Genetic and morphologic determination of diatom community composition in surface sediments from glacial and thermokarst lakes in the Siberian Arctic

Lakes cover large parts of the climatically sensitive Arctic landscape and respond rapidly to environmental change. Arctic lakes have different origins and include the predominant thermokarst lakes, which are small, young and highly dynamic, as well as large, old and stable glacial lakes. Freshwater diatoms dominate the primary producer community in these lakes and can be used to detect biotic responses to climate and environmental change. We used specific diatom metabarcoding on sedimentary DNA, combined with next-generation sequencing and diatom morphology, to assess diatom diversity in five glacial and 15 thermokarst lakes within the easternmost expanse of the Siberian treeline ecotone in Chukotka, Russia. We obtained 163 verified diatom sequence types and identified 176 diatom species morphologically. Although there were large differences in taxonomic assignment using the two approaches, they showed similar high abundances and diversity of Fragilariceae and Aulacoseiraceae. In particular, the genetic approach detected hidden within-lake variations of fragilarioids in glacial lakes and dominance of centric Aulacoseira species, whereas Lindavia ocellata was predominant using morphology. In thermokarst lakes, sequence types and valve counts also detected high diversity of Fragilariaceae, which followed the vegetation gradient along the treeline. Ordination analyses of the genetic data from glacial and thermokarst lakes suggest that concentrations of sulfate, an indicator of the activity of sulfate-reducing microbes under anoxic conditions, and bicarbonate, which relates to surrounding vegetation, have a significant influence on diatom community composition. For thermokarst lakes, we also identified lake depth as an important variable, but sulfate best explains diatom diversity derived from genetic data, whereas bicarbonate best explains the data from valve counts. Higher diatom diversity was detected in glacial lakes, most likely related to greater lake age and different edaphic settings, which gave rise to diversification and endemism. In contrast, small, dynamic thermokarst lakes are inhabited by stress-tolerant fragilarioids and are related to different vegetation types along the treeline ecotone. Our study demonstrated that genetic investigations of lake sediments can be used to interpret climate and environmental responses of diatoms. It also showed how lake type affects diatom diversity, and that such genetic analyses can be used to track diatom community changes under ongoing warming in the Arctic

Intraspecific structure of the Coregonus lavaretus complex in water bodies of Siberia: a case of postglacial allopatric origin of Yukagirian whitefish

The results of morphological and genetic analyses of forms/species of the Coregonus lavaretus pidschian (Gmelin, 1789) complex from the Indigirka and Kolyma river basins are presented in the context of there being recent postglacial speciation events. It has been found that the studied whitefishes belong to the sparsely rakered and low lateral-line forms and have previously been described as Coregonus lavaretus pidschian n. jucagiricus Drjagin (Berg), 1932. Based on these characters, this whitefish does not differ from most Arctic whitefish populations (in particular from Coregonus lavaretus glacialis Kirillov, 1972). Analysis of variability of the ND1 gene (mtDNA) showed that whitefishes from the Indigirka and Kolyma basins belong to a distant phylogenetic lineage, which is significantly different from all previously studied whitefish lineages from the Ob, Yenisei, Lena, Anadyr, and Amur river basins. Analysis of variability of the ITS1 fragment (nDNA) showed that all studied forms/species (from Ob River to Amur River basins), including C. l. pidschian n. jucagiricus, have a tandem arrangement of two identical nucleotide fragments and very similar nucleotide composition of the ITS1 region. Based on contemporary data, this phylogenetic lineage of the C. pidschian complex could be considered a young postglacial allopatric species.info:eu-repo/semantics/acceptedVersio

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

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

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, https://doi.org/10.1594/PANGAEA.933263). 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.ii. 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, https://doi.org/10.1594/PANGAEA.932821). 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.iii. Dataset 3 contains a synthesis of 10 000 generated images and masks that have the tree crowns of two species of larch (Larix gmelinii and Larix cajanderi) automatically extracted from the RGB UAV images in the common objects in context (COCO) format (van Geffen et al., 2021a, https://doi.org/10.1594/PANGAEA.932795). 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.iv. Dataset 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, https://doi.org/10.1594/PANGAEA.933268). 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.</p

Paleolimnological studies in Russian northern Eurasia: A review

© 2017, Pleiades Publishing, Ltd. This article presents a review of the current data on the level of paleolimnological knowledge about lakes in the Russian part of the northern Eurasia. The results of investigation of the northwestern European part of Russia as the best paleolimnologically studied sector of the Russian north is presented in detail. The conditions of lacustrine sedimentation at the boundary between the Late Pleistocene and Holocene and the role of different external factors in formation of their chemical composition, including active volcanic activity and possible large meteorite impacts, are also discussed. The results of major paleoclimatic and paleoecological reconstructions in northern Siberia are presented. Particular attention is given to the databases of abiotic and biotic parameters of lake ecosystems as an important basis for quantitative reconstructions of climatic and ecological changes in the Late Pleistocene and Holocene. Keywords: paleolimnology, lakes, bottom sediments, northern

Растительность низовий р. Индигирки (равнинные и горные тундры)

Район низовий р. Индигирки отлича­ется довольно высоким ценотическим разнообрази­ем, здесь выявлено 9 ассоциаций, 4 субассоциации и 5 вариантов, относящихся к 5 классам эколого-фло­ристической классификации. Пять ассоциации и 4 субассоциаций описаны впервые. Описаны широко распространенные в Сибирской Арктике моховые (асс. Carici arctisibiricae–Hylocomietum alaskani) и дриадовые (асс. Rhytidio rugosi–Dryadetum punc­tate) тундры, нивальные мохово-разнотравные луга (асс. Deschampsio–Cerastietum regelii) и криофитные травяные болота (асс. Meesio triquetris–Caricetum stantis). Выделены также новые синтаксоны. Для подзоны типичных тундр описаны влагалищнопуши­цево-лишайниково-моховые тундры (асс. Tephrosero atropurpureae–Salicetum pulchrae), приуроченные к выположенным частям водоразделов, и злаково-ку­старничково-зеленомошные нивальные тундры (асс. Astragalo frigidi–Salicetum reptantis), развитые на прирусловых речных террасах. Тундровые моховые ивняки (асс. Sanionio uncinati–Salicetum hastatae) за­нимают склоны водоразделов как в подзоне южных тундр, так и подгольцовом горном поясе Кондаков­ского плоскогорья. Осоково-сфагновые болота (асс. Carici rariflorae–Sphagnetum warnstorfii) являются элементом валиково-полигональных тундрово-болот­ных комплексов в подзоне южных тундр. Эродиро­ванные щебнисто-каменистые склоны р. Индигирки занимают сообщества асс. Potentillo arenosae–Thy­metum oxyodonti.Выявлены особенности подзонально-поясной дифференциации синтаксонов в зависимости от соот­ношения географических групп видов. Разнообразие растительности обусловлено выраженностью здесь наряду с равнинными, также и горных ландшафтов Кондаковского плоскогорья.</p

Disturbance-effects on treeline larch-stands in the lower Kolyma River area (NE Siberia)

Tree stands in the boreal treeline ecotone are, in addition to climate change, impacted by disturbances such as fire, water-related disturbances and logging. We aim to understand how these disturbances affect growth, age structure, and spatial patterns of larch stands in the north-eastern Siberian treeline ecotone (lower Kolyma River region), an insufficiently researched region. Stand structure of Larix cajanderi Mayr was studied at seven sites impacted by disturbances. Maximum tree age ranged from 44 to 300 years. Young to medium-aged stands had, independent of disturbance type, the highest stand densities with over 4000 larch trees per ha. These sites also had the highest growth rates for tree height and stem diameter. Overall lowest stand densities were found in a polygonal field at the northern end of the study area, with larches growing in distinct “tree islands”. At all sites, saplings are significantly clustered. Differences in fire severity led to contrasting stand structures with respect to tree, recruit, and overall stand densities. While a low severity fire resulted in low-density stands with high proportions of small and young larches, high severity fires resulted in high-density stands with high proportions of big trees. At waterdisturbed sites, stand structure varied between waterlogged and drained sites and latitude. These mixed effects of climate and disturbance make it difficult to predict future stand characteristics and the treeline position