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Grundwassermessstelle APP_GWMN_284

Dieser Datensatz beschreibt die Grundwassermessstelle APP_GWMN_284 in Schleswig-Holstein. Die Messstelle liegt im Grundwasserkörper EL13 : Krückau - Altmoränengeest Nord. Es liegen insgesamt 33544 Messwerte vor. Es liegen außerdem 5 Probenentnahmen vor (siehe Resourcen).

Grundwassermessstelle APP_GWMN_583

Dieser Datensatz beschreibt die Grundwassermessstelle APP_GWMN_583 in Schleswig-Holstein. Die Messstelle liegt im Grundwasserkörper ST09 : Schwentine - Unterlauf. Es liegen insgesamt 39136 Messwerte vor. Es liegen außerdem 29 Probenentnahmen vor (siehe Resourcen).

Grundwassermessstelle APP_GWMN_760

Dieser Datensatz beschreibt die Grundwassermessstelle APP_GWMN_760 in Schleswig-Holstein. Die Messstelle liegt im Grundwasserkörper EL08 : Stör - Geest und östl. Hügelland. Es liegen insgesamt 5942 Messwerte vor. Es liegen außerdem 11 Probenentnahmen vor (siehe Resourcen).

Grundwassermessstelle APP_GWMN_567

Dieser Datensatz beschreibt die Grundwassermessstelle APP_GWMN_567 in Schleswig-Holstein. Die Messstelle liegt im Grundwasserkörper EL08 : Stör - Geest und östl. Hügelland. Es liegen insgesamt 21313 Messwerte vor. Es liegen außerdem 51 Probenentnahmen vor (siehe Resourcen).

Grundwassermessstelle APP_GWMN_121

Dieser Datensatz beschreibt die Grundwassermessstelle APP_GWMN_121 in Schleswig-Holstein. Die Messstelle liegt im Grundwasserkörper EI23 : Gotteskoog - Altmoränengeest. Es liegen insgesamt 37993 Messwerte vor. Es liegen außerdem 32 Probenentnahmen vor (siehe Resourcen).

Grundwassermessstelle APP_GWMN_555

Dieser Datensatz beschreibt die Grundwassermessstelle APP_GWMN_555 in Schleswig-Holstein. Die Messstelle liegt im Grundwasserkörper EI14 : Eider/Treene - Geest. Es liegen insgesamt 24536 Messwerte vor. Es liegen außerdem 55 Probenentnahmen vor (siehe Resourcen).

Grundwassermessstelle APP_GWMN_603

Dieser Datensatz beschreibt die Grundwassermessstelle APP_GWMN_603 in Schleswig-Holstein. Die Messstelle liegt im Grundwasserkörper EI11 : Arlau/Bongsieler Kanal - Geest. Es liegen insgesamt 48660 Messwerte vor. Es liegen außerdem 22 Probenentnahmen vor (siehe Resourcen).

Geochemical parameters in peat depth profiles from ombrotrophic bogs in North and Central Europe. Pichlmaier Moor, Austria

This dataset contains geochemical variables measured in six depth profiles from ombrotrophic peatlands in North and Central Europe. Peat cores were taken during the spring and summer of 2022 from Amtsvenn (AV1), Germany; Drebbersches Moor (DM1), Germany; Fochteloër Veen (FV1), the Netherlands; Bagno Kusowo (KR1), Poland; Pichlmaier Moor (PI1), Austria and Pürgschachen Moor (PM1), Austria. The cores AV1, DM1 and KR1 were taken using a Wardenaar sampler (Royal Eijkelkamp, Giesbeek, the Netherlands) and had diameter of 10 cm. The cores FV1, PM1 and PI1 had an 8 cm diameter and were obtained using an Instorf sampler (Royal Eijkelkamp, Giesbeek, the Netherlands). The cores FV1, DM1 and KR1 were 100 cm, core AV1 was 95 cm, core PI1 was 85 cm and core PM1 was 200 cm. The cores were subsampeled in 1 cm (AV1, DM1, KR1, FV1) and 2 cm (PI1, PM1) sections. The subsamples were milled after freeze drying in a ballmill using tungen carbide accesoires. X-Ray Fluorescence (WD-XRF; ZSX Primus II, Rigaku, Tokyo, Japan) was used to determine Al (μg g-1), As (μg g-1), Ba (μg g-1), Br (μg g-1), Ca (g g-1), Cl (μg g-1), Cr (μg g-1), Cu (μg g-1), Fe (g g-1), K (g g-1), Mg (μg g-1), Mn (μg g-1), Na (μg g-1), P (μg g-1), Pb (μg g-1), Rb (μg g-1), S (μg g-1), Si (μg g-1), Sr (μg g-1), Ti (μg g-1) and Zn (μg g-1). These data were processed and calibrated using the iloekxrf package (Teickner & Knorr, 2024) in R. C, N and their stable isotopes were determined using an elemental analyser linked to an isotope ratio mass spectrometer (EA-3000, Eurovector, Pavia, Italy & Nu Horizon, Nu Instruments, Wrexham, UK). C and N were given in units g g-1 and stable isotopes were given as δ13C and δ15N for stable isotopes of C and N, respectively. Raw data C, N and stable isotope data were calibrated with certified standard and blank effects were corrected with the ilokeirms package (Teickner & Knorr, 2024). Using Fourier Transform Mid-Infrared Spectroscopy (FT-MIR) (Agilent Cary 670 FTIR spectromter, Agilent Technologies, Santa Clara, Ca, USA) humification indices (HI) were determined. Spectra were recorded from 600 cm-1 to 4000 cm-1 with a resolution of 2 cm-1 and baselines corrected with the ir package (Teickner, 2025) to estimate relative peack heights. The HI (no unit) for each sample was calculated by taking the ratio of intensities at 1630 cm-1 to the intensities at 1090 cm-1. Bulk densities (g cm-3) were estimated from FT-MIR data (Teickner et al., in preparation).

Between Path Dependence and Path Creation: The Impact of Farmers' Behavior and Policies on Structural Change in Agriculture

Farm structures are often characterized by regional heterogeneity, agglomeration effects, sub-optimal farm sizes and income disparities. The main objective of this study is to analyze whether this is a result of path dependent structural change, what the determinants of path dependence are, and how it may be overcome. The focus is on the German dairy sector which has been highly regulated and subsidized in the past and faces severe structural deficits. The future of this sector in the process of an ongoing liberalization will be analyzed by applying theoretical concepts of path dependence and path breaking. In these regards, key issues are the actual situation, technological and market trends as well as agricultural policies. The methodology will be based on a participative use of the agent-based model AgriPoliS and participatory laboratory experiments. On the one hand, AgriPoliS will be tested as a tool for stakeholder oriented analysis of mechanisms, trends and policy effects. This part aims to analyze whether and how path dependence of structural change can be overcome on a sector level. In a second part, AgriPoliS will be extended such that human players (farmers, students) can take over the role of agents in the model. This part aims to compare human agents with computer agents in order to overcome single farm path dependence.

Effects of water content, input of roots and dissolved organic matter and spatial inaccessibility on C turnover & determination of the spatial variability of subsoil properties

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.

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