Browsing by Subject "Szenario"

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Developing a biodiversity evaluation tool and scenario design methods for the Greater Mekong Subregion
(2011) Cotter, Marc; Sauerborn, Joachim
The Xishuangbanna Prefecture in Yunnan Province (PR China) is facing increasing conflicts between rural development and nature conservation because of an ongoing expansion and commercialization of farming. The rapid development of large-scale farming and the improvement of infrastructure throughout the region are posing serious threats to the conservation of endemic species of flora and fauna, while also offering possibilities for enhancing the livelihood of rural populations to an extend never seen before. The expansion of rubber (Hevea brasiliensis Willd Ex A. Juss) has caused a reduction and fragmentation of natural and secondary forest cover, thereby decreasing structural and species diversity as well as the loss of valuable ecosystem services. The establishment of intensified agriculture, especially plantations on sloping terrain, often leads to an increased erosion risk, nutrient run-off and sedimentation in water courses. Thus, large scale deforestation is not just a problem for nature conservation but also one for the rural economies. Rural development and simultaneous environment conservation often face trade-offs, especially in regions that host an exceptionally high biodiversity, such as many tropical areas. In order to adequately consider and evaluate these interactions, tools and methods have to be developed that allow decision makers to assess the impacts of different management and infrastructure options on the environment. The aim of the work presented in this thesis was to analyze and evaluate the effect of large-scale rubber cultivation on local and regional biodiversity by developing methods to integrate field studies from various disciplines into a comprehensive assessment model. This model was then used to highlight key aspects of anthropogenic influence on the plant species composition within the research area and to identify possible impacts of alternative land use decisions. Furthermore, the development of an interdisciplinary approach to scientific scenario design methods has been supplemented with a study on the acceptance of 3D-visualization as communication tool for land use planning in the background of nature conservation sciences. In order to achieve this, an overview of the agronomical and ecological aspects of rubber cultivation was provided. Literature sources referring to the impact of different cultivation systems on natural biodiversity were discussed and an introduction to the effect of rubber cultivation on Ecosystem Services was given. A method for projection of regionally adapted carbon capture properties of rubber cultivation under suboptimal growth conditions was presented and a comparative assessment of greenhouse gas emissions during the establishment of rubber plantations in regard to the preexisting vegetation was made. A biodiversity evaluation tool based on the combination of approaches from landscape ecology and empirical data within a Geographic Information System was developed. Detailed data on plant species diversity and distribution were combined with quality criteria like endemism or invasiveness to form spatially explicit biodiversity indices for different land use types in various elevation classes. Up-scaling in accordance to the land use distribution observed allowed the estimation of overall plant diversity and the evaluation of the effect of possible future land use scenarios. Habitat characteristics and spatial distribution were included into the analysis of the land use map derived from remote sensing information to allow for the assessment of fragmentation and landscape matrix structure. The methodology was tested with an array of possible present and future land use maps. It was possible not only to evaluate the different land use classes within and their distribution throughout the research area, but we were also able to compare distinct sub-regions based on topography or administrative status. The challenges stakeholders and nature conservation face in the different elevation zones of Nabanhe were highlighted and related to the findings of our partner workgroups from economy and social sciences. The feasibility of this approach to administration staff with limited experience in ecological modeling was one of the main goals in designing the methods. Given a reasonable data set on species diversity and distribution within any given tropical research area, this approach will enable planners and nature park administration to quickly project possible consequences on species diversity indices deriving from land use change within their respective research area. Using this approach, the importance of natural tropical forests for the maintenance of species diversity in tropical cultivated landscapes was highlighted. With the information gained from constructing this evaluation tool, the design and development process for a land use scenario based on the integration of multidisciplinary assessments and iterative scenario refinement with repeated stakeholder inclusion was promoted. By combining stricter conservation rules with alternative sources of income for the rural population in order to offer an alternative to monoculture rubber farming, the economic models and the land use allocation model predicted a stop in rubber and agriculture related deforestation, and the establishment of a considerable amount of reforested area. This was achieved by introducing an innovative land use type that is closely related to traditional local home garden agroforestry systems. By coupling reforestation efforts with the economic gain derived from intercropping Traditional Chinese Medicinal plants into degraded secondary forests, this scenario was, at least theoretically, able to remove deforestation pressure from the natural forest types and to offer an economic alternative to rubber cultivation. The methods used for this assignment can serve as guideline for future projects that want to implement scenario design procedures based on the combination of social sciences, economics, ecology and landscape planning. The acceptance and comprehensibility of computer based 3D visualization models for the communication of possible future land use scenarios was also tested. Two alternative scenarios were visualized and compared to the status quo, with questionnaires and guided interviews covering the acceptability and adaptability of such techniques for professionals from various fields of nature conservation. This thesis presents an overview over agronomic, economic and ecological aspects of rubber cultivation and highlights its implications on biodiversity and nature conservation. The methods discussed here can serve as a guideline for the integration of ecological indicators in land use planning and decision making processes. Although the concepts and topics introduced herein are closely interlinked within the framework of the Living Landscapes China (LILAC) research project, the methods and approaches can easily be applied to other areas in the Greater Mekong Subregion and beyond, be it the expansion of oil palm plantations in the Malayan Archipelago or the fragmentation of forests due to increased population pressure in Central Africa. Nature conservation is facing similar problems all over the developing world, and adaptable approaches such as the ones presented here are needed to support decision making processes in order to secure the preservation and long-term survival of the worlds? diversity in species and natural habitats.
Regionalising a soil-plant model ensemble to simulate future yields under changing climatic conditions
(2023) Bendel, Daniela Silke; Streck, Thilo
Models are supportive in depicting complex processes and in predicting their effects. Climate models are applied in many areas to assess the possible consequences of climate change. Even though Global Climate Models (GCM) have now been regionalised to the national level, their resolution of down to 5x5 km2 is still rather coarse from the perspective of a plant modeller. Plant models were developed for the field scale and work spatially explicitly. This requires to make adjustments if they are applied at coarser scales. The regionalisation of plant models is reasonable and advantageous against the background of climate change and policy advice, both gaining in importance. The higher the spatial and temporal heterogeneity of a region, the greater the computational need. The (dis)aggregation of data, frequently available in differing resolutions or quality, is often unavoidable and fraught with high uncertainties. In this dissertation, we regionalised a spatially-explicit crop model ensemble to improve yield projections for winter wheat under a changing climate. This involved upscaling a crop model ensemble consisting of three crop models to the Stuttgart region, which has an area of 3,654 km2. After a thorough parameter estimation performed with a varying number of Agricultural Response Units on a high-performance computing cluster, yield projections up to the year 2100 were computed. The representative concentration pathways of the Intergovernmental Panel on Climate Change (IPCC) RCP2.6 (large reduction of CO2 emissions) and RCP8.5 (worst case scenario) served as a framework for this effort. Under both IPCC scenarios, the model ensemble predicts stable winter wheat yields up to 2100, with a moderate decrease of 5 dt/ha for RCP2.6 and a small increase of 1 dt/ha for RCP8.5. The variability within the model ensemble is particularly high for RCP8.5. Results were obtained without accounting for a potential progress in wheat breeding.
Wirtschaftliche Analyse der Tierhaltungsbetriebe um die Metropole Moskau unter besonderer Berücksichtiung von Aufwands- und Ertragsrisiken
(2017) Droganova, Yulia; Fuchs, Clemens
The slow modernisation of the agricultural sector in the Russian Federation after the USSR era, the adoption and the ratification of the Basel Accords, the accession of Russia to the World Trade Organisation in 2012, and finally the crisis in the Ukraine, followed by the import ban on numerous agricultural, fishery products from the EU, USA, Canada, Australia, Norway in August 2014 are the most significant problems which found their reflection in this dissertation. This lead to an increased interest to analyse livestock farms in the Moscow region in consideration of risks in order to predict their profitable development. The goal of the current research was to identify the impending bankruptcy of the Russian livestock farms as early as possible in order to engage in efficient counter planning. The majority of the livestock farms in the Moscow region are dairy farms, which was why this type of livestock farming became the main topic of research for this thesis. The classification of dairy farms into solvent and insolvent farms is based on the application of the multivariate discriminant analysis, a bankruptcy predicting method that is widely used by many banks in Europe and the USA. The risk factor is taken into account in the empirical model of the dairy farm by setting up the stochastic Monte Carlo simulation with the most important random variables (prices, yields and interest rate) in order to quantitatively measure their influence on the economic profitability of a typical dairy farm. Following the results of the discriminant analysis, questions concerning the validation of this model were be raised. What measures were required for the dairy farms, classified as insolvent to deter bankruptcy? This question was examined using a cash flow model, summaries of relevant data and requirements for an empirical model of the dairy farms were collected through interviews of subject experts. On the basis of reference scenario/status quo scenario, three main scenarios were created: Scenario 1 Re-structuring, scenario 2 Improvement of Management and Marketing Activities, and scenario 3 Risk analysis, whereby the measures from scenarios 1 and 2 were stochastically simulated in the scenario 3 Risk analysis in order to be able to estimate the economic risks. From the data set of 31 farms, five typical model farms were selected: two correctly classified solvent, two correctly classified insolvent, and one, which showed up as a type 1 error in the discriminant analysis. A reference scenario describes the data period based on the average values of operational performance from 2008-2010, and the individualized data from the Russian statistics of 2011-2013 and forms a data basis for the scenarios 1 to 3. Scenario 1a Restructuring under Russian Insolvency Law is counterpoised to scenario 1b Restructuring under German Insolvency Law. Scenario 2a Improvement of Management and Marketing Activities without Investment and scenario 2b Improvement of Management and Marketing Activities with Investment contains measures to improve management and marketing. Labour costs were doubled, maintenance, repair costs as well as some other costs were adjusted; while the milk yields, the weight of the dairy cows, the silage yields and the yields of pastures, meadows have been estimated with a logistic function. Over a planning period of twelve years, the dairy farms classified as solvent maximised the increase of their equity capital in scenario 2b, which represents the best result compared to all other scenarios considered. Firstly, it has shown that an adequate insolvency law should support the restructuring process, secondly that training and education, consulting, motivation of employees through higher wages can lead to a better-combined performance in comparison to restructuring. In scenario 3 Risk Analysis, ten relevant random variables and their volatility were simulated and analysed within the frame conditions of the initial Scenarios 1 and 2. In addition, the target values selected were: equity after tax, equity change per hectare of agricultural area, internal equity interest and profit after tax. The presented results explain how on one hand, an adequate insolvency law can support the restructuring process and lead to reinstate solvency of the dairy farms. On the other hand, these results confirm, that the improvements in management can also lead to significant positive achievements in operational performance as opposed to restructuring. The farm, which belongs to type 1 error in the discriminant analysis, has ranked as a solvent dairy farm over the planning period of twelve years in all the scenarios considered. In this case, it can be concluded that the simulation model in the researched composition with the multivariate discriminant analysis has indirectly served to be applicable for validation purposes of the determined discriminant function.