Refine
Year of publication
Language
- English (49)
Is part of the Bibliography
- yes (49)
Keywords
- pollen (9)
- Siberia (8)
- treeline (6)
- climate change (4)
- metabarcoding (4)
- vegetation (4)
- Diatoms (3)
- diatoms (3)
- permafrost (3)
- sedimentary ancient DNA (3)
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.
A strong temperature increase in the Arctic is expected to lead to latitudinal treeline shift. This tundra-taiga turnover would cause a positive vegetation-climate feedback due to albedo decrease. However, reliable estimates of tree migration rates are currently lacking due to the complex processes involved in forest establishment, which depend strongly on seed dispersal. We aim to fill this gap using LAVESI, an individual-based and spatially explicit Larix vegetation simulator. LAVESI was designed to simulate plots within homogeneous forests. Here, we improve the implementation of the seed dispersal function via field-based investigations. We inferred the effective seed dispersal distances of a typical open-forest stand on the southern Taymyr Peninsula (northern central Siberia) from genetic parentage analysis using eight nuclear microsatellite markers. The parentage analysis gives effective seed dispersal distances (median similar to 10 m) close to the seed parents. A comparison between simulated and observed effective seed dispersal distances reveals an overestimation of recruits close to the releasing tree and a shorter dispersal distance generally. We thus adapted our model and used the newly parameterised version to simulate south-to-north transects; a slow-moving treeline front was revealed. The colonisation of the tundra areas was assisted by occasional long-distance seed dispersal events beyond the treeline area. The treeline (similar to 1 tree ha(-1)) advanced by similar to 1.6 m yr(-1), whereas the forest line (similar to 100 trees ha(-1)) advanced by only similar to 0.6 m yr(-1). We conclude that the treeline in northern central Siberia currently lags behind the current strong warming and will continue to lag in the near future.
Forest structure is a crucial component in the assessment of whether a forest is likely to act as a carbon sink under changing climate. Detailed 3D structural information about the tundra–taiga ecotone of Siberia is mostly missing and still underrepresented in current research due to the remoteness and restricted accessibility. Field based, high-resolution remote sensing can provide important knowledge for the understanding of vegetation properties and dynamics. In this study, we test the applicability of consumer-grade Unmanned Aerial Vehicles (UAVs) for rapid calculation of stand metrics in treeline forests. We reconstructed high-resolution photogrammetric point clouds and derived canopy height models for 10 study sites from NE Chukotka and SW Yakutia. Subsequently, we detected individual tree tops using a variable-window size local maximum filter and applied a marker-controlled watershed segmentation for the delineation of tree crowns. With this, we successfully detected 67.1% of the validation individuals. Simple linear regressions of observed and detected metrics show a better correlation (R2) and lower relative root mean square percentage error (RMSE%) for tree heights (mean R2 = 0.77, mean RMSE% = 18.46%) than for crown diameters (mean R2 = 0.46, mean RMSE% = 24.9%). The comparison between detected and observed tree height distributions revealed that our tree detection method was unable to representatively identify trees <2 m. Our results show that plot sizes for vegetation surveys in the tundra–taiga ecotone should be adapted to the forest structure and have a radius of >15–20 m to capture homogeneous and representative forest stands. Additionally, we identify sources of omission and commission errors and give recommendations for their mitigation. In summary, the efficiency of the used method depends on the complexity of the forest’s stand structure.
Genetic investigations on eukaryotic plankton confirmed the existence of modern biogeographic patterns, but analyses of palaeoecological data exploring the temporal variability of these patterns have rarely been presented. Ancient sedimentary DNA proved suitable for investigations of past assemblage turnover in the course of environmental change, but genetic relatedness of the identified lineages has not yet been undertaken. Here, we investigate the relatedness of diatom lineages in Siberian lakes along environmental gradients (i.e. across treeline transects), over geographic distance and through time (i.e. the last 7000 years) using modern and ancient sedimentary DNA. Our results indicate that closely-related Staurosira lineages occur in similar environments and less-related lineages in dissimilar environments, in our case different vegetation and co-varying climatic and limnic variables across treeline transects. Thus our study reveals that environmental conditions rather than geographic distance is reflected by diatom-relatedness patterns in space and time. We tentatively speculate that the detected relatedness pattern in Staurosira across the treeline could be a result of adaptation to diverse environmental conditions across the arctic boreal treeline, however, a geographically-driven divergence and subsequent repopulation of ecologically different habitats might also be a potential explanation for the observed pattern.
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.
Forest structure and individual tree inventories of northeastern Siberia along climatic gradients
(2022)
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.
This paper presents two new pollen records and quantitative climate reconstructions from northern Chukotka documenting environmental changes over the last 27.9 ka. Open tundra- and steppe-like habitats dominated between 27.9 and 18.7 cal. ka BP. Betula and Alnus shrubs might have grown in sheltered microhabitats but disappeared after 18.7 cal. ka BP. Although the climate was rather harsh, local herb-dominated communities supported herbivores as is evident by the presence of coprophilous spores in the sediments. The increase in Salix and Cyperaceae similar to 16.1 cal. ka BP suggests climate amelioration. Shrub Betula appeared similar to 15.9 cal. ka BP, and became dominant after similar to 15.52 cal. ka BP, whilst typical steppe communities drastically reduced. Very high presence of Botryococcus in the Lateglacial sediments reflects widespread shallow habitats, probably due to lake level increase. Shrub Alnus became common after similar to 13 cal. ka BP reflecting further climate amelioration. Simultaneously, herb communities gradually decreased in the vegetation reaching a minimum similar to 11.8 cal. ka BP. A gradual decrease of algae remains suggests a reduction of shallow-water habitats. Shrubby and graminoid tundra was dominant similar to 11.8-11.1 cal. ka BP, later Salix stands significantly decreased. The forest-tundra ecotone established in the Early Holocene, shortly after 11.1 cal. ka BP. Low contents of green algae in the Early Holocene sediments likely reflect deeper aquatic conditions. The most favourable climate conditions were between similar to 10.6 and 7 cal. ka BP. Vegetation became similar to the modern after similar to 7 cal. ka BP but Pinus pumila came to the Ilirney area at about 1.2 cal. ka BP. It is important to emphasize that the study area provided refugia for Betula and Alnus during MIS 2. It is also notable that our records do not reflect evidence of Younger Dryas cooling, which is inconsistent with some regional environmental records but in good accordance with some others.
Relationships between climate, species composition, and species richness are of particular importance for understanding how boreal ecosystems will respond to ongoing climate change. This study aims to reconstruct changes in terrestrial vegetation composition and taxa richness during the glacial Late Pleistocene and the interglacial Holocene in the sparsely studied southeastern Yakutia (Siberia) by using pollen and sedimentary ancient DNA (sedaDNA) records. Pollen and sedaDNA metabarcoding data using the trnL g and h markers were obtained from a sediment core from Lake Bolshoe Toko. Both proxies were used to reconstruct the vegetation composition, while metabarcoding data were also used to investigate changes in plant taxa richness. The combination of pollen and sedaDNA approaches allows a robust estimation of regional and local past terrestrial vegetation composition around Bolshoe Toko during the last similar to 35,000 years. Both proxies suggest that during the Late Pleistocene, southeastern Siberia was covered by open steppe-tundra dominated by graminoids and forbs with patches of shrubs, confirming that steppe-tundra extended far south in Siberia. Both proxies show disturbance at the transition between the Late Pleistocene and the Holocene suggesting a period with scarce vegetation, changes in the hydrochemical conditions in the lake, and in sedimentation rates. Both proxies document drastic changes in vegetation composition in the early Holocene with an increased number of trees and shrubs and the appearance of new tree taxa in the lake's vicinity. The sedaDNA method suggests that the Late Pleistocene steppe-tundra vegetation supported a higher number of terrestrial plant taxa than the forested Holocene. This could be explained, for example, by the "keystone herbivore" hypothesis, which suggests that Late Pleistocene megaherbivores were able to maintain a high plant diversity. This is discussed in the light of the data with the broadly accepted species-area hypothesis as steppe-tundra covered such an extensive area during the Late Pleistocene.
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.
Continuous pollen and chironomid records from Lake Emanda (65 degrees 17'N, 135 degrees 45'E) provide new insights into the Late Quaternary environmental history of the Yana Highlands (Yakutia). Larch forest with shrubs (alders, pines, birches) dominated during the deposition of the lowermost sediments suggesting its Early Weichselian [Marine Isotope Stage (MIS) 5] age. Pollen- and chironomid-based climate reconstructions suggest July temperatures (T-July) slightly lower than modern. Gradually increasing amounts of herb pollen and cold stenotherm chironomid head capsules reflect cooler and drier environments, probably during the termination of MIS 5. T-July dropped to 8 degrees C. Mostly treeless vegetation is reconstructed during MIS 3. Tundra and steppe communities dominated during MIS 2. Shrubs became common after similar to 14.5 ka BP but herb-dominated habitats remained until the onset of the Holocene. Larch forests with shrub alder and dwarf birch dominated after the Holocene onset, ca. 11.7 ka BP. Decreasing amounts of shrub pollen during the Lateglacial are assigned to the Older Dryas and Younger Dryas with T-July similar to 7.5 degrees C. T-July increased up to 13 degrees C. Shrub stone pine was present after similar to 7.5 ka BP. The vegetation has been similar to modern since ca. 5.8 ka BP. Chironomid diversity and concentration in the sediments increased towards the present day, indicating the development of richer hydrobiological communities in response to the Holocene thermal maximum.