Focus on Environmental, Socio-Economic and Climatic Changes in Northern Eurasia and Their Feedbacks to the Global Earth System

The letters collected in this focus issue of Environmental Research Letters on 'Environmental, socio-economic and climatic changes in Northern Eurasia and their feedbacks to the global Earth system' represent the third special issue based on the results of research within the Northern Eurasia Earth Science Partnership Initiative (NEESPI: http://neespi.org) program domain. Through the years, NEESPI researchers have presented a diverse array of articles that represent a variety of spatial scales and demonstrate the degree to which abrupt climatic and socio-economic changes are acting across Northern Eurasia and feed back to the global Earth system.

BALTEX is an environmental research network dealing with the Earth system of the entire Baltic Sea drainage basin. Important elements include the water and energy cycle, climate variability and change, water management and extreme events, and related impacts on biogeochemical cycles. BALTEX was founded in 1993 as a GEWEX continental-scale experiment and is currently in its second 10 yr phase. Phase I (1993–2002) was primarily dedicated to hydrological, meteorological and oceanographic processes in the Baltic Sea drainage basin, hence mostly dealt with the physical aspects of the system. Scientific focus was on the hydrological cycle and the exchange of energy between the atmosphere, the Baltic Sea and the surface of its catchment. The BALTEX study area was hydrologically defined as the Baltic Sea drainage basin. The second 10 yr phase of BALTEX (Phase II: 2003–12) has strengthened regional climate research, water management issues, biogeochemical cycles and overarching efforts to reach out to stakeholders and decision makers, as well as to foster communication and education. Achievements of BALTEX Phase II have been the establishment of an assessment report of regional climate change and its impacts on the Baltic Sea basin (from hydrological to biological and socio-economic), the further development of regional physical climate models and the integration of biogeochemical and ecosystem models. BALTEX features a strong infrastructure, with an international secretariat and a publication series, and organizes various workshops and conferences. This article gives an overview of the BALTEX programme, with an emphasis on Phase II, with some examples from BALTEX-related research.

This review paper summarizes current understanding of the transport of organic carbon to, and the fate of organic carbon within, the East Siberian Arctic Shelf (ESAS), and of processes determining carbon dioxide (CO₂) and methane (CH₄) fluxes from the ESAS to the atmosphere achieved from analyzing the data sets obtained on 20 expeditions performed from 1999 to 2011. This study of the ESAS was aimed at investigating how redistribution of old carbon from degrading terrestrial and sub-sea permafrost and from coastal erosion contributes to the carbon pool of the ESAS, how changes in the hydrological cycle of the surrounding land and alteration of terrestrial carbon cycles affect the hydrological and biogeochemical parameters of shelf water masses, and which factors control CH₄ and CO₂ emissions from the ESAS. This report describes selected results achieved by a developing international scientific partnership that has been crucial at every stage of the study and will be even more important in the future.

Stressors including regional climate change, economic development effects upon land use and an increasing demand for food production have resulted in significant impacts on the dryland ecosystems in the East Asia (DEA) region. Ecosystem services, such as its provisional services in providing forage for grazing as well as its functional services in regulating water and carbon fluxes, have been significantly altered over the past three decades. Conversely, changes in the landscape, particularly land cover types, have also been blamed for intensified climatic events such as dust storms and severe and frequent droughts within the region. The interactive nature of climate, ecosystems and society is complex and not fully understood, making it difficult, if not impossible, to develop effective adaptation strategies for the region. A special synthesis workshop on 'Dryland Ecosystems in East Asia: State, Changes, Knowledge Gaps, and Future' was held from 18–20 July 2011 in Kaifeng, Henan Province, China, with the aim of identifying knowledge gaps, quantifying impacts and developing a future research agenda for the region. The specific objectives of this workshop were to answer some key socio-environmental questions, including the following. (1) What do we know about the drylands in DEA? (2) What are the knowledge gaps? (3) What are the solutions to these issues? This paper provides a synthesis of the workshop consensus and findings on the state of knowledge and challenges in addressing these science issues for the DEA region.

An overview of the current status of the operational seasonal climate prediction for North Eurasia is presented. It is shown that the performance of existing climate models is rather poor in seasonal prediction for North Eurasia. Multi-model ensemble forecasts are more reliable than single-model ones; however, for North Eurasia they tend to be close to climatological ones. Application of downscaling methods may improve predictions for some locations (or regions). However, general improvement of the reliability of seasonal forecasts for North Eurasia requires improvement of the climate prediction models.

This study quantifies the effect of precipitation bias corrections on basin water balance calculations for the Yellow River Source region (YRS). We analyse long-term (1959–2001) monthly and yearly data of precipitation, runoff, and ERA-40 water budget variables and define a water balance regime. Basin precipitation, evapotranspiration and runoff are high in summer and low in winter. The basin water storage change is positive in summer and negative in winter. Monthly precipitation bias corrections, ranging from 2 to 16 mm, do not significantly alter the pattern of the seasonal water budget. The annual bias correction of precipitation is about 98 mm (19%); this increase leads to the same amount of evapotranspiration increase, since yearly runoff remains unchanged and the long-term storage change is assumed to be zero. Annual runoff and evapotranspiration coefficients change, due to precipitation bias corrections, from 0.33 and 0.67 to 0.28 and 0.72, respectively. These changes will impact the parameterization and calibration of land surface and hydrological models. The bias corrections of precipitation data also improve the relationship between annual precipitation and runoff.

Changes of total and low cloud fraction and the occurrence of different cloud types over Russia were assessed. The analysis was based on visual observations from more than 1600 meteorological stations. Differences between the 2001–10 and 1991–2000 year ranges were evaluated. In general, cloud fraction has tended to increase during recent years. A major increase of total cloud fraction and a decrease of the number of days without clouds are revealed in spring and autumn mostly due to an increase of the occurrence of convective and non-precipitating stratiform clouds. In contrast, the occurrence of nimbostratus clouds has tended to decrease. In general, the ratio between the occurrence of cumulonimbus and nimbostratus clouds has increased for the period 2001–10 relative to 1991–2000. Over particular regions, a decrease of total cloud fraction and an increase of the number of days without clouds are noted.

The analysis of long-term changes of the major climate variables was conducted using a time series of observations from meteorological stations that had continuous observations from 65 up to 120 years. The surface air temperature in the region is characterized by considerable temporal variability which is most apparent in the winter months and thus in the annual values. The positive regional trends of the surface air temperature vary from 0.2 to 0.6 °C per decade. On a century time scale, a tendency for a reduction of the annual precipitation totals prevails. However, the trend values are much lower than the interannual variability of precipitation.

Analyzing the historical climatic conditions of the Baikal Region, we found that the occurrence of drought is possible in any month of the vegetation period, particularly in May, when the maximum numbers of dry years (33–64%), and the years with strong droughts (8–15%) were documented. The influence of climatic conditions on annual wood growth was studied using the response function technique. Results of this analysis show that in the Middle Priangarye region, the greatest impact upon the tree ring growth of pine reflects the mean April temperature, and in the Upper Priangarye region, annual atmospheric precipitation totals (for the hydrological year) control this growth.

Surface air temperature (T_a) is a critical variable in the energy and water cycle of the Earth–atmosphere system and is a key input element for hydrology and land surface models. This is a preliminary study to evaluate estimation of T_a from satellite remotely sensed land surface temperature (T_s) by using MODIS-Terra data over two Eurasia regions: northern China and fUSSR. High correlations are observed in both regions between station-measured T_a and MODIS T_s. The relationships between the maximum T_a and daytime T_s depend significantly on land cover types, but the minimum T_a and nighttime T_s have little dependence on the land cover types. The largest difference between maximum T_a and daytime T_s appears over the barren and sparsely vegetated area during the summer time. Using a linear regression method, the daily maximum T_a were estimated from 1 km resolution MODIS T_s under clear-sky conditions with coefficients calculated based on land cover types, while the minimum T_a were estimated without considering land cover types. The uncertainty, mean absolute error (MAE), of the estimated maximum T_a varies from 2.4 °C over closed shrublands to 3.2 °C over grasslands, and the MAE of the estimated minimum T_a is about 3.0 °C.

The spatiotemporal pattern of the dynamics of surface air temperature and precipitation and those bioclimatic indices that are based upon factors which control vegetation cover are investigated. Surface air temperature and precipitation data are retrieved from the ECMWF ERA Interim reanalysis and APHRODITE JMA datasets, respectively, which were found to be the closest to the observational data. We created an archive of bioclimatic indices for further detailed studies of interrelations between local climate and vegetation cover changes, which include carbon uptake changes related to changes of vegetation types and amount, as well as with spatial shifts of vegetation zones. Meanwhile, analysis reveals significant positive trends of the growing season length accompanied by a statistically significant increase of the sums of the growing degree days and precipitation over the south of West Siberia. The trends hint at a tendency for an increase of vegetation ecosystems' productivity across the south of West Siberia (55°–60°N, 59°–84°E) in the past several decades and (if sustained) may lead to a future increase of vegetation productivity in this region.

Current snow state descriptions and estimates of major snow characteristics (snow cover duration, maximum winter snow depth, snow water equivalent) up to 2010 have been recorded from 958 meteorological stations in Russia. Apart from the description of long-term averages of snow characteristics, the estimates of their change that are averaged over quasi-homogeneous climatic regions are derived and regional differences in the change of snow characteristics are studied. In recent decades, the Russian territory has experienced an increase in snow depth, both winter average and maximum snow depths, against the background of global temperature rise and sea ice reduction in the northern hemisphere. The first generalized regional characteristics of maximum snow water equivalent in the winter season have been obtained. According to field observations, an increase in water supply has been revealed in the north of the East European Plain, in the western part by 4.5% (10 yr) ^{− 1} and in the eastern part by 6% (10 yr) ^{− 1}. This characteristic also increases by ∼ 6% (10 yr) ^{− 1} in the southern forest zone of Western Siberia and in the Far East. Snow water equivalent in central Eastern Siberia increases by 3.4% (10 yr) ^{− 1}. From snow course observations in the forest, a tendency for a decrease in water supply (−6.4% (10 yr) ^{− 1} is only found in the southwest of the East European Plain. Snow cover characteristics, being a product of several climate-forming factors that simultaneously affected them, change nonlinearly and different characteristics may and often do change differently with time. Therefore, one cannot assume that having information about the trend of one of the snow characteristics implies knowledge of the trend sign of others. In particular, whilst during the past four decades over the Russian Federation most snow cover characteristics—including the most important of them responsible for water supply—have increased, the only quantity that is reliably monitored from space (snow cover extent) has decreased, but in the last two decades this decrease has ceased. These tendencies are opposite to those observed in Canada and Alaska.

We analyze snow cover extent (SCE) trends in the National Oceanic and Atmospheric Administration's (NOAA) northern hemisphere weekly satellite SCE data using the Mann–Kendall trend test and find that North American and Eurasian snow cover in the pan-Arctic have declined significantly in spring and summer over the period of satellite record beginning in the early 1970s. These trends are reproduced, both in trend direction and statistical significance, in reconstructions using the variable infiltration capacity (VIC) hydrological model. We find that spring and summer surface radiative and turbulent fluxes generated in VIC have strong correlations with satellite observations of SCE. We identify the role of surface energy fluxes and determine which is most responsible for the observed spring and summer SCE recession. We find that positive trends in surface net radiation (SNR) accompany most of the SCE trends, whereas modeled latent heat (LH) and sensible heat (SH) trends associated with warming on SCE mostly cancel each other, except for North America in spring, and to a lesser extent for Eurasia in summer. In spring over North America and summer in Eurasia, the SH contribution to the observed snow cover trends is substantial. The results indicate that ΔSNR is the primary energy source and ΔSH plays a secondary role in changes of SCE. Compared with ΔSNR and ΔSH, ΔLH has a minor influence on pan-Arctic snow cover changes.

Analysis of vegetation cover and tendencies in forest cover changes at a typical site in the south of West Siberia was performed using remote sensing observations from Landsat. The Northern Eurasia Land Cover legend was used for the assessment of unsupervised classification results. The land cover maps constructed have shown that about half of the study area is occupied by wetlands with several distinctively different vegetation types. The area studied is typical for the South Taiga zone (ecoregion) of Western Siberia from the Ob' river to the Irtysh river, where loamy and clayey soil forming rocks are widespread. Similar vegetation structures dominate over 600 000  km², or about 20%, of the West Siberia area. Analyses of the forest cover changes show that the forest cover loss is not very significant. The area of forest disturbed in 1990–9 is equal to 16 008 ha. The area of forest disturbances during the 2000–7 period was about twice as high (30 907 ha). The main reasons for the forest reduction are intensive forest harvesting and strong windthrow. The high sustainability of the region studied against anthropogenic impacts is explained by the high overall wetness of the territory, the small population density, and the prevalence of deciduous forests at different succession stages with rich vegetation cover.

This study systematically evaluates simulations of near-surface temperature and precipitation using the station observations collected in the semi-arid region of China during the Coordinated Enhanced Observing Period (CEOP) from October 2002 to December 2004 (EOP3 and EOP4). The outputs being evaluated are from eight general circulation models (GCMs) archived by the Coordinated Energy and Water Cycle Observations Project (CEOP), as well as a multi-model ensemble based on these eight models. We find that the multi-model ensemble has a better performance than most of the individual models. Our results show that all individual models and the Model Analysis Comparison (MAC) ensemble mean perform much better when simulating regionally averaged temperature than precipitation. For most models, a systematically low bias is identified in the regionally averaged simulated temperatures, while a high bias exists in the simulated precipitation except in summer. For the simulated temperatures, the lowest and largest rRMSE are found in JMA and BMRC, respectively. Furthermore, temperature is always overestimated when it is between  − 18 and  − 10 °C, while the temperature is underestimated when it is greater than 6 °C; the best performance lies between  − 10 and 2 °C for all the models except BMRC. For the simulated precipitation, excessive rainfall is reproduced at all intervals except in ECPC-SFM, and the largest deviation is identified at the interval of 2–5 mm with a bias of 18.3%. With respect to sub-regions, the simulated temperatures are better in eastern China, but the simulated precipitation is better in the transition zone from the semi-arid region to the arid region. However, the simulation bias increases west of 100°E, which may be associated with the complex and steep topography there. We want to stress that the MAC ensemble mean is superior to any individual models.

This study focused on structural analysis of ground carbon storage following fires in light conifer stands of the Lower Angara region (Siberia, Russia). Experimental fires of varying frontal intensity were conducted at Scots pine and mixed larch forests of southern taiga. Considerable amounts of surface and ground forest fuels (21–38 tC ha ^{− 1}) enhanced low- to high-intensity fires. Post-fire carbon storage decreased by 16–49% depending on fire intensity and rate of spread, with depth of burn being 0.9–6.6 cm. Carbon emissions varied from 4.48 to 15.89 t ha ^{− 1} depending on fire intensity and forest type. Depth of burn and carbon emissions for four major site types were correlated with a weather-based fire hazard index.

The fire history of the northern larch forests within the permafrost zone in a portion of northern Siberia (∼66°N, 100°E) was studied. Since there is little to no human activity in this area, fires within the study area were mostly caused by lightning. Fire return intervals (FRI) were estimated on the basis of burn marks on tree stems and dates of tree natality. FRI values varied from 130 to 350 yr with a 200 ± 50 yr mean. For southerly larch dominated communities, FRI was found to be shorter (77 ± 20 yr at ∼ 61°N, and 82 ± 7 at 64°N), and it was longer at the northern boundary (∼71°) of larch stands (320 ± 50 yr). During the Little Ice Age period in the 16th–18th centuries, FRI was approximately twice as long those as recorded in this study. Fire caused changes in the soil including increases in soil drainage and permafrost thawing depth, and a radial growth increase to about twice the background value (with more than six times observed in extreme cases). This effect may simulate the predicted warming impact on the larch growth in the permafrost zone.

Methane emissions from mires in all climate–vegetation zones of West Siberia (forest steppe, subtaiga, south taiga, middle taiga, north taiga, forest tundra and tundra) were measured using a static chamber method. The observed fluxes varied considerably from small negative values in forested bogs and palsa to hundreds of mgC m ^{− 2} h ^{− 1} in ponds and wet hollows. Observed data were consolidated in the form of the empirical model of methane emissions designated as the 'standard model'. The model is based on medians of CH₄ flux distributions of eight different micro-landscape types depending on their location and estimated duration of methane emission period within the climate–vegetation zone. The current version (Bc8) of the 'standard model' estimates methane flux from West Siberia mires at 2.93 ± 0.97 TgC CH₄ yr ^{− 1} that accounts for about 2.4% of the total methane emission from all mires or 0.7% of global methane emission from all sources.

Frequent measurements of dissolved organic (DOC) and inorganic (DIC) carbon concentrations in rivers during snowmelt, the entire ice-free season, and winter were made in five large watersheds (15 000–174 000 km²) of the Central Siberian Plateau (Yenisey River basin). These differ in the degree of continuous permafrost coverage, mean annual air temperature, and the proportion of tundra and forest vegetation. With an annual DOC export from the catchment areas of 2.8–4.7 gC m ^{− 2} as compared to an annual DIC export of 1.0–2.8 gC m ^{− 2}, DOC was the dominant component of terrigenous C released to rivers. There was strong temporal variation in the discharge of DOC and DIC. Like for other rivers of the pan-arctic and boreal zones, snowmelt dominated annual fluxes, being 55–71% for water runoff, 64–82% for DOC and 37–41% for DIC. Likewise, DOC and DIC exhibited also a strong spatial variation in C fluxes, with both dissolved C species decreasing from south to north. The rivers of the southern part of the plateau had the largest flow-weighted DOC concentrations among those previously reported for Siberian rivers, but the smallest flow-weighted DIC concentrations. In the study area, DOC and DIC fluxes were negatively correlated with the distribution of continuous permafrost and positively correlated with mean annual air temperature. A synthesis of literature data shows similar trends from west to east, with an eastward decrease of dissolved C concentrations and an increased proportion of DOC in the total dissolved C flux. It appears that there are two contemporary limitations for river export of terrigenous C across Siberia: (1) low productivity of ecosystems with respect to potentially mobilizable organic C, slow weathering rates with concomitant small formation of bicarbonate, and/or wildfire disturbance limit the pools of organic and inorganic C that can be mobilized for transport in rivers (source-limited), and (2) mobilization of available pools of C is constrained by low precipitation in the severe continental climate of interior Siberia (transport-limited). Climate warming may reduce the source limitation by enhancing primary production and weathering rates, while causes leading to surmounting the transport limitation remain debatable due to uncertainties in predictions of precipitation trends and other likely sources of reported increase of river discharges.

Humans have traditionally cultivated steppe and forest-steppe on fertile soils for agriculture. Forests are predicted to shift northwards in a warmer climate and are likely to be replaced by forest-steppe and steppe ecosystems. We analyzed potential climate change impacts on agriculture in south-central Siberia believing that agriculture in traditionally cold Siberia may benefit from warming. Simple models determining crop range and regression models determining crop yields were constructed and applied to climate change scenarios for various time frames: pre-1960, 1960–90 and 1990–2010 using historic data and data taken from 2020 and 2080 HadCM3 B1 and A2 scenarios. From 50 to 85% of central Siberia is predicted to be climatically suitable for agriculture by the end of the century, and only soil potential would limit crop advance and expansion to the north. Crop production could increase twofold. Future Siberian climatic resources could provide the potential for a great variety of crops to grow that previously did not exist on these lands. Traditional Siberian crops could gradually shift as far as 500 km northwards (about 50–70 km/decade) within suitable soil conditions, and new crops nonexistent today may be introduced in the dry south that would necessitate irrigation. Agriculture in central Siberia would likely benefit from climate warming. Adaptation measures would sustain and promote food security in a warmer Siberia.

We used a biogeochemistry model, the Terrestrial Ecosystem Model (TEM), to examine the methane (CH₄) exchanges between terrestrial ecosystems and the atmosphere in Northern Eurasia from 1971 to 2100. Multiple model simulations using various wetland extent datasets and climate change scenarios were conducted to assess the uncertainty of CH₄ fluxes, including emissions and consumption. On the basis of these simulations we estimate the current net emissions in the region to be 20–24 Tg CH₄ yr ^{− 1} (1 Tg = 10¹² g), two-thirds of which are emitted during the summer. In response to climate change over the 21st century, the annual CH₄ emissions in the region are projected to increase at a rate of 0.06 Tg CH₄ yr ^{− 1}, which is an order of magnitude greater than that of annual CH₄ consumption. Further, the annual net CH₄ emissions are projected to increase by 6–51% under various wetland extent datasets and climate scenarios by the end of the 21st century, relative to present conditions. Spatial patterns of net CH₄ emissions were determined by wetland extent. Net CH₄ emissions were dominated by wetlands within boreal forests, grasslands and wet tundra areas in the region. Correlation analyses indicated that water table depth and soil temperature were the two most important environmental controls on both CH₄ emissions and consumption in the region. Our uncertainty analyses indicated that the uncertainty in wetland extent had a larger effect on future CH₄ emissions than the uncertainty in future climate. This study suggests that better characterization of the spatial distribution and the natural diversity of wetlands should be a research priority for quantifying CH₄ fluxes in this region.

West Siberia contains the largest extent of wetlands in the world, including large peat deposits; the wetland area is equivalent to 27% of the total area of West Siberia. This study used inverse modeling to refine emissions estimates for West Siberia using atmospheric CH₄ observations and two wetland CH₄ emissions inventories: (1) the global wetland emissions dataset of the NASA Goddard Institute for Space Studies (the GISS inventory), which includes emission seasons and emission rates based on climatology of monthly surface air temperature and precipitation, and (2) the West Siberian wetland emissions data (the Bc7 inventory), based on in situ flux measurements and a detailed wetland classification. The two inversions using the GISS and Bc7 inventories estimated annual mean flux from West Siberian wetlands to be 2.9 ± 1.7 and 3.0 ± 1.4 Tg yr ^{− 1}, respectively, which are lower than the 6.3 Tg yr ^{− 1} predicted in the GISS inventory, but similar to those of the Bc7 inventory (3.2  Tg yr ^{− 1}). The well-constrained monthly fluxes and a comparison between the predicted CH₄ concentrations in the two inversions suggest that the Bc7 inventory predicts the seasonal cycle of West Siberian wetland CH₄ emissions more reasonably, indicating that the GISS inventory predicts more emissions from wetlands in northern and middle taiga.

A simple regression model for calculating annual actual evapotranspiration (ET) and potential evapotranspiration (PET), as well as annual transpiration (TR) of mature boreal forests grown in the European part of Russia in the Holocene using paleoclimatic and paleobotanical data (air temperature, precipitation, forest species compositions) is presented. The model is based on nonlinear approximations of annual values of ET, TR and PET obtained by the Levenberg–Marquardt method using the results of numerical simulations of ET, TR and PET provided by a process-based Mixfor-SVAT model for forests with different species compositions under various thermal and moistening conditions. The results of ET, TR and PET reconstructions for the Holocene show large variability and high correlation with the air temperature pattern. Minimal values of ET and PET are obtained for the Younger Dryas cold phase (11.0–10.0 ¹⁴C kyr BP) when ET varied between 320 and 370  mm yr ^{− 1} and PET varied between 410 and 480 mm yr ^{− 1}. During the Late Atlantic periods of the Holocene (4.5–5.1 ¹⁴C kyr BP), ET and PET reached maximal values (ET: 430–450  mm yr ^{− 1} and PET: 550–570 mm yr ^{− 1}).

The collapse of socialism in 1989 triggered a phase of institutional restructuring in Central and Eastern Europe. Several countries chose to privatize forests or to return them to pre-socialist owners. Here, we assess the implications of forest restitution on the terrestrial carbon balance. New forest owners have strong incentives to immediately clearcut their forests, resulting in increased terrestrial emissions. On the other hand, logging generally decreased after 1989 and forests are expanding on unused or abandoned farmland, both of which may offset increased logging on restituted forests. We mapped changes in forest cover for the entire country of Romania using Landsat satellite images from 1990 to 2010. We use our satellite estimates, together with historic data on logging rates and changes in forest cover, to parameterize a carbon book-keeping model for estimating the terrestrial carbon flux (above and below ground) as a consequence of land use change and forest harvest. High logging rates during socialism resulted in substantial terrestrial carbon emissions and Romania was a net carbon source until the 1980s. After the collapse of the Soviet Union forest harvest rates decreased dramatically, but since restitution laws were implemented they have increased by 60% (from 15 122 ± 5397 ha y ^{− 1} in 2000 to 23 884 ± 11 510 ha y ^{− 1} in 2010), but still remain lower than prior to 1989. Romania currently remains a terrestrial carbon sink, offsetting 7.6% ± 2.5% of anthropogenic carbon emissions. A further increase in logging could result in net emissions from terrestrial ecosystems during the coming decades. However, forest expansion on degraded land and abandoned farmland offers great potential for carbon sequestration.

Land use change is a principal force and inherent element of global environmental change, threatening biodiversity, natural ecosystems, and their services. However, our ability to anticipate future land use change is severely limited by a lack of understanding of how major socio-economic disturbances (e.g., wars, revolutions, policy changes, and economic crises) affect land use. Here we explored to what extent socio-economic disturbances can shift land use systems onto a different trajectory, and whether this can result in less intensive land use. Our results show that the collapse of the Soviet Union in 1991 caused a major reorganization in land use systems. The effects of this socio-economic disturbance were at least as drastic as those of the nuclear disaster in the Chernobyl region in 1986. While the magnitudes of land abandonment were similar in Ukraine and Belarus in the case of the nuclear disaster (28% and 36% of previously farmed land, respectively), the rates of land abandonment after the collapse of the Soviet Union in Ukraine were twice as high as those in Belarus. This highlights that national policies and institutions play an important role in mediating effects of socio-economic disturbances. The socio-economic disturbance that we studied caused major hardship for local populations, yet also presents opportunities for conservation, as natural ecosystems are recovering on large areas of former farmland. Our results illustrate the potential of socio-economic disturbances to revert land use intensification and the important role institutions and policies play in determining land use systems' resilience against such socio-economic disturbances.

The 187 million hectares of pasturelands in Kazakhstan play a key role in the nation's economy, as livestock production accounted for 54% of total agricultural production in 2010. However, more than half of these lands have been degraded as a result of unregulated grazing practices. Therefore, effective long term ecological monitoring of pasturelands in Kazakhstan is imperative to ensure sustainable pastureland management. As a case study in this research, we demonstrated how the ecological conditions could be assessed with remote sensing technologies and pastureland models. The example focuses on the southern Balkhash area with study sites on a foothill plain with Artemisia-ephemeral plants and a sandy plain with psammophilic vegetation in the Turan Desert. The assessment was based on remotely sensed imagery and meteorological data, a geobotanical archive and periodic ground sampling. The Pasture agrometeorological model was used to calculate biological, ecological and economic indicators to assess pastureland condition. The results showed that field surveys, meteorological observations, remote sensing and ecological models, such as Pasture, could be combined to effectively assess the ecological conditions of pasturelands and provide information about forage production that is critically important for balancing grazing and ecological conservation.