Search

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 rapid What-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. [ABSTRACT FROM AUTHOR]

This paper uses two models to examine the direct and indirect costs of sea-level rise for Europe for a range of sea-level rise scenarios for the 2020s and 2080s: (1) the DIVA model to estimate the physical impacts of sea-level rise and the direct economic cost, including adaptation, and (2) the GTAP-EF model to assess the indirect economic implications. Without adaptation, impacts are quite significant with a large land loss and increase in the incidence of coastal flooding. By the end of the century Malta has the largest relative land loss at 12% of its total surface area, followed by Greece at 3.5% land loss. Economic losses are however larger in Poland and Germany ($483 and $391 million, respectively). Coastal protection is very effective in reducing these impacts and optimally undertaken leads to protection levels that are higher than 85% in the majority of European states. While the direct economic impact of sea-level rise is always negative, the final impact on countries' economic performances estimated with the GTAP-EF model may be positive or negative. This is because factor substitution, international trade, and changes in investment patterns interact with possible positive implications. The policy insights are (1) while sea-level rise has negative and huge direct economic effects, overall effects on GDP are quite small (max −0.046% in Poland); (2) the impact of sea-level rise is not confined to the coastal zone and sea-level rise indirectly affects landlocked countries as well (Austria for instance loses −0.003% of its GDP); and (3) adaptation is crucial to keep the negative impacts of sea-level rise at an acceptable level. [ABSTRACT FROM AUTHOR]