The 10-Point Action Plan to catalyse a Circular Bioeconomy of Wellbeing is a call for collective and integrated action to global leaders, investors, companies, scientists, governments, nongovernmental and intergovernmental organisations, funding agencies and society at large to put the world on a sustainable path. The Plan is guided by new scientific insights and breakthrough technologies from a number of disciplines and sectors. It is articulated around six transformative action points (1–6) and four enabling action points (7–10), which mutually reinforce each other and need to be implemented in an integrated manner.

Contents Authors................................................................................................................................ 7 Acknowledgements............................................................................................................9 Executive summary ........................................................................................................... 11 1. Introduction....................................................................................................................13 Riccardo Valentini, Pekka Leskinen, Pieter Johannes Verkerk, Gert-Jan Nabuurs, George Safonov and Elena Kulikova 2. State of Russian forests and forestry............................................................................17 Dmitry Zamolodchikov, Anatoly Shvidenko, Sergey Bartalev, Elena Kulikova, Alexander Held, Riccardo Valentini and Marcus Lindner 2.1 Major characteristics of Russian forests..........................................................17 2.2 Natural forest disturbances.............................................................................. 21 2.3 Forest governance and use..............................................................................26 2.4 Ecosystem functions and services of Russia’s forests....................................28 2.5 Key challenges in forest resource management..............................................35 2.6 Key messages.................................................................................................... 38 3. Climate change in Russia – past, present and future................................................. 45 Riccardo Valentini, Dmitry Zamolodchikov, Christopher Reyer, Sergio Noce, Monia Santini and Marcus Lindner 3.1 Observed changes of Russian climate in recent decades.............................. 45 3.2 Climate change scenarios................................................................................48 3.3 Key messages.....................................................................................................51 4. Climate change and Russian forests: impacts, vulnerability and adaptation needs... 53 Christopher Reyer, Marcus Lindner, Dmitry Zamolodchikov, Anatoly Shvidenko, Martin Gutsch and Sergey Bartalev 4.1 Observed impacts of climate change...............................................................53 4.2 Projected impacts.............................................................................................56 4.3 Vulnerability assessment................................................................................. 61 4.4 Adaptation needs............................................................................................. 64 4.5 Key messages....................................................................................................67

5. Climate-Smart Forestry in Russia and potential climate change mitigation benefits.............................................................................................................................. 73 Bas Lerink, Mariana Hassegawa, Alexander Kryshen, Anton Kovalev, Eldar Kurbanov, Gert-Jan Nabuurs, Sergei Moshnikov and Pieter Johannes Verkerk 5.1 Introduction...................................................................................................... 73 5.2 Approach and general scenario assumptions.................................................74 5.3 Case study: Republic of Karelia.......................................................................78 5.4 Case study: Republic of Mari El.......................................................................84 5.5 Case study: Angara macro-district (Krasnoyarsk kray).................................. 91 5.6 Concluding remarks, discussion and implications....................................... 98 5.7 Key messages...................................................................................................101 6. The role of the bioeconomy in climate change mitigation in Russia..................... 105 Pekka Leskinen, Jo Van Brusselen, Mariana Hassegawa, Alexander Alekseev, Natalia Lukina, Olga Rakitova, George Safonov, Elena Kulikova and Mikhail Safonov 6.1 Introduction.................................................................................................... 105 6.2 The bioeconomy concept in Russia...............................................................106 6.3 The link between bioeconomy and climate change mitigation.................. 107 6.4 State of Russian forest industry and potential for bioeconomy................... 111 6.5 Sectoral development and outlook................................................................. 113 6.6 Summary and conclusions: Opportunities and challenges for a bioeconomy in Russia.....................................................................................123 6.7 Key messages...................................................................................................125 7. Conclusions.................................................................................................................. 131 Pekka Leskinen, Jo Van Brusselen, Marcus Lindner, Gert-Jan Nabuurs, Pieter Johannes Verkerk, Natalia Lukina, Sergey Bartalev and Elena Kulikova 7.1 Forest resources............................................................................................... 131 7.2 Climate change impacts, adaptation and mitigation....................................132 7.3 Forest management........................................................................................ 133 7.4 Enabling environment for a bioeconomy......................................................134 7.5 Holistic view.................................................................................................... 135 7.6 Key messages and next steps ........................................................................ 136

Understanding the connections between climate change policies and sustainable development is critically important for the implementation of the Paris Agreement and the United Nations Sustainable Development Goals (SDGs). Well-designed climate mitigation policy can lead to significant co-benefits for a range of development priorities, including enhanced energy security and safety and reduced indoor air pollution; however, if not properly managed, mitigation can also lead to trade-offs. Maximizing synergies and avoiding trade-offs thus requires an integrated strategy based on a new generation of technological and socio-economic pathways that includes climate-resilient adaptation strategies. Over the last four years, CD-LINKS brought together an international team of interdisciplinary researchers with both global and national expertise. Funded by the Horizon 2020 programme of the European Union, the project applied cutting-edge scientific tools and models to explore the linkages between climate policies and sustainable development. Major achievements of the project include the development of globally consistent national low-carbon development pathways, and the formation of a research network and capacity building platform to leverage knowledge exchange among institutions. The project also improved understanding of the linkages between climate change policies and multiple sustainable development objectives and greatly enhanced the existing evidence base on policy effectiveness. A particular asset of the project are the insights related to policy designs that adequately account for mitigation trade-offs across sectors, actors, and objectives. We invite you to learn more about this ground-breaking work in the pages that follow.

Genomic selection is routinely used worldwide in agricultural breeding. However, in Russia, it is still not used to its full potential partially due to high genotyping costs. The use of genotypes imputed from the low-density chips (LD-chip) provides a valuable opportunity for reducing the genotyping costs. Pork production in Russia is based on the conventional 3-tier pyramid involving 3 breeds; therefore, the best option would be the development of a single LD-chip that could be used for all of them. Here, we for the first time have analyzed genomic variability in 3 breeds of Russian pigs, namely, Landrace, Duroc, and Large White and generated the LD-chip that can be used in pig breeding with the negligible loss in genotyping quality. We have demonstrated that out of the 3 methods commonly used for LD-chip construction, the block method shows the best results. The imputation quality depends strongly on the presence of close ancestors in the reference population. We have demonstrated that for the animals with both parents genotyped using high-density panels high-quality genotypes (allelic discordance rate < 0.05) could be obtained using a 300 single nucleotide polymorphism (SNP) chip, while in the absence of genotyped ancestors at least 2,000 SNP markers are required. We have shown that imputation quality varies between chromosomes, and it is lower near the chromosome ends and drops with the increase in minor allele frequency. Imputation quality of the individual SNPs correlated well across breeds. Using the same LD-chip, we were able to obtain comparable imputation quality in all 3 breeds, so it may be suggested that a single chip could be used for all of them. Our findings also suggest that the presence of markers with extremely low imputation quality is likely to be explained by wrong mapping of the markers to the chromosomal positions

The Paris Agreement invited Parties to develop low-emission development strategies. This study presents national low-emission scenarios to inform such strategies for Australia, Brazil, Canada, China, EU-28, India, Indonesia, Japan, Republic of Korea, Russia and the USA. We use country-level technology-rich energy-economy and integrated assessment models that include detailed representations of the energy, transport and land systems and provide insights on emissions, energy system and economic implications of low-emission pathways until 2050. We show that the low-emission pathways of most economies studied here are consistent with pathways limiting global temperature increase to well-below 2 °C, while emission reductions are achieved through uptake of renewable energy, energy efficiency improvements and electrification of energy services. The role of mitigation options like nuclear, carbon capture and storage (CCS) and advanced biofuels is differentiates across countries, depending on national priorities, specificities and resource endowments. The energy system transformation requires a pronounced reallocation of investments towards low-carbon technologies, but without raising significant affordability issues in most countries. National pathways improve the consistency between country policy plans with global temperature goals and capture structural heterogeneities and broad socio-economic considerations.

The concept of “blue growth,” which aims to promote the growth of ocean economies while holistically managing marine socioecological systems, is emerging within national and international marine policy. The concept is often promoted as being novel; however, we show that historical analogies exist that can provide insights for contemporary planning and implementation of blue growth. Using a case-study approach based on expert knowledge, we identified 20 historical fisheries or aquaculture examples from 13 countries, spanning the last 40–800 years, that we contend embody blue growth concepts. This is the first time, to our knowledge, that blue growth has been investigated across such broad spatial and temporal scales. The past societies managed to balance exploitation with equitable access, ecological integrity and/or economic growth for varying periods of time. Four main trajectories existed that led to the success or failure of blue growth. Success was linked to equitable rather than open access, innovation and management that was responsive, holistic and based on scientific knowledge and monitoring. The inability to achieve or maintain blue growth resulted from failures to address limits to industry growth and/or anticipate the impacts of adverse extrinsic events and drivers (e.g. changes in international markets, war), the prioritization of short-term gains over long-term sustainability, and loss of supporting systems. Fourteen cross-cutting lessons and 10 recommendations were derived that can improve understanding and implementation of blue growth. Despite the contemporary literature broadly supporting our findings, these recommendations are not adequately addressed by agendas seeking to realize blue growth.

Despite harsh natural conditions and remoteness, farming is spread worldwide on Arctic margins. Russia is the leading country by area under agricultural use of the circumpolar territories. Agricultural activities in the northern regions vary from traditional ones such as semi‐nomadic reindeer breeding to technologically smart urban agriculture. These activities are geographically unequally represented, which causes significant regional differences in productivity of agricultural land and labour. Comparative analysis of these basic variables enables us to identify specific patterns of modern agricultural development and their dynamics in northern regions of Russia, comparing them with Northern European countries and North America.

The objective of this work is to analyze the impact of seasonality on the socio-economic development of rural areas of the southern part of Karelia. This study is based on the field data obtained via semi-structured indepth interviews with experts from the local community. The results show that the influence of seasonality is rather indirect, being a constituent of other factors: economic, infrastructural, institutional, social, etc. Although seasonality is most often perceived as a negative phenomenon regarding socio-economic development, modern types of economic activity characterized by a peak of activity in different seasons of the year mitigate the effect of seasonality and even benefit from being seasonal. Based on the materials collected, a typology of rural settlements of the souther npart of Karelia based on the nature of the effect of seasonality has been developed (with a predominantly positive and predominantly negative effect).

Russia is one of the largest carbon emitters in the world, possessing huge resources of both fossil fuels and zero-carbon energy sources. The Paris Agreement targets require substantial efforts to limit global warming to “well below 2 °C”. Energy-economic modeling provides sound conclusions that continuation of existing energy and climate policy will lead to stabilization of energy carbon emissions in Russia at the current level in 2010–2050 (about 30% below 1990). Stronger mitigation policies could gradually reduce domestic energy CO2 emissions by 61% from 2010 to 2050 (75% below 1990). Deep decarbonization policies with even more ambitious commitments could ensure an 83% reduction in energy CO2 emissions from 2010 levels (88% below 1990) by 2050. All key sectors (energy, industries, transport, and buildings) can play a substantial role in decarbonizing the national economy. However Russia’s historical reliance on domestic consumption and exports of fossil fuels creates strong barriers to decarbonization. Emission reduction costs are expected to be below 29 USD/tCO2 by 2030, 55 USD/ tCO2 by 2040, and 82 USD/tCO2 by 2050 in the most ambitious decarbonization scenario. The results of this study provide insights into how Russia can enhance its ambitions to implement the Paris Agreement and contribute to global efforts toward building a climate-neutral economy by 2050.

In the last 50 years, the biosphere, upon which humanity depends, has been altered to an unparalleled degree. The current economic model relying on fossil resources and addicted to “growth at all costs” is putting at risk not only life on our planet, but also the world’s economy. The need to react to the unprecedented COVID-19 crisis is a unique opportunity to transition towards a sustainable wellbeing economy centered around people and nature. After all, deforestation, biodiversity loss and landscape fragmentation have been identified as key processes enabling direct transmission of zoonotic infectious diseases. Likewise, a changing climate has profound implications for human health. Putting forward a new economic model requires transformative policies, purposeful innovation, access to finance, risk-taking capacity as well as new and sustainable business models and markets. But above all we need to address the past failure of our economy to value nature, because our health and wellbeing fundamentally depends on it. A circular bioeconomy offers a conceptual framework for using renewable natural capital to holistically transform and manage our land, food, health and industrial systems with the goal of achieving sustainable wellbeing in harmony with nature. Within the framework of the Sustainable Markets Initiative, under the leadership of His Royal Highness The Prince of Wales, a 10-Point Action Plan to create a circular bioeconomy is proposed below. The Action Plan is a response to The Prince of Wales’ call to invest in nature as the true engine for our economy. The Action Plan, guided by new scientific insights and breakthrough technologies, is articulated around six transformative action points further discussed below and four enabling action points, which mutually reinforce each other.

An age-structured bioeconomic model, which is completely continuous in age and time, is developed in order to compare with traditional discrete models. Both types have advantages and disadvantages. The continuous framework complements discrete models as it allows for deeper and more transparent analytical study and leads to analytical results that would be difficult to achieve within a discrete framework. To make the model realistic, a nonlinear recruitment function is introduced and steady state solutions and constant-effort optimal fishing are studied analytically. In addition, the framework has been used for numerical analysis. Simulations are used to investigate how optimal harvesting patterns vary with parameter values.

Russia's agriculture produces around 3.7 per cent of the country's GDP, employs 9.2 per cent of the national workforce and contributes around 6 per cent of the country's exports. The sector has shown remarkable resilience in the face of wider economic turbulence. Self‐sufficiency rates for the main agricultural commodities are relatively high. Agricultural exports have grown very significantly since 2000 especially for wheat and meslin (wheat and rye mixture). Meat production has been growing steadily, particularly in the poultry and pork sectors. Whilst the agri‐food sector has great potential to play an even more prominent role in Russia's economy, it suffers from relatively low productivity and an outdated technological base. The main drive for efficiency has come mainly from the relatively large‐scale agricultural firms, who generated more than half of the total value of agricultural output in 2016. Foreign policy instability, including economic sanctions, the devaluation of the national currency and declining economic growth have weakened the sector and caused an increase in the prices of imported goods and equipment. At the same time Russian products have replaced high value‐added imports and Russia's agricultural producers are expanding into new markets.