Forests often rebound from deforestation following industrialization and urbanization, but for many regions our understanding of where and when forest transitions happened, and how they affected carbon budgets remains poor. One such region is Eastern Europe, where political and socio-economic conditions changed drastically over the last three centuries, but forest trends have not yet been analyzed in detail. We present a new assessment of historical forest change in the European part of the former Soviet Union and the legacies of these changes on contemporary carbon stocks. To reconstruct forest area, we homogenized statistics at the provincial level for ad 1700-2010 to identify forest transition years and forest trends. We contrast our reconstruction with the KK11 and HYDE 3.1 land change scenarios, and use all three datasets to drive the LPJ dynamic global vegetation model to calculate carbon stock dynamics. Our results revealed that forest transitions in Eastern Europe occurred predominantly in the early 20th century, substantially later than in Western Europe. We also found marked geographic variation in forest transitions, with some areas characterized by relatively stable or continuously declining forest area. Our data suggest extensive deforestation in European Russia already prior to ad 1700, and even greater deforestation in the 18th and 19th centuries than in the KK11 and HYDE scenarios. Based on our reconstruction, cumulative carbon emissions from deforestation were greater before 1700 (60 Pg C) than thereafter (29 Pg C). Summed over our entire study area, forest transitions led to a modest uptake in carbon over recent decades, with our dataset showing the smallest effect (<5.5 Pg C) and a more heterogeneous pattern of source and sink regions. This suggests substantial sequestration potential in regrowing forests of the region, a trend that may be amplified through ongoing land abandonment, climate change, and CO2 fertilization.

This paper deals with the problem of constructing graphic images of territories that make the density of a variable (e.g., the density of population) uniform. The authors discuss some existing construction algorithms and describe a new algorithm and the results of its applications.

This article describes the Pan-Eurasian Experiment (PEEX) program and indicators for monitoring of implementation and digitalization of Sustainable Development Goals (SDG) in Russia, especially environmental goals. The authors considered the possibility of integration and identification of the methodological approaches of the socioeconomic research to environmental sciences. Paper gives insights into the international framework of the United nations, addreses several relevant indicators to be monitored in a Russian perspective and summarizes shortly the status of the monitoring activities and provide an overview on the main tasks for the upcoming years to reach the sustainable development goals established by the United Nations. The tasks to which the Goals divided are considered in detail. The indicators of Russian statistics that can be used to monitor the implementation of these tasks are determined. It is shown, that more detailed regional analysis and new data is needed in order to quantify the feedbackloops.

No abstract