Müller, C., Pugh, T. A., Clark, D. B., Deryng, D., Elliott, J., et al. (2014). Multisectoral climate impact hotspots in a warming world. Proc. Natl. Acad. Sci. U. S. A., 111(9), 3233–3238.
Abstract: The impacts of global climate change on different aspects of humanity’s diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case studies on vulnerability and multifaceted adaptation strategies. We consider impacts related to water, agriculture, ecosystems, and malaria at different levels of global warming. Multisectoral overlap starts to be seen robustly at a mean global warming of 3 °C above the 1980-2010 mean, with 11% of the world population subject to severe impacts in at least two of the four impact sectors at 4 °C. Despite these general conclusions, we find that uncertainty arising from the impact models is considerable, and larger than that from the climate models. In a low probability-high impact worst-case assessment, almost the whole inhabited world is at risk for multisectoral pressures. Hence, there is a pressing need for an increased research effort to develop a more comprehensive understanding of impacts, as well as for the development of policy measures under existing uncertainty.
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Rosenzweig, C., Elliott, J., Deryng, D., Ruane, A. C., Müller, C., Arneth, A., et al. (2014). Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proc. Natl. Acad. Sci. U. S. A., 111(9), 3268–3273.
Abstract: Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies.
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Sollitto, D., De Benedetto, D., Castrignanò, A., Crescimanno, G., Provenzano, G., & Ventrella, D. (2012). Spatial data fusion and analysis for soil characterization: a case study in a coastal basin of south-western Sicily (southern Italy). Ital. J. Agron., 7(1), 4.
Abstract: Salinization is one of the most serious problems confronting sustainable agriculture in semi-arid and arid regions. Accurate mapping of soil salinization and the associated risk represent a fundamental step in planning agricultural and remediation activities. Geostatistical analysis is very useful for soil quality assessment because it makes it possible to determine the spatial relationships between selected variables and to produce synthetic maps of spatial variation. The main objective of this paper was to map the soil salinization risk in the Delia-Nivolelli alluvial basin (south-western Sicily, southern Italy), using multivariate geostatistical techniques and a set of topographical, physical and soil hydraulic properties. Elevation data were collected from existing topographic maps and analysed preliminarily to improve the estimate precision of sparsely sampled primary variables. For interpolation multi-collocated cokriging was applied to the dataset, including textural and hydraulic properties and electrical conductivity measurements carried out on 128 collected soil samples, using elevation data as auxiliary variable. Spatial dependence among elevation and physical soil properties was explored with factorial kriging analysis (FKA) that could isolate and display the sources of variation acting at different spatial scales. FKA isolated significant regionalised factors which give a concise description of the complex soil physical variability at the different selected spatial scales. These factors mapped, allowed the delineation of zones at different salinisation risk to be managed separately to control and prevent salinization risk. The proposed methodology could be a valid support for land use and soil remediation planning at regional scale.
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