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Veränderungen im thermalen Regime des Permafrosts verursachen Störungen der Erdoberfläche. Diese Veränderungen werden durch die in der Arktis seit Jahrzehnten ansteigenden Temperaturen verstärkt. Thermokarst ist ein Prozess, welcher die Erdoberfläche durch Schmelzen von Grundeis, oder Auftauen von Permafrost absacken lässt, wodurch charakteristische Landformen entstehen. Thermokarst ist vor allem entlang von Hängen weit verbreitet und die Anzahl der damit verbundenen Landformen in der Arktis steigt stetig an. Dieser Prozess mobilisiert große Mengen an Material, welche in Richtung Meer transportiert oder entlang von Hängen akkumuliert werden. Während entlang von Hängen auftretender Thermokarst terrestrische sowie aquatische Ökosysteme stark verändert, ist dessen Einfluss auf regionaler Skala zurzeit noch Gegenstand der Forschung.
In dieser Arbeit quantifizieren wir die Auswirkungen von Thermokarstprozessen entlang von Hängen auf die umliegenden Ökosysteme der küstennahen Täler und Nahküstenbereiche entlang der Yukon Küste in Kanada. Mittels überwachtem maschinellen Lernen haben wir geomorphische Faktoren identifiziert, welche die Entwicklung von retrogressiven Auftaurutschungen (RTS) begünstigen. RTS sind eine Erscheinungsform von Thermokarst entlang von Hängen. Die Küstengeomorphologie, sowie der Grundeistyp und -inhalt sind die wesentlichen bestimmenden Faktoren für das Auftreten von RTS. Wir haben Luftbildaufnahmen und Satellitenbilder genutzt, um die Evolution von RTS im Zeitraum von 1952 bis 2011 zu verfolgen. Während dieser Zeit ist die Anzahl und Ausdehnung von RTS linear angestiegen. Wir zeigen, dass 56% der RTS welche entlang der Küste in 2011 identifiziert wurden, 16.6 × 106 m3 an Material erodiert haben. Hiervon wurden 45% durch Küstenprozesse entlang der Küste transportiert. RTS tragen wesentlich zu dem Kohlenstoff-Budget des Nahküstenbereiches bei: 17% der in 2011 identifizierten RTS, haben 0.6% des organischen Kohlenstoffes transportiert, welcher durch Küstenerosion entlang der Yukon Küste jährlich freigesetzt wird. Um den Einfluss von Thermokarst entlang von Hängen auf das terrestrische Ökosystem zu beurteilen, haben wir die räumliche Verteilung von organischem Bodenkohlenstoff und Stickstoff (SOC, TN) entlang von Hangprofilen in drei arktischen Tälern analysiert.Wir weisen auf eine hohe räumliche Variabilität in der Verteilung von SOC und TN hin, welche auf komplexe Bodenprozesse zurückzuführen ist, welche entlang von Hängen auftreten. Thermokarst entlang von Hängen hat einen großen Einfluss auf die Degradierung von organischem Material und die Speicherung von SOC und TN.
Effect of mass wasting on soil organic carbon storage and coastal erosion in permafrost environments
(2015)
Accelerated permafrost thaw under the warming Arctic climate can have a significant impact on Arctic landscapes. Areas underlain by permafrost store high amounts of soil organic carbon (SOC). Permafrost disturbances may contribute to increased release of carbon dioxide and methane to the atmosphere. Coastal erosion, amplified through a decrease in Arctic sea-ice extent, may also mobilise SOC from permafrost. Large expanses of permafrost affected land are characterised by intense mass-wasting processes such as solifluction, active-layer detachments and retrogressive thaw slumping. Our aim is to assess the influence of mass wasting on SOC storage and coastal erosion.
We studied SOC storage on Herschel Island by analysing active-layer and permafrost samples, and compared non-disturbed sites to those characterised by mass wasting. Mass-wasting sites showed decreased SOC storage and material compaction, whereas sites characterised by material accumulation showed increased storage. The SOC storage on Herschel Island is also significantly correlated to catenary position and other slope characteristics. We estimated SOC storage on Herschel Island to be 34.8 kg C m-2. This is comparable to similar environments in northwest Canada and Alaska.
Coastal erosion was analysed using high resolution digital elevation models (DEMs). Two LIDAR scanning of the Yukon Coast were done in 2012 and 2013. Two DEMs with 1 m horizontal resolution were generated and used to analyse elevation changes along the coast. The results indicate considerable spatial variability in short-term coastline erosion and progradation. The high variability was related to the presence of mass-wasting processes. Erosion and deposition extremes were recorded where the retrogressive thaw slump (RTS) activity was most pronounced. Released sediment can be transported by longshore drift and affects not only the coastal processes in situ but also along adjacent coasts.
We also calculated volumetric coastal erosion for Herschel Island by comparing a stereo-photogrammetrically derived DEM from 2004 with LIDAR DEMs. We compared this volumetric erosion to planimetric erosion, which was based on coastlines digitised from satellite imagery. We found a complex relationship between planimetric and volumetric coastal erosion, which we attribute to frequent occurrence of mass-wasting processes along the coasts. Our results suggest that volumetric erosion corresponds better with environmental forcing and is more suitable for the estimation of organic carbon fluxes than planimetric erosion.
Mass wasting can decrease SOC storage by several mechanisms. Increased aeration following disturbance may increase microbial activity, which accelerates organic matter decomposition. New hydrological conditions that follow the mass wasting event can cause leaching of freshly exposed material. Organic rich material can also be directly removed into the sea or into a lake. On the other hand the accumulation of mobilised material can result in increased SOC storage. Mass-wasting related accumulations of mobilised material can significantly impact coastal erosion in situ or along the adjacent coast by longshore drift. Therefore, the coastline movement observations cannot completely resolve the actual sediment loss due to these temporary accumulations. The predicted increase of mass-wasting activity in the course of Arctic warming may increase SOC mobilisation and coastal erosion induced carbon fluxes.
Climatic variations and human activity now and increasingly in the future cause land cover changes and introduce perturbations in the terrestrial carbon reservoirs in vegetation, soil and detritus. Optical remote sensing and in particular Imaging Spectroscopy has shown the potential to quantify land surface parameters over large areas, which is accomplished by taking advantage of the characteristic interactions of incident radiation and the physico-chemical properties of a material. The objective of this thesis is to quantify key soil parameters, including soil organic carbon, using field and Imaging Spectroscopy. Organic carbon, iron oxides and clay content are selected to be analyzed to provide indicators for ecosystem function in relation to land degradation, and additionally to facilitate a quantification of carbon inventories in semiarid soils. The semiarid Albany Thicket Biome in the Eastern Cape Province of South Africa is chosen as study site. It provides a regional example for a semiarid ecosystem that currently undergoes land changes due to unadapted management practices and furthermore has to face climate change induced land changes in the future. The thesis is divided in three methodical steps. Based on reflectance spectra measured in the field and chemically determined constituents of the upper topsoil, physically based models are developed to quantify soil organic carbon, iron oxides and clay content. Taking account of the benefits limitations of existing methods, the approach is based on the direct application of known diagnostic spectral features and their combination with multivariate statistical approaches. It benefits from the collinearity of several diagnostic features and a number of their properties to reduce signal disturbances by influences of other spectral features. In a following step, the acquired hyperspectral image data are prepared for an analysis of soil constituents. The data show a large spatial heterogeneity that is caused by the patchiness of the natural vegetation in the study area that is inherent to most semiarid landscapes. Spectral mixture analysis is performed and used to deconvolve non-homogenous pixels into their constituent components. For soil dominated pixels, the subpixel information is used to remove the spectral influence of vegetation and to approximate the pure spectral signature coming from the soil. This step is an integral part when working in natural non-agricultural areas where pure bare soil pixels are rare. It is identified as the largest benefit within the multi-stage methodology, providing the basis for a successful and unbiased prediction of soil constituents from hyperspectral imagery. With the proposed approach it is possible (1) to significantly increase the spatial extent of derived information of soil constituents to areas with about 40 % vegetation coverage and (2) to reduce the influence of materials such as vegetation on the quantification of soil constituents to a minimum. Subsequently, soil parameter quantities are predicted by the application of the feature-based soil prediction models to the maps of locally approximated soil signatures. Thematic maps showing the spatial distribution of the three considered soil parameters in October 2009 are produced for the Albany Thicket Biome of South Africa. The maps are evaluated for their potential to detect erosion affected areas as effects of land changes and to identify degradation hot spots in regard to support local restoration efforts. A regional validation, carried out using available ground truth sites, suggests remaining factors disturbing the correlation of spectral characteristics and chemical soil constituents. The approach is developed for semiarid areas in general and not adapted to specific conditions in the study area. All processing steps of the developed methodology are implemented in software modules, where crucial steps of the workflow are fully automated. The transferability of the methodology is shown for simulated data of the future EnMAP hyperspectral satellite. Soil parameters are successfully predicted from these data despite intense spectral mixing within the lower spatial resolution EnMAP pixels. This study shows an innovative approach to use Imaging Spectroscopy for mapping of key soil constituents, including soil organic carbon, for large areas in a non-agricultural ecosystem and under consideration of a partially vegetation coverage. It can contribute to a better assessment of soil constituents that describe ecosystem processes relevant to detect and monitor land changes. The maps further provide an assessment of the current carbon inventory in soils, valuable for carbon balances and carbon mitigation products.