Einfluss des Wassergehalts, des Eintrags von Wurzeln und gelöster organischer Substanz und räumlicher Unzugänglichkeit auf den C-Umsatz & Bestimmung der räumlichen Variabilität von Bodeneigenschaften

这是公认的，减少供应的新鲜有机质，有机质与矿物相的相互作用和空间不可达性影响C股票在底土。然而，所需的定量信息，以更好地了解每一个不同的过程中的碳封存在底土和底土碳模型的改进的贡献是稀缺的。底土有机质分解速率的主要控制因素也是如此。此外，关于底土中不同性质的空间变异性的信息很少。现有的几项研究，耦合近，中红外光谱（NIRS/MIRS）与地质统计学的方法表明，有可能创建空间地图，可能会显示热点增加生物活动的土壤剖面及其对C含量的分布的影响。目的是：（1）应用分馏法结合~（14）C测量，确定不同组分C在土壤中的平均停留时间;（2）在自动微宇宙系统中，研究水分含量、~（13）C标记根系和溶解有机质的输入以及空间不可达性对C周转的影响;（iii）利用近红外光谱和中红外光谱确定土壤的一般特性和生物及化学特性，以及（iv）利用不同的空间插值技术将测量和估计的土壤性质外推到垂直剖面。对于NIRS/MIRS应用，将优化样品预处理（风干样品与冻干样品）和校准程序（改进的偏最小二乘（MPLS）方法与遗传算法结合MPLS或PLS）。我们假设，化学分馏与14 C测量和孵育实验的结果相结合的组合应用将给出被动，中间，不稳定和非常不稳定的C和N的池大小和不稳定和非常不稳定的C和N的平均停留时间。这些结果将使人们有可能初始化的新的量化模型，将由子项目PC开发。此外，我们假设，样品预处理“冷冻干燥”将是更有用的土壤生物学特性的估计比空气干燥。预计GA-MPLS和GA-PLS方法比MPLS和PLS方法更好地估计土壤特性。不同底土特征的空间分布图结合温度和水分含量的空间分布图，可能有助于解释C含量的空间异质性。

It is well established that reduced supply of fresh organic matter, interactions of organic matter with mineral phases and spatial inaccessibility affect C stocks in subsoils. However, quantitative information required for a better understanding of the contribution of each of the different processes to C sequestration in subsoils and for improvements of subsoil C models is scarce. The same is true for the main controlling factors of the decomposition rates of soil organic matter in subsoils. Moreover, information on spatial variabilities of different properties in the subsoil is rare. The few studies available which couple near and middle infrared spectroscopy (NIRS/MIRS) with geostatistical approaches indicate a potential for the creation of spatial maps which may show hot spots with increased biological activities in the soil profile and their effects on the distribution of C contents. Objectives are (i) to determine the mean residence time of subsoil C in different fractions by applying fractionation procedures in combination with 14C measurements; (ii) to study the effects of water content, input of 13C-labelled roots and dissolved organic matter and spatial inaccessibility on C turnover in an automatic microcosm system; (iii) to determine general soil properties and soil biological and chemical characteristics using NIRS and MIRS, and (iv) to extrapolate the measured and estimated soil properties to the vertical profiles by using different spatial interpolation techniques. For the NIRS/MIRS applications, sample pretreatment (air-dried vs. freeze-dried samples) and calibration procedures (a modified partial least square (MPLS) approach vs. a genetic algorithm coupled with MPLS or PLS) will be optimized. We hypothesize that the combined application of chemical fractionation in combination with 14C measurements and the results of the incubation experiments will give the pool sizes of passive, intermediate, labile and very labile C and N and the mean residence times of labile and very labile C and N. These results will make it possible to initialize the new quantitative model to be developed by subproject PC. Additionally, we hypothesize that the sample pretreatment “freeze-drying” will be more useful for the estimation of soil biological characteristics than air-drying. The GA-MPLS and GA-PLS approaches are expected to give better estimates of the soil characteristics than the MPLS and PLS approaches. The spatial maps for the different subsoil characteristics in combination with the spatial maps of temperature and water contents will presumably enable us to explain the spatial heterogeneity of C contents.