Microeconomic analysis of short-term agricultural management and its interaction with climate change
Final Report Abstract
This project dealt with the short term management of agricultural crops under the influence of climate change. The question when to time the agricultural actions on the field is highly weather dependent and thus subject to gradual changes with changing climate. On the other side, the timing of the actions has crucial influence of the obtainable yields and on surface coverage of the fields and thus causes a feedback towards climate. In this project the model FARMACTOR was developed which models the day by day actions of farmers on the field by so called triggers, which are conditions regarding date, soil and plant properties. The model was able to reproduce the overall trend of observed timing shifts observed in the past and forecasts further shifts in the future. Coupling to crop growth model with the model EXPERT-N resulted in an analysis of future yield potential which may be harmed by climate stress, however may still increase, if breeding progress continues and if CO2 fertilization may be taken into account. Variation of yield is likely to increase, however the interplay with varying prices are blurring this clear picture for the variable profit. Empirical surveys among the farmers in the research area show that most respondents are aware of climate change, however many are still unsure whether the changes are to the advantage or disadvantage of agriculture. Heat waves, droughts and storms are of major concerns. In this project, robust rules have been developed that allow an easy introduction of the timing shifts of the field activities into the large coupled models BEMS and ALCM. This increases the validity of these models in contrast to a constant assumption of activity timing and closes the feedback cycle between climate and farming. Finally, a novel meta model technique was developed that captures the behavior of complex simulation models in terms of conditional probability tables in a Bayesian Network. This type of model requires low computational resources and can thus easily be applied in interactive modeling sessions with stakeholders. First test with students were promising.
Publications
- 2012. The influence of climate change on short-term farm management – interdisciplinary modelling approach. Annual conference of Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V. (GEWISOLA) from 26.-28.09.2012 at Stuttgart-Hohenheim
Aurbacher, J., Reinmuth, E., Parker, P., Calberto, G., Steinbach, J., Ingwersen, J., Dabbert, S.
(See online at https://doi.org/10.22004/ag.econ.137143) - 2013. Influence of climate change on short term management of field crops - a modelling approach. Agricultural Systems 119, 44-57
Aurbacher, J., Parker, P.S., Calberto Sánchez, G.A., Steinbach, J., Reinmuth, E., Ingwersen, J., Dabbert, S.
(See online at https://doi.org/10.1016/j.agsy.2013.04.005) - 2013. The influence of climate change on short-term farm management - An interdisciplinary modelling approach. Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V. 48, 499-501
Aurbacher, J., Reinmuth, E., Parker, P., Calberto, G., Steinbach, J., Ingwersen, J., Dabbert, S.
- 2015. German farmers' perception of climate change effects and determinants influencing their climate awareness. Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V. 51, 407–418
Jänecke, A., Eisele, M., Reinmuth, E., Steinbach, J., Aurbacher, J.
- 2015. Simulation-based projections of crop management and gross margin variance in contrasting regions of Southwest Germany. Journal of Agricultural Studies 3, 79-98
Parker, P.S., Reinmuth, E., Ingwersen, J., Högy, P., Priesack, E., Wizemann, H.-D., Aurbacher, J.
(See online at https://doi.org/10.5296/jas.v3i1.5956) - 2016. Cause and consequence in maize planting dates in Germany. Journal of Agronomy and Crop Science, 1-14
Parker, P.S., Shonkwiler, J.S., Aurbacher, J.
(See online at https://doi.org/10.1111/jac.12182) - 2016. Simulating regional climateadaptive field cropping with fuzzy logic management rules and genetic advance. The Journal of Agricultural Science 154, 207-222
Parker, P., Ingwersen, J., Högy, P., Priesack, E., Aurbacher, J.
(See online at https://doi.org/10.1017/S0021859615000490) - 2016. Simulation of daily field management and crop performance in Southwest Germany under climate and technological change. Dissertation, Justus-Liebig-Universität Gießen
Parker, P. S.
- 2017. Modeling perceptions of climatic risk in crop production. PLOS ONE 12, e0181954
Reinmuth, E., Parker, P., Aurbacher, J., Högy, P., Dabbert, S.
(See online at https://doi.org/10.1371/journal.pone.0181954) - 2017. Toward more efficient model development for farming systems research – An integrative review. Computers and Electronics in Agriculture 138, 29–38
Reinmuth, E., Dabbert, S.
(See online at https://doi.org/10.1016/j.compag.2017.04.007) - 2018. Land use management under climate change: a microeconomic analysis with emphasis on risk. Dissertation, Universität Hohenheim
Reinmuth, E.
