@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{SchulteLiLisovskietal.2022,
  author    = {Schulte, Luise and Li, Chenzhi and Lisovski, Simeon and Herzschuh, Ulrike},
  title     = {Forest-permafrost feedbacks and glacial refugia help explain the unequal distribution of larch across continents},
  series = {Journal of biogeography},
  volume    = {49},
  journal   = {Journal of biogeography},
  number    = {10},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {0305-0270},
  doi       = {10.1111/jbi.14456},
  pages     = {1825 -- 1838},
  year      = {2022},
  abstract  = {Aim: The continental-scale distribution of plant functional types, such as evergreen and summergreen needle-leaf forest, is assumed to be determined by contemporary climate. However, the distribution of summergreen needle-leaf forest of larch (Larix Mill.) differs markedly between the continents, despite relatively similar climatic conditions. The reasons for these differences are little understood. Our aim is to identify potential triggers and drivers of the current distribution patterns by comparing species' bioclimatic niches, glacial refugia and postglacial recolonization patterns. Location: Northern hemisphere. Taxon: Species of the genus Larix (Mill.). Methods: We compare species distribution and dominance using species ranges and sites of dominance, as well as their occurrence on modelled permafrost extent, and active layer thickness (ALT). We compare the bioclimatic niches and calculate the niche overlap between species, using the same data in addition to modern climate data. We synthesize pollen, macrofossil and ancient DNA palaeo-evidence of past Larix occurrences of the last 60,000 years and track differences in distribution patterns through time. Results: Bioclimatic niches show large overlaps between Asian larch species and American Larix laricina. The distribution across various degrees of permafrost extent is distinctly different for Asian L. gmelinii and L. cajanderi compared to the other species, whereas the distribution on different depths of ALT is more similar among Asian and American species. Northern glacial refugia for Larix are only present in eastern Asia and Alaska. Main Conclusion: The dominance of summergreen larches in Asia, where evergreen conifers dominate most of the rest of the boreal forests, is dependent on the interaction of several factors which allows Asian L. gmelinii and L. cajanderi to dominate where these factors coincide. These factors include the early postglacial spread out of northern glacial refugia in the absence of competitors as well as a positive feedback mechanism between frozen ground and forest.},
  language  = {en}
}
@article{vanGeffenHeimBriegeretal.2022,
  author    = {van Geffen, Femke and Heim, Birgit and Brieger, Frederic and Geng, Rongwei and Shevtsova, Iuliia A. and Schulte, Luise and Stuenzi, Simone M. and Bernhardt, Nadine and Troeva, Elena and Pestryakova, Luidmila A. 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. <br /> 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{vonHippelStoofLeichsenringSchulteetal.2022,
  author    = {von Hippel, Barbara and Stoof-Leichsenring, Kathleen R. and Schulte, Luise and Seeber, Peter Andreas and Epp, Laura Saskia and Biskaborn, Boris K. and Diekmann, Bernhard and Melles, Martin and Pestryakova, Luidmila Agafyevna and Herzschuh, Ulrike},
  title     = {Long-term funguseplant covariation from multi-site sedimentary ancient DNA metabarcoding},
  series = {Quaternary science reviews : the international multidisciplinary research and review journal},
  volume    = {295},
  journal   = {Quaternary science reviews : the international multidisciplinary research and review journal},
  publisher = {Elsevier},
  address   = {Oxford},
  issn      = {0277-3791},
  doi       = {10.1016/j.quascirev.2022.107758},
  pages     = {18},
  year      = {2022},
  abstract  = {Climate change has a major impact on arctic and boreal terrestrial ecosystems as warming leads to northward treeline shifts, inducing consequences for heterotrophic organisms associated with the plant taxa. To unravel ecological dependencies, we address how long-term climatic changes have shaped the co-occurrence of plants and fungi across selected sites in Siberia. We investigated sedimentary ancient DNA from five lakes spanning the last 47,000 years, using the ITS1 marker for fungi and the chloroplast P6 loop marker for vegetation metabarcoding. We obtained 706 unique fungal operational taxonomic units (OTUs) and 243 taxa for the plants. We show higher OTU numbers in dry forest tundra as well as boreal forests compared to wet southern tundra. The most abundant fungal taxa in our dataset are Pseudeurotiaceae, Mortierella, Sordariomyceta, Exophiala, Oidiodendron, Protoventuria, Candida vartiovaarae, Pseudeurotium, Gryganskiella fimbricystis, and Tricho-sporiella cerebriformis. The overall fungal composition is explained by the plant composition as revealed by redundancy analysis. The fungal functional groups show antagonistic relationships in their climate susceptibility. The advance of woody taxa in response to past warming led to an increase in the abun-dance of mycorrhizae, lichens, and parasites, while yeast and saprotroph distribution declined. We also show co-occurrences between Salicaceae, Larix, and Alnus and their associated pathogens and detect higher mycorrhizal fungus diversity with the presence of Pinaceae. Under future warming, we can expect feedbacks between fungus composition and plant diversity changes which will affect forest advance, species diversity, and ecosystem stability in arctic regions.},
  language  = {en}
}