Russian forest sequesters substantially more carbon than previously reported

Schepaschenko, Dmitry; Moltchanova, Elena; Fedorov, Stanislav; Karminov, Victor; Ontikov, Petr; Santoro, Maurizio; See, Linda; Косицын, В Н; Shvidenko, А.; Romanovskaya, A. A.; Коротков, В. Н.; Lesiv, Myroslava; Bartalev, Sergey; Shchepashchenko, Maria; Kraxner, Florian

doi:10.1038/s41598-021-92152-9

Cited by 62 publications

(29 citation statements)

References 19 publications

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“…CC BY 4.0 License.In the two largest boreal and arctic countries Canada (CAN) and Russian (RUS), inversions produce a CO2 sink (average 219 and 326 TgC yr -1 ) which is systematically larger than the NIs (2 and 173 TgC yr -1 , respectively) during 2001-2019. The larger Russian sink of inversions is similar with the results of a recent analysis(Schepaschenko et al, 2021)of forest inventory data estimating a carbon accumulation of 343 TgC yr -1 from 1988 to 2014. The Russian carbon stock increase is 6.0 TgC yr -1 annually in the NI during the 2000s, smaller than the increasing CO2 sink rate of 16.4 TgC yr -1 across inversions.…”

supporting

confidence: 86%

Comparing national greenhouse gas budgets reported in UNFCCC inventories against atmospheric inversions

Deng

Ciais

Tzompa-Sosa

et al. 2021

Preprint

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Abstract. In support of the Global Stocktake of the Paris Agreement on Climate change, this study presents a comprehensive framework to process the results of atmospheric inversions in order to make them suitable for evaluating UNFCCC national inventories of land-use carbon dioxide (CO2) emissions and removals, corresponding to the Land Use, Land Use Change and Forestry and waste sectors. We also deduced anthropogenic methane (CH4) emissions regrouped into fossil and agriculture and waste emissions, and anthropogenic nitrous oxide (N2O) emissions from inversions. To compare inversions with national reports, we compiled a new global harmonized database of national emissions and removals from periodical UNFCCC inventories by Annex I countries, and from sporadic and less detailed emissions reports by Non-Annex I countries, given by National Communications and Biennial Update Reports. The method to reconcile inversions with inventories is applied to selected large countries covering 78 % of the global land carbon uptake for CO2, as well as emissions and removals in the land use, land use change and forestry sector, and top-emitters of CH4 and N2O. Our method uses results from an ensemble of global inversions produced by the Global Carbon Project for the three greenhouse gases, with ancillary data. We examine the role of CO2 fluxes caused by lateral transfer processes from rivers and from trade in crop and wood products, and the role of carbon uptake in unmanaged lands, both not accounted for by the rules of inventories. Here we show that, despite a large spread across the inversions, the median of available inversion models points to a larger terrestrial carbon sink than inventories over temperate countries or groups of countries of the Northern Hemisphere like Russia, Canada and the European Union. For CH4, we find good consistency between the inversions assimilating only data from the global in-situ network and those using satellite CH4 retrievals, and a tendency for inversions to diagnose higher CH4 emissions estimates than reported by inventories. In particular, oil and gas extracting countries in Central Asia and the Persian Gulf region tend to systematically report lower emissions compared to those estimated by inversions. For N2O, inversions tend to produce higher anthropogenic emissions than inventories for tropical countries, even when attempting to consider only managed land emissions. In the inventories of many non-Annex I countries, this can be tentatively attributed to either a lack of reporting indirect N2O emissions from atmospheric deposition and from leaching to rivers, or to the existence of natural sources intertwined with managed lands, or to an under-estimation of N2O emission factors for direct agricultural soil emissions. The advantage of inversions is that they provide insights on seasonal and interannual greenhouse gas fluxes anomalies, e.g. during extreme events such as drought or abnormal fire episodes, whereas inventory methods are established to estimate trends and multi-annual changes. As a much denser sampling of atmospheric CO2 and CH4 concentrations by different satellites coordinated into a global constellation is expected in the coming years, the methodology proposed here to compare inversion results with inventory reports could be applied regularly for monitoring the effectiveness of mitigation policy and progress by countries to meet the objective of their pledges.

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confidence: 86%

Comparing national greenhouse gas budgets reported in UNFCCC inventories against atmospheric inversions

Deng

Ciais

Tzompa-Sosa

et al. 2021

Preprint

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“…The work presented in this paper is focused specifically on estimation of GSV in the Russian boreal forest. The Boreal forest generally, and the Russian part in particular, is poorly inventoried [1,61] and yet its importance in our understanding of the global climate system is high [62]. Globally, the boreal forest accounts for 31% of the area, 20% of the GSV, and 13% of the above-ground biomass of all forest whereas Russia, which is dominated by boreal forest, accounts for 20% of the global forest area [63].…”

Section: Introductionmentioning

confidence: 99%

“…Globally, the boreal forest accounts for 31% of the area, 20% of the GSV, and 13% of the above-ground biomass of all forest whereas Russia, which is dominated by boreal forest, accounts for 20% of the global forest area [63]. However, a recent study based on remote sensing data has shown that the growing stock of Russian forests is 39% higher than the value of official statistics in the State Forest Register [61]. Multispectral VNIR remote sensing-based GSV estimation for boreal forest is particularly challenging because of the low canopy coverage, combined with the fact the field layer is often composed of dwarf shrubs that are spectrally not very different from the forest canopy [64].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Boreal Forest Growing Stock Volume in Russia from Sentinel-2 MSI and Land Cover Classification

et al. 2021

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Growing stock volume (GSV) is a fundamental parameter of forests, closely related to the above-ground biomass and hence to carbon storage. Estimation of GSV at regional to global scales depends on the use of satellite remote sensing data, although accuracies are generally lower over the sparse boreal forest. This is especially true of boreal forest in Russia, for which knowledge of GSV is currently poor despite its global importance. Here we develop a new empirical method in which the primary remote sensing data source is a single summer Sentinel-2 MSI image, augmented by land-cover classification based on the same MSI image trained using MODIS-derived data. In our work the method is calibrated and validated using an extensive set of field measurements from two contrasting regions of the Russian arctic. Results show that GSV can be estimated with an RMS uncertainty of approximately 35–55%, comparable to other spaceborne estimates of low-GSV forest areas, with 70% spatial correspondence between our GSV maps and existing products derived from MODIS data. Our empirical approach requires somewhat laborious data collection when used for upscaling from field data, but could also be used to downscale global data.

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“…The Russian forest sector is of great importance for the global economy in several dimensions, including climate change and carbon storage, biodiversity preservation, water regulation and soil protection, and global ecosystem services, and plays a significant role in timber supply [1,2].…”

Section: Introductionmentioning

confidence: 99%

Drivers of Spatial Heterogeneity in the Russian Forest Sector: A Multiple Factor Analysis

Gordeev

Pyzhev

Yagolnitser

2021

Forests

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This study explored the regional differences in the forest industry and management via a Multiple Factor Analysis approach. The dataset used comprises all Russian regions and 34 variables that comprehensively describe the situation in the sector. Based on the Multiple Factor Analysis, the variables contributing most to the spatial heterogeneity in Russian forestry were divided into industrial and forestry factors. The regions leading in the development of the timber industry are mainly located in the Northwestern and Southeastern parts of Russia. They show similarities in high logging volumes, investment attractiveness, and competitiveness in foreign markets. However, a divergence was found between the Northwestern regions and the Siberian and the Far East territories in terms of forest management factors. The Western part of Russia benefits from the density of the population and infrastructure, and proximity to the national financial centers and European markets. By comparison, Asian Russia suffers from labor shortages caused by negative demographic trends and the negative consequences of climate change, resulting in an increase in forest losses and a lack of control, finance, and transport accessibility due to the vast territory. To alleviate regional inequalities, we propose the introduction of private ownership of forests, support for investment projects, and human capital development.

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Russian forest sequesters substantially more carbon than previously reported

Cited by 62 publications

References 19 publications

Comparing national greenhouse gas budgets reported in UNFCCC inventories against atmospheric inversions

Comparing national greenhouse gas budgets reported in UNFCCC inventories against atmospheric inversions

Estimation of Boreal Forest Growing Stock Volume in Russia from Sentinel-2 MSI and Land Cover Classification

Drivers of Spatial Heterogeneity in the Russian Forest Sector: A Multiple Factor Analysis

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