| Records |
Author  |
Gutzler, C.; Helming, K.; Balla, D.; Dannowski, R.; Deumlich, D.; Glemnitz, M.; Knierim, A.; Mirschel, W.; Nendel, C.; Paul, C.; Sieber, S.; Stachow, U.; Starick, A.; Wieland, R.; Wurbs, A.; Zander, P. |
| Title |
Agricultural land use changes – a scenario-based sustainability impact assessment for Brandenburg, Germany |
Type |
Journal Article |
| Year |
2015 |
Publication |
Ecological Indicators |
Abbreviated Journal |
Ecological Indicators |
| Volume |
48 |
Issue |
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Pages |
505-517 |
| Keywords |
scenarios; impact assessment; agricultural intensification; land use change; irrigation; bioenergy; social and environmental indicators; climate-change; landscape; model |
| Abstract |
Decisions for agricultural management are taken at farm scale. However, such decisions may well impact upon regional sustainability. Two of the likely agricultural management responses to future challenges are extended use of irrigation and increased production of energy crops. The drivers for these are high commodity prices and subsidy policies for renewable energy. However, the impacts of these responses upon regional sustainability are unknown. Thus, we conducted integrated impact assessments for agricultural intensification scenarios in the federal state of Brandenburg, Germany, for 2025. One Irrigation scenario and one Energy scenario were contrasted with the Business As Usual (BAU) scenario. We applied nine indicators to analyze the economic, social and environmental effects at the regional, in this case district scale, which is the smallest administrative unit in Brandenburg. Assessment results were discussed in a stakeholder workshop involving 16 experts from the state government. The simulated area shares of silage maize for fodder and energy were 29%, 37% and 49% for the BAU, Irrigation, and Energy scenarios, respectively. The Energy scenario increased bio-electricity production to 41% of the demand of Brandenburg, and it resulted in CO2 savings of up to 3.5 million tons. However, it resulted in loss of biodiversity, loss of landscape scenery, increased soil erosion risk, and increased area demand for water protection requirements. The Irrigation scenario led to yield increases of 7% (rapeseed), 18% (wheat, sugar beet), and 40% (maize) compared to the BAU scenario. It also reduced the year-to-year yield variability. Water demand for irrigation was found to be in conflict with other water uses for two of the 14 districts. Spatial differentiation of scenario impacts showed that districts with medium to low yield potentials were more affected by negative impacts than districts with high yield potentials. In this first comprehensive sustainability impact assessment of agricultural intensification scenarios at regional level, we showed that a considerable potential for agricultural intensification exists. The intensification is accompanied by adverse environmental and socio-economic impacts. The novelty lies in the multiscale integration of comprehensive, agricultural management simulations with regional level impact assessment, which was achieved with the adequate use of indicators. It provided relevant evidence for policy decision making. Stakeholders appreciated the integrative approach of the assessment, which substantiated ongoing discussions among the government bodies. The assessment approach and the Brandenburg case study may stay exemplary for other regions in the world where similar economic and policy driving forces are likely to lead to agricultural intensification. (C) 2014 The Authors. Published by Elsevier Ltd. |
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1470-160x |
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CropM |
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no |
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MA @ admin @ |
Serial |
4561 |
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| Author |
Vilvert, E.; Lana, M.; Zander, P.; Sieber, S. |
| Title |
Multi-model approach for assessing the sunflower food value chain in Tanzania |
Type |
Journal Article |
| Year |
2018 |
Publication |
Agricultural Systems |
Abbreviated Journal |
Agric. Syst. |
| Volume |
159 |
Issue |
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Pages |
103-110 |
| Keywords |
Sunflower; Food value chain; Modelling; Tanzania; Food security; Systems Simulation; Crop Model; Agricultural Systems; Farming Systems; Yield Response; Land-Use; Water; Aquacrop; Security; Stics |
| Abstract |
Sunflower is one of the major oilseeds produced in Tanzania, but due to insufficient domestic production more than half of the country’s demand is imported. The improvement of the sunflower food value chain (FVC) understanding is important to ensure an increase in the production, availability, and quality of edible oil. In order to analyse causes and propose solutions to increase the production of sunflower oil, a conceptual framework that proposes the combined use of different models to provide insights about the sunflower FVC was developed. This research focus on the identification of agricultural models that can provide a better understanding of the sunflower FVC in Tanzania, especially within the context of food security improvement. A FVC scheme was designed considering the main steps of sunflower production. Thereafter, relevant models were selected and placed along each step of the FVC. As result, the sunflower FVC model in Tanzania is organized in five steps, namely (1) natural resources; (2) crop production; (3) oil processing; (4) trade; and (5) consumption. Step 1 uses environmental indicators to analyse soil parameters on soil-water models (SWAT, LPJmL, APSIM or CroSyst), with outputs providing data for step 2 of the FVC. In the production step, data from step 1, together with other inputs, is used to run crop models (DSSAT, HERMES, MONICA, STICS, EPIC or AquaCrop) that analyse the impact on sunflower yields. Thereafter, outputs from crop models serve as input for bio-economic farm models (FSSIM or MODAM) to estimate production costs and farm income by optimizing resource allocation planning for step 2. In addition, outputs from crop models are used as inputs for macro-economic models (GTAP, MAGNET or MagPie) by adjusting supply functions and environmental impacts within steps 3, 4, and 5. These models simulate supply and demand, including the processing of products to determine prices and trade volumes at market equilibrium. In turn, these data is used by bio-economic farm models to assess sunflower returns for different farm types and agro-environmental conditions. Due to the large variety of models, it is possible to assess significant parts of the FVC, reducing the need to make assumptions, while improving the understanding of the FVC. |
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2018-01-25 |
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0308-521x |
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CropM, TradeM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
5187 |
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| Author |
Zander, P. |
| Title |
Modelling regional agricultural land use and climate change adaptation strategies in 4 case study regions Northern Germany |
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2015 |
Publication |
FACCE MACSUR Reports |
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4 |
Issue |
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Pages |
SP4-22 |
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TradeM International Workshop 2014 »Economics of integrated assessment approaches for agriculture and the food sector«, 25–27 November 2014, Hurdalsjø, Norway |
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no |
| Call Number |
MA @ admin @ |
Serial |
2212 |
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| Author |
Zander, P. |
| Title |
Scenarios of regional agricultural land use under climate change for 4 case study regions in Northern Germany |
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2015 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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| Volume |
5 |
Issue |
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Pages |
Sp5-73 |
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| Abstract |
Agricultural land use in Northern Germany is characterized by a gradient of decreasing precipitation from west to east. Climate change is expected to increase temperature and decrease summer precipitation. In the context of a nationally funded project we aim to analyze climate change adaptation strategies for agricultural land use. The research is focused in 4 study regions from Eastern to Western Germany. The presented modelling approach analyses agricultural land use under climate change and for three policy scenarios (business as usual, biodiversity and climate protection). The biodiversity and climate protection scenarios each reserve area for specific scenario objectives: 10% for specific biodiversity measures and 20% for N-fixing legumes in case of the climate protection scenario. All scenarios are executed for three time steps representing year 2010, 2020 and 2030 with a constant yield increase, extrapolated from past observations. Building on IACS data for a farm typology and expert assessments of current and future land use options, we applied a linear programming farm model. Prices are exogenous and derived from CAPRI model runs for 2020 and 2030. First preliminary results show strong impacts of price assumptions and yield assessments. This results in 2020 in lower gross margins for a number of crops and finally to higher set aside areas in eastern Germany. For 2030 input–output price relations are more favourable for farmers and thus lead to lower set aside areas. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
2188 |
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| Author |
Zander, P. |
| Title |
Modelling regional land use and climate change adaptation strategies in NorthernGermany |
Type |
Conference Article |
| Year |
2013 |
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TradeM |
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MACSUR TradeM workshop: Exploring new ideas for trade and agriculture model integration for assessing the impacts of climate change on food security, The Natural Resource and Environmental Research Center (NRERC), University of Haifa, Israel, 2013-03-03 t |
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no |
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MA @ admin @ |
Serial |
2914 |
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