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In terms of climate change and climate change mitigation, the quantitative knowledge of global carbon pools is important information. On the one hand, knowledge on the amount of carbon cycling among – and stored in – global pools (i.e. Atmosphere, Biosphere, Cryosphere, Hydrosphere, and Lithosphere) may improve the reliability of models predicting atmospheric CO2 concentrations in terms of fossil fuel combustion. On the other hand, the carbon sequestration potential of specific ecosystems allows for estimating their feasibility regarding carbon trade mechanisms such as the Clean Development Mechanism or the Reducing Emissions from Deforestation and Degradation Program (REDD+). However, up to date, the majority of terrestrial carbon assessments have focused on forests and peatlands, leaving a data gap open regarding the remaining ecosystems. This data gap is likely to be explained by the relatively high carbon densities and/or productivities of forests and peatlands. Nevertheless, to get a precise as possible global picture, information on carbon pools and sequestration of other ecosystems is needed. Although desert ecosystems generally express low carbon densities, they may absolutely store a remarkable amount of carbon due to their large areal extent. In this context, Central Asian Deserts (in particular within the Turanian Deserts, i.e. Karakum, Kysylkum, Muyunkum) likely inhibit comparably high carbon pools as they express a sparse vegetation cover due to an exceptionally high annual precipitation if compared to the World’s deserts. In this dissertation, three important woody plant species – Populus euphratica and Haloxylon aphyllum and Haloxylon persicum – of Central Asian Deserts were investigated for their carbon pools and carbon sequestration potential. These species were chosen as they I) locally express high carbon densities, II) are dominant species, III) have a rather large spatial distribution, and IV) have experienced a strong degradation throughout the 20th century. Thus, they likely show a remarkable potential for carbon re-sequestration through restoration and thus for an application of carbon trade mechanisms (CHAPTER I). P. euphratica was investigated in the nature reserve Kabakly at the Amu Darya, Turkmenistan and in Iminqak at the Tarim He, Xinjiang, China. The assessment of Haloxylon species was restricted to the Turanian deserts west of the Tain Shan. To achieve a first scientific basis for large scale estimates, different methodologies, ranging from allometric formulas, over dendrochronology to remote sensing were combined (CHAPTERS II-V). In CHAPTER II allometric formulas were successfully developed for Haloxylon aphyllum and Haloxylon persicum and applied to six study sites distributed over the Turanian Deserts to represent the allometric variability of Haloxylon species in Central Asia. CHAPTER III derives another allometric formula (only based on canopy area) for H. aphyllum and combines it with a remote sensing analysis from the nature reserve Repetek. Thereby, a first large scale estimate covering the Northeastern Karakum Desert of carbon pools related to mono specific H. aphyllum stands is achieved. CHAPTER IV describes the wood structure of Populus euphratica forests in the nature reserve Kabakly (Turkmenistan) and in Iminqak (Xinjiang, China). In CHAPTER V a dendrochronological approach derives models for predicting the Net Primary Productivity (NPP) and the age of P. euphratica in the nature reserve Kabakly. Thereby, a first feasibility assessment regarding remote sensing analyses and the upscaling of the obtained NPP results is carried out. First estimates based on these local studies (CHAPTER VI), reveal carbon densities ranging from 0.1 – 26.3 t C ha 1 for the three investigated species. Highest maximum and median carbon densities were found for P. euphratica, but Haloxylon aphyllum expressed remarkable maximum carbon densities (13.1 t C ha-1), too. The total carbon pools were estimated at 6480 kt C for P. euphratica, 520 kt C for H. aphyllum stands and 6900 kt C for Haloxylon persicum shrubland. Accounting for the extent of degraded areas, the total re-sequestration potentials of the respective species were estimated at 4320 kt C, 1620 kt C and 21900 kt C, this highlighting the remarkable absolute re-sequestration potential of H. persicum shrubland despite its low average carbon densities. In the end, the main results were put into a broader context (CHAPTER VI), discussing the general feasibility of reforestations both in ecological terms as well as in terms of carbon trade mechanisms. A short example highlights the strong connection between the feasibility of reforestations and the global carbon market. Finally, open research questions are brought forth revealing the yet large research potential of Central Asian Desert ecosystems in general and in terms of carbon sequestration.
High resolution palaeo-ecological analysis of an Arctic ice-wedge polygon mire (Kytalyk, NE Siberia)
(2020)
Ice-wedge polygon mires are typical features of the Artic and therefore especially affected by climate change. They show, caused by soil-ice action, an amazing regular polygonal structure in meter dimension of higher and lower elevated dry and wet parts, and to this microtopography adapted vegetation. Polygon mires play, analogous to other mires, an important role in carbon sequestration, water balance, wildlife habitat and archive value with local to global significance. By storing enormous amounts of the global soil carbon polygon mires are crucial for our climate. Despite this relevance by covering large areas, polygon mires are comparatively poorly scientifically investigated and understood. It is still difficult to make forecasts on how polygon mires will develop under a changing climate in the Arctic, especially because internal factors and self-organisation complicate the understanding of their functioning. Therefore the investigation of modern and past polygon mires is necessary. This dissertation presents high resolution palaeo-ecological studies of a Northeast Siberian model polygon: ice-wedge polygon Lhc11 located in the Indigirka Lowlands at the scientific station Kytalyk. During field work in July 2011 the study site, covering an area of 26 × 21 m was divided into 546 plots, in which vegetation composition and microtopographical elevation characteristics were assessed and surface samples were collected. For palaeoecological analysis a 105.5 cm long peat section was excavated from the same site. Cluster analysis revealed five plant communities, which are clearly separated with respect to ground surface height, frost surface height and coverages of open water and vegetation, confirming the pattern already identified in other studies of Arctic ice-wedge polygons. The correct recognition of these patterns is crucial in palaeoecological studies in order to reconstruct landscape elements and their dynamics. This recognition requires insight in the short-distance relationships between surface elevation/wetness, vegetation and pollen deposition. The applied pollen-vegetation reference study shows that in general modern pollen deposition in polygon Lhc11 corresponds well with actual vegetation, allowing accurate reconstruction of local site conditions from fossil palynomorph sequences, including the reconstruction of the dynamics of closely spaced microtopographical elements. We conducted an evaluation of common palaeo proxies to compare their wetness reconstruction potential. The analysed proxies macrofossils, pollen, testate amoebae, geochemistry and sediment properties show similar wetness trends. Macrofossils provided the most detailed wetness reconstruction, spanning several wetness classes from very dry to wet, because they could be identified to genus or species level. However, as the proxies sometimes show contradictory results, a multi-proxy approach is preferable over a single proxy interpretation as it allows the reconstruction of environmental development in a broader palaeoecological context. For a better understanding of polygon dynamics and former greenhouse gas fluxes, more detailed and better quantified palaeo-microtopographical information is required. Therefore we developed a new transfer approach for modelling past Ground Surface Heights (GSH) in polygon mires from plant fossils. Based on the composition of modern vegetation we constructed two sets of potential fossil types (plant macrofossils and pollen), an extensive and a more restricted one. We applied Canonical Correspondence Analysis to model the relationships between potential fossil types and measured GSH. Both models show a strong relationship between modelled and measured GSH values and a high accuracy in prediction. Finally, we used the models to predict GSH values for Holocene peat samples. We found a fair correspondence with expert-based multi-proxy reconstruction of wetness conditions, even though only a minor part of the encountered fossils were represented in the GSH models, illustrating the robustness of the approach. The method can thus be used to reconstruct palaeoenvironmental conditions in a more objective way and can serve as a template for further palaeoecological studies. The 4000 years lasting history of the Lhc11 polygon site started with the establishment of a low-centre polygon in a drained thermokarst lake basin. Polygon Lhc11 formed part of a low-centre polygon for about 2000 years, experiencing enormous environmental influences discernible by incidence of silt, charred detritus, change of fossils composition and strongly declined peat accumulation rates and finally developed into a mature and degradation stage, into a low-high-centre polygon, currently characterized by high elevation differences. In the context of less studied but large-scale polygon mire occurrence, the high-resolution analysed ice-wedge polygon Lhc11 delivers insights into state and dynamics of a representative Siberian polygon site, in terms of modern and past vegetation and elevation characteristics. Furthermore the present study provides facilities for palaeoecological polygon studies including a new quantitative elevation modelling approach and provides valuable datasets for future research, e.g. greenhouse gas emissions and therefore contributes to a better understanding of these climate relevant ecosystems.