FOR 1695: Agricultural Landscapes under Global Climate Change - Processes and Feedbacks on a Regional Scale

农业部门是对气候最敏感的部门之一，因为气温、降水和大气中二氧化碳浓度的变化直接影响农作物的生长条件。农民将适应变化，这将对水平衡、生物多样性和许多其他农业景观的结构和功能产生重大影响。除此之外，这可能还会影响气候本身。由于对变化的反应基本上是地方性的，因此需要制定适应战略，考虑到区域不同的生态、经济和社会因素，并在区域范围内实施。然而，目前的模型系统不足以在区域范围内准确模拟气候变化影响，因为它们没有在足够的程度上考虑相关过程，特别是土地利用与气候之间的相互作用。研究股的共同目标是，通过将综合模拟与迄今无与伦比的空间分辨率、密集的实地测量和受控实验相结合，增进对过程的理解和对地面与大气之间反馈的了解。这将使我们能够对2030年前的景观发展和潜在的适应战略进行预测。为此，高分辨率的气候、土地利用和作物生长模型将与社会经济模型相结合，形成一个先进的土地系统模型。通过特定的传感器系统和遥感技术，将在德国西南部的两个研究区域收集土壤-植物系统和大气之间的能量和物质通量的数据。作物将在气候室中暴露在未来的二氧化碳和气候条件下，以评估对作物产量和产量质量的影响。从实地测量和气候室实验以及从研究区域的社会经济调查中获得的数据将有助于改进模型组成部分并验证新的土地系统模型。

The agricultural sector is among the most climate-sensitive sectors, because changes in temperature, precipitation and carbon dioxide concentrations of the atmosphere directly affect the growth conditions of agricultural crops. Farmers will adapt to changes, which will have substantial consequences for the structure and functions of agricultural landscapes such as water balance, biological diversity and many others. Added to that, this may also affect the climate itself. Because the reaction to changes is essentially local, adaptation strategies need to be developed taking into account regionally varying ecological, economic and societal factors and implemented on a regional scale. Current model systems, though, are not good enough to accurately simulate climate change effects on a regional scale as they do not consider relevant processes, especially the interactions between land use and climate, to a sufficient extent. It is the joint objective of the Research Unit to improve process understanding and knowledge of feedbacks between land surface and atmosphere by combining integrated modelling with hitherto unequalled spatial resolution, intensive field measurements and controlled experiments. This will enable us to produce projections of landscape development and potential adaptation strategies until 2030. For this purpose, high-resolution climate, land use, and crop growth models will be coupled with socio-economic models forming an advanced land system model. By means of specific sensor systems and remote sensing techniques, data on energy and matter fluxes between the soil-plant system and the atmosphere will be collected in two study regions in Southwest Germany. Crops will be exposed to future CO2 and climate conditions in climatic chambers in order to assess the effects on crop yield and yield quality. Data obtained from field measurements and climatic chamber experiments as well as from socio-economic investigations in the study regions will serve to improve model components and to validate the novel land system model.