Are advantages from the partial replacement of corn with second-generation energy crops undermined by climate change? A case study for giant reed in northern Italy. (September 2015) - Cappelli, G.; Yamaç, S.S.; Stella, T.; Francone, C.; Paleari, L.; Negri, M.; Confalonieri, R.
Abstract: Among non-food energy crops, giant reed ( Arundo donax L.) represents a promising opportunity to reduce the fossil fuel dependency of Mediterranean countries. Nevertheless, the response of this crop to future climate projections is an open issue despite the crucial implications for mid-term planning policies. In this study, we present an exploratory analysis of the climate change impact on giant reed productivity in the Lombardy plain (northern Italy), an area that is currently characterized by intensive fodder corn-based cropping systems, but where corn is expected to be negatively affected by projected changes in thermal and pluviometric regimes. A dedicated simulation environment was developed, by coupling Arungro, a process-based model specific to giant reed, to a database including information on the presence of biogas plants, land use, crop management and distribution, in addition to weather scenarios for current climate and future projections. The baseline climate (1975–1994) was obtained from the European Commission MARS database; the Hadley3 and NCAR realizations of the IPCC AR4 emission scenarios A1B and B1 were used to generate 20-year climate projections centred on 2020 and 2050. Spatially distributed simulations were run at a sub-regional scale in areas selected according to their attractiveness for investments and low risk of competition between feed and no-feed crop destinations. The results indicate that an increased local suitability of giant reed in future climate projections is expected in terms of biomass production (+20% in 2020 for all scenarios and +30% in 2050 for Hadley-A1B) and the economic and environmental sustainability of related cropping systems. Highlights: Climate change is threatening sustainability of current energy cropping systems. We coupled a process-based crop model specific for Arundo with a full scale database. We develop a filter to select the most attractive simulation units at subregional scale. We explore climate change impact on giant reed productivity in the medium-long term. We evaluate the opportunity of local changes in the land use from maize to giant reed.