Agriculture is one of the economic sectors primarily affected by climate change. This impact is very uneven, especially for countries with large territories. This paper examines the contribution of climate change to the improvement in agricultural productivity in Russia over the past two decades. Several ensembles of fixed effects regressions on yields and gross harvests of grain, fruits, and berries, potato, and vegetables were evaluated for a sample of 77 Russian regions over the 2002–2019 period. In contrast to similar studies of the climate impact on Russian agriculture, we considered a larger set of variables, including both Russian and global climate trends, technological factors, and producer prices. Russian weather trends such as winter softening and increase in summer heat have a significant but opposite effect on yields. An interesting finding is a significant and mostly positive influence of global climatic variables, such as the CO₂ concentration, El Niño and La Niña events on both harvests and yields. Although technological factors are the main drivers of growth in Russian agricultural performance over the past 20 years, we found a strong positive effect on yield and gross harvest only for mineral fertilizers. The influence of the other variables is mixed, which is mainly due to data quality and aggregation errors.

Russia owns one-fifth of the world’s forest-covered area but has never been the leader of the global forest sector nor in gross output or relative productivity. The issues of the Russian forest sector have attracted research attention, but for many topics, this is still a green field on the map of sectoral studies. We developed a novel approach to understand the primary causes of the inefficiency of the Russian forest policy through the qualitative assessment of completeness and reliability of forest sector-related data. The main output of this paper is a thorough overview of the available sources of data with an assessment of their quality, completeness and reliability. We show that the Russian official forest sector statistics provide only basic indicators for very short periods with few observations being incomplete and inconsistent. Besides a critical analysis of the official statistics, we also discover some known, but still underemployed, resources of information on the Russian forest sector: textual information of official public bodies and companies, accounting records, remote-sensing data, etc. Finally, we discuss the possible ways to improve the data procurement of the forest sector in Russia to support future decision-making. We are convinced that a prerequisite for the implementation of effective forest policy in Russia is a significant expansion and improvement of the volume and quality of statistics on the dynamics of Russian forests and forest economy. Integration of existing and new data sources is necessary to achieve synergistic effects, both in terms of deepening the understanding of key business processes in the industry and in the sense of solving strategic tasks of its development.

The article considers the prospects of the domestic timber industry in the context of sanctions restrictions. Based on the data on average annual trade flows for 2018—2020, the potential damage from trade restrictions is assessed. Particular attention is paid to the fifth package of EU sanctions, which contains the most severe restrictions on trade with Russia for a wide range of forest commodities. The potential loss of income for the Russian timber industry from the ban on exports to the EU is estimated at 3.5 billion dollars. The ban on imports from the EU countries may also be sensitive for the industry, but it should not be regarded as fatal. The possibilities of partial replacement of the deficit of products for a considerable list of goods are shown. At the same time, the violation of free trade in forest products because of sanctions becomes a new turn in the spiral of the global crisis, which began in the pandemic COVID-19. Consequently, the damage to countries imposing sanctions on Russia is also significant. The most affected will be the largest RF trading partners in Europe — Finland and Germany, as well as the Baltic States. A sharp increase in logging in the EU against the background of the energy crisis creates an additional opportunity for the Russian timber complex. The reciprocal nature of economic losses, as well as multiple examples of circumventing sanctions in other industries, suggest that the most likely scenario will be attempts to maintain trade relations while formally implementing the imposed restrictions.

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.

Dead wood, including coarse woody debris, CWD, and fine woody debris, FWD, plays a substantial role in forest ecosystem functioning. However, the amount and dynamics of dead wood in the forests of Northern Eurasia are poorly understood. The aim of this study was to develop a spatially distributed modelling system (limited to the territories of the former Soviet Union) to assess the amount and structure of dead wood by its components (including snags, logs, stumps, and the dry branches of living trees) based on the most comprehensive database of field measurements to date. The system is intended to be used to assess the dead wood volume and the amount of dead wood in carbon units as part of the carbon budget calculation of forests at different scales. It is presented using multi-dimensional regression equations of dead wood expansion factors (DWEF)—the ratio of the dead wood component volume to the growing stock volume of the stands. The system can be also used for the accounting of dead wood stock and its dynamics in national greenhouse gas inventories and UNFCCC reporting. The system’s accuracy is satisfactory for the average level of disturbance regimes but it may require corrections for regions with accelerated disturbance regimes.