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Landslides
(2022)
Erosion by landslides is a common phenomenon in mountain regions around the globe, affecting all climatic zones. Landslides facilitate bedrock weathering, pedogenesis and ecological succession, being key drivers of biodiversity. Landslide chronosequences have long been used for studies of vegetation succession in initial ecosystems, but they further offer ideal model systems for studies of soil development and microbial community succession. In this review we synthesize the state of knowledge on the role of landslides in ecosystems, their influence on element cycles and interactions with biota. Further, we discuss feedback mechanisms between global warming, landslide activity and greenhouse gas emissions. In the view of increasing anthropogenic influence and climate change, soils are becoming a critical resource. Due to their ubiquity, landslide chronosequences have the potential to provide critical insights into soil development under different climates and thereby contribute to future soil restoration efforts.
The effects of climate and topography on soil physico-chemical and microbial parameters were studied along an extensive latitudinal climate gradient in the Coastal Cordillera of Chile (26 degrees-38 degrees S). The study sites encompass arid (Pan de Azucar), semiarid (Santa Gracia), mediterranean (La Campana) and humid (Nahuelbuta) climates and vegetation, ranging from arid desert, dominated by biological soil crusts (biocrusts), semiarid shrubland and mediterranean sclerophyllous forest, where biocrusts are present but do have a seasonal pattern to temperate-mixed forest, where biocrusts only occur as an early pioneering development stage after disturbance. All soils originate from granitic parent materials and show very strong differences in pedogenesis intensity and soil depth. Most of the investigated physical, chemical and microbiological soil properties showed distinct trends along the climate gradient. Further, abrupt changes between the arid northernmost study site and the other semi-arid to humid sites can be shown, which indicate non-linearity and thresholds along the climate gradient. Clay and total organic carbon contents (TOC) as well as Ah horizons and solum depths increased from arid to humid climates, whereas bulk density (BD), pH values and base saturation (BS) decreased. These properties demonstrate the accumulation of organic matter, clay formation and element leaching as key-pedogenic processes with increasing humidity. However, the soils in the northern arid climate do not follow this overall latitudinal trend, because texture and BD are largely controlled by aeolian input of dust and sea salts spray followed by the formation of secondary evaporate minerals. Total soil DNA concentrations and TOC increased from arid to humid sites, while areal coverage by biocrusts exhibited an opposite trend. Relative bacterial and archaeal abundances were lower in the arid site, but for the other sites the local variability exceeds the variability along the climate gradient. Differences in soil properties between topographic positions were most pronounced at the study sites with the mediterranean and humid climate, whereas microbial abundances were independent on topography across all study sites. In general, the regional climate is the strongest controlling factor for pedogenesis and microbial parameters in soils developed from the same parent material. Topographic position along individual slopes of limited length augmented this effect only under humid conditions, where water erosion likely relocated particles and elements downward. The change from alkaline to neutral soil pH between the arid and the semi-arid site coincided with qualitative differences in soil formation as well as microbial habitats. This also reflects non-linear relationships of pedogenic and microbial processes in soils depending on climate with a sharp threshold between arid and semi-arid conditions. Therefore, the soils on the transition between arid and semi-arid conditions are especially sensitive and may be well used as indicators of long and medium-term climate changes. Concluding, the unique latitudinal precipitation gradient in the Coastal Cordillera of Chile is predestined to investigate the effects of the main soil forming factor - climate - on pedogenic processes.
From north to south, denudation rates from cosmogenic nuclides are similar to 10 t km(-2) yr(-1) at the arid Pan de Aziicar site, similar to 20 t km(2) yr(-1) at the semi-arid site of Santa Gracia, -60 t km(-2) yr(-1) at the Mediterranean climate site of La Campana, and similar to 30 t km(-2) yr(-1) at the humid site of Nahuelbuta. A and B horizons increase in thickness and elemental depletion or enrichment increases from north (similar to 26 degrees S) to south (similar to 38 degrees S) in these horizons. Differences in the degree of chemical weathering, quantified by the chemical depletion fraction (CDF), are significant only between the arid and sparsely vegetated site and the other three sites. Differences in the CDF between the sites, and elemental depletion within the sites are sometimes smaller than the variations induced by the bedrock heterogeneity. Microbial abundances (bacteria and archaea) in saprolite substantially increase from the arid to the semi-arid sites. With this study, we provide a comprehensive dataset characterizing the Critical Zone geochemistry in the Chilean Coastal Cordillera. This dataset confirms climatic controls on weathering and denudation rates and provides prerequisites to quantify the role of biota in future studies.
Understanding how organisms adapt to their local environment is a major focus of evolutionary biology. Local adaptation occurs when the forces of divergent natural selection are strong enough compared to the action of other evolutionary forces. An improved understanding of the genetic basis of local adaptation can inform about the evolutionary processes in populations and is of major importance because of its relevance to altered selection pressures due to climate change. So far, most insights have been gained by studying model organisms, but our understanding about the genetic basis of local adaptation in wild populations of species with little genomic resources is still limited.
With the work presented in this thesis I therefore set out to provide insights into the genetic basis of local adaptation in populations of two voles species: the common vole (Microtus arvalis) and the bank vole (Myodes glareolus). Both voles species are small mammals, they have a high evolutionary potential compared to their dispersal capabilities and are thus likely to show genetic responses to local conditions, moreover, they have a wide distribution in which they experience a broad range of different environmental conditions, this makes them an ideal species to study local adaptation.
The first study focused on producing a novel mitochondrial genome to facilitate further research in M. arvalis. To this end, I generated the first mitochondrial genome of M. arvalis using shotgun sequencing and an iterative mapping approach. This was subsequently used in a phylogenetic analysis that produced novel insights into the phylogenetic relationships of the Arvicolinae.
The following two studies then focused on the genetic basis of local adaptation using ddRAD-sequencing data and genome scan methods. The first of these involved sequencing the genomic DNA of individuals from three low-altitude and three high-altitude M. arvalis study sites in the Swiss Alps. High-altitude environments with their low temperatures and low levels of oxygen (hypoxia) pose considerable challenges for small mammals. With their small body size and proportional large body surface they have to sustain high rates of aerobic metabolism to support thermogenesis and locomotion, which can be restricted with only limited levels of oxygen available. To generate insights into high-altitude adaptation I identified a large number of single nucleotide polymorphisms (SNPs). These data were first used to identify high levels of differentiation between study sites and a clear pattern of population structure, in line with a signal of isolation by distance. Using genome scan methods, I then identified signals of selection associated with differences in altitude in genes with functions related to oxygen transport into tissue and genes related to aerobic metabolic pathways. This indicates that hypoxia is an important selection pressure driving local adaptation at high altitude in M. arvalis. A number of these genes were linked with high-altitude adaptation in other species before, which lead to the suggestion that high-altitude populations of several species have evolved in a similar manner as a response to the unique conditions at high altitude
The next study also involved the genetic basis of local adaptation, here I provided insights into climate-related adaptation in M. glareolus across its European distribution. Climate is an important environmental factor affecting the physiology of all organisms. In this study I identified a large number of SNPs in individuals from twelve M. glareolus populations distributed across Europe. I used these, to first establish that populations are highly differentiated and found a strong pattern of population structure with signal of isolation by distance. I then employed genome scan methods to identify candidate loci showing signals of selection associated with climate, with a particular emphasis on polygenic loci. A multivariate analysis was used to determine that temperature was the most important climate variable responsible for adaptive genetic variation among all variables tested. By using novel methods and genome annotation of related species I identified the function of genes of candidate loci. This showed that genes under selection have functions related to energy homeostasis and immune processes. Suggesting that M. glareolus populations have evolved in response to local temperature and specific local pathogenic selection pressures.
The studies presented in this thesis provide evidence for the genetic basis of local adaptation in two vole species across different environmental gradients, suggesting that the identified genes are involved in local adaptation. This demonstrates that with the help of novel methods the study of wild populations, which often have little genomic resources available, can provide unique insights into evolutionary processes.
Human mortality shows a pronounced temperature dependence. The minimum mortality temperature (MMT) as a characteristic point of the temperature-mortality relationship is influenced by many factors. As MMT estimates are based on case studies, they are sporadic, limited to data-rich regions, and their drivers have not yet been clearly identified across case studies. This impedes the elaboration of spatially comprehensive impact studies on heat-related mortality and hampers the temporal transfer required to assess climate change impacts. Using 400 MMTs from cities, we systematically establish a generalised model that is able to estimate MMTs (in daily apparent temperature) for cities, based on a set of climatic, topographic and socio-economic drivers. A sigmoid model prevailed against alternative model setups due to having the lowest Akaike Information Criterion (AICc) and the smallest RMSE. We find the long-term climate, the elevation, and the socio-economy to be relevant drivers of our MMT sample within the non-linear parametric regression model. A first model application estimated MMTs for 599 European cities ( >100 000 inhabitants) and reveals a pronounced decrease in MMTs (27.8-16 degrees C) from southern to northern cities. Disruptions of this pattern across regions of similar mean temperatures can be explained by socio-economic standards as noted for central eastern Europe. Our alternative method allows to approximate MMTs independently from the availability of daily mortality records. For the first time, a quantification of climatic and non-climatic MMT drivers has been achieved, which allows to consider changes in socio-economic conditions and climate. This work contributes to the comparability among MMTs beyond location-specific and regional limits and, hence, towards a spatially comprehensive impact assessment for heat-related mortality.
Early agriculture can be detected in palaeovegetation records, but quantification of the relative importance of climate and land use in influencing regional vegetation composition since the onset of agriculture is a topic that is rarely addressed. We present a novel approach that combines pollen-based REVEALS estimates of plant cover with climate, anthropogenic land-cover and dynamic vegetation modelling results. This is used to quantify the relative impacts of land use and climate on Holocene vegetation at a sub-continental scale, i.e. northern and western Europe north of the Alps. We use redundancy analysis and variation partitioning to quantify the percentage of variation in vegetation composition explained by the climate and land-use variables, and Monte Carlo permutation tests to assess the statistical significance of each variable. We further use a similarity index to combine pollen based REVEALS estimates with climate-driven dynamic vegetation modelling results. The overall results indicate that climate is the major driver of vegetation when the Holocene is considered as a whole and at the sub-continental scale, although land use is important regionally. Four critical phases of land-use effects on vegetation are identified. The first phase (from 7000 to 6500 BP) corresponds to the early impacts on vegetation of farming and Neolithic forest clearance and to the dominance of climate as a driver of vegetation change. During the second phase (from 4500 to 4000 BP), land use becomes a major control of vegetation. Climate is still the principal driver, although its influence decreases gradually. The third phase (from 2000 to 1500 BP) is characterised by the continued role of climate on vegetation as a consequence of late-Holocene climate shifts and specific climate events that influence vegetation as well as land use. The last phase (from 500 to 350 BP) shows an acceleration of vegetation changes, in particular during the last century, caused by new farming practices and forestry in response to population growth and industrialization. This is a unique signature of anthropogenic impact within the Holocene but European vegetation remains climatically sensitive and thus may continue to respond to ongoing climate change. (C) 2017 Elsevier Ltd. All rights reserved.
The Dead Sea region has faced substantial environmental challenges in recent decades, including water resource scarcity, similar to 1 m annual decreases in the water level, sinkhole development, ascending-brine freshwater pollution, and seismic disturbance risks. Natural processes are significantly affected by human interference as well as by climate change and tectonic developments over the long term. To get a deep understanding of processes and their interactions, innovative scientific approaches that integrate disciplinary research and education are required. The research project DESERVE (Helmholtz Virtual Institute Dead Sea Research Venue) addresses these challenges in an interdisciplinary approach that includes geophysics, hydrology, and meteorology. The project is implemented by a consortium of scientific institutions in neighboring countries of the Dead Sea (Israel, Jordan, Palestine Territories) and participating German Helmholtz Centres (KIT, GFZ, UFZ). A new monitoring network of meteorological, hydrological, and seismic/geodynamic stations has been established, and extensive field research and numerical simulations have been undertaken. For the first time, innovative measurement and modeling techniques have been applied to the extreme conditions of the Dead Sea and its surroundings. The preliminary results show the potential of these methods. First time ever performed eddy covariance measurements give insight into the governing factors of Dead Sea evaporation. High-resolution bathymetric investigations reveal a strong correlation between submarine springs and neo-tectonic patterns. Based on detailed studies of stratigraphy and borehole information, the extension of the subsurface drainage basin of the Dead Sea is now reliably estimated. Originality has been achieved in monitoring flash floods in an arid basin at its outlet and simultaneously in tributaries, supplemented by spatio-temporal rainfall data. Low-altitude, high resolution photogrammetry, allied to satellite image analysis and to geophysical surveys (e.g. shear-wave reflections) has enabled a more detailed characterization of sinkhole morphology and temporal development and the possible subsurface controls thereon. All the above listed efforts and scientific results take place with the interdisciplinary education of young scientists. They are invited to attend joint thematic workshops and winter schools as well as to participate in field experiments. (C) 2015 The Authors. Published by Elsevier B.V.
We report the first high-resolution (20-50 years) mid- to late Holocene pollen records from Lake Teletskoye, the largest lake in the Altai Mountains, in south-eastern West Siberia. Generally, the mid- to late Holocene (the last 4250 years) vegetation of the north-eastern Altai, as recorded in two studied sediment cores, is characterised by Siberian pine-spruce-fir forests that are similar to those of the present day. A relatively cool and dry interval with July temperatures lower than those of today occurred between 3.9 and 3.6 ka BP. The widespread distribution of open, steppe-like communities with Artemisia, Chenopodiaceae and Cyperaceae reflects maximum deforestation during this interval. After ca. 3.5 ka BP, the coniferous mountain taiga spread significantly, with maximum woody coverage and taiga biome scores between ca. 2.7 and 1.6 ka BP. This coincides well with the highest July temperature (approximately 1 degrees C higher than today) intervals. A short period of cooling about 13-1.4 ka BP could have been triggered by the increased volcanic activity recorded across the Northern Hemisphere. A new period of cooling started around 1100-1150 CE, with the minimum July temperatures occurring between 1450 and 1800 CE. (C) 2016 Elsevier B.V. All rights reserved.
The semiarid northeast of Brazil is one of the most densely populated dryland regions in the world and recurrently affected by severe droughts. Thus, reliable seasonal forecasts of streamflow and reservoir storage are of high value for water managers. Such forecasts can be generated by applying either hydrological models representing underlying processes or statistical relationships exploiting correlations among meteorological and hydrological variables. This work evaluates and compares the performances of seasonal reservoir storage forecasts derived by a process-based hydrological model and a statistical approach.
Driven by observations, both models achieve similar simulation accuracies. In a hindcast experiment, however, the accuracy of estimating regional reservoir storages was considerably lower using the process-based hydrological model, whereas the resolution and reliability of drought event predictions were similar by both approaches. Further investigations regarding the deficiencies of the process-based model revealed a significant influence of antecedent wetness conditions and a higher sensitivity of model prediction performance to rainfall forecast quality.
Within the scope of this study, the statistical model proved to be the more straightforward approach for predictions of reservoir level and drought events at regionally and monthly aggregated scales. However, for forecasts at finer scales of space and time or for the investigation of underlying processes, the costly initialisation and application of a process-based model can be worthwhile. Furthermore, the application of innovative data products, such as remote sensing data, and operational model correction methods, like data assimilation, may allow for an enhanced exploitation of the advanced capabilities of process-based hydrological models.
The semiarid northeast of Brazil is one of the most densely populated dryland regions in the world and recurrently affected by severe droughts. Thus, reliable seasonal forecasts of streamflow and reservoir storage are of high value for water managers. Such forecasts can be generated by applying either hydrological models representing underlying processes or statistical relationships exploiting correlations among meteorological and hydrological variables. This work evaluates and compares the performances of seasonal reservoir storage forecasts derived by a process-based hydrological model and a statistical approach.
Driven by observations, both models achieve similar simulation accuracies. In a hindcast experiment, however, the accuracy of estimating regional reservoir storages was considerably lower using the process-based hydrological model, whereas the resolution and reliability of drought event predictions were similar by both approaches. Further investigations regarding the deficiencies of the process-based model revealed a significant influence of antecedent wetness conditions and a higher sensitivity of model prediction performance to rainfall forecast quality.
Within the scope of this study, the statistical model proved to be the more straightforward approach for predictions of reservoir level and drought events at regionally and monthly aggregated scales. However, for forecasts at finer scales of space and time or for the investigation of underlying processes, the costly initialisation and application of a process-based model can be worthwhile. Furthermore, the application of innovative data products, such as remote sensing data, and operational model correction methods, like data assimilation, may allow for an enhanced exploitation of the advanced capabilities of process-based hydrological models.