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Ma, S., Ben, T., H., Lellei-Kovács, E., Barcza, Z., Hidy, D., & Bellocchi, G. (2014). Grassland model intercomparison of the knowledge hub MACSUR: illustrative results from the models PaSim and Biome-BGC MuSo..
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Krzyszczak, J., Baranowski, P., & Slawinski, C. (2014). Chamber system measurements of carbon dioxide fluxes from winter wheat field in a Lubelskie province..
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Schönhart, M., Schauppenlehner, T., & Schmid, E. (2014). Integrated Land Use modelling of climate change impacts in two Austrian case study landscapes at field level..
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Witkowska-Walczak, B., Sławiński, C., Bartmiński, P., Melke, J., & Cymerman, J. (2014). Water conductivity of arctic zone soils (Spitsbergen). International Agrophysics, 28(4), 529–535.
Abstract: The water conductivity of arctic zone soils derived in different micro-relief forms was determined. The greatest water conductivity at the 0-5 cm depth for the higher values of water potentials (> -7 kJ m(-3)) was shown by tundra polygons (Brunic-Turbic Cryosol, Arenic) – 904-0.09 cm day(-1), whereas the lowest were exhibited by Turbic Cryosols – 95-0.05 cm day(-1). Between -16 and -100 kJ m(-3), the water conductivity for tundra polygons rapidly decreased to 0.0001 cm day(-1), whereas their decrease for the other forms was much lower and in consequence the values were 0.007, 0.04, and 0.01 cm day(-1) for the mud boils (Turbic Cryosol (Siltic, Skeletic)), cell forms (Turbic Cryosol (Siltic, Skeletic)), and sorted circles (Turbic Cryosol (Skeletic)), respectively. In the 10-15 cm layer, the shape of water conductivity curves for the higher values of water potentials is nearly the same as for the upper layer. Similarly, the water conductivity is the highest -0.2 cm day(-1) for tundra polygons. For the lower water potentials, the differences in water conductivity increase to the decrease of soil water potential. At the lowest potential the water conductivity is the highest for sorted circles -0.02 cm day(-1) and the lowest in tundra polygons -0.00002 cm day(-1).
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Höhn, J., & Rötter, R. P. (2014). Impact of global warming on European cereal production. CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources, 9(022), 1–15.
Abstract: This review examines relevant impact assessments identified by a literature search from 1991to date. A bibliographic search was applied to the CAB Abstracts database with a given searchstring. Resultant papers were checked for relevance, based on expert judgment. This yielded 91 papers, which were subjected to further analysis. Firstly, publication intensity over time and distribution by geographic location and cereal crop were examined. Next, for a given crop, the assessments and their outcomes were grouped by type and number of the change variables considered – that is, effects of climate change only, elevated CO 2 and technological progress(improved breeds, management). Finally, separately for individual countries/subregions and Europe as a whole, we examined whether and to what extent study results have changed over time, for example become more positive/negative. Based on our sample, we found that publication intensity increased exponentially during thelast 4 years, the majority of studies are Europe-wide, but some concentrated on a few countries(Italy, Spain and UK), whereby studies on wheat are clearly most popular. Taking the factor of technological progress into account has an overruling influence on results. Finally, over time, projected yield impacts have become more negative. This is in line with finding from global analyses, as reflected by the most recent comparison of agricultural impact chapters, of the 4thand 5th Assessment Reports of Intergovernmental Panel on Climate Change, Working Group II.In the future, there is particular need to consider impacts under various incremental and transformational adaptation measures in more depth (e.g. their interconnections across scales)and with more breadth (e.g. anticipated new breeds). Follow-up reviews should also examine how projected impacts are changing with the new climate scenario data sets (CMIP5) and with improved impact models and assessment approaches.
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