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

[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] / V. I. Kharuk [et al.] // Int. J. Remote Sens. - 2003. - Vol. 24, Is. 1. - P23-37, DOI 10.1080/0143116021000021143. - Cited References: 30 . - 15. - ISSN 0143-1161РУБ Remote Sensing + Imaging Science & Photographic Technology

Аннотация: In this paper NOAA AVHRR data acquired at the Sukachev Institute of Forest in Siberia, Russia is evaluated for forest management mapping applications. First a classification of the entire 1000 km x 3000 km transect was performed, but was found to be too general to be of value. More useful interpretation procedures require a landscape-ecological approach. This means that computer classification should be made separately for segments of territory based ecologically distinct regions. This segmentation of the transect into ecological regions was found to improve the level of detail available in the classification. Using this approach AVHRR data were found to be adequate for small scale mapping at the level of vegetation types or plant formations. A limited study using AVHRR data for classification of mountainous regions showed that AVHRR-derived maps were more detailed than existing landscape maps. AVHRR derived classifications also compared favourably to larger scale forest management maps of softwood and hardwood forests. Current forest management in Siberia relies on very small-scale inventory maps. Thus, there is a potential role for AVHRR (or Terra) data for northern Siberian forest monitoring. The southern forests of the Yenisey meridian (below the 57th parallel) are less uniform due to considerable human activity, and NOAA/AVHRR data will play a subordinate role in its monitoring.

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Держатели документа:
Sukachev Inst Forest, Krasnoyarsk, Russia
NASA, Goddard Space Flight Ctr, Biospher Sci Branch, Greenbelt, MD 20771 USA

Доп.точки доступа:
Kharuk, V.I.; Ranson, K.J.; Burenina, T.A.; Fedotova, E.V.

[Text] / S. . Wilhelm [et al.] // Forests. - 2014. - Vol. 5, Is. 8. - P1999-2015, DOI 10.3390/f5081999. - Cited References: 50. - The authors want to thank the employees of the Sukachev Institute of Forest in Krasnoyarsk, Russia, Siberia, who were involved in the validation of the mapping results. In addition, thanks go out to Tim Robin van Doorn for proofreading this article. The maps were produced within the FP 7 EU-Russia ZAPAS (Russian: 3anac, stands for GSV or forest stock) project on the assessment and monitoring of forest resources in central Siberia. ZAPAS was funded by the European Commission, Space, Cross-cutting Activities, International Cooperation, Grant No. SPA.2010.3.2-01 EU-Russia Cooperation in Global Monitoring for Environment and Security (GMES). . - ISSN 1999-4907РУБ Forestry

Аннотация: The forests of the Russian Taiga can be described as an enormous biomass and carbon reservoir. Therefore, they are of utmost importance for the global carbon cycle. Large-area forest inventories in these mostly remote regions are associated with logistical problems and high financial efforts. Remotely-sensed data from satellite platforms may have the capability to provide such huge amounts of information. This study presents an application-oriented approach to derive aboveground growing stock volume (GSV) maps using the annual large-area L-band backscatter mosaics provided by the Japan Aerospace Exploration Agency (JAXA). Furthermore, a multi-temporal map has been created to improve GSV estimation accuracy. Based on information from Russian forest inventory data, the maps were generated using the machine learning algorithm, RandomForest. The results showed the high potential of this method for an operational, large-scale and high-resolution biomass estimation over boreal forests. An RMSE from 55.2 to 63.3 m(3)/ha could be obtained for the annual maps. Using the multi-temporal approach, the error could be slightly reduced to 54.4 m(3)/ha.

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Держатели документа:
[Wilhelm, Sebastian] Earth Observat Serv EOS Jena GmbH, D-07743 Jena, Germany
[Huettich, Christian
Schmullius, Christiane] Univ Jena, Dept Earth Observat, D-07743 Jena, Germany
[Korets, Mikhail] Russian Acad Sci, VN Sukachev Inst Forest, Siberian Branch, Krasnoyarsk 660036, Russia
ИЛ СО РАН

Доп.точки доступа:
Wilhelm, S...; Huttich, C...; Korets, M...; Schmullius, C...; European Commission, Space, Cross-cutting Activities, International Cooperation, EU-Russia Cooperation in Global Monitoring for Environment and Security (GMES) [SPA.2010.3.2-01]

/ N. M. Tchebakova, E. I. Parfenova, A. J. Soja ; ed.: L. . Mueller, A. K. Sheudshen, F. . Eulenstein // NOVEL METHODS FOR MONITORING AND MANAGING LAND AND WATER RESOURCES IN : SPRINGER INT PUBLISHING AG, 2016. - P269-285. - (Springer Water), DOI 10.1007/978-3-319-24409-9_10. - Cited References:51 . - РУБ Environmental Sciences + Soil Science + Water Resources

Аннотация: The redistribution of terrestrial ecosystems and individual species is predicted to be profound under Global Climate Model simulations. We modeled the progression of potential vegetation and forest types in Siberia by the end of the twenty-first century by coupling large-scale bioclimatic models of vegetation zones and major conifer species with climatic variables and permafrost using the B1 and A2 Hadley Centre HadCM3 climate change scenarios. In the projected warmer and dryer climate, Siberian taiga forests are predicted to dramatically decrease and shift to the northeast, and forest-steppe, steppe, and novel temperate broadleaf forests are predicted to dominate most of Siberia by 2090. The permafrost should not retreat sufficiently to provide favorable habitats for dark (Pinus sibiric, Abies sibirica, and Picea obovata) taiga, and the permafrost-tolerant L. dahurica taiga should remain the dominant forest type in many current permafrost-lain areas. Water stress and fire-tolerant tree species (Pinus sylvestris and Larix spp.) should have an increased advantage over moisture-loving tree species (P. sibirica, A. sibirica, and P. obovata) in a new climate. Accumulated surface fuel loads due to increased tree mortality from drought, insects, and other factors, especially at the southern forest border and in the Siberian interior (Yakutia), together with an increase in severe fire weather, should also lead to increases in large, high-severity fires that are expected to facilitate vegetation progression toward a new equilibrium with the climate. Adaptation of the forest types and tree species to climate change in the south may be based on the genetic means of individual species and human willingness to aid migration, perhaps by seeding. Additionally, useful and viable crops could be established in agricultural lands instead of failing forests.

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Держатели документа:
Russian Acad Sci, VN Sukachev Inst Forest, Siberian Branch SIF SB RAS, Akademgorodok 50-28, Krasnoyarsk 660036, Russia.
NASA, Langley Res Ctr, 21 Langley Blvd,Mail Stop 420, Hampton, VA 23681 USA.

Доп.точки доступа:
Tchebakova, Nadezhda M.; Parfenova, Elena I.; Soja, Amber J.; Mueller, L... \ed.\; Sheudshen, A.K. \ed.\; Eulenstein, F... \ed.\

/ N. I. Kirichenko, E. N. Akulov, P. Triberti, S. A. Belokobylskij // ZooKeys. - 2021. - Is. 1061. - P131-163, DOI 10.3897/zookeys.1061.70929. - Cited References:49. - We thank Jean-Francois Landry (Canada) and Charley Eiseman (USA) for fruitful discussions on Thermopsis-feeding Micrurapteryx and the comments on M. occulta and "Parectopa" thermopsella, Svetlana V. Shishova and Ekaterina A. Kirichenko (Krasnoyarsk, Russia) for assistance in the field, Dmitry R. Kasparyan and Andrei I. Khalaim (St. Petersburg, Russia) for consultation and determination of Campopleginae, Marko Mutanen (Finland), Torbjorn Ekrem (Norway), Evgeny V. Zakharov (Canada), Tatsiana Lipinskaya (Belarus), Caroline Chimeno (Germany) for allowing us to use the sequences of parasitoid species, Irina A. Mikhailova (Krasnoyarsk, Russia) for helping with mapping, and Olga V. Kuznetsova (Siberian Federal University, Krasnoyarsk, Russia) for English language checking. Special thanks to Erik J van Nieukerken (the Netherlands), Camiel Doorenweerd (USA), and Tengteng Liu (China) for thoughtful revision of the manuscript. NK was partially supported by the Russian Foundation for Basic Research (project No. 1904-01029-a) [field sampling, morphological and molecular genetic analysis] and the basic project of Sukachev Institute of Forest SB RAS, Krasnoyarsk, Russia (project No. 0287-2021-0011) [indoor rearing]. SAB received support from the Russian Foundation for Basic Research (project No. 19-04-00027) and the Russian State Research Project (No. AAAA-A19-119020690101-6). We also thank the team at the Biodiversity Institute of Ontario, University of Guelph (Ontario, Canada) for their great assistance in the production of DNA barcodes. . - ISSN 1313-2989. - ISSN 1313-2970РУБ Zoology

Аннотация: A new species of leaf-mining moth described here as Micrurapteryx baranchikovi Kirichenko, Akulov & Triberti, sp. nov. was detected in large numbers feeding on Thermopsis lanceolata (Fabaceae) in the Republic of Khakassia (Russia) in 2020. A morphological diagnosis of adults, bionomics and DNA barcoding data of the new species are provided. The developmental stages (larva, pupa, adult), male and female genitalia, as well as the leaf mines and the infestation plot in Khakassia are illustrated; the pest status of the new species in the studied region is discussed. Additionally, parasitism rate was estimated, the parasitoid wasps reared from pupae of the new species were identified (morphologically and genetically) and illustrated . Among them, one ichneumonid, Campoplex sp. aff. borealis (Zetterstedt) and two braconids, Agathis fuscipennis (Zetterstedt) and Illidops subversor (Tobias et Kotenko), are novel records for the Republic of Khakassia. Furthermore, they are all documented as parasitoids of Gracillariidae for the first time. The DNA barcode of A. fuscipennis is newly obtained and can be used as a reference sequence for species identification.

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Держатели документа:
Russian Acad Sci, Fed Res Ctr, Krasnoyarsk Sci Ctr SB RAS, Sukachev Inst Forest, Akademgorodok 50-28, Krasnoyarsk 660036, Russia.
Siberian Fed Univ, Svobodny Pr 79, Krasnoyarsk 660041, Russia.
All Russian Plant Quarantine Ctr, Krasnoyarsk Branch, Zhelyabova Str 6-6, Krasnoyarsk 660020, Russia.
Museo Civ Storia Nat, Lungadige Porta Vittoria 9, I-37129 Verona, Italy.
Russian Acad Sci, Zool Inst, Univ Skaya Nab 1, St Petersburg 199034, Russia.
Polish Acad Sci, Museum & Inst Zool, 64 Wilcza, PL-00679 Warsaw, Poland.

Доп.точки доступа:
Kirichenko, Natalia, I; Akulov, Evgeny N.; Triberti, Paolo; Belokobylskij, Sergey A.; Russian Foundation for Basic ResearchRussian Foundation for Basic Research (RFBR) [1904-01029-a, 19-04-00027]; Sukachev Institute of Forest SB RAS, Krasnoyarsk, Russia [0287-2021-0011]; Russian State Research Project [AAAA-A19-119020690101-6]