Terrestrial CDOM in Lakes of Yamal Peninsula: Connection to Lake and Lake Catchment Properties

Mitochondrial genomes of Pleistocene megafauna retrieved from recent sediment layers of two Siberian lakes

Ancient environmental DNA (aeDNA) from lake sediments has yielded remarkable insights for the reconstruction of past ecosystems, including suggestions of late survival of extinct species. However, translocation and lateral inflow of DNA in sediments can potentially distort the stratigraphic signal of the DNA. Using three different approaches on two short lake sediment cores of the Yamal peninsula, West Siberia, with ages spanning only the past hundreds of years, we detect DNA and identified mitochondrial genomes of multiple mammoth and woolly rhinoceros individuals-both species that have been extinct for thousands of years on the mainland. The occurrence of clearly identifiable aeDNA of extinct Pleistocene megafauna (e.g. >400 K reads in one core) throughout these two short subsurface cores, along with specificities of sedimentology and dating, confirm that processes acting on regional scales, such as extensive permafrost thawing, can influence the aeDNA record and should be accounted for in aeDNA paleoecology.

Analysis of bio-optical active constituents for lentic ecosystem through spectral-spatial and in-vitro observation

The neural network algorithm approach was adopted in Kolavai Lake to retrieve the inherent optical properties (IOP) of active constituents. The retrieval of IOP by absorption and the scattering of optically active constituents (OAC) through employing Sentinel-2 MSI reflectance and field measured the salinity and temperature. The result illustrates the relationship between the IOP and measured OAC's concentrations and its sensitivity towards spectral wavelength. It shows that the phytoplankton absorption ap is highly related with chlorophyll-a concentration and has an R2 value of 0.808. Furthermore, at the total absorption of water has high correlation with chl-a which indicates the significant dominance in the lentic water. Also, the pigment constituents are showing an R2 value of 0.754. The total backscattering of water (btot) is strongly related to the total suspended matter with R value > 0.73. The spatial distribution of OAC in Kolavai Lake helps monitor the lake water quality. This approach is well-performed in estimating the inherent optical properties of optically active constituents that gives insight for assessing the relationship between IOP and water quality. The research has proved to be a good potential for monitoring lentic water quality through Sentinel-2 MSI.

Optical properties of dissolved organic matter in Japanese rivers and contributions to photoformation of reactive oxygen species

The optical properties of dissolved organic matter (DOM) from five rivers (Kokubu, Kurose, Ohta, Yamato, and Yodo) in Japan were investigated and contributions of DOM to photoformation of three reactive oxygen species (ROS) (hydroxyl radicals (OH), nitric oxide radicals (NO), and singlet oxygen (¹O₂)) were assessed. The lowest and highest mean dissolved organic carbon concentrations were for the Ohta River (0.95 (mg C) L^-1) and Yamato River (2.85 (mg C) L^-1), respectively, and the concentrations correlated with some optical parameters. Absorption ratios (e.g., the E₂:E₃ and A₂₈₀/A₃₅₀ ratios) and the spectral slope S_275-295 indicated that DOM from the Yodo and Kokubu rivers had the lowest and highest molecular weights, respectively. PARAFAC models and DOM excitation-emission matrices were used to assess the sources and fates of DOM in the rivers. The PARAFAC model indicated that the main types of fluorescent DOM in the rivers were terrestrial humic-like (TH-L) and tryptophan-like (TP-L) substances. The Kokubu River contained other compounds such as fluorescent whitening agents, autochthonous humic-like substances, and extracellular polymeric substances. Statistically significant relationships between the dissolved organic carbon and TH-L, TP-L, and extracellular polymeric substance concentrations suggested that TH-L, TP-L, and extracellular polymeric substances are important contributors to total DOM in the rivers. TH-L and TP-L substances strongly contribute to ROS photoformation, but TH-L substances play roles in both ROS generation and scavenging. Comprehensive models for estimating the photoformation rates of different ROS (in M s^-1) were established by integrating the contributions of the relevant major and minor sources. Examples are R_OH (10^-12) = 21.0 [NO₂^-]__μM + 0.460 [TH-L]__QSU + 10.9, R_NO (10^-12) = 67.9 [NO₂^-]__μM + 35.2 [a₃₀₀]__m^-1 - 2.51 [TH-L]__QSU - 0.765 [TP-L]__QSU - 8.14, and R_1O2 (10^-9) = 3.81 [a₃₀₀]__m^-1 - 0.101 [TP-L]__QSU + 11.1.

Research into Cryolithozone Spatial Pattern Changes Based on the Mathematical Morphology of Landscapes

Lacustrine thermokarst is receiving great interest as a landscape-forming process. Despite this, research dealing with the quantitative analysis of the changes in the morphological patterns of thermokarst plains under ongoing climate change is lacking. This study aims to analyze changes in the morphological patterns of cryolithozone landscapes based on models provided by the mathematical morphology of landscapes. Our research involves eight key sites within lacustrine thermokarst plains and nine key sites within thermokarst plains with fluvial erosion. These sites differ in geomorphological, geocryological, and physiographical terms, and are situated in different regions such as Yamal, Taimyr, Kolyma lowland, river Lena delta, Baffin’s Land, and Alaska. Archival Corona images (date 1) and high-resolution satellite imagery from June to August 2008–2014 (date 2) were used to obtain the model’s morphometric data. According to quantitative analysis of the models, the morphological pattern of the lacustrine thermokarst plains did not undergo significant changes during the observation period, while 20% of the key sites within the thermokarst plains with fluvial erosion underwent essential changes in lake area distributions. This difference may come from the higher reactivity of the fluvial erosion process on climate change than that of the thermokarst.

Trends in Satellite Earth Observation for Permafrost Related Analyses—A Review

Climate change and associated Arctic amplification cause a degradation of permafrost which in turn has major implications for the environment. The potential turnover of frozen ground from a carbon sink to a carbon source, eroding coastlines, landslides, amplified surface deformation and endangerment of human infrastructure are some of the consequences connected with thawing permafrost. Satellite remote sensing is hereby a powerful tool to identify and monitor these features and processes on a spatially explicit, cheap, operational, long-term basis and up to circum-Arctic scale. By filtering after a selection of relevant keywords, a total of 325 articles from 30 international journals published during the last two decades were analyzed based on study location, spatio-temporal resolution of applied remote sensing data, platform, sensor combination and studied environmental focus for a comprehensive overview of past achievements, current efforts, together with future challenges and opportunities. The temporal development of publication frequency, utilized platforms/sensors and the addressed environmental topic is thereby highlighted. The total number of publications more than doubled since 2015. Distinct geographical study hot spots were revealed, while at the same time large portions of the continuous permafrost zone are still only sparsely covered by satellite remote sensing investigations. Moreover, studies related to Arctic greenhouse gas emissions in the context of permafrost degradation appear heavily underrepresented. New tools (e.g., Google Earth Engine (GEE)), methodologies (e.g., deep learning or data fusion etc.) and satellite data (e.g., the Methane Remote Sensing LiDAR Mission (Merlin) and the Sentinel-fleet) will thereby enable future studies to further investigate the distribution of permafrost, its thermal state and its implications on the environment such as thermokarst features and greenhouse gas emission rates on increasingly larger spatial and temporal scales.

Research Trends in the Use of Remote Sensing for Inland Water Quality Science: Moving Towards Multidisciplinary Applications

Remote sensing approaches to measuring inland water quality date back nearly 50 years to the beginning of the satellite era. Over this time span, hundreds of peer-reviewed publications have demonstrated promising remote sensing models to estimate biological, chemical, and physical properties of inland waterbodies. Until recently, most of these publications focused largely on algorithm development as opposed to implementation of those algorithms to address specific science questions. This slow evolution contrasts with terrestrial and oceanic remote sensing, where methods development in the 1970s led to publications focused on understanding spatially expansive, complex processes as early as the mid-1980s. This review explores the progression of inland water quality remote sensing from methodological development to scientific applications. We use bibliometric analysis to assess overall patterns in the field and subsequently examine 236 key papers to identify trends in research focus and scale. The results highlight an initial 30 year period where the majority of publications focused on model development and validation followed by a spike in publications, beginning in the early-2000s, applying remote sensing models to analyze spatiotemporal trends, drivers, and impacts of changing water quality on ecosystems and human populations. Recent and emerging resources, including improved data availability and enhanced processing platforms, are enabling researchers to address challenging science questions and model spatiotemporally explicit patterns in water quality. Examination of the literature shows that the past 10–15 years has brought about a focal shift within the field, where researchers are using improved computing resources, datasets, and operational remote sensing algorithms to better understand complex inland water systems. Future satellite missions promise to continue these improvements by providing observational continuity with spatial/spectral resolutions ideal for inland waters.