Труды сотрудников ИЛ им. В.Н. Сукачева СО РАН

/ E. A. Kukavskaya [et al.] // Can. J. For. Res.-Rev. Can. Rech. For. - 2013. - Vol. 43, Is. 5. - P493-506, DOI 10.1139/cjfr-2012-0367. - Cited References: 65. - The authors gratefully acknowledge financial support from the National Aeronautics and Space Administration (NASA), Land Cover Land Use Change (LCLUC), Terrestrial Ecology (TE), and Inter-DiSciplinary (IDS) projects, all of which fall under the Northern Eurasia Earth Science Partnership Initiative (NEESPI) domain; the Institute of International Education, Fulbright Scholar Program; the Russian Foundation for Basic Research (Grant No. 12-04-31258; FGP "Scientific and scientific-pedagogical staff of innovative Russia"; and the Russian Academy of Sciences. . - 14. - ISSN 0045-5067РУБ Forestry

Аннотация: Boreal forests constitute the world's largest terrestrial carbon pools. The main natural disturbance in these forests is wildfire, which modifies the carbon budget and atmosphere, directly and indirectly. Wildfire emissions in Russia contribute substantially to the global carbon cycle and have potentially important feedbacks to changing climate. Published estimates of carbon emissions from fires in Russian boreal forests vary greatly depending on the methods and data sets used. We examined various fire and vegetation products used to estimate wildfire emissions for Siberia. Large (up to fivefold) differences in annual and monthly area burned estimates for Siberia were found among four satellite-based fire data sets. Official Russian data were typically less than 10% of satellite estimates. Differences in the estimated proportion of annual burned area within each ecosystem were as much as 40% among five land-cover products. As a result, fuel consumption estimates would be expected to vary widely (3%-98%) depending on the specific vegetation mapping product used and as a function of weather conditions. Verification and validation of burned area and land-cover data sets along with the development of fuel maps and combustion models are essential for accurate Siberian wildfire emission estimates, which are central to balancing the carbon budget and assessing feedbacks to climate change.

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Держатели документа:
[Kukavskaya, Elena A.
Ponomarev, Evgeni I.
Ivanova, Galina A.] VN Sukachev Inst Forest SB RAS, Krasnoyarsk 660036, Russia
[Soja, Amber J.] Natl Inst Aerosp, Hampton, VA 23666 USA
[Soja, Amber J.] NASA, Langley Res Ctr, Hampton, VA 23681 USA
[Petkov, Alexander P.
Conard, Susan G.] US Forest Serv, USDA, Rocky Mt Res Stn, Missoula, MT 59808 USA
[Conard, Susan G.] George Mason Univ, Fairfax, VA 22030 USA

Доп.точки доступа:
Kukavskaya, E.A.; Кукавская, Елена Александровна; Soja, A.J.; Petkov, A.P.; Ponomarev, E.I.; Пономарев, Евгений Иванович; Ivanova, G.A.; Иванова, Галина Александровна; Conard, S.G.

[Text] / D. . Pflugmacher [et al.] // Remote Sens. Environ. - 2011. - Vol. 115, Is. 12. - P3539-3553, DOI 10.1016/j.rse.2011.08.016. - Cited References: 65. - The research was supported by the Land Cover/Land-Use Change Program of the National Aeronautics and Space Administration (grant numbers NNGO6GF54G and NNX09AK88G) and in part by the Asia-Pacific Network for Global Change Research and the Alexander von Humboldt Foundation. We like to thank Dr. Curtis Woodcock for his advice in the early planning of this study, and Gretchen Bracher for preparing graphs. We are also thankful for the comments of two anonymous reviewers that helped to improve this manuscript. . - 15. - ISSN 0034-4257РУБ Environmental Sciences + Remote Sensing + Imaging Science & Photographic Technology

Аннотация: Information on land cover at global and continental scales is critical for addressing a range of ecological, socioeconomic and policy questions. Global land cover maps have evolved rapidly in the last decade, but efforts to evaluate map uncertainties have been limited, especially in remote areas like Northern Eurasia. Northern Eurasia comprises a particularly diverse region covering a wide range of climate zones and ecosystems: from arctic deserts, tundra, boreal forest, and wetlands, to semi-arid steppes and the deserts of Central Asia. In this study, we assessed four of the most recent global land cover datasets: GLC-2000, GLOBCOVER, and the MODIS Collection 4 and Collection 5 Land Cover Product using cross-comparison analyses and Landsat-based reference maps distributed throughout the region. A consistent comparison of these maps was challenging because of disparities in class definitions, thematic detail, and spatial resolution. We found that the choice of sampling unit significantly influenced accuracy estimates, which indicates that comparisons of reported global map accuracies might be misleading. To minimize classification ambiguities, we devised a generalized legend based on dominant life form types (LFT) (tree, shrub, and herbaceous vegetation, barren land and water). LFT served as a necessary common denominator in the analyzed map legends, but significantly decreased the thematic detail. We found significant differences in the spatial representation of LFT's between global maps with high spatial agreement (above 0.8) concentrated in the forest belt of Northern Eurasia and low agreement (below 0.5) concentrated in the northern taiga-tundra zone, and the southern dry lands. Total pixel-level agreement between global maps and six test sites was moderate to fair (overall agreement: 0.67-0.74, Kappa: 0.41-0.52) and increased by 0.09-0.45 when only homogenous land cover types were analyzed. Low map accuracies at our tundra test site confirmed regional disagreements and difficulties of current global maps in accurately mapping shrub and herbaceous vegetation types at the biome borders of Northern Eurasia. In comparison, tree dominated vegetation classes in the forest belt of the region were accurately mapped, but were slightly overestimated (10%-20%), in all maps. Low agreement of global maps in the northern and southern vegetation transition zones of Northern Eurasia is likely to have important implications for global change research, as those areas are vulnerable to both climate and socio-economic changes. (C) 2011 Elsevier Inc. All rights reserved.

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Держатели документа:
[Pflugmacher, Dirk
Krankina, Olga N.
Kennedy, Robert E.
Nelson, Peder] Oregon State Univ, Dept Forest Ecosyst & Soc, Corvallis, OR 97331 USA
[Cohen, Warren B.] US Forest Serv, USDA, Pacific NW Res Stn, Forestry Sci Lab, Corvallis, OR 97331 USA
[Friedl, Mark A.
Sulla-Menashe, Damien] Boston Univ, Dept Geog & Environm, Boston, MA 02215 USA
[Loboda, Tatiana V.] Univ Maryland, Dept Geog, College Pk, MD 20742 USA
[Kuemmerle, Tobias] Potsdam Inst Climate Impact Res PIK, D-14412 Potsdam, Germany
[Dyukarev, Egor] Inst Monitoring Climat & Ecol Syst, Tomsk 634021, Russia
[Elsakov, Vladimir] Russian Acad Sci, Komi Sci Ctr, Inst Biol, Syktyvkar 167610, Russia
[Kharuk, Viacheslav I.] VN Sukachev Inst Forest, Krasnoyarsk, Russia

Доп.точки доступа:
Pflugmacher, D...; Krankina, O.N.; Cohen, W.B.; Friedl, M.A.; Sulla-Menashe, D...; Kennedy, R.E.; Nelson, P...; Loboda, T.V.; Kuemmerle, T...; Dyukarev, E...; Elsakov, V...; Kharuk, V.I.

[Text] / J. . Heintzenberg [et al.] // Atmos. Chem. Phys. - 2011. - Vol. 11, Is. 16. - P8703-8719, DOI 10.5194/acp-11-8703-2011. - Cited References: 65. - The Max Planck Society in collaboration with the V. N. Sukachev Institute of Forest established the ZOTTO facility after many years of preparatory fieldwork, planning and massive investments. We thank E.-D. Schulze and M. Heimann (MPI Biogeochemistry), A. A. Onuchin, and S. Verchovetz, (V. N. Sukachev Institute of Forest) for their contributions to the establishment and management of ZOTTO, and Y. Kisilyakhov, A. Tsukanov (V. N. Sukachev Institute of Forest), M. Welling and N. Jurgens (MPI Chemistry), as well as S. Leinert and T. Muller (IfT) for technical support. The ZOTTO project is funded by the Max Plank Society through the International Science and Technology Center (ISTC) partner project #2757p within the framework of the proposal 'Observing and Understanding Biogeochemical Responses to Rapid Climate Changes in Eurasia', and by the German Research Council (DFG). We thank S. Schmidt and K. Kubler (MPI Jena) for their continuous logistic assistance during the experiment. We acknowledge U. Riebel (Technical University of Cottbus, Chair for Particle Technology) for generously sharing his technology of the corona discharge based aerosol neutralizer. We thank A. Wiedensohler (IfT Leipzig) for the fruitful discussions about environmental aerosol charging. . - 17. - ISSN 1680-7316РУБ Meteorology & Atmospheric Sciences

Аннотация: This paper analyses aerosol particle number size distributions, particulate absorption at 570 nm wavelength and carbon monoxide (CO) measured between September 2006 and January 2010 at heights of 50 and 300 m at the Zotino Tall Tower Facility (ZOTTO) in Siberia (60.8 degrees N; 89.35 degrees E). Average number, surface and volume concentrations are broadly comparable to former studies covering shorter observation periods. Fits of multiple lognormal distributions yielded three maxima in probability distribution of geometric mean diameters in the Aitken and accumulation size range and a possible secondary maximum in the nucleation size range below 25 nm. The seasonal cycle of particulate absorption shows maximum concentrations in high winter (December) and minimum concentrations in mid-summer (July). The 90th percentile, however, indicates a secondary maximum in July/August that is likely related to forest fires. The strongly combustion derived CO shows a single winter maximum and a late summer minimum, albeit with a considerably smaller seasonal swing than the particle data due to its longer atmospheric lifetime. Total volume and even more so total number show a more complex seasonal variation with maxima in winter, spring, and summer. A cluster analysis of back trajectories and vertical profiles of the pseudo-potential temperature yielded ten clusters with three levels of particle number concentration: Low concentrations in Arctic air masses (400-500 cm(-3)), mid-level concentrations for zonally advected air masses from westerly directions between 55 degrees and 65 degrees N (600-800 cm(-3)), and high concentrations for air masses advected from the belt of industrial and population centers in Siberia and Kazakhstan (1200 cm(-3)). The observational data is representative for large parts of the troposphere over Siberia and might be particularly useful for the validation of global aerosol transport models.

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Держатели документа:
[Heintzenberg, J.
Birmili, W.
Otto, R.] Leibniz Inst Tropospher Res, D-04318 Leipzig, Germany
[Andreae, M. O.
Mayer, J. -C.
Chi, X.] Max Planck Inst Chem, D-55020 Mainz, Germany
[Panov, A.] Russian Acad Sci, Siberian Branch, VN Sukachev Inst Forest, Krasnoyarsk 660036, Russia

Доп.точки доступа:
Heintzenberg, J...; Birmili, W...; Otto, R...; Andreae, M.O.; Mayer, J.C.; Chi, X...; Panov, A...

[Text] / L. B. Marchesini [et al.] // Biogeosciences. - 2007. - Vol. 4, Is. 4. - P581-595. - Cited References: 64 . - 15. - ISSN 1726-4170РУБ Ecology + Geosciences, Multidisciplinary

Аннотация: Steppe ecosystems represent an interesting case in which the assessment of carbon balance may be performed through a cross validation of the eddy covariance measurements against ecological inventory estimates of carbon exchanges (Ehman et al., 2002; Curtis et al., 2002). Indeed, the widespread presence of ideal conditions for the applicability of the eddy covariance technique, as vast and homogeneous grass vegetation cover over flat terrains (Baldocchi, 2003), make steppes a suitable ground to ensure a constrain to flux estimates with independent methodological approaches. We report about the analysis of the carbon cycle of a true steppe ecosystem in southern Siberia during the growing season of 2004 in the framework of the TCOS-Siberia project activities performed by continuous monitoring of CO2 fluxes at ecosystem scale by the eddy covariance method, fortnightly samplings of phytomass, and ingrowth cores extractions for NPP assessment, and weekly measurements of heterotrophic component of soil CO2 effluxes obtained by an experiment of root exclusion. The carbon balance of the monitored natural steppe was, according to micrometeorological measurements, a sink of carbon of 151.7 +/- 36.9 g Cm-2, cumulated during the growing season from May to September. This result was in agreement with the independent estimate through ecological inventory which yielded a sink of 150.1 g Cm-2 although this method was characterized by a large uncertainty (+/- 130%) considering the 95% confidence interval of the estimate. Uncertainties in belowground process estimates account for a large part of the error. Thus, in particular efforts to better quantify the dynamics of root biomass (growth and turnover) have to be undertaken in order to reduce the uncertainties in the assessment of NPP. This assessment should be preferably based on the application of multiple methods, each one characterized by its own merits and flaws.

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Держатели документа:
Univ Tuscia, Dept Forest Resources & Environm, I-01100 Viterbo, Italy
Max Planck Inst Biogeochem, D-07745 Jena, Germany
RAS, SB, Sukachev Inst Forest, Krasnoyarsk 660036, Russia

Доп.точки доступа:
Marchesini, L.B.; Papale, D...; Reichstein, M...; Vuichard, N...; Tchebakova, N...; Valentini, R...

[Text] / G. . Sun [et al.] // Remote Sens. Environ. - 2003. - Vol. 88, Is. 4. - P401-411, DOI 10.1016/j.rse.2003.09.001. - Cited References: 28 . - 11. - ISSN 0034-4257РУБ Environmental Sciences + Remote Sensing + Imaging Science & Photographic Technology

Аннотация: Spaceborne Interferometric SAR (InSAR) technology used in the Shuttle Radar Topography Mission (SRTM) and spaceborne lidar such as Shuttle Laser Altimeter-02 (SLA-02) are two promising technologies for providing global scale digital elevation models (DEMs). Each type of these systems has limitations that affect the accuracy or extent of coverage. These systems are complementary in developing DEM data. In this study, surface height measured independently by SRTM and SLA-02 was cross-validated. SLA data was first verified by field observations, and examinations of individual lidar waveforms. The geolocation accuracy of the SLA height data sets was examined by checking the correlation between the SLA surface height with SRTM height at 90 in resolution, while shifting the SLA ground track within its specified horizontal errors. It was found that the heights from the two instruments were highly correlated along the SLA ground track, and shifting the positions did not improve the correlation significantly. Absolute surface heights from SRTM and SLA referenced to the same horizontal and vertical datum (World Geodetic System (WGS) 84 Ellipsoid) were compared. The effects of forest cover and surface slope on the height difference were also examined. After removing the forest effect on SRTM height, the mean height difference with SLA-02 was near zero. It can be further inferred from the standard deviation of the height differences that the absolute accuracy of SRTM height at low vegetation area is better than the SRTM mission specifications (16 in). The SRTM height bias caused by forest cover needs to be further examined using future spaceborne lidar (e.g. GLAS) data. (C) 2003 Elsevier Inc. All rights reserved.

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Держатели документа:
Univ Maryland, Dept Geog, College Pk, MD 20742 USA
NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA
VN Sukachev Inst Forest, Krasnoyarsk, Russia
Sci Syst & Applicat Inc, Lanham, MD 20706 USA

Доп.точки доступа:
Sun, G...; Ranson, K.J.; Khairuk, V.I.; Kovacs, K...

[Text] / G. E. Rehfeldt [et al.] // Glob. Change Biol. - 2002. - Vol. 8, Is. 9. - P912-929, DOI 10.1046/j.1365-2486.2002.00516.x. - Cited References: 49 . - 18. - ISSN 1354-1013РУБ Biodiversity Conservation + Ecology + Environmental Sciences

Аннотация: Five population-specific response functions were developed from quadratic models for 110 populations of Pinus sylvestris growing at 47 planting sites in Eurasia and North America. The functions predict 13 year height from climate: degree-days > 5 degreesC; mean annual temperature; degree-days < 0 degreesC; summer-winter temperature differential; and a moisture index, the ratio of degree-days > 5 degreesC to mean annual precipitation. Validation of the response functions with two sets of independent data produced for all functions statistically significant simple correlations with coefficients as high as 0.81 between actual and predicted heights. The response functions described the widely different growth potentials typical of natural populations and demonstrated that these growth potentials have different climatic optima. Populations nonetheless tend to inhabit climates colder than their optima, with the disparity between the optimal and inhabited climates becoming greater as the climate becomes more severe. When driven by a global warming scenario of the Hadley Center, the functions described short-term physiologic and long-term evolutionary effects that were geographically complex. The short-term effects should be negative in the warmest climates but strongly positive in the coldest. Long-term effects eventually should ameliorate the negative short-term impacts, enhance the positive, and in time, substantially increase productivity throughout most of the contemporary pine forests of Eurasia. Realizing the long-term gains will require redistribution of genotypes across the landscape, a process that should take up to 13 generations and therefore many years.

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Держатели документа:
USDA, Forest Serv, Rocky Mt Res Stn, Moscow, ID 83843 USA
Russian Acad Sci, Sikachev Inst Forest, Siberian Branch, Krasnoyarsk 660036, Russia

Доп.точки доступа:
Rehfeldt, G.E.; Tchebakova, N.M.; Parfenova, Y.I.; Wykoff, W.R.; Kuzmina, N.A.; Milyutin, L.I.

/ D. Schepaschenko [et al.] // Journal of Land Use Science. - 2011. - Vol. 6, Is. 4. - P245-259, DOI 10.1080/1747423X.2010.511681 . - ISSN 1747-423X
Аннотация: Despite being recognized as a key baseline dataset for many applications, especially those relating to biogeochemical cycles, land cover products in their current form are limiting. Typically they lack the thematic detail necessary for driving the models that depend upon them. This study has demonstrated the ability to produce a highly detailed (both spatially and thematically) land cover/land use dataset over Russia - by combining existing datasets into a hybrid information system. The resulting dataset contains detailed subclasses of land cover and attributes necessary for biogeochemical modeling. In lieu of suitable validation data, a confidence map was produced creating six classes of confidence in the agreement between the various remote sensing and statistical datasets. In specific regions, a significant difference between the remote sensing products and the official statistics was observed. For example, in the northwest of Russia the statistics appear to be underreporting the amount of forest land which has likely been increasing in recent decades because of encroachment of forests on abandoned marginal agricultural land. В© 2011 Copyright Taylor and Francis Group, LLC.

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Держатели документа:
IIASA, Laxenburg, Austria
Moscow State Forest University, Moscow, Russian Federation
Institute of Forest, Siberian Branch, Russian Academy of Science, Krasnoyarsk, Russian Federation

Доп.точки доступа:
Schepaschenko, D.; McCallum, I.; Shvidenko, A.; Fritz, S.; Kraxner, F.; Obersteiner, M.

/ P. P. Bobrov [et al.] // Progress in Electromagnetics Research Symposium. - 2011. - Progress in Electromagnetics Research Symposium, PIERS 2011 Suzhou (12 September 2011 through 16 September 2011, Suzhou) Conference code: 88875. - P121-124 . -
Аннотация: The results of in situ measurements of radiobrightness temperature at the frequency 1.4 GHz and soil moisture in the surface layer of the test area located in Western Siberia near Omsk are given. It is shown that at low soil moisture these data are in satisfactory agreement with the SMOS data of the levels 1c and 2. In addition, correlation analysis between the topsoil moisture provided with the SMOS, on the one hand, and the forest fire danger index derived on the basis of rainfalls and temperatures recorded by the net of weather stations located in the area of the city of Krasnoyarsk Eastern Siberia was carried out. This effort was made to investigate if the SMOS data can be used to estimate forest fire danger over the areas where no weather stations are availabe. The correlation analysis showed good relationships between SMOS soil moisture data and fire danger indices.

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Держатели документа:
Omsk State Pedagogical University, Omsk, Russian Federation
Kirensky Institute of Physics, SB RAS, Krasnoyarsk, Russian Federation
Sukachev Institute of Forest, SB RAS, Krasnoyarsk, Russian Federation
Reshetnev Aerospace State University, Krasnoyarsk, Russian Federation

Доп.точки доступа:
Bobrov, P.P.; Kondratieva, O.V.; Mironov, V.L.; Shvetsov, E.; Sukhinin, A.I.; Yashchenko, A.S.

/ G. Sun [et al.] // International Geoscience and Remote Sensing Symposium (IGARSS). - 2004. - Vol. 2: 2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004 (20 September 2004 through 24 September 2004, Anchorage, AK) Conference code: 64488. - P722-724 . -
Аннотация: The transition zone between the Arctic Tundra and boreal forest is sensitive to both climate change and human activities. Monitoring the dynamics of this tundra-forest ecotone is important for understanding of the causes and consequences of changes in land cover. MSS image in 1973 and ETM+ image in 2002 were used to identify the changes at the taiga-tundra transition zones in Ary Mas, Siberia. Linear spectral unmixing was used to map taiga abundances across the boundary. An ETM+ image acquired in 2001 was also processed using linear spectral unmixing, and the results showed the consistence between 2001 and 2002. In order to make the results from MSS and ETM+ comparable, ETM+ images were re-sampled to the pixel size of MSS image, and only three bands (2,3,4) similar to MSS bands 7,5,4 were used. Comparing results from these two datasets shows the changes that occurred in the transition zone during this period. The most significant change is the thickening of taiga forests near the transition zone. The change of tree cover along the taiga-tundra transition zone may be attributed to climate change; however, the validation of these changes needs to be further studied.

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Держатели документа:
Department of Geography, University of Maryland, College Park, United States
NASA's Goddard Space Flight Center, Code 923, Greenbelt, MD, United States
V.N. Sukachev Institute of Forest, Academgorodok, Krasnoyarsk, Russian Federation
Sci. Systems and Applications, Inc., Lanliam, MD, United States

Доп.точки доступа:
Sun, G.; Ranson, K.J.; Kharuk, V.I.; Kovacs, K.

/ V. G. Sukhovol'skii, R. G. Khlebopros, T. R. Iskhakov // Doklady. Biochemistry and biophysics. - 2003. - Vol. 390. - P171-173 . - ISSN 1607-6729

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Держатели документа:
Sukachev Institute of Forest, Siberian Division, Russian Academy of Sciences, Akademgorodok, Krasnoyarsk, 660036 Russia.

Доп.точки доступа:
Sukhovol'skii, V.G.; Khlebopros, R.G.; Iskhakov, T.R.

/ C. Huttich [et al.] // Forests. - 2014. - Vol. 5, Is. 7. - P1753-1776, DOI 10.3390/f5071753 . - ISSN 1999-4907
Аннотация: Growing stock volume is an important biophysical parameter describing the state and dynamics of the Boreal zone. Validation of growing stock volume (GSV) maps based on satellite remote sensing is challenging due to the lack of consistent ground reference data. The monitoring and assessment of the remote Russian forest resources of Siberia can only be done by integrating remote sensing techniques and interdisciplinary collaboration. In this paper, we assess the information content of GSV estimates in Central Siberian forests obtained at 25 m from ALOS-PALSAR and 1 km from ENVISAT-ASAR backscatter data. The estimates have been cross-compared with respect to forest inventory data showing 34% relative RMSE for the ASAR-based GSV retrievals and 39.4% for the PALSAR-based estimates of GSV. Fragmentation analyses using a MODIS-based land cover dataset revealed an increase of retrieval error with increasing fragmentation of the landscape. Cross-comparisons of multiple SAR-based GSV estimates helped to detect inconsistencies in the forest inventory data and can support an update of outdated forest inventory stands. © 2014 by the authors.licensee MDPI, Basel, Switzerland.

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Держатели документа:
Department for Earth Observation, Friedrich-Schiller-University Jena, Lobdergraben 32, 07743 Jena, Germany
Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Sciences, Krasnoyarsk, 660036, Russian Federation
Space Research Institute of the Russian Academy of Sciences, Moscow 117997, Russian Federation
International Institute for Advanced System Analyses, Laxenburg 2361, Austria

Доп.точки доступа:
Huttich, C.; Korets, M.; Bartalev, S.; Zharko, V.; Schepaschenko, D.; Shvidenko, A.; Schmullius, C.

[Text] / Y. L. Liu [et al.] // Clim. Change. - 2014. - Vol. 126, Is. 03.04.2014. - P413-427, DOI 10.1007/s10584-014-1234-9. - Cited References: 53. - This research is supported by the NASA Land Use and Land Cover Change program (NASA-NNX09AI26G, NN-H-04-Z-YS-005-N, and NNX09AM55G), the Department of Energy (DE-FG02-08ER64599), the National Science Foundation (NSF-1028291 and NSF- 0919331), the NSF Carbon and Water in the Earth Program (NSF-0630319), and the Dynamics of Coupled Natural and Human Systems (CNH) Program of the NSF (#1313761). We also acknowledge the Global Runoff Data Centre for provision of the gauge station data. Runoff data in Peterson et al. (2002) were obtained from the R-ArcticNet database. A special acknowledgment is made here to Prof. Eric Wood for his generous provision of the ET datasets of Vinukollu et al. (2011), and to Dr. Brigitte Mueller and Dr. Martin Hirsci for the provision of the LandFlux-EVAL dataset of Mueller et al. (2013). Diego Miralles acknowledges the support by the European Space Agency WACMOS-ET project (4000106711/12/I-NB). . - ISSN 0165-0009. - ISSN 1573-1480РУБ Environmental Sciences + Meteorology & Atmospheric Sciences

Аннотация: Northern Eurasian ecosystems play an important role in the global climate system. Northern Eurasia (NE) has experienced dramatic climate changes during the last half of the 20th century and to present. To date, how evapotranspiration (ET) and water availability (P-ET, P: precipitation) had changed in response to the climatic change in this region has not been well evaluated. This study uses an improved version of the Terrestrial Ecosystem Model (TEM) that explicitly considers ET from uplands, wetlands, water bodies and snow cover to examine temporal and spatial variations in ET, water availability and river discharge in NE for the period 1948-2009. The average ET over NE increased during the study period at a rate of 0.13 mm year(-1) year(-1). Over this time, water availability augmented in the western part of the region, but decreased in the eastern part. The consideration of snow sublimation substantially improved the ET estimates and highlighted the importance of snow in the hydrometeorology of NE. We also find that the modified TEM estimates of water availability in NE watersheds are in good agreement with corresponding measurements of historical river discharge before 1970. However, a systematic underestimation of river discharge occurs after 1970 indicates that other water sources or dynamics not considered by the model (e.g., melting glaciers, permafrost thawing and fires) may also be important for the hydrology of the region.

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Держатели документа:
[Liu, Yaling
Zhuang, Qianlai
He, Yujie] Purdue Univ, Dept Earth Atmospher & Planetary Sci, W Lafayette, IN 47907 USA
[Zhuang, Qianlai] Purdue Univ, Dept Agron, W Lafayette, IN 47907 USA
[Pan, Zhihua] China Agr Univ, Coll Resources & Environm Sci, Beijing 100094, Peoples R China
[Miralles, Diego] Univ Ghent, Lab Hydrol & Water Management, B-9000 Ghent, Belgium
[Miralles, Diego] Univ Bristol, Sch Geog Sci, Bristol, Avon, England
[Tchebakova, Nadja] Russian Acad Sci, Siberian Branch, VN Sukachev Inst Forest, Krasnoyarsk, Russia
[Kicklighter, David
Melillo, Jerry] Marine Biol Lab, Ctr Ecosyst, Woods Hole, MA 02543 USA
[Chen, Jiquan] Michigan State Univ, CGCEO Geog, E Lansing, MI 48824 USA
[Sirin, Andrey] Acad Sci, Lab Peatland Forestry & Ameliorat, Inst Forest Sci, Uspenskoye, Moscow Oblast, Russia
[Zhou, Guangsheng] Chinese Acad Sci, Inst Bot, Beijing, Peoples R China
ИЛ СО РАН

Доп.точки доступа:
Liu, Y.L.; Zhuang, Q.L.; Pan, Z.H.; Miralles, D...; Tchebakova, N...; Kicklighter, D...; Chen, J.Q.; Sirin, A...; He, Y.J.; Zhou, G.S.; Melillo, J...; NASA Land Use and Land Cover Change program [NASA-NNX09AI26G, NN-H-04-Z-YS-005-N, NNX09AM55G]; Department of Energy [DE-FG02-08ER64599]; National Science Foundation [NSF-1028291, NSF- 0919331]; NSF Carbon and Water in the Earth Program [NSF-0630319]; Dynamics of Coupled Natural and Human Systems (CNH) Program of the NSF [1313761]; European Space Agency WACMOS-ET project [4000106711/12/I-NB]

/ J. K. Shuman [et al.] // Can. J. For. Res. - 2015. - Vol. 45, Is. 2. - P175-184, DOI 10.1139/cjfr-2014-0138 . - ISSN 0045-5067
Аннотация: Vegetation models are essential tools for projecting large-scale land-cover response to changing climate, which is expected to alter the distribution of biomes and individual species. A large-scale bioclimatic envelope model (RuBCliM) and an individual species based gap model (UVAFME) are used to simulate the Russian forests under current and future climate for two greenhouse gas emissions scenarios. Results for current conditions are compared between models and assessed against two independent maps of Russian forest biomes and dominant tree species. Comparisons measured with kappa statistics indicate good agreement between the models (kappa values from 0.76 to 0.69), as well as between the model results and two observationbased maps for both species presence and absence (kappa values from 0.70 to 0.43). Agreement between these multiple types of data on forest distribution provides confidence in the projected forest response to changing climate. For future conditions, both models indicate a shift in the dominant biomes from conifers to deciduous leaved species. These projections have implications for feedbacks between the energy budget, carbon cycle, and land cover in the boreal system. The distinct biome and species changes emphasize the need for continued investigation of this landmass that has the size necessary to influence regional and global climate.

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Держатели документа:
University of Virginia, Department of Environmental Sciences, Clark Hall, 291 McCormick Road, P.O. Box 400123Charlottesville, VA, United States
Sukachev Institute of Forest, Russian Academy of SciencesKrasnoyarsk, Russian Federation
National Institute of Aerospace, NASA Langley Research Center, Climate Science and Radiation and Aerosols Branches, 21 Langley Blvd. MS 420Hampton, VA, United States
Center for Problems of Ecology and Productivity of Forests, Russian Academy of SciencesMoscow, Russian Federation
University of Virginia, Alliance for Computational Science and EngineeringCharlottesville, VA, United States

Доп.точки доступа:
Shuman, J.K.; Tchebakova, N.M.; Parfenova, E.I.; Soja, A.J.; Shugart, H.H.; Ershov, D.; Holcomb, K.

[Text] / J. K. Shuman [et al.] // Can. J. For. Res. - 2015. - Vol. 45, Is. 2. - P175-184, DOI 10.1139/cjfr-2014-0138. - Cited References:53. - This work was funded by NASA grants to H.H. Shugart (Terrestrial Ecology10-CARBON10-0068) and A.J. Soja (Inter-Disciplinary Science09-IDS09-116). We thank the anonymous reviewers and V.A. Seamster forhelpful comments on earlier versions of this manuscript, and RobertSmith for figure preparation. We also appreciate the software packagesthat made this work possible: IDRISI developed in 1987 by R.J. Eastmanat Clark University in Worcester, Massachusetts, USA, and ESRI 2008(ESRI ArcGIS version 9.3, ESRI, Redlands, California, USA). . - ISSN 0045-5067. - ISSN 1208-6037РУБ Forestry

Аннотация: Vegetation models are essential tools for projecting large-scale land-cover response to changing climate, which is expected to alter the distribution of biomes and individual species. A large-scale bioclimatic envelope model (RuBCliM) and an individual species based gap model (UVAFME) are used to simulate the Russian forests under current and future climate for two greenhouse gas emissions scenarios. Results for current conditions are compared between models and assessed against two independent maps of Russian forest biomes and dominant tree species. Comparisons measured with kappa statistics indicate good agreement between the models (kappa values from 0.76 to 0.69), as well as between the model results and two observation-based maps for both species presence and absence (kappa values from 0.70 to 0.43). Agreement between these multiple types of data on forest distribution provides confidence in the projected forest response to changing climate. For future conditions, both models indicate a shift in the dominant biomes from conifers to deciduous leaved species. These projections have implications for feedbacks between the energy budget, carbon cycle, and land cover in the boreal system. The distinct biome and species changes emphasize the need for continued investigation of this landmass that has the size necessary to influence regional and global climate.

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Держатели документа:
Univ Virginia, Dept Environm Sci, Charlottesville, VA 22904 USA.
Russian Acad Sci, Sukachev Inst Forest, Krasnoyarsk, Russia.
NASA, Natl Inst Aerosp, Langley Res Ctr, Climate Sci Branch, Hampton, VA 23681 USA.
NASA, Natl Inst Aerosp, Langley Res Ctr, Radiat & Aerosols Branch, Hampton, VA 23681 USA.
Russian Acad Sci, Ctr Problems Ecol & Prod Forests, Moscow, Russia.
Univ Virginia, Alliance Computat Sci & Engn, Charlottesville, VA 22904 USA.
ИЛ СО РАН

Доп.точки доступа:
Shuman, Jacquelyn K.; Tchebakova, Nadezhda M.; Parfenova, Elena I.; Soja, Amber J.; Shugart, Herman H.; Ershov, Dmitry; Holcomb, Katherine; NASA [10-CARBON10-0068, 09-IDS09-116]

/ F. Kraxner [et al.] // For. Policy Econ. - 2017. - Vol. 83. - P10-18, DOI 10.1016/j.forpol.2017.04.014 . - ISSN 1389-9341
Аннотация: There are currently no spatially explicit, openly accessible data available on forest certification below national level, so understanding the drivers of certification in the past, examining the scope for further certification and using this information for development of future sustainable forest management strategies is challenging. Hence, this paper presents a methodology for the development of a global map of certified forest areas at 1 km resolution in order to satisfy this information need. Validation of the map with certified areas in Russia showed reasonable results, but the lack of openly accessible data requires broadening the strategy for improving the global certification map in the future. Thus, the second aim of the paper is to present an online tool for visualization and interactive improvement of the global forest certification product through collaborative mapping, aiming at a range of stakeholders including third-party certifiers, green NGOs, forestry organizations, decision-makers, scientists and local experts. Such an approach can help to make more accurate information on forest certification available, promote the sharing of data and encourage more transparent and sustainable forest management, i.e. both producers and users can benefit from this online tool. © 2017

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Держатели документа:
Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, Laxenburg, Austria
Mercator Research Institute on Global Commons and Climate Change (MCC), Torgauer Str. 12–15, Berlin, Germany
Norwegian University of Life Sciences (NMBU), School of Economics and Business, Box 5003, Aas, Norway
Austrian Research and Training Centre for Forests, Natural Hazards and Landscape, Seckendorff-Gudent-Weg 8, Vienna, Austria
Shinshu University, Cooperative Research Center, 4-17-1 Wakasato, Nagano, Japan
Sukachev Institute of Forest, Russian Academy of Sciences, Siberian Branch, Akademgorodok 50/28, Krasnoyarsk, Russian Federation
Mytischi filial of Bauman Moscow State Technical University, Institutskaya, 1, Mytishchi, Russian Federation

Доп.точки доступа:
Kraxner, F.; Schepaschenko, D.; Fuss, S.; Lunnan, A.; Kindermann, G.; Aoki, K.; Durauer, M.; Shvidenko, A.; See, L.

/ J. Emile-Geay [et al.] // Sci. Data. - 2017. - Vol. 4. - Ст. 170088, DOI 10.1038/sdata.2017.88. - Cited References:314. - PAGES, a core project of Future Earth, is supported by the U.S. and Swiss National Science Foundations. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Some of this work was conducted as part of the North America 2k Working Group supported by the John Wesley Powell Center for Analysis and Synthesis, funded by the U.S. Geological Survey. B. Bauer, W. Gross, and E. Gille (NOAA National Centers for Environmental Information) are gratefully acknowledged for helping assemble the data citations and creating the NCEI versions of the PAGES 2k data records. We thank all the investigators whose commitment to data sharing enables the open science ethos embodied by this project. . - ISSN 2052-4463РУБ Multidisciplinary Sciences

Аннотация: Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850-2014. Global temperature composites show a remarkable degree of coherence between high-and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python. (TABLE) Since the pioneering work of D'Arrigo and Jacoby1-3, as well as Mann et al. 4,5, temperature reconstructions of the Common Era have become a key component of climate assessments6-9. Such reconstructions depend strongly on the composition of the underlying network of climate proxies10, and it is therefore critical for the climate community to have access to a community-vetted, quality-controlled database of temperature-sensitive records stored in a self-describing format. The Past Global Changes (PAGES) 2k consortium, a self-organized, international group of experts, recently assembled such a database, and used it to reconstruct surface temperature over continental-scale regions11 (hereafter, ` PAGES2k-2013'). This data descriptor presents version 2.0.0 of the PAGES2k proxy temperature database (Data Citation 1). It augments the PAGES2k-2013 collection of terrestrial records with marine records assembled by the Ocean2k working group at centennial12 and annual13 time scales. In addition to these previously published data compilations, this version includes substantially more records, extensive new metadata, and validation. Furthermore, the selection criteria for records included in this version are applied more uniformly and transparently across regions, resulting in a more cohesive data product. This data descriptor describes the contents of the database, the criteria for inclusion, and quantifies the relation of each record with instrumental temperature. In addition, the paleotemperature time series are summarized as composites to highlight the most salient decadal-to centennial-scale behaviour of the dataset and check mutual consistency between paleoclimate archives. We provide extensive Matlab code to probe the database-processing, filtering and aggregating it in various ways to investigate temperature variability over the Common Era. The unique approach to data stewardship and code-sharing employed here is designed to enable an unprecedented scale of investigation of the temperature history of the Common Era, by the scientific community and citizen-scientists alike.

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Держатели документа:
Univ Southern Calif, Dept Earth Sci, Los Angeles, CA 90089 USA.
Univ Southern Calif, Ctr Appl Math Sci, Los Angeles, CA 90089 USA.
Univ Arizona, Sch Earth Sci & Environm Sustainabil, Flagstaff, AZ 86001 USA.
PAGES Int Project Off, CH-3012 Bern, Switzerland.
Mathworks Inc, Natick, MA 01760 USA.
Univ Arizona, Sch Geog & Dev, Tucson, AZ 85721 USA.
Univ Arizona, Tree Ring Res Lab, Tucson, AZ 85721 USA.
Australian Natl Univ, Res Sch Earth Sci, Canberra, ACT 2601, Australia.
Australian Natl Univ, ARC Ctr Excellence Climate Syst Sci, Canberra, ACT 2601, Australia.
US Geol Survey, 345 Middlefield Rd, Menlo Pk, CA 94025 USA.
Australian Antarctic Div, Kingston, Tas 7050, Australia.
Univ Tasmania, Antarctic Climate & Ecosyst CRC, Hobart, Tas 7050, Australia.
Univ Maryland, Dept Geol, College Pk, MD 20742 USA.
Univ Maryland, Earth Syst Sci Interdisciplinary Ctr, College Pk, MD 20742 USA.
Univ Melbourne, Sch Earth Sci, Melbourne, Vic 3010, Australia.
Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.
Spanish Council Sci Res, Inst Environm Assessment & Water Res, Dept Environm Chem, Barcelona 08034, Spain.
Univ Cambridge, Dept Earth Sci, Cambridge CB2 3EQ, England.
Univ Wollongong, Sch Earth & Environm Sci, Wollongong, NSW 2522, Australia.
Univ Bern, Oeschger Ctr Climate Change Res, CH-3012 Bern, Switzerland.
Univ Bern, Inst Geog, CH-3012 Bern, Switzerland.
US Geol Survey, Northern Rocky Mt Sci Ctr, Bozeman, MT 59715 USA.
Ca Foscari Univ Venice, Dept Environm Sci Informat & Stat, I-30170 Venice, Italy.
Univ Texas Austin, Inst Geophys, Jackson Sch Geosci, Austin, TX 78758 USA.
Univ Bergen, Dept Earth Sci, N-5020 Bergen, Norway.
Univ Bergen, Bjerknes Ctr Climate Res, N-5020 Bergen, Norway.
Chinese Acad Sci, Inst Geol & Geophys, Beijing 100029, Peoples R China.
Norwegian Polar Res Inst, Fram Ctr, N-9296 Tromso, Norway.
Univ Tromso, Fac Sci & Technol, Dept Math & Stat, N-9037 Tromso, Norway.
Univ Melbourne, Sch Geog, Melbourne, Vic 3010, Australia.
Univ Melbourne, Sch Earth Sci, Melbourne, Vic 3010, Australia.
Univ Melbourne, Australian Res Council Ctr Excellence Climate Sys, Melbourne, Vic 3010, Australia.
Univ Nacl Cuyo, IANIGLA CONICET, M5502IRA, Mendoza, Argentina.
Univ Nacl Cuyo, Fac Ciencias Exactas & Nat, M5502IRA, Mendoza, Argentina.
Res Inst Humanity & Nat, Kyoto 6038047, Japan.
Univ Tasmania, Inst Marine & Antarctic Studies, Hobart, Tas 7001, Australia.
Univ Washington, Quaternary Res Ctr, Seattle, WA 98195 USA.
Univ Washington, Dept Earth & Space Sci, Seattle, WA 98195 USA.
Univ Arizona, Dept Geosci, Tucson, AZ 85721 USA.
Univ Adelaide, Dept Earth Sci, Adelaide, SA 5005, Australia.
Univ Adelaide, Sprigg Geobiol Ctr, Adelaide, SA 5005, Australia.
Univ Melbourne, Sch Ecosyst & Forest Sci, Melbourne, Vic 3121, Australia.
Victoria Univ Wellington, Joint Antarctic Res Inst, Wellington 6012, New Zealand.
GNS Sci, Wellington 6012, New Zealand.
Swiss Fed Res Inst WSL, CH-8903 Birmensdorf, Switzerland.
Univ Montpellier, Inst Sci Evolut Montpellier, CNRS, UMR 5554, F-34095 Montpellier 5, France.
Natl Taiwan Ocean Univ, Inst Appl Geosci, Keelung 20224, Taiwan.
Lamont Doherty Earth Observ, Palisades, NY 10964 USA.
Louisiana State Univ, Dept Geog & Anthropol, Baton Rouge, LA 70803 USA.
Univ Maine, Climate Change Inst, Orono, ME 04469 USA.
Arctic & Antarctic Res Inst, St Petersburg 199397, Russia.
St Petersburg State Univ, Inst Earth Sci, St Petersburg 199178, Russia.
Northumbria Univ, Dept Geog, Newcastle Upon Tyne NE1 8ST, Tyne & Wear, England.
Lund Univ, Dept Geol, SE-22362 Lund, Sweden.
Inst Natl Rech Sci, Ctr Eau Terre Environm, Quebec City, PQ G1K 9A9, Canada.
ENEA, CR Casaccia, I-00123 Rome, Italy.
Nepal Acad Sci & Technol, Fac Sci, Lalitpur, Nepal.
Tribhuvan Univ, Cent Dept Environm Sci, Kathmandu, Nepal.
Univ Ottawa, Dept Geog Environm & Geomat, Ottawa, ON K1N 6N5, Canada.
Catholic Univ Louvain, Earth & Life Inst, B-1348 Louvain La Neuve, Belgium.
RAS, Urals Branch, Inst Geophys, Ekaterinburg, Russia.
Hirosaki Univ, Grad Sch Sci & Technol, Aomori 0368561, Japan.
Univ Gothenburg, Dept Earth Sci, Fac Sci, SE-40530 Gothenburg, Sweden.
Xiamen Univ, State Key Lab Marine Environm Sci, Xiamen 361102, Peoples R China.
Xiamen Univ, Dept Geol Oceanog, Xiamen 361102, Peoples R China.
Natl Inst Polar Res, Tachikawa, Tokyo 1908518, Japan.
Dept Polar Sci, Tachikawa, Tokyo 1908518, Japan.
Japan Agcy Marine Earth Sci & Technol, Inst Biogeosci, Yokosuka, Kanagawa 2370061, Japan.
Univ Maryland, Chesapeake Biol Lab, Ctr Environm Sci, Solomons, MD 20688 USA.
Aix Marseille Univ, CNRS, IRD, CEREGE UM34, F-13545 Aix En Provence 4, France.
Univ Gothenburg, Dept Earth Sci, SE-40530 Gothenburg, Sweden.
Natl Inst Water & Atmospher Res, Auckland Cent 1010, New Zealand.
Russian Acad Sci, Inst Geog, Moscow 119017, Russia.
Univ Autonoma Barcelona, Inst Environm Sci & Technol, Bellaterra 08193, Spain.
Univ Autonoma Barcelona, Dept Geog, Bellaterra 08193, Spain.
Natl Inst Polar Res, Res Org Informat & Syst, Midoricho 10-3, Tachikawa, Tokyo, Japan.
British Antarctic Survey, Cambridge CB3 0ET, England.
Eberhard Karls Univ Tubingen, D-72074 Tubingen, Germany.
Univ Brighton, Sch Environm & Technol, Brighton BN2 4GJ, E Sussex, England.
Univ Witwatersrand, Sch Geog Archaeol & Environm Studies, ZA-2050 Johannesburg, South Africa.
Helmholtz Ctr Polar & Marine Res, Alfred Wegener Inst, D-27515 Bremerhaven, Germany.
Helmholtz Ctr Polar & Marine Res, Alfred Wegener Inst, D-14473 Potsdam, Germany.
Lab Sci Climat & Environm, F-91191 Gif Sur Yvette, France.
Russian Acad Sci, Siberian Branch, Sukachev Inst Forest, Krasnoyarsk 660036, Russia.
Univ Toronto, Dept Geog, Mississauga, ON L5L 1C6, Canada.
SUNY Buffalo, Dept Geol, Buffalo, NY 14260 USA.
Univ Washington, Joint Inst Study Atmosphere & Ocean, Seattle, WA 98105 USA.
Australian Nucl Sci & Technol Org, Lucas Heights, NSW 2234, Australia.
Univ Bern, Oeschger Ctr Climate Change Res, CH-3012 Bern, Switzerland.
Univ Bern, Inst Geog, CH-3012 Bern, Switzerland.
Aarhus Univ, Ctr Climate Studies, DK-8000 Aarhus C, Denmark.
Aarhus Univ, Arctic Res Ctr, Dept Geosci, DK-8000 Aarhus C, Denmark.
Univ Florence, Dept Chem, Sesto Fiorentino, Italy.
Sorbonne Univ, LOCEAN, Case 100, F-75005 Paris, France.
Paul Scherrer Inst, Lab Environm Chem, CH-5232 Villigen, Psi Ost, Switzerland.
Appl Aquat Res Ltd, Calgary, AB T3C 0K3, Canada.
Univ Minnesota, Dept Geog Environm & Soc, Minneapolis, MN 55455 USA.
Univ Regina, Prairie Adaptat Res Collaborat, Regina, SK S4S 0A2, Canada.
Concordia Univ, Geog Planning & Environm, Montreal, PQ H3G 1M8, Canada.
Natl Ctr Antarctic & Ocean Res, Vasco Da Gama 403804, Goa, India.
Univ New South Wales, Sch Biol Earth & Environm Sci, Climate Change Res Ctr, Sydney, NSW 2052, Australia.
Univ Ryukyus, Dept Chem Biol & Marine Sci, Fac Sci, Nishihara, Okinawa 9030213, Japan.
NOAA, Natl Ctr Environm Informat, World Data Serv Paleoclimatol, Boulder, CO 80305 USA.
Univ Colorado, Inst Arctic & Alpine Res, Boulder, CO 80309 USA.
Lehigh Univ, Dept Earth & Environm Sci, Bethlehem, PA 18015 USA.
Dept Environm & Agr, Bentley, WA 6845, Australia.
Australian Inst Marine Sci, Townsville, Qld 4810, Australia.
Free Univ Berlin, Inst Geol Sci, Paleontol, D-12249 Berlin, Germany.

Доп.точки доступа:
Emile-Geay, Julien; McKay, Nicholas P.; Kaufman, Darrell S.; von Gunten, Lucien; Wang, Jianghao; Anchukaitis, Kevin J.; Abram, Nerilie J.; Addison, Jason A.; Curran, Mark A. J.; Evans, Michael N.; Henley, Benjamin J.; Hao, Zhixin; Martrat, Belen; McGregor, Helen V.; Neukom, Raphael; Pederson, Gregory T.; Stenni, Barbara; Thirumalai, Kaustubh; Werner, Johannes P.; Xu, Chenxi; Divine, Dmitry V.; Dixon, Bronwyn C.; Gergis, Joelle; Mundo, Ignacio A.; Nakatsuka, Takeshi; Phipps, Steven J.; Routson, Cody C.; Steig, Eric J.; Tierney, Jessica E.; Tyler, Jonathan J.; Allen, Kathryn J.; Bertler, Nancy A. N.; Bjorklund, Jesper; Chase, Brian M.; Chen, Min-Te; Cook, E.d.; de Jong, Rixt; DeLong, Kristine L.; Dixon, Daniel A.; Ekaykin, Alexey A.; Ersek, Vasile; Filipsson, Helena L.; Francus, Pierre; Freund, Mandy B.; Frezzotti, Massimo; Gaire, Narayan P.; Gajewski, Konrad; Ge, Quansheng; Goosse, Hugues; Gornostaeva, Anastasia; Grosjean, Martin; Horiuchi, Kazuho; Hormes, Anne; Husum, Katrine; Isaksson, Elisabeth; Kandasamy, Selvaraj; Kawamura, Kenji; Kilbourne, K. Halimeda; Koc, Nalan; Leduc, Guillaume; Linderholm, Hans W.; Lorrey, Andrew M.; Mikhalenko, Vladimir; Mortyn, P. Graham; Motoyama, Hideaki; Moy, Andrew D.; Mulvaney, Robert; Munz, Philipp M.; Nash, David J.; Oerter, Hans; Opel, Thomas; Orsi, Anais J.; Ovchinnikov, Dmitriy V.; Porter, Trevor J.; Roop, Heidi A.; Saenger, Casey; Sano, Masaki; Sauchyn, David; Saunders, Krystyna M.; Seidenkrantz, Marit-Solveig; Severi, Mirko; Shao, Xuemei; Sicre, Marie-Alexandrine; Sigl, Michael; Sinclair, Kate; St George, Scott; St Jacques, Jeannine-Marie; Thamban, Meloth; Thapa, Udya Kuwar; Thomas, Elizabeth R.; Turney, Chris; Uemura, Ryu; Viau, Andre E.; Vladimirova, Diana O.; Wahl, Eugene R.; White, James W. C.; Yu, Zicheng; Zinke, Jens; U.S. and Swiss National Science Foundations; John Wesley Powell Center for Analysis and Synthesis - U.S. Geological Survey

[Текст] : статья / Дмитрий Геннадьевич Щепащенко [и др.] // Сибирский лесной журнал. - 2017. - № : 4. - С. 3-11, DOI 10.15372/SJFS20170401 . - ISSN 2311-1410
   Перевод заглавия: Forest biomass observation: current state and prospective

УДК

528.8

581.5

Аннотация: Дан обзор современных методов, инструментов и перспектив мониторинга лесной фитомассы в глобальном масштабе. Рассмотрены преимущества и недостатки различных дистанционных методов космического базирования, включая оптические, радарные (C-, L-, P-диапазонов) и лазерные, а также соответствующие им инструменты, находящиеся на орбите (MODIS, Proba-V, Landsat, Sentinel-1, Sentinel-2, ALOS PALSAR, Envisat ASAR) или готовящиеся к запуску (BIOMASS, GEDI, NISAR, SAOCOM-CS). Подчеркнута роль наземных методов в разработке моделей фитомассы, обеспечении калибровки и проверки дистанционных данных. Описаны имеющиеся в свободном доступе карты, базы данных и эмпирические модели (как подеревные - аллометрические, так и на уровне насаждений) лесной фитомассы. Описаны функциональные возможности интернет-портала Biomass.Geo-Wiki.org, который предоставляет доступ к коллекции глобальных и региональных карт фитомассы в полном разрешении с унифицированной легендой, наложенных на снимки высокого разрешения. Анонсирована международная кооперация ученых, проводящих измерения на постоянных пробных площадях (Forest Observation System), и рассмотрены ее перспективы в развитии сети наземных наблюдений во взаимодействии с дистанционным сообществом. Кратко рассмотрены перспективы беспилотных летательных аппаратов в инвентаризации лесов. Авторы адресуют данный обзор специалистам лесного хозяйства и научным работникам в области лесоведения и экологии, которые не являются экспертами в дистанционном зондировании, но хотят получить представление о современных тенденциях в этой области знания. Также статья нацелена на уменьшение разобщенности научных коллективов и более широкий обмен данными и знаниями между дистанционным и экологическим сообществами.
With this article, we provide an overview of the methods, instruments and initiatives for forest biomass observation at global scale. We focus on the freely available information, provided by both remote and in-situ observations. The advantages and limitation of various space borne methods, including optical, radar (C, L and P band) and LiDAR, as well as respective instruments available on the orbit (MODIS, Proba-V, Landsat, Sentinel-1, Sentinel-2, ALOS PALSAR, Envisat ASAR) or expecting (BIOMASS, GEDI, NISAR, SAOCOM-CS) are discussed. We emphasize the role of in-situ methods in the development of a biomass models, providing calibration and validation of remote sensing data. We focus on freely available forest biomass maps, databases and empirical models. We describe the functionality of Biomass.Geo-Wiki.org portal, which provides access to a collection of global and regional biomass maps in full resolution with unified legend and units overplayed with high-resolution imagery. The Forest-Observation-System.net is announced as an international cooperation to establish a global in-situ forest biomass database to support earth observation and to encourage investment in relevant field-based observations and science. Prospects of unmanned aerial vehicles in the forest inventory are briefly discussed.

РИНЦ

Держатели документа:
Ботанический сад УрО РАН
Всероссийский институт повышения квалификации руководящих работников и специалистов лесного хозяйства
Институт биологии Коми научного центра УрО РАН
Институт леса им. В. Н. Сукачева СО РАН
Международный институт прикладного системного анализа
Московский государственный технический университет им. Н. Э. Баумана
Национальный университет биоресурсов и природопользования Украины

Доп.точки доступа:
Щепащенко, Дмитрий Геннадьевич; Schepaschenko D.G.; Осипов, Андрей Федорович; Osipov A.F.; Мартыненко, Ольга Вениаминовна; Martynenko O.V.; Карминов, Виктор Николаевич; Karminov V.N.; Онтиков, Пётр Вячеславович; Ontikov P.V.; Щепащенко, Мария Владимировна; Shchepashchenko M.V.; Кракснер, Флориан; Kraxner F.; Швиденко, Анатолий Зиновьевич; Shvidenko A.Z.; Пергер, Кристоф; Perger C.; Дресел, Кристофер; Dresel C.; Фриц, Штефен; Fritz S.; Лакида, Петр Иванович; Lakyda P.I.; Мухортова, Людмила Владимировна; Mukhortova L.V.; Усольцев, Владимир Андреевич; Usoltsev V.A.; Бобкова, Капитолина Степановна; Bobkova K.S.

/ O. V. Churakova [et al.] // Clim. Past. - 2019. - Vol. 15, Is. 2. - P685-700, DOI 10.5194/cp-15-685-2019. - Cited References:91. - This work was supported by a Marie Curie International Incoming Fellowship (EU_ISOTREC 235122), a Reintegration Marie Curie Fellowship (909122), and grants to the following: a UFZ scholarship (2006), RFBR (09-05-98015_r_sibir_a), granted to Olga V. Churakova (Sidorova); SNSF to Matthias Saurer (200021_ 121838/1); an Era. Net RusPlus project granted to Markus Stoffel (SNF IZRPZ0_ 164735); RFBR (no. 16-55-76012 Era_ a) granted to Eugene A. Vaganov; and a project grant to Vladimir S. Myglan RNF, Russian Scientific Fund (no. 15-14-30011). Alexander V. Kirdyanov was supported by the Ministry of Education and Science of the Russian Federation (no. 5.3508.2017/4.6) and RSF (no. 14-14-00295). We acknowledge a Scientific School (3297.2014.4) grant to Eugene A. Vaganov, US National Science Foundation (NSF) grants (no. 9413327, no. 970966, no. 0308525) to Malcolm K. Hughes, and US CRDF grant no. RC1-279 to Malcolm K. Hughes and Eugene A. Vaganov. We thank Tatjana Boettger for her support and access to the stable isotope facilities within the framework of the UFZ Haale/Saale scholarship 2006 and stable isotope facilities at the Paul Scherrer Institute (PSI), Switzerland; we thank Anne Verstege and Daniel Nievergelt for their help with sample preparation for the MXD and Paolo Cherubini for providing lab access at the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL). . - ISSN 1814-9324. - ISSN 1814-9332РУБ Geosciences, Multidisciplinary + Meteorology & Atmospheric Sciences

Аннотация: Stratospheric volcanic eruptions have far-reaching impacts on global climate and society. Tree rings can provide valuable climatic information on these impacts across different spatial and temporal scales. To detect temperature and hydroclimatic changes after strong stratospheric Common Era (CE) volcanic eruptions for the last 1500 years (535 CE unknown, 540 CE unknown, 1257 CE Samalas, 1640 CE Parker, 1815 CE Tambora, and 1991 CE Pinatubo), we measured and analyzed tree-ring width (TRW), maximum late-wood density (MXD), cell wall thickness (CWT), and delta C-13 and delta O-18 in tree-ring cellulose chronologies of climate-sensitive larch trees from three different Siberian regions (northeastern Yakutia - YAK, eastern Taimyr - TAY, and Russian Altai - ALT). All tree-ring proxies proved to encode a significant and specific climatic signal of the growing season. Our findings suggest that TRW, MXD, and CWT show strong negative summer air temperature anomalies in 536, 541-542, and 1258-1259 at all studied regions. Based on delta C-13, 536 was extremely humid at YAK, as was 537-538 in TAY. No extreme hydroclimatic anomalies occurred in Siberia after the volcanic eruptions in 1640, 1815, and 1991, except for 1817 at ALT. The signal stored in delta O-18 indicated significantly lower summer sunshine duration in 542 and 1258-1259 at YAK and 536 at ALT. Our results show that trees growing at YAK and ALT mainly responded the first year after the eruptions, whereas at TAY, the growth response occurred after 2 years. The fact that differences exist in climate responses to volcanic eruptions - both in space and time - underlines the added value of a multiple tree-ring proxy assessment. As such, the various indicators used clearly help to provide a more realistic picture of the impact of volcanic eruption on past climate dynamics, which is fundamental for an improved understanding of climate dynamics, but also for the validation of global climate models.

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Держатели документа:
Univ Geneva, Inst Environm Sci, 66 Bvd Carl Vogt, CH-1205 Geneva, Switzerland.
Siberian Fed Univ, Inst Ecol & Geog, Svobodny Pr 79, Krasnoyarsk 660041, Russia.
Swiss Fed Inst Forest Snow & Landscape Res WSL, Zurcherstr 111, CH-8903 Birmensdorf, Switzerland.
Paul Scherrer Inst, CH-5232 Villigen, Switzerland.
Univ Blaise Pascal, Geolab, CNRS, UMR 6042, 4 Rue Ledru, F-63057 Clermont Ferrand, France.
Siberian Fed Univ, Inst Humanities, Svobodny Pr 82, Krasnoyarsk 660041, Russia.
RAS, VN Sukachev Inst Forest, SB, Fed Res Ctr Krasnoyarsk Sci Ctr, Akademgorodok 50,Bldg 28, Krasnoyarsk 660036, Russia.
Univ Cambridge, Dept Geog, Downing Pl, Cambridge CB2 3EN, England.
Siberian Fed Univ, Inst Fundamental Biol & Biotechnol, Svobodny Pr 79, Krasnoyarsk 660041, Russia.
Univ Arizona, Lab Tree Ring Res, 1215 E Lowell St, Tucson, AZ 85721 USA.
Siberian Fed Univ, Rectorate, Svobodny Pr 79-10, Krasnoyarsk 660041, Russia.
Univ Geneva, Dept Earth Sci, 13 Rue Maraichers, CH-1205 Geneva, Switzerland.
Univ Geneva, Dept FA Forel Environm & Aquat Sci, 66 Blvd Carl Vogt, CH-1205 Geneva, Switzerland.

Доп.точки доступа:
Churakova, O. V.; Fonti, Marina V.; Saurer, Matthias; Guillet, Sebastien; Corona, Christophe; Fonti, Patrick; Myglan, Vladimir S.; Kirdyanov, Alexander V.; Naumova, Oksana V.; Ovchinnikov, Dmitriy V.; Shashkin, Alexander V.; Panyushkina, Irina P.; Buntgen, Ulf; Hughes, Malcolm K.; Vaganov, Eugene A.; Siegwolf, Rolf T. W.; Stoffel, Markus; Churakova, Olga; Marie Curie International Incoming Fellowship [EU_ISOTREC 235122]; Reintegration Marie Curie Fellowship [909122]; RFBR [16-55-76012, 09-05-98015_r_sibir_a]; SNSF [200021_ 121838/1, SNF IZRPZ0_ 164735]; Russian Scientific Fund [15-14-30011]; Ministry of Education and Science of the Russian Federation [5.3508.2017/4.6]; RSF [14-14-00295, 3297.2014.4]; US National Science Foundation (NSF) [9413327, 970966, 0308525]; US CRDF [RC1-279]

/ D. Schepaschenko [et al.] // Sci Data. - 2019. - Vol. 6, Is. 1. - P198, DOI 10.1038/s41597-019-0196-1 . - ISSN 2052-4463
Аннотация: Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25?ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.

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Держатели документа:
Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Laxenburg, A-2361, Austria
Forestry faculty, Bauman Moscow State Technical University, Mytischi141005, Russian Federation
Laboratoire Evolution et Diversite Biologique CNRS/Universite Paul Sabatier, Toulouse, France
School of Geography, University of Leeds, Leeds, LS2 9JT, United Kingdom
University College London, 30 Guilford Street, London, WC1N 1EH, United Kingdom
Forest Global Earth Observatory, Smithsonian Tropical Research Institute, P.O. Box 37012WA 20013, United States
AMAP, IRD, CNRS, CIRAD, INRA, University Montpellier, Montpellier, France
CIRAD, Forets et Societes, Campus International de Baillarguet, Montpellier, F-34398, France
Forets et Societes, Univ Montpellier, CIRAD, Montpellier, F-34398, France
European Space Agency, ESTEC, Noordwijk, Netherlands
Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Laxenburg, A-2361, Austria
Spatial Focus GmbHVienna, Austria
Department Foresterie et Environnement (DFR FOREN), Institut National Polytechnique Felix Houphouet-Boigny, BP 2661Yamoussoukro, Cote d'Ivoire
Mensuration Unit, Forestry Commission of Ghana, Kumasi, Ghana
Center of Forest Ecology and Productivity of the Russian Academy of SciencesMoscow 117997, Russian Federation
Smithsonian Conservation Biology Institute, 1100 Jefferson Dr SW, DCWA, United States
Centre for International Forestry Research, CIFOR, Jalan CIFOR ,Situ Gede, Bogor, 16115, Indonesia
Universidad Autonoma Gabriel Rene MorenoSanta Cruz, Bolivia
Department of Geographical Sciences, University of Maryland, MD, 2181 Lefrak Hall ,College Park20742, United States
Joint Remote Sensing Research Program, School of Earth and Environmental Sciences, University of Queensland, Chamberlain Building (35), Campbell Road ,St Lucia Campus, Brisbane, 4072, Australia
Museo de Historia Natural Noel Kempff Mercado, Universidad Autonoma Gabriel Rene Moreno Av. Irala 565 - casillaSanta Cruz 2489, Bolivia
Instituto Boliviano de Investigacion Forestal, Av. 6 de agosto # 28, Km 14 doble via La GuardiaCasillaSanta Cruz 6204, Bolivia
Embrapa, Rodovia AM 10, km 29AM, Manaus, 69010-970, Brazil
Forest Research Institute, Department of Geomatics, Braci Lesnej 3 ,Sekocin Stary, Raszyn, 05-090, Poland
ONF, ONF-Reserve de Montabo Cayenne Cedex, Cayenne, BP 7002; 97307, French Guiana
Landscapes and Livelihoods Group, 20 Chambers St, Edinburgh, EH1 1JZ, United Kingdom
National University of Life and Environmental Sciences of Ukraine, General Rodimtsev 19Kyiv 3041, Ukraine
Herbier National du Gabon (IPHAMETRA), B.P 1165, Libreville, Gabon
Institute of Biology, Komi Scientific Center, Ural Branch of Russian Academy of Sciences, Syktyvkar, 167982, Russian Federation
School of Biological Sciences, University of Aberdeen, Cruickshank Building, St Machar Drive, Aberdeen, AB24 3UU, United Kingdom
Morton Arboretum, 4100 Illinois Rte. 53, Lisle, 60532, United States
Department of Environment and Geography, University of York, Heslington, York, YO10 5NG, United Kingdom
V.N. Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Science, Krasnoyarsk, 660036, Russian Federation
Instituto de Investigaciones de la Amazonia Peruana, Av. Abelardo Quinones km 2.5Apartado Postal 784, Iquitos, Peru
CIRAD, UMR EcoFoG, Campus Agronomique - BP 701, Kourou, 97387, French Guiana
Embrapa, Rodovia Juscelino Kubitscheck, no 2.600, 68903-419, Km 5Caixa Postal 10, Macapa, Brazil
Embrapa, BR 364, Caixa postal 321, Rio Branco, 69.900-970, Brazil
SI Entomology, Smithsonian Institution, DC, PO Box 37012 ,MRC 187WA, United States
Department Forest Ecology and Management, Swedish University of Agricultural Sciences, SLU, Umea, SE 901 83, Sweden
Geography, College of Life and Environmental Sciences, University of Exeter, Laver Building, North Park Road, Exeter, EX4 4QE, United Kingdom
Forestry Research Institute of Ghana, KNUST, UP Box 63, Kumasi, Ghana
Field Musium, 1400S Lake Shore Dr, Chicago, 60605, United States
Universidad Politecnica de Madrid ,Calle Ramiro de MaeztuMadrid 28040, Spain
Institut Centrafricain de Recherche Agronomique, ICRA, BP 122Bangui, Central African Republic
School of Biology, University of Leeds, Leeds, LS2 9JT, United Kingdom
Forestry and Environment Research Development and Innovation Agency, Jalan Gunung Batu No 5, Bogor, 16610, Indonesia
Instituto Nacional de Pesquisas da Amazonia - Coordenacao de Pesquisas em Silvicultura Tropical, Manaus, 69060-001, Brazil
Gent-Woodlab, Laboratory of Wood Technology, Department of Environment, Ghent University, Ghent, 9000, Belgium
Department of Ecology and Evolutionary Biology, University of California, 621 Charles E. Young Dr. South, Los Angeles, CA, 90095-1606, USA
Embrapa Amazonia Oriental, Travessa Doutor Eneas Pinheiro, Belem, 66095-903, Brazil
World Wildlife Fund, Calle Diego de Mendoza 299, Santa Cruz de la Sierra, Bolivia
boulevard Francois Mitterrand01BP 3770Abidjan, Cote d'Ivoire
Global Change Research Institute CAS, Belidla 986/4a, Brno, 603 00, Czech Republic
Department of Geography and Earth Sciences, Aberystwyth University, AberystwythSY23 3DB, United Kingdom
School of Geography and the Environment, University of Oxford, Oxford, OX1 3QY, United Kingdom
Laboratorio de Ecologia Vegetal, Universidade do Estado de Mato Grosso, UNEMAT, Campus de Nova Xavantina, Nova Xavantina, Mato Grosso 78.690-000, Brazil
Jardin Botanico de Missouri; Universidad Nacional de San Antonio Abad del Cusco, Oxapampa, Peru
Russian Institute of Continuous Education in Forestry, Pushkino, 141200, Russian Federation
Institute for Evolutionary Ecology of the National Academy of Sciences of UkraineKyiv 03143, Ukraine
University of Oregon, 1585 E 13th AveOR, Eugene, 97403, United States
Forest Management in Bolivia, Bolivia
FRIM Forest Reserach Institute of Malaysia, 52109 Kepong, Selangor, Kuala Lumpur, Malaysia
Hiroshima University, 1-7-1 Kagamiyama ,Higashi-HiroshimaHiroshima 739-8521, Japan
Forestry faculty, Bauman Moscow State Technical University, Mytischi141005, Russian Federation
Center for Agricultural research in SurinameParamaribo 1914, Suriname
Nicholas School of the Environment, Duke University, P.O. Box 90328, Durham, 27708, United States
IIC, Iwokrama International Centre for Rain Forest Conservation and Development, 77 High Street, Georgetown, Guyana
Cibodas Botanic Gardens - Indonesian Institute of Sciences (LIPI)43253, Indonesia
Smithsonian Tropical Research Institute, Balboa, Ancon, Panama 3092, Panama
Museu Universitario, Universidade Federal do Acre, BR 364, Km 04 - Distrito Industrial, Rio Branco, 69915-559, Brazil
Guyana Forestry Commission, 1 Water Street, Guyana
Plant Systematic and Ecology Laboratory, University of Yaounde I, P.O. Box 047, Yaounde, Cameroon
Bioversity international, P.O. Box 2008, Yaounde
Naturalis Biodiversity Center, Leiden, Netherlands
School of Natural Sciences, Bangor University, Thoday Building. Deiniol Rd, Bangor, LL57 2UW, United Kingdom
Siberian Federal University, 79, Krasnoyarsk, 660041, Russian Federation
Reshetnev Siberian state university of science and technology, pr. Mira 82, Krasnoyarsk, 660049, Russian Federation
Department of Forest Sciences, Luiz de Queiroz College of Agriculture, University of Sao Paolo, PO Box 9 ,Av. Padua Dias ,11, Piracicaba, Sao Paulo 13418-900, Brazil
State Nature Reserve Denezhkin Kamen, Sverdlovsk reg, Lenina, Russian Federation
International Center for Tropical Botany, Department of Biological Sciences, Florida International University, FL, 11200 S.W. 8th Street, Miami, 33199, United States
Universidad Autonoma del Beni, Riberalta, Bolivia
Department of Microbiology and Ecosystem Science, Division of Terrestrial Ecosystem research, University of Vienna, Althanstrasse 14Vienna A-1090, Austria
New Zealand Forest Research Institute (Scion) Te Papa Tipu Innovation Park ,49 Sala Street, Rotorua, 3046, New Zealand
Unaffiliated (retired), Bad Aussee, 8990, Austria
W.R.T College of Agriculture and Forestry, University of Liberia, Capitol Hill, Monrovia, 9020, Liberia
FRIM Forest Research Institute of Malaysia, 52109 Kepong, Selangor, Kuala Lumpur, Malaysia

Доп.точки доступа:
Schepaschenko, D.; Chave, J.; Phillips, O. L.; Lewis, S. L.; Davies, S. J.; Rejou-Mechain, M.; Sist, P.; Scipal, K.; Perger, C.; Herault, B.; Labriere, N.; Hofhansl, F.; Affum-Baffoe, K.; Aleinikov, A.; Alonso, A.; Amani, C.; Araujo-Murakami, A.; Armston, J.; Arroyo, L.; Ascarrunz, N.; Azevedo, C.; Baker, T.; Balazy, R.; Bedeau, C.; Berry, N.; Bilous, A. M.; Bilous, S. Y.; Bissiengou, P.; Blanc, L.; Bobkova, K. S.; Braslavskaya, T.; Brienen, R.; Burslem, D. F.R.P.; Condit, R.; Cuni-Sanchez, A.; Danilina, D.; Del Castillo Torres, D.; Derroire, G.; Descroix, L.; Sotta, E. D.; d'Oliveira, M. V.N.; Dresel, C.; Erwin, T.; Evdokimenko, M. D.; Falck, J.; Feldpausch, T. R.; Foli, E. G.; Foster, R.; Fritz, S.; Garcia-Abril, A. D.; Gornov, A.; Gornova, M.; Gothard-Bassebe, E.; Gourlet-Fleury, S.; Guedes, M.; Hamer, K. C.; Susanty, F. H.; Higuchi, N.; Coronado, E. N.H.; Hubau, W.; Hubbell, S.; Ilstedt, U.; Ivanov, V. V.; Kanashiro, M.; Karlsson, A.; Karminov, V. N.; Killeen, T.; Koffi, J. -C.K.; Konovalova, M.; Kraxner, F.; Krejza, J.; Krisnawati, H.; Krivobokov, L. V.; Kuznetsov, M. A.; Lakyda, I.; Lakyda, P. I.; Licona, J. C.; Lucas, R. M.; Lukina, N.; Lussetti, D.; Malhi, Y.; Manzanera, J. A.; Marimon, B.; Junior, B. H.M.; Martinez, R. V.; Martynenko, O. V.; Matsala, M.; Matyashuk, R. K.; Mazzei, L.; Memiaghe, H.; Mendoza, C.; Mendoza, A. M.; Moroziuk, O. V.; Mukhortova, L.; Musa, S.; Nazimova, D. I.; Okuda, T.; Oliveira, L. C.; Ontikov, P. V.; Osipov, A. F.; Pietsch, S.; Playfair, M.; Poulsen, J.; Radchenko, V. G.; Rodney, K.; Rozak, A. H.; Ruschel, A.; Rutishauser, E.; See, L.; Shchepashchenko, M.; Shevchenko, N.; Shvidenko, A.; Silveira, M.; Singh, J.; Sonke, B.; Souza, C.; Sterenczak, K.; Stonozhenko, L.; Sullivan, M. J.P.; Szatniewska, J.; Taedoumg, H.; Ter Steege, H.; Tikhonova, E.; Toledo, M.; Trefilova, O. V.; Valbuena, R.; Gamarra, L. V.; Vasiliev, S.; Vedrova, E. F.; Verhovets, S. V.; Vidal, E.; Vladimirova, N. A.; Vleminckx, J.; Vos, V. A.; Vozmitel, F. K.; Wanek, W.; West, T. A.P.; Woell, H.; Woods, J. T.; Wortel, V.; Yamada, T.; Nur Hajar, Z. S.; Zo-Bi, I. C.

/ O. V. Masyagina, S. Y. Evgrafova, O. V. Menyailo [et al.] // Forests. - 2021. - Vol. 12, Is. 1. - Ст. 107. - P1-25, DOI 10.3390/f12010107 . - ISSN 1999-4907
Аннотация: The observed high spatial variation in soil respiration (SR) and associated parameters emphasized the importance of SR heterogeneity at high latitudes and the involvement of many factors in its regulation, especially within fire-affected areas. The problem of estimating CO2 emissions during post-fire recovery in high-latitude ecosystems addresses the mutual influence of wildfires and climate change on the C cycle. Despite its importance, especially in permafrost regions because of their vulnerability, the mutual influence of these factors on CO2 dynamics has rarely been stud-ied. Thus, we aimed to understand the dynamics of soil respiration (SR) in wildfire-affected larch recovery successions. We analyzed 16-year data (1995–2010) on SR and associated soil, biological, and environmental parameters obtained during several field studies in larch stands of different ages (0–276 years) in the Krasnoyarsk region (Russia). We observed a high variation in SR and related parameters among the study sites. SR varied from 1.77 ± 1.18 (mean ± SD) µmol CO2 m?2 s?1 in the 0–10-year-old group to 5.18 ± 2.70 µmol CO2 m?2 s?1 in the 150–276-year-old group. We found a significant increasing trend in SR in the 88–141-year old group during the study period, which was related to the significant decrease in soil water content due to the shortage of precipitation during the growing season. We observed a high spatial variation in SR, which was primarily regulated by biological and environmental factors. Different parameters were the main contributors to SR in each group, an SR was significantly affected by the inter-relationships between the studied parameters. The obtained results can be incorporated into the existing SR databases, which can allow their use in the construction and validation of C transport models as well as in monitoring global fluctuations in the C cycle in response to climate change. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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Держатели документа:
Sukachev Institute of Forest SB RAS, Federal Research Center “Krasnoyarsk Science Center SB RAS”, 50/28 Akademgorodok St., Krasnoyarsk, 660036, Russian Federation
Institute of Fundamental Biology and Biotechnology, Siberian Federal University, 79 Svobodny Avenue, Krasnoyarsk, 660041, Russian Federation
Melnikov Permafrost Institute SB RAS, 36 Merzlotnaya St., Yakutsk, 677010, Russian Federation
Faculty of Agriculture, Yamagata University, Wakabamachi 1-23, Yamagata, Tsuruoka, 997-8555, Japan
Research Faculty of Agriculture, Hokkaido University, Sapporo, 060-8589, Japan

Доп.точки доступа:
Masyagina, O. V.; Evgrafova, S. Y.; Menyailo, O. V.; Mori, S.; Koike, T.; Prokushkin, S. G.