ALBERT

Beschreibung: Scientists have long attempted to explain why closely similar age patterns of death are characteristic of highly diverse human and nonhuman populations. Historical efforts to identify a general "law of mortality" from these patterns that applied across species ended in 1935 when it was declared that such a law did not exist. These early efforts were conducted using mortality curves based on all causes of death. The authors predict that if comparisons of mortality are based instead on "intrinsic" causes of death (i.e., deaths that reflect the basic biology of the organism), then age patterns of mortality consistent with the historical concept of a law might be revealed. Using data on laboratory animals and humans, they demonstrate that age patterns of intrinsic mortality overlap when graphed on a biologically comparable time scale. These results are consistent with the existence of a law of mortality following sexual maturity, as originally asserted by Benjamin Gompertz and Raymond Pearl. The societal, medical, and research implications of such a law are discussed.

Beschreibung: Periphyton was grown on transparent plastic substrata in the Kiel Fjord and used for short-term laboratory experiments to study the feeding selectivity of the periwinkle Littorina littorea in response to the vertical structure of the periphyton. The susceptibility of algae to periwinkle grazing was assessed by comparing the species-specific biomass within the grazing tracks of the snails to the biomass outside the tracks. After 3 weeks of incubation, the periphyton consisted of a scattered monolayer of algal cells without vertical structure. No apparent grazing could be found. After 6 weeks of incubation, periphyton consisted of a tightly attached undergrowth (mainly Cocconeis scutellum, Bacillariophyceae, and Myrionema sp., Phaeophyceae) and canopy of filamentous (Melosira moniliformis, Bacillariophyceae) and stalked forms (Achnanthes longipes, Bacillariophyceae). The unicellular diatoms Fragilaria tabulata and Stauroneis constricta grew partly on the primary substratum and partly as epiphytes on the canopy species. The canopy species and the epiphytes were decimated inside the grazing tracks, while the tightly attached undergrowth species appeared ungrazed.

Beschreibung: Infrastructure and anthropogenic impacts are expanding across the Arctic. A consistent record of human impact is required in order to quantify the changes and to assess climate change impacts on the communities. We derived a first panarctic satellite-based record of expanding infrastructure and anthropogenic impacts along all permafrost affected coasts (100 km buffer) within the H2020 project Nunataryuk based on Sentinel-1/2 satellite imagery. C-band synthetic aperture radar and multi-spectral information is combined through a machine learning framework. Depending on region, we identified up to 50% more information (human presence) than in OpenStreetMap. The combination with satellite records on vegetation change (specifically NDVI from Landsat since 2000) allowed quantification of recent expansion of infrastructure. Most of the expanded human presence occurred in Russia related predominantly to oil/gas industry. The majority of areas with human presence will be subject to thaw by mid-21st century based on ground temperature trends derived from the ESA CCI+ Permafrost time series (1997-2019). Of specific concern in this context are also settlements located directly at permafrost affected coasts. An efficient erosion rate monitoring scheme needs to be developed and combined with settlement records in order to assess the risk for local communities and infrastructure. Relevant progress in the framework of the ESA EO4PAC project will be discussed.

Beschreibung: Retrogressive thaw slumps (RTS) are typical landforms indicating processes of rapid thawing and degrading permafrost. Their abundance is increasing in many regions and quantifying their dynamics is of high importance for assessing geomorphic, hydrologic, and biogeochemical impacts of climate change in the Arctic. Here we present a deep-learning (DL) based semantic segmentation framework to detect RTS, using high-resolution multi-spectral PlanetScope, topographic (ArcticDEM elevation and slope), and medium-resolution multi-temporal Landsat Trend data. We created a highly automated processing pipeline, which is designed to allow reproducible results and to be flexible for multiple input data types. The processing workflow is based on the pytorch deep-learning framework and includes a variety of different segmentation architectures (UNet, UNet++, DeepLabV3), backbones and includes common data transformation techniques such as augmentation or normalization. We tested (training, validation) our DL based model in six different regions of 100 to 300 km² size across Canada, and Siberia. We performed a regional cross-validation (5 regions training, 1 region validation) to test the spatial robustness and transferability of the algorithm. Furthermore, we tested different architectures, backbones and loss-functions to identify the best performing and most robust parameter sets. For training the models we created a database of manually digitized and validated RTS polygons. The resulting model performance varied strongly between different regions with maximum Intersection over Union (IoU) scores between 0.15 and 0.58. The strong regional variation emphasizes the need for sufficiently large training data, which is representative of the diversity of RTS types. However, the creation of good training data proved to be challenging due to the fuzzy definition and delineation of RTS. We are further continuing to improve the usability and the functionality to add further datasets and classes. We will show first results from the upscaling beyond small test areas towards large spatial clusters of extensive RTS presence e.g. Peel Plateau in NW Canada.

Beschreibung: With the Earth’s climate rapidly warming, the Arctic represents one of the most vulnerable regions to environmental change. These northern high latitude regions experience intensified fire seasons and especially tundra fires are projected to become more frequent and severe. Fires in permafrost regions have extensive impacts, including the initiation of thermokarst (rapid thaw of ice-rich ground), as they combust the upper organic soil layers which provide insulation to the permafrost below. Rapid permafrost thaw is, thus, often observable in fire scars in the first years post-disturbance. In polygonal ice-wedge landscapes, this becomes most prevalent through melting ice wedges and degrading troughs. The further these ice wedges degrade, the more troughs will likely connect and build an extensive hydrological network with changing patterns and degrees of connectivity that influences hydrology and runoff. While subsiding troughs over melting ice wedges may host new ponds, an increasing connectivity may also subsequently lead to more drainage of ponds, which in turn can limit further thaw and help stabilize the landscape. To quantify the changes in such dynamic landscapes over large regions, highly automated methods are needed that allow extracting information on the geomorphic state and changes over time of ice-wedge trough networks from remote sensing data. We developed a computer vision algorithm to automatically derive ice-wedge polygonal networks and the current microtopography of the degrading troughs from very high resolution, airborne laserscanning-based digital terrain models. We represent the networks as graphs (a concept from the computer sciences to describe complex networks) and apply methods from graph theory to describe and quantify hydrological network characteristics of the changing landscape. In fire scars, we especially observe rapidly growing networks and fast micromorphological change in those degrading troughs. In our study, we provide a space-for-time substitution comparing fire scars throughout the Alaskan tundra of up to 70 years since the fire disturbance, to show how this type of disturbed landscape evolves over time.

Beschreibung: Using our custom visualization tool for multitemporal Landsat satellite imagery we discovered, to our knowledge, an undocumented mega-landslide in far-east Siberia, which occurred in summer 2017 (https://bit.ly/2WYRLM1; 61.55°N; 170.01°E). To create and visualize this unique dataset, we processed temporal trends of multispectral indices of 〉100,000 Landsat images for a period from 2000-2019 using the freely available Google Earth Engine cloud processing platform (https://ingmarnitze.users.earthengine.app/view/hotspottcvisapp). The megaslide has a size of 3.66 km² and using the ArcticDEM data we estimate a volume movement of ~20 Mm³. With this size and volume, the landslide is among the largest globally known in recent decades. The landslide is accompanied by a smaller one (0.31 km², 1 Mm³) about 600 m further east, which already occurred in summer 2015. The large landslide caused the formation of several small lakes by blocking two valleys with debris and within newly formed crevasses near the hilltop, which are still persisting as of August 2021. As this event occurred in a remote valley far from any settlement, no visible damage to infrastructure or human livelihoods was detected. The remoteness has likely led to being not detected, like many similar, albeit a lot smaller, erosion features in the Arctic permafrost region. In this presentation we will show the main properties of the landslide, potential trigger mechanisms in the traditional sense. As this region is located along the fringes of permafrost presence we will discuss its potential connection to the rapidly warming climate in the high latitudes. Further, we will discuss how such a large event remained undetected for several years. We discuss and highlight the value of our landscape change visualization tool based on Landsat trend analysis (see Nitze et al., AGU 2020), which helped us to identify this extreme event. With more and more available data sources, this tool in addition to automated image analysis (e.g. deep-learning) or seismic analysis will help to uncover the hidden processes and dynamics of the Earth’s surface.

Beschreibung: Several decades of research have provided insight into patterns of and controls on thermokarst initiation and expansion, yet studies tend to focus on individual types of thermokarst (i.e., thaw lake formation and subsequent drainage) in particular regions. Today, we are left with uneven knowledge about abrupt permafrost thaw both conceptually and regionally. The goal of this presentation is to summarize recent advancements in monitoring thermokarst and its impact on soil, vegetation, and water while also framing a call to action for the next decade of research. Over the next decade, permafrost researchers must align their efforts on several fronts to not only increase our knowledge about changing permafrost but to align this knowledge with key community and policy needs. To support climate change planning and adaptation, northern communities need future thaw vulnerability mapped at scales relevant to their needs, which will require a suite of downscaled and new mapping and remote sensing products. Thermokarst predisposition maps based on circumpolar datasets greatly overestimate the area vulnerable to thermokarst, which can lead to poor planning and climate anxiety. In some situations, existing mapping products may be useful for downscaling with more detailed input data. In other situations, entirely new approaches may be required to support local action. A second key need for community relevant research is the ability to detect and monitor early warning indicators of thermokarst. Such information is needed to support scenario planning and to help mitigate the risks to social, cultural, and physical infrastructure created by permafrost change. We are evaluating the potential for using changes in vegetation, wetting/drying and topography as early warning indicators of thermokarst, all of which can be remotely sensed. Finally, integrating fine-scale disturbances such as thermokarst into large scale models remains a key challenge but critical for supporting sound climate policy. While a diversity of permafrost modeling approaches is necessary, we outline guiding principles that will help enhance model comparisons, assimilation of simulated data across spatiotemporal scales, and the ability for policy decisions to be rapidly informed by emerging science on permafrost change.

Beschreibung: Methane emissions from northern high latitude wetlands constitute a major uncertainty in the atmospheric methane (CH4) budget during the Holocene. To reconstruct northern wetland methane emissions, we used an empirical model based on syntheses of observations of peat initiation from more than 3600 radiocarbon-dated basal peat ages, plant-macrofossil-derived peatland type from more than 250 peat cores from sites across the northern high latitudes, and observed CH4 emissions averaged from modern-day wetland types in order to explore the effects of wetland expansion and changes in wetland type. Peatland basal ages and plant macrofossil records showed the widespread formation of fens in major northern wetland complexes before 8000 BP. After 8000 BP, new fen formation continued, but widespread peatland succession (to bogs) and permafrost aggradation also occurred. Reconstructed CH4 emissions from peatlands increased rapidly between 10,600 BP and 6900 BP due to fen formation and expansion, then stabilized after 5000 BP at 42 ± 25 Tg CH4 y-1, as high methane-emitting fens transitioned to lower methane-emitting bogs and permafrost peatlands. Permafrost formation in northern peatlands after 1000 BP decreased CH4 emissions by 20% to 34 ± 21 Tg y-1 by the present day. Warming temperatures, changes in peatland hydrology, and permafrost thaw will likely change the magnitude of northern peatland emissions in the future.

Beschreibung: The modeling of the atmospheric boundary layer over sea ice is still challenging because of the complex interaction between clouds, radiation and turbulence over the often inhomogeneous sea ice cover. There is still much uncertainty concerning sea ice roughness, near-surface thermal stability and related processes, and their accurate parameterization. Here, a regional Arctic climate model forced by ERA-interim data was used to test the sensitivity of climate simulations to a modified surface flux parameterization for wintertime conditions over the Arctic. The reference parameterization as well as the modified one is based on Monin–Obukhov similarity theory, but different roughness lengths were prescribed and the stability dependence of the transfer coefficients for momentum, heat and moisture differed from each other. The modified parameterization accounts for the most compre- hensive observations that are presently available over sea ice in the inner Arctic. Independent of the parameterization used, the model was able to reproduce the two observed dominant winter states with respect to cloud cover and longwave radiation. A stepwise use of the different parameterization assumptions showed that modifications of both surface roughness and stability dependence had a considerable impact on quantities such as air pressure, wind and near-surface turbulent fluxes. However, the reduction of surface roughness to values agreeing with those observed during t he Surface Heat Budget of the Arctic Ocean campaign led to an improvement in the western Arctic, while the modified stability parameteri- zation had only a minor impact. The latter could be traced back to the model's underestimation of the strength of stability over sea ice. Future work should concentrate on possible reasons for this underestimation and on the question of generality of the results for other climate models

Beschreibung: Globally, mesoscale processes create a rich and filamented pattern in biological productivity. Despite of remoteness and a harsh environment, observations likewise show an impact of mesoscale processes on phytoplankton growth in the Arctic. Observations of sufficiently high resolution are, however, difficult to carry out. Large-scale models are another way to gain knowledge about the system. In the current study, we use a global sea ice-ocean biogeochemical model, which is eddy resolving in Fram Strait, to show that the mesoscale dynamics has a strong effect on shaping phytoplankton growth. For the year 2009, we demonstrate that the growth season in the West Spitzbergen Current can be divided into two regimes; during Regime I, which takes place in May and June before and during the spring bloom, high chlorophyll concentrations are associated with areas of positive vorticity and a shallow mixed layer, pointing toward light limitation controlling growth. During Regime II, which occurs after the bloom from mid-July to late August, the highest chlorophyll concentration is found in areas of negative vorticity. Here, upwelling of nutrient-rich water occurs, through doming isopycnals, acting to raise the nutricline, may also play a role in alleviating nutrient limitation in the surface water. The study suggests that the mesoscale eddy environment locally modulates the seasonal cycle of light and nutrient limitation. Knowledge of the eddy field should be taken into consideration for making conclusions from point-wise measurements in Fram Strait.

Beschreibung: Predicting the implications of ongoing ocean climate warming demands a better understanding of how short-term thermal variability impacts marine ectotherms, particularly at beyond-optimal average conditions during summer heatwaves. Using a globally important model species, the blue mussel Mytilus, in a 5-week-long experiment, we (a) assessed growth performance traits under 12 scenarios, consisting of four thermal averages (18.5, 21, 23.5 and 26℃) imposed as constant or daily fluctuating regimes with amplitudes of 2 or 4℃. Additionally, we conducted a short-term assay using different mussel individuals to (b) test for the species capacity for suppression and recovery of metabolic performance traits (feeding and aerobic respiration) when exposed to a 1-day thermal fluctuation regime (16.8–30.5℃). Using this high-resolution data, we (c) generated short-term thermal metabolic performance curves to predict and explain growth responses observed in the long-term experiment. We found that daily high-amplitude thermal cycles (4℃) improved mussel growth when fluctuations were imposed around an extreme average temperature of 26℃, representing end-of-century heatwaves. In contrast, thermal cycles negatively affected mussel growth at a less extreme average temperature of 23.5℃, resembling current peak summer temperature scenarios. These results suggest that fluctuations ameliorate heat stress impacts only at critically high average temperatures. The short-term assay demonstrated that during the warming phase, animals stopped feeding between 24 and 30℃ while gradually suppressing respiration. In the subsequent cooling phase, feeding and respiration partially and fully recovered to pre-heating rates respectively. Furthermore, nonlinear averaging of short-term feeding responses (upscaling) well-predicted longer term growth responses to fluctuations. Our findings suggest that fluctuations can be beneficial to or detrimental for the long-term performance of ectothermic animals, depending on the fluctuations' average and amplitude. Furthermore, the observed effects can be linked to fluctuation-mediated metabolic suppression and recovery. In a general framework, we propose various hypothetical scenarios of fluctuation impacts on ectotherm performance considering inter- or intra-species variability in heat sensitivity. Our research highlights the need for studying metabolic performance in relation to cyclic abiotic fluctuations to advance the understanding of climate change impacts on aquatic systems. A free Plain Language Summary can be found within the Supporting Information of this article

Beschreibung: Three arrays of ocean bottom seismographs have been deployed to study the seismicity at the northern end of the Juan de Fuca ridge system off western Canada. Nearly 100 events were located with estimated accuracies generally better than ±10 km, all lying on or near the en echalon ridge-transform fault plate boundaries as defined in this area by the magnetic anomalies, the seafloor morphology and by other geophysical data. The depths of 12 events were determined to lie between 2 and 6 km below the top of the crust. The seismograms exhibit clear P and S wave arrivals along with phases that involve P to S and sometimes S to P conversion probably at the base of the sediments beneath the instruments. The event magnitudes have been estimated from signal duration using four calibration events that were well recorded by a land station. The magnitude estimates permit the determination of rough magnitude-frequency of occurrence relations over the magnitude range of 1 to 3 that are in surprisingly good agreement with the recurrence relations for the area at larger magnitudes from 75 years of land station data. The mean P wave velocity in the uppermost mantle from the earthquake data recorded by the sea floor arrays is 7.6 km s-1 and the mean Vp/Vs ratio is 1.71 or a Poisson's ratio of 0.24.

Beschreibung: The Bransfield Basin is a young (∼4 Ma) back-arc basin related to the remnant subduction of the Phoenix Plate that once existed along the entire Pacific margin of the Antarctic Peninsula. Based on a recently deployed amphibious seismic network, we use ambient noise tomography to obtain the S-wave velocity structure in the Central Bransfield Basin (CBB). Combining with the stress field inverted from focal mechanisms, our images reveal that the CBB suffers a significant extension in the northwest-southeast direction. The extension is strongest in the northeastern CBB with associated mantle exhumation and weakens to the southwest with decoupled deformations between the upper crust and lithospheric mantle. Such an along-strike variation of extension can be explained by slab window formation and forearc rotation, which are associated with the Phoenix Plate detachment during the ridge–trench collisions at the southwest of the Hero Fracture Zone.

Beschreibung: Physical activity is important for health. However, there is a lack of literature related to the physical activity levels of adults living in urban villagers, which is a vulnerable population in China. The aim of this study is to compare the physical activity and sedentary behavior engagements between urban villagers and non-urban villagers using the 2019 Luohu Shenzhen, China Community Diagnosis Questionnaire. A total of 1205 adults living in urban villages and non-urban villages were included in the analysis. Unadjusted and multiple multivariate logistic regression were conducted for the dependent variable of engagement in recreational physical activity, frequency of recreational physical activity per week, and hours spent in sedentary behaviors per day. Descriptive analysis was conducted to identify the reasons for not engaging in physical activity among urban villagers and non-urban villagers. Across the included sample, 29.05% were urban villagers and 70.95% were non-urban villagers. The results suggested that urban villagers are more likely to engage in physical activity than non-urban villager (OR = 1.90, 95% CI [1.40, 2.59], p 〈 0.001). However, it was also found that urban village status had no significant association for frequency in engaging in physical activity and average hours spent in sedentary behaviors. Both urban villagers and non-urban villages indicated that lack of time, lack of safe and appropriate environment, and working in labor intensive occupations as some of the reasons for not engaging in physical activity. There is a need for tailed interventions and policies for promoting physical activity among urban villagers and non-urban villagers. Additional studies are needed to further our understanding of the physical activity behaviors among urban villagers in China.

Beschreibung: Adherent-invasive Escherichia coli (AIEC) is a pathovar linked to inflammatory bowel diseases (IBD), especially Crohn’s disease, and colorectal cancer. AIEC are genetically diverse, and in the absence of a universal molecular signature, are defined by in vitro functional attributes. The relative ability of difference AIEC strains to colonize, persist, and induce inflammation in an IBD-susceptible host is unresolved. To evaluate strain-level variation among tissue-associated E. coli in the intestines, we develop a long-read sequencing approach to identify AIEC by strain that excludes host DNA. We use this approach to distinguish genetically similar strains and assess their fitness in colonizing the intestine. Here we have assembled complete genomes using long-read nanopore sequencing for a model AIEC strain, NC101, and seven strains isolated from the intestinal mucosa of Crohn’s disease and non-Crohn’s tissues. We show these strains can colonize the intestine of IBD susceptible mice and induce inflammatory cytokines from cultured macrophages. We demonstrate that these strains can be quantified and distinguished in the presence of 99.5% mammalian DNA and from within a fecal population. Analysis of global genomic structure and specific sequence variation within the ribosomal RNA operon provides a framework for efficiently tracking strain-level variation of closely-related E. coli and likely other commensal/pathogenic bacteria impacting intestinal inflammation in experimental settings and IBD patients.