TY - JOUR A1 - Dvornikov, Yury A1 - Leibman, Marina A1 - Heim, Birgit A1 - Bartsch, Annett A1 - Herzschuh, Ulrike A1 - Skorospekhova, Tatiana A1 - Fedorova, Irina A1 - Khomutov, Artem A1 - Widhalm, Barbara A1 - Gubarkov, Anatoly A1 - Rößler, Sebastian T1 - Terrestrial CDOM in lakes of Yamal Peninsula BT - Connection to lake and lake catchment properties JF - Remote Sensing N2 - In this study, we analyze interactions in lake and lake catchment systems of a continuous permafrost area. We assessed colored dissolved organic matter (CDOM) absorption at 440 nm (a(440)(CDOM)) and absorption slope (S300-500) in lakes using field sampling and optical remote sensing data for an area of 350 km(2) in Central Yamal, Siberia. Applying a CDOM algorithm (ratio of green and red band reflectance) for two high spatial resolution multispectral GeoEye-1 and Worldview-2 satellite images, we were able to extrapolate the a()(CDOM) data from 18 lakes sampled in the field to 356 lakes in the study area (model R-2 = 0.79). Values of a(440)(CDOM) in 356 lakes varied from 0.48 to 8.35 m(-1) with a median of 1.43 m(-1). This a()(CDOM) dataset was used to relate lake CDOM to 17 lake and lake catchment parameters derived from optical and radar remote sensing data and from digital elevation model analysis in order to establish the parameters controlling CDOM in lakes on the Yamal Peninsula. Regression tree model and boosted regression tree analysis showed that the activity of cryogenic processes (thermocirques) in the lake shores and lake water level were the two most important controls, explaining 48.4% and 28.4% of lake CDOM, respectively (R-2 = 0.61). Activation of thermocirques led to a large input of terrestrial organic matter and sediments from catchments and thawed permafrost to lakes (n = 15, mean a(440)(CDOM) = 5.3 m(-1)). Large lakes on the floodplain with a connection to Mordy-Yakha River received more CDOM (n = 7, mean a(440)(CDOM) = 3.8 m(-1)) compared to lakes located on higher terraces. KW - CDOM KW - lakes KW - lake catchments KW - permafrost KW - Yamal KW - remote sensing data Y1 - 2018 U6 - https://doi.org/10.3390/rs10020167 SN - 2072-4292 VL - 10 IS - 2 PB - MDPI CY - Basel ER - TY - JOUR A1 - Marcisz, Katarzyna A1 - Jassey, Vincent E. J. A1 - Kosakyan, Anush A1 - Krashevska, Valentyna A1 - Lahr, Daniel J. G. A1 - Lara, Enrique A1 - Lamentowicz, Lukasz A1 - Lamentowicz, Mariusz A1 - Macumber, Andrew A1 - Mazei, Yuri A1 - Mitchell, Edward A. D. A1 - Nasser, Nawaf A. A1 - Patterson, R. Timothy A1 - Roe, Helen M. A1 - Singer, David A1 - Tsyganov, Andrey N. A1 - Fournier, Bertrand T1 - Testate amoeba functional traits and their use in paleoecology JF - Frontiers in Ecology and Evolution N2 - This review provides a synthesis of current knowledge on the morphological and functional traits of testate amoebae, a polyphyletic group of protists commonly used as proxies of past hydrological changes in paleoecological investigations from peatland, lake sediment and soil archives. A trait-based approach to understanding testate amoebae ecology and paleoecology has gained in popularity in recent years, with research showing that morphological characteristics provide complementary information to the commonly used environmental inferences based on testate amoeba (morpho-)species data. We provide a broad overview of testate amoeba morphological and functional traits and trait-environment relationships in the context of ecology, evolution, genetics, biogeography, and paleoecology. As examples we report upon previous ecological and paleoecological studies that used trait-based approaches, and describe key testate amoebae traits that can be used to improve the interpretation of environmental studies. We also highlight knowledge gaps and speculate on potential future directions for the application of trait-based approaches in testate amoeba research. KW - protists KW - functional traits KW - morphological traits KW - ecology KW - peatlands KW - lakes KW - soils KW - trait-based approaches Y1 - 2020 U6 - https://doi.org/10.3389/fevo.2020.575966 SN - 2296-701X VL - 8 PB - Frontiers Media CY - Lausanne ER - TY - JOUR A1 - Subetto, D. A. A1 - Nazarova, Larisa B. A1 - Pestryakova, Luidmila Agafyevna A1 - Syrykh, Liudmila A1 - Andronikov, A. V. A1 - Biskaborn, Boris A1 - Diekmann, Bernhard A1 - Kuznetsov, D. D. A1 - Sapelko, T. V. A1 - Grekov, I. M. T1 - Paleolimnological studies in Russian northern Eurasia BT - a review JF - Contemporary Problems of Ecology N2 - 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. KW - paleolimnology KW - lakes KW - bottom sediments KW - northern Eurasia KW - Russian Arctic KW - databases Y1 - 2017 U6 - https://doi.org/10.1134/S1995425517040102 SN - 1995-4255 SN - 1995-4263 VL - 10 SP - 327 EP - 335 PB - Pleiades Publ. CY - New York ER - TY - JOUR A1 - Muster, Sina A1 - Riley, William J. A1 - Roth, Kurt A1 - Langer, Moritz A1 - Aleina, Fabio Cresto A1 - Koven, Charles D. A1 - Lange, Stephan A1 - Bartsch, Annett A1 - Grosse, Guido A1 - Wilson, Cathy J. A1 - Jones, Benjamin M. A1 - Boike, Julia T1 - Size distributions of arctic waterbodies reveal consistent relations in their statistical moments in space and time JF - Frontiers in Earth Science N2 - Arctic lowlands are characterized by large numbers of small waterbodies, which are known to affect surface energy budgets and the global carbon cycle. Statistical analysis of their size distributions has been hindered by the shortage of observations at sufficiently high spatial resolutions. This situation has now changed with the high-resolution (<5 m) circum-Arctic Permafrost Region Pond and Lake (PeRL) database recently becoming available. We have used this database to make the first consistent, high-resolution estimation of Arctic waterbody size distributions, with surface areas ranging from 0.0001 km(2) (100 m(2)) to 1 km(2). We found that the size distributions varied greatly across the thirty study regions investigated and that there was no single universal size distribution function (including power-law distribution functions) appropriate across all of the study regions. We did, however, find close relationships between the statistical moments (mean, variance, and skewness) of the waterbody size distributions from different study regions. Specifically, we found that the spatial variance increased linearly with mean waterbody size (R-2 = 0.97, p < 2.2e-16) and that the skewness decreased approximately hyperbolically. We have demonstrated that these relationships (1) hold across the 30 Arctic study regions covering a variety of (bio)climatic and permafrost zones, (2) hold over time in two of these study regions for which multi-decadal satellite imagery is available, and (3) can be reproduced by simulating rising water levels in a high-resolution digital elevation model. The consistent spatial and temporal relationships between the statistical moments of the waterbody size distributions underscore the dominance of topographic controls in lowland permafrost areas. These results provide motivation for further analyses of the factors involved in waterbody development and spatial distribution and for investigations into the possibility of using statistical moments to predict future hydrologic dynamics in the Arctic. KW - permafrost KW - hydrology KW - waterbodies KW - size distribution KW - thermokarst KW - statistical moments KW - ponds KW - lakes Y1 - 2019 U6 - https://doi.org/10.3389/feart.2019.00005 SN - 2296-6463 VL - 7 PB - Frontiers Research Foundation CY - Lausanne ER - TY - JOUR A1 - Korzeniowska, Karolina A1 - Korup, Oliver T1 - Object-Based Detection of Lakes Prone to Seasonal Ice Cover on the Tibetan Plateau JF - Remote sensing KW - Tibetan Plateau KW - lakes KW - LANDSAT KW - SRTM KW - MNDWI KW - OBIA KW - change detection Y1 - 2017 U6 - https://doi.org/10.3390/rs9040339 SN - 2072-4292 VL - 9 PB - MDPI CY - Basel ER - TY - JOUR A1 - Tang, Kam W. A1 - Gladyshev, Michail I. A1 - Dubovskaya, Olga P. A1 - Kirillin, Georgiy A1 - Grossart, Hans-Peter T1 - Zooplankton carcasses and non-predatory mortality in freshwater and inland sea environments JF - Journal of plankton research N2 - Zooplankton carcasses are ubiquitous in marine and freshwater systems, implicating the importance of non-predatory mortality, but both are often overlooked in ecological studies compared with predatory mortality. The development of several microscopic methods allows the distinction between live and dead zooplankton in field samples, and the reported percentages of dead zooplankton average 11.6 (minimum) to 59.8 (maximum) in marine environments, and 7.4 (minimum) to 47.6 (maximum) in fresh and inland waters. Common causes of non-predatory mortality among zooplankton include senescence, temperature change, physical and chemical stresses, parasitism and food-related factors. Carcasses resulting from non-predatory mortality may undergo decomposition leading to an increase in microbial production and a shift in microbial composition in the water column. Alternatively, sinking carcasses may contribute significantly to vertical carbon flux especially outside the phytoplankton growth seasons, and become a food source for the benthos. Global climate change is already altering freshwater ecosystems on multiple levels, and likely will have significant positive or negative effects on zooplankton non-predatory mortality. Better spatial and temporal studies of zooplankton carcasses and non-predatory mortality rates will improve our understanding of this important but under-appreciated topic. KW - carbon flux KW - inland waters KW - lakes KW - live KW - dead sorting KW - non-predatory mortality KW - zooplankton carcasses Y1 - 2014 U6 - https://doi.org/10.1093/plankt/fbu014 SN - 0142-7873 SN - 1464-3774 VL - 36 IS - 3 SP - 597 EP - 612 PB - Oxford Univ. Press CY - Oxford ER - TY - JOUR A1 - Sommer, Ulrich A1 - Adrian, Rita A1 - Domis, Lisette Nicole de Senerpont A1 - Elser, James J. A1 - Gaedke, Ursula A1 - Ibelings, Bas A1 - Jeppesen, Erik A1 - Lurling, Miquel A1 - Molinero, Juan Carlos A1 - Mooij, Wolf M. A1 - van Donk, Ellen A1 - Winder, Monika ED - Futuyma, DJ T1 - Beyond the Plankton Ecology Group (PEG) Model mechanisms driving plankton succession JF - Annual review of ecology, evolution, and systematics JF - Annual Review of Ecology Evolution and Systematics N2 - The seasonal succession of plankton is an annually repeated process of community assembly during which all major external factors and internal interactions shaping communities can be studied. A quarter of a century ago, the state of this understanding was described by the verbal plankton ecology group (PEG) model. It emphasized the role of physical factors, grazing and nutrient limitation for phytoplankton, and the role of food limitation and fish predation for zooplankton. Although originally targeted at lake ecosystems, it was also adopted by marine plankton ecologists. Since then, a suite of ecological interactions previously underestimated in importance have become research foci: overwintering of key organisms, the microbial food web, parasitism, and food quality as a limiting factor and an extended role of higher order predators. A review of the impact of these novel interactions on plankton seasonal succession reveals limited effects on gross seasonal biomass patterns, but strong effects on species replacements. KW - lakes KW - oceans KW - seasonal patterns KW - pelagic zone KW - light KW - overwintering KW - grazing KW - parasitism KW - food quality Y1 - 2012 SN - 978-0-8243-1443-9 U6 - https://doi.org/10.1146/annurev-ecolsys-110411-160251 SN - 1543-592X VL - 43 IS - 2-4 SP - 429 EP - 448 PB - Annual Reviews CY - Palo Alto ER -