REDUCING GHG EMISSIONS BY ABANDONING AGRICULTURAL LAND USE ON ORGANIC SOILS

6.5% of the German UAA is located on organic soils (fens and bogs). Nevertheless, the drainage of these areas in order to allow their agricultural utilization causes roughly a third of the greenhouse gas emissions (GHG) of the German agricultural sector, being equivalent to 4% of the total German GHG emissions. Obviously, German policies trying to reduce the GHG emissions successfully must tackle this issue. The abandonment of the cultivation of organic soils would be an effective policy to reduce the GHG emissions however the question remains whether it is an efficient measure compared with the other options? In the paper we compare the land use on mineral and organic soils using the data of the farm structure survey. We assess the mitigation costs on the basis of the standard gross margin of the agriculturally used peatlands and with the sector model RAUMIS. Without engineering and transaction costs the mitigation costs are in the magnitude of 10 to 45 € per to of CO2eq.. This makes rewetting of peatlands at least in the medium and long run a fairly efficient options for reducing GHG emissions, especially as the implications on the sector are fairly small due to reallocation affects.Agricultural and Food Policy, Environmental Economics and Policy, Resource /Energy Economics and Policy,

Which parameters determine farm development in Germany?

In 2005, Germany implemented the Single Payment Scheme which lead to the conversion of direct payments into tradable, production decoupled, single farm payments. The transition from coupled to decoupled support instruments may impact the rate of structural change. The rate of structural change may accelerate since farms with a high share of income derived from CAP payments will abandon farming and lease their land. However, there are also good reasons why the rate of structural change might decrease especially if farmers do not behave as profit maximizers. In Germany agricultural land use is very heterogeneous with respect to management orientation and productivity even at local level. Most of the concerns related to structural change and development of land use intensity, e.g. abandonment of high nature value farmland, are only relevant in a very specific local context. Therefore, it is necessary to establish indicators for farm development on adisaggregated level. The objective of this paper is twofold. First, we derive criteria and threshold values to classify regions according to their respective natural, socio economic conditions and land use. Second, we evaluate the stability of the link between a set of explanatory variables and the rate of structural change at different spatial scales. Our results indicate that only for a few variables a generally valid link between them and the rate of structural change can be established. For the majority of the explanatory variables, their respective impact on structural change depends heavily on the regional context.Structural change, Data mining, Fischler Reform, Agricultural and Food Policy, Q16, Q15, R14,

Salvage the treasure of geographic information in Farm census data

In Germany, since several decades the RAUMIS modelling system is applied for policy impact assessments to measure the impact of agriculture on the environment. A disaggregation at the municipality level with more than 9.600 administrative units, instead of currently used 316 counties, would tremendously improve the environmental impact analysis. Two sets of data are used for this purpose. The first are geo-referenced data, that are, however, incomplete with respect its coverage of production activities in agriculture. The second set is the micro census statistic itself, that has a full coverage, but data protection rules (DPR) prohibit its straightforward use. The paper show how this bottleneck can be passed to obtain a reliable modelling data set at municipality level with a complete coverage of the agricultural sector in Germany. We successfully applied a Bayesian estimator, that uses prior information derived a cluster analysis based on the micro census and GIS information. Our test statistics of the estimation, calculated by the statistical office, comparing our estimates and the real protected data, reveals that the proposed approach adequately estimates most activities and can be used to fed the municipality layer in the RAUMIS modelling system for an extended policy analysis.Highest Posterior Density estimator (HPD), RAUMIS, Down scaling, Research Methods/ Statistical Methods, C11, C61, C81, Q15,

Integrating small farms in agent based models

In German agriculture structural change is mainly a result of the outmigration of smaller farms from the sector. The decisions of these farmers to leave or stay in the sector, are not based solely on financial data and market expectations. Other aspects are important such as the preservation of the cultural landscape, the continuation of the family tradition, or self-realisation. Only if these goals are adequately integrated into land use models, one can hope that the type and magnitude of reactions predicted by the model will be similar to that observed in reality. The main goal of this paper is to present a model approach that allows for the integration of non-monetary aspects into an agri-economic land use model. The approach is tested for a sample of 20 farms located in a municipality in the Bavarian Alps. The results show that the choice of the farmers’ attitude has a larger impact on results than the peculiarities of the policy scenario. This holds especially for the emerging farm structure but also for the general land use intensity

Which parameters determine farm development in Germany?

In 2005, Germany implemented the Single Payment Scheme which lead to the conversion of direct payments into tradable, production decoupled, single farm payments. The transition from coupled to decoupled support instruments may impact the rate of structural change. The rate of structural change may accelerate since farms with a high share of income derived from CAP payments will abandon farming and lease their land. However, there are also good reasons why the rate of structural change might decrease especially if farmers do not behave as profit maximizers. In Germany agricultural land use is very heterogeneous with respect to management orientation and productivity even at local level. Most of the concerns related to structural change and development of land use intensity, e.g. abandonment of high nature value farmland, are only relevant in a very specific local context. Therefore, it is necessary to establish indicators for farm development on adisaggregated level. The objective of this paper is twofold. First, we derive criteria and threshold values to classify regions according to their respective natural, socio economic conditions and land use. Second, we evaluate the stability of the link between a set of explanatory variables and the rate of structural change at different spatial scales. Our results indicate that only for a few variables a generally valid link between them and the rate of structural change can be established. For the majority of the explanatory variables, their respective impact on structural change depends heavily on the regional context

Reducing GHG emissions by abandoning agricultural land use on organic soils - A cost assessment -

Roughly 4.9% of the German utilized agricultural area is located on organic soils (fens and bogs). Nevertheless, the drainage of these areas in order to allow their agricultural utilization causes roughly a third of the greenhouse gas emissions (GHG) of the German agricultural sector, being equivalent to 2.3% of the total German GHG emissions. Obviously, German policies trying to reduce the GHG emissions successfully must tackle this issue. The abandonment of the cultivation of organic soils would be an effective policy to reduce the GHG emissions however the question remains whether it is an efficient measure compared with the other options? In the paper we assess the mitigation costs on the basis of the standard gross margin and tenure of the agriculturally used peatlands and with the sector model RAUMIS. Without engineering and transaction costs the mitigation costs are below 50 € per Mg CO2eq. This makes rewetting of peatlands at least in the medium and long run a fairly efficient options for reducing GHG emissions, especially as the implications on the sector due to reallocation affects are fairly small

Salvage the treasure of geographic information in Farm census data

In Germany, since several decades the RAUMIS modelling system is applied for policy impact assessments to measure the impact of agriculture on the environment. A disaggregation at the municipality level with more than 9.600 administrative units, instead of currently used 316 counties, would tremendously improve the environmental impact analysis. Two sets of data are used for this purpose. The first are geo-referenced data, that are, however, incomplete with respect its coverage of production activities in agriculture. The second set is the micro census statistic itself, that has a full coverage, but data protection rules (DPR) prohibit its straightforward use. The paper show how this bottleneck can be passed to obtain a reliable modelling data set at municipality level with a complete coverage of the agricultural sector in Germany. We successfully applied a Bayesian estimator, that uses prior information derived a cluster analysis based on the micro census and GIS information. Our test statistics of the estimation, calculated by the statistical office, comparing our estimates and the real protected data, reveals that the proposed approach adequately estimates most activities and can be used to fed the municipality layer in the RAUMIS modelling system for an extended policy analysis

REDUCING GHG EMISSIONS BY ABANDONING AGRICULTURAL LAND USE ON ORGANIC SOILS

6.5% of the German UAA is located on organic soils (fens and bogs). Nevertheless, the drainage of these areas in order to allow their agricultural utilization causes roughly a third of the greenhouse gas emissions (GHG) of the German agricultural sector, being equivalent to 4% of the total German GHG emissions. Obviously, German policies trying to reduce the GHG emissions successfully must tackle this issue. The abandonment of the cultivation of organic soils would be an effective policy to reduce the GHG emissions however the question remains whether it is an efficient measure compared with the other options? In the paper we compare the land use on mineral and organic soils using the data of the farm structure survey. We assess the mitigation costs on the basis of the standard gross margin of the agriculturally used peatlands and with the sector model RAUMIS. Without engineering and transaction costs the mitigation costs are in the magnitude of 10 to 45 € per to of CO2eq.. This makes rewetting of peatlands at least in the medium and long run a fairly efficient options for reducing GHG emissions, especially as the implications on the sector are fairly small due to reallocation affects

Integrating small farms in agent based models

In German agriculture structural change is mainly a result of the outmigration of smaller farms from the sector. The decisions of these farmers to leave or stay in the sector, are not based solely on financial data and market expectations. Other aspects are important such as the preservation of the cultural landscape, the continuation of the family tradition, or self-realisation. Only if these goals are adequately integrated into land use models, one can hope that the type and magnitude of reactions predicted by the model will be similar to that observed in reality. The main goal of this paper is to present a model approach that allows for the integration of non-monetary aspects into an agri-economic land use model. The approach is tested for a sample of 20 farms located in a municipality in the Bavarian Alps. The results show that the choice of the farmers’ attitude has a larger impact on results than the peculiarities of the policy scenario. This holds especially for the emerging farm structure but also for the general land use intensity.Farmer attitude, linear programming, agent based modelling, land market, Agricultural and Food Policy, Consumer/Household Economics, Land Economics/Use, Q12, Q15, R14,