• Energy Research

While it is developing rapidly throughout Germany, bioenergy provision is open to different development opportunities. To understand the cause–effect relationships that drive bioenergy development and explore different development options and their effects on regional development, qualitative scenarios have been drafted using the Gorlitz district as an example. The paper introduces the scenario method, with scenarios that are expressed in storylines. Driving forces and their relationships are thereupon reflected. The results show that the relation of the Common Agricultural Policy and Renewable Energy Act is of particular importance for future development in general. For the specific type of development in particular in rural regions, technologies are equally important, as they allow for both strongly central and highly decentralised developments. Due to an increasing diversity of options, the decision between central and decentral developments is, however, less technologically determined, but rather dependent on stakeholders’ decisions. Such stakeholders not only include stakeholders from the production sector, but also include consumers and affected parties, particularly the inhabitants whose living environment is changing rapidly. Both the landscape and society are subject to change. As a major driving force and an impacted system under change itself, social constellations must be taken into account to ensure a sustainable development under the signs of renewable energy expansion. Management tools should consider the interlinkage between landscape, energy, and social systems.

AbstractDecisions 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 3.5milliontons. 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.

Combining resource-based theory and social exchange theory, this paper studies the role that political connections play in maintaining the sustainability of enterprises’ R&D investment. Furthermore, this paper discusses the moderating effect of policy burdens and ownership on political connections and R&D investment. Based on the Euler equation model, this study used dynamic panel data from Chinese listed companies over the period 2006–2015 to test the hypothesis. The results show that the sustainability of R&D investments of enterprises are more likely to face the threat of financing constraints. However, political connections can help maintain the sustainability of R&D investment of enterprises, but this effect exists only at the local political level, and firms need to undertake a policy burden in return. Additionally, this effect is more effective in private enterprises than non-private enterprises.

The aim of this chapter is to present a bio-economic modelling framework established to provide insight into the complex nature of agricultural systems and to assess the impacts of agricultural and environmental policies and technological innovations. This framework consists of a Farm System Simulator (FSSIM) using mathematical programming that can be linked to a cropping system model to estimate at field level the engineering production and environmental functions. FSSIM includes a module for agricultural management (FSSIM-AM) and a mathematical programming model (FSSIM-MP). FSSIM-AM aims to define current and alternative activities and to quantify their input output coefficients (both yields and environmental effects) using a cropping system model, such as APES (Agricultural Production and Externalities Simulator) and other sources (expert knowledge, surveys, etc.). FSSIM-MP seeks to describe the behaviour of the farmer given a set of biophysical, socio-economic and policy constraints and to predict its reactions under new technologies, policy and market changes. The communication between these different tools and models is based on explicit definitions of spatial scales and software for model integration.

Regional impact studies are needed to explore possible adaptation options to climate change. We estimated impacts and adaptation options for future scenarios that feature different assumptions regarding climate, cropping pattern and access to irrigation with two bio-economic farm models. Farm profit, soil organic matter balance and labor input are used as indicators of farm performance. The difference between the baseline and the alternative configurations computed by models is referred as adaptation potential, indicative of the adaptation options including the corresponding changes in cropping patterns. Our results show that as long as there is sufficient access to irrigation water, there is little incentive to change current practices, as farming is at the economic optimum, has a positive soil organic matter balance and labor requirements can be met. Conversely, if irrigation is no longer possible, drastic impacts occur, causing a need to sustainably adjust on-going farm practices. Adaptation through changed crop selection reduced losses to some extent. We conclude that the use of bio-economic models can assist in evaluating the qualitative findings of participatory studies by quantitatively assessing possible climate change impacts and adaptation measures. Strong impacts of climate change, however, cannot be offset by changes in cropping patterns and need further adaptation measures.

The thesis presents the modeling system MODAM (Multi-Objective Decision support tool for Agroecosystem Management) which was developed at the Centre for Agricultural Landscape and Land Use Research (ZALF) Müncheberg. The aim of the development of MODAM is to foster sustainable development of agricultural landscapes by decision support at farm and at policy level. Therefore, indicators assessing the environmental performance of agricultural activities are included in an economic farm decision model. The hierarchical modeling approach of MODAM is based on relational databases combined with Basic-modules, fuzzy tools and a solver for linear programming problems. A three level approach is performed, in which at the first level a catalogue of production practices is described. The second level consists of economic and environmental evaluation tools, delivering technical, economic and ecological coefficients like potential water erosion risk for each production practice. In the third level, an integrated analyses of all available data is performed by generating a linear programming farm model. MODAM has been applied in several research projects at farm and at regional level, delivering trade-off's and scenario specific land use patterns.

Landscape services are inevitably interlinked with human wellbeing. It is essential to assess landscape services and multifunctionality from both supply and demand points of view toward sustainable landscape management. This study focused on the spatiotemporal variations of the supply, demand, and budget of landscape services in suburban Shanghai, China, including crop production, nutrient regulation, air-quality regulation, soil-erosion regulation, water purification, and recreation and aesthetical value. A new index landscape multifunctionality budget (BMFI) was developed, integrating the budget status of surplus and deficit with landscape management. Spatial autocorrelation analysis and regression analysis were conducted to identify spatial agglomeration and influencing factors of BMFI. Pronounced spatiotemporal heterogeneity of landscape services was observed. BMFI was in surplus status in 2005 and 2010, but turned to deficit in 2015. Landscape service budgets generally followed the spatial pattern of positive in the west and negative in the east. Budget deficits covered half of the villages in 2015, which were mainly situated near central Shanghai with high population density, high average income, and a fragmented and less diverse landscape pattern. Rapid urban sprawl and the following land-cover changes are the main drivers for the spatiotemporal variations. Landscape function zoning with effective economic development and ecological conservation policies can comprehensively improve the competitiveness achieving sustainable future.