Groisman et al. Progress in Earth and Planetary Science (2017) 4:41
DOI 10.1186/s40645-017-0154-5

Progress in Earth andPlanetary Science

REVIEW

Open AccessNorthern Eurasia Future Initiative (NEFI):
facing the challenges and pathways ofglobal change in the twenty-first century
Pavel Groisman1,9,30* , Herman Shugart2, David Kicklighter3, Geoffrey Henebry4, Nadezhda Tchebakova5,
Shamil Maksyutov6, Erwan Monier7, Garik Gutman8, Sergey Gulev9, Jiaguo Qi10,19, Alexander Prishchepov11,31,
Elena Kukavskaya5, Boris Porfiriev12, Alexander Shiklomanov13, Tatiana Loboda14, Nikolay Shiklomanov15,
Son Nghiem16, Kathleen Bergen17, Jana Albrechtová18, Jiquan Chen10,19, Maria Shahgedanova20,
Anatoly Shvidenko21, Nina Speranskaya22, Amber Soja23, Kirsten de Beurs24, Olga Bulygina25, Jessica McCarty26,27,
Qianlai Zhuang28 and Olga Zolina29

Abstract
During the past several decades, the Earth system has changed significantly, especially across NorthernEurasia. Changes in the socio-economic conditions of the larger countries in the region have also resulted ina variety of regional environmental changes that can have global consequences. The Northern Eurasia Future
Initiative (NEFI) has been designed as an essential continuation of the Northern Eurasia Earth Science
Partnership Initiative (NEESPI), which was launched in 2004. NEESPI sought to elucidate all aspects of ongoingenvironmental change, to inform societies and, thus, to better prepare societies for future developments. A
key principle of NEFI is that these developments must now be secured through science-based strategies codesigned with regional decision-makers to lead their societies to prosperity in the face of environmental andinstitutional challenges. NEESPI scientific research, data, and models have created a solid knowledge base tosupport the NEFI program. This paper presents the NEFI research vision consensus based on that knowledge.
It provides the reader with samples of recent accomplishments in regional studies and formulates new NEFI
science questions. To address these questions, nine research foci are identified and their selections are briefly
justified. These foci include warming of the Arctic; changing frequency, pattern, and intensity of extreme andinclement environmental conditions; retreat of the cryosphere; changes in terrestrial water cycles; changes inthe biosphere; pressures on land use; changes in infrastructure; societal actions in response to environmental
change; and quantification of Northern Eurasia’s role in the global Earth system. Powerful feedbacks between
the Earth and human systems in Northern Eurasia (e.g., mega-fires, droughts, depletion of the cryosphereessential for water supply, retreat of sea ice) result from past and current human activities (e.g., large-scalewater withdrawals, land use, and governance change) and potentially restrict or provide new opportunities for
future human activities. Therefore, we propose that integrated assessment models are needed as the final
stage of global change assessment. The overarching goal of this NEFI modeling effort will enable evaluation(Continued on next page)* Correspondence: Pasha.Groisman@noaa.gov
1
NEESPI Project Scientist, NC State University Research Scholar, at at NOAA
National Centers for Environment Information, Federal Building, 151 Patton
Avenue, Asheville, NC 28801, USA
9P.P. Shirshov Institute of Oceanology, RAS, 36 Nakhimovsky Ave, 117218
Moscow, Russia
Full list of author information is available at the end of the article© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made.

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

Page 2 of 48(Continued from previous page)of economic decisions in response to changing environmental conditions and justification of mitigation andadaptation efforts.
Keywords: Environmental changes, Northern Eurasia, Ecosystems dynamics, Terrestrial water cycle, Cryosphereretreat, Extreme and inclement environmental conditions, Sustainable development, Land cover and land usechange, Integrated assessment models for decision-makers

Introduction
Northern Eurasia Future Initiative (NEFI) was conceived at the Workshop “Ten years of Northern Eurasia
Earth Science Partnership Initiative (NEESPI): Synthesis
and Future Plans” hosted by Charles University in
Prague, Czech Republic (April 9–12, 2015). That event
was attended by more than 70 participants from Japan,
China, Russia, Ukraine, Kyrgyzstan, Kazakhstan, theEuropean Union, and the USA. The workshop included
an overview, synthesis presentations, and scientific visions for NEESPI in its transition to NEFI. These results (http://neespi.org/web-content/PragueWorkshop
SynthesisBriefing.pdf ) were delivered at a dedicatedopen public Splinter Meeting at the European Geophysical Union Assembly in Vienna, Austria (16 April2015). On 20 May 2016, a NEFI White Paper was released for public consideration on the NEESPI website
and 4 months later, after accounting for numerous
comments and recommendations, it was finalized andposted at http://nefi-neespi.org/. The current paper
presents the consensus of the future NEFI vision to address the challenges facing the region and to develop
pathways to mitigate future problematic changes.
During the past 12 years, NEESPI has been quite successful at conducting and advancing research within its
large geographical domain of Northern Eurasia (Fig. 1;
Groisman and Bartalev 2007). The NEFI research domain is the same. The NEESPI program accommodated
172 projects focused on different environmental issues
in Northern Eurasia. More than 1500 peer-reviewed
journal papers and 40 books were published during thepast decade (http://nefi-neespi.org/science/publicati
ons.html; Groisman et al. 2009, 2014; Groisman and Soja
2009). Several overview books further synthesized findings (Gutman and Reissell 2011; Groisman and Lyalko
2012; Groisman and Gutman 2013; Chen et al. 2013;
Gutman and Radeloff 2016). While the initial durationof the NEESPI research program was estimated to be
10-12 years, its momentum has exceeded original expectations. In addition to accumulating knowledge and publishing scientific journal papers and books, NEESPI
scientists developed new observations, datasets, data
networks, tools, and models. As a result, a new research
realm emerged for studies in Northern Eurasia, and weare now poised to apply these results to directly support

decision-making for various coupled environmentalsocietal needs.
The past accomplishments are not the only driver forthe proposed NEFI initiative. Just as, or perhaps evenmore importantly, NEFI will address two significant andintertwined changes that have emerged. These are (1)continued and exacerbated change in the global Earthand climate system, and (2) societal change and stresswith a heightened need for mitigation and adaptation
approaches. With respect to the first, the global Earthsystem has significantly changed, with the changes inNorthern Eurasia being substantially larger than the global average (cf., Figs. 2 and 3). Subsequently, one NEFI
endeavor is to analyze this new state with its unexpectednovel features and distributions. These novel characteristics include shifts of the seasonal cycle for various climatic functions to changes in intensity, frequency, andspatial patterns and temporal trends of extreme events.
These changes have already occurred, but their impactson (and feedbacks to) atmospheric, biospheric, cryospheric, hydrologic, oceanic, and macro-socioeconomic
processes are ongoing.
The second significant change that NEFI will need toaddress concerns the socio-economic dynamics in the
major nations of Northern Eurasia. These dynamics havealso dramatically changed, including the ability of societies
to withstand and adapt to the adverse manifestations of
the above-described environmental changes. Fundamental
to addressing this is the sound scientific understandingand quantification of the amount of Earth system changethat societies are currently experiencing and may experience by the end of the twenty-first century. However, in
addition to understanding the scientific basis, communities (and even nations) have increasingly begun to inquire
about what mitigation and/or adaptation strategies are
possible for the upcoming decades. These types of questions need to be addressed differently, because societal
decision-making impacts the environment, which feeds
back to influence future societal decision-making. The
major anthropogenic causes of global change remain ongoing. Thus, the Earth science community and society ingeneral will need to be informed and prepared to assure asustainable future.
The results of scientific research, data, and models accumulated during the past decade will allow us to build upon

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

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Fig. 1 The NEESPI study area is loosely defined as the region between 15° E in the west, the Pacific Coast in the east, 40° N in the south, and the Arctic
Ocean coastal zone in the north. On this map, green corresponds to vegetated lands. Light brown and yellow indicate sparse vegetation and arid areas,
respectively (Groisman et al. 2009). Major cities within the NEESPI domain and their names are shown by red dots and text in white inserts, respectively.
During the NEESPI studies, we expand the study domain occasionally to address the ecosystem in its entirety beyond the strict lat/long boundaries(e.g., taiga and tundra zones in Fennoscandia or barren and semi-desert areas in China. The Dry Land Belt of Northern Eurasia is sketched on the map by adashed white line

Fig. 2 Global annual surface air temperature anomalies (°C) derived from the meteorological station data for the 1957–2016 period (Lugina et al. 2006,
updated). This time series is based upon the land-based surface air temperature station data with a processing algorithm developed 25 years ago by
Vinnikov et al. (1990). The reference period used for calculations of anomalies is 1951–1975. Dotted ovals in the figure show this reference period, the
new state of the global Earth system (+ 0.3° to 0.4 °C of the global temperature) with shift during the late 1970s and early 1980s, that manifested itself inbiospheric, oceanic, cryospheric, and atmospheric variables around the world (Reid et al. 2016), and the last period (since circa 2001), when impacts on the
Earth system (e.g., retreat of the cryosphere, Arctic warming, increasing dryness of interior of the continents) still need to be completely documented

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

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Fig. 3 Seasonal temperature anomalies over Northern Eurasia (the NEESPI study domain) for the 1881–2016 period. The reference period used for
calculations of anomalies is 1951–1975. The annual anomaly for 2016 is + 2.0 °C. Linear trend estimates shown by dash lines are provided fordemonstration purposes only. Data source: archive of Lugina et al. (2006 updated)

this knowledge to directly support decision-making activities that address societal needs in Northern Eurasia. During the last decade, substantial climatic and environmental
changes have already been quantified. While natural processes (except the high amplitude of their variations) aremainly the same as in other parts of the World, human factors and changes in land cover and land use in the NEFI
domain during the past decades were dramatic and unique.
Changes in the socio-economics of major nations in the region have ultimately transformed human-environment interactions. This in turn has transformed regional land
cover and water resources towards conditions that endanger or even overcome the resilience of natural ecosystems(e.g., disappearing lakes and runoff diversions, deforestation, degradation and abandonment of agriculture fields
and pasture; air, soil, and water pollution). These and projected changes will require expeditious direct responses onbehalf of human well-being and societal health in order tomove towards a sustainable future.
Therefore, the core motivation of NEFI is to best use
science to serve the decision-making process to maintain
Earth system health and to sustain society. In the next
two sections, we: Formulate three major science questions of global

concern associated with unique features ofNorthern Eurasia,
 Formulate the major research foci for the next
decade that, as the NEFI Science Plan authors
believe, are of crucial importance to be addressed
expediently, and Examine and justify the issues related to theseresearch foci in more detail.
An approach to regional studies in Northern Eurasia
based on integrated assessment modeling is describedand justified in the last section of the paper. Because thispaper is an overview of a large amount of relevant findings from the past decade, we also provide a comprehensive list of references to those works.

ReviewThree unique features of Northern Eurasia of global
concern and their related major science questions

To develop effective mitigation and adaptation strategies, future NEFI activities will need to consider threeunique features of Northern Eurasia: (1) the sensitivity

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

of land surface characteristics to global change that feedback to influence the global energy budget; (2) potentialchanges in the Dry Land Belt of Northern Eurasia (DLB)
that will have a large influence on the availability ofwater for food, energy, industry, and transportation; and(3) evolving social institutions and economies. Below, welook at these features in more detail and suggest thatthree major science questions emerge from thisexamination.
Sensitivity of land surface characteristics to global change

The Arctic, Arctic Ocean shelf, and the boreal Zone ofEurasia are areas of substantial terrestrial carbon storage
in wetlands, soil, boreal forest, terrestrial, and sea shelfpermafrost. From these emerge powerful carboncryosphere interactions and variability that intertwine
with strong climatic and environmental changes (Fig. 4).
These interactions also can generate positive feedback to
Earth system changes via both biogeochemical (atmospheric composition, water quality, plant, and microbial
metabolism) and biogeophysical impacts (surface albedo,
fresh water budget, and thermohaline circulation of theWorld Ocean). These intertwined linkages and feedbacks
may increase the rate of global (or near-global) change
and/or increase uncertainties about that change. In turn,this places the wellbeing of societies at risk if planned
mitigation and adaptation measures are not implemented in a sound and timely fashion.
Thus, in future studies within Northern Eurasia, special attention should be paid to the changes on the volatile boundaries of the Arctic, boreal, and dry zones. The
highly variable components of the cryosphere (seasonal
snow cover) which are vitally controlled by componentsthat have been systematically changing (e.g., glaciers andpermafrost) should be recognized. The rates of change
due to catastrophic forest fires (Conard et al. 2002;
Goldammer 2013), dust storms (Goudie and Middleton
1992; Sokolik 2013), and controversial future methane
release from frozen ground in high latitudinal land andshelf areas (Kirschke et al. 2013; Shakhova et al. 2013,2015; Zhu et al. 2013; Ruppel and Kessler 2017) must be
accounted for or ameliorated.
Based on the above, the first Major Science Question
is “How can we quantify and project ecosystem dynamics in Northern Eurasia that influence the global energy
budget when these dynamics are internally unstable (e.g.,
operate within narrow temperature ranges), are interrelated and have the potential to impact the global Earthsystem with unprecedented rates of change?”
Water availability and the dry land belt of Northern Eurasia

The interior of the Earth’s largest continent is mostly cut
off from water vapor transport from the tropics bymountain ridges and plateaus spread across the central

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regions of Asia, thus creating the Dry Land Belt ofNorthern Eurasia (DLB; Fig. 1). The DLB is the largest
dry area in the extratropics and may be expanding
northward (Shuman et al. 2015; Fig. 4) as it has done inpast millennia (Chen et al. 2008, 2010; Kozharinov andBorisov 2013). Parts of the DLB are quite densely populated (e.g., Northern China, Central Asia) and havefertile land. For example, the Pannonian Lowland andthe black soils in Ukraine and European Russia provide
substantial grain export to the global market.
However, the DLB has strong physical limitations in
the production of crops. It has a very limited fresh watersupply, which is highly dependent upon irregular extratropical cyclones (mostly from the North Atlantic) and ashrinking regional cryosphere. Increases in evapotranspiration arising from increases in warm season temperatures and expansions of the growing season in the DLB
are generally not compensated by precipitation increase.
Further, changes in the spatio-temporal shifts inprecipitation pattern increase the probability of various
unusual or extreme events affecting the livelihoods of regional societies and their interactions with the global
economy (e.g., Henebry et al. 2013; Chen et al. 2015).
This region is a source of dust storms that can adversely
impact the environment, climate, and human well-being(Darmenova et al. 2009).
Arising from these considerations, the second Major
Science Question is “What are the major drivers of theongoing and future changes in the water cycles within
the regions of Northern Eurasia with insufficient water
resources (i.e., DLB and its vicinity)?” In addressing thisquestion, future studies should examine how changes in
the water cycle will affect regional ecosystems and societies, and how these changes will feedback to the Earthsystem and the global economy.
Evolving social institutions and economies

Institutional changes in Northern Eurasia that havetaken place over the past few decades have led to largechanges in the socio-economic fabric of the societies in
the region, affecting land use and the natural environment (cf., Lerman et al. 2004). One overarching challenge has been the transition from command-driven to“transitional” and more market-driven economics in the
countries of Northern Eurasia. This phenomenon has
occurred at different rates, with differing levels of success, and often with societal costs. This has created unexpected economic and environmental problems but
also opportunities (Bergen et al. 2013; Gutman andRadeloff 2016). Environmental changes and their related
problems include massive agricultural land abandonment (Alcantara et al. 2013; Griffiths et al. 2013; Wrightet al. 2012), inefficient and illegal forest logging(Kuemmerle et al. 2009; Knorn et al. 2012; Newell andGroisman et al. Progress in Earth and Planetary Science (2017) 4:41

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Fig. 4 Vegetation distribution under present climate conditions and equilibrium vegetation distribution under future climate conditions (scenarios)
over Northern Eurasia in current climate and by the year 2090 as calculated by the RuBCliM ecosystem model (developed by modifying the SibCliM
ecosystem models, Tchebakova et al. 2009, 2010, 2016) using an ensemble of Canadian (CGCM3.1), UK (HadCM3), and French (IPCLCM4) GCM outputs
for the B1 and A2 scenarios for the IPCC Fourth Assessment Report (Core Writing Team 2007), where greenhouse gases induced global warming of
3–5 °C and 6–8 °C, respectively, by 2090 (Tchebakova et al. 2016)

Simeone 2014), degradation of cultivated and pasturelands (Ioffe et al. 2012; Chen et al. 2015, 2015), growing
water deficits and drought (especially in the DLB and

new independent states), and the spread of humaninduced fires (Soja et al. 2007; McCarty et al. 2017).
Many of these outcomes have become important

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

concerns with policy implications at the national andintergovernmental levels. Opportunities emerge mostly
with advances of warmer climate conditions northward(agriculture benefits at high latitudes, better transportation conditions in the Arctic Seas; Tchebakova et al.
2011). Other opportunities are institutional, such as cooperation between nations and non-profit organizationsin attempting to implement forestry certification.
Furthermore, the countries of Northern Eurasia withthese “transitional” economies are playing an increasingly important role in the world economic system.
Thus, they face further challenges in highly competitive
economic conditions under the additional stresses ofclimatic, environmental, and internal societal change.
For countries and/or regions with resource-rich lands
and low population (e.g., Russia, Kazakhstan, Mongolia,
and Turkmenistan), their development continues to depend on natural resources inclusive especially of timber,
oil/gas, mining, fisheries, agriculture, and hydropower(Bergen et al. 2013). Other countries (e.g., China andJapan) with very large populations and strained or limited resources (such as available domestic timber in
China or Japan) may be strong consumers of natural resources from elsewhere in Northern Eurasia (Newell andSimeone 2014).
Considering the triad “climate – environmental –socio-economic impacts,” past NEESPI investigations
sufficiently embraced regional climate diagnostics and,to a somewhat lesser extent, diagnostics of environmental and ecosystem characteristics. However, the socioeconomic impacts of variability and/or systematicchanges in climate and environmental variables are still
poorly defined. This makes it difficult to effectively planfor the future or to accurately interpret prospective actions based on existing model experiments. Thesemodel-based projections of climate and environmental
changes still have to be attributed to and associated withthe mid-term and long-term strategies for the development of different sectors of the economy including agriculture and grazing, forestry, fisheries, mining, energy,
and on-shore and off-shore infrastructure development.
This will be an important NEFI endeavor.
The third Major Science Question is “How can thesustainable development of societies of NorthernEurasia be secured in the near future (the next few decades)? In addressing this question, future studies
should examine how societies can overcome the “transitional” nature of their economic, environmental, andclimatic change challenges, and resolve counterproductive institutional legacies.
Major research foci: why do they matter?

During the preparation and review of the NEFI Science
Plan, the directions of future research over Northern

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Eurasia have been analyzed in light of the new information gained from past NEESPI activities, the apparent
need to advance further in these directions addressing
the latest dynamics of environmental and socioeconomic changes, and the unique features of NorthernEurasia that are of global concern. Nine major researchfoci have been identified as NEFI priorities (listed in no
specific order):1. Influence of global change, with a focus on warmingin the Arctic;
2. Increasing frequency and intensity of extremes(e.g., intense rains, floods, droughts, wildfires) andchanges in the spatial and temporal distributions ofinclement weather conditions (e.g., heavy wet
snowfalls, freezing rains, untimely thaws, and peakstreamflow);
3. Retreat of the cryosphere (snow cover, sea ice,
glaciers, and permafrost);
4. Changes in the terrestrial water cycle (quantity andquality of water supply available for societal needs);
5. Changes in the biosphere (e.g., ecosystem shifts,
changes in the carbon cycle, phenology, land-coverdegradation and dust storms);
6. Pressures on agriculture and pastoral production(growing supply and demand, changes in land use,water available for irrigation, and food-energy-water
security);
7. Changes in infrastructure (roads, new routes,
construction codes, pipelines, risks with permafrost
thawing, air, water, and soil pollution);
8. Societal adaptations and actions to mitigate thenegative consequences of environmental changes
and benefit from the positive consequences; and9. Quantification of the role of Northern Eurasia in the
global Earth and socioeconomic systems to advanceresearch tools with an emphasis on observations andmodels.
Socio-economic research challenges are the top priority for several of these foci. These challenges have notbeen overlooked in the past but have not been addressedsatisfactorily in the NEESPI domain, nor indeed globally.
The introduction of the Future Earth research objectives
is a response to this gap (http://www.futureearth.org/).
There is an urgent need to incorporate socio-economic
studies into regional programs by linking the findings ofdiagnostic and model-based climate and environmental
analyses with the requirements for the regional infrastructure, which arise from the detailed treatment ofsocio-economic conditions.
We are establishing this strategy as the foundation for
the Northern Eurasia Future Initiative (NEFI) and expectthat it will bridge climate and environmental studies

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

with the economic consequences of the observedchanges. This will spur advances in physical sciences tobetter quantify observed and projected climate and environmental changes and improve economic analyses ofimpacts. This new strategy will directly benefit many
stakeholders and end-users. It will provide them withrecommendations and assessments going far beyond
those based exclusively on the analysis of climate andenvironmental variables. It will also provide them with a
new suite of modeling tools and new data sets to enablemuch better and smarter decision-making. Furthermore,this strategy will provide a strong feedback on further
planning of climate and environmental studies, pointing
to the parameters, phenomena, and mechanisms which,so far, have not been studied and quantified to a full extent. This will make it possible to revisit and comprehensively review the 12-year NEESPI legacy in order totransform conventional climate and environmental metrics to those relevant for building more effective economic strategies and risk assessments.
Below, we examine and justify the issues related tothe above nine major research foci in more detail,and in the final section propose an integrated assessment modeling approach that would allow NEFI toeventually address them as best as current technology
and knowledge will support.

Research focus 1: global change and the Arctic

Global changes are ongoing and until the causes of thesechanges are eliminated or mitigated, there are no expectations that they will slow down (Intergovernmental
Panel on Climate Change (IPCC) 2014; Barros et al.
2014; Karl et al. 2015; see also Fig. 2). Regionally, thetemperature changes in Northern Eurasia have beenamong the largest (Blunden and Arndt 2015, 2016).
Additionally, there are special reasons to list the changes
in the Arctic among major concerns for future environmental well-being in the extratropics. This small sliverof the globe (the zone north of 60° N occupies only 7%of the globe surface) plays an important role in the

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global climate. Its air temperature changes during thepast decade were unprecedented for the period of instrumental observations (Fig. 5, left) and well above the 2 °C
warming threshold set by the recent United Nations
Climate Change Conference (30 November–12 December
2015, Paris, France).
There are two major consequences of Arctic warming:(a) changes in the Arctic sea ice and (b) changes in themeridional gradient of air temperature. The Arctic has
become increasingly closely interlinked with the polar
atmosphere with the ongoing retreat and thinning of thesea ice (Fig. 5, right; Renner et al. 2014). The depletionof sea ice increases the heat and water vapor exchangewith the atmosphere, especially during the cold season(i.e., from mid-September through early June), affecting
weather, climate, and the water cycle across the extratropics and, possibly, over the entire hemisphere (Drozdov
1966; Newson 1973; Groisman et al. 2003, 2013; Arctic
Climate Impact Assessment 2005; AMAP 2011; Bulygina
et al. 2013). There are direct practical implications fortransportation, regional infrastructure development andmaintenance, and fisheries (AMAP 2011; Farré et al.
2014; Strategic Assessment of Development of the Arctic
2014; Streletskiy et al. 2015).
The Arctic is closely interlinked with the North Atlantic
Ocean. Together they control the World Ocean
thermohaline circulation, which provide most of thecold water influx into the deep ocean. They define theclimate of the northern extratropics (especially the regions adjacent to the North Atlantic) due to intense
meridional heat and mass exchange of the atmospherewith the ocean in the Atlantic Sector of the Arctic andthe subsequent transport of air masses inside the continents. This exchange is modulated by variations of the
Arctic Oscillation, a large-scale mode of climate variability, also referred to as the Northern Hemisphere annular mode (Thompson and Wallace 1998). All
together, they create strong deviations from the zonal
temperature distribution (for example, compare theclimate of Edinburgh, Scotland, UK with Churchill,
Canada, and Yakutsk, Russia) and are highly volatile.

Fig. 5 Left: annual surface air temperature anomalies (°C) area-averaged over the 60° N–90° N latitudinal zone (Lugina et al. 2006, updated). Right: September
Arctic sea ice extent, SIE, 106 km2 (US National Snow and Ice Data Center, Boulder, CO, USA website, http://nsidc.org/data; date of retrieval; 30 December2015). For possible change in 2016, see Gannon (2016). Linear trend estimates shown by dash lines are provided for demonstration purposes onlyGroisman et al. Progress in Earth and Planetary Science (2017) 4:41

Relatively small deviations of the oceanic salinity andsea ice distribution in the northernmost Atlantic may
affect the deep water formation process with adverse
globalconsequencesfor
oceanic
circulation(Gulfstream) and climate of the extratropics (LeGrande
et al. 2006). The ongoing decrease of the meridionaltemperature gradient in the cold season (Groisman andSoja 2009) may weaken westerlies, causing cold winteroutbreaks in the interior of the continent, larger
meandering of the cyclone trajectories over the extratropics (Francis and Vavrus 2012), and increasing probability of blocking events (Lupo et al. 1997; Semenov
2012; Mokhov et al. 2013; Schubert et al. 2014) thatcan devastate regional agriculture through the combination of harsh winters and summer heatwaves (Wrightet al. 2014).
Research focus 2: frequency and intensity of extremes

There is already evidence of climate-induced change
across Northern Eurasia during the past few decades(Soja et al. 2007; Groisman and Gutman 2013; Rimkus
et al. 2013; Shvidenko and Schepaschenko 2013;
Valendik et al. 2014) with southern regions being particularly vulnerable to climate change and fires(Malevsky-Malevich et al. 2008). First, there has been an
increase in rainfall intensity and prolonged no-rain periods (summarized in Groisman et al. 2013; see also Zhai
et al. 2004 and Chen and Zhai 2014), which at times
may occur in the same region. Second, an increase in
extraordinary temperature anomalies has been accompanied by summer droughts (Barriopedro et al. 2011; Lei
2011; Lupo et al. 2012; Bastos et al. 2014; Horion et al.
2016). Third, cold outbreaks and/or thaws haveincreased during winter (Arctic Climate Impact Assessment 2005; Groisman et al. 2016). Fourth, an increase in
the frequency of large and severe wildfires has occurred(Conard et al. 2002; Soja et al. 2007; Kukavskaya et al.
2013; Shvidenko and Schepaschenko 2013). Finally, intense dust storms have occurred (Xi and Sokolik 2015a).
Official Russian statistics on “dangerous meteorologicalphenomena” (DMP), which are events that caused significant damage to the national economy and vital activities of the population, report that seven years of the last
decade (2006–2015) had the largest numbers of DMP(from 385 to 467). The impacts of these events often extend far beyond Northern Eurasia, sending aftershocks
into global markets and raising concerns about global
food security (Loboda et al. 2016).
There are also changes in the spatial and temporal distribution of inclement weather conditions (e.g., heavy
wet snowfalls, freezing rains, rain on snow, untimely
thaws and peak streamflow) that, while not being extremes per se, substantially affect societal well-being andhealth (e.g., freezing events, Bulygina et al. 2015;

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Groisman et al. 2016) or indirectly impact the regional
water budget (e.g., the influence of winter thaws and/or
early snowmelt on the water deficit of the following
growing season, Bulygina et al. 2009, 2011; Groisman
and Soja 2009). Societal consequences of changes in thefrequency and intensity of these extreme and inclement
events have become an urgent task to address for theentire Earth Science research community (Forbes et al.
2016). In this regard, it is not enough to report and/or
to project changes in characteristics of these events but
also to develop a suite of strategies for resilient responses to new climate conditions that are forthcoming
and/or have an increased higher probability than waspreviously expected.
Extreme events that affect the biosphere and theirtemporal and spatial changes represent a special focus
for NEFI studies. Wildland fire is the dominant disturbance agent in the boreal forests, which are in turn thelargest global reservoir of terrestrial carbon (Pan et al.
2011; Parham et al. 2014; Gauthier et al. 2015). While
fire plays a critical role in maintaining the overall forest
well-being through regulating ecosystem functioning,productivity, and health, extreme fire events and changing fire regimes intensify the impacts of climate change
and variability on ecosystem states and deliver a suite of
powerful feedbacks to the climate system. These events
heighten the interactions among the biosphere, atmosphere, and climate systems by affecting carbon balances,hydrologic regimes, permafrost structure, modifying patterns of clouds and precipitation, and radiative forcing
by changing surface and planetary albedo (Rogers et al.
2015). Wildfires, in general and particularly during extreme events, also have a direct adverse impact on human health, pose a considerable threat to life andproperty, and impose a substantial economic burden.
A typical feature of the current fire regime is increasing
frequency and severity of mega-fires, defined as fires thatinvolve high suppression costs, property losses, natural resource damages, and loss of life (Williams 2013). Thesefires may cause the irreversible transformation of the forest environment for a period that exceeds the life cycle ofmajor forest-forming species (Sukhinin 2010; Shvidenko
et al. 2011; Fig. 6). Mega-fires of the last decade have led
up to a two-fold increase in the share of crown and peat
fires. Post-fire dieback in the area of mega-fires as a rule
exceeds 50%. A substantial part of post-fire areas may become unsuitable for forest growth for hundreds of years.
For instance, such areas in the Russian Far East (RFE) are
estimated to cover tens of million hectares (Shvidenko et
al. 2013). The increasing aridity of the climate provokes
outbreaks of harmful insects that could envelope large
areas, for example, the outbreak of Siberian silk moth(Dendrolimus superans sibiricus) which enveloped an areaof about 10 × 106 ha in 2010. Human- and climate-Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

Page 10 of 48

a

c
b

f

g

e

d

ii

j

Fig. 6 Examples of fire-induced forest transformations in the light-coniferous (Scots pine and larch) forests of southern Siberia when logging
and plantation are done. a Unburned forest. b Forest burned by low-severity fire with high trees survival. c Forest burned by high-severity firewith high tree mortality. d Repeatedly burned forest with all trees killed and almost all organic layer consumed. e Logging after post-fire treemortality. f Repeatedly burned and logged forest site, with little to no tree regeneration, dominated by tall grasses. g Plantation of Scots pine
on a repeatedly disturbed site with no natural regeneration. i Burned plantation. j The “question” mark indicates sites where management
activities may alter these disturbance trajectories in unknown ways (Kukavskaya et al. 2016)

induced change in disturbance regimes is currently acting
in concert to force ecosystems to move more quickly
towards a new equilibrium with the climate (van den Werf
et al. 2010; Soja et al. 2007).
Severe fires, driven by anomalous weather conditions,
are increasingly becoming the new norm across Russia. In
the past 15 years, extreme fires have been reported acrossnearly all large geographic regions, including very remotezones (e.g., Yakutia in 2002) and densely populated regions(European Russia in 2010). Fire weather (temperature,
precipitation, relative humidity and wind speed) in recent
decades (2003–2012) is much more dangerous than in an
earlier decade (1984–1993). In Fig. 6, at the stages from b
to i, forests might have the possibility to recover with (1)the absence of repeated disturbances; and (2) implementation of forest management mitigation efforts with increased resources for the most severe cases. However, if
the recent tendencies of fire weather continue, the survivalof the forest biome in its present boundaries is not possible (Tchebakova et al. 2009).
In 2008, smoke and related emissions from early season fires associated with agricultural/clearing in the
country of Kazakhstan, in the Transbaikal region, andthe Russian Amur Oblast (oblast is a large administrative
division in Russia) were observed in the Arctic. On
reaching the Arctic, this early season ash deposition
could result in more rapid snow and ice melting, further
altering albedo impacts on the ice sheet (Warneke et al.
2009). In 2010, the Moscow region experienced a record
drought and the hottest summer in Russian recorded
history (42 °C), which resulted in extreme fires thatburned in previously drained peatlands. This lethal combination of natural and human forcings resulted in monetary losses of 3.6 × 109 $US (by other estimates up to
10 × 109 $US) and the death of nearly 56,000 people(Guha-Sapir 2010). In the spring of 2015, anomalous
weather caused extensive and severe fires in Siberia that
destroyed 1200 houses in 42 settlements and resulted in
36 deaths and hundreds of injuries in the Republic of
Khakassia (Valendik et al. 2015). Similarly, fires in theTransbaikal region resulted in the loss of more than 240
houses in 18 settlements, the death of 11 people, andmore than 30 people injured (Kukavskaya et al. 2016).
Wildfires are uncommon in Eastern Europe andEuropean Russia (Krylov et al. 2014), but anthropogenic
fires in agricultural areas, including croplands andGroisman et al. Progress in Earth and Planetary Science (2017) 4:41

Page 11 of 48

pastures, are widespread (Soja et al. 2004; Dubinin et al.
2011; McCarty et al. 2017; Derevyagin 1987). Romanenkov
et al. (2014) noted that a peak of satellite fire detections
occurs in cropland areas in Russia, Baltic countries,
Belarus, Ukraine, and Kazakhstan directly after the snow
melt in the spring (indicating field preparation) and after
agricultural harvests in the fall. Agricultural burning is asource of short-lived climate pollutants like black carbon(McCarty et al. 2012) and methane (McCarty et al. 2017).
However, prescribed fire in forests, grasslands, or croplands is either illegal or not reported by national agencies
in Lithuania, Belarus, or Russia (Narayan et al. 2007).
Efforts to organize reliable monitoring of such fires fromspace are warranted.

Research focus 3: retreat of the cryosphere

The cryosphere in the montane regions of NorthernEurasia is represented by three components: (i) seasonal
and perennial snow pack; (ii) glaciers; and (iii) permafrost.
The cryosphere retreat has a continent-wide spatial scalewith temporal scales that vary from the century to millennia for glaciers and permafrost, to seasonal for snow coverextent (Shahgedanova et al. 2010, 2012, 2014; Aizen et al.
2007; Bulygina et al. 2011; Gutman and Reissell 2011; Sorg
et al. 2012; Chen et al. 2013; Groisman and Gutman 2013;
Nosenko et al. 2013; Khromova et al. 2014; Blunden andArndt 2015; Farinotti et al. 2015; Syromyatina et al. 2014,2015; Fausto et al. 2016).
This retreat affects (a) continental energy balancechanges due to decreases in surface albedo, increases inheat flux into the upper surface layers, and earlier spring
onsets and longer growing seasons; (b) the depletion of
the continental water storage accumulated during thepast millennia in ground ice with the subsequent desiccation of lands that rely upon water supply from glacial
melt and permafrost thaw; and (c) large-scale biospherechanges (Fig. 4) especially prominent in regions where
the cryosphere is intrinsically linked with the survival/
dominance of major species within biomes (e.g., larch
forest over the permafrost areas in northern Asia).

ab

The most prominent snow cover changes are observedin the late spring (Fig. 7a) while the total duration ofseasonal snow on the ground is decreasing, there aredays/periods, when snow maximum water equivalentand maximum snow depth have been increased overmost of Russia (Bulygina et al. 2009, 2011, updated).
Note that the strong systematic increase in spring temperatures in Northern Eurasia (Fig. 3) was apparently
enhanced by positive snow cover feedback.
Changes in the extent and mass balance of glaciers areimportant primarily because of their impact on water resources. Yet, while there is extensive information about
glacier area change, less is known about changes in glacier volume and mass, either observed or projected.
Within the domain of Northern Eurasia, assessments ofchanges of glacier mass on a regional scale are available
for the Tien-Shan mountain system using Landsat andCorona satellite imagery which provided data on volume
change (e.g., Pieczonka and Bolch 2015) and Gravity
Recovery Satellite Experiment (GRACE) data (e.g.,
Farinotti et al. 2015). The latter provides data on changes
in ice mass and is therefore directly relevant to the assessment of water resources. Yet for regions other than the
Tien-Shan, the uncertainty of measurements using
GRACE remains very high and often exceed the measured
signal (Jacob et al. 2012). In other regions, changes in themass and volume of ice are characterized using traditional
glaciological surveyors’ pole measurements of massbalance at the benchmark glaciers (World Glacier
Monitoring Service 2015). Geodetic mass balance forsmaller areas is based on using in situ geodetic measurements, aerial photography and high-resolution satellite
imagery (e.g., Shahgedanova et al. 2012), and groundpenetrating radar (GPR) measurements performed both insitu and from the air (e.g., Kutuzov et al. 2015). This last
method appears to be promising, particularly in combination with ice thickness modeling, e.g., the recently developed glacier base topography model, 2nd version(GLABTOP2; Linsbauer et al. 2012).
Within Northern Eurasia, the contemporary glaciation
reaches its maximum extent in the mountains of CentralcdFig. 7 Manifestations of the cryosphere retreat. a Spring snow cover extent anomalies over Eurasia (Blunden and Arndt 2016). b Number of
newly emerging thermokarst lakes in West Siberia during the 1973–2013 period (Polishchuk et al. 2015). c-d Altai Mountains on the boundary of
Russia, China, and Mongolia; Kozlov glacier in 1906 and 2013, respectively (Syromyatina et al. 2015)

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

Asia. In the Tien-Shan alone, according to different estimates, glaciers occupy between 15,400 and 16,400 km2(Sorg et al. 2012). The Altai Sayan Mountains and theCaucasus Mountains are other important centers of contemporary montane glaciation with a combined glacierarea of approximately 1550 km2 (Aizen 2011) and
1350 km2 (Shahgedanova et al. 2014), respectively.
Smaller centers of contemporary glaciation occur in the
Polar Urals, mountains of eastern Siberia (e.g., Kodar,
Chersky,andSuntar-Kayata),
andKamchatka(Khromova et al. 2014). Across all these regions, withthe exception of the coastal glaciers of Kamchatka(Khromova et al. 2014), glaciers are retreating although
regional variations in retreat rates are observed both between and within the mountainous systems (Kutuzov
and Shahgedanova 2009; Narama et al. 2010; Sorg et al.
2012; Shahgedanova et al. 2010). When observations
allow, the retreat of glaciers can be documented at thecentury scale (cf., Fig. 7c, d). In the first decade of thetwenty-first century, the retreat rates increased to
1% year−1, e.g., across most of Tien-Shan and Djungarskiy
Alatau (Severskiy et al. 2016; Sorg et al. 2012; Farinotti etal. 2015; Pieczonka and Bolch 2015). In addition to glaciers, the ongoing climate warming has already affected
the ground ice of these mountain ecosystems (Jin et al.
2000, 2007; Marchenko et al. 2007; Wu et al. 2013).
Across the Caucasus, the glaciered area has been
shrinking at a slower rate of 0.4–0.5% year−1 (Shahgedanova et al. 2014). Changes in the extent of glaciers ofnortheastern Siberia and the Urals are often more difficult to quantify because of the small size and cloudy
summer weather which make it difficult to obtain suitable satellite imagery. However, analysis of glacierchange in the Kodar Mountains shows both a strong lossof glacier area, as high as 0.9% year−1 between the 1960s
and 2010 (Stokes et al. 2013), and a strong loss of glacier
volume and negative mass balance (Shahgedanova et al.
2011). Glaciers of the Polar Urals have lost nearly half ofPage 12 of 48

their area since the 1950s and exhibited negative massbalance (Shahgedanova et al. 2012).
It is difficult to believe that the temperature increases
over montane areas of Central Asia and Caucasus will
not affect the extent of the regional cryosphere unlessthere is a concurrent two-digit percentage increase in regional precipitation. Analyses of cyclonic activity overCentral Asia do not show sizeable changes in the total
cyclone numbers, and there are some increases in theirvariability. Furthermore, the number of deep cyclones,
which are already rare here, has decreased in the last
decade (Fig. 8). Thus, the countries comprising this region should be prepared to confront potential problems
with water availability for montane agricultural fields
and pastures.
Permafrost and associated periglacial landforms canstore large quantities of fresh water in the form of ice(30–70% by volume, Bolch and Marchenko 2009) to buffer the loss of glacial mass. The impact of a declining
cryosphere on water resources varies among the regions.
While the impact is predicted to be moderate in thenorthern Caucasus, which receives ample precipitation(Lambrecht et al. 2011), it is likely to be stronger in arid
regions such as southern Caucasus and Central Asia. In
particular, the mountains and plateaus of Central Asia
have been in the spotlight of cryosphere research because they are a major regional source of fresh water forsurface runoff, groundwater recharge, hydropower
plants, community water supply, agriculture, urban industry, and wildlife habitat. Central Asia is categorized
as a water-stressed area where projected climate change
could further decrease streamflow and groundwater recharge (Core Writing Team 2007).
It is anticipated that under the current climate warming trend, the recession of glaciers in Central Asia will
accelerate, leading to a temporary increase of runoff during the dry season. The studies of the observed and projected changes in discharge suggest that the peak flow

Fig. 8 Annual number of deep cyclones with sea surface atmospheric pressure in its center less than 980 hPa entering sector [45° N–50° N 60° E–90°
E] that encompasses Central Asia according to ERA-interim reanalysis (Archive of Tilinina et al. 2013, updated)

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

might have already been reached and will continue for the
next decade (Hagg et al. 2006, 2013; Shahgedanova et al.
2016). However, on longer time-scales (> 50 years), thecrucial dry season glacier runoff will be substantially reduced, as glaciers will lose most or all of their ice storage.
In the same period, the melt of ground ice (initiallytrapped and accumulated in the permafrost) could become an increasingly important source of freshwater inthe region. Currently few projections of future climate
using regional climate modeling exist for Central Asia
(Mannig et al. 2013; Shahgedanova et al. 2016). While all
existing simulations project an increase in air temperature
for the region, there is substantial disagreement among
the models on the future trends in precipitation.
In the last 30–40 years, observations have indicated a
warming of permafrost in many northern regions with aresulting degradation of ice- and carbon-rich permafrost.
Increases of permafrost temperatures observed in
Northern Eurasia and North America have resulted in
the thawing of permafrost in natural, undisturbed conditions in areas close to the southern boundary of thepermafrost zone (Romanovsky et al. 2010, 2017). Mostof the permafrost observatories in Northern Eurasia
show its substantial warming since the 1980s. The magnitude of warming has varied with location, but was typically from 0.5 to 3 °C. In the regions where permafrost
surface is already “warm” (i.e., where its temperature isclose to the freezing point: Arctic shelf seas, riverbeds,
edges of the present permafrost boundaries), such warming causes multiple changes in the terrestrial hydrological cycle, land cover, and man-made infrastructure(Pokrovsky et al. 2012; Shvidenko et al. 2013; Shiklomanovet al. 2017). The close proximity of the exceptionally icerich soil horizons to the ground surface, which is typicalfor the arctic tundra biome, makes tundra surfaces extremely sensitive to the natural and human-made changes
that resulted in the development of processes such as
thermokarst, thermal erosion, and retrogressive thaw
slumps that strongly affect the stability of ecosystems andinfrastructure (see “Research focus 7: changes in infrastructure”). Figure 7b shows the number of newly
emerging thermokarst lakes in West Siberia which indicate the rate of degradation there of the upper layerof the permafrost. A main aim of the future NEFI efforts related to permafrost is to evaluate its vulnerability under climate warming across the permafrost
regions of the northern and high-elevation Eurasia
with respect to ecosystems stability, infrastructure,and socioeconomic impact. A second aim is to estimate the volume of newly thawed soils, which could
be a potential source or sink of an additional amountof carbon in the Earth system.
During the NEESPI studies of the past decade, thecryosphere retreat and its major manifestations were

Page 13 of 48

documented (Fig. 7) and it was shown that thisprocess plays a critical role in environmental changes
across Northern Eurasia.
Research focus 4: changes in the terrestrial water cycle

The mountains of Northern Eurasia cut its landmass offfrom the major sources of water supply from the tropics.
Even in the regions of “sufficient” moisture, this sufficiency is secured not by an abundance of water, but rather
by suppressed evapotranspiration during the lengthy coldseason, soil insulation from the atmosphere by seasonal
snow cover, and by external water supply from cryosphericstorage. The rest of the water is provided through unstable
atmospheric circulation (e.g., cyclones). Changes caused
by global warming can decrease and/or redistribute watersupplies from the cryosphere, increase the vegetation
period, and affect the water vapor transport from theoceans into the continental interiors where both absolutechanges and variation in the water vapor transport are ofgreat consequence. Both natural ecosystems and humanactivities rely upon the stability of the water supply.
Looming changes include (a) depletion of relatively stablewater sources (cryosphere; Khromova et al. 2014), (b) an
already unstable water source (atmospheric circulation)
becoming even more variable (Schubert et al. 2014), and(c) a longer and warmer period for vegetation growth(“greening”) increasing the biospheric water demand (Parket al. 2016). Given these, it becomes clear that changes inthe terrestrial water cycle across Northern Eurasia can adversely affect the well-being of local societies as well as theworld economy.
There is ample evidence of changes in the terrestrial
water cycle across Northern Eurasia (AMAP 2011;
Barros et al. 2014; Fig. 9), including reduced snow cover(Brown and Robinson 2011; Callaghan et al. 2011a;
AMAP 2011, 2017), intensifying spring melt (Bulygina et
al. 2011), increasing river flow (Shiklomanov and Lammers 2009, 2013; Georgiadi et al. 2011, 2014a, 2014b;
Georgiadi and Kashutina 2016; Holmes et al. 2015), disappearance of lakes (Smith et al. 2005; Shiklomanov etal. 2013) lengthened ice-free period in lakes and rivers(Shiklomanov and Lammers 2014), degradation of
permafrost (Streletskiy et al. 2015), and melting of glaciers (Velicogna and Wahr 2013; Duethmann et al.
2015) among others.
River flow is a dynamic characteristic that integrates
numerous environmental processes and aggregates theirchanges over large areas. River runoff plays a significant
role in the fresh-water budget of the Arctic Ocean andits water supply especially during low flow seasons (fallwinter). Ocean salinity and sea ice formation are critically affected by river input (Rawlins et al. 2009). Changes
in the fresh water flux to the Arctic Ocean can exert significant control over global ocean circulation by

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

Page 14 of 48

Fig. 9 Changes in the surface water cycle over Northern Eurasia that have been statistically significant in the twentienth century; areas with morehumid conditions (blue), with more dry conditions (red), with more agricultural droughts (circles and ovals), and with more prolonged dry
episodes (rectangles) (Groisman et al. 2009, updated). In the westernmost region of this map (Eastern Europe), blue and red rectangles overlap
indicating “simultaneous” (although in different years) increases of heavy rainfall frequency and of occurrences of prolonged no-rain periods

affecting the North Atlantic deep water formation withirreversible consequences for Northern Hemisphere climate (Peterson et al. 2002; Rahmstorf 2002; Fichot et al.
2013). Eurasia contributes 74% of the total terrestrial
runoff to the Arctic Ocean. The total annual dischargeof six large Eurasian rivers increased from 1936 to 2010
by approximately 210 km3- more than the annual discharge of the Yukon River (Shiklomanov and Lammers
2011), with a new historical maximum in 2007 (Fig. 10;
Shiklomanov and Lammers 2009; Holmes et al. 2015).

Fig. 10 Top panel: annual precipitation and surface air temperature in Siberia (east of the Ural Mountains, excluding Chukotka) from 18 Siberian
stations and reanalysis fields. Lower panel: total annual river discharge to the Arctic Ocean from the six largest rivers in the Eurasian Arctic for theobservational period 1936–2014 (Holmes et al. 2015) and annual minimum sea ice extent for 1979–2014 (source of the sea ice extent data: US
National Snow and Ice Data Center, Boulder, CO, USA website, http://nsidc.org/data)

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

River discharge into the Arctic Ocean is a highly effective conveyor in transporting continental heat acrossEurasia (Nghiem et al. 2014) under a warming climate
with increasing temperatures (Fig. 2). Eurasian rivers
with immense watersheds, particularly the Severnaya
Dvina, Pechora, Ob, Yenisei, Lena, and Kolyma Rivers,
provide a massive flux of warm waters into the Arctic
Ocean or peripheral seas contributing to melt sea ice inspring and summer. The massive river energy flux to the
Arctic Ocean carries an enormous heating power of
1.0 × 1019 J/year for each 1 °C of the warm river waters
above freezing, which is equivalent to the power releasefrom detonation of 2.5 × 109 TNT/°C/year (Nghiem etal. 2014). With increased water temperatures (Lammers
et al. 2007) and longer ice-free periods of the Arctic rivers (Shiklomanov and Lammers 2014), the role of riverheat input is increasing and must be incorporated in sea
ice prediction and projection models. These changes ofriver discharge in Northern Eurasia have a predictive potential to force Arctic change at interannual to decadal
timescales and beyond (Richter-Menge et al. 2012).
The Northern Eurasian freshwater cycle has been an
important focus of ongoing research, and a great deal ofwork has been carried out to understand the increases
in the river discharge to the Arctic Ocean and to identify
whether or not the regional hydrological system is accelerating (e.g., Smith et al. 2007; White et al. 2007; Rawlins
et al. 2010; Holmes et al. 2013). Although a variety oftheories have been put forward, the physical mechanisms
driving the observed runoff changes are not yet fully
understood. Comprehensive analyses of water balancecomponents (Rawlins et al. 2005, 2010; Serreze et al.
2006; Shiklomanov et al. 2007), human impacts(McClelland et al. 2004, 2006; Yang et al. 2004; Adam etal. 2007; Shiklomanov and Lammers 2009; Zhang et al.
2012a), and hydrological modeling experiments (Bowlingand Lettenmaier 2010, Troy et al. 2012) have not revealeda clear cause of the observed increase in river discharge.
Precipitation in the Eurasian pan-Arctic, which is themost important water balance component for the runoff
generation, does not show a significant change to support
the observed increasing trend in river flow (Adam andLettenmaier 2008; Groisman et al. 2014).
In contrast, the increase in air temperature across thepan-Arctic has been widely and consistently documented(Overland et al. 2014), and it is expected to continue
with the higher rates in the future (Barros et al. 2014).
The air temperature rise leads to significant changes in
the regional cryosphere including spring snow cover retreat, less frozen soil in the winter season, deeper annual
thaw propagation in the permafrost zone (deeper active
layer), and melting of glaciers. Several local or regional
studies have shown the important influence of changes indifferent cryospheric components including permafrost

Page 15 of 48

thaw (Davydov et al. 2008; Woo 2012; Streletskiy et al.
2015), glacier melt (Bennett et al. 2015), less thickness of
seasonally frozen soil (Markov 1994, 2003; Frauenfeld etal. 2004; Frauenfeld and Zhang 2011; Shiklomanov et al.
2017), and river ice on river runoff generation (Gurevich 2009; Shiklomanov and Lammers 2014). However, it is not clear from these studies how these
locally observed changes will interact among eachother and with spatially varying precipitation changes
to affect the river flow over the entire region and the
freshwater flux to the ocean. There is also considerable uncertainty about how these local changes will
scale up to regional and continental scale impacts.
Terrestrial evaporation and transpiration (evapotranspiration) are the components of the terrestrial hydrological cycle that are the most difficult to measure given
few direct observations (Speranskaya 2011, 2016). Nearsurface air temperatures are increasing, and one can expect that the evaporation from wet land surfaces should
increase. However, the near-surface wind speeds overthe entire territory of Russia have been decreasing in thepast several decades (Bulygina et al. 2013 updated to2016; such studies have not been completed for otherparts of Northern Eurasia), and this may reduce the airsurface water vapor exchange. Furthermore, most
Northern Eurasian land surfaces are not “wet” so atemperature increase does not automatically induce anincrease in evaporation. Opposite processes may prevail
due to evaporation suppression by dry upper soil layer(Golubev et al. 2001). Thawing of permafrost and lessseasonally frozen ground can significantly change underground hydrological pathways. This will lead to an increase in ground flow, higher runoff during the coldseason and, correspondingly, to a decrease in total
evapotranspiration. Finally, future ecosystem shifts candramatically change the vegetation composition (Fig. 4)
and the transpiration rate of the new communities can
induce further fundamental changes to the regional
water cycle. All of the processes above suggest thatchanges in this component of the hydrological cycle are
not trivial and should be assessed within new models
that properly account for the interactions among the atmosphere, soil, and biosphere. Large-scale geochemicaland geophysical runoff changes (biological and inorganic
matter transports) also should be considered.
Recently, there were a number of assessments oftrends in the discharge from glaciered catchments ofCentral Asia. A detailed review of changes in river discharge in the Tien-Shan has been provided by UngerShayesteh et al. (2013) who reported contrasting trends
for its different sectors including increasing summer
runoff in the northern and inner Tien-Shan, and decreasing summer runoff in the central and western
Tien-Shan and at the lower elevations in the inner Tien-

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

Shan. More recently, Shahgedanova et al. (2016)
reported an increase in discharge from the glacieredcatchments unaffected by human activities in thenorthern Tien-Shan using homogenized long-term records. Positive trends in the discharge from the headwater catchments of the Tarim River were reported by
Duethmann et al. (2015), Krysanova et al. (2015), andKundzewicz et al. (2015) who also attributed thesechanges primarily to the increasing glacier melt, buthighlighted their inability to quantify water withdrawal
and its contribution to the long-term trends as a limitation of these studies.
It is important to recognize that the increases in discharge due to glacier melt (if any) have been a temporary relief for water resources in the interior regions ofCentral Asia and Caucasus. In these regions, water
stored in the cryosphere is limited and, if the current
tendencies of the cryosphere depletion persist, they will
result in severe water deficits in future decades. Therefore, it is time to begin preparations to mitigate and/or
adapt to these deficits beforehand by developing management routines for water preservation and responsible
consumption as well as by modifying agriculture andpastoral practices accordingly.
Accelerated climate- and anthropogenic-inducedchanges in the hydrological cycle raise societal concern
because changes in the water level, streamflow, snow,
ice, and frozen ground have pronounced effects on local
and regional economies and the well-being of the Northern Eurasian residents. In particular, there may be immediate implications for water supply, irrigation, energy
production, navigation, land and water transport, andstructural engineering.
Presently, changes of the hydrological regime inNorthern Eurasia are producing more and more freshwater input to the Arctic Ocean. The changes in riverdischarge, along with the sea ice decline, and higher precipitation over the ocean may exert a significant control
over the North Atlantic meridional overturning (thermohaline) circulation with potentially dramatic consequences for climate of the entire Northern Hemisphere.
Accordingly, we should expand our knowledge to better
understand these hydrological processes, to better project possible extreme events, and better adapt to ongoing
and upcoming environmental changes.
Research focus 5: changes in the biosphere

Ecosystems in Northern Eurasia are subjected to the impacts of climate change and human activities over theentire sub-continent. In the northern part on sites withpermafrost, anthropogenic changes are primarily due tooil and gas exploration and extraction, mining, and infrastructure development. Further south, timber harvest(along with oil/gas) is predominant in the boreal andPage 16 of 48

temperate forest zones, as are agricultural and pastoral
activities in the forest-steppe and steppe zones. Industrial development often leads to the physical destruction of landscapes, changes of the hydrological regime,
and widespread contamination of air, soil, and water(Derome and Lukina 2011; Baklanov et al. 2013).
Climate-induced changes in terrestrial ecosystems transform important ecosystems and their services, which inturn, require an adjustment in business planning, nature
conservation, forest management, agricultural practices,and regional economic policies to mitigate or adapt tothese changes. The Siberian Taiga and Far East zones together comprise the largest part of the world’s mostintact remaining boreal forests (Potapov et al. 2008).
It is now recognized that the RFE in particular ishome to unique ecosystems and biodiversity (Newell
and Wilson 2004).
In the long term, terrestrial ecosystems function in a
dynamic balance with the states of climate, water resources, the lithosphere, and cryosphere. When thesefour driving forces change, ecological systems also begin
to change. Currently, significant changes in forest area
and composition are predicted to occur within a few future decades (see Fig. 4 and discussion). Ongoingclimate change already impacts the ecosystems ofNorthern Eurasia and may provide hints for projecting
future changes. These impacts are manifold and relate todiverse features of ecosystem states and behavior likehealth, productivity, resilience, change of natural disturbance regimes, major biogeochemical cycles, among
many others (Kharuk et al. 2017).
Forests disturbed within the last 30 years account for
approximately 75 × 106 ha (9%) of Russian forests(Loboda and Chen 2016). Dendrochronological data
show that fire frequency has been increasing in different
parts of Russia throughout the twentieth century(Voronin and Shubkin 2007; Kharuk et al. 2016). Recent
satellite-based assessments show that the rates of forest
disturbance have increased further since 2000 comparedto the pre-2000 era across all forest biomes with the largest increase from 1.2 to 2.2 × 106 ha year−1 in Eastern
Siberia associated with an increase in fire occurrence(Loboda and Chen 2016). The average extent of burnt
area during the last 15 years over Russia is estimated at
10–13 × 106 ha year−1 with the post-fire forest mortality
rate of 1.76 × 106 ha year−1 (Krylov et al. 2014; Bartalev
et al. 2015). In the future, the frequency and extent of afire occurrence in boreal forests are expected to rise further under the projected scenarios of climate change byanywhere from 25 to 50% (Flannigan et al. 2000, 2013)
to 300–400% (Shvidenko and Schepaschenko 2013;
Abbot et al. 2016) with an accompanying 50% increasein fire weather severity. These, in turn, are likely to result in large-scale ecosystem shifts. For example, anGroisman et al. Progress in Earth and Planetary Science (2017) 4:41

increase in fire frequency is expected to lead to the disappearance of the pure Siberian pine stands in southern
Siberia and the replacement of Siberian pine forests by
Scots pine stands in the northern regions (Sedykh 2014).
Repeated disturbances have resulted in substantial decreases in fuel loads and led to soil erosion, overheating,the absence of nearby seed sources, and the proliferationof tall grasses. As a result, the lack of natural post-fireregeneration of forests has led to their conversion to
steppe vegetation (Kukavskaya et al. 2016; Fig. 6). Basedon the analysis of satellite vegetative indices combinedwith ground-based data, repeated fires have been foundto have the most negative impact on reforestation, forcing the failure of post-fire regeneration in more than
10% of the forested area in the south-western part of theTransbaikal region (Shvetsov et al. 2016). Furthermore,
Flannigan et al. (2013) project that cumulative fire severity would increase three times and fire season length
could increase by 20 days by 2091 for Northern Eurasia.
Thus, there is an urgent need for planning adaptive forestry and fire management activities designed specificallyfor the regions that take into account trends in conditions and local features (climatic, forest-vegetation, social, technical, and economic).
While productivity of forests at the continental level has
increased during the last few decades at a rate of 0.2–0.3%
per year due to increasing temperature and lengthening of
the growth period, there are large territories with decreasing productivity (Schaphoff et al. 2015) and enhanced
mortality of trees. This mirrors the general condition for
the entire boreal belt (Allen et al. 2010). The forests overlarge territories in different regions of Northern Eurasia
are exposed to substantial dryness, particularly thosewhich are dominated by dark coniferous tree species(Shvidenko et al. 2013) resulting in increased water stressand impacts of forest pests and pathogens. Increasing climate aridity has caused the morphological structure offorests to change (Lapenis et al. 2005). High variability ofclimate and an increase in the frequency and severity oflong dry and hot periods (heat waves) impact forest healthand the productivity of ecosystems in a visibly negativeway (Bastos et al. 2014; Gauthier et al. 2015). Impacts ofseasonal weather on net primary production and soil heterotrophic respiration is ecosystem/soil type and bioclimatic zone specific (Shvidenko and Schepaschenko 2014;
Mukhortova et al. 2015).
Influences of climate changes on vegetation are primarily manifested in the alteration of the basic biogeochemical functions—first of all, the exchange rates ofwater vapor and carbon dioxide between plant ecosystems and the atmosphere. When ecosystems respond tochanges in ambient temperature and moisture conditions, the direct response can be quite rapid. For example, an increased frequency and duration of droughts

Page 17 of 48

result in a transformation of the functional role of wetlands to be a source rather than a sink of CO2 for the atmosphere (Bohn et al. 2013; Olchev et al. 2013, 2013).
Sustainability of the forest carbon sink under changing
climate is a serious concern, given the huge task of limiting the growth of atmospheric greenhouse gases (GHG)
concentrations to levels adopted under the Paris
Agreement of 2015 (http://ec.europa.eu/clima/policies/
international/negotiations/paris_en). The global growthof CO2 in the atmosphere is significantly compensatedby the terrestrial biosphere sequestering 2 to 4 Pg of carbon every year as evidenced globally from atmosphericcomposition measurements (Le Quéré et al. 2015).
Atmospheric inverse models (Dolman et al. 2012) estimate the sink, which amounts to less than 4% of global
net primary production, to be disproportionally allocatedto high and mid latitudes of the Northern Hemisphere,
including Northern Eurasia. This result is especially convincing when atmospheric observations over NorthernEurasia are used (Stephens et al. 2007; Maksyutov et al.
2013; Jiang et al. 2012, 2016; Saeki et al. 2013).
Terrestrial biosphere models and long-term atmosphericobservations (Graven et al. 2013) reveal an increase ofbiospheric CO2 seasonal exchange during the past few
decades that are driven by rising temperatures and atmospheric CO2 concentrations. Maintaining the size ofthe carbon sink in Northern Eurasia into the twenty-first
century under the negative impacts of increased
droughts and fires requires basically the same measures
as those needed for sustaining forestry, namely, fire protection and efficient forest management (Hurtt et al.
2002, 2011; Shvidenko et al. 2013). Despite the high levelof natural and human-induced disturbances, the ecosystems of Northern Eurasia currently serve as a net sink ofcarbon up to 0.5–0.6 Pg C year−1 (Dolman et al. 2012)
with about 90% of this sink occurring in forested landscapes. However, Fig. 11 shows that large areas of disturbed forests, basically on permafrost, have alreadybecome a carbon source.
Current biosphere models predict diverse responses
based on the acceleration of the carbon cycle by futureclimate change. A significant change is expected for ecosystems on permafrost, but many important features of
ecosystems at high latitudes are not adequately incorporated in these models. For the permafrost-region in
Russia, current estimates indicate that the end-of-the-century release of organic carbon from the Arctic rivers andcollapsing coastlines may increase by 75% (Gustafsson etal. 2011). The carbon loss from wildfires may increase
substantially (Shvidenko et al. 2013). The expectedchanges of ecosystems in permafrost regions include
forest decline over large regions from changes in thehydrological regime and increasing water stress (Fig. 4).
Still, it is not clear whether northern forest ecosystems will

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

Page 18 of 48

Fig. 11 Carbon sources and sinks by full carbon account of Russian terrestrial ecosystems (average for 2007–2009). Units of sinks and sources are
g C m−2 year−1 (Shvidenko and Schepaschenko 2014)

reach a tipping point, but this is very likely under regional
warming above 7 °C (Gauthier et al. 2015; Schaphoff et al.
2015). The uncertainty of such a prediction is high. However, it is very likely that the permafrost region will become a carbon source to the atmosphere by the end of
this century, regardless of which warming scenario is used.
Purposeful forest management could substantially slow
down this process (Abbot et al. 2016).
Logging is an important disturbance factor in many
forest areas of Northern Eurasia (Achard et al. 2006;
Gauthier et al. 2015). Logged sites are usually highly susceptible to fire due to a combination of high fuel loads
in leftover debris and accessibility for human-caused ignition (Loboda and Csiszar 2007; Loboda et al. 2012).
These sites typically experience higher severity fires than
do unlogged forests, and these fires can spread to adjacent areas (Ivanov et al. 2011; Kukavskaya et al. 2013).
In the dry lands, clear-cut logging accelerates the conversion from forest or forest-steppe to steppe vegetation.
Throughout the Taiga zone, timber harvesting (Bergen
et al. 2008), and possibly human-exacerbated forest fires(Kasischke et al. 1999) are major contributors to change
in the ecological systems of Northern Eurasia. Forest
harvest in Russia as a whole, and in particular in Siberia
and the RFE has changed over the past 50 years withhigh harvest rates characterizing the late Soviet era(Peterson et al. 2009). After the dissolution of theformer Soviet Union, these rates dropped to less than
to 100 × 106 m3 (Bergen et al. 2008) although more
recently they have partially rebounded. The early

Soviet era saw an emphasis on harvest from western
Russia. Since the 1980s, the greater development oflogging in Siberia and the RFE was spurred by declining western Russia reserves, incentives to establish industry in the eastern reaches of Russia andagreements with Japan (in 1968 and 1974) for forestry
infrastructure development in Siberia/RFE. Most recently (and in the foreseeable future), trade in easternregions is influenced by increasing demand from
China (Fig. 12), with significant potential to adversely
impact the health and intactness of Siberian and RFE
forests in particular (Bergen et al. 2013; Newell andSimeone 2014).
Predictions of the future distribution and state of ecosystems in Northern Eurasia vary considerably (Gustafson
et al. 2011, 2011; Tchebakova and Parfenova 2012, 2013),
with remaining large uncertainties in the vegetation
dynamics. Progress in dynamic vegetation observations
and modeling in North Eurasia has become more visible
with the recent availability of high-resolution remote sensing data on topography, plant phenology, biomass, andsoil wetness (Kharuk et al. 2017; Tchebakova et al. 2016,2016). However, more efforts will be needed to expand the
new data capabilities into lowlands and tundra regions.
Study results from the region suggest that further global warming will put at risk the sustainability of forest
and forest landscapes (Gauthier et al. 2015; Schaphoff et
al. 2015; Fig. 4). As mentioned earlier in this paper,models predict substantial shifts of vegetation to thenorth with forest steppe and steppe expected to beGroisman et al. Progress in Earth and Planetary Science (2017) 4:41

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Fig. 12 Major export markets for Russian forest products 1960—2009 (archive of Newell and Simeone 2014; data source European Forest Institute 2014)

dominant across large southern territories of the present
forest zone (Schaphoff et al. 2006; Tchebakova and Parfenova 2012). However, the changes in climatic conditions during the last several decades have occurred too
rapidly for vegetation structure to completely adjust to
the new conditions. The immediate response of vegetation cover to changes of climatic variables can be quite
rapid, but the recovery can be characterized to occur
over a longer time frame with significant delay. Whenthe climate changes shift a region to conditions outsideof the range of dominant species, the past and current
seed dispersal rates (Udra 1988) are slower than the migration rate needed for vegetation to alter its composition to one appropriate to the predicted climate change.
A similar conclusion was reached based on comparisons of palynological data and radio-carbon dating inWestern Europe (Huntley and Birks 1983) and in theEuropean part of Russia (Velichko 2002; Velichko et al.
2004). It has been shown that under warming during thefirst half of the Holocene, the expansion rate of the majority of tree species was 200–300 m/year although therate did reach 500–1000 m/year for pioneer species(birch and aspen). Similar estimates of the expansion
rate of the boreal and temperate tree species in the early
Holocene (from 100 to 1000 m/year) have been obtained
from palynological data (Higgins and Richardson 1999;
Tinner and Lotter 2001; Higgins and Harte 2006).
The results of paleoclimatic and paleogeographical reconstructions of the past epochs can be useful (as analogues) for prediction of the possible changes of thevegetation cover due to the projected change of climate
conditions in the twenty-first century. Numerous refugia(areas with species that are different from the surrounding dominant ecosystems/populations) provide clues tothe boundaries of the past ecosystems and also show thelevel of their resilience to a changing environment. Many
global and regional paleoclimatic reconstructions havebeen compiled for various warming and cooling periodsof the Late Pleistocene and Holocene (Velichko 2002).
According to available paleogeographical data, the thermal
maximum of the Holocene (about 6–5.5 ka BP) could beconsidered as an analogue of the climatic conditions forthe middle of the twenty-first century and the optimum of
the last Interglacial (Mikulino-Eemian-Sangamon, Stage
5e of the deep-sea oxygen curve, about 125 ka BP) period
could be considered as a paleo analogue for the end of thetwenty-first century (Velichko et al. 2004). Still, it is notclear how much dispersal rates may accelerate under climate change, but it is very likely that the southern parts ofthe forest zone will be under very high risk, and thepotential loss or decline of southern taiga forests will not
be compensated for by increasing forest area beyond thecurrent northern tree line.
Ecosystem changes in the present forest zone ofNorthern Eurasia may be quite rapid due to simultaneous
effects of climate change that is among the largest overthe planet (Fig. 3; Blunden and Arndt 2015, 2016) and ofanthropogenic factors such as logging (Fig. 12), air, soil,
and water pollution, and man-induced fires (see “Research
focus: frequency and intensity of extremes”). First of all,the feedbacks from these changes directly affect the ecosystem services to societies of the region and, thus, theirwell-being. Secondly, the biogeochemical feedbacks of the
carbon cycle changes in the forest and tundra zones ofNorthern Eurasia and its Arctic shelf seas may go far beyond the continent after the release of methane and CO2
from large carbon storage in forest, wetlands, and frozen
soil to the atmosphere due to biomass decomposition,
fires, and thawing (Friedlingstein et al. 2006; Shvidenko et
al. 2011, 2013; Gao et al. 2013; Gauthier et al. 2015;

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

Shakhova et al. 2015; Ruppel and Kessler 2017). Thesetypes of feedbacks affect the rates of global Earth systemchange and, therefore, represent a global concern.
In Central Europe, air pollution has been recognized
as a key threat for forest ecosystems since the second
half of the twentieth century. At the end of the twentiethcentury, sulfur and nitrogen depositions in Europe connected with lignite combustion and the high concentration of industry reached their highest levels. Thereafter,
the deposition of S decreased by > 80% (Schöpp et al.
2003), with concurrent reductions in NH3 and NOx(Kopáček and Posch 2011). The decrease of SO2 emissions in Czechia has been one of the most pronounced(Vestreng et al. 2007) and is believed to have profoundconsequences for ecosystem biogeochemistry (Oulehle
et al. 2011). This reduction in pollution has to be continued and its monitoring remains an important task.
Norway spruce (Picea abies) is a tree species sensitive
to air pollution. Thus, Norway spruce forests in themountains of Central and Eastern Europe have been selected for regional studies of the interaction of climate
and socio-economic drivers (Campbell et al. 2004;
Mišurec et al. 2016; Kopačková et al. 2014, 2015). Since
1994, a network of 15 small forested watersheds(GEOMON) was established in Czechia to understandthe forest response to air pollution. Since then,
GEOMON has provided a testbed for exploration ofelement cycling on a watershed scale using modern remote and proximal sensing methods (Fottová 1995;
Oulehle et al. 2008).
Research focus 6: pressure on agriculture and pastoral
production

The temperate and steppe zones of East Europe are abreadbasket for a large part of Northern Eurasia(Swinnen et al. 2017). However, under pressure of growing population, the nations of these zones will need toinvest in climate-smart agricultural techniques to sustain
or continue to improve agricultural yields and livestock
production given forecasted climate change. “Climatesmart” agricultural systems are resilient to climatechange and offer carbon and GHG emissions mitigation
potential without compromising productivity, food security, and the livelihoods of those working in the agricultural sector. So far, Iizumi and Ramankutty (2016)
found that statistically significant increases in wheatyields in Ukraine were explained by improved agroclimatic conditions, i.e., warmer and longer growing seasons, and not by management strategies.
Land abandonment and recultivation During the pastquarter-century, land abandonment in the NorthernEurasia region has been associated with fundamental
changes in agricultural production and land use caused

Page 20 of 48

by the breakup of the Soviet Union in 1991 (Lerman etal. 2004). The guaranteed markets and subsidized production from the Soviet era, particularly in the livestock
sector and less productive agricultural land, were lost.
This caused an unprecedented drop in fodder-crop
production, plummeting livestock numbers (Schierhorn
et al. 2014), decline in grain yields (Trueblood andArnade 2001), increased fallow periods (de Beurs andIoffe 2014), and widespread agricultural land abandonment (Alcantara et al. 2012, 2013; Prishchepov et al.
2012; Griffiths et al. 2013; Lieskovský et al. 2015).
According to official statistics, approximately, 59 Mha offarmland were abandoned from 1991 to 2000 across thepost-Soviet countries (Fig. 13). A large portion of thischange occurred in Russia. Two generalized trajectoriesof change resulted from this perturbation of 1991 and its
subsequent effects up to the present: (1) some former
agriculture lands have been taken out of production andhave become reforested, and (2) others were temporarily
taken out of production but have been later recultivatedand/or otherwise put back into production under
different ownership, management, or other socioeconomic processes.
With regards to the first trajectory, overall, the abandoned agricultural fields in Eastern Europe and Russia
are driving an increase of forest cover, and have becomea terrestrial carbon sink at the global scale over the latetwentieth and early twenty-first centuries (Kuemmerle etal. 2011; Schierhorn et al. 2013; Kurganova et al. 2014,2015). By 2010, approximately 5 Mha of new forests
were observed on former agricultural fields in Eastern
Europe that were cultivated during the Soviet era(Potapov et al. 2015). In the temperate zone, abandoned
fields are often slowly but steadily encroached by shrubs
and forests. Varying levels and timing of abandonmentof agricultural lands were observed at the landscape levelin three Landsat scene case study sites over the period
1975–2001 in the Siberian Taiga zone (Bergen et al.
2008), with most consistent decreases in agriculturalland areas after 1990.
After the dissolution of the Soviet Union and subsequent cessation of the state subsidies for collective agriculture, large areas of less productive croplands were either
abandoned (Alcantara et al. 2012, 2013; Prishchepov et al.
2012) or the fallow periods increased (de Beurs and Ioffe
2014). Potapov et al. (2015) reported that 32% of total forest regrowth between 1985 and 2012 was due to afforestation of former agricultural lands. However, afforestationof abandoned croplands is currently not included in theofficial forestry reports (Potapov et al. 2012), and the legal
status of these lands remains uncertain.
The second trajectory which centers on land recultivation is more complex. First, agriculture abandonment
rates varied across all of the former-USSR countries andGroisman et al. Progress in Earth and Planetary Science (2017) 4:41

Page 21 of 48

Fig. 13 Changes in sown areas across the former Soviet Union (Russia, Ukraine, and Kazakhstan) from 1990 to 2013; areas of abandoned sown
areas for this period are 40 Mha in Russia (Rosstat 2016); 5.4 Mha in Ukraine (Ukrstat 2014); and 13 Mha in Kazakhstan (Kazstat 2014)

were mediated by national and regional policies regarding support of agriculture (Prishchepov et al. 2012), as
well as access to new markets (de Beurs and Ioffe 2014).
One of the lowest rates of abandonment was observed
where land reforms were successfully completed in ashort period (Poland) or, in an alternate case, where they
were absent (Belarus). Strong regional differences werealso observed within countries. For example, Ioffe et al.
(2012) looked at the contrasting situation of Kostroma,
an oblast in the north of European Russia and Samara,
an oblast in southern European Russia. In the northernoblast, agriculture is now limited and in retreat beyond
relatively small-scale operations in suburbia, while in
Samara, the agricultural activity now appears to be sustainable, albeit on a somewhat less extensive spatial scalethan in the past.
After 2000, a partial recultivation of abandoned lands
has been observed, which is primarily driven by adjustment of agricultural policies and growing prices for agricultural commodities (de Beurs and Ioffe 2014; Estel etal. 2015; Meyfroidt et al. 2016; Smaliychuk et al. 2016).
However, recultivation rates have been compensated byongoing agricultural land abandonment—reaching 60 Mha

by 2013 for three largest post-Soviet agricultural nations(Fig. 13). From 2000 to 2010, grain yields increased (Trueblood and Arnade 2001; Liefert et al. 2010). In southern
Russia where the physical attributes, location, and humanresources are best positioned to support agricultural activity (e.g., in Stravropol’ Krai), there is growth potential for
agriculture (Kattsov et al. 2012). Here, there is evolving
specialization of former socialized farms in response tomarket conditions. In Stavropol’, this involves a shrinkage
of animal husbandry and a consequent release of surplus
labor, increased levels of absentee (corporate) ownership offarmland in the more favorable locations, decoupling of
the economic fate of successful large farms from deficient
local municipal budgets, and an expansion of non-Russianethnic communities in the countryside (Ioffe et al. 2014).
Dynamics of cultural landscapes in European countriesof the former Soviet Bloc can also be characterized by
two opposite processes—intensification and extensification (Fjellstad and Dramstad 1999; Bičík et al. 2015).
Intensification occurs when cropping intensity or livestock
stocking increases on some land. This may be accompanied by abandonment of other, more marginal cropland,
pastures, or rangeland. In contrast, extensification occurs

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

when more cropland or pastures are needed so that
additional natural lands are converted to agriculture.
Land abandonment in Central and Eastern Europe
since the 1950s has resulted from a complex multidimensional process with environmental, ecological,
economic, and social consequences (Kuemmerle et al.
2008; Keenleyside and Tucker 2010). Detailed information about abandoned lands is missing from European
national land resource statistics.
The combined abandonment-reforestation andabandonment-recultivation trajectories potentially provide future options for both biofuel production andcropland expansion. The Northern Eurasian region represents a great potential to boost agricultural production(Schierhorn et al. 2014), and also to provide other ecosystem services on abandoned lands. However, climatechange and socio-economic and political development
may substantially limit such opportunities (Meyfroidt etal. 2016). The future of some abandoned lands is uncertain due to the fluctuation of prices for agricultural commodities, growing interest in biofuel production, anddevelopment of national food security programs by the
successors of the former Soviet Union. In some postSoviet countries (e.g., Ukraine), land reforms are not yet
completed to this date (2017), limiting recultivation ofabandoned lands. Adverse demographic conditions in
Eastern Europe associated with an exodus of the rural
population (Nikodemus et al. 2005; Prishchepov et al.
2013) and the depopulation of rural areas in China (Liuet al. 2010) may trigger additional land abandonment. Because of limited institutional and economic ability toadapt to changing weather patterns, the increase of weather extremes represents a real threat for future agricultural production in Northern Eurasia. This may reduce
the possibility to close existing yield gaps (Dronin and
Kirilenko 2010; Lioubimtseva and Henebry 2012;
Schierhorn et al. 2014; Horion et al. 2016). Last but notleast, the observed increases in cropping intensity (deBeurs and Ioffe 2014) without adequate application offertilizers may reduce soil fertility and diminish yields.
With respect to the above, the importance of socioeconomic factors in land use is paramount. For example,
the level of institutional suppression in two major cropproducing nations of the former Soviet Union, Ukraine
and Russia, during the last 60 years of the Soviet period
was so high, that the former Soviet Union imported
grain in the last two decades of its history. Conversely,in recent years, even after the massive land abandonment in the 1990s, these two nations have become thesecond and third major wheat exporters globally.
Agriculture and pastoral production in the DLB
Spanning 25–125° E and 24–55° N across 17 countries(Fig. 1), the DLB is the largest contiguous dryland in the

Page 22 of 48

extratropics. The region has served as the historical traderoute between the Chinese East and the MediterraneanWest, combining the Persian Royal Road and the Silk
Road. The Silk Road was and is an important international
trade route between China and the Mediterranean. Historically, the Silk Road has experienced major expansions
and geopolitical conflicts among cultures and religions,political and institutional shifts including the collapseof the Soviet Union (Hostert et al. 2011). Especially inthe last millennium, resource extractions (e.g., oil),rapid land use change (e.g., urban and agricultural expansion), climatic change, and natural disturbances(e.g., dust storms) have driven change in the region.
The increased demand for meat and dairy products
have produced strong pressure on agro-pastoral lands
where transitional economies with frequent institutional shifts, water resource scarcity and climate conditions interact to alter DLB ecosystems and societies.
The geopolitical systems are diverse, but most countries
in the region are either developing or transitional economies with great demands for meat and dairy production (Ojima and Chuluun 2008).
While climate projection models agree that the DLB
will become much warmer over the rest of the century,
there is little agreement and considerable uncertainty
about future precipitation patterns for the region. The
Fifth IPCC Assessment Report (AR5; IPCC 2014) statedwith high confidence that the Coupled Model Intercomparison Project Phase 5 (CMIP5) generation of models
could project temperature distribution at a regional scalebetter than the previous generation of models. However,the AR5 report states with “a medium confidence” that
there had been no improvements in model performancefor precipitation. Moreover, global and regional climate
models are seriously challenged by the rugged terrainfound in much of the DLB (Parfenova et al. 2013; Lu etal. 2009; John et al. 2013, 2016).
Over the past three decades, the DLB has gone
through several major changes that drive regional agricultural and pastoral land changes. First, the regional
population has increased at a moderate rate similar to
the global population trend. But some areas, especiallyaround urban agglomerations in the East Asian part of
the DLB, have increased more rapidly resulting in
greater pressure on agricultural and pastoral lands (Qi etal. 2012, 2012; Kraemer et al. 2015). Second, there havebeen profound institutional shifts in the agricultural sector, primarily in post-Soviet Central Asia where the
newly independent states have disparate natural resource
endowments. To balance food security with commodities for export, these new nations have shifted their agricultural priorities (for example, replaced high water
demanding cotton by wheat) that have altered regional
water demands—resulting in agricultural abandonment

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

in some locations and intensification in others (Wrightet al. 2012; de Beurs et al. 2015; Kraemer et al. 2015).
Observations and biosphere models suggest that climate change is producing shifts of the ecotones in thedrylands of Asia (Groisman and Soja 2009; Tchebakova
et al. 2016). The northward movement of the tree line
and the changing dynamics of cover types, such as
shrublands and savannas in the grassland matrix, alter
feedbacks to carbon, water, and energy balances. Warming trends along with land use and land cover change(LULCC) could substantially modify the carbon balanceand biodiversity of the Eurasian Steppe. Natural and anthropogenic factors act in concert amplifying one another. Consequences of reckless land use and generaldrying of the continental interiors include water scarcity,
lowered water quality, soil salinization from agriculture
intensification, and the disappearance of lakes/rivers due
to reduced snow packs, glacier loss, and aggressive fresh
water extraction (Klein et al. 2012).
The region has also experienced a rapid transformation in land cover. Grasslands have been converted
to croplands in Central Asia and in portions of East
Asia. Changes from cropland to vacant land have accompanied the collapse of the Soviet Union as farms
were abandoned en masse (Lioubimtseva and Henebry
2009; Chen et al. 2015; Fig. 13). The net gain in carbon sequestration due to abandonment of croplands
is offset by grassland degradation from the increased

Page 23 of 48

grazing pressures following dramatic increases in land
privatization (e.g., herding policy on the Mongolia
Plateau, Chen et al. 2015), and increased fooddemands (Qi et al. 2012).
LULCC has simultaneously occurred at an alarming
scale across the DLB. A transition matrix based on theModerate Resolution Imaging Spectroradiometer(MODIS) Land Cover Type Product (MCD12Q1) between 2001 and 2012 revealed that shrublands and savannas (i.e., steppe) show a high degree of turnoveracross the entire region, at 38% for shrublands and 73%
for savannas, respectively (Fig. 14). Regionally, shrublands and savannas showed a greater turnover (77 and89%, respectively) during the decade, with East Asianand Central Asia at 47 and 88%, respectively, and the
Middle East at 39 and 54%, respectively. Similarly, croplands and cropland/natural vegetation mosaics have highturnover in East Asia (53 and 72%, respectively), in Central
Asia (49 and 66%, respectively), and in the Middle East (25and 73%, respectively). Barren and water cover types represent about 35 and 1% of total land area, respectively, butshowed a 15 and 18% turnover across the region, respectively. Intensive use of exposed barren areas has escalated
dust storms, drought severity, and water shortages (e.g.,
Xuan et al. 2000; Chen and Liu 2014). Worse yet, in theFifth IPCC Report, Barros et al. (2014) predicts that thiswater-limited region will experience a warming trend significantly higher than the global mean, which would alter

Fig. 14 Land cover change from 2001 to 2012 based on MODIS LC products for the three regions within DLB

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

summer and winter precipitation patterns and increase thefrequency of extreme climate events with longer, more intense, and more frequent summer heat waves. Cook et al.
(2016) reports that, since 1998, the drought in the eastern
Mediterranean Levant region (Cyprus, Israel, Jordan,
Lebanon, Palestine, Syria, and Turkey) is the worst
drought of the past nine centuries. Furthermore, the
LULCC in DLB is expected to be significantly higher inthe upcoming decades than now (Kelley et al. 2015; Chenet al. 2017), jeopardizing the regional stability and sustainability of the DLB. All of these factors along with its landlocked geographic location make DLB a hotspot for thescientific community concerned with negative consequences of ongoing global change.
By shifting C stocks in soils and vegetation, bothabandonment and intensification strongly impact theregional carbon budget. For instance, the total extra
C sink in abandoned croplands in Kazakhstan(12.9 Mha) over 1991–2010 is estimated to be nearly
31 ± 2 Mt. C year−1, which could compensate annuallyfor about 49% of the current fossil fuel emissions inthis country (Kurganova et al. 2015). Most countries
within the DLB implemented various reform policies
to promote economic growth while improving qualityof life. The new governance and policies increased
GDPs, but at the same time resulted in shifting foodPage 24 of 48

demands, moving towards more processed, high protein animal products, which can drive increases ingrasslands-based livestock production (Chen et al.
2015, 2015).
A regional land use change analysis using MODIS datasuggests differential land use change across the DLB(Fig. 15) with cropland abandonment in the west (zoomwindows at the bottom) and expansion in the east (zoomwindows at right) are driven primarily by shifts in governance and economic development. Therefore, the DLB
has seen increasing demands for food quantity and quality as well as decreasing food production, resulting in
unbalanced pressure on agricultural and pastoral lands(Chen et al. 2015, 2015).
From the perspective of cultural and social norms, theAsian part of DLB shares similarities in history of nomadic herding lifestyles and in geographic proximity.
Totaling 8.82 million km2, Central Asia, Mongolia, andNorthern China includes the largest land-locked countries (Kazakhstan and Mongolia) and has been influenced by some of the most severe geopolitical,
biophysical, and socioeconomic disturbances affecting
societies and simultaneously their livestock, a major
source of food in the region. The region’s total livestockof 209.16 million animals in 1992 increased to 278.3 million in 2011 (33.1% increase). However, livestock in

Fig. 15 Land use and land cover change in the Asian part of the DLB without steppe regions of Siberia from 2001 to 2012 (Qi et al. 2012, 2012
updated). Two zoomed windows show the land use and land cover changes between 2001 and 2012 in a the Central Asia around the
Uzbekistan and b southern border of the Gobi Desert around Lanzhou, China

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

Kazakhstan and Kyrgyzstan decreased substantially (by43.8 and 34.1%, respectively) likely due to the collapse of
the Soviet Union. Empirical relationships among ecosystem production, population density, gross domestic production, and land use remain intrinsically connectedeven with major policy shifts (such as the collapse of theSoviet Union or the new status of China within the World
Trade Organization (Chen et al. 2015, 2015). The underlying mechanisms responsible for these consistent
relationships, as well as their dynamics, remain unknown.
Food security in the Central Asian part of the DLB
critically depends on the water availability from themountains, especially given the drying, browning, andbrightening trends that characterize the region during
the past 15 years (de Beurs et al. 2015). Some countries
started taking practical measures by constructing reservoirs in order to ensure their economic development.
These actions will have short-term benefits, but estimates of contemporary and future water resources thatwill originate from the high mountain cryosphere at theregional scale are needed to develop long-term adaptation and mitigation strategies. These estimates will be
used for socio-economic vulnerability assessments of thebenefits to local communities whose livelihood dependon the quantity and seasonality of water discharges fromthe Central Asian mountains with respect to regionaland national priorities. This specific objective will require the blending of geosciences with social sciences toevaluate the role of high-elevation ice storage in permafrost and glaciers for levels of vulnerability and the resilience of mountain and downstream ecosystems alongwith their inhabitants.
Research focus 7: changes in infrastructure

In the previous sections, we mostly describe environmental and climatic changes in Northern Eurasia in recent decades. They have affected infrastructure of theregion. In particular, the Arctic and Siberia have been
substantially affected by the permafrost changes and its
impact on man-made infrastructure (e.g., buildings, factories, mines, bridges, roadways, and pipelines). In the
boreal zone, gradual onset of drier climate conditions accompanied with more frequent wild fires endangers human settlements, silviculture, and agriculture. In the
DLB, a general depletion of already scarce water resources affects the general well-being of all populationgroups, and all aspects of human activity. These
climate-related impacts on the infrastructure have been
compounded by the marked social, economic, and institutional changes over Northern Eurasia during the past
three decades. Therefore, this section is devoted mostly
to the socio-economic changes attributable to the dramatic political and economic transformations that haveaffected infrastructures of Northern Eurasia.

Page 25 of 48

In Russia, these transformations have been most pronounced in its Arctic regions where regional welfare
critically depends upon the well-being of the entire
country (e.g., Stammler 2005; Forbes et al. 2009;
Kumpula et al. 2011; Pelyasov 2011; Hitztaler andBergen 2013; Andrew 2014). Here, several socioeconomic processes are major anthropogenic drivers ofenvironmental change since the 1960s. These include
migration, urbanization, and industrialization (e.g.,
Heleniak 2010, 2014). Ongoing and projected climateinduced changes in natural systems will impact the human environment with direct, immediate implications
for land use, the economy, subsistence, and social life.
Although some climatic changes may be economicallybeneficial (e.g., decrease in climate severity and associated heating costs, longer navigation season), otherchanges negatively impact the natural environment, bothtraditional and non-traditional sectors of the economy,
and the regional socioeconomic conditions. Overall,these climatic-induced changes in natural conditions
exert additional pressure on the marginal environmentsof Eurasian Arctic, which are already stressed by humanactivities (Fondahl 1996; Crate 2006; Forbes et al. 2009).
For example, infrastructure development and climatechange are interacting in complex ways to alter permafrost over large areas of the Eurasian Arctic (Shur andGoering 2009; Polishchuk and Polishchuk 2013, 2014).
Communities, urban environments, and industrial infrastructure built on ice-rich soils can be catastrophicallyaffected by thawing permafrost (Streletskiy et al. 2012;
Shiklomanov and Streletskiy 2013; Shiklomanov et al.
2017). Simultaneously, permafrost thawing, caused byboth climate and infrastructure changes, affects naturallandscapes and ecosystems (Raynolds et al. 2014;
Khrustalev and Davidova 2007; Khrustalev et al. 2011).
Permafrost thawing and its associated impacts on natural and built environments have been identified as priority issues for all Arctic regions (Walker and Pierce
2015). Due to unprecedented levels of urban and industrial development, this problem is most pronounced for
the Arctic regions of Northern Eurasia.
The Taiga ecoregion of Northern Eurasia has also seen
dramatic pendulum-like shifts in population, infrastructure, and forest resource use between the late Soviet,
early post-Soviet, and the present-day eras. Over thistime span, additional changes in the ecosystems driven
by climate factors have also been accompanied by multiple severe wildfire years. Siberia’s population expanded
by 9 million people (23.5 to 32.5 million) between theyears 1959 to 1989; a similar trend occurred in the RFE.
This was due in large part to state incentives encouraging settlement of these eastern reaches of the Soviet
domain. Thus in these ‘peripheral’ regions away fromthe ‘center’ (Moscow and St. Petersburg), population

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

growth was strongly a product of in-migration and not
intrinsic population growth.
With the relatively sudden withdrawal of statesupported programs, this situation precipitated significant shifts in population and natural resource use in theimmediate post-Soviet era (Voinova et al. 1993; Bergen
et al. 2013). Driven by significant economic hardship,subsequent population out-migration began ~ 1990,
which pervaded East Siberia and the RFE and has only
recently been lessening. In addition to high rates of migration out of the regions altogether, residents also migrated within the regions from rural areas to the few
main cities, resulting in a more urban population.
During the final three decades of the Soviet era, theforestry sector sustained high rates of timber productionin Siberia. Some of this timber was exported to Japan
based on official agreements with Japan in 1958 and1974 (Mathieson 1979) and, in the last decades, to China(Fig. 12). This brought investments in infrastructure.
Despite the otherwise successful commitment of theFederal Forest Service to scientific forestry including thecreation of forest inventory and an exceptional scientificknowledge (Kukuev et al. 1997), late Soviet-era forest
harvest itself was surprisingly inefficient (Shvidenko andNilsson 1994). Immediately after political dissolution in
1991, total harvest volumes significantly declined acrossRussia to approximately 175 million m3 compared to approximately 400 m3 in 1989 (Bergen et al. 2013). Significant growth did not occur again in the forest industry
until approximately 2009.
As governance and institutions have regrouped after
the early post-Soviet transition era, new or renewed developments in forest and energy sectors have emerged.
Resource use in the taiga of Siberia and the RFE is influenced by its proximity to China, Japan, and Korea. These
countries have (a) some of the world’s highest humanpopulation density numbers, (b) either naturally limited
or depleted forest resources, and (c) far-reaching globalindustrial and trade conglomerates (Crowley 2005;
Bergen et al. 2013). Thus, in Russia, the geographic location of forest exploitation is shifting to eastern reaches
that can easily supply and transport logs to the growing
Asian market (Newell and Simeone 2014). This occurs
both through legal forest management and harvest but
also through illegal harvest (Vandergert and Newell 2003).
Siberia and the RFE Taiga regions are also rich in oil,gas, and minerals, i.e., natural resources which are ofgreat current economic and strategic importance.
Within Russia, there may be a greater shift in oil and gas
extraction to East Siberia and the RFE given that the historic large oil reserves of Western Siberia are thought tobe approximately 75% tapped (Dienes 2004). The
Eastern Siberia-Pacific Ocean pipeline has recently been
completed, along with a spur directly into Northern

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China. Most significantly, Russia sees its energy sector
as a strategic central pillar to its re-establishment as a
global economic power (Dienes 2004; Hashim 2010).
Thus, it is likely that energy extraction and associatedinfrastructure will increase.
Communities in the Asian part of DLB are poised between dry and cold weather conditions. Their position isprecarious in the face of multiple forces: climatic variations, extremes, and their changes; environmental degradation and loss of ecosystem services; globalization ofmarkets; rapid population growth and changes to demographic structure; out-migration of the young and able
segments of society with the subsequent brain drain andremittances to the left-behind families. Rural drylandcommunities in Central and East Asia face further challenges and opportunities due to the lingering consequences of the institutional upheaval and uncertainty
following the end of the Soviet Union, China’s market
reforms and increasing regional influence of China. The
DLB region has a low population, but the population is
rapidly increasing. The total population in Central Asia
and Mongolia in 1992 was 54.05 million. In 2011, it increased to 67.09 million, a 24.1% increase over the
20 year period. As might be expected, this population increase is coupled with rapid urbanization, agriculturaldevelopment, and desertification (caused by heavy grazing) across Central and East Asia. The average regional
increase of urban population from 1992 to 2011 was
27.3% with the largest increases occurring in China andTajikistan (both of ~ 50%) and the lowest increase occurring in Kazakhstan (6.4%). In contrast, there is a 10.1%
decrease in urban population in Mongolia.
Along with drastic changes in economics, institution,and governance, land use in the dryland Asia region includes the improvements of major infrastructures, whichhave facilitated the transition of these nations. An obvious example is the region-wide installation of mobile
communication facilities enabling information exchanges
for effective and efficient communications. A second
major infrastructure improvement is the development oftransportation networks including aviation, railways, andhighways across the region that enabled more efficientlogistics management and distribution of goods withincountries as well as trade across countries.
A crucial infrastructure factor in these DLB regions is
a rapid rate of urbanization (Koch and Valiyev 2015). In
particular, real estate development in the decade of the
2000s has led to major lateral expansion as well as vertical build-up that have transformed small cities into
major metropolises. For example, in Kazakhstan, theextent of the Almaty urban agglomeration has increased substantially as observed by the dense sampling
method (DSM) (Nghiem et al. 2009) using NASA satellite scatterometer data in 2000–2009 (Fig. 16). With theGroisman et al. Progress in Earth and Planetary Science (2017) 4:41

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Fig. 16 Almaty urban region in Kazakhstan from DSM satellite observations in 2000 (left) and 2009 (right), translucently draped over 3D topography.
Red represents main urban areas, transitioned into orange for urban area with less development, then to yellow for suburban, and finally to green forrural/natural/wilderness areas. Blue indicates surface water (lakes, reservoirs, etc.). Astounding expansion of the Almaty urban extent occurred between
2000 and 2009

capability to track urban change in three dimensions(Nghiem and Small 2016), DSM results also reveal thesignificant vertical build-up as observed in the Almaty
urban core area with a fast growth rate of approximately 7% per year in terms of the total volume ofbuilding structures in the 2000s (Fig. 17). Such an overheated urbanization rate may result in an excessivebuilding supply that surpasses the building occupancy
rate and thereby may turn the real estate boom into abust.
In Northern China, tremendous urban development
quadrupled Beijing urban extent observed by DSM in
the 2000s and brought along severe air pollution as aconsequence (Jacobson et al. 2015). Similarly, in the

DLB cities such as the complex of Xiangfang, Nangang,and Harbin have experienced multi-fold lateral expansion and significant vertical build up shrouded in smog
due to soaring air pollution from coal combustion andthe petrochemical industry (Huang et al. 2016).
Mongolia has also undergone rapid urbanization similar
to that of many cities in Northern China, resulting inserious air pollution problems caused by automobiles
and industrialization (Batmunkh et al. 2013). In any case,the rapid urban transformation exerts a high demand for
rapid infrastructure development, such as road networks
not only for intra-urban but also for inter-urban connectivity to support the commercial and industrial activities for the increasing population.

Fig. 17 Dramatic increase in the total building volume corresponding to the real estate boom since 2000 in an area of ~ 6 km2 centered in theurban extent of Almaty in 2009 seen in red in the right panel of Fig. 16. Error bars show the accuracy of regional averaged values (columns) andincorporate together errors of the observation and area-averaging methods used. The linear trend line indicates the mean rate of the building
volume increase during the study period and its comparison with error bars shows that the changes are clearly seen beyond the noise generated
by observations and the averaging procedureGroisman et al. Progress in Earth and Planetary Science (2017) 4:41

Complex interactions among a rapidly changing climate and the continuously evolving social, economic,
and political systems in Northern Eurasia require an integrative approach for studying the cumulative effects ofinfrastructure and climate change on high-latitude
social-economic and natural systems. This researchshould focus on assessing the vulnerability of communities, industries, and ecosystems and should aim at developing adaptation and mitigation strategies and plans forthe sustainable development of the Arctic infrastructure.
The high latitudes of Eurasia, the largest and most dynamically complex northern region, can serve as a basis
for developing effective climate mitigation policies andadaptation measures for global circumpolar north. The
observed disparity of changes among the DLB countries
hints that the socioeconomic factors define the resilienceof these countries to ongoing changes and not so muchthe climatic factors.
Research focus 8: societal feedbacks in response toenvironmental changes

In the distant past, humans reacted to environmental
changes passively—they migrated away from environmentsthat became adverse or unsustainable. Nowadays, manysocieties are equipped with tools and resources to withstand the negative consequences of environment change,
to some extent. Common approaches to addressing
adverse environmental changes include irrigation, construction of dams and dikes, diversion of water streams,
large-scale geo-engineering projects (e.g., reforestation),
mandatory ecological standards to curb pollution, more effective agronomic practices and robust crops, new construction codes, and the application of ecological expertiseto each new large development.
Planning is also now beginning to be practiced to reduce the adverse impact of disasters associated with environmental changes and to increase the resilience ofthe communities at risk. Implementation of these activities has associated costs and requires careful planning
based upon numerical experiments with models thatrealistically describe processes of environmental
changes in all their complexity and interactions. It
should also consider disruptive effects of environmental
hazards given the uncertainty of the future environment state and the trend of increasing frequency of loss
events and damage produced by disasters and creeping
environmental crises globally (Fig. 18) and also regionally (Porfiriev 2001, 2016). The need for a suite of suchmodels is more urgent when the risks of negative consequences of environmental change are higher(Porfiriev 2012, 2013, 2014).
Human activities have been the drivers of certain ongoing environmental changes. It is important torecognize the loop: societal feedbacks in response to

Page 28 of 48

these changes may facilitate the recurrence of disasters
or cause a second cycle of inadvertent environmental
change if the response misses the target or is illdesigned. For instance, reforestation may cause more intense rainfall and dykes may increase flood peaks.
Curbing industrial development may negatively impact
human well-being and overall societal resilience. Thismeans that studies of the impact of environmental
changes on societies and the development of adaptationand mitigation measures in response to their detrimental
consequences should be accompanied by thorough assessments of the “end state” resulting from the environmental changes and the actual and projected societal
response to these changes. This can be implemented only
by mainstreaming all these kinds of impacts and feedbacks
into comprehensive Earth system and integrated assessment models (see the next section of this paper).
Research focus 9: quantification of the role of NorthernEurasia in the global earth and socioeconomic system

Northern Eurasia is a key part of the global Earth andsocioeconomic systems. It occupies a substantial portionof the land surface of the Earth (19%) and 60% of land
surface north of 40° N. Northern Eurasia is where someof the largest climatic, environmental, and socioeconomic changes have occurred during the past century. In many aspects, changes here presage the rates ofglobal change including global temperature rise (cf.,Fig. 3 versus Fig. 2). The strength of the snow covertemperature biogeophysical feedback, biogeochemical
feedback due to depletion of the surface and upper soil
layer carbon and frozen ice storages (Fig. 7; Romanovsky
et al. 2010, 2010; Schepaschenko et al. 2013; Shakhova
et al. 2015), atmospheric dust load from extensive DLB
desert areas (Lioubimtseva and Henebry 2009, Sokolik
2013; Sokolik et al. 2013), and atmospheric pollution
from industrial development (Lu et al. 2010) and fromboreal forest fires (Soja et al. 2007) affect the global climate and environment. Large areas of natural and anthropogenic land cover change are closely related to theinteraction of the cryosphere and terrestrial hydrology
change (Tchebakova et al. 2009; Zhang et al. 2011,
Mátyás and Sun 2014; Fig. 4) with human activities (Qiet al. 2012, 2012; Chen et al. 2013, 2015; Horion et al.
2016, Figs. 12 and 15). The importance of these changes
and associated impacts on Northern Eurasia and potential feedbacks to the global Earth and socioeconomic
systems may be quantified using models.
Global change modeling for Northern Eurasia

As discussed in the previous sections, Northern Eurasia
is comprised of a complex and diverse set of physical,
ecological, climatic, and human regional systems, which

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

Page 29 of 48

abFig. 18 The frequency (a) of and monetary losses (b) from the major natural and environmental disasters across the globe. Source: Munich Re-insurance
NatCatSERVICE (http://www.munichre.com/en/reinsurance/business/non-life/natcatservice/index.html)

interact among themselves and can have potentially important feedbacks on the evolution of the global Earthand human systems. At the same time, the region has
experienced dramatic climate, environmental, and socioeconomic changes, which leads us to argue that studying
the fate of Northern Eurasia needs to be placed in thecontext of global change modeling (i.e., the modeling of
the coupled human and Earth systems at the global
scale) and include interactions with other regions of the
globe. In this section, we review past and ongoing modeling studies over Northern Eurasia and provide new approaches for integrated modeling for Northern Eurasia.
Past and ongoing modeling studies over Northern Eurasia

Many models have been developed and used to study
various components of the Earth system with a focus on
Northern Eurasia. Monier et al. (2017) provides an overview of recent and ongoing modeling studies over
Northern Eurasia and identifies the many ecological andgeophysical processes comprising Earth system dynamics(i.e., the hydrological cycle, soil thermal dynamics, wildfires, dust emissions, carbon cycle, terrestrial ecosystem
dynamics, climate and weather, sea ice) and the humandimensions (i.e., demography, risk management addressed, agriculture, forestry, water management)
addressed by the Northern Eurasia modeling community. Because of the major role of Northern Eurasia in
the global land system, they find that most studies focus
on the land processes (i.e., land and water carbon cycle,
energy balance) or on the fate of the land system underclimate change (permafrost thawing, agriculture, wildfire). They also find that most studies focus on a single
component of the Earth system, with generally little attention placed on interactions and feedbacks, and withclimate change being imposed. Nonetheless, Monier etal. (2017) identify a few studies that try to integrate various aspects of the Earth system, in terms of scale, teleconnection or global feedbacks, and processes, as well asother studies focusing on integrated systems where multiple disciplines overlap, such as modeling studies ofwater management (Shiklomanov et al. 2013) or land
management (Gustafson et al. 2011, 2011; Kuemmerle etal. 2011, 2011, 2014; Lebed et al. 2012; Loboda et al.
2012; Robinson et al. 2013; Shuman et al. 2013a; Blyakharchuk et al. 2014). This growing effort to integrate
existing models through scale, processes, and feedback

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

has translated into more coordinated and multidisciplinary research projects by NEESPI scientists alongwith the development and integration of models that
can interact with each other, including weather andaerosol physics, permafrost, and terrestrial hydrology
with water management, the carbon and water cycles,
land carbon and atmospheric transport modeling, andbiospheric and climate information (Table 1).

Page 30 of 48

Modeling studies focusing on a specific component of
the Earth system have provided valuable insight into
processes controlling their behavior and the direct impact of climate change. Meanwhile, more integrated
modeling studies have been useful for identifying andquantifying potential interactions and feedbacks among
various components of the Earth system and societal activities associated with environmental changes overTable 1 Non-exhaustive list of modeling studies with a focus on Northern Eurasia. The list is sorted by specific aspects of the Earthand human systems. Some studies are listed under several aspects of the Earth and human systems. From Monier et al. (2017updated)Specific aspects of the Earthand human systems

References to modeling studies with a focus on Northern Eurasia

Agriculture(crop modeling, economics)

Dronin and Kirilenko 2010; Gelfan et al. 2012; Iizumi and Ramankutty 2016; Magliocca et al. 2013; Peng et al. 2013;
Schierhorn et al. 2014, 2014; Tchebakova et al. 2011

Air quality
Baklanov et al. 2013; Darmenova et al. 2009; Lu et al. 2010; Siljamo et al. 2013; Sofiev et al. 2013; Soja et al. 2004;(aerosols, ozone, pollen, dust) Sokolik et al. 2013; Xi and Sokolik 2015a, 2015b
Carbon (in land and water)

Bohn et al. 2013, 2015; Cresto-Aleina et al. 2015; Dargaville et al. 2002, 2002; Dass et al. 2016; Dolman et al. 2012;
Gao et al. 2013; Glagolev et al. 2011; Gustafson et al. 2011; Hayes et al. 2011, 2011, 2014; John et al. 2013;
Kicklighter et al. 2013, 2014; Kim et al. 2011; Koven et al. 2011; Kuemmerle et al. 2011, 2011; Kurganova et al. 2014, 2015;
Lu et al. 2009; McGuire et al. 2010; Mukhortova et al. 2015; Narayan et al. 2007; Olchev et al. 2009, 2013; Rawlins et al. 2015;
Rossini et al. 2014; Sabrekov et al. 2014, 2016; Saeki et al. 2013; Schaphoff et al. 2015; Schierhorn et al. 2013;
Schulze et al. 2012; Shakhova et al. 2013, 2015; Shuman and Shugart 2009; Shuman et al. 2013a; Yue et al. 2016;
Zhang et al. 2012b; Zhao et al. 2009; Zhu et al. 2013, 2014; Zhu and Zhuang 2013; Zhuang et al. 2013

ClimateAnisimov et al. 2013; Arzhanov et al. 2012, 2012; Miao et al. 2014; Monier et al. 2013; Onuchin et al. 2014;
Shahgedanova et al. 2010; Shkolnik and Efimov 2013; Volodin 2013; Volodin et al. 2013; Zuev et al. 2012

Cryosphere(snow, glaciers, sea ice)

Callaghan et al. 2011a, 2011b; Farinotti et al. 2015; Hagg et al. 2006; Klehmet et al. 2013; Loranty et al. 2014;
Mokhov et al. 2013; Pieczonka and Bolch 2015; Shahgedanova et al. 2010; Shakhova et al. 2015;
Sokratov and Shmakin 2013; Sorg et al. 2012

Demography

Heleniak 2015

Energy balance

Brovkin et al. 2006; Gálos et al. 2013; Loranty et al. 2014; Olchev et al. 2009; Oltchev et al. 2002; Tchebakova et al. 2012

Hydrological cycle

Bowling and Lettenmaier 2010; Cresto-Aleina et al. 2015; Gelfan 2011; Georgiadi et al. 2010, 2014a; Hagg et al. 2006;
Karthe et al. 2015; Khon and Mokhov 2012; Kicklighter et al. 2013; Klehmet et al. 2013; Kuchment et al. 2011;
Liu et al. 2013, 2014, 2015; McClelland et al. 2004; Motovilov and Gelfan 2013; Novenko and Olchev 2015;
Olchev et al. 2009, 2013; Oltchev et al. 2002, 2002; Osadchiev 2015; Rawlins et al. 2010; Serreze et al. 2006;
Shiklomanov et al. 2013; Shiklomanov and Lammers 2013; Shkolnik et al. 2017; Sorg et al. 2012; Streletskiy et al. 2015;
Troy et al. 2012; Zhang et al. 2011Land-use change

Blyakharchuk et al. 2014; Chen et al. 2017; Griffiths et al. 2013; Gustafson et al. 2011; Hayes et al. 2011;
Hitztaler and Bergen 2013; Kicklighter et al. 2014; Kraemer et al. 2015; Kuemmerle et al. 2009; Meyfroidt et al. 2016;
Peterson et al. 2009; Prishchepov et al. 2013, 2017; Robinson et al. 2013; Schierhorn et al. 2013, 2014, 2014;
Smaliychuk et al. 2016; Zhang et al. 2015

Infrastructure

Shiklomanov and Streletskiy 2013; Shiklomanov et al. 2017; Stephenson et al. 2011; Streletskiy et al. 2012

Nitrogen

Kopáček et al. 2012; Kopáček and Posch 2011; Oulehle et al. 2012; Zhu and Zhuang 2013; Zhuang et al. 2013

Permafrost

Euskirchen et al. 2006; Gao et al. 2013; Gouttevin et al. 2012; Hayes et al. 2014; MacDougall and Knutti 2016;
Marchenko et al. 2007; Shakhova et al. 2013, 2015; Shkolnik et al. 2012; Streletskiy et al. 2012, 2015; Zhang et al. 2011

Terrestrial ecosystems
characteristics

Cresto-Aleina et al. 2013; Kopačková et al. 2014, 2015; Lapenis et al. 2005; Lebed et al. 2012; Li et al. 2016;
Shuman et al. 2013a, 2013b; Shuman and Shugart 2012; Ziółkowska et al. 2014

Vegetation shifts

Gustafson et al. 2011; Jiang et al. 2012, 2016; Khvostikov et al. 2015; Kicklighter et al. 2014; Li et al. 2014;
Macias-Fauria et al. 2012; Novenko et al. 2014; Schaphoff et al. 2015; Shuman et al. 2015; Soja et al. 2007;
Tchebakova et al. 2009, 2010, 2016, 2016; Tchebakova and Parfenova 2012; Velichko et al. 2004

Weather(i.e., extreme events)

Barriopedro et al. 2011; Meredith et al. 2015; Mokhov et al. 2013; Schubert et al. 2014; Shkolnik et al. 2012

Wildfire

Balshi et al. 2007; Dubinin et al. 2011; Gustafson et al. 2011; Kantzas et al. 2013; Loboda and Csiszar 2007;
Malevsky-Malevich et al. 2008; Narayan et al. 2007; Park and Sokolik 2016; Schulze et al. 2012; Soja et al. 2004;
Tchebakova et al. 2009, 2012; Vasileva and Moiseenko 2013

Zoology

Bragina et al. 2015; Kuemmerle et al. 2011, 2014; Ziółkowska et al. 2014

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

Northern Eurasia. However, most studies of climatechange impacts rely on standard socio-economic and climate change scenarios, thus limiting the possibility of
conducting integrated studies. A common experimental
design for these studies is to prescribe climate change
and to examine the varied response of a particular component of the Earth system (Rosenzweig et al. 2014). In
such an approach, many potential global and regional
feedbacks that can have major implications for the climate system, both in Northern Eurasia and globally, areoverlooked. The development of effective climate mitigation and adaptation strategies for Northern Eurasia depends on understanding how environmental conditions
may evolve in the region within the context of globalchange, including the influence of feedbacks and potential thresholds (i.e., “tipping points”). Fortunately, modeling frameworks have already been developed to study
these issues (see the next section), and they could be improved to better represent the important aspects of the
Earth system that are unique to Northern Eurasia.
New approaches to integrated modeling for Northern Eurasia

Earth System Models (ESMs; Brovkin et al. 2006, 2013;Friedlingstein et al. 2006; Arora et al. 2013; Eby et al.
2013; Zickfeld et al. 2013; Koven et al. 2015; Zaehle etal. 2015) have been developed by coupling together
unique Earth system component models (e.g., atmosphere, land, cryosphere, oceans). These provide an ideal
modeling framework to investigate interactions andfeedbacks among these components as well as the impact of changes in Northern Eurasia on the global Earthsystem. For example, in an ESM, carbon emissions fromland-use change in Northern Eurasia may increase atmospheric carbon dioxide concentrations to influence
climate, the uptake of atmospheric carbon dioxide byoceans to influence ocean acidification, and the uptakeof atmospheric carbon dioxide by land vegetation in the
future. ESMs provide tools to investigate the response of
the system to changes in external forcings that not only
affect each of the components individually but also theinteractions among them. For example, climate change
impacts cannot be examined without considering therole of human activity. In current ESMs, however, there
is a simple representation of the influence of human activity on earth system components. Anthropogenic effects related to industrial, residential, and agriculturalactivities may be represented by simply prescribing an
input of greenhouse gases into the atmosphere. More sophisticated ESMs might also use prescribed changes inland use across the globe to simulate the effects ofspatial and temporal variations in albedo, sensible andlatent heat fluxes, and greenhouse gas fluxes on regionaland global energy budgets. In these ESM studies, thesimulated human activity is determined solely byPage 31 of 48

prescribed policies without any consideration about how
feedbacks from changing environmental conditions
might modify these activities in the future. For example,
the land use change prescribed in CMIP5 simulations isdriven solely by socio-economic considerations and does
not account for climate change impacts on land productivity (Hurtt et al. 2011).
Because ecological and social systems are interdependent and constantly co-evolving, their non-linear behavior
is difficult to predict. Taking into account that humanwell-being and ecosystem integrity are fundamentally
linked, these processes must be managed in a way that
implies balancing economic capacity, environmental integrity, and resilience to future changes (Jones et al.
2013; DeLucia 2015). For this reason, another major effort has been put into the linkage between models of human activity, including the global economy, global trade,demography, technologies, and user preferences—which
are essential to study the potential impacts of humanson the environment—and models of the physical climate
system, generally simplified compared to ESMs. Thesemodels are known as integrated assessment models andallow economic decisions to respond to changing environmental conditions to support mitigation and adaptation efforts (IAMs; Rotmans et al. 1990; Alcamo et al.
1994; Weyant et al. 1996; Prinn et al. 1999; Sokolov et al.
2005, 2009; van Vuuren et al. 2006, 2007; Riahi et al. 2007;
Hijioka et al. 2008; Melillo et al. 2009, 2016; Wise et al.
2009; Reilly et al. 2012; Hallgren et al. 2013; Prinn 2013;
Nelson et al. 2014, 2014; Sue Wing et al. 2015).
IAMs have been at the core of the Representative
Concentration Pathways (RCPs, van Vuuren et al. 2011),
a set of socio-economic and emission scenarios, including socio-economic change, technological change, energy and land use, and emissions of greenhouse gases
and air pollutants, developed for the climate modelingcommunity in support of the IPCC AR5.
More recently, major efforts have focused on developing models with a detailed representation of all components of the coupled Human-Earth system, by coupling
IAMs with ESMs, or essentially replacing the simplified
representation of the climate system in IAMs with
ESMs. Such models can provide novel insights into thecomplex issue of global change by accounting for an exhaustive number of feedbacks among the components ofthe Earth system and of the human system.
Figure 19 shows an example of a coupled humanEarth system model, with three pathways for feedbacks
between the two systems. The first pathway includes thehuman activity model providing emissions of greenhousegases, aerosols, and other precursors of atmospheric pollution, thus providing the footprint for both future climate change and air quality, with a feedback on thehuman system through health impacts. The second

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

Page 32 of 48

Fig. 19 An example schematic of an integrated assessment model (IAM) that couples a human activity model and an Earth system model (ESM)with a focus on three feedback pathways: health, land use change, and water resources (from Monier et al. 2017). See text for details

pathway centers on land, with the human activity model
making decisions on land use change based on natural
ecosystem productivity and crop yield. Finally, the third
pathway centers on water, with the Earth system modelcomputing basin-wide geophysical water resources andthe irrigation demand from crops, and the human systemmodel making economically based decisions on water
availability for irrigation, with competition from municipal
and energy use. The global and regional climate would inturn be affected by land use and land cover change and irrigation, through both emissions of greenhouse gases,changes in albedo and in the hydrological cycle.
At the frontier of integrated assessment modeling, anumber of issues have emerged that can be better examined with the ongoing development of coupled humanEarth system models for Northern Eurasia (Monier et al.
2017) and include the following: The food-energy-water (FEW) nexus. While the

FEW is a global issue and major efforts areunderway to improve its representation in models of
the coupled human-Earth system, it also has uniquecharacteristics over Northern Eurasia that require
specific improvements for such models to be useful,including thermokarst dynamics, permafrost
degradation, scarcity of human infrastructure, variedlevels of agricultural development and management
practices, locally diverse hydrological conditions
associated with complex biomes, and climate
interactions.
 The air quality and health nexus. In addition to the
traditional anthropogenic precursor emissions
associated with the industry, energy andtransportation sectors, or biogenic emissions ofprecursors, Northern Eurasia experiences varied andcomplex sources of air pollution, including wildfires,
crop residue burning, and dust. Accounting forthese sources of pollutants, specific to NorthernEurasia, along with the transport of pollutants toand from surrounding countries, to quantify theGroisman et al. Progress in Earth and Planetary Science (2017) 4:41

economic impact of future changes in air
pollution in the region can prove key toaccurately inform policy responses for NorthernEurasia.
 The new transnationalism of natural resources. The
more porous international borders that haveemerged after the dissolution of the former Soviet
Bloc have considerable implications for NorthernEurasia’s natural resources. In particular, forest
resources, but also oil and gas, are at the nexus ofregional demand due to uneven distributions within
the countries of Northern Eurasia. Understanding
and developing levels of sustainable use will have
implications ranging from local human livelihoods
to the global carbon budget. Integrated models willneed to include local, regional and, now, eveninternational drivers and consequences of these
coupled human-natural systems pertaining tonatural resources.
 The opening of new Arctic trade routes. New traderoutes emerging as the result of the shrinking ofArctic sea ice extent could result in the ability of thetimber industry and energy exploration to reachremote areas like Siberia. The development of
infrastructures to respond to these new economic
opportunities, including potential population
migration within Northern Eurasia and fromneighboring regions, will face challenges such aswith climate-driven permafrost degradation or thedisappearance of temporary roads constructed overfrozen lakes and rivers. Investigating the fate ofNorthern Eurasia as these new trade routes emerge
will require a detailed regional coupled human-Earthsystem model.
As with any model activity, the representation of interactions and feedbacks among Earth system components
and societal activities in Northern Eurasia can be improved within models, in order for these models to address such emerging issues. Insights gained fromprevious and ongoing efforts by the NEESPI/NEFI research community, such as those on the unique featuresand processes of Northern Eurasia described above,
could be incorporated to guide these model improvements to create a new generation of coupled humanEarth system models to study the role of NorthernEurasia on global change. For example, most ESMs do
not have a representation of permafrost dynamics, which
is important for Northern Eurasia as the presence of
permafrost affects the availability of soil moisture andthe timing and magnitude of runoff (which are important for the FEW nexus), the ability to support buildings
and other infrastructure (which is important for thesocio-economic development of remote regions inPage 33 of 48

Siberia as Arctic trade routes open up after the sea ice
retreat), and vegetation primary production rates anddecomposition rates of organic matter (which influence
the ability of the landscape to provide food, energy, andtimber and impact the timing, extent, and severity of
wildfires, which in turn, impact air quality and health).
In addition, the degradation of permafrost might also be
associated with several important tipping points including those related to water availability and the release ofland carbon to the atmosphere. The representation of
permafrost dynamics in ESMs could strongly benefit
from an improved representation of soil thermal dynamics, as influenced by water, ice, organic matter and soil
texture in the soil profile, and of the surface insulating
layer and its modification by snow cover, moss, litter, or
wildfires. Furthermore, we suggest that to improve key
processes relevant to Northern Eurasia in ESM and
IAM, like permafrost degradation, a stronger involvement of the Northern Eurasia modeling community andlocal stakeholders is needed.

Conclusions
The major goal of this paper is to introduce the reader
to the present challenges in Northern Eurasia and tooutline the pathways forward to address these challenges
in the coming decades. In doing so, we have provided
the reader with a sample of exemplars of NEESPI’s accomplishments. The science questions of the “NorthernEurasia Future Initiative” or NEFI derive from an urgent
need to incorporate and expand our knowledge of theconsequences of human and social dimensions in assessing current and future change in Northern Eurasia.
Across this region, the future strongly depends upon thisincorporation and the amelioration of environmental
change, the effects of these changes on human societies,
and bridging the considerable gaps in research
procedures, capacity for prediction, and in time- andspace-scales that complicate the integration of humandynamics with environmental dynamics.
When the embryonic NEESPI project began over a
decade ago, there were concerns that a program spanning Eurasia involving scientists from multiple disciplines based in a score of nations with complex andsometimes opposing diplomatic missions could havebeen a failure. However, there were several significant
factors that brightened and opposed such a dark forecast. Truly, interdisciplinary interactions among engaged
scientists who tackled a shared problem are a remarkable glue for holding research projects together, and they
proved that creativity can prosper in “bottom-up” research programs. The role of Northern Eurasia as a recipient and generator of planetary climatic change is an
important “big question” that captures the imagination

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

of many scientists and transcends disciplines, cultures,
languages, and national politics. It is also a challenge
whose unraveling requires teams working together
openly in earnest and in good faith. The consequencesof environmental and socio-economic change in Northern Eurasia that may spread well beyond its boundaries
have been simply too dire to leave them unstudied and,generally speaking, unknown. NEESPI was born to reverse the situation by elucidating both negative andbeneficial aspects of these changes to inform societies
and, thus, better prepare them for resilient future development. An objective of NEFI is that this development
must now be secured by science-based strategies provided to regional decision-makers at different levels thatwill lead their societies to prosperity.
Northern Eurasia has undergone significant environmental change, having experienced warming in the pastfew decades that already exceeds the 1.5 to 2.0 °C warming limits adopted as a target at the United Nations
Climate Change Conference (30 November−12
December 2015, Paris, France). Several aspects of thiswarming are manifested in changes in the regional energy and hydrological cycles, which affect and interact
with the biosphere and with socio-economic activities.
These changes are multifaceted. Some of them seem andare inevitable (e.g., ecosystems’ shift, glacial retreat andpermafrost thawing, increased fire regimes, the new stateof the regional environment); however, it is imperative
they are acknowledged and comprehended. Some ofthese changes, particularly if their consequences are adverse for human well-being, can be reversed, moderated,or mitigated—hopefully to levels that will completely or
substantially negate their undesirable impacts. These latter instances include proactive and sometimes quite
expensive interventions in water management, forestry
and agricultural practices, environmental protection,
infrastructure and urban planning, and resource consumption. In any case, the scientist’s duty is to
propose and justify strategies for resilient future development in the region. “To justify” is a key word
here. Scientists must strive to know the Earth system
in its functional entirety to develop the tools necessary to project the future state in response to naturaland societal impacts, as well as to estimate the overall
consequences of the realization of these scenarios onhuman wellbeing.
To these ends, we have formulated three major science
questions to be answered by NEFI:
1) How can we quantify and project ecosystem
dynamics in Northern Eurasia when these dynamics
may be internally unstable, are controlled bycomponents that have been systematically changing,and have a potential to impact the global Earth

Page 34 of 48

system with unprecedented rates of change over the
next few decades?
2) What are the major drivers of the ongoing andfuture changes in the water cycles of NorthernEurasia and how will their changes affect regional
ecosystems and societies, and feedback to the Earthsystem and global economy?
3) How can the sustainable development of societies ofNorthern Eurasia be secured in the near future by
overcoming the ‘transitional’ nature of theireconomics, environmental and climatic change
challenges, and by disentangling restrictive
institutional legacies?
To address these science questions, nine research fociare identified and their selection has been briefly justified in this paper. These research foci are (1) globalchange influence, particularly warming in the Arctic; (2)increasing frequency and intensity of extremes andchanges in the spatial and temporal distributions of inclement weather conditions; (3) retreat of the cryosphere; (4) changes in the terrestrial water cycle; (5)changes in the biosphere; (6) pressures on agriculture
and pastoral production; (7) changes in infrastructure;(8) societal actions to mitigate the negative consequences of environmental change and to benefit fromthe positive consequences; and (9) quantification of therole of Northern Eurasia in the global Earth and socioeconomic systems to advance research tools with an emphasis on observations and models. The socio-economic
research challenges are integral to and a top priority forthese research foci.
Taking into account the numerous powerful feedbacks
between the Earth and human systems in Northern Eurasia, we propose to employ integrated assessment
models (IAMs) at the final stage of this global change
assessment. The purpose of these IAMs is to couple
Earth system component models with the result being afunctioning integrated Earth system model. Simultaneously, models of the human system that represent the
global economy, global trade, demography, technologies,
and user preferences will be incorporated. These will
provide support to economic and societal decisionmakers, so they are able to thoughtfully respond tochanging environmental conditions to support mitigation and adaptation efforts. Development of IAMs which
include detailed representation of all components of thehuman-Earth coupled system to account for the exhaustive number of feedbacks among these components is theoverarching goal of NEFI global change research. Thesemodels will provide information and guidance todecision-makers in their efforts to secure sustainable
and prosperous societal development and resiliencebased ecosystem stewardship in Northern Eurasia.

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

Finally, Northern Eurasia presents a range of complex
human and environmental systems varying from modern
industrial societies to traditional indigenous cultures, allundergoing significant social and environmental change.
Certainly, the continuing transformation of the former
USSR, China, Mongolia, and Eastern Europe represents
one of the largest and most profound social changes ofrecent decades. Through NEFI, the work in NorthernEurasia is moving to more effectively address sharedgoals with interdisciplinary programs at the global level.
The research record that will stand as the basis fromwhich to launch NEFI is a logical consequence of the accomplishments of NEESPI. This situation and the needfor progress is critical. Now is the time to press forwardwith this opportunity. The challenge lies before us.
Abbreviations
ACIA: Arctic Climate Impact Assessment; AMAP: Arctic Monitoring andAssessment Programme; AR5: The Fifth IPCC Assessment Report; BP: Before
present; CGCM3.1: Canadian Centre for Climate Modeling and Analysis Model,
3rd version; CMIP5: Coupled Model Intercomparison Project Phase 5; DLB: Dryland belt of Northern Eurasia; DSM: Dense sampling method; ERA-interim: Global
atmospheric reanalysis developed at the European Centre for Medium-Range
Weather Forecasts; ESM: Earth system model; GCM: Global climate model;
GHG: Greenhouse gases; GLABTOP2: Glacier base topography model, 2ndversion; GPR: Ground-penetrating radar; GRACE: Gravity Recovery Satellite
Experiment; GTN-P: Global Terrestrial Network for Permafrost; GTOS: Global
Terrestrial Observing System; HadCM3: UK Hadley Centre Climate Model, 3rdversion; IAM: Integrated assessment model; ICSU: International Council for
Science Union; IPCC: Intergovernmental Panel on Climate Change;
IPCLCM4: Institute Pierre Simon Laplace Climate Model, 4th version; LC/LU: Land
cover/land use; LCLUC: Land cover and land use change; MODIS: Moderate
resolution imaging spectroradiometer; NEESPI: Northern Eurasia Earth Science
Partnership Initiative; NEFI: Northern Eurasia Future Initiative; RFE: Russian Far East;
RubCliM: Large-scale bioclimatic envelope model; SibCliM: Siberian bioclimatic
model; SIE: Sea ice extent; WMO: World Meteorological Organization
Acknowledgements
All authors of this paper are also the authors and the members of the NEFI
Science Plan Preparation Team. Other Members of the NEFI Science Plan
Preparation Team are the following:
Elena Parfenova, Russia; Daniel Brown, USA; Yizhao Chen, China; Alexander
Georgiadi, Russia; Vladimir Gershenzon, Russia; Evgeny Gordov, Russia;
Serguei Ivanov, Ukraine; Martin Kappas, Germany; Julia Kurbatova, Russia;
Richard Lawford, USA; Guoping Lei, China; Sergey Marchenko, USA;
Alexander Olchev, Russia; Irina Danilovich, Belarus; Vladimir Romanovsky,
USA; Dmitry Schepaschenko, Austria; Andrei Sokolov, USA; Dmitry Streletskiy,
USA; Margarita Syromyatina, Russia; Natalia Tilinina, Russia; Xiaoping Xin,
China; Panmao Zhai, China; Tatiana Blyaharchuk, Russia; Lin Zhen, China.
Special credit to Alan Cantin, Canadian Forest Service, Natural Resources
Canada, who prepared climate change scenarios used in biosphere model
simulations for Fig. 4 of this paper and Deborah Misch, Telesolv Consulting,
USA for preparation of high quality figures of this paper.
Funding
Support for most of the US authors and contributors of this paper as well as
the multiannual support for the office of the NEESPI Project Scientist wasprovided by the NASA Land Cover and Land Use Change (LCLUC) Program, inparticular, by grants NNX13AC66G, NNX11AB77G, NNX13AN58G, NNX15AD10G,
NAG5–11084, 08–LCLUC08–2–0003, NNX14AD88G, NNX08AW51G,
NNX12AD34G, NNX14AD91G, and NNX15AP81G. The research carried out at
the Jet Propulsion Laboratory, California Institute of Technology, was also
supported by the NASA LCLUC Program. Support of NASA grants 08–TE08–029
and NNH09ZDA001N–IDS for AS and NT are acknowledged. Research of MS is
supported by Newton-al-Farabi Fund (grant 172722855). Grant 14.B25.31.0026
of the Ministry of Education and Science of the Russian Federation provided
support to PG, SG, NT, AS, OB, BP, and IP for their work conducted at the P.P.

Page 35 of 48

Shirshov Institute of Oceanology. The Project “ARCTIC-ERA: ARCTIC climatechange and its impact on Environment, infrastructures, and Resource
Availability” sponsored by: ANR (France), RFBR (Russia), and the US NSF(grants 1717770 and 1558389) in response to Belmont Forum Collaborative
Research Action on Arctic Observing and Research for Sustainability
provided support for OZ, SG, BP, PG, and NS. A part of the paper is basedon the research carried out with the financial support of the RussianFoundation for Basic Research (Project No. 15–06–08163 “Assessment andforecast of the socioeconomic and environmental implications of theclimate change in the Arctic region”). Support for AP is provided by the
Russian Government Program of Competitive Growth of Kazan Federal
University (OpenLab Initiative). Support for JA is provided by grant
NPUILO1417 of the Ministry of Education, Youth and Sports of Czechia.
Authors’ contributions
PG, HS, GG, SM, and SG proposed the topic, conceived, and designed thisoverview. They wrote the “Introduction” part of the manuscript. Other major
contributors to the Introduction Section are NS, ASo, and JQ. Major
contributors to section on “Three unique features of Northern Eurasia ofglobal concern and their related major science questions” are PG, NT, JQ, HS,
NS, GH, KB, TL, AP, and DK. Each author of the paper has contributed to the“Major research foci” section of the paper. EM and DK are the major
contributors to section devoted to “Global change modeling in NorthernEurasia” of the paper. HS and PG were the major contributors to the“Conclusions” section. All authors read and approved the final manuscript. All
Authors suggested numerous editorial corrections to the manuscript. In
addition to scientific contributions, the language editorial service wasprovided by the authors, who are the native English speakers: HS, DK, GH,
KB, KdB, ASo, and JM.
Authors’ information
All authors and contributors of this paper are the members of the NorthernEurasia Earth Science Partnership Initiative (NEESPI) and the Northern Eurasia
Future Initiative (NEFI) (http://neespi.org).
Competing interests
The authors declare that they have no competing interest.

Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims inpublished maps and institutional affiliations.
Author details
1
NEESPI Project Scientist, NC State University Research Scholar, at at NOAA
National Centers for Environment Information, Federal Building, 151 Patton
Avenue, Asheville, NC 28801, USA. 2Department Environmental Sciences,
University of Virginia, 291 McCormick Drive, Charlottesville, Virginia
22904-4123, USA. 3The Ecosystems Center, Marine Biological Laboratory,
Woods Hole, MA 02543, USA. 4Geospatial Sciences Center of Excellence,
South Dakota State University, 1021 Medary Avenue, Wecota Hall 506B,
Brookings, SD 57007-3510, USA. 5Sukachev Institute of Forest, SB RAS–Federal
Research Center “Krasnoyarsk Science Center SB RAS”, 50/28
Akademgorodok, Krasnoyarsk 660036, Russia. 6National Institute forEnvironmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
7
Joint Program of the Science and Policy of Global Change, Massachusetts
Institute of Technology, Cambridge, MA 02139-4307, USA. 8NASA
Headquarters, The NASA Land-Cover/Land-Use Change Program, Mail Suite
3B74, Room 3Y77, 300 E Street, SW, Washington, DC 20546, USA. 9P.P.
Shirshov Institute of Oceanology, RAS, 36 Nakhimovsky Ave, 117218 Moscow,
Russia. 10Department of Geography, Michigan State University, 673
Auditorium Rd, East Lansing, MI 48824, USA. 11Department Geosciences andNatural Resource Management, Section of Geography, University of
Copenhagen, Øster Voldgade 10, 1350 København K, Denmark. 12Institute for
Economic Forecasting, RAS, 47 Nakhimovsky Ave, 117418 Moscow, Russia.
13
Earth Systems Research Center, University of New Hampshire, Morse Hall, 8College Rd, Rm. 21, Durham, NH 03824, USA. 14Department GeographicalSciences, University of Maryland–College Park, 1121 LeFrak Hall, 7251
Preinkert Drive, College Park, MD 20742, USA. 15Department of Geography,
George Washington University, Old Main Bldg, 1922 F Street, NW,
Washington, DC 20052, USA. 16Jet Propulsion Laboratory, California Instituteof Technology, MS 300-235, 4800 Oak Grove Drive, Pasadena, CA 91109, USA.

Groisman et al. Progress in Earth and Planetary Science (2017) 4:41

17

School of Natural Resources and Environment, University of Michigan, 440
Church St, Ann Arbor, MI 48109, USA. 18Department of Experimental Plant
Biology, Faculty of Science, Charles University in Prague, Vinicna 5, 128 44
Prague, Czechia. 19Center for Global Change and Earth Observations,
Michigan State University, 1405 S. Harrison Road, East Lansing, MI 48823,
USA. 20Department of Geography and Environmental Science, The Universityof Reading, Whiteknights, Reading RG6 6AB, UK. 21Ecosystems Services andManagement Program, International Institute for Applied Systems Analysis(IIASA), Schlossplatz 1, A-2361 Laxenburg, Austria. 22State Hydrological
Institute, 2nd Lane, Basil Island, St. Petersburg 199053, Russia. 23National
Institute of Aerospace, NASA Langley Research Center, 21 Langley Boulevard,
MS 420, Hampton, VA 23681, USA. 24Department of Geography andEnvironmental Sustainability, University of Oklahoma, 100 East Boyd Street,
SEC Suite 510, Norman, OK 73019, USA. 25Russian Institute for
Hydrometeorological Information, 6 Koroleva Street, Obninsk 249020, Kaluga
Area, Russia. 26Michigan Tech Research Institute, 3600 Green Court, Suite 100,
Ann Arbor, MI 48105, USA. 27Department of Geography, Miami University,
250 S. Patterson Ave, Oxford, OH 45056, USA. 28Purdue University, 550
Stadium Mall Drive, West Lafayette, IN 47907, USA. 29Laboratoire deGlaciologie et Géophysique de l’Environnement, Joseph Fourier
University-Grenoble 1, 54 rue Moliere, BP 96, 38402 Saint Martin d’Heres
Cedex, France. 30Hydrology Science and Service Corporation, 920 RockholdDrive, Asheville, NC 28804, USA. 31Institute of Environmental Sciences, Kazan
Federal University, Kazan, Tovarishcheskaya str.5, Kazan 420097, Russia.
Received: 15 December 2016 Accepted: 29 November 2017

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