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

基于改善区域尺度土壤碳库分布的土壤碳周转气候变化情景模型

• 批准号: 200779430
• 负责人: Professor Dr. Georg Cadisch
• 金额: --
• 依托单位: Fachgebiet Pflanzenbau in den Tropen und Subtropen (490e)
• 依托单位国家: 德国
• 项目类别: Research Units
• 财政年份: 2012
• 资助国家: 德国
• 起止时间: 2011-12-31 至 2019-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/200779430?language=en
• 关键词: Climate; change; scenario; modelling; soil

A high resolution representation of regional soil organic C (SOC) fluxes and pools facilitates an improved assessment of impacts of climate change and feedbacks on agro-ecosystems. However, soil organic carbon (SOC) pool partitioning in dynamic SOC models (i.e., DAISY) remains challenging, in particular when considering the driving influence of changing climatic conditions, e.g., by temperature sensitivities of individual SOC pools. The complexity of this constraint is magnified when SOC modelling is performed at a regional scale, where ecosystem and farm system heterogeneity exist. We propose an improvement of the DAISY SOC turnover model in Phase 2 including the development of novel and generic SOC stability indexes for the two SOC pools SOM1 and SOM2 as well as the generation of a microbial pool partition index based on activities of microbial enzymes for SMB1 and SMB2 pool distinction also considering substrate utilisation efficiencies. These essential steps will be primarily achieved through a further development of infrared (IR)-based techniques (diffuse reflectance mid-infrared Fourier transform spectroscopy (midDRIFTS), evolved gas analysis (EGA), in situT midDRIFTS, pyrolysis-MIRS) allowing a high-throughput, soil texture-independent analysis of SOC and microbial biomass pools at regional scale. Similar techniques will be employed to generate crop residue quality indexes for the two added organic matter pools AOM1 and AOM2 as initial regulators of C and N cycling. To account for the projected impact of climate variability in the two model regions (Kraichgau, Swabian Alb), the SOC model will be furthered through explicit temperature functions for corresponding C and N pools. For calibration and validation of the dynamic SOC model, we will revert to the experimental field sites in the two model regions as well as considering our existing cooperations with international researchers at long-term field experiments. Prior to coupling to the new Integrated Land-system Model System (ILMS) of FOR 1695, sensitivity analysis of individual and combined parameters related to the impact of expected regional climate with the advanced regional SOC model will be performed with DAISY-EXPERTN. The relevant developed and parameterised model routines and high resolution regional soil input maps will be incorporated into ILMS. In the final step, impacts of respective climate scenario analysis under alternative land uses, with and without improved CN module, on soil C dynamics and feedback from the atmosphere will be evaluated to derive recommendations for improved soil C sequestration approaches.

区域土壤有机碳（SOC）通量和库的高分辨率表示有利于改善气候变化的影响和农业生态系统的反馈评估。然而，动态SOC模型中的土壤有机碳库分配（即，DAISY）仍然具有挑战性，特别是在考虑气候条件变化的驱动影响时，例如，由单个SOC池的温度敏感性决定。在区域尺度上进行SOC建模时，这种约束的复杂性被放大，其中存在生态系统和农场系统的异质性。我们提出了一个改进的DAISY SOC营业额模型在第2阶段，包括开发新的和通用的SOC稳定性指标的两个SOC池SOM 1和SOM 2，以及生成的微生物池分区指数的基础上的微生物酶的活动SMB 1和SMB 2池的区别，也考虑到底物利用效率。这些重要步骤将主要通过进一步开发基于红外（IR）的技术（漫反射中红外傅立叶变换光谱（midDRIFTS），演化气体分析（EGA），原位midDRIFTS，热解MIRS）来实现，从而可以在区域范围内对SOC和微生物生物量库进行高通量，土壤质地独立的分析。将采用类似的技术来生成两个添加的有机质库AOM 1和AOM 2作为C和N循环的初始调节剂的作物残留物质量指数。考虑到两个模型区域（Kraichgau，Swabian Alb）气候变率的预计影响，SOC模型将通过相应C和N库的显式温度函数进一步扩展。对于动态SOC模型的校准和验证，我们将回到两个模型区域的实验场，并考虑我们与国际研究人员在长期实地实验中的现有合作。在与FOR 1695的新的综合陆地系统模式系统（ILMS）耦合之前，将使用DAISY-EXPERTTN对与高级区域SOC模式的预期区域气候影响相关的单个和组合参数进行敏感性分析。相关的开发和参数化模型程序和高分辨率区域土壤输入图将纳入综合土地管理系统。在最后一步中，将评估在有和没有改进的CN模块的情况下，在替代土地利用下各自气候情景分析对土壤碳动态和大气反馈的影响，以得出改进土壤碳固存方法的建议。

项目成果

Overcoming carbonate interference on labile soil organic matter peaks for midDRIFTS analysis

• DOI: 10.1016/j.soilbio.2016.05.010
• 发表时间: 2016-08
• 期刊: Soil Biology & Biochemistry
• 影响因子: 9.7
• 作者: Reza Mirzaeitalarposhti;M. S. Demyan;F. Rasche;G. Cadisch;T. Müller

Controls on microbially regulated soil organic carbon decomposition at the regional scale

• DOI: 10.1016/j.soilbio.2017.12.007
• 发表时间: 2018-03
• 期刊: Soil Biology & Biochemistry
• 影响因子: 9.7
• 作者: Rana Shahbaz Ali;E. Kandeler;S. Marhan;M. S. Demyan;J. Ingwersen;Reza Mirzaeitalarposhti;F. Rasche

Mechanisms controlling soil organic carbon composition pertaining to microbial decomposition of biochemically contrasting organic residues: Evidence from midDRIFTS peak area analysis

• DOI: 10.1016/j.soilbio.2014.05.006
• 发表时间: 2014-09-01
• 期刊: SOIL BIOLOGY & BIOCHEMISTRY
• 影响因子: 9.7
• 作者: Kunlanit, Benjapon;Vityakon, Patma;Rasche, Frank
• 通讯作者: Rasche, Frank

Combining a coupled FTIR-EGA system and in situ DRIFTS for studying soil organic matter in arable soils

结合耦合 FTIR-EGA 系统和原位 DRIFTS 研究耕地土壤有机质

• DOI: 10.5194/bg-10-2897-2013
• 发表时间: 2013
• 期刊: Biogeosciences
• 影响因子: 4.9
• 作者: Demyan;Rasche;Schütt;Smirnova;Schulz;Cadisch
• 通讯作者: Cadisch

midDRIFTS-based partial least square regression analysis allows predicting microbial biomass, enzyme activities and 16S rRNA gene abundance in soils of temperate grasslands

基于 midDRIFTS 的偏最小二乘回归分析可以预测温带草原土壤中的微生物生物量、酶活性和 16S rRNA 基因丰度

• DOI: 10.1016/j.soilbio.2012.09.030
• 发表时间: 2013
• 期刊: Soil Biology & Biochemistry
• 影响因子: 9.7
• 作者: Rasche;Marhan;Berner;Kandeler;Cadisch
• 通讯作者: Cadisch