It appears you don't have support to open PDFs in this web browser. To view this file, Open with your PDF reader
Abstract
Since the collapse of the Soviet Union and transition to a new forest inventory system, Russia has reported almost no change in growing stock (+ 1.8%) and biomass (+ 0.6%). Yet remote sensing products indicate increased vegetation productivity, tree cover and above-ground biomass. Here, we challenge these statistics with a combination of recent National Forest Inventory and remote sensing data to provide an alternative estimate of the growing stock of Russian forests and to assess the relative changes in post-Soviet Russia. Our estimate for the year 2014 is 111 ± 1.3 × 109 m3, or 39% higher than the value in the State Forest Register. Using the last Soviet Union report as a reference, Russian forests have accumulated 1163 × 106 m3 yr-1 of growing stock between 1988–2014, which balances the net forest stock losses in tropical countries. Our estimate of the growing stock of managed forests is 94.2 × 109 m3, which corresponds to sequestration of 354 Tg C yr-1 in live biomass over 1988–2014, or 47% higher than reported in the National Greenhouse Gases Inventory.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details
1 Center for Forest Ecology and Productivity of the Russian Academy of Sciences, Moscow, Russia (GRID:grid.465437.7); International Institute for Applied Systems Analysis, Laxenburg, Austria (GRID:grid.75276.31) (ISNI:0000 0001 1955 9478); Siberian Federal University, Krasnoyarsk, Russia (GRID:grid.412592.9) (ISNI:0000 0001 0940 9855)
2 University of Canterbury, School of Mathematics and Statistics, Christchurch, New Zealand (GRID:grid.21006.35) (ISNI:0000 0001 2179 4063)
3 FSBI Roslesinforg, Federal Forestry Agency, Moscow, Russia (GRID:grid.21006.35)
4 Center for Forest Ecology and Productivity of the Russian Academy of Sciences, Moscow, Russia (GRID:grid.465437.7); Russian Institute of Continuous Education in Forestry, Pushkino, Russia (GRID:grid.465437.7)
5 FSBI Roslesinforg, Federal Forestry Agency, Moscow, Russia (GRID:grid.465437.7)
6 Gamma Remote Sensing, Gümligen, Switzerland (GRID:grid.424908.3) (ISNI:0000 0004 0613 3138)
7 International Institute for Applied Systems Analysis, Laxenburg, Austria (GRID:grid.75276.31) (ISNI:0000 0001 1955 9478)
8 Federal Forestry Agency, Moscow, Russia (GRID:grid.494087.6)
9 International Institute for Applied Systems Analysis, Laxenburg, Austria (GRID:grid.75276.31) (ISNI:0000 0001 1955 9478); Siberian Branch of the Russian Academy of Science, V.N. Sukachev Institute of Forest, Krasnoyarsk, Russia (GRID:grid.415877.8) (ISNI:0000 0001 2254 1834)
10 Yu. A. Izrael Institute of Global Climate and Ecology, Moscow, Russia (GRID:grid.435253.6) (ISNI:0000 0004 0499 2879)
11 Space Research Institute of the Russian Academy of Sciences, Moscow, Russia (GRID:grid.426428.e) (ISNI:0000 0004 0405 8736)
12 Russian Institute of Continuous Education in Forestry, Pushkino, Russia (GRID:grid.75276.31)




