Time-lagged response of siberian treeline forests revealed by individual-based modelling

Global warming allows arctic vegetation, which is mainly limited by temperatures, to move north. A change from tundra to taiga will cause a decrease of albedo which further fuels the warming through positive feedback mechanisms. This raises several questions of which we want to address here: (1) Will trees move northwards and thereby change vast treeless tundra areas to taiga? (2) And if so, how long does this response lags behind the temperature changes? To answer these questions we built an individual-based and spatially-explicit vegetation simulator model for larches in Siberia (LAVESI). We present the parameterization and validation of the model's incorporated processes which describe the full life-cycle of the simulated larch species Larix gmelinii. Furthermore, we share results of the first regional-scale simulations testing the model's performance at the Taymyr Peninsula, Russia, ranging from 64-80° N and 92-120° E. In a second experiment, we tested the influence of up to 6 °C warmer and cooler climates on simulated populations. Our results show that already the recent temperature rise will allow forests to expand farther north by roughly one degree, when no seed limitation hinders populations to migrate. Furthermore, climate warming caused populations to densify but with a time-lag of decades. We conclude that in the near future expanding taiga after its first establishment in the former tundra will rapidly form dense tree stands, thus ultimatively fueling the feedback loop of global warming. We show that simulation results of the newly-build vegetation model were reliable, and hence the model can be used as a tool to improve our knowledge about individual-based processes that are important to understand past and future treeline migration

Spring snow cover duration and tundra greenness in the Lena Delta, Siberia: two decades of MODIS satellite time series (2001–2021)

The Lena Delta in Siberia is the largest delta in the Arctic and as a snow-dominated ecosystem particularly vulnerable to climate change. Using the two decades of MODerate resolution Imaging Spectroradiometer satellite acquisitions, this study investigates interannual and spatial variability of snow-cover duration and summer vegetation vitality in the Lena Delta. We approximated snow by the application of the normalized difference snow index and vegetation greenness by the normalized difference vegetation index (NDVI). We consolidated the analyses by integrating reanalysis products on air temperature from 2001 to 2021, and air temperature, ground temperature, and the date of snow-melt from time-lapse camera (TLC) observations from the Samoylov observatory located in the central delta. We extracted spring snow-cover duration determined by a latitudinal gradient. The ‘regular year’ snow-melt is transgressing from mid-May to late May within a time window of 10 days across the delta. We calculated yearly deviations per grid cell for two defined regions, one for the delta, and one focusing on the central delta. We identified an ensemble of early snow-melt years from 2012 to 2014, with snow-melt already starting in early May, and two late snow-melt years in 2004 and 2017, with snow-melt starting in June. In the times of TLC recording, the years of early and late snow-melt were confirmed. In the three summers after early snow-melt, summer vegetation greenness showed neither positive nor negative deviations. Whereas, vegetation greenness was reduced in 2004 after late snow-melt together with the lowest June monthly air temperature of the time series record. Since 2005, vegetation greenness is rising, with maxima in 2018 and 2021. The NDVI rise since 2018 is preceded by up to 4 °C warmer than average June air temperature. The ongoing operation of satellite missions allows to monitor a wide range of land surface properties and processes that will provide urgently needed data in times when logistical challenges lead to data gaps in land-based observations in the rapidly changing Arctic.GeoXREKLIMBMBFERCPeer Reviewe

Forest structure and individual tree inventories of northeastern Siberia along climatic gradients

We compile a data set of forest surveys from expeditions to the northeast of the Russian Federation, in Krasnoyarsk Krai, the Republic of Sakha (Yakutia), and the Chukotka Autonomous Okrug (59–73∘ N, 97–169∘ E), performed between the years 2011 and 2021. The region is characterized by permafrost soils and forests dominated by larch (Larix gmelinii Rupr. and Larix cajanderi Mayr). Our data set consists of a plot database describing 226 georeferenced vegetation survey plots and a tree database with information about all the trees on these plots. The tree database, consisting of two tables with the same column names, contains information on the height, species, and vitality of 40 289 trees. A subset of the trees was subject to a more detailed inventory, which recorded the stem diameter at base and at breast height, crown diameter, and height of the beginning of the crown. We recorded heights up to 28.5 m (median 2.5 m) and stand densities up to 120 000 trees per hectare (median 1197 ha−1), with both values tending to be higher in the more southerly areas. Observed taxa include Larix Mill., Pinus L., Picea A. Dietr., Abies Mill., Salix L., Betula L., Populus L., Alnus Mill., and Ulmus L. In this study, we present the forest inventory data aggregated per plot. Additionally, we connect the data with different remote sensing data products to find out how accurately forest structure can be predicted from such products. Allometries were calculated to obtain the diameter from height measurements for every species group. For Larix, the most frequent of 10 species groups, allometries depended also on the stand density, as denser stands are characterized by thinner trees, relative to height. The remote sensing products used to compare against the inventory data include climate, forest biomass, canopy height, and forest loss or disturbance. We find that the forest metrics measured in the field can only be reconstructed from the remote sensing data to a limited extent, as they depend on local properties. This illustrates the need for ground inventories like those data we present here. The data can be used for studying the forest structure of northeastern Siberia and for the calibration and validation of remotely sensed data. They are available at https://doi.org/10.1594/PANGAEA.943547 (Miesner et al., 2022).</p

Neurological manifestations in children and adolescents with neurofibromatosis type-1-implications for management and surveillance [Abstract]

INTRODUCTION: We aimed to (1) characterize the spectrum of clinical phenotypes of NF1 in a random pediatric population, (2) correlate genotype with phenotypic expression for those with a genetic diagnosis, and (3) explore radiological features of NF1 in the central nervous system (CNS) by radiomics analyses to predict clinical course. METHODS: We performed a database search in the hospital information system of the University Children′s Hospital between January 2017 and December 2020 for patients with NF1 and evaluated the clinical phenotype by retrospective chart review. RESULTS: 75 children/adolescents were identified with suspicion/clinical diagnosis of NF1 (median age 10.0 years (range, 1.1-22.6); 35 female), confirmatory revised “diagnostic criteria” were met in 57 patients at the last follow-up. Per number of documented items, major signs were detected as 73/75 café-au-lait macules, 31/63 freckling, 38/71 neurofibromas (thereof 21 plexiform neurofibromas), 18/43 optic pathway glioma, 5/66 Lisch nodules, and two patients with sphenoid dysplasia. Genetic analysis (31/75) identified pathogenic NF1 variants in 27 patients. In 20/66 cases a parent met diagnostic criteria. Cognitive symptoms included developmental delay (28/68), learning deficits (12/48), attention-deficit hyperactivity disorder (3/53), and behavior anomalies (7/63). Classical unidentified bright objects were seen in 29/43, other intracranial tumors in 7/43, and cerebrovascular abnormalities in 5/43. Analysis of imaging features of the CNS in these patients will involve lesion segmentation and radiomics features. Symptomatic/progressive low-grade glioma necessitated neurosurgical resection (4/25) and/or chemotherapy (12/25). In 10/25 neuropsychological functions were assessed by the German neuropsychological basic diagnostic instrument. Until June 30th, 2021, one patient died of progressive plexiform neurofibroma. CONCLUSIONS: A wide range of neurological manifestations, including neuropsychological deficits, should raise the suspicion of NF1 in an unselected pediatric population. We expect imaging features of the CNS to better predict the clinical course and enhance decision-making

Peptide exchange on MHC-I by TAPBPR is driven by a negative allostery release cycle.

Chaperones TAPBPR and tapasin associate with class I major histocompatibility complexes (MHC-I) to promote optimization (editing) of peptide cargo. Here, we use solution NMR to investigate the mechanism of peptide exchange. We identify TAPBPR-induced conformational changes on conserved MHC-I molecular surfaces, consistent with our independently determined X-ray structure of the complex. Dynamics present in the empty MHC-I are stabilized by TAPBPR and become progressively dampened with increasing peptide occupancy. Incoming peptides are recognized according to the global stability of the final pMHC-I product and anneal in a native-like conformation to be edited by TAPBPR. Our results demonstrate an inverse relationship between MHC-I peptide occupancy and TAPBPR binding affinity, wherein the lifetime and structural features of transiently bound peptides control the regulation of a conformational switch located near the TAPBPR binding site, which triggers TAPBPR release. These results suggest a similar mechanism for the function of tapasin in the peptide-loading complex

Digitalisierung beruflicher Lern- und Arbeitsprozesse. Impulse aus der Bauwirtschaft und anderen gewerblich-technischen Sektoren

Der Sammelband stellt aktuelle Ansätze zum digital unterstützten beruflichen Lernen dar. Die Beiträge geben Einblicke in die dynamische Entwicklung der Schnittstellen von Erwerbsarbeit und beruflicher Aus-, Fort- und Weiterbildung im Kontext der Digitalisierung Arbeits- und Lernmitteln. Der Band schließt damit an die 2019 ebenfalls im Universitätsverlag der Technischen Universität Berlin erschienene Publikation „Berufsbildung am Bau digital“ (hrsg. von Bernd Mahrin und Johannes Meyser) an. Das erste Kapitel erörtert grundsätzliche didaktische Fragen zu digital unterstütztem Lernen und Arbeiten einschließlich der Rahmenbedingungen. Im zweiten Kapitel schließen sich Beiträge zur Kapazitätsentwicklung, zu Standards und zu digitalen Werkzeugen an. Das dritte Kapitel widmet sich konkreten Einzellösungen mit starkem Praxisbezug und hohem Transferpotenzial zum digitalisierten Arbeiten und Lernen im Bausektor und im Metallbereich. Das abschließende vierte Kapitel präsentiert übergreifend nutzbare und frei zugängliche Online-Angebote wie einen Medienpool für Bildungszwecke, eine Lernmedien-Datenbank und ein hybrides Lernsystem mit virtuellem 3D-Gebäudemodell. Das Buch ist entstanden im Rahmen des durch das Bundesministerium für Bildung und Forschung und den Europäischen Sozialfonds geförderten Projektes DigiBAU – Digitales Bauberufliches Lernen und Arbeiten. (DIPF/Orig.)The anthology presents current approaches to digitally supported professional learning. The articles provide insights into the dynamic development of the interfaces between gainful employment and vocational training and further education in the context of digitization of work and learning aids. The volume is thus connected to the publication “Berufsbildung am Bau digital” (edited by Bernd Mahrin and Johannes Meyser), which was published in 2019 by the University Press of the Technische Universität Berlin. The first chapter discusses fundamental didactic questions about digitally supported learning and working, including the framework conditions. The second chapter picks contributions on capacity development, standards, and digital tools out as central themes. The third chapter is dedicated to concrete specific solutions with strong practical relevance and high transfer potential for digitized work and learning in the construction sector and in the metal sector. The final fourth chapter presents comprehensive and freely accessible online offers such as a media pool for educational purposes, a learning media database and a hybrid learning system with a virtual 3D building model. The book was created as part of the DigiBAU project - digital vocational learning and working in the field of construction - funded by the German Federal Ministry of Education and Research and the European Social Fund. (DIPF/Orig.

Compilation of pollen productivity estimates and taxonomically harmonised relative pollen productivity (RPP) datasets for Europe, northern America, China and the Northern Hemisphere extratropics

Relative pollen productivity (RPP) estimates allow to recalculate vegetation cover from pollen counts. This dataset contains: * a comprehensive compilation of available RPP studies and their data including information on the study design and models used to calculate the RPP values in the original studies. * taxonomically harmonised RPP datasets for America (including Greenland), Europe (including Arctic Russia), China and one combined for the whole Northern hemisphere extratropics built out of the available studies. * fall speeds, which are necessary to reconstruct vegetation cover out of pollen counts and RPP values. We advise the user to read the manuscript doi:10.5194/essd-2019-242 accompanying the dataset prior to use especially the taxonomically harmonised datasets

Compilation of relative pollen productivity (RPP) estimates and taxonomically harmonised RPP datasets for single continents and Northern Hemisphere extratropics

Relative pollen productivity (RPP) estimates are fractionate values, often in relation to Poaceae, that allow vegetation cover to be estimated from pollen counts with the help of models. RPP estimates are especially used in the scientific community in Europe and China, with a few studies in North America. Here we present a comprehensive compilation of available northern hemispheric RPP studies and their results arising from 51 publications with 60 sites and 131 taxa. This compilation allows scientists to identify data gaps in need of further RPP analyses but can also aid them in finding an RPP set for their study region. We also present a taxonomically harmonised, unified RPP dataset for the Northern Hemisphere and subsets for North America (including Greenland), Europe (including arctic Russia), and China, which we generated from the available studies. The unified dataset gives the mean RPP for 55 harmonised taxa as well as fall speeds, which are necessary to reconstruct vegetation cover from pollen counts and RPP values. Data are openly available at https://doi.org/10.1594/PANGAEA.922661 (Wieczorek and Herzschuh, 2020)

Treeline dynamics in Siberia under changing climates as inferred from an individual-based model for Larix

Siberian boreal forests are expected to expand northwards in the course of global warming. However, processes of the treeline ecotone transition, as well astiming and related climate feedbacks are still not understood. Here, we present ‘Larix Vegetation Simulator’ LAVESI, an individual-based spatially-explicit model that can simulate Larix gmelinii (Rupr.) Rupr. stand dynamics in an attempt to improve our understanding about past and future treeline movements under changing climates. The relevant processes (growth, seed production and dispersal, establishment and mortality) are incorporated and adjusted to observation data mainly gained from the literature. Results of a local sensitivity analysis support the robustness of the model’s parameterization by giving relatively small sensitivity values. We tested the model by simulating tree stands under modern climate across the whole Taymyr Peninsula, north-central Siberia (c. 64–80° N; 92–119° E). We find tree densities similar to observed forests in the northern to mid-treeline areas, but densities are overestimated in the southern parts of the simulated region. Finally, from a temperature-forcing experiment, we detect that the responses of tree stands lag the hypothetical warming by several decades, until the end of 21st century. With our simulation experiments we demonstrate that the newly-developed model captures the dynamics of the Siberian latitudinal treeline