Browsing by Author "Trnka, M."
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Item Open Access Interactively modelling land profitability to estimate European agricultural and forest land use under future scenarios of climate, socio-economics and adaptation(Springer Verlag, 2014-07-01) Audsley, Eric; Trnka, M.; Sabate, Santiago; Maspons, Joan; Sanchez, Anabel; Sandars, Daniel L.; Balek, Jan; Pearn, Kerry R.Studies of climate change impacts on agricultural land use generally consider sets of climates combined with fixed socio-economic scenarios, making it impossible to compare the impact of specific factors within these scenario sets. Analysis of the impact of specific scenario factors is extremely difficult due to prohibitively long run-times of the complex models. This study produces and combines metamodels of crop and forest yields and farm profit, derived from previously developed very complex models, to enable prediction of European land use under any set of climate and socio-economic data. Land use is predicted based on the profitability of the alternatives on every soil within every 10' grid across the EU. A clustering procedure reduces 23,871 grids with 20+ soils per grid to 6,714 clusters of common soil and climate. Combined these reduce runtime 100 thousand-fold. Profit thresholds define land as intensive agriculture (arable or grassland), extensive agriculture or managed forest, or finally unmanaged forest or abandoned land. The demand for food as a function of population, imports, food preferences and bioenergy, is a production constraint, as is irrigation water available. An iteration adjusts prices to meet these constraints. A range of measures are derived at 10' grid-level such as diversity as well as overall EU production. There are many ways to utilise this ability to do rapidWhat-If analysis of both impact and adaptations. The paper illustrates using two of the 5 different GCMs (CSMK3, HADGEM with contrasting precipitation and temperature) and two of the 4 different socio-economic scenarios ("We are the world", "Should I stay or should I go" which have contrasting demands for land), exploring these using two of the 13 scenario parameters (crop breeding for yield and population) . In the first scenario, population can be increased by a large amount showing that food security is far from vulnerable. In the second scenario increasing crop yield shows that it improves the food security problem.Item Open Access What can scenario modelling tell us about future European scale agricultural land use, and what not?(Elsevier Science B.V., Amsterdam., 2006-04-01T00:00:00Z) Audsley, Eric; Pearn, Kerry R.; Simota, C.; Cojocaru, G.; Koutsidou, E.; Rounsevell, M. D. A.; Trnka, M.; Alexandrov, V.Given scenarios describing future climates and socio-techno-economics, this study estimates the consequences for agricultural land use, combining models of crop growth and farm decision making to predict profitability over the whole of Europe, driven solely by soil and climate at each location. Each location is then classified by its profitability as intensive or extensive agriculture or not suitable for agriculture. The main effects of both climate and socio- economics were in the agriculturally marginal areas of Europe. The results showed the effect of different climates is relatively small, whereas there are large variations when economic scenarios are included. Only Finland's agricultural area significantly responds to climate by increasing at the expense of forests in several scenarios. Several locations show more difference due to climate model (PCM versus HadCM3) than emission scenario, because of large differences in predicted precipitation, notably the Ardennes switching to arable in HadCM3. Scenario modelling has identified several such regions where there is a need to be watchful, but few where all of the scenario results agree, suggesting great uncertainty in future projections. Thus, it has not been possible to predict any futures, though all results agree that in Central Europe, changes are likely to be relatively small.