Agrarökonomische Forschung : Forschungsbericht

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Agriculture as emission source and carbon sink : economic-ecological modelling for the EU-15
(2010) Blank, Daniel; Zeddies, Jürgen
The thesis develops and applies analytical tools to describe economic and ecological impacts of greenhouse gas mitigation strategies in European agriculture. Agriculture is widely perceived as emission source, but actually it can also act as emission sink by sequestration of atmospheric carbon to agricultural soils. Thereby, soil carbon pools potentially store twice as much carbon as contained in the atmosphere. In view of this circumstance, the study analysed agricultural emission sources and mitigation scenarios in the area of conservation tillage and bio-energy production. The analysis was within a mixed-integer programming model optimizing total gross margins of typical farms of NUTS-II-regions in the EU-15. For this micro-economic analysis high quality region specific cost estimates for main agricultural products were indispensible. Thereby a new approach was developed that draws European accountancy data and German engineering cost data. The first dataset comprises of up-to-date crop-unspecific cost data as indicated by European bookkeeping farms. The second comprises of crop specific cost data from German farms. Through a combination of both datasets crop specific estimates of production costs on regional level for the EU-15 evolved. Another study that starts from accountancy data to deduct product cost estimates is currently funded by the European Commission (Farm Accountancy Cost Estimation and Policy Analysis of European Agriculture). By monetarizing greenhouse gas emissions, the Kyoto-Protocol has increased the demand for economic-ecological models to analyse emission scenarios. The study model, EU-EFEM, integrates biophysical data to site-specifically simulate soil carbon dynamics in terms of the mitigation scenario ?conservational tillage?. This approach provides a level of detail that is significantly superior to the one achieved by soil emission factors specified only to global climate zones, a few soil types, and soil management alternatives like provided by the global standard work for the calculation of greenhouse gas emissions, the guidelines of the Intergovernmental Panel on Climate Change (IPCC). The biophysical data was integrated from the EPIC-model to which an interface was established. In the analysis of the agricultural sink function increased input of organic matter, crop rotational modifications, and conservational tillage were assessed. A first scenario that could be monitored relatively easily forces minimum shares of conservational tillage per farm. It was shown that all farms in the EU-15 could comply even with a forced share of 100%. But on average, shares exceeding 80% entail economic losses, basically because of the incompatibility of certain current crop rotations with conservational tillage. Against the average loss of 20 ?/ha in case of 100% of forced conservational tillage, stand single farms facing a loss of 350 ?/ha. Simultaneously soil carbon accumulation remained at marginal levels. In another scenario that directly forces soil carbon accumulation while leaving the choice of the appropriate means to farmers, an accumulation of 181 million tCO2e was achieved. This value corresponds to a forced accumulation of 1.0 t C/ha, a rate out of reach for 25 out of all analysed NUTS-II-regions. Mitigation costs are at 70 ?/tCO2e in this case, but at 10 ?/tCO2e only if only those regions are considered in which the minimum accumulation rates can be achieved. The latter is a competitive value compared to current values of EU traded emission rights. Policy, however, should withdraw from a regulation forcing minimum SOC-accumulation. Main reasons are the difficult monitoring, which would be required on site level, and the absence of a success guarantee on side of farmers for taken measures. Designing effective political instruments, the humus balance as stipulated in the Cross-Compliance regulation of the reformed AGENDA 2000 represents a prefect starting point. The study also analyzed agricultural biogas production with electricity recovery in a combined heat and power (CHP) unit and different (waste) heat utilization rates. European agriculture could increase annual profits by 1.6 to 9.2 billion ? depending mainly on waste heat utilization rate. In the best case, the contribution to climate change mitigation is 263 Mill tCO2e while realising a mitigation gain of 5 ?/tCO2e when excluding subsidies comprised in the feed-in tariff. Being an issue in any discussion about agricultural bio-energy production, the study also analyses the competition for agricultural land with food and feed production. Tapping the full agricultural biogas production potential, 28.7% of grassland and 18.5% of arable land would be bound, although the study constrains biogas production to co-fermentation with manure. The impacts of this competition on agricultural prices could not be analysed in this study, since the applied model is a farm model and not a market equilibrium model. By means of literature research, however, it was concluded that subsidies of biogas production should focus on promoting the fermentation of manure and the utilization of waste heat in order to limit area competition and not to promote the utilization of cultivated biomass.
Ökonomische Auswirkungen der afrikanischen Schweinepest in Deutschland sowie Konsequenzen für die Seuchenprävention und Seuchenbekämpfung
(2023) Heinrich, Franziska; Bahrs, Enno
Ein Ausbruch der Afrikanischen Schweinepest (ASP), einer Tierseuche welche durch das ASP-Virus ausgelöst wird und nicht als Zoonose gilt, geht neben schwerwiegenden Folgen für die Gesundheit der Schweine auch häufig mit erheblichen ökonomischen Schäden einher. Die ökonomischen Auswirkungen der ASP sind vielfältig und entstehen im Ausbruchsfall nicht nur auf einzelbetrieblicher Ebene für die betroffenen Tierhalter, sondern können sich auch auf andere landwirtschaftliche Betriebe sowie weitere Glieder der Wertschöpfungskette ausweiten und auch andere Stakeholder der Gesamtwirtschaft wie beispielsweise staatliche Institutionen und die Konsumenten betreffen. Ziel der vorliegenden Arbeit ist es, exemplarisch ökonomische Konsequenzen eines ASP-Ausbruchs in Deutschland sowohl auf einzelbetrieblicher als auch auf sektoraler Ebene für Schweinehalter, aber auch für ausgewählte weitere Stakeholder wie Flächenbewirtschafter, Schlachtunternehmen sowie staatliche Institutionen zu untersuchen. Die Auswirkungen werden dabei exemplarisch für verschiedene Seuchenszenarien berechnet. Zur Analyse der ökonomischen Folgen für Schweinemäster und Ferkelerzeugerbetriebe werden die Mindererträge und Mehraufwendungen bei ASP-Ausbruch in vier verschiedenen Untersuchungsregionen ermittelt und durch Übertragung dieser Ergebnisse auf sämtliche deutschen Landkreise regionale Schadenshöhen berechnet. Auf der Basis der ermittelten einzelbetrieblichen Schäden wird die Rentabilität verschiedener Präventionsmaßnahmen wie beispielsweise eines Versicherungsabschlusses untersucht. Da in diesem Zusammenhang Eintrittswahrscheinlichkeiten für einen Seuchenausbruch eine Rolle spielen, werden diese in einem weiteren Teil der Arbeit mittels einer Expertenbefragung zur Identifizierung und Klassifizierung von Risikofaktoren und Parametern zu deren regionaler Abbildbarkeit beleuchtet. Des Weiteren werden Zukunftsperspektiven möglicher Impfstrategien sowie die Auswirkungen künftig erwarteter Veränderungen in der Schweinehaltung auf die ökonomischen Schäden bei einem ASP-Ausbruch beleuchtet. Zusammenfassend zeigen die Berechnungen dieser Arbeit, dass die Haupteffekte der ökonomischen Auswirkungen eines ASP-Ausbruchs aus den zu erwartenden Exportbeschränkungen für Schweinefleisch und den damit verbundenen Preissenkungen für Schweinefleisch resultieren. Für die Gesamtheit der schweinehaltenden Betriebe in den Restriktionsgebieten ergeben sich bei einem ASP-Ausbruch in der Hausschweinpopulation unter der Annahme einer maximalen Sperrzeit von 90 Tagen Mindererträge und Mehraufwendungen von bis zu etwa 10 Mio. Euro in der Untersuchungsregion Nordrhein-Westfalen. Dagegen fallen die Schäden für die Gesamtheit der schweinehaltenden Betriebe im gefährdeten Gebiet bei einem ASP-Ausbruch in der Wildschweinpopulation je nach Region mit 0,8-2,2 Mio. Euro deutlich geringer aus. Dazu kommen hier jedoch Schäden für die Flächenbewirtschafter, die sich durch Nutzungsverbote im gefährdeten Gebiet ergeben und zu Mindererträgen und Mehraufwendungen von etwa 17.133 Euro bis rund 38 Mio. Euro je nach Sperrdauer und Region führen. Durch eine Reduzierung dieser Nutzungsverbote für landwirtschaftliche Flächen lassen sich diese Schäden nach Berechnungen der vorliegenden Arbeit um bis zu etwa 90 % senken, wenn die Restriktionen auf das Kerngebiet beschränkt werden und nicht mehr für das gesamte gefährdete Gebiet gelten. Insgesamt ergibt sich sowohl bei einem ASP-Ausbruch in der Hausschwein- als auch in der Wildschweinpopulation in Deutschland für die Gesamtheit der berücksichtigten Stakeholder ein potentieller Gesamtschaden von jeweils rund 1,4 Mrd. Euro. Dabei spielen vor allem die angenommenen Exportverbote für die Dauer von 12 Monaten und die damit verbundenen erwarteten Preissenkungen eine Rolle. Die Ergebnisse der Arbeit zeigen, wie wichtig Maßnahmen zur Prävention eines ASP-Ausbruchs wie z.B. der Abschluss von Versicherungen und die Umsetzung von Biosicherheitsmaßnahmen sowie politische Bemühungen zur Vereinbarung von Regionalisierungsabkommen zur Begrenzung der Exportbeschränkungen auf direkt betroffene ASP-Gebiete sind, um mögliche Schäden zu minimieren.
Simulation of the sustainability of farming systems in Northern Thailand
(2008) Potchanasin, Chakrit; Zeddies, Jürgen
Introduction Due to an increase in environmental problems and resource degradation, economic development should be pursued with consideration of environmental functions and the supply and quality of natural resources. Monitoring and assessment of whether the development approaches a sustainable path are required to provide information for policy development. This becomes increasingly important ? especially for marginal areas where the environment and natural resources are sensitive. The study area is located in the mountainous area of Northern Thailand with abundant natural resources and a healthy ecological environment. However, population growth, land limitation, and external factors ? such as market forces ? are inducing change and pressure on resource utilization. The resources are intensively used and farming systems are changing to more commercial practices. Therefore, the region?s long term sustainability needs investigation. Objectives This study aims at assessing the sustainability of the farming systems in the study area under the sustainability concept, farming systems approach and Multi-Agent Systems (MAS) approach. The first objective of this study is to describe the characteristics of the farming systems in the study area. The second objective is to develop and use a MAS model to evaluate sustainability of the study area. The last objective is to use the model to present sustainability of farming systems under different scenarios based on changes of significant factors and policy intervention. In addition, the ability of the systems to cope with and recover themselves from these changes is examined. Methodology The sustainability of the farming systems in the study area was assessed through defined indicators representing three conditions: the economic, social and environmental condition. The indicators were defined based on the framework of indicator determination to serve the objectives and methodology of this study. The selected indicators for this study are: household income, net farm income, household capital, household saving, food security, top-soil erosion and fallow period. For these indicators the following sustainability classes were defined: Sustained (S), Conditional sustained (C), and Non-sustained (N) class. Evaluation of sustainability was carried out at two levels: the household and the village level. At the household level the sustainability situation was evaluated based on the individual farm household performance corresponding to each indicator. The sustainability at village level was assessed through the Sustainability index (SI) when single indicators are considered and the Performance index (PI) in which a group of indicators is regarded. The dynamics of the sustainability situation at household and village level were extrapolated over 15 years (2003 ? 2017) in order to examine the sustainability of the study area?s farming systems. The MAS model was developed and named CatchScapeFS. The model structure relies on descriptions of the farming systems in the study area. The MAS approach was applied in order to capture the complexity and extrapolate the long-term sustainability situation in the study area. The model composes of two components: a biophysical and a socioeconomic component. The biophysical component is based on the CatchScape3 model. It consists of biophysical models: a hydrological model, a crop model, a water balance model and a soil erosion model, which are embedded in the landscape model of the study area (represented in spatial grid cells as plots of one rai or 0.16 ha). The socioeconomic component is composed of farm household agents and other social elements. The farm household samples were classified based on the similarity of characteristics and behaviour into the market, subsistence, and partnership oriented group. The Monte Carlo technique was applied to generate farm agents out of the existing farm household samples. The CatchScapeFS model was designed according to the object-oriented modelling approach. The CORMAS platform was selected as a capable tool to facilitate modelling and simulation. During a simulation time step covering 10 days, activities in six principal phases including activities in eight phases of farm agent household activities are executed. The model was validated and tested for its stability. Validation was conducted by social validation and statistic data comparison validation. The results of the model validation and stability test showed the reliability of using the model to serve the study objectives. Main results Sustainability of study area at the household level The results show unsustainability over time in the study area. The number of households in the Sustained class (S) decreases whereas the number in the Non-sustained (N) and Conditional sustained class (C) tend to increase. For the economic condition, unsustained aspects occurred because of rising private household expenditure and decreasing capital products on the farm. For the social condition, the results show an increase of the households? rice deficit and rice acquisition in the long run which enhances the area?s unsustainability. For the environmental condition, erosion and shortening fallow aspects induce the area?s unsustainability. The area?s erosion is severe and increases over time. For the fallow aspect, the average fallow period is shortening because of intensive land use in order to produce for consumption ? which potentially induces land degradation in the long run. Sustainability of the study area at village level Similar to the results at household level, the findings show that farming systems in the study area are not sustainable. Unsustainability was observed by a declining Performance index (PI) and declining Sustainability indexes (SIs) of all indicators in the long term. By considering PI values with the trends, the area?s sustainability in economic condition is better than the social and especially environmental condition. This can be explained by relative high SI values for the economic indicators compared to the SIs of the social and environmental indicators. By considering all SIs and their dynamic trend, sustainability issues can be ranked to determine the sustainability issues which need to be improved. Food security is the most unsustained issue followed by the issues of household saving, household capital, top-soil erosion, household income, fallow period, and net farm income respectively. Scenario analysis The scenarios were the implementation of a policy to improve sustainability and occurrence of unexpected events through changes of biophysical and economic factors. The scenario of the sustainability improving policy is defined as introduction of a high yield variety of upland rice and maize including introduction of mango to the households who currently only produce annual crops. Unexpected events due to the change of biophysical factors were simulated with a drought and rain increasing scenario. A decreasing crop price scenario represented an unexpected event due to the change of an economic factor. Implementation of proposed sustainability improvement policy The results show that the sustainability in the study area is obviously improved; represented by an increase of the PI value with a positive trend over time. In addition, the SIs of many indicators increase in this scenario, except the SI of household saving, which was rather constant. The PI of economic indicators improves with a higher number of households in the sustainable class when considering the household income, net farm income and household capital indicators. For the social condition, PI and SI values of food security increase because of a reduced rice deficit. For the environmental condition, the PI value of the environmental indicators increases because of a reduction of soil erosion and a longer fallow periods. It can be concluded that this scenario provides a policy option which potentially leads to an improvement of the sustainability situation in the study area. Drought scenario The results show that the study area was still unsustainable similar to the baseline scenario. However, the results show a slightly better PI during drought with a higher value and a slower decrease over time. These are the effects of the trade-offs between the indicators. The top-soil erosion indicator (influenced by decreasing rain) becomes better. This positive effect compensates for the negative effects regarding household savings, food security and fallow period indicators ? which all declined. In addition, the simulation results presented the adaptation and reaction of farm agents to drought. Drought is perceived and causes a delay in planting to avoid damage. This induced a variation of the planted area. However, the variation becomes lower because of adaptation as the farm households learn from their experiences. During drought, an increase in the rice and maize deficiency occurred. The average amount of borrowed rice increased over time and the rice acquisition of the farm agents is performed by borrowing from the village rice bank and neighbours In addition, the farm agents acquire maize by collecting wild vegetables to feed their animals. Furthermore, the results indicate the ability of the farm households to cope with and to recover to some extent from a drought. Rain increasing scenario In this scenario, the study area was still unsustainable, similar to the baseline. However, for this scenario, the top-soil erosion is worse because of the increasing rainfall. The PI of economic indicators slightly increased in the first year with increasing rain because of the rising income from livestock production. However, this was caused by random effects influencing the model?s initial stage. For the social condition, there are only small random changes compared to the baseline scenario. For the environmental condition, the PI and SIs of environmental indicators become worse due to an increase of top-soil erosion. Price decreasing scenario The results show that the area?s sustainability is worse compared to the baseline. A reduction of the crop price directly affects household income and cash ? which consequently generates a cash deficit problem. However, due to the area characteristics and household behaviour, there is no effect on resource use because prices do not influence the farm agents? decision making. The PI of this scenario declines faster than in the baseline. This was affected by the decrease of the SIs of the economic indicators which decreased during the periods of the price fall. The households are confronted with a decline in cash which results in a deficiency of cash. Cash acquisition of the households is performed by selling livestock and borrowing from the village fund and neighbours. For the social and environmental condition, there are only small changes due to random effects. Policy recommendations Based on the study results, policies to improve sustainability of the study area farming systems are recommended. Firstly, to improve the area?s sustainability, the introduction of high yield variety of upland rice and maize with conservation practices as well as the introduction of mango to the farm households who currently produce only annual crops is recommended. Secondly, diverting research efforts to develop cash crop alternatives is required in order to improve household cash income. Thirdly, the promotion and support for raising livestock and off-farm activities, such as weaving and the development of tourism, should be performed in order to increase household cash income. Fourthly, awareness raising measures for stakeholders concerning environmental and resource protection have to be executed and achieved. For this, the CatchScapeFS model can be used as a tool to promote a common view between stakeholders. Fifthly, the introduction of birth control in this area is also necessary. Simultaneously, an understanding of households? regarding the effects of population growth should be created in order to obtain the villagers? cooperation without cultural conflicts. Recommendations for further research Guidelines for further studies and applications are recommended. Firstly, development of the model to be more realistic could be undertaken by representing more details of the systems, for example, introducing a nutrient soil dynamic model. However, this should be based on the considered research question (s) and should consider both the marginal benefits and marginal costs of development. Secondly, application of the CatchScapeFS model to other study areas would need to consider the compatibility of the model components and structure of the characteristics in the new study area. In addition, if applied to new areas the indicators to represent sustainability of the study area should be revised. Thirdly, applications following this study framework can be extended to different sustainability approaches ? such as sustainable rural livelihood or sustainable land management. However, the compatibility and relationship of the indicators with the study framework should be considered. Fourthly, a framework through application of object-oriented modelling is recommended as an alternative for further studies to investigate the consequences of policy interventions. However, resource requirements for any research application should be taken into account. Fifthly, the CatchScapeFS model can be used as a tool to test and monitor the effects of potential policies which can be implemented into Bor Krai village. Also, the model can be used as a tool to promote a common view of the overall village systems as well as to support collective decision making managed by stakeholders of the systems. Recommendations for newcomers to MAS application research Suggestions from the present study for newcomers have been proposed. The first recommendation to deal with the MAS application research is that newcomers have to learn the computer programs and programming. Learning programming with advice of programming experts at the beginning period and attention of newcomers to apply the code in different circumstances are highly recommended. Secondly, development of an integrated model in multidisciplinary research requires learning the academic knowledge from other disciplines. Therefore, determining the study objectives within the possible extent, introducing assumptions to simplify the additional disciplines, and consulting specialists to learn the required knowledge within a short time frame are suggested. Lastly, the development of integrated model requires a huge amount of data. Therefore, in the case which required data cannot be obtained, introducing assumptions based on theory and literature is recommended.

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