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Witzke, P., Frank, S., Zimmermann, A., Havlík, P., & Ciaian, P. (2013). The impact of climate change on food security – results from a European perspective..
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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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Wilson, A. J., & Gubbins, S. (2014). Modelling interactions between climate and livestock pathogen transmission. FACCE MACSUR Mid-term Scientific Conference, 3(S) Sassari, Italy.
Abstract: Climate affects the transmission of livestock pathogens via multiple direct and indirect pathways. The impact of climate change on livestock pathogens is therefore complex and difficult to predict. Recent improvements in the availability of climatic data, the accumulation of epidemiological data and the development of Bayesian methodologies allow improved inferences to be made about the responses of pathogens to climate change. We discuss recent studies demonstrating these principles and present a proposal for future work using an extensively validated model for the transmission of bluetongue virus to forecast the potential consequences of predicted environmental changes to the expected impact of the disease and efficacy of current control strategies under a range of incursion scenarios.
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Wilson, A. (2014). Introduction and purpose of meeting..
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Wilson, A. (2016). Emerging infectious disease challenges..
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