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Stürck, J.; Levers, C.; van der Zanden, E.H.; Schulp, C.J.E.; Verkerk, P.J.; Kuemmerle, T.; Helming, J.; Lotze-Campen, H.; Tabeau, A.; Popp, A.; Schrammeijer, E.; Verburg, P. |
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Title |
Simulating and delineating future land change trajectories across Europe |
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Journal Article |
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Year |
2015 |
Publication |
Regional Environmental Change |
Abbreviated Journal |
Reg. Environ. Change |
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in press |
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land use change; land system; modeling; scenario; Europe; ecosystem services |
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Explorations of future land use change are important to understand potential conflicts between competing land uses, trade-offs associated with particular land change trajectories, and the effectiveness of policies to steer land systems into desirable states. Most model-based explorations and scenario studies focused on conversions in broad land use classes, but disregarded changes in land management or focused on individual sectors only. Using the European Union (EU) as a case study, we developed an approach to identifying typical combinations of land cover and management changes by combining the results of multimodel simulations in the agriculture and forest sectors for four scenarios from 2000 to 2040. We visualized land change trajectories by mapping regional hotspots of change. Land change trajectories differed in extent and spatial pattern across the EU and among scenarios, indicating trajectory-specific option spaces for alternative land system outcomes. In spite of the large variation in the area of change, similar hotspots of land change were observed among the scenarios. All scenarios indicate a stronger polarization of land use in Europe, with a loss of multifunctional landscapes. We analyzed locations subject to change by comparing location characteristics associated with certain land change trajectories. Results indicate differences in the location conditions of different land change trajectories, with diverging impacts on ecosystem service provisioning. Policy and planning for future land use needs to account for the spatial variation of land change trajectories to achieve both overarching and location-specific targets. |
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1436-3798 |
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MA @ admin @ |
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4996 |
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Bodirsky, B.L.; Rolinski, S.; Biewald, A.; Weindl, I.; Popp, A.; Lotze-Campen, H. |
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Global Food Demand Scenarios for the 21st Century |
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Journal Article |
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2015 |
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PLoS One |
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PLoS One |
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10 |
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11 |
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e0139201 |
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Long-term food demand scenarios are an important tool for studying global food security and for analysing the environmental impacts of agriculture. We provide a simple and transparent method to create scenarios for future plant-based and animal-based calorie demand, using time-dependent regression models between calorie demand and income. The scenarios can be customized to a specific storyline by using different input data for gross domestic product (GDP) and population projections and by assuming different functional forms of the regressions. Our results confirm that total calorie demand increases with income, but we also found a non-income related positive time-trend. The share of animal-based calories is estimated to rise strongly with income for low-income groups. For high income groups, two ambiguous relations between income and the share of animal-based products are consistent with historical data: First, a positive relation with a strong negative time-trend and second a negative relation with a slight negative time-trend. The fits of our regressions are highly significant and our results compare well to other food demand estimates. The method is exemplarily used to construct four food demand scenarios until the year 2100 based on the storylines of the IPCC Special Report on Emissions Scenarios (SRES). We find in all scenarios a strong increase of global food demand until 2050 with an increasing share of animal-based products, especially in developing countries. |
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1932-6203 |
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TradeM, ftnotmacsur |
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4997 |
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Humpenöder, F.; Popp, A.; Stevanovic, M.; Müller, C.; Bodirsky, B.L.; Bonsch, M.; Dietrich, J.P.; Lotze-Campen, H.; Weindl, I.; Biewald, A.; Rolinski, S. |
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Land-use and carbon cycle responses to moderate climate change: implications for land-based mitigation |
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2015 |
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Environmental Science and Technology |
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Environ Sci Technol |
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49 |
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11 |
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6731-6739 |
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Climate change has impacts on agricultural yields, which could alter cropland requirements and hence deforestation rates. Thus, land-use responses to climate change might influence terrestrial carbon stocks. Moreover, climate change could alter the carbon storage capacity of the terrestrial biosphere and hence the land-based mitigation potential. We use a global spatially explicit economic land-use optimization model to (a) estimate the mitigation potential of a climate policy that provides economic incentives for carbon stock conservation and enhancement, (b) simulate land-use and carbon cycle responses to moderate climate change (RCP2.6), and (c) investigate the combined effects throughout the 21st century. The climate policy immediately stops deforestation and strongly increases afforestation, resulting in a global mitigation potential of 191 GtC in 2100. Climate change increases terrestrial carbon stocks not only directly through enhanced carbon sequestration (62 GtC by 2100) but also indirectly through less deforestation due to higher crop yields (16 GtC by 2100). However, such beneficial climate impacts increase the potential of the climate policy only marginally, as the potential is already large under static climatic conditions. In the broader picture, this study highlights the importance of land-use dynamics for modeling carbon cycle responses to climate change in integrated assessment modeling. |
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0013-936x |
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TradeM, ftnotmacsur |
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MA @ admin @ |
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4998 |
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Lotze-Campen, H.; von Witzke, H.; Noleppa, S.; Schwarz, G. |
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Science for food, climate protection and welfare: An economic analysis of plant breeding research in Germany |
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Journal Article |
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2015 |
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Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
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136 |
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79-84 |
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Plant breeding; CO2 emissions; Cost–benefit analysis; Social rate of return; Agricultural research policy |
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Highlights • We analyze the economic effects of plant breeding research in Germany. • Effects of reduced CO2 emissions due to productivity increases are being quantified. • Expansion of global agricultural area has been reduced by 1–1.5 million ha. • CO2 emissions have been reduced by 160–235 million tons. • German plant breeding research has an economic value of 10.8–15.6 billion EUR. Abstract We analyze the economic effects of plant breeding research in Germany. In addition to market effects, for the first time also effects of reduced CO2 emissions due to productivity increases are being quantified. The analysis shows that investments in German plant breeding research in the period 1991–2010 have reduced the global expansion of agricultural area by 1–1.5 million hectares. This has led to reduced CO2 emissions of 160–235 million tons. The economic value generated by plant breeding research, through increased production and reduced greenhouse gas emissions, is estimated at 10.8–15.6 billion EUR in the same period. This can be translated into a social rate of return on research investment in the range of 40–80% per year. Projections for the period 2011–2030 generate a return rate in the range of 65–140% per year. Investments into plant breeding research in Germany are highly profitable from a societal point of view. At the same time, our results show significant under-investments in agricultural research in Germany. These results provide a good justification for policy-makers to reverse funding cuts for public agricultural research over the last decades and to improve institutional conditions for private research, e.g. through better protection of intellectual property rights. |
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0308521x |
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TradeM, ftnotmacsur |
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MA @ admin @ |
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4999 |
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Wang, X.; Biewald, A.; Dietrich, J.P.; Schmitz, C.; Lotze-Campen, H.; Humpenöder, F.; Bodirsky, B.L.; Popp, A. |
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Taking account of governance: Implications for land-use dynamics, food prices, and trade patterns |
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Journal Article |
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2016 |
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Ecological Economics |
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Ecol. Econ. |
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122 |
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12-24 |
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Highlights • Governance impacts on land use dynamics are modeled at the global scale with an agro-economic dynamic optimization model. • Improved governance performance lowers deforestation, reduces cropland expansion and increases agricultural yield. • Good governance makes a decisive difference in investment for increasing yields in developing regions. • Weak governance increases food prices, particularly in Sub-Saharan Africa and Southeast Asia. • Improving governance performance has significant impacts on poverty reduction. Abstract Deforestation, mainly caused by unsustainable agricultural expansion, results in a loss of biodiversity and an increase in greenhouse gas emissions, as well as impinges on local livelihoods. Countries’ governance performance, particularly with respect to property rights security, exerts significant impacts on land-use patterns by affecting agricultural yield-related technological investment and cropland expansion. This study aims to incorporate governance factors into a recursive agro-economic dynamic model to simulate governance impacts on land-use patterns at the global scale. Due to the difficulties of including governance indicators directly into numerical models, we use lending interest rates as discount rates to reflect risk-accounting factors associated with different governance scenarios. In addition to a reference scenario, three scenarios with high, low and mixed divergent discount rates are formed to represent weak, strong and fragmented governance. We find that weak governance leads to slower yield growth, increased cropland expansion and associated deforestation, mainly in Latin America, Sub-Saharan Africa, South Asia and Southeast Asia. This is associated with increasing food prices, particularly in Sub-Saharan Africa and Southeast Asia. By contrast, strong governance performance provides a stable political and economic situation which may bring down deforestation rates, stimulate investment in agricultural technologies, and induce fairly strong decreases in food prices. |
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0921-8009 |
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TradeM, ftnotmacsur |
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MA @ admin @ |
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5002 |
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