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Küsten und Klimawandel in den Augen von Touristen : eine Wahrnehmungsanalyse an der deutschen Ostsee
(2011)
Aufgrund seiner wirtschaftlichen Bedeutung spielt der Tourismus in Mecklenburg-Vorpommern eine große Rolle. Insbesondere die Küstengebiete sind beliebte Reiseziele. In den letzten Jahren konnte ein kontinuierlicher Anstieg der Ankünfte und Übernachtungen verzeichnet werden. Neben anderen Faktoren werden die regionalen Auswirkungen des Klimawandels jedoch in Zukunft eine Herausforderung für den Tourismussektor darstellen. Die globale Erwärmung wird für den Strand- und Badetourismus sowohl negative, als auch positive Folgen haben, auf die reagiert werden muss. Neben vorbeugenden Klimaschutzmaßnahmen werden künftig auch Anpassungsstrategien entwickelt werden müssen, die den zu erwartenden Veränderungen Rechnung tragen. Doch zu welchen tourismusrelevanten Veränderungen wird es überhaupt kommen und was geschieht bereits aktuell? Sind die Folgen des Klimawandels durch Touristen schon jetzt wahrnehmbar? Wie reagieren die Urlauber auf eventuelle Veränderungen? Diese und andere Fragen soll die vorliegende Arbeit, die innerhalb des RAdOST-Vorhabens (Regionale Anpassungsstrategien für die deutsche Ostseeküste) angesiedelt ist, beantworten. Dazu wurde zum einen eine Literaturrecherche zu tourismusrelevanten Klimawandelfolgen an der deutschen Ostseeküste durchgeführt. Zum anderen erfolgte in den Sommermonaten 2010 eine Befragung der Strandgäste in Markgrafenheide, Warnemünde und Nienhagen an der mecklenburgischen Ostseeküste. Im Mittelpunkt der Umfrage stand die Wahrnehmung von Erscheinungen (z.B. viele Quallen oder warmes Ostseewasser) sowie kurz- oder langfristigen Veränderungen an der Küste (z.B. schmalere Strände, vermehrter Strandanwurf) durch die Urlauber. Außerdem wurden die Einstellung und der Informationsgrad der Gäste zum Thema Klimawandel an der Ostseeküste analysiert. Ziel war es, aus den Umfrageergebnissen Handlungsempfehlungen für das lokale Strandmanagement hinsichtlich künftiger Anpassungsstrategien abzuleiten. Die Literaturrecherche zeigte, dass in einigen Bereichen schon jetzt Veränderungen (z.B. der Luft- und Wassertemperatur oder des Meeresspiegels) nachweisbar sind und laut verschiedener Modellprojektionen von weiteren Veränderungen ausgegangen werden kann. Wie die Umfrage deutlich machte, sind die Veränderungen momentan durch Touristen jedoch kaum oder gar nicht wahrnehmbar. Dementsprechend gering ist auch ihre Reaktion auf die einzelnen Phänomene. Generell ist die Wahrnehmung der Urlauber sehr subjektiv und selektiv. Manche Gegebenheiten wie beispielsweise existierende Küstenschutzmaßnahmen werden von einem großen Teil der Touristen gar nicht wahrgenommen. Hinsichtlich anderer Erscheinungen wie Strandanwurf und Quallen sind viele Besucher wiederum sehr sensibel. Es zeigte sich außerdem, dass es für die meisten Urlauber schwierig ist, zu beurteilen, ob bestimmte Gegebenheiten am Strand und an der Küste mit der globalen Erwärmung in Verbindung stehen oder nicht. Es besteht eine große Unsicherheit zu diesem Thema und oft wird der Klimawandel als Ursache für Erscheinungen genannt, auch wenn der kausale Zusammenhang wissenschaftlich nicht nachzuweisen ist. Es zeigte sich, dass die Urlauber sehr wenig über die regionalen Auswirkungen des Klimawandels informiert sind, sich aber Informationen wünschen. Folglich sollte zunächst die Aufklärung und Information der Urlauber über die Folgen der Veränderung des Klimas im Vordergrund stehen. Denn manche Aspekte, wie der Verlust von Strandabschnitten durch Erosion oder eine eventuelle Zunahme von Blaualgen in der Sommersaison, können nicht gänzlich vermieden werden. Durch gezielte Aufklärung könnte jedoch beispielsweise eine Akzeptanz für naturnahe Strände oder für den Rückzug aus einzelnen Gebieten geschaffen werden. Darüber hinaus sollte die zu erwartende Saisonverlängerung systematisch genutzt werden, um sowohl die Küste, als auch das Hinterland durch gezielte Angebote für Touristen attraktiv zu machen. Auf diese Weise könnte eine Entzerrung der Hauptsaison und eine bessere Auslastung der Beherbergungsbetriebe sowie der touristischen Infrastruktur erreicht werden.
Raumbilder im Wandel?
(2011)
Low-cost monitoring of snow height and thermal properties with inexpensive temperature sensors
(2011)
Small, self-recording temperature sensors were installed at several heights along a metal rod at five locations in a case study catchment. For each sensor, the presence or absence of snow cover was determined on the basis of its insulating effect and the resulting reduction of the diurnal temperature oscillations. Sensor coverage was then converted into a time series of snow height for each location. Additionally, cold content was calculated. Snow height and cold content provide valuable information for spring flood prediction.
Good agreement of estimated snow heights with reference measurements was achieved and increased discharge in the study catchment coincided with low cold content of the snow cover. The results of the proposed distributed assessment of snow cover and snow state show great potential for (i) flood warning, (ii) assimilation of snow state data and (iii) modelling snowmelt process.
In this paper we investigate the use of hydrological models as learning tools to help improve our understanding of the hydrological functioning of a catchment. With the model as a hypothetical conceptualization of how dominant hydrological processes contribute to catchment-scale response, we investigate three questions: (1) During which periods does the model (not) reproduce observed quantities and dynamics? (2) What is the nature of the error during times of bad model performance? (3) Which model components are responsible for this error? To investigate these questions, we combine a method for detecting repeating patterns of typical differences between model and observations (time series of grouped errors, TIGER) with a method for identifying the active model components during each simulation time step based on parameter sensitivity (temporal dynamics of parameter sensitivities, TEDPAS). The approach generates a time series of occurrence of dominant error types and time series of parameter sensitivities. A synoptic discussion of these time series highlights deficiencies in the assumptions about the functioning of the catchment. The approach is demonstrated for the Weisseritz headwater catchment in the eastern Ore Mountains. Our results indicate that the WaSiM-ETH complex grid-based model is not a sufficient working hypothesis for the functioning of the Weisseritz catchment and point toward future steps that can help improve our understanding of the catchment.
The quest for improved hydrological models is one of the big challenges in hydrology. When discrepancies are observed between simulated and measured discharge, it is essential to identify which algorithms may be responsible for poor model behavior. Particularly in complex hydrological models, different process representations may dominate at different moments and interact with each other, thus highly complicating this task. This paper investigates the analysis of the temporal dynamics of parameter sensitivity as a way to disentangle the simulation of a hydrological model and identify dominant parameterizations. Three existing methods (the Fourier amplitude sensitivity test, the extended Fourier amplitude sensitivity test, and Sobol's method) are compared by applying them to a TOPMODEL implementation in a small mountainous catchment in the tropics. For the major part of the simulation period, the three methods give comparable results, while the Fourier amplitude sensitivity test is much more computationally efficient. This method is also applied to the complex hydrological model WaSiM-ETH implemented in the Weisseritz catchment, Germany. A qualitative model validation was performed on the basis of the identification of relevant model components. The validation revealed that the saturation deficit parameterization of WaSiM-ETH is highly susceptible to parameter interaction and lack of identifiability. We conclude that temporal dynamics of model parameter sensitivity can be a powerful tool for hydrological model analysis, especially to identify parameter interaction as well as the dominant hydrological response modes. Finally, an open source implementation of the Fourier amplitude sensitivity test is provided.
Saturated hydraulic conductivity (Ks) of the soil is a key variable in the water cycle. For the humid tropics, information about spatial scales of Ks and their relation to soil types deduced from soil map units is of interest, as soil maps are often the only available data source for modelling. We examined the influence of soil map units on the mean and variation in Ks along a transect in a tropical rainforest using undisturbed soil cores at 06 and 612 cm depth. The Ks means were estimated with a linear mixed model fitted by residual maximum likelihood (REML), and the spatial variation in Ks was investigated with the maximum overlap discrete wavelet packet transform (MODWPT). The mean values of Ks did not differ between soil map units. The best wavelet packet basis for Ks at 06 cm showed stationarity at high frequencies, suggesting uniform small-scale influences such as bioturbation. There were substantial contributions to wavelet packet variance over the range of spatial frequencies and a pronounced low frequency peak corresponding approximately to the scale of soil map units. However, in the relevant frequency intervals no significant changes in wavelet packet variance were detected. We conclude that near-surface Ks is not dominated by static, soil-inherent properties for the examined range of soils. Several indicators from the wavelet packet analysis hint at the more dominant dynamic influence of biotic processes, which should be kept in mind when modelling soil hydraulic properties on the basis of soil maps.
The flowpaths by which water moves from watersheds to streams has important consequences for the runoff dynamics and biogeochemistry of surface waters in the Amazon Basin. The clearing of Amazon forest to cattle pasture has the potential to change runoff sources to streams by shifting runoff to more surficial flow pathways. We applied end-member mixing analysis (EMMA) to 10 small watersheds throughout the Amazon in which solute composition of streamwater and groundwater, overland flow, soil solution, throughfall and rainwater were measured, largely as part of the Large-Scale Biosphere-Atmosphere Experiment in Amazonia. We found a range in the extent to which streamwater samples fell within the mixing space determined by potential flowpath end-members, suggesting that some water sources to streams were not sampled. The contribution of overland flow as a source of stream flow was greater in pasture watersheds than in forest watersheds of comparable size. Increases in overland flow contribution to pasture streams ranged in some cases from 0% in forest to 27-28% in pasture and were broadly consistent with results from hydrometric sampling of Amazon forest and pasture watersheds that indicate 17- to 18-fold increase in the overland flow contribution to stream flow in pastures. In forest, overland flow was an important contribution to stream flow (45-57%) in ephemeral streams where flows were dominated by stormflow. Overland flow contribution to stream flow decreased in importance with increasing watershed area, from 21 to 57% in forest and 60-89% in pasture watersheds of less than 10 ha to 0% in forest and 27-28% in pastures in watersheds greater than 100 ha. Soil solution contributions to stream flow were similar across watershed area and groundwater inputs generally increased in proportion to decreases in overland flow. Application of EMMA across multiple watersheds indicated patterns across gradients of stream size and land cover that were consistent with patterns determined by detailed hydrometric sampling.
This study was conducted to evaluate the effect of different wood vermicompost application rates on some soil physical and chemical properties as well as on growth parameters of a grass seed mixture (RSM 7.2.1) in tertiary sand contaminated with coal spoil. The experiment was carried out in a greenhouse over a period of 42 days. Soil was mixed with vermicompost at ratios of 0.0, 3.0, 12.5, and 25.0% and sown with the grass seed mixture. Soil samples and plant material were analyzed to determine the effect of different vermicompost application rates on the physical and chemical properties. Results revealed that the physical and chemical properties of the soil improved with increasing application rates of vermicompost. In addition, soil treated with vermicompost showed significant increases in fresh-and dry-matter yields of the grass, as well as enhanced uptake of nutrients by the grass. This indicated that treatment of contaminated soils with vermicompost may be beneficial for reclamation processes by facilitating revegetation of disturbed areas.
Rund 20 Jahre nach dem Ende der Sowjetunion verharrt ein Großteil ländlich geprägter Regionen in der Russländischen Föderation in einer strukturellen Krise, die sich auf ökonomischer, sozialer und politischer Ebene niederschlägt. Auch wenn sich ländliche Räume als vermeintliche Verlierer der Transformation erwiesen haben, so sind sie doch vielfach in sich differenziert und zeigen verschiedenartige Problemlagen und Entwicklungspfade auf, die vom Umgang mit den Herausforderungen des Systemwechsels zeugen. Beispielhaft wird dies am Deutschen Nationalen Rayon Altai (DNR Altai) dargestellt, dessen Transformationsphase in der vorliegenden Arbeit rekonstruiert wird. Der DNR Altai stellt in vielerlei Hinsicht einen Sonderfall dar, da er als räumlicher Fixpunkt russlanddeutscher Entwicklungspolitik in die bundesdeutsche Förderkulisse eingebettet war. Mit dem allmählichen Rückzug der deutschen Förderinstitutionen stellt sich jedoch die Frage nach nachhaltigen Strukturen, Verstetigung von Projekten und der Zukunft russlanddeutscher Kultur im Altai.
Angesichts zunehmender globaler Städtekonkurrenzen haben politische Wiedererfindungen des Städtischen Konjunktur – mit immer kürzeren Zyklen und wechselnden Dynamiken der Inszenierung der jeweiligen Programmatiken. Berlin als junge Metropole liefert für die Implementation exogener Konzepte vielfältige Ansatzpunkte, zeigt jedoch auch umgehend ihre Grenzen auf. Die Beiträge dieses Bandes setzen sich mit Imaginationen, Diskursbeiträgen und Positionierungen auseinander, die den „großen“ politischen Konzepten jeweils „von unten“ entgegenwachsen und teilweise in Gegenbewegungen münden. Anschauungsmaterial liefern die Europäische Metropolregion Berlin-Brandenburg und das Projekt Mediaspree.
Complete protection against flood risks by structural measures is impossible. Therefore flood prediction is important for flood risk management. Good explanatory power of flood models requires a meaningful representation of bio-physical processes. Therefore great interest exists to improve the process representation. Progress in hydrological process understanding is achieved through a learning cycle including critical assessment of an existing model for a given catchment as a first step. The assessment will highlight deficiencies of the model, from which useful additional data requirements are derived, giving a guideline for new measurements. These new measurements may in turn lead to improved process concepts. The improved process concepts are finally summarized in an updated hydrological model. In this thesis I demonstrate such a learning cycle, focusing on the advancement of model evaluation methods and more cost effective measurements. For a successful model evaluation, I propose that three questions should be answered: 1) when is a model reproducing observations in a satisfactory way? 2) If model results deviate, of what nature is the difference? And 3) what are most likely the relevant model components affecting these differences? To answer the first two questions, I developed a new method to assess the temporal dynamics of model performance (or TIGER - TIme series of Grouped Errors). This method is powerful in highlighting recurrent patterns of insufficient model behaviour for long simulation periods. I answered the third question with the analysis of the temporal dynamics of parameter sensitivity (TEDPAS). For calculating TEDPAS, an efficient method for sensitivity analysis is necessary. I used such an efficient method called Fourier Amplitude Sensitivity Test, which has a smart sampling scheme. Combining the two methods TIGER and TEDPAS provided a powerful tool for model assessment. With WaSiM-ETH applied to the Weisseritz catchment as a case study, I found insufficient process descriptions for the snow dynamics and for the recession during dry periods in late summer and fall. Focusing on snow dynamics, reasons for poor model performance can either be a poor representation of snow processes in the model, or poor data on snow cover, or both. To obtain an improved data set on snow cover, time series of snow height and temperatures were collected with a cost efficient method based on temperature measurements on multiple levels at each location. An algorithm was developed to simultaneously estimate snow height and cold content from these measurements. Both, snow height and cold content are relevant quantities for spring flood forecasting. Spatial variability was observed at the local and the catchment scale with an adjusted sampling design. At the local scale, samples were collected on two perpendicular transects of 60 m length and analysed with geostatistical methods. The range determined from fitted theoretical variograms was within the range of the sampling design for 80% of the plots. No patterns were found, that would explain the random variability and spatial correlation at the local scale. At the watershed scale, locations of the extensive field campaign were selected according to a stratified sample design to capture the combined effects of elevation, aspect and land use. The snow height is mainly affected by the plot elevation. The expected influence of aspect and land use was not observed. To better understand the deficiencies of the snow module in WaSiM-ETH, the same approach, a simple degree day model was checked for its capability to reproduce the data. The degree day model was capable to explain the temporal variability for plots with a continuous snow pack over the entire snow season, if parameters were estimated for single plots. However, processes described in the simple model are not sufficient to represent multiple accumulation-melt-cycles, as observed for the lower catchment. Thus, the combined spatio-temporal variability at the watershed scale is not captured by the model. Further tests on improved concepts for the representation of snow dynamics at the Weißeritz are required. From the data I suggest to include at least rain on snow and redistribution by wind as additional processes to better describe spatio-temporal variability. Alternatively an energy balance snow model could be tested. Overall, the proposed learning cycle is a useful framework for targeted model improvement. The advanced model diagnostics is valuable to identify model deficiencies and to guide field measurements. The additional data collected throughout this work helps to get a deepened understanding of the processes in the Weisseritz catchment.
Species respond to environmental change by dynamically adjusting their geographical ranges. Robust predictions of these changes are prerequisites to inform dynamic and sustainable conservation strategies. Correlative species distribution models (SDMs) relate species’ occurrence records to prevailing environmental factors to describe the environmental niche. They have been widely applied in global change context as they have comparably low data requirements and allow for rapid assessments of potential future species’ distributions. However, due to their static nature, transient responses to environmental change are essentially ignored in SDMs. Furthermore, neither dispersal nor demographic processes and biotic interactions are explicitly incorporated. Therefore, it has often been suggested to link statistical and mechanistic modelling approaches in order to make more realistic predictions of species’ distributions for scenarios of environmental change. In this thesis, I present two different ways of such linkage. (i) Mechanistic modelling can act as virtual playground for testing statistical models and allows extensive exploration of specific questions. I promote this ‘virtual ecologist’ approach as a powerful evaluation framework for testing sampling protocols, analyses and modelling tools. Also, I employ such an approach to systematically assess the effects of transient dynamics and ecological properties and processes on the prediction accuracy of SDMs for climate change projections. That way, relevant mechanisms are identified that shape the species’ response to altered environmental conditions and which should hence be considered when trying to project species’ distribution through time. (ii) I supplement SDM projections of potential future habitat for black grouse in Switzerland with an individual-based population model. By explicitly considering complex interactions between habitat availability and demographic processes, this allows for a more direct assessment of expected population response to environmental change and associated extinction risks. However, predictions were highly variable across simulations emphasising the need for principal evaluation tools like sensitivity analysis to assess uncertainty and robustness in dynamic range predictions. Furthermore, I identify data coverage of the environmental niche as a likely cause for contrasted range predictions between SDM algorithms. SDMs may fail to make reliable predictions for truncated and edge niches, meaning that portions of the niche are not represented in the data or niche edges coincide with data limits. Overall, my thesis contributes to an improved understanding of uncertainty factors in predictions of range dynamics and presents ways how to deal with these. Finally I provide preliminary guidelines for predictive modelling of dynamic species’ response to environmental change, identify key challenges for future research and discuss emerging developments.
Die Ursache der Nachwuchsschwäche ist der Geburtenrückgang. Quantitative demografische Determinanten sind auf ideelle Merkmalsausprägungen der Bevölkerung und strukturelle Eigenschaften der Gesellschaft zurückzuführen. Die niedrige Fertilität führt als einflussreiche Kenngröße zu einem Bevölkerungsrückgang und zu altersstrukturellen Veränderungen in der Zusammensetzung der Bevölkerung, die mit weitreichenden und umfassenden gesellschaftlichen Konsequenzen einhergehen. Indem die Konsequenzen künftig insbesondere auf junge Generationen zurückwirken werden und somit zugleich die Ursachen der niedrigen Geburtenrate verstärken, entfaltet die demografische Entwicklung eine Eigendynamik. Maßnahmen zur Nachwuchssicherung treffen jedoch auf ungünstige Handlungsvoraussetzungen. Monetäre und materielle Fertilitätsanreize sind von unterschiedlicher demografischer Wirksamkeit und haben an Bedeutung verloren. Gesellschaft und Staat haben den Fokus von einer reaktionären Symptomkurierung, die eine passive Gestaltung der Konsequenzen verfolgt, auf eine aktive Ursachenbekämpfung zu richten. Es zeigt sich, dass auf der nationalen Ebene die größten Handlungspotentiale erschlossen werden können.
Für den Flugverkehr als Teil eines regional und global verdichteten Infrastruktursystems sind Naturgefahren wie Vulkanausbrüche gleichbedeutend mit Risiken. Die Kommunikation von Risiken verläuft im Spannungsfeld von wirtschaftlichen und staatlichen Akteuren einerseits und Medien und Zivilgesellschaft andererseits. Demgegenüber stehen Modelle diskursiver Risikoregulierung als Instrumente öffentlicher Aushandlungsprozesse. Diskutiert werden Einflussfaktoren auf Entscheidungen im Kontext von Risikodiskursen. Dabei wird insbesondere die Funktionslogik der Medien untersucht. Am Beispiel der Aschewolke des Eyjafjallajökull 2010 wird die Phänomenkonstellation von Akteuren und Diskurspositionen illustriert und der Verlauf einer medialen Risikoentwicklung nachgezeichnet.
Land use and mineral characteristics affect the ability of surface as well as subsurface soils to sequester organic carbon and their contribution to mitigation of the greenhouse effect. There is less information about the effects of land use and soil properties on the amount and composition of organic matter (OM) for subsurface soils as compared with surface soils. Here we aimed to analyse the long-term (>= 100 years) impact of arable and forest land use and soil mineral characteristics on subsurface soil organic carbon (SOC) contents, as well as on amount and composition of OM sequentially separated by Na pyrophosphate solution (OM(PY)) from subsurface soil samples. Seven soils with different mineral characteristics (Albic and Haplic Luvisol, Colluvic and Haplic Regosol, Haplic and Vertic Cambisol, Haplic Stagnosol) were selected from within Germany. Soil samples were taken from subsurface horizons of forest and adjacent arable sites continuously used for > 100 years. The OM(PY) fractions were analysed for their OC content (OC(PY)) and characterized by Fourier transform infrared spectroscopy. Multiple regression analyses for the arable subsurface soils indicated significant positive relationships between the SOC contents and combined effects of the (i) exchangeable Ca (Ca(ex)) and oxalate-soluble Fe (Fe(ox)) and (ii) the Ca(ex) and Al(ox) contents. For these soils the increase in OC (OC(PY) multiplied by the relative C=O content of OM(PY)) and increasing contents of Ca(ex) indicated that OM(PY) mainly interacts with Ca2+. For the forest subsurface soils (pH < 5), the OC(PY) contents were related to the contents of Na-pyrophosphate-soluble Fe and Al. The long-term arable and forest land use seems to result in different OM(PY)-mineral interactions in subsurface soils. On the basis of this, we hypothesize that a long-term land-use change from arable to forest may lead to a shift from mainly OM(PY)-Ca2+ to mainly OM(PY)-Fe3+ and -Al3+ interactions if the pH of subsurface soils significantly decreases to < 5.