Servicenavigation

Project Details

Back

Projekt Print View

Climate change scenario modelling of soil carbon turnover on basis of improved soil carbon pool distribution on a regional scale

Subject Area Plant Cultivation, Plant Nutrition, Agricultural Technology
Term from 2012 to 2020
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 193709899
 
Final Report Year 2019

Final Report Abstract

A high resolution representation of regional soil organic carbon (SOC) pools and fluxes facilitates an improved assessment of the impact of climate change on agro-ecosystems (soil fertility/plant productivity) and respective feedbacks to the atmosphere via greenhouse gas emissions. However, parameterization of SOC pools of dynamic soil models at regional scale is challenging due the lack of corresponding spatial data and cost/time efficient methods to derive necessary model input parameters. The research conducted here demonstrated that soil mid infrared spectroscopy (midDRIFTS) derived C compound specific peaks have a high potential as a proxy for SOC pool partitioning (i.e., in DAISY model). Furthermore, it could be shown that the coupling of thermal soil treatments (i.e., slow or instant heating (pyrolysis)) with infrared spectroscopy removes mineral interference from the spectra which then contain valuable information about SOC stability. However, because part of the SOC remains in the soil after pyrolysis, and because some secondary reactions might happen during pyrolysis, the resulting spectra are more complex than midDRIFTS, and not easy to apply to existing two pool model structures. In contrast, as our results demonstrate, the midDRIFTS technique is a suitable fast and low-cost technique with very high potential for regional SOC pool mapping as well as upscaling of many other soil parameters that are needed in modeling, such as soil nitrogen, microbial biomass, texture. A main impact of future climate change is an increasing temperature. Hence, it is necessary to better understand temperature sensitivities (Q10) of SOC turnover. Incorporating newly obtained soil enzyme based Q10 values into an existing SOC model (DAISY) showed that they were lower than the commonly used values and they differed between SOC pools. However, the resulting simulations of SOC turnover revealed that a major impact on soil respiration occurs only at elevated soil temperatures due to the low average temperatures in the research region of Southwest Germany. Furthermore, the quality of incoming plant material plays a large role in its decomposition and incorporation in SOC. Therefore, a dynamic partitioning was implemented into the soil-plant EXPERTN-DAISY model so that regional feedback of plant residue quality to climate change can be simulated and changes carbon inputs into the soil. The results presented here, also highlight general challenges with modeling complex systems. Many parameters are either chosen by strong assumptions that cannot easily be validated or they correspond to local minima of objective functions – but not necessarily the best solution. Due to the DAISY model structure, there is also a high equifinality of model parameters and a wide range of parameters that are realistic. This should be considered when parameters are used as input for any kinds of simulations, but especially at the regional scale. Impacts of climate change on soil carbon stocks and greenhouse gas emissions are not only a matter of model parameterization, increased temperature sensitivities and altered rainfall conditions but also driven by associated future changes in crop types and management chosen by farmers.

Publications

 
 

Additional Information

© 2024 DFG Disclaimer / Copyright / Privacy Policy

Textvergrößerung und Kontrastanpassung