@phdthesis{Bernhardt2008, author = {Bernhardt, Ulrike}, title = {Untersuchung zur Rolle von Adapterprotein-Komplexen im Targeting der Glucosetransporter GLUT8 und GLUT4}, pages = {V, 117 Bl. : graph. Darst.}, year = {2008}, language = {de} } @article{ZimmermannHarmsEppetal.2019, author = {Zimmermann, Heike Hildegard and Harms, Lars and Epp, Laura Saskia and Mewes, Nick and Bernhardt, Nadine and Kruse, Stefan and Stoof-Leichsenring, Kathleen Rosemarie and Pestryakova, Luidmila Agafyevna and Wieczorek, Mareike and Trense, Daronja and Herzschuh, Ulrike}, title = {Chloroplast and mitochondrial genetic variation of larches at the Siberian tundrataiga ecotone revealed by de novo assembly}, series = {PLoS one}, volume = {14}, journal = {PLoS one}, number = {7}, publisher = {PLoS}, address = {San Fransisco}, issn = {1932-6203}, doi = {10.1371/journal.pone.0216966}, pages = {21}, year = {2019}, abstract = {Larix populations at the tundra-taiga ecotone in northern Siberia are highly under-represented in population genetic studies, possibly due to the remoteness of these regions that can only be accessed at extraordinary expense. The genetic signatures of populations in these boundary regions are therefore largely unknown. We aim to generate organelle reference genomes for the detection of single nucleotide polymorphisms (SNPs) that can be used for paleogenetic studies. We present 19 complete chloroplast genomes and mitochondrial genomic sequences of larches from the southern lowlands of the Taymyr Peninsula (northernmost range of Larix gmelinii (Rupr.) Kuzen.), the lower Omoloy River, and the lower Kolyma River (both in the range of Larix cajanderi Mayr). The genomic data reveal 84 chloroplast SNPs and 213 putatively mitochondrial SNPs. Parsimony-based chloroplast haplotype networks show no spatial structure of individuals from different geographic origins, while the mitochondrial haplotype network shows at least a slight spatial structure with haplotypes from the Omoloy and Kolyma populations being more closely related to each other than to most of the haplotypes from the Taymyr populations. Whole genome alignments with publicly available complete chloroplast genomes of different Larix species show that among official plant barcodes only the rcbL gene contains sufficient polymorphisms, but has to be sequenced completely to distinguish the different provenances. We provide 8 novel mitochondrial SNPs that are putatively diagnostic for the separation of L. gmelinii and L. cajanderi, while 4 chloroplast SNPs have the potential to distinguish the L. gmelinii/ L. cajanderi group from other Larix species. Our organelle references can be used for a targeted primer and probe design allowing the generation of short amplicons. This is particularly important with regard to future investigations of, for example, the biogeographic history of Larix by screening ancient sedimentary DNA of Larix.}, language = {en} } @article{vanGeffenHeimBriegeretal.2022, author = {van Geffen, Femke and Heim, Birgit and Brieger, Frederic and Geng, Rongwei and Shevtsova, Iuliia and Schulte, Luise and Stuenzi, Simone M. and Bernhardt, Nadine and Troeva, Elena I. and Pestryakova, Luidmila Agafyevna and Zakharov, Evgenii S. and Pflug, Bringfried and Herzschuh, Ulrike and Kruse, Stefan}, title = {SiDroForest: a comprehensive forest inventory of Siberian boreal forest investigations including drone-based point clouds, individually labeled trees, synthetically generated tree crowns, and Sentinel-2 labeled image patches}, series = {Earth system science data}, volume = {14}, journal = {Earth system science data}, number = {11}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1866-3508}, doi = {10.5194/essd-14-4967-2022}, pages = {4967 -- 4994}, year = {2022}, abstract = {The SiDroForest (Siberian drone-mapped forest inventory) data collection is an attempt to remedy the scarcity of forest structure data in the circumboreal region by providing adjusted and labeled tree-level and vegetation plot-level data for machine learning and upscaling purposes. We present datasets of vegetation composition and tree and plot level forest structure for two important vegetation transition zones in Siberia, Russia; the summergreen-evergreen transition zone in Central Yakutia and the tundra-taiga transition zone in Chukotka (NE Siberia). The SiDroForest data collection consists of four datasets that contain different complementary data types that together support in-depth analyses from different perspectives of Siberian Forest plot data for multi-purpose applications. i. Dataset 1 provides unmanned aerial vehicle (UAV)-borne data products covering the vegetation plots surveyed during fieldwork (Kruse et al., 2021, ). The dataset includes structure-from-motion (SfM) point clouds and red-green-blue (RGB) and red-green-near-infrared (RGN) orthomosaics. From the orthomosaics, point-cloud products were created such as the digital elevation model (DEM), canopy height model (CHM), digital surface model (DSM) and the digital terrain model (DTM). The point-cloud products provide information on the three-dimensional (3D) structure of the forest at each plot. Dataset 2 contains spatial data in the form of point and polygon shapefiles of 872 individually labeled trees and shrubs that were recorded during fieldwork at the same vegetation plots (van Geffen et al., 2021c, ). The dataset contains information on tree height, crown diameter, and species type. These tree and shrub individually labeled point and polygon shapefiles were generated on top of the RGB UVA orthoimages. The individual tree information collected during the expedition such as tree height, crown diameter, and vitality are provided in table format. This dataset can be used to link individual information on trees to the location of the specific tree in the SfM point clouds, providing for example, opportunity to validate the extracted tree height from the first dataset. The dataset provides unique insights into the current state of individual trees and shrubs and allows for monitoring the effects of climate change on these individuals in the future. Dataset 3 contains a synthesis of 10 000 generated images and masks that have the tree crowns of two species of larch ( and ) automatically extracted from the RGB UAV images in the common objects in context (COCO) format (van Geffen et al., 2021a, ). As machine-learning algorithms need a large dataset to train on, the synthetic dataset was specifically created to be used for machine-learning algorithms to detect Siberian larch species. Larix gmeliniiLarix cajanderiDataset 4 contains Sentinel-2 (S-2) Level-2 bottom-of-atmosphere processed labeled image patches with seasonal information and annotated vegetation categories covering the vegetation plots (van Geffen et al., 2021b, ). The dataset is created with the aim of providing a small ready-to-use validation and training dataset to be used in various vegetation-related machine-learning tasks. It enhances the data collection as it allows classification of a larger area with the provided vegetation classes. The SiDroForest data collection serves a variety of user communities.
The detailed vegetation cover and structure information in the first two datasets are of use for ecological applications, on one hand for summergreen and evergreen needle-leaf forests and also for tundra-taiga ecotones. Datasets 1 and 2 further support the generation and validation of land cover remote-sensing products in radar and optical remote sensing. In addition to providing information on forest structure and vegetation composition of the vegetation plots, the third and fourth datasets are prepared as training and validation data for machine-learning purposes. For example, the synthetic tree-crown dataset is generated from the raw UAV images and optimized to be used in neural networks. Furthermore, the fourth SiDroForest dataset contains S-2 labeled image patches processed to a high standard that provide training data on vegetation class categories for machine-learning classification with JavaScript Object Notation (JSON) labels provided. The SiDroForest data collection adds unique insights into remote hard-to-reach circumboreal forest regions.}, language = {en} } @article{SchulteBernhardtStoofLeichsenringetal.2020, author = {Schulte, Luise and Bernhardt, Nadine and Stoof-Leichsenring, Kathleen Rosemarie and Zimmermann, Heike Hildegard and Pestryakova, Luidmila Agafyevna and Epp, Laura S. and Herzschuh, Ulrike}, title = {Hybridization capture of larch (Larix Mill.) chloroplast genomes from sedimentary ancient DNA reveals past changes of Siberian forest}, series = {Molecular ecology resources}, volume = {21}, journal = {Molecular ecology resources}, number = {3}, publisher = {Wiley}, address = {Hoboken}, issn = {1755-098X}, doi = {10.1111/1755-0998.13311}, pages = {801 -- 815}, year = {2020}, abstract = {Siberian larch (Larix Mill.) forests dominate vast areas of northern Russia and contribute important ecosystem services to the world. It is important to understand the past dynamics of larches in order to predict their likely response to a changing climate in the future. Sedimentary ancient DNA extracted from lake sediment cores can serve as archives to study past vegetation. However, the traditional method of studying sedimentary ancient DNA-metabarcoding-focuses on small fragments, which cannot resolve Larix to species level nor allow a detailed study of population dynamics. Here, we use shotgun sequencing and hybridization capture with long-range PCR-generated baits covering the complete Larix chloroplast genome to study Larix populations from a sediment core reaching back to 6700 years from the Taymyr region in northern Siberia. In comparison with shotgun sequencing, hybridization capture results in an increase in taxonomically classified reads by several orders of magnitude and the recovery of complete chloroplast genomes of Larix. Variation in the chloroplast reads corroborates an invasion of Larix gmelinii into the range of Larix sibirica before 6700 years ago. Since then, both species have been present at the site, although larch populations have decreased with only a few trees remaining in what was once a forested area. This study demonstrates for the first time that hybridization capture applied directly to ancient DNA of plants extracted from lake sediments can provide genome-scale information and is a viable tool for studying past genomic changes in populations of single species, irrespective of a preservation as macrofossil.}, language = {en} } @article{StoofLeichsenringBernhardtPestryakovaetal.2014, author = {Stoof-Leichsenring, Kathleen Rosemarie and Bernhardt, Nadine and Pestryakova, Luidmila Agafyevna and Epp, Laura Saskia and Herzschuh, Ulrike and Tiedemann, Ralph}, title = {A combined paleolimnological/genetic analysis of diatoms reveals divergent evolutionary lineages of Staurosira and Staurosirella (Bacillariophyta) in Siberian lake sediments along a latitudinal transect}, series = {Journal of paleolimnolog}, volume = {52}, journal = {Journal of paleolimnolog}, number = {1-2}, publisher = {Springer}, address = {Dordrecht}, issn = {0921-2728}, doi = {10.1007/s10933-014-9779-1}, pages = {77 -- 93}, year = {2014}, abstract = {Diatom diversity in lakes of northwest Yakutia (Siberia) was investigated by microscopic and genetic analysis of surface and cored lake sediments, to evaluate the use of sedimentary DNA for paleolimnological diatom studies and to identify obscure genetic diversity that cannot be detected by microscopic methods. Two short (76 and 73 bp) and one longer (577 bp) fragments of the ribulose 1,5-bisphosphate carboxylase/oxygenase (rbcL) gene, encoding the large subunit of the rbcL, were used as genetic markers. Diverse morphological assemblages of diatoms, dominated by small benthic fragilarioid taxa, were retrieved from the sediments of each lake. These minute fragilarioid taxa were examined by scanning electron microscopy, revealing diverse morphotypes in Staurosira and Staurosirella from the different lakes. Genetic analyses indicated a dominance of haplotypes that were assigned to fragilarioid taxa and less genetic diversity in other diatom taxa. The long rbcL_577 amplicon identified considerable diversification among haplotypes clustering within the Staurosira/Staurosirella genera, revealing 19 different haplotypes whose spatial distribution appears to be primarily related to the latitude of the lakes, which corresponds to a vegetation and climate gradient. Our rbcL markers are valuable tools for tracking differences between diatom lineages that are not visible in their morphologies. These markers revealed putatively high genetic diversity within the Staurosira/Staurosirella species complex, at a finer scale than is possible to resolve by microscopic determination. The rbcL markers may provide additional reliable information on the diversity of barely distinguishable minute benthic fragilarioids. Environmental sequencing may thus allow the tracking of spatial and temporal diversification in Siberian lakes, especially in the context of diatom responses to recent environmental changes, which remains a matter of controversy.}, language = {en} }