@phdthesis{Schmidt2024,
  author    = {Schmidt, Lena Katharina},
  title     = {Altered hydrological and sediment dynamics in high-alpine areas - Exploring the potential of machine-learning for estimating past and future changes},
  doi       = {10.25932/publishup-62330},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-623302},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xxi, 129},
  year      = {2024},
  abstract  = {Climate change fundamentally transforms glaciated high-alpine regions, with well-known cryospheric and hydrological implications, such as accelerating glacier retreat, transiently increased runoff, longer snow-free periods and more frequent and intense summer rainstorms. These changes affect the availability and transport of sediments in high alpine areas by altering the interaction and intensity of different erosion processes and catchment properties. Gaining insight into the future alterations in suspended sediment transport by high alpine streams is crucial, given its wide-ranging implications, e.g. for flood damage potential, flood hazard in downstream river reaches, hydropower production, riverine ecology and water quality. However, the current understanding of how climate change will impact suspended sediment dynamics in these high alpine regions is limited. For one, this is due to the scarcity of measurement time series that are long enough to e.g. infer trends. On the other hand, it is difficult - if not impossible - to develop process-based models, due to the complexity and multitude of processes involved in high alpine sediment dynamics. Therefore, knowledge has so far been confined to conceptual models (which do not facilitate deriving concrete timings or magnitudes for individual catchments) or qualitative estimates ('higher export in warmer years') that may not be able to capture decreases in sediment export. Recently, machine-learning approaches have gained in popularity for modeling sediment dynamics, since their black box nature tailors them to the problem at hand, i.e. relatively well-understood input and output data, linked by very complex processes. Therefore, the overarching aim of this thesis is to estimate sediment export from the high alpine {\"O}tztal valley in Tyrol, Austria, over decadal timescales in the past and future - i.e. timescales relevant to anthropogenic climate change. This is achieved by informing, extending, evaluating and applying a quantile regression forest (QRF) approach, i.e. a nonparametric, multivariate machine-learning technique based on random forest. The first study included in this thesis aimed to understand present sediment dynamics, i.e. in the period with available measurements (up to 15 years). To inform the modeling setup for the two subsequent studies, this study identified the most important predictors, areas within the catchments and time periods. To that end, water and sediment yields from three nested gauges in the upper {\"O}tztal, Vent, S{\"o}lden and Tumpen (98 to almost 800 km² catchment area, 930 to 3772 m a.s.l.) were analyzed for their distribution in space, their seasonality and spatial differences therein, and the relative importance of short-term events. The findings suggest that the areas situated above 2500 m a.s.l., containing glacier tongues and recently deglaciated areas, play a pivotal role in sediment generation across all sub-catchments. In contrast, precipitation events were relatively unimportant (on average, 21 \% of annual sediment yield was associated to precipitation events). Thus, the second and third study focused on the Vent catchment and its sub-catchment above gauge Vernagt (11.4 and 98 km², 1891 to 3772 m a.s.l.), due to their higher share of areas above 2500 m. Additionally, they included discharge, precipitation and air temperature (as well as their antecedent conditions) as predictors. The second study aimed to estimate sediment export since the 1960s/70s at gauges Vent and Vernagt. This was facilitated by the availability of long records of the predictors, discharge, precipitation and air temperature, and shorter records (four and 15 years) of turbidity-derived sediment concentrations at the two gauges. The third study aimed to estimate future sediment export until 2100, by applying the QRF models developed in the second study to pre-existing precipitation and temperature projections (EURO-CORDEX) and discharge projections (physically-based hydroclimatological and snow model AMUNDSEN) for the three representative concentration pathways RCP2.6, RCP4.5 and RCP8.5. The combined results of the second and third study show overall increasing sediment export in the past and decreasing export in the future. This suggests that peak sediment is underway or has already passed - unless precipitation changes unfold differently than represented in the projections or changes in the catchment erodibility prevail and override these trends. Despite the overall future decrease, very high sediment export is possible in response to precipitation events. This two-fold development has important implications for managing sediment, flood hazard and riverine ecology. This thesis shows that QRF can be a very useful tool to model sediment export in high-alpine areas. Several validations in the second study showed good performance of QRF and its superiority to traditional sediment rating curves - especially in periods that contained high sediment export events, which points to its ability to deal with threshold effects. A technical limitation of QRF is the inability to extrapolate beyond the range of values represented in the training data. We assessed the number and severity of such out-of-observation-range (OOOR) days in both studies, which showed that there were few OOOR days in the second study and that uncertainties associated with OOOR days were small before 2070 in the third study. As the pre-processed data and model code have been made publically available, future studies can easily test further approaches or apply QRF to further catchments.},
  language  = {en}
}
@phdthesis{WindirschWoiwode2024,
  author    = {Windirsch-Woiwode, Torben},
  title     = {Permafrost carbon stabilisation by recreating a herbivore-driven ecosystem},
  doi       = {10.25932/publishup-62424},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-624240},
  school      = {Universit{\"a}t Potsdam},
  pages     = {X, 104, A-57},
  year      = {2024},
  abstract  = {With Arctic ground as a huge and temperature-sensitive carbon reservoir, maintaining low ground temperatures and frozen conditions to prevent further carbon emissions that contrib-ute to global climate warming is a key element in humankind's fight to maintain habitable con-ditions on earth. Former studies showed that during the late Pleistocene, Arctic ground condi-tions were generally colder and more stable as the result of an ecosystem dominated by large herbivorous mammals and vast extents of graminoid vegetation - the mammoth steppe. Characterised by high plant productivity (grassland) and low ground insulation due to animal-caused compression and removal of snow, this ecosystem enabled deep permafrost aggrad-ation. Now, with tundra and shrub vegetation common in the terrestrial Arctic, these effects are not in place anymore. However, it appears to be possible to recreate this ecosystem local-ly by artificially increasing animal numbers, and hence keep Arctic ground cold to reduce or-ganic matter decomposition and carbon release into the atmosphere. By measuring thaw depth, total organic carbon and total nitrogen content, stable carbon iso-tope ratio, radiocarbon age, n-alkane and alcohol characteristics and assessing dominant vegetation types along grazing intensity transects in two contrasting Arctic areas, it was found that recreating conditions locally, similar to the mammoth steppe, seems to be possible. For permafrost-affected soil, it was shown that intensive grazing in direct comparison to non-grazed areas reduces active layer depth and leads to higher TOC contents in the active layer soil. For soil only frozen on top in winter, an increase of TOC with grazing intensity could not be found, most likely because of confounding factors such as vertical water and carbon movement, which is not possible with an impermeable layer in permafrost. In both areas, high animal activity led to a vegetation transformation towards species-poor graminoid-dominated landscapes with less shrubs. Lipid biomarker analysis revealed that, even though the available organic material is different between the study areas, in both permafrost-affected and sea-sonally frozen soils the organic material in sites affected by high animal activity was less de-composed than under less intensive grazing pressure. In conclusion, high animal activity af-fects decomposition processes in Arctic soils and the ground thermal regime, visible from reduced active layer depth in permafrost areas. Therefore, grazing management might be utilised to locally stabilise permafrost and reduce Arctic carbon emissions in the future, but is likely not scalable to the entire permafrost region.},
  language  = {en}
}
@phdthesis{Hippel2024,
  author    = {Hippel, Barbara von},
  title     = {Long-term bacteria-fungi-plant associations in permafrost soils inferred from palaeometagenomics},
  doi       = {10.25932/publishup-63600},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-636009},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xii, 198},
  year      = {2024},
  abstract  = {The arctic is warming 2 - 4 times faster than the global average, resulting in a strong feedback on northern ecosystems such as boreal forests, which cover a vast area of the high northern latitudes. With ongoing global warming, the treeline subsequently migrates northwards into tundra areas. The consequences of turning ecosystems are complex: on the one hand, boreal forests are storing large amounts of global terrestrial carbon and act as a carbon sink, dragging carbon dioxide out of the global carbon cycle, suggesting an enhanced carbon uptake with increased tree cover. On the other hand, with the establishment of trees, the albedo effect of tundra decreases, leading to enhanced soil warming. Meanwhile, permafrost thaws, releasing large amounts of previously stored carbon into the atmosphere. So far, mainly vegetation dynamics have been assessed when studying the impact of warming onto ecosystems. Most land plants are living in close symbiosis with bacterial and fungal communities, sustaining their growth in nutrient poor habitats. However, the impact of climate change on these subsoil communities alongside changing vegetation cover remains poorly understood. Therefore, a better understanding of soil community dynamics on multi millennial timescales is inevitable when addressing the development of entire ecosystems. Unravelling long-term cross-kingdom dependencies between plant, fungi, and bacteria is not only a milestone for the assessment of warming on boreal ecosystems. On top, it also is the basis for agriculture strategies to sustain society with sufficient food in a future warming world. The first objective of this thesis was to assess ancient DNA as a proxy for reconstructing the soil microbiome (Manuscripts I, II, III, IV). Research findings across these projects enable a comprehensive new insight into the relationships of soil microorganisms to the surrounding vegetation. First, this was achieved by establishing (Manuscript I) and applying (Manuscript II) a primer pair for the selective amplification of ancient fungal DNA from lake sediment samples with the metabarcoding approach. To assess fungal and plant co-variation, the selected primer combination (ITS67, 5.8S) amplifying the ITS1 region was applied on samples from five boreal and arctic lakes. The obtained data showed that the establishment of fungal communities is impacted by warming as the functional ecological groups are shifting. Yeast and saprotroph dominance during the Late Glacial declined with warming, while the abundance of mycorrhizae and parasites increased with warming. The overall species richness was also alternating. The results were compared to shotgun sequencing data reconstructing fungi and bacteria (Manuscripts III, IV), yielding overall comparable results to the metabarcoding approach. Nonetheless, the comparison also pointed out a bias in the metabarcoding, potentially due to varying ITS lengths or copy numbers per genome. The second objective was to trace fungus-plant interaction changes over time (Manuscripts II, III). To address this, metabarcoding targeting the ITS1 region for fungi and the chloroplast P6 loop for plants for the selective DNA amplification was applied (Manuscript II). Further, shotgun sequencing data was compared to the metabarcoding results (Manuscript III). Overall, the results between the metabarcoding and the shotgun approaches were comparable, though a bias in the metabarcoding was assumed. We demonstrated that fungal shifts were coinciding with changes in the vegetation. Yeast and lichen were mainly dominant during the Late Glacial with tundra vegetation, while warming in the Holocene lead to the expansion of boreal forests with increasing mycorrhizae and parasite abundance. Aside, we highlighted that Pinaceae establishment is dependent on mycorrhizal fungi such as Suillineae, Inocybaceae, or Hyaloscypha species also on long-term scales. The third objective of the thesis was to assess soil community development on a temporal gradient (Manuscripts III, IV). Shotgun sequencing was applied on sediment samples from the northern Siberian lake Lama and the soil microbial community dynamics compared to ecosystem turnover. Alongside, podzolization processes from basaltic bedrock were recovered (Manuscript III). Additionally, the recovered soil microbiome was compared to shotgun data from granite and sandstone catchments (Manuscript IV, Appendix). We assessed if the establishment of the soil microbiome is dependent on the plant taxon and as such comparable between multiple geographic locations or if the community establishment is driven by abiotic soil properties and as such the bedrock area. We showed that the development of soil communities is to a great extent driven by the vegetation changes and temperature variation, while time only plays a minor role. The analyses showed general ecological similarities especially between the granite and basalt locations, while the microbiome on species-level was rather site-specific. A greater number of correlated soil taxa was detected for deep-rooting boreal taxa in comparison to grasses with shallower roots. Additionally, differences between herbaceous taxa of the late Glacial compared to taxa of the Holocene were revealed. With this thesis, I demonstrate the necessity to investigate subsoil community dynamics on millennial time scales as it enables further understanding of long-term ecosystem as well as soil development processes and such plant establishment. Further, I trace long-term processes leading to podzolization which supports the development of applied carbon capture strategies under future global warming.},
  language  = {en}
}