Permafrost

Permafrost is perennially frozen ground, such as soil, rock, and ice. In permafrost regions, plant and microbial life persists primarily in the near-surface soil that thaws every summer, called the ‘active layer’ (Figure 20). The cold and wet conditions in many permafrost regions limit decomposition of organic matter. In combination with soil mixing processes caused by repeated freezing and thawing, this has led to the accumulation of large stocks of soil organic carbon in the permafrost zone over multi-millennial timescales. As the climate warms, permafrost carbon could be highly vulnerable to climatic warming. Permafrost occurs primarily in high latitudes (e.g. Arctic and Antarctic) and at high elevation (e.g. Tibetan Plateau, Figure 21). The thickness of permafrost varies from less than 1 m (in boreal peatlands) to more than 1 500 m (in Yakutia). The coldest permafrost is found in the Transantarctic Mountains in Antarctica (−36°C) and in northern Canada for the Northern Hemisphere (-15°C; Obu et al., 2019, 2020). In contrast, some of the warmest permafrost occurs in peatlands in areas with mean air temperatures above 0°C. Here permafrost exists because thick peat layers insulate the ground during the summer. Most of the permafrost existing today formed during cold glacials (e.g. before 12 000 years ago) and has persisted through warmer interglacials. Some shallow permafrost (max 30–70m depth) formed during the Holocene (past 5000 years) and some even during the Little Ice Age from 400–150 years ago. There are few extensive regions suitable for row crop agriculture in the permafrost zone. Additionally, in areas where large-scale agriculture has been conducted, ground destabilization has been common. Surface disturbance such as plowing or trampling of vegetation can alter the thermal regime of the soil, potentially triggering surface subsidence or abrupt collapse. This may influence soil hydrology, nutrient cycling, and organic matter storage. These changes often have acute and negative consequences for continued agricultural use of such landscapes. Thus, row-crop agriculture could have a negative impact on permafrost (e.g. Grünzweig et al., 2014). Conversely, animal husbandry is widespread in the permafrost zone, including horses, cattle, and reindeer

Systematic Quantification and Assessment of Digital Image Correlation Performance for Landslide Monitoring

Accurate and reliable analyses of high-alpine landslide displacement magnitudes and rates are key requirements for current and future alpine early warnings. It has been proved that high spatiotemporal-resolution remote sensing data combined with digital image correlation (DIC) algorithms can accurately monitor ground displacements. DIC algorithms still rely on significant amounts of expert input; there is neither a general mathematical description of type and spatiotemporal resolution of input data nor DIC parameters required for successful landslide detection, accurate characterisation of displacement magnitude and rate, and overall error estimation. This work provides generic formulas estimating appropriate DIC input parameters, drastically reducing the time required for manual input parameter optimisation. We employed the open-source code DIC-FFT using optical remote sensing data acquired between 2014 and 2020 for two landslides in Switzerland to qualitatively and quantitatively show which spatial resolution is required to recognise slope displacements, from satellite images to aerial orthophotos, and how the spatial resolution affects the accuracy of the calculated displacement magnitude and rate. We verified our results by manually tracing geomorphic markers in orthophotos. Here, we show a first generic approach for designing and optimising future remote sensing-based landslide monitoring campaigns to support time-critical applications like early warning systems.ISSN:2076-326

Global and Planetary Change / Glacial lakes in Austria - Distribution and formation since the Little Ice Age

Glacial lakes constitute a substantial part of the legacy of vanishing mountain glaciation and act as water storage, sediment traps and sources of both natural hazards and leisure activities. For these reasons, they receive growing attention by scientists and society. However, while the evolution of glacial lakes has been studied intensively over timescales tied to remote sensing-based approaches, the longer-term perspective has been omitted due a lack of suitable data sources. We mapped and analyzed the spatial distribution of glacial lakes in the Austrian Alps. We trace the development of number and area of glacial lakes in the Austrian Alps since the Little Ice Age (LIA) based on a unique combination of a lake inventory and an extensive record of glacier retreat. We find that bedrock-dammed lakes are the dominant lake type in the inventory. Bedrock- and morainedammed lakes populate the highest landscape domains located in cirques and hanging valleys. We observe lakes embedded in glacial deposits at lower locations on average below 2000ma.s.l. In general, the distribution of glacial lakes over elevation reflects glacier erosional and depositional dynamics rather than the distribution of total area. The rate of formation of new glacial lakes (number, area) has continuously accelerated over time with present rates showing an eight-fold increase since LIA. At the same time the total glacier area decreased by twothirds. This development coincides with a long-term trend of rising temperatures and a significant stepping up of this trend within the last 20 years in the Austrian Alps.FUTURELAKES(VLID)359348

Performance Testing of Optical Flow Time Series Analyses Based on a Fast, High-Alpine Landslide

Accurate remote analyses of high-alpine landslides are a key requirement for future alpine safety. In critical stages of alpine landslide evolution, UAS (unmanned aerial system) data can be employed using image registration to derive ground motion with high temporal and spatial resolution. However, classical area-based algorithms suffer from dynamic surface alterations and their limited velocity range restricts detection, resulting in noise from decorrelation and hindering their application to fast landslides. Here, to reduce these limitations we apply for the first time the optical flow-time series to landslides for the analysis of one of the fastest and most critical debris flow source zones in Austria. The benchmark site Sattelkar (2130–2730 m asl), a steep, high-alpine cirque in Austria, is highly sensitive to rainfall and melt-water events, which led to a 70,000 m³ debris slide event after two days of heavy precipitation in summer 2014. We use a UAS data set of five acquisitions (2018–2020) over a temporal range of three years with 0.16 m spatial resolution. Our new methodology is to employ optical flow for landslide monitoring, which, along with phase correlation, is incorporated into the software IRIS. For performance testing, we compared the two algorithms by applying them to the UAS image stacks to calculate time-series displacement curves and ground motion maps. These maps allow the exact identification of compartments of the complex landslide body and reveal different displacement patterns, with displacement curves reflecting an increased acceleration. Visually traceable boulders in the UAS orthophotos provide independent validation of the methodology applied. Here, we demonstrate that UAS optical flow time series analysis generates a better signal extraction, and thus less noise and a wider observable velocity range—highlighting its applicability for the acceleration of a fast, high-alpine landslide

NO and N 2 O transformations of diverse fungi in hypoxia: evidence for anaerobic respiration only in Fusarium strains

International audienceFungal denitrification is claimed to produce non‐negligible amounts of N2O in soils, but few tested species have shown significant activity. We hypothesized that denitrifying fungi would be found among those with assimilatory nitrate reductase, and tested 20 such batch cultures for their respiratory metabolism, including two positive controls, Fusarium oxysporum and Fusarium lichenicola, throughout the transition from oxic to anoxic conditions in media supplemented with urn:x-wiley:14622912:media:emi14980:emi14980-math-0001. Enzymatic reduction of urn:x-wiley:14622912:media:emi14980:emi14980-math-0002 (NIR) and NO (NOR) was assessed by correcting measured NO‐ and N2O‐kinetics for abiotic NO‐ and N2O‐production (sterile controls). Significant anaerobic respiration was only confirmed for the positive controls and for two of three Fusarium solani cultures. The NO kinetics in six cultures showed NIR but not NOR activity, observed through the accumulation of NO. Others had NOR but not NIR activity, thus reducing abiotically produced NO to N2O. The presence of candidate genes (nirK and p450nor) was confirmed in the positive controls, but not in some of the NO or N2O accumulating cultures. Based on our results, we conclude that only the Fusarium cultures were able to sustain anaerobic respiration and produced low amounts of N2O as a response to an abiotic NO production from the medium