Boreal forests in permafrost regions make up around one-third of the global forest cover and are an essential component of regional and global climate patterns. Further, climatic change can trigger extensive ecosystem shifts such as the partial disappearance of near-surface permafrost or changes to the vegetation structure and composition. Therefore, our aim is to understand how the interactions between the vegetation, permafrost and the atmosphere stabilize the forests and the underlying permafrost. Existing model setups are often static or are not able to capture important processes such as the vertical structure or the leaf physiological properties. There is a need for a physically based model with a robust radiative transfer scheme through the canopy. A one-dimensional land surface model (CryoGrid) is adapted for the application in vegetated areas by coupling a multilayer canopy model (CLM-ml v0; Community Land Model) and is used to reproduce the energy transfer and thermal regime at a study site (63.18946^∘ N, 118.19596^∘ E) in mixed boreal forest in eastern Siberia. An extensive comparison between measured and modeled energy balance variables reveals a satisfactory model performance justifying its application to investigate the thermal regime; surface energy balance; and the vertical exchange of radiation, heat and water in this complex ecosystem. We find that the forests exert a strong control on the thermal state of permafrost through changing the radiation balance and snow cover phenology. The forest cover alters the surface energy balance by inhibiting over 90 % of the solar radiation and suppressing turbulent heat fluxes. Additionally, our simulations reveal a surplus in longwave radiation trapped below the canopy, similar to a greenhouse, which leads to a magnitude in storage heat flux comparable to that simulated at the grassland site. Further, the end of season snow cover is 3 times greater at the forest site, and the onset of the snow-melting processes are delayed.

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 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.

Vegetation is responding to climate change, which is especially prominent in the Arctic. Vegetation change is manifest in different ways and varies regionally, depending on the characteristics of the investigated area. Although vegetation in some Arctic areas has been thoroughly investigated, central Chukotka (NE Siberia) with its highly diverse vegetation, mountainous landscape and deciduous needle-leaf treeline remains poorly explored, despite showing strong greening in remote-sensing products. Here we quantify recent vegetation compositional changes in central Chukotka over 15 years between 2000/2001/2002 and 2016/2017. We numerically related field-derived information on foliage projective cover (percentage cover) of different plant taxa from 52 vegetation plots to remote-sensing derived (Landsat) spectral indices (Normalised Difference Vegetation Index (NDVI), Normalised Difference Water Index (NDWI) and Normalised Difference Snow Index (NDSI)) using constrained ordination. Clustering of ordination scores resulted in four land-cover classes: (1) larch closed-canopy forest, (2) forest tundra and shrub tundra, (3) graminoid tundra and (4) prostrate herb tundra and barren areas. We produced land-cover maps for early (2000, 2001 or 2002) and recent (2016 or 2017) time-slices for four focus regions along the tundra-taiga vegetation gradient. Transition from graminoid tundra to forest tundra and shrub tundra is interpreted as shrubification and amounts to 20% area increase in the tundra-taiga zone and 40% area increase in the northern taiga. Major contributors of shrubification are alder, dwarf birch and some species of the heather family. Land-cover change from the forest tundra and shrub tundra class to the larch closed-canopy forest class is interpreted as tree infilling and is notable in the northern taiga. We find almost no land-cover changes in the present treeless tundra.

Rapidly changing climate in the Northern Hemisphere and associated socio-economic impacts require reliable understanding of lake systems as important freshwater resources and sensitive sentinels of environmental change. To better understand time-series data in lake sediment cores, it is necessary to gain information on within-lake spatial variabilities of environmental indicator data. Therefore, we retrieved a set of 38 samples from the sediment surface along spatial habitat gradients in the boreal, deep, and yet pristine Lake Bolshoe Toko in southern Yakutia, Russia. Our methods comprise laboratory analyses of the sediments for multiple proxy parameters, including diatom and chironomid taxonomy, oxygen isotopes from diatom silica, grain-size distributions, elemental compositions (XRF), organic carbon content, and mineralogy (XRD). We analysed the lake water for cations, anions, and isotopes. Our results show that the diatom assemblages are strongly influenced by water depth and dominated by planktonic species, i.e. Pliocaenicus bolshetokoensis. Species richness and diversity are higher in the northern part of the lake basin, associated with the availability of benthic, i.e. periphytic, niches in shallower waters. δ¹⁸O_diatom values are higher in the deeper south-western part of the lake, probably related to water temperature differences. The highest amount of the chironomid taxa underrepresented in the training set used for palaeoclimate inference was found close to the Utuk River and at southern littoral and profundal sites. Abiotic sediment components are not symmetrically distributed in the lake basin, but vary along restricted areas of differential environmental forcing. Grain size and organic matter are mainly controlled by both river input and water depth. Mineral (XRD) data distributions are influenced by the methamorphic lithology of the Stanovoy mountain range, while elements (XRF) are intermingled due to catchment and diagenetic differences. We conclude that the lake represents a valuable archive for multiproxy environmental reconstruction based on diatoms (including oxygen isotopes), chironomids, and sediment–geochemical parameters. Our analyses suggest multiple coring locations preferably at intermediate depth in the northern basin and the deep part in the central basin, to account for representative bioindicator distributions and higher temporal resolution, respectively.

The variability of the 12S gene fragment of the mtDNA for taxa belonging to subgenus Daphnia (Daphnia) O.F. Müller, 1776 (Crustacea: Cladocera) in NE Russia is studied, and their phylogenetic analysis performed. We identified (based both on morphological and molecular data) nine species belonging to four species complexes, namely: (A) D. longispina s.l.: (1) D. longispina O.F. Müller, 1776; (2) D. dentifera Forbes, 1893; (3) D. galeata Sars, 1864; (4) D. umbra Taylor, Hebert et Colbourne, 1996; (B) D. cristata s.l.: (5) D. cristata Sars, 1862; (6) D. longiremis Sars, 1862; (C) D. curvirostris s.l.: (7) D. curvirostris Eylmann, 1887; (D) D. pulex s.l.: (8) D. pulex Leydig, 1860; (9) D. middendorffiana Fischer, 1851. Rare arcto-mountainous taxon D. umbra was found in the mountains of the Sakha (Yakutia) Republic for the first time. Species diversity in NE Asia is relatively low, and the most revealed taxa are trans-Beringian. We also performed a phylogeographic analysis of D. dentifera and D. pulex s.l., the two most common species in NE Russia. Our new data allow us to assume that the daphniids of NE Asia have undergone various evolutionary scenarios during the Pleistocene period: survival is within some local refugia, and re-colonization from these areas and from North America through the Beringian land bridge, etc. We agree with previous authors who revealed that the patterns in the studied species groups are relatively recent (of Late Pleistocene or even Holocene age), although the main phylogenetic daphniid lineages (mainly congruent with the biological species) are very old. Our results provide convincing evidence for the hypothesis that NE Russia is a very important source of modern haplotypic diversity for the cladocerans.