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Modeling high-resolution climate change impacts on wheat and maize in Italy

Authors: Donatella Spano; Donatella Spano; Andrea Gallo; Valentina Mereu; Valentina Mereu; Antonio Trabucco; Antonio Trabucco; +1 Authors

Modeling high-resolution climate change impacts on wheat and maize in Italy

Abstract

The Mediterranean basin has been identified as a prominent hotspot of climate change, with expected negative impacts on crop productivity, among others. Given the primary role that agriculture has to sustain cultural values, economic opportunities, and food security, it is crucial to identify specific risks in agriculture due to climate change, which can address more effective adaptation strategies and policies to cope with climate change. This study aims to evaluate the high-resolution impacts of climate change on the length of the growing cycle and yield of durum wheat, common wheat, and maize in Italy by using the CERES-Wheat and CERES-Maize crop models implemented in the Decision Support System for Agrotechnology Transfer (DSSAT) software. A digital platform (GIS-DSSAT) was developed to couple crop simulation models with dynamically downscaled climate projections at high resolution for Italy, which can better represent the Italian landscape complexity and the spatial distribution of different pedological and crop management features, providing more detailed information on the expected impacts on crops respect to previous studies at a coarser resolution. The projections have been extended for two climate change scenarios and accounting for uncertainty, either considering or not the potential direct effects of increasing atmospheric CO2 concentrations ([CO2]). Results show that climate change may affect Italian cereal production in the medium to long term periods. Maize is the main affected crop, with yield reductions homogeneously distributed from North to South Italy. Wheat yield is expected to decrease mainly in southern Italy, while northern Italy may benefit from higher precipitation regimes. Higher levels of atmospheric CO2 concentrations may partially offset the negative impact posed by climate change and increase the benefits in the northern regions, especially for common and durum wheat.

Country
Italy
Keywords

Atmospheric Science, Global and Planetary Change, Geography, Planning and Development, Carbon dioxide effect; Crop models; Decision support; GIS-DSSAT; Gridded simulation, GIS-DSSAT, Management, Monitoring, Policy and Law, Carbon dioxide effect, Energy Research, Decision support, Rural Digital Europe, Meteorology. Climatology, Crop models, QC851-999, Gridded simulation

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    23
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
23
Top 10%
Average
Top 10%
Green
gold