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Lotze-Campen, H.; von Witzke, H.; Noleppa, S.; Schwarz, G. |
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Title |
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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Year |
2015 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
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136 |
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79-84 |
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Keywords |
Plant breeding; CO2 emissions; Cost–benefit analysis; Social rate of return; Agricultural research policy |
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Abstract |
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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Mitter, H.; Schmid, E.; Sinabell, F. |
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Title |
Integrated modelling of protein crop production responses to climate change and agricultural policy scenarios in Austria |
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Journal Article |
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Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
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65 |
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205-220 |
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Climate change impact; Adaptation; Soybean; EPIC; Common Agricultural Policy; Land use |
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Abstract |
Climate and policy changes are likely to affect protein crop production and thus trade balances in Europe, which is highly dependent on imports. Exemplified for Austrian cropland, we developed an integrated modelling framework to analyze climate change and policy scenario impacts on protein crop production and environmental outcomes. The integrated modelling framework consists of a statistical climate change model, a crop rotation model, the bio-physical process model EPIC, and the economic bottom-up land use optimization model BiomAT. EPIC is applied to simulate annual dry matter crop yields for different crop management practices including crop rotations, fertilization intensities, and irrigation, as well as for 3 regional climate change scenarios until 2040 at a 1 km grid resolution. BiomAT maximizes total gross margins by optimizing land use choices and crop management practices subject to spatially explicit cropland endowments. The model results indicate that changes in agricultural policy conditions, cropland use, and higher flexibility in crop management practices may reduce protein import dependence under changing climatic conditions. Expanding protein crop production is most attractive in south-eastern Austria with its Central European continental climate where maize is most often replaced in crop rotations. However, the acreage of protein crops is limited by agronomically suitable cropland. An intended side effect is the reduction of nitrogen fertilizer inputs by about 0.1% if total protein crop production increases by 1%. |
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0936-577x |
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TradeM, ft_macsur |
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MA @ admin @ |
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5012 |
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Yin, X.; Olesen, J.E.; Wang, M.; Kersebaum, K.-C.; Chen, H.; Baby, S.; Öztürk, I.; Chen, F. |
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Title |
Adapting maize production to drought in the Northeast Farming Region of China |
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Journal Article |
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2016 |
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European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
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77 |
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47-58 |
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Drought; Maize production; Adaptation strategies; Household characteristics; Policy support; The Northeast Farming Region of China; climate change; Jilin province; water-stress; sowing date; yield; risk; tolerance; impacts; corn; agriculture |
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Maize (Zea mays L.) is the most prominent crop in the Northeast Farming Region of China (NFR), and drought has been the largest limitation for maize production in this area during recent decades. The question of how to adapt maize production to drought has received great attention from policy makers, researchers and farmers. In order to evaluate the effects of adaptation strategies against drought and examine the influences of policy supports and farmer households’ characteristics on adopting decisions, a large scale household survey was conducted in five representative maize production counties across NFR. Our survey results indicated that using variety diversification, drought resistant varieties and dibbling irrigation are the three major adaptation strategies against drought in spring, and farmers also adopted changes in sowing time, conservation tillage and mulching to cope with drought in spring. About 20% and 18% of households enhanced irrigation against drought in summer and autumn, respectively. Deep loosening tillage and organic fertilizer are also options for farmers to resist drought in summer. Maize yield was highly dependent on soil qualities, with yields on land of high soil quality approximately 1050 kg/ha and 2400 kg/ha higher than for normal and poor soil conditions, respectively. Using variety diversification and drought resistant varieties can respectively increase maize yield by approximately 150 and 220 kg/ha under drought. Conservation tillage increased maize yield by 438–459 kg/ha in drought years. Irrigation improved maize yield by 419–435 kg/ha and 444–463 kg/ha against drought in summer and autumn, respectively. Offering information service, financial and technical support can greatly increase the use of adaptation strategies for farmers to cope with drought. However, only 46% of households received information service, 43% of households received financial support, and 26% of households received technical support against drought from the local government. The maize acreage and the irrigation access are the major factors that influenced farmers’ decisions to apply adaptation strategies to cope with drought in each season, but only 25% of households have access to irrigation. This indicates the need for enhanced public support for farmers to better cope with drought in maize production, particularly through improving access to irrigation. |
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2016-10-31 |
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1161-0301 |
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CropM, ft_macsur |
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MA @ admin @ |
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4825 |
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Cortignani, R.; Dono, G. |
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Simulation of the impact of greening measures in an agricultural area of the southern Italy |
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Journal Article |
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2015 |
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Land Use Policy |
Abbreviated Journal |
Land Use Policy |
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48 |
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525-533 |
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agricultural policy; supply analysis; mathematical programming; maximum-entropy; level; models |
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Together, sustainable management of natural resources and climate action form one of the three objectives of the 2014-2020 Common Agricultural Policy. This objective is being addressed by replacing the existing direct payments under Pillar 1 with a basic payment, combined with an additional payment conditional on farmers undertaking agricultural practices beneficial for the climate and the environment, a policy referred to as greening. In this study, the impact of greening was assessed using a hybrid model calibrated using positive mathematical programming. The model describes the macro-types of farm production in a Mediterranean agricultural area. The results show that greening was not beneficial throughout the study area and only some farm types have been particularly affected. However, greening appears to have a positive impact on curtailing the use of chemicals, particularly nitrogen, and on crop diversity. (C) 2015 Elsevier Ltd. All rights reserved. |
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0264-8377 |
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TradeM, ft_macsur |
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MA @ admin @ |
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4746 |
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Kipling, R.P.; Bannink, A.; Bellocchi, G.; Dalgaard, T.; Fox, N.J.; Hutchings, N.J.; Kjeldsen, C.; Lacetera, N.; Sinabell, F.; Topp, C.F.E.; van Oijen, M.; Virkajärvi, P.; Scollan, N.D. |
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Title |
Modeling European ruminant production systems: Facing the challenges of climate change |
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Journal Article |
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Year |
2016 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agricultural Systems |
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147 |
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24-37 |
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Food security; Livestock systems; Modeling; Pastoral systems; Policy support; Ruminants |
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Ruminant production systems are important producers of food, support rural communities and culture, and help to maintain a range of ecosystem services including the sequestering of carbon in grassland soils. However, these systems also contribute significantly to climate change through greenhouse gas (GHG) emissions, while intensi- fication of production has driven biodiversity and nutrient loss, and soil degradation. Modeling can offer insights into the complexity underlying the relationships between climate change, management and policy choices, food production, and the maintenance of ecosystem services. This paper 1) provides an overview of how ruminant systems modeling supports the efforts of stakeholders and policymakers to predict, mitigate and adapt to climate change and 2) provides ideas for enhancing modeling to fulfil this role. Many grassland models can predict plant growth, yield and GHG emissions from mono-specific swards, but modeling multi-species swards, grassland quality and the impact of management changes requires further development. Current livestock models provide a good basis for predicting animal production; linking these with models of animal health and disease is a prior- ity. Farm-scale modeling provides tools for policymakers to predict the emissions of GHG and other pollutants from livestock farms, and to support the management decisions of farmers from environmental and economic standpoints. Other models focus on how policy and associated management changes affect a range of economic and environmental variables at regional, national and European scales. Models at larger scales generally utilise more empirical approaches than those applied at animal, field and farm-scales and include assumptions which may not be valid under climate change conditions. It is therefore important to continue to develop more realistic representations of processes in regional and global models, using the understanding gained from finer-scale modeling. An iterative process of model development, in which lessons learnt from mechanistic models are ap- plied to develop ‘smart’ empirical modeling, may overcome the trade-off between complexity and usability. De- veloping the modeling capacity to tackle the complex challenges related to climate change, is reliant on closer links between modelers and experimental researchers, and also requires knowledge-sharing and increasing technical compatibility across modeling disciplines. Stakeholder engagement throughout the process of model development and application is vital for the creation of relevant models, and important in reducing problems re- lated to the interpretation of modeling outcomes. Enabling modeling to meet the demands of policymakers and other stakeholders under climate change will require collaboration within adequately-resourced, long-term inter-disciplinary research networks |
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0308521x |
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LiveM, ft_macsur |
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MA @ admin @ |
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4734 |
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