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Schönhart, M., & Nadeem, I. (2015). Direct climate change impacts on cattle indicated by THI models. Advances in Animal Biosciences, 6, 17.
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Twardy, S., & Kopacz, M. (2015). The role of permanent grasslands in mountain areas: Study on agri-environmental importance of permanent grasslands – based on research carried out in the upper Dunajec River basin and Grajcarek Stream basin. Falenty-Krakow.
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Van Middelkoop, J. (2015). Promoting climate mitigation on agricultural and forest land through the CAP..
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Virkajärvi, P., Lehtonen, H., & Järvenranta, K. (2015). Regional impacts of climate change, observations and projections. Finnish Pilot study: North Savo region. (Vol. 6, pp. SP6–5). Brussels.
Abstract: Regional adjustment of regulation is important (eg. water protection) Due to expected growing yield potential fertilisation restrictions need adjustmentNitrate directive restricts efficient and sustainable grass productionGreening practices have only slight – and partly negative – impact on ruminant production (permanent grassland not suitable for northern conditions)Inefficient markets for agricultural land cause difficulties for farms that are increasing their productionCapitalisation of area payments to land prices + incentives for extensification (e.g. nature management and other set aside schemes under pillar 2) fit better part-time crop farms, not full-time livestock farmsthey express frustration on weak land supplyProduction based support for suckler cows and (dairy originated) beef production is vital for producersNo significant increase in production expected, budgetary limits of coupled supports No Label
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Toscano, P., Genesio, L., Crisci, A., Vaccari, F. P., Ferrari, E., La Cava, P., et al. (2015). Empirical modelling of regional and national durum wheat quality. Agricultural and Forest Meteorology, 204, 67–78.
Abstract: The production of durum wheat in the Mediterranean basin is expected to experience increased variability in yield and quality as a consequence of climate change. To assess how environmental variables and agronomic practices affect grain protein content (GPC), a novel approach based on monthly gridded input data has been implemented to develop empirical model, and validated on historical time series to assess its capability to reproduce observed spatial and inter-annual GPC variability. The model was applied in four Italian regions and at the whole national scale and proved reliable and usable for operational purposes also in a forecast ‘real-time’ mode before harvesting. Precipitable water during autumn to winter and air temperature from anthesis to harvest were extremely important influences on GPC; these and additional variables, included in a linear model, were able to account for 95% of the variability in GPC that has occurred in the last 15 years in Italy. Our results are a unique example of the use of modelling as a predictive real-time platform and are a useful tool to understand better and forecast the impacts of future climate change projections on durum wheat production and quality.
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