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Ventrella, D., Giglio, L., Charfeddine, M., Lopez, R., Castellini, M., Sollitto, D., et al. (2012). Climate change impact on crop rotations of winter durum wheat and tomato in southern Italy: yield analysis and soil fertility. Ital. J. Agron., 7(1), 15.
Abstract: Cropping systems are affected by climate change because of the strong relationship between crop development, growth, yield, CO2 atmospheric concentration and climate conditions. The increasing temperatures and the reduction of available water resources may result in negative impacts on the agricultural activity in Mediterranean environments than other areas. In this study the CERES-Wheat and CROPGRO-Tomato models were used to assess the effects of climate change on winter wheat (Triticum durum L.) and processing tomato (Lycopersicon aesculentum Mill.) in one of most productive areas of Italy, located in the northern part of the Puglia region. In particular we have compared three different General Circulation Models (HadCM3, CCSM3, ECHAM5) subjected to a statistical downscaling under two future IPCC scenarios (B1 and A2). The analysis was carried out at regional scale repeating the simulations for seven homogeneous area characterizing the spatial variability of the region. In the second part of the study, considering only HadCM3 data set, climate change impact on long-term sequences of the two crops combined in three crop rotations were evaluated in terms of yield performances and soil fertility as indicated by the soil organic content of carbon and nitrogen. The comparison between GCMs showed no significant differences for winter durum wheat yield, while noticeable differences were found for yield and irrigation requirements of tomato. Under future scenarios, the production levels were reduced for tomato, whereas positive yield effects were observed for winter durum wheat. For winter durum wheat the simulation indicated that two- and three-year rotations, including one year of tomato cultivation, improved the cereal yield and this positive effect maintained its validity also in future scenarios. For both crops higher requirements of water and nitrogen were predicted under future scenarios. This result coupled with the decrease of yield caused negative reduction of water use efficiency and nitrogen use efficiency for tomato cultivation.
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Constantin, J., Raynal, H., Casellas, E., Hoffman, H., Bindi, M., Doro, L., et al. (2019). Management and spatial resolution effects on yield and water balance at regional scale in crop models. Agricultural and Forest Meteorology, 275, 184–195.
Abstract: Due to the more frequent use of crop models at regional and national scale, the effects of spatial data input resolution have gained increased attention. However, little is known about the influence of variability in crop management on model outputs. A constant and uniform crop management is often considered over the simulated area and period. This study determines the influence of crop management adapted to climatic conditions and input data resolution on regional-scale outputs of crop models. For this purpose, winter wheat and maize were simulated over 30 years with spatially and temporally uniform management or adaptive management for North Rhine-Westphalia ((similar to)34 083 km(2)), Germany. Adaptive management to local climatic conditions was used for 1) sowing date, 2) N fertilization dates, 3) N amounts, and 4) crop cycle length. Therefore, the models were applied with four different management sets for each crop. Input data for climate, soil and management were selected at five resolutions, from 1 x 1 km to 100 x 100 km grid size. Overall, 11 crop models were used to predict regional mean crop yield, actual evapotranspiration, and drainage. Adaptive management had little effect (< 10% difference) on the 30-year mean of the three output variables for most models and did not depend on soil, climate, and management resolution. Nevertheless, the effect was substantial for certain models, up to 31% on yield, 27% on evapotranspiration, and 12% on drainage compared to the uniform management reference. In general, effects were stronger on yield than on evapotranspiration and drainage, which had little sensitivity to changes in management. Scaling effects were generally lower than management effects on yield and evapotranspiration as opposed to drainage. Despite this trend, sensitivity to management and scaling varied greatly among the models. At the annual scale, effects were stronger in certain years, particularly the management effect on yield. These results imply that depending on the model, the representation of management should be carefully chosen, particularly when simulating yields and for predictions on annual scale.
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Dono, G., Cortignani, R., Doro, L., Giraldo, L., Ledda, L., Pasqui, M., et al. (2013). An integrated assessment of the impacts of changing climate variability on agricultural productivity and profitability in an irrigated Mediterranean catchment. Water Resource Manage., 27(10), 3607–3622.
Abstract: Climate change is likely to have a profound effect on many agricultural variables, although the extent of its influence will vary over the course of the annual farm management cycle. Consequently, the effect of different and interconnected physical, technical and economic factors must be modeled in order to estimate the effects of climate change on agricultural productivity. Such modeling commonly makes use of indicators that summarize the among environmental factors that are considered when farmers plan their activities. This study uses net evapotranspiration (ETN), estimated using EPIC, as a proxy index for the physical factors considered by farmers when managing irrigation. Recent trends suggest that the probability distribution function of ETN may continue to change in the near future due to changes in the irrigation needs of crops. Also, water availability may continue to vary due to changes in the rainfall regime. The impacts of the uncertainties related to these changes on costs are evaluated using a Discrete Stochastic Programming model representing an irrigable Mediterranean area where limited water is supplied from a reservoir. In this context, adaptation to climate change can be best supported by improvements to the collective irrigation systems, rather than by measures aimed at individual farms such as those contained within the rural development policy.
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Ruete, A., Velarde, A., & Blanco-Penedo, I. (2015). Eco-DREAMS-S: modelling the impact of climate change on milk performance in organic dairy farms. Advances in Animal Biosciences, 6(01), 21–23.
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Lessire, F., Hornick, J. L., Minet, J., & Dufrasne, I. (2015). Rumination time, milk yield, milking frequency of grazing dairy cows milked by a mobile automatic system during mild heat stress. Advances in Animal Biosciences, 6(01), 12–14.
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