Microeconomic analysis of short-term agricultural management and its interaction with climate change

气候变化不仅会迫使农业生产者调整其农业组织和生产计划，还会鼓励他们调整年度工作安排。这些影响将通过生物经济模拟模型进行检验，该模型将作物模型系统EXPERTN与FARMACTOR的经济决策功能集成在一起。短期管理决策是启发式模拟，以响应大气、土壤条件和作物生长阈值或“触发因素”，以一种考虑经济主体经验学习的方式。这使得复制环境、作物性能和农场管理之间的密切关系成为可能。特别注意研究“嵌入风险”，它代表了人类对不断变化的不确定经济和环境条件的可能反应的灵活性。通过使用随机拉丁方抽样程序的系统灵敏度分析，元模型的数据库将有助于检查基本模型结构。为此，该模式将由研究部提供的天气数据驱动。贝叶斯网络将通过灵敏度结果进行校准，以协助进一步分析。通过这种方法，生产决策将得到优化，这一步的模拟模型将过于复杂。此外，这使利益相关者能够参与现场级模拟，以测试模型结果的合理性。最后，将简化的管理规则转移到综合土地利用模型中，使其能够基于现有模型数据（如天气和作物数据）整合短期决策。模拟的未来天气情景将被用来预测气候变化对欧洲可耕地的影响。

Climate change will not only challenge agricultural producers to adapt their farm organisation and production planning, but also encourage adjustments to annual work scheduling. These effects will be examined through a bio-economic simulation model that integrates the crop model system EXPERTN with the economic decision-making functionality of FARMACTOR. Short-term management decisions are heuristically simulated to respond to atmospheric, soil condition and crop growth thresholds or "triggers" in a way that considers experiential learning by economic agents. This makes it possible to replicate the close relationships between the environment, crop performance and farm management. Special attention is paid to studying "embedded risk" which represents the flexibility of possible human reactions to evolving uncertain economic and environmental conditions over time. By way of systematic sensitivity analysis using a random Latinsquare sampling procedure, a data base for meta-modelling will facilitate the examination of the fundamental model structure. For this, the model will be driven by weather data provided in the Research Unit. A Bayesian network will be calibrated via sensitivity results to assist in further analysis. Through this, production decisions will be optimised, a step for which the simulation model would be too complex. Further, this enables the engagement of stakeholders with field-level simulations in order to test the plausibility of model results. Finally, simplified management rules will be transferred to the integrated land-use models, enabling them to integrate short-term decisions based on existing model data such as weather and crop data. Simulated future weather scenarios will then be utilised to forecast the effects of climate change on arable lands in Europe.