TY - JOUR A1 - Stuenzi, Simone Maria A1 - Kruse, Stefan A1 - Boike, Julia A1 - Herzschuh, Ulrike A1 - Oehme, Alexander A1 - Pestryakova, Luidmila A. A1 - Westermann, Sebastian A1 - Langer, Moritz T1 - Thermohydrological impact of forest disturbances on ecosystem-protected permafrost JF - Journal of geophysical research : Biogeosciences N2 - Boreal forests cover over half of the global permafrost area and protect underlying permafrost. Boreal forest development, therefore, has an impact on permafrost evolution, especially under a warming climate. Forest disturbances and changing climate conditions cause vegetation shifts and potentially destabilize the carbon stored within the vegetation and permafrost. Disturbed permafrost-forest ecosystems can develop into a dry or swampy bush- or grasslands, shift toward broadleaf- or evergreen needleleaf-dominated forests, or recover to the pre-disturbance state. An increase in the number and intensity of fires, as well as intensified logging activities, could lead to a partial or complete ecosystem and permafrost degradation. We study the impact of forest disturbances (logging, surface, and canopy fires) on the thermal and hydrological permafrost conditions and ecosystem resilience. We use a dynamic multilayer canopy-permafrost model to simulate different scenarios at a study site in eastern Siberia. We implement expected mortality, defoliation, and ground surface changes and analyze the interplay between forest recovery and permafrost. We find that forest loss induces soil drying of up to 44%, leading to lower active layer thicknesses and abrupt or steady decline of a larch forest, depending on disturbance intensity. Only after surface fires, the most common disturbances, inducing low mortality rates, forests can recover and overpass pre-disturbance leaf area index values. We find that the trajectory of larch forests after surface fires is dependent on the precipitation conditions in the years after the disturbance. Dryer years can drastically change the direction of the larch forest development within the studied period. KW - permafrost KW - boreal forest KW - periglacial process KW - Siberia KW - larch forest KW - disturbance Y1 - 2022 U6 - https://doi.org/10.1029/2021JG006630 SN - 2169-8953 SN - 2169-8961 VL - 127 IS - 5 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Heim, Birgit A1 - Lisovski, Simeon A1 - Wieczorek, Mareike A1 - Morgenstern, Anne A1 - Juhls, Bennet A1 - Shevtsova, Iuliia A1 - Kruse, Stefan A1 - Boike, Julia A1 - Fedorova, Irina A1 - Herzschuh, Ulrike T1 - Spring snow cover duration and tundra greenness in the Lena Delta, Siberia BT - two decades of MODIS satellite time series (2001-2021) JF - Environmental research letters N2 - 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 degrees 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. KW - Arctic vegetation KW - tundra KW - snow cover duration KW - NDVI KW - NDSI KW - MODIS KW - Lena Delta Y1 - 2022 U6 - https://doi.org/10.1088/1748-9326/ac8066 SN - 1748-9326 VL - 17 IS - 8 PB - IOP Publ. Ltd. CY - Bristol ER - TY - JOUR A1 - Kruse, Stefan A1 - Stünzi, Simone Maria A1 - Boike, Julia A1 - Langer, Moritz A1 - Gloy, Josias A1 - Herzschuh, Ulrike T1 - Novel coupled permafrost-forest model (LAVESI-CryoGrid v1.0) revealing the interplay between permafrost, vegetation, and climate across eastern Siberia JF - Geoscientific model development : GMD ; an interactive open access journal of the European Geosciences Union N2 - Boreal forests of Siberia play a relevant role in the global carbon cycle. However, global warming threatens the existence of summergreen larch-dominated ecosystems, likely enabling a transition to evergreen tree taxa with deeper active layers. Complex permafrost-vegetation interactions make it uncertain whether these ecosystems could develop into a carbon source rather than continuing atmospheric carbon sequestration under global warming. Consequently, shedding light on the role of current and future active layer dynamics and the feedbacks with the apparent tree species is crucial to predict boreal forest transition dynamics and thus for aboveground forest biomass and carbon stock developments. Hence, we established a coupled model version amalgamating a one-dimensional permafrost multilayer forest land-surface model (CryoGrid) with LAVESI, an individual-based and spatially explicit forest model for larch species (Larix Mill.), extended for this study by including other relevant Siberian forest species and explicit terrain.
Following parameterization, we ran simulations with the coupled version to the near future to 2030 with a mild climate-warming scenario. We focus on three regions covering a gradient of summergreen forests in the east at Spasskaya Pad, mixed summergreen-evergreen forests close to Nyurba, and the warmest area at Lake Khamra in the southeast of Yakutia, Russia. Coupled simulations were run with the newly implemented boreal forest species and compared to runs allowing only one species at a time, as well as to simulations using just LAVESI. Results reveal that the coupled version corrects for overestimation of active layer thickness (ALT) and soil moisture, and large differences in established forests are simulated. We conclude that the coupled version can simulate the complex environment of eastern Siberia by reproducing vegetation patterns, making it an excellent tool to disentangle processes driving boreal forest dynamics. Y1 - 2022 U6 - https://doi.org/10.5194/gmd-15-2395-2022 SN - 1991-959X SN - 1991-9603 VL - 15 IS - 6 SP - 2395 EP - 2422 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Miesner, Timon A1 - Herzschuh, Ulrike A1 - Pestryakova, Luidmila Agafyevna A1 - Wieczorek, Mareike A1 - Zakharov, Evgenii S. A1 - Kolmogorov, Alexei I. A1 - Davydova, Paraskovya V. A1 - Kruse, Stefan T1 - Forest structure and individual tree inventories of northeastern Siberia along climatic gradients JF - Earth system science data : ESSD N2 - 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 degrees N, 97-169 degrees 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. Y1 - 2022 U6 - https://doi.org/10.5194/essd-14-5695-2022 SN - 1866-3508 SN - 1866-3516 VL - 14 IS - 12 SP - 5695 EP - 5716 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Jia, Weihan A1 - Anslan, Sten A1 - Chen, Fahu A1 - Cao, Xianyong A1 - Dong, Hailiang A1 - Dulias, Katharina A1 - Gu, Zhengquan A1 - Heinecke, Liv A1 - Jiang, Hongchen A1 - Kruse, Stefan A1 - Kang, Wengang A1 - Li, Kai A1 - Liu, Sisi A1 - Liu, Xingqi A1 - Liu, Ying A1 - Ni, Jian A1 - Schwalb, Antje A1 - Stoof-Leichsenring, Kathleen R. A1 - Shen, Wei A1 - Tian, Fang A1 - Wang, Jing A1 - Wang, Yongbo A1 - Wang, Yucheng A1 - Xu, Hai A1 - Yang, Xiaoyan A1 - Zhang, Dongju A1 - Herzschuh, Ulrike T1 - Sedimentary ancient DNA reveals past ecosystem and biodiversity changes on the Tibetan Plateau: overview and prospects JF - Quaternary science reviews : the international multidisciplinary research and review journal N2 - Alpine ecosystems on the Tibetan Plateau are being threatened by ongoing climate warming and intensified human activities. Ecological time-series obtained from sedimentary ancient DNA (sedaDNA) are essential for understanding past ecosystem and biodiversity dynamics on the Tibetan Plateau and their responses to climate change at a high taxonomic resolution. Hitherto only few but promising studies have been published on this topic. The potential and limitations of using sedaDNA on the Tibetan Plateau are not fully understood. Here, we (i) provide updated knowledge of and a brief introduction to the suitable archives, region-specific taphonomy, state-of-the-art methodologies, and research questions of sedaDNA on the Tibetan Plateau; (ii) review published and ongoing sedaDNA studies from the Tibetan Plateau; and (iii) give some recommendations for future sedaDNA study designs. Based on the current knowledge of taphonomy, we infer that deep glacial lakes with freshwater and high clay sediment input, such as those from the southern and southeastern Tibetan Plateau, may have a high potential for sedaDNA studies. Metabarcoding (for microorganisms and plants), metagenomics (for ecosystems), and hybridization capture (for prehistoric humans) are three primary sedaDNA approaches which have been successfully applied on the Tibetan Plateau, but their power is still limited by several technical issues, such as PCR bias and incompleteness of taxonomic reference databases. Setting up high-quality and open-access regional taxonomic reference databases for the Tibetan Plateau should be given priority in the future. To conclude, the archival, taphonomic, and methodological conditions of the Tibetan Plateau are favorable for performing sedaDNA studies. More research should be encouraged to address questions about long-term ecological dynamics at ecosystem scale and to bring the paleoecology of the Tibetan Plateau into a new era. KW - Sedimentary ancient DNA (sedaDNA) KW - Tibetan Plateau KW - Environmental DNA KW - Taphonomy KW - Ecosystem KW - Biodiversity KW - Paleoecology KW - Paleogeography Y1 - 2022 U6 - https://doi.org/10.1016/j.quascirev.2022.107703 SN - 0277-3791 SN - 1873-457X VL - 293 PB - Elsevier CY - Oxford ER - TY - JOUR A1 - van Geffen, Femke A1 - Heim, Birgit A1 - Brieger, Frederic A1 - Geng, Rongwei A1 - Shevtsova, Iuliia A. A1 - Schulte, Luise A1 - Stuenzi, Simone M. A1 - Bernhardt, Nadine A1 - Troeva, Elena A1 - Pestryakova, Luidmila Agafyevna A1 - Zakharov, Evgenii S. A1 - Pflug, Bringfried A1 - Herzschuh, Ulrike A1 - Kruse, Stefan T1 - 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 JF - Earth system science data N2 - 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. Y1 - 2022 U6 - https://doi.org/10.5194/essd-14-4967-2022 SN - 1866-3508 SN - 1866-3516 VL - 14 IS - 11 SP - 4967 EP - 4994 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Kruse, Stefan A1 - Herzschuh, Ulrike T1 - Regional opportunities for tundra conservation in the next 1000 years JF - eLife N2 - The biodiversity of tundra areas in northern high latitudes is threatened by invasion of forests under global warming. However, poorly understood nonlinear responses of the treeline ecotone mean the timing and extent of tundra losses are unclear, but policymakers need such information to optimize conservation efforts. Our individual-based model LAVESI, developed for the Siberian tundra-taiga ecotone, can help improve our understanding. Consequently, we simulated treeline migration trajectories until the end of the millennium, causing a loss of tundra area when advancing north. Our simulations reveal that the treeline follows climate warming with a severe, century-long time lag, which is overcompensated by infilling of stands in the long run even when temperatures cool again. Our simulations reveal that only under ambitious mitigation strategies (relative concentration pathway 2.6) will ~30% of original tundra areas remain in the north but separated into two disjunct refugia. KW - Larix gmelinii KW - Larix cajanderi KW - nonlinear response KW - treeline ecotone KW - tundra KW - Ecology KW - Short Report Y1 - 2022 U6 - https://doi.org/10.7554/eLife.75163 SN - 2050-084X VL - 11 PB - eLife Sciences Publications CY - Cambridge ER - TY - JOUR A1 - Herzschuh, Ulrike A1 - Böhmer, Thomas A1 - Li, Chenzhi A1 - Cao, Xianyong A1 - Hébert, Raphaël A1 - Dallmeyer, Anne A1 - Telford, Richard J. A1 - Kruse, Stefan T1 - Reversals in temperature-precipitation correlations in the Northern Hemisphere extratropics during the Holocene JF - Geophysical research letters N2 - Future precipitation levels remain uncertain because climate models have struggled to reproduce observed variations in temperature-precipitation correlations. Our analyses of Holocene proxy-based temperature-precipitation correlations and hydrological sensitivities from 2,237 Northern Hemisphere extratropical pollen records reveal a significant latitudinal dependence and temporal variations among the early, middle, and late Holocene. These proxy-based variations are largely consistent with patterns obtained from transient climate simulations (TraCE21k). While high latitudes and subtropical monsoon areas show mainly stable positive correlations throughout the Holocene, the mid-latitude pattern is temporally and spatially more variable. In particular, we identified a reversal from positive to negative temperature-precipitation correlations in the eastern North American and European mid-latitudes from the early to mid-Holocene that mainly related to slowed down westerlies and a switch to moisture-limited convection under a warm climate. Our palaeoevidence of past temperature-precipitation correlation shifts identifies those regions where simulating past and future precipitation levels might be particularly challenging. Y1 - 2022 U6 - https://doi.org/10.1029/2022GL099730 SN - 0094-8276 SN - 1944-8007 VL - 49 IS - 22 PB - American Geophysical Union CY - Washington ER -