Focus on Northern Eurasia in the Global Earth and Human Systems: Changes, Interactions, and Sustainable Societal Development

The Mongolian Plateau hosts two different governments: the Mongolian People's Republic and the Inner Mongolia Autonomous Region, a provincial-level government of the People's Republic of China. The divergence between these governments has widened in the past century, mostly due to a series of institutional changes that generated different socioeconomic and demographic trajectories. Due to its high latitude and altitude, the Plateau has been highly sensitive to the rapid changes in global and regional climates that have altered the spatial and temporal distributions of energy and water. Based on a recent workshop to synthesize findings on the sustainability of the Plateau amidst socioeconomic and environmental change, we identify five critical issues facing the social-ecological systems (SES): (1) divergent and uncertain changes in social and ecological characteristics; (2) declining prevalence of nomadism; (3) consequences of rapid urbanization in transitional economies; (4) the unsustainability of large-scale afforestation efforts in the semi-arid and arid areas of Inner Mongolia; and (5) the role of institutional changes in shaping the SES on the Plateau. We emphasize that lessons learned in Inner Mongolia are valuable, but may not always apply to Mongolia. National land management policies and regulations have long-term effects on the sustainability of SES; climate change adaptation policies and practices must be tuned to local conditions and should be central to decision-making on natural resource management and socioeconomic development pathways.

Northern Eurasia is made up of a complex and diverse set of physical, ecological, climatic and human systems, which provide important ecosystem services including the storage of substantial stocks of carbon in its terrestrial ecosystems. At the same time, the region has experienced dramatic climate change, natural disturbances and changes in land management practices over the past century. For these reasons, Northern Eurasia is both a critical region to understand and a complex system with substantial challenges for the modeling community. This review is designed to highlight the state of past and ongoing efforts of the research community to understand and model these environmental, socioeconomic, and climatic changes. We further aim to provide perspectives on the future direction of global change modeling to improve our understanding of the role of Northern Eurasia in the coupled human–Earth system. Modeling efforts have shown that environmental and socioeconomic changes in Northern Eurasia can have major impacts on biodiversity, ecosystems services, environmental sustainability, and the carbon cycle of the region, and beyond. These impacts have the potential to feedback onto and alter the global Earth system. We find that past and ongoing studies have largely focused on specific components of Earth system dynamics and have not systematically examined their feedbacks to the global Earth system and to society. We identify the crucial role of Earth system models in advancing our understanding of feedbacks within the region and with the global system. We further argue for the need for integrated assessment models (IAMs), a suite of models that couple human activity models to Earth system models, which are key to address many emerging issues that require a representation of the coupled human–Earth system.

Livestock production is the largest anthropogenic methane (CH₄) source globally over the decades. Enteric fermentation of ruminants is responsible for the majority of global livestock CH₄ emissions. Both inventory-based models (IvtMs) and process-based models (PcMs) are extensively used to assess the livestock CH₄ emission dynamics. However, the model performance and the associated uncertainty have not been well quantified and understood, which greatly hamper our credibility of the regional and global CH₄ emission predictions. In this study, we compared the CH₄ emissions of livestock enteric fermentation (CH_4,ef) predicted by multiple IvtMs and PcMs across Inner Mongolia, a region dominated by typical temperate grasslands that are widely used for animal husbandry. Twenty predictions from five IvtMs, and ten predations from five PcMs were explicitly calculated and compared for the reference year of 2006. The CH_4,ef predicted from PcMs is lower than IvtMs and the variation between PcMs is substantially higher, i.e. 0.34 ± 0.36 g CH₄/m²yr and 0.78 ± 0.14 g CH₄/m²yr for PcMs and IvtMs, respectively. Different model strategies undertaken, i.e. the demand-oriented strategy for IvtMs and the resource-demand co-determined one for PcMs, cause the different predictions of CH_4,ef between the two model groups. Using the results from IvtMs as the baseline scalar, we identified and benchmarked the performance of individual PcMs in the study region. The quantitative information provided can facilitate the understanding of key principles and processes of CH_4,ef estimations, which will contribute to the future model development of global CH₄ emission.

Precipitation extremes are widely thought to intensify with global warming due to an exponential growth following the Clausius–Clapeyron (C–C) equation which links the atmosphere water vapor saturation pressure with air temperature. However, a number of recent studies based on station and reanalyzes data for the contemporary period showed that scaling rates between extreme precipitation and temperature strongly depend on temperature range, moisture availability, and a region of interest. Being performed for some regions, such estimates, however, lack for Northern Eurasia, where prominent temperature changes and rapid shift from large-scale to convective precipitation are observed. Here, we examine the scaling between daily precipitation extremes and surface air temperature (SAT) over Russia for 1966–2017 using meteorological station data and for 1979–2020 using ERA5 reanalysis. The precipitation-temperature relation is examined for total precipitation and, separately, for convective and large-scale precipitation types. In winter, we reveal a general increase in extreme precipitation of all precipitation types according to the C–C relationship. For the Russian Far East region, the stratiform precipitation extremes scale with SAT following even super C–C rates, about two times as fast as C–C. However, in summer we find a peak-like structure of the precipitation-temperature scaling, especially for the convective precipitation in the southern regions. Extreme precipitation reaches their peak values at the temperature range between 15 °C and 20 °C. At higher temperatures, the negative scaling prevails. Analyzed data show a pronounced decrease in relative humidity with increasing surface temperatures beyond the 15 °C–20 °C threshold. This indicates that moisture availability is the major factor for the peak-shaped relationship between extreme precipitation and temperature revealed by our analysis.

The specifics of solid waste storage in permafrost were analyzed. The main types of impact of the waste on the natural environment and frozen soils were determined as mechanical, physicochemical, load, and thermal. The research allowed us to define eight main types of waste storage in the permafrost zone, which were different both in terms of waste accumulation and in terms of their impact on the environment in general and the permafrost in particular. These were: industrial waste storage facilities (slag, sludge and tailing dumps, ash dumps); dumps of rock in sites of mining; household waste accumulators; dumps of wood processing waste in the centers of the timber industry; abandoned territories resulting from a decrease in the population of Northern settlements; storage areas for tanks with residues of fuels and lubricants; tank farms for storing petroleum products in settlements and cities of the North; storage areas for contaminated snow exported from built-up areas. Pollution of waste territories and destruction of many ecosystems as a result of waste storage were caused by use of imperfect technologies for the extraction and processing of raw materials, the 'legacy' of past years with disregard to the environmental conditions, the lack of special standards for the storage of garbage and by-product industrial materials, undeveloped methods of waste disposal in harsh climatic conditions.

Forest disturbances are a critical environmental issue globally and within the boreal biome, yet detailed attribution and trends in disturbances are lacking for many Siberian regions. The Angara region located in the southern taiga of Central Siberia has experienced significant disturbances during the past several decades and is a hotspot of change in Eurasia. Here we estimated fire and logging disturbances using MODIS and Landsat data for the period 2002–2020 across the Angara region and analyzed the resulting trends. Average annual burned and logged area was about 220 and 31 thousand ha or 2 and 0.3% of the study area, respectively. In total, about 4.1 million ha (38% of the region) and 0.6 million ha (6% of the region) were disturbed by fires and logging, respectively. Spatial analysis showed that almost 50% of fires were ignited within 2 km of anthropogenic features such as settlements, roads and logged areas. Almost 5% of the Angara region was burned two or more times during the 19 years of observations. Improved and strictly-enforced conservation and management policies are required to halt continued forest degradation in the Angara region and similarly-affected boreal forests in Siberia.

The Aral Sea desiccation is one of the worst aquatic ecological disasters of the last century, important for understanding the worldwide trends to degradation of arid lakes under water use and climate change. Formerly the fourth largest lake worldwide, the Aral Sea has lost ∼90% of its water since the early 1960s due to irrigation in its drainage basin. Our survey on the seasonal thermal and mixing regime in Chernyshev—a semi-isolated hypersaline part of the Aral Sea—revealed a newly formed two-layered structure with strong gradients of salinity and water transparency at mid-depths. As a result, the Chernyshev effectively accumulates solar energy, creating a temperature maximum at the water depth of ∼5 m with temperatures up to 37 °C. Herewith, this part of the Aral Sea has evolved to an unprecedently large (∼80 km²) heliothermal lake akin to artificial solar ponds used for 'green energy' production. The newly formed heliothermal lake, with transparent and freshened layer on top of the hypersaline and nutrient-rich deep water, acts as a solar energy trap and facilitates intense biogeochemical processes. The latter reveal themselves in practically 100% opacity of the deep layer to the solar light, permanent deep anoxia, and growing methane concentrations. The recent emergence of the Chernyshev as a heliothermal lake provides an opportunity for tracing the biogeochemical and ecological response of aquatic ecosystems to suddenly changed environmental conditions.

The impact of climate change, rising CO₂, land-use/land-cover change and land management on the carbon cycle in terrestrial ecosystems has been widely reported. However, only rarely have studies have been conducted to clarify the impact of climate change and rising CO₂ on the carbon sink contributed by ecological restoration projects (ERPs). To better understand the impact of climate change and rising CO₂ on ERPs, we took the Beijing–Tianjin Sand Source Control Project zone as an example to set up different scenarios to distinguish the confounding effects of these factors on the regional carbon budget based on a remote sensing data-driven model. Compared with business as usual, our results show that climate change caused a carbon loss of 78.97 Tg C. On the contrary, ERPs contributed a carbon sink of approximately 199.88 Tg C in forest and grassland. Furthermore, rising CO₂ also contributed an additional carbon sink of 107.80 Tg C. This study distinguished the individual effects of different factors, and clarified the net carbon sink contributed by ERPs and rising CO₂ and their significance for enhancing the regional carbon sink and reversing the adverse effects of climate change on the carbon sink. Furthermore, ERPs can sequester carbon more effectively and faster compared with rising atmospheric CO₂ concentration.

The fate of a boreal forest may depend on the trend in its normalized difference vegetation index (NDVI), such as whether the NDVI has been increasing significantly over the past few decades. In this study, we analyzed the responses of two Siberian larch forests at Spasskaya Pad and Elgeeii in eastern Siberia to various waterlogging-induced disturbances, using satellite-based NDVI and meteorological data for the 2000–2019 period. The forest at Spasskaya Pad experienced waterlogging (i.e. flooding events caused by abnormal precipitation) during 2005–2008 that damaged canopy-forming larch trees and increased the abundance of water-resistant understory vegetation. By contrast, the forest at Elgeeii did not experience any remarkable disturbance, such as tree dieback or changes in the vegetation community. Significant increasing NDVI trends were found in May and June–August at Elgeeii (p < 0.05), whereas no significant trends were found at Spasskaya Pad (p > 0.05). NDVI anomalies in May and June–August at Elgeeii were significantly associated with precipitation or temperature depending on the season (p < 0.05), whereas no significant relationships were found at Spasskaya Pad (p > 0.05). Thus, the 20 year NDVI trend and NDVI–temperature–precipitation relationship differed between the two larch forests, although no significant trends in temperature or precipitation were observed. These findings indicate that nonsignificant NDVI trends for Siberian larch forests may reflect waterlogging-induced dieback of larch trees, with a concomitant increase in water-resistant understory vegetation.

Assessments of changes in landscape patterns and functions during urban development need to factor urban fringes (UPs) as part of the overall social-environmental system, especially in regions with poor transportation systems where urban functions depend heavily on surrounding suburbs. In this study, we use net primary production (NPP) as an integrative measure to delineate UPs and to measure the expansion in 15 urban areas in the remote Qinghai-Tibet Plateau. Using a logistic curve fitting model based on NPP to delineate differences between the UF and rural landscapes, we explore how NPP-inferred UF expansions may have changed with increase in urban population and the secondary and tertiary industrial production. The UF width (area) was 17.4 km (950.67 km²) in 2000 but increased to 27.0 km (2289.06 km²) in 2019 for Lhasa. For Xining, this was from 28.0 km (2461.76 km²) to 36.0 km (4069.44 km²) during 2000–2019. For the prefecture-level cities, the rate increased from 2–16 km (12.56–803.84 km²) to 7–17 km (153.86–907.46 km²). More importantly, the ratio between UF width and population during the five study periods showed a linear decreasing trend, but an exponential decrease with economic measures. The urban expansion due to population increase changed from 26 m in 2000 to 21 m in 2019 for every increase of 1000 residents, while the expansion due to economic changes was significantly reduced from 732 m per billion RMB (Ren Min Bi) in 2000 to 52 m per billion RMB in 2019. We confirm a hypothesis that the ratio of expansion of UFs was more dependent on economic growth in early stages of urbanization than in later stages, whereas urban population promoted expansions over the entire study period.

Mountains play a critical role in water cycles in semiarid regions by providing for the majority of the total runoff. However, hydroclimatic conditions in mountainous regions vary considerably in space and time, with high interannual fluctuations driven by large-scale climate oscillations. Here, we investigated teleconnections between global climate oscillations and the peak precipitation season from February to June in the Tian-Shan and Pamir Mountains of Central Asia. Using hierarchical climate regionalization, we identified seven subregions with distinct precipitation patterns, and assessed correlations with selected climate oscillations at different time lags. We then simulated the seasonal precipitation in each subregion from 1979 to 2020 using the most prevalent teleconnections as predictors with support vector regression (SVR). Our findings indicate that the El Niño–Southern Oscillation, the Pacific Decadal Oscillation, and the Eastern Atlantic/West Russia pattern are among the major determinants of the seasonal precipitation. The dominant lead-lag times of these oscillations make them reliable predictors ahead of the season. We detected notable teleconnections with the North Atlantic Oscillation and Scandinavian Pattern, with their strongest associations emerging after onset of the season. While the SVR-based models exhibit robust prediction skills, they tend to underestimate precipitation in extremely wet seasons. Overall, our study highlights the value of appropriate spatial and temporal aggregations for exploring the impacts of climate teleconnections on precipitation in complex terrains.

The 2019/20 winter was extremely warm globally and in the Northern Hemisphere extratropics. The main cause of climate extremes particularly in East Asia, was the extreme positive Arctic Oscillation (AO) event superimposed on steady global warming. The negligible trend in the AO over the preceding 41 years makes it possible to distinguish the roles of AO and global warming in the observed extremes. We estimate and compare contributions to January–March 2020 climate extremes by the AO and global warming represented by local temperature trends using the ERA5 reanalysis data. Based on results from a preliminary study, we estimate the contribution by global warming using linear regression while that by the AO using cubic regression, which is more restrained for the high AO index values than linear. The results show that the temperature extremes were mainly caused by the extreme positive AO event which accounts for approximately 3/4 of the observed temperature anomalies in northern East Asia and 2/3 in eastern East Asia. In southern East Asia, the AO contributes negligibly and positive temperature anomalies are related to global warming and local and regional impacts, particularly extreme sea surface temperature, enhance south-westerlies and local radiative forcing. General conclusion is that the observed strong positive temperature anomalies including extreme anomalies over East Asia could have been achieved only as a combined effect of the extreme positive AO event and global warming. Quantification of the roles of the AO and global warming in climate extremes helps to estimate future anomalies caused by extreme AO events as well as assess uncertainties in climate model projections.

The phases of long-lasting (more than 10–15 years) increased and decreased water flow, water temperature and heat flux values in the Northern Dvina River and the Pechora River were studied for the observation period from the 1930s to 2020. To distinguish between different phases, statistical homogeneity tests and normalized cumulative deviation curves were used. Generally, the identified phases displayed statistically significant differences between average values of the measured characteristics. During contrasting phases, the general pattern of water temperature during the warm season, water runoff and heat flux in the Northern Dvina and Pechora River Basins differed considerably. The number of the identified phases varied between the studied rivers and ranged from two to four contrasting phases in the Northern Dvina River exceeded those of the Pechora River. Consequently, the duration of the phases also varied quite significantly. The difference in mean values of the hydrological characteristics during the contrasting phases in the Northern Dvina River exceeded those of the Pechora River. The longest phases of increased and decreased heat flux nearly coincide with contrasting periods of water runoff and water temperature. The phases of simultaneous increased or decreased values of all hydrological characteristics were associated with corresponding periods of increased or decreased air temperature (on average for a year and for the open water period) and annual precipitation values. Those long-lasting phases of simultaneously increased or decreased values of river flow, heat flux, and water temperature were associated with changes of the global thermal regime, regional cryosphere variations, and long-term periods of intensification or weakening of the atmospheric circulation over the North Atlantic, characterised by variability in macrocirculation indices such as the North Atlantic Oscillation and Scandinavian circulation pattern.

The Lena Delta in Siberia is the largest delta in the Arctic and as a snow-dominated ecosystem particularly vulnerable to climate change. Using the two decades of MODerate resolution Imaging Spectroradiometer satellite acquisitions, this study investigates interannual and spatial variability of snow-cover duration and summer vegetation vitality in the Lena Delta. We approximated snow by the application of the normalized difference snow index and vegetation greenness by the normalized difference vegetation index (NDVI). We consolidated the analyses by integrating reanalysis products on air temperature from 2001 to 2021, and air temperature, ground temperature, and the date of snow-melt from time-lapse camera (TLC) observations from the Samoylov observatory located in the central delta. We extracted spring snow-cover duration determined by a latitudinal gradient. The 'regular year' snow-melt is transgressing from mid-May to late May within a time window of 10 days across the delta. We calculated yearly deviations per grid cell for two defined regions, one for the delta, and one focusing on the central delta. We identified an ensemble of early snow-melt years from 2012 to 2014, with snow-melt already starting in early May, and two late snow-melt years in 2004 and 2017, with snow-melt starting in June. In the times of TLC recording, the years of early and late snow-melt were confirmed. In the three summers after early snow-melt, summer vegetation greenness showed neither positive nor negative deviations. Whereas, vegetation greenness was reduced in 2004 after late snow-melt together with the lowest June monthly air temperature of the time series record. Since 2005, vegetation greenness is rising, with maxima in 2018 and 2021. The NDVI rise since 2018 is preceded by up to 4 °C warmer than average June air temperature. The ongoing operation of satellite missions allows to monitor a wide range of land surface properties and processes that will provide urgently needed data in times when logistical challenges lead to data gaps in land-based observations in the rapidly changing Arctic.

Global climate changes give us the important task of obtaining information about the spatial distribution of bioclimatic comfort indicators at the global or continental level. One of the most applicable tools can be based on reanalysis data (meteorological gridded data with global coverage). This issue is fully relevant for the territory of Northern Eurasia with its diverse climates, rapid environmental changes, and often sparse network of in situ observations. In this paper, we present a conceptually new dataset for the most popular thermal comfort indices, namely heat index (HI), humidex (HUM), wind chill temperature, mean radiant temperature, physiologically equivalent temperature (PET) and Universal Thermal Comfort Index (UTCI) derived from ERA-Interim reanalysis hourly data for the territory of Northern Eurasia (the area limited by 40° N–80° N, 10° W–170° W). The dataset has horizontal resolution of 0.75° × 0.75° (up to 79 km), temporal resolution of 3 h, and covers the period from 1979 to 2018 (40 years), which corresponds to the standard of the World Meteorological Organization in determining the parameters of the modern climate. Time series of indices are supplemented with a set of 8092 pre-calculated statistical parameters characterizing climatology of the thermal stress conditions. We further present several examples of the North Eurasian Thermal Comfort Indices Dataset (NETCID) data application, including analysis of the spatial heterogeneity of thermal stress conditions, assessment of their changes and analysis of specific extreme events. Presented examples demonstrate a pronounced difference between considered indices and highlight the need of their accurate selection for applied tasks. In particular, for the whole study areas HI and HUM indices show much smaller thermal stress repeatability and weaker trends of its changes in comparison to PET and UTCI indices. NETCID is available for free download at https://doi.org/10.6084/m9.figshare.12629861.

The ongoing military conflict in Eastern Ukraine has resulted in significant land use changes as well as economic shifts particularly in agricultural and industrial activities. The day/night band detectors on-board the Suomi-NPP Visible Infrared Imaging Radiometer Suite provides an opportunity to assess socio-economic impacts of human conflicts based on physical radiometric measurements. In this study, we show a near 50% decrease in night-time light activity in Donetsk and Luhansk (Donbass Region) from 2012 to 2016. Furthermore, by separating night-time light losses between areas inside official city boundaries and those outside, we illustrate the sensitivity to residential land-use types. A 43.5% of night-time light loss inside cities was attributed to residential areas and 17.5% registered outside of cities. Additionally, this separation showed considerable differences for night-time light losses attributed to industrial land-use types with higher losses occurring in regions outside of cities (36.5%) than regions inside cities (24%). The separation of night-time light losses inside and outside cities reveal considerable discrepancies in night-time light losses showing that considerable activity occurs outside of traditionally targeted urban activities. The results demonstrate night-time light losses are sensitive to proximity to civilian-residential populations, and highlight discrepancies between urban cores and their attached peripheries.

Studies examining the joint interactions and impacts of social-environmental system (SES) drivers on vegetation dynamics in Central Asia are scarce. We investigated seasonal trends and anomalies in drivers and their impacts on ecosystem structure and function (ESF). We explored the response of net primary production, evapotranspiration and normalized difference vegetation index (NDVI) to various SES drivers—climate, human influence, heat stress, water storage, and water content—and their latent relationships in Kazakhstan. We employed 13 predictor drivers from 2000 to 2016 to identify the interactions and impacts on ESF variables that reflect vegetation growth and productivity. We developed 12 models with different predictor–response variable combinations and separated them into two approaches. First, we considered the winter percent snow cover (SNOWc) and spring rainfall (P_MAM) as drivers and then as moderators in a structural equation model (SEM). SNOWc variability (SNOWc_SD) as an SEM moderator exhibited superior model accuracy and explained the interactions between various predictor–response combinations. Winter SNOWc_SD did not have a strong direct positive influence on summer vegetation growth and productivity; however, it was an important moderator between human influence and the ESF variables. Spring rainfall had a stronger impact on ESF variability than summer rainfall. We also found strong positive feedback between soil moisture (SM) and NDVI, as well as a strong positive influence of vegetation optical depth (VOD) and terrestrial water storage (TWS) on ESF. Livestock density (LSK_D) exhibited a strong negative influence on ESF. Our results also showed a strong positive influence of socioeconomic drivers, including crop yield per hectare (CROPh), gross domestic product per capita (GDPca), and population density (POP_D) on vegetation productivity. Finally, we found that vegetation dynamics were more sensitive to SM, VOD, LSK_D and POP_D than climatic drivers, suggesting that water content and human influence drivers were more critical in Kazakhstan.

Climate change has adverse impacts on Arctic natural ecosystems and threatens northern communities by disrupting subsistence practices, limiting accessibility, and putting built infrastructure at risk. In this paper, we analyze spatial patterns of permafrost degradation and associated risks to built infrastructure due to loss of bearing capacity and thaw subsidence in permafrost regions of the Arctic. Using a subset of three Coupled Model Intercomparison Project 6 models under SSP245 and 585 scenarios we estimated changes in permafrost bearing capacity and ground subsidence between two reference decades: 2015–2024 and 2055–2064. Using publicly available infrastructure databases we identified roads, railways, airport runways, and buildings at risk of permafrost degradation and estimated country-specific costs associated with damage to infrastructure. The results show that under the SSP245 scenario 29% of roads, 23% of railroads, and 11% of buildings will be affected by permafrost degradation, costing $182 billion to the Arctic states by mid-century. Under the SSP585 scenario, 44% of roads, 34% of railroads, and 17% of buildings will be affected with estimated cost of $276 billion, with airport runways adding an additional $0.5 billion. Russia is expected to have the highest burden of costs, ranging from $115 to $169 billion depending on the scenario. Limiting global greenhouse gas emissions has the potential to significantly decrease the costs of projected damages in Arctic countries, especially in Russia. The approach presented in this study underscores the substantial impacts of climate change on infrastructure and can assist to develop adaptation and mitigation strategies in Arctic states.

The Yenisei River is the largest contributor of freshwater and energy fluxes among all rivers draining to the Arctic Ocean. Modeling long-term variability of Eurasian runoff to the Arctic Ocean is complicated by the considerable variability of river discharge in time and space, and the monitoring constraints imposed by a sparse gauged-flow network and paucity of satellite data. We quantify tree growth response to river discharge at the upper reaches of the Yenisei River in Tuva, South Siberia. Two regression models built from eight tree-ring width chronologies of Larix sibirica are applied to reconstruct winter (Nov–Apr) discharge for the period 1784–1997 (214 years), and annual (Oct–Sept) discharge for the period 1701–2000 (300 years). The Nov–Apr model explains 52% of the discharge variance whereas Oct–Sept explains 26% for the calibration intervals 1927–1997 and 1927–2000, respectively. This new hydrological archive doubles the length of the instrumental discharge record at the Kyzyl gauge and resets the temporal background of discharge variability back to 1784. The reconstruction finds a remarkable 80% upsurge in winter flow over the last 25 years, which is unprecedented in the last 214 years. In contrast, annual discharge fluctuated normally for this system, with only a 7% increase over the last 25 years. Water balance modeling with CRU data manifests a significant discrepancy between decadal variability of the gauged flow and climate data after 1960. We discuss the impact on the baseflow rate change of both the accelerating permafrost warming in the discontinuous zone of South Siberia and widespread forest fires. The winter discharge accounts for only one third of the annual flow, yet the persistent 25 year upsurge is alarming. This trend is likely caused by Arctic Amplification, which can be further magnified by increased winter flow delivering significantly more fresh water to the Kara Sea during the cold season.

Boreal forest landscapes are experiencing various anthropogenic pressures from industrial activity, transportation, urbanization, and recreation compounding already significant changes in regional climate. However, the impact of the transportation infrastructure on boreal forests is rarely considered, and information about road extent is often incomplete, especially in the case of informal roads. Using a combination of landscape observations and interviews with local residents this case study examines the role of informal roads, i.e. vehicular roadways existing outside of the current publicly governed road networks, in transforming Siberian boreal forest landscapes in the Vershina Khandy taiga, Russia. Informal roads constitute 88% of the total road length in the study area and exert significant and multifaceted effects on social-ecological systems and landscape sustainability. Native dark coniferous forests have been disturbed by cutting, logging and human-caused fires proliferated from the roads. In their immediate vicinity, the informal road networks also exacerbate the replacement of primary forests with different successional states. Landscape vulnerability was assessed using three main factors of road-related disturbance: erosion, permafrost degradation and wildfires. Valley landscapes, where roads are prevalent, found to be the most vulnerable to environmental degradation. They are more often located within the wetlands with permafrost occurrences. The impact of informal roads is not limited to environmental changes. Among consequences there are also increased mobilities of local and Indigenous communities, as well an improved access to the area by outsiders: recreational anglers and poachers. The effects on subsistence activities and mobility vary across different landscapes. Further research on natural and social components of landscape sustainability in boreal forests affected by informal road networks is needed to better understand the local, regional and global role of this phenomena.

The Tarim Basin is a typical arid area and has the world's most severe desertification of natural and semi-natural land due to limited water resources. However, knowledge about the impacts of changes in water resources on the spatio-temporal dynamics of natural and semi-natural land is still limited. We analyzed the spatio-temporal changes in natural and semi-natural land and the associations with desertification in the Tarim Basin during the period 1990–2015. We then investigated the changes in water resources and the consequent impacts on the spatio-temporal changes of natural and semi-natural land by integrating Gravity Recovery and Climate Experiment territorial water storage data and field observations. The results showed that a total area of 10.32 × 10³ km² of natural and semi-natural land was converted to desert during the period 1990–2015. Desert vegetation type and saline type were the natural and semi-natural land types most sensitive to conversion to desert. The area of natural and semi-natural land decreased by 0.83% every year, and the proportion of desertified land was 34.79% on average during the period 2000–2010; this is less than for the period 1990–2000 (1.14% yr⁻¹ and 52.01%) due to increased availability of water resources from the water conveyance program. However, the rate of decrease of natural and semi-natural land area (0.93% yr⁻¹) and the proportion of desertified land (58.88%) rose again during the period 2010–2015 due to the rapid decrease in water resources. During the period 2000–2015, the rate of loss of natural and semi-natural land area (7.89%) in the region with decreased water resources was about twice that in the region with increased water resources (3.88%), highlighting the critical role of water resources in maintaining natural and semi-natural land and slowing desertification.

Numerous extreme climate anomalies were recorded in the northern extratropics in January–March (JFM) 2020, significantly impacting human lives and ecosystems in the affected areas. Those anomalies were caused by an extreme positive Arctic Oscillation (AO) event, with the JFM 2020 AO index of 2.8 being the highest on the record. However, all well-established autumn precursors pointed towards the following wintertime AO phase being negative. Indeed, a negative AO phase was developing until late December when a sudden shift to the strong positive AO event occurred in the troposphere. The geopotential anomalies associated with positive AO spread into the lower stratosphere, and were steadily enhancing throughout JFM resulting in an extreme positive AO event. We show that the strong positive AO event was a result of the destructive interference of the anomalous planetary waves with climatological ones, which led to wave flattening and enhancement of the polar vortex.

Warming has resulted in increases in frequency, intensity and/or duration of droughts in most land regions over the globe. Nevertheless, knowledge on how ecosystem water use efficiency (WUE) responds to extreme drought stress and whether the responses are affected by drought timing is still limited. In this study, we examined the changes in ecosystem WUE under extreme drought years over Northern Eurasia during 1982–2011 and further assessed WUE responses to droughts with separate groupings designed to characterize the timing of extreme drought stress. We found that drought timing indeed influenced the responses of ecosystem WUE under extreme drought years. Negative impacts of extreme drought stress during the dry season on ecosystem WUE were more remarkable than those from extreme drought stress during the wet season. Particularly, impacts of droughts on ecosystem carbon–water interactions differed among ecosystem types due to the specific hydrothermal condition of each biome. The information provided by our analyses plays an importance role in identifying water use strategies of terrestrial vegetation in response to drought stress and will help improve our understanding and predictions of the response of ecosystem WUE to global environmental change.

Obtaining a better understanding of groundwater dynamics in permafrost zones is a critical issue in permafrost hydrology. This includes assessing the impacts of climate change on permafrost thaw and ground ice-melt. Both permafrost thaw and ground ice-melt can be related to groundwater discharges (i.e. spring discharges), and spring water is an important local water resource; accordingly, changes in these processes can have large impacts on local people and their subsistence activities. To detect permafrost thaw and ground ice-melt in the permafrost zone of Mongolia, groundwater ages of several spring discharges were determined using two transient tracers: tritium (³H) and chlorofluorocarbons (CFCs). Spring water samples were collected seasonally from 2015 to 2019 at seven spring sites around the Khangai Mountains in central Mongolia. The sites included two thermokarst landscapes on the northern and southern sides of the mountains. The ³H and CFC concentrations in the spring water in the thermokarst landscapes were very low, especially on the southern side of the mountains, and the estimated mean groundwater age for these sites was older than that for the other sampled springs. Consequently, the young water ratios of the thermokarst sites were lower than those for the other springs. This ratio, however, showed a gradual increase with time, which indicates that recently recharged rainwater began to contribute to the spring discharge at the thermokarst sites. An atmospheric water budget analysis indicated that net recharge from modern and recent precipitation to shallow groundwater in the summer season was almost zero on the southern side of the mountains. Thus, we inferred that the spring water at the thermokarst sites on the southern side of the mountains contained large amounts of ground ice-melt water.

Biodiversity conservation is one of the most important objectives of protected areas. Most biodiversity assessment-related studies use the change in species abundance data to measure the level of biodiversity conservation. Yet for many areas, long-term species data are not available and thus it is necessary to use biodiversity indices to monitor the effect of land use (LU) changes or the impact of protected area establishment. Poyang Lake wetland is one of the most important wintering sites for migratory water birds on the East Asian–Australasian flyway. To protect this habitat, 14 nature reserves were created in the region between 1997 and 2003. This paper aims to assess the effect of nature reserve creation on the status of habitat for overwintering water birds in Poyang Lake wetland by analysing LU and land cover data from 1995, 2005 and 2015. We developed a composite biodiversity index to search for current biodiversity hotspots (conservation priority) in the study area. An integrated approach consisting of the Integrated Valuation of Ecosystem Services and Trade-offs model, GIS, fragment analysis and hotspot analysis was used to realize our objective. Our results showed that the creation of the nature reserve had positive effects on overwintering water bird habitat. However, tremendous changes (such as change of habitat area, quality and fragmentation) within and outside the nature reserve showed that the role of protected area still needs to be further discussed. Moreover, regional synthesis LU management plans such as ecological restoration should be carried out. The results of the habitat assessment also indicate that a comprehensive biodiversity index framework based on net primary productivity, habitat connectivity and habitat quality could be more efficient in assessing biodiversity and defining a reasonable protected area, from data obtain in large scale perspective.

Mercury (Hg), cadmium (Cd) and lead (Pb) are toxic metals that continue to attract much attention because they are prone to be accumulated in fish tissues and can harm human health if taken up with food. Data acquired by studying the bioaccumulation of these metals in the various fish species from water bodies along a latitudinal gradient in Russia (from northern Arctic lakes to the southern mouth segments of the Volga River) are utilized to identify general tendencies and specifics in the accumulation of toxic metals depending on the aquatic environment and temperature. Results demonstrate that small quantities of the metals are accumulated in various functionally important organs: Hg is enriched in the liver and muscles, Cd in the kidneys and gills, and Pb in the kidneys and liver. The metals are proved to be simultaneously accumulated in all organs and tissues of the organism, and this reflects the uptake of the metals by the organism and their subsequent distribution in it. The aquatic environment and fish habitats affect the elements' bioavailability. The metals are more significantly accumulated in predatory fish. At low Hg concentrations in the water, statistically significant dependences were identified between Hg accumulated in predatory fish organisms and concentrations of organic matter in the water. Cd is more bioavailable in waters with low pH. Pb displays the strongest dependence of its bioaccumulation in low-salinity water. Extensive data on fish in water bodies occurring in large territories in Russia, from the Arctic to warm southern latitudes, indicate that climate affects the intensity of Hg accumulation, whereas the accumulation of the other metals also depends on the Ca concentrations, with the uptake of these metals being more significant at low Ca concentrations. Concentrations of toxic metals in the muscles of the fish were below the values critical to food to be consumed by humans.

Food consumption acts as an intermediary that connects ecosystems with human systems in grassland areas. In this study, we used fuzzy cognitive mapping to quantitatively assess the factors that affect food consumption in the Xilin Gol Grassland, China, from the perspective of local rural households. We found that household perceptions of the factors that affect food consumption differed among parts of the grassland transects in both the number and the strength of these factors. Livestock numbers, household income, regional economic development, consumption habits, age, and infrastructure were the most important factors mentioned by the farmers and herders, but herders were more sensitive to ecological and economic factors, whereas farmers focused more on personal and social factors. The differences in the main factors between study areas revealed the key economic, social, and ecological dimensions. Our results provide a reference for policymakers to develop improved policies to encourage regional sustainable development.

During the past three decades, sea water level (SWL) in the Caspian Sea has declined by about 2 m and sea area has decreased by about 15 000 km². This has affected coastal communities, the environment and economically important gulfs of the sea (e.g. Dead Kultuk). To assess the effects of coastline change and evaluate zones vulnerable to desiccation, we simulated SWL using total inflow from feeder rivers and precipitation and evaporation over the sea. We determined potential vulnerable areas of the sea over the past 80 years by comparing the minimum and maximum annual water body maps (for 1977 and 1995). We then determined the linear regression between SWL rise and covered potential vulnerable area (CVA), using annual Normalised Difference Water Index (NDWI) maps and SWL data from 1977 to 2018. Combining SWL-CVA regression and SWL simulation model enabled us to determine desiccated areas in different regions of the Caspian Sea due to changes in precipitation, evaporation and total inflow. The results showed that 25 000 km² of the sea is potentially vulnerable to SWL fluctuations in terms of desiccation, with 70% of this vulnerable area located in Kazakhstan. Potential vulnerable area per kilometre coastline was found to be 6 km² in Kazakhstan, 4 km² in Russia and whole of Caspian Sea, 1.5 km² in Iran, 1 km² in Azerbaijan and 0.5 km² in Turkmenistan. The results also indicated that SWL in the Caspian Sea is sensitive to evaporation and that e.g. a 37.5 mm decrease in mean annual net precipitation would lead to a 1875 km² decrease in the sea area, while a 1 km³ decrease in mean annual inflow would lead to a 1400 km² decrease in the sea area. Thus the developed framework enabled the spatial consequences of changes in water balance parameters on sea area to be quantified. It can be used to assess future changes in SWL and sea area due to anthropogenic activities and climate change.

Improving wind erosion prevention in the key ecological zones of sand fixation are closely linked to human welfare in China and Northern Eurasia. In this research, we studied the sand transport rate (STT), soil water content (SWC), and retention rate of the wind erosion prevention services (RR) in five experimental zones in Yanchi Country, including bare sandy land (BL), and four restoration zones with different types of vegetation restoration approaches, including artificial restored grassland with low-coverage (AGL), artificial restored grassland with high-coverage (AGH), artificial shrub land (AS), and naturally restored grassland (NG). The results showed that: (1) From 2006 to 2018, the STTs of the four restoration zones were lower than those of BL, and those of the AS were much lower than those of AGL, AGH, and NG; (2) in the rainy season, the SWCs of AS, NG, AGH, AGL, and BL were 3.01%, 2.80%, 2.79%, 2.68%, and 2.41% respectively. In the dry season, the SWCs of NG, BL, AGH, AHL, and AS were 2.86%, 2.93%, 3.00%, 3.08%, and 3.20%, respectively. The differences in the SWCs between the two seasons of BL were the largest (0.52%), while those of NG were the lowest (0.06%); (3) the annual average RRs in AS, AGH, NG, and AGL were 74.41%, 69.41%, 69.28%, and 61.64%, respectively, while the annual change of the RR in the NG was the smallest. This study reveals the effects of different types of vegetation restoration on wind erosion prevention in Yanchi country, thereby providing a scientific basis for policymakers to engage in effective vegetation restoration and formulate ecological protection policies.

As globally important forested areas situated in a context of dramatic socio-economic changes, Siberia and the Russian Far East (RFE) are important regions to monitor for anthropogenic land-use trends. Therefore, we compiled decadal Landsat-derived land-cover and land-use data for eight dominantly rural case study sites in these regions and focused on trends associated with settlements, agriculture, logging, and roads 1975–2010. Several key spatial–temporal trends emerged from the integrated landscape-scale analyses. First, road building increased in all case study sites over the 35-year period, despite widespread socio-economic decline post-1990. Second, increase in settlements area was negligible over all sites. Third, increased road building, largely of minor roads, was especially high in more rugged and remote RFE case study sites not associated with greater agriculture extent or settlement densities. High demands for wood export coupled with the expansion of commercial timber harvest leases starting in the mid-1990s are likely among leading reasons for an increase in roads. Fourth, although fire was the dominant disturbance over all sites and dates combined, logging exerted a strong land-use pattern, serving as a reminder that considering local anthropogenic landscapes is important, especially in Siberia and the RFE, which represent almost 10% of the Earth's terrestrial land surface. The paper concludes by identifying remaining research needs regarding anthropogenic land use in the region: more frequent moderate spatial resolution imagery and greater access to more finely resolved statistical and other spatial data will enable further research.

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Landsat reveals long-term anthropogenic land-use trends in Siberia and Russian Far East

Understanding the joint impact of anthropologic and climatic changes on ecosystem function and dynamics is among the frontiers in global environmental change studies. Carbon and water balances are especially crucial to the sustainable ecosystem and functional returns in sensitive regions such as the Mongolian Plateau. In this study, the significance of non-climatic component (NCC) on carbon and water use efficiency (CUE and WUE) is quantified among the ecosystem types on the Mongolian Plateau. We mapped the spatial gradients of carbon/water balance and delineated the hotspots of NCC-driven CUE and WUE for 2000–2013 using gross and net primary production (GPP and NPP) and evapotranspiration (ET) products derived from the MODIS databases. Significantly higher CUE and WUE values were found in Mongolia (MG) than in Inner Mongolia (IM) due to both climatic forcing (CF) and NCC. NCC was found to dominate the changes in CUE and WUE in the steppes on the plateau by over 16% and 22%, respectively, but with spatially uneven distributions. NCC-driven WUE values were much higher than those driven by CF. The hotspots for NCC-driven CUE did not overlap with those of WUE, with CUE hotspots concentrated in the east of MG and northeast of IM; WUE hotspots were found in the central and Khangai regions of MG and eastern regions of IM. The NCC-driven CUE area in MG was from population growth and the industrial shares in gross domestic product, while the NCC-driven WUE area was due to livestock growth in MG but driven by the growth of cultivated lands in IM. In sum, we conclude that NCC provoked substantial spatiotemporal changes on carbon and water use. CF and NCC effects on carbon and water balance varied in space, by ecosystem type, and between the two political entities.

In eastern Siberia, topography controls the abundance of the larch forest via both drought and flooding stresses. For the reconstruction of these topographical effects, we modified a dynamic vegetation model to represent soil water relocation owing to within-grid heterogeneity of elevation, over-wet-kill of trees, and air temperature differences within-grid. After calibration, the model reasonably reconstructed the geographical distributions of observation-based-estimates of fundamental properties of plant productivity and thermo-hydrology. Thus, the model appropriately responded to environmental gradients in eastern Siberia. The modified model also partially reconstructed the topography control on tree abundance and thermo-hydrology status in eastern Siberia, although its geographical distribution was not always good. In the modified model, soil water redistribution increased the risk of over-wet-kill in lower elevation classes, whereas it reduced the risk of over-wet-kill for larch trees in higher elevation classes. We demonstrated that without considering the latter effect, forest collapse due to over-wet stress would happen throughout eastern Siberia under a forecasted climatic condition during the 21st century, which will deliver a much moister environment throughout eastern Siberia. Therefore, modeling the over-wet-kill of trees without considering topographical heterogeneity would result in the overestimation of forest collapse caused by the over-wet-kill of trees under an expected climate trend in eastern Siberia.

This paper presents metal speciation calculations that are based on mathematical modelling of chemical reactions in natural waters. Metal concentrations (Hg, Cd, Pb, Ni, Cu, Al, Sr) were determined, and their speciation in water were calculated for 22 water areas in the Kola region. Meanwhile, the accumulation of metals in fish organs and tissues was studied (e.g. whitefish). The biogeochemical activity of metals determines the proportions of labile and non-labile speciation in water. In the distribution zones of non-ferrous industry effluents, metal aqua-ions prevail; during the distribution, the proportions change in accordance with the metal activity. The bioavailability of metal speciation is estimated depending on aqueous geochemical conditions and, accordingly, the speciation of metals (in situ), based on the original studies of the lakes of the Kola region in northern Russia. The connection among the metal contents in fish and water has been identified using multidimensional scaling and redundancy analysis techniques. Using the example of natural conditions in northern low-salinity freshwaters, it is demonstrated that labile Cd, Pb, Ni, Cu, Al, and Sr are the species most bioavailable and able to penetrate fish; meanwhile, the organic complexes of Hg, Pb, and Al have a greater affinity to accumulation in the gills. This study demonstrates the need to correct the approved water quality standards in Russia, taking into account the high bioavailability of metals in northern low-salinity waters.

Vegetation is responding to climate change, which is especially prominent in the Arctic. Vegetation change is manifest in different ways and varies regionally, depending on the characteristics of the investigated area. Although vegetation in some Arctic areas has been thoroughly investigated, central Chukotka (NE Siberia) with its highly diverse vegetation, mountainous landscape and deciduous needle-leaf treeline remains poorly explored, despite showing strong greening in remote-sensing products. Here we quantify recent vegetation compositional changes in central Chukotka over 15 years between 2000/2001/2002 and 2016/2017. We numerically related field-derived information on foliage projective cover (percentage cover) of different plant taxa from 52 vegetation plots to remote-sensing derived (Landsat) spectral indices (Normalised Difference Vegetation Index (NDVI), Normalised Difference Water Index (NDWI) and Normalised Difference Snow Index (NDSI)) using constrained ordination. Clustering of ordination scores resulted in four land-cover classes: (1) larch closed-canopy forest, (2) forest tundra and shrub tundra, (3) graminoid tundra and (4) prostrate herb tundra and barren areas. We produced land-cover maps for early (2000, 2001 or 2002) and recent (2016 or 2017) time-slices for four focus regions along the tundra-taiga vegetation gradient. Transition from graminoid tundra to forest tundra and shrub tundra is interpreted as shrubification and amounts to 20% area increase in the tundra-taiga zone and 40% area increase in the northern taiga. Major contributors of shrubification are alder, dwarf birch and some species of the heather family. Land-cover change from the forest tundra and shrub tundra class to the larch closed-canopy forest class is interpreted as tree infilling and is notable in the northern taiga. We find almost no land-cover changes in the present treeless tundra.

Frequent temperature extremes due to climate change have had serious effects on human society and the natural environment. Using a 0.25° × 0.25° gridded Tmax (daily maximum temperature) and Tmin (daily minimum temperature) data set and 12 global climate models simulations from the sixth phase of the Coupled Model Intercomparison Project (CMIP6), we investigated variations in yearly temperature extremes in China during the past five decades with respect to four characteristics, namely, their start date, end date, frequency, and intensity. Results showed that the occurrence of nighttime extremes (the cold nights and warm nights) responded strongly to climate change. For 1961–2017, cold extremes started later (3.25 d/decade) and ended earlier (−4.58 d/decade), with decreased frequency (−6.56 d/decade), especially for cold nights, and weakened intensity (0.14 °C/decade). In the same period, warm extremes started earlier (−3.43 d/decade) and ended later (3.15 d/decade) with increased frequency (6.79 d/decade), especially for warm nights, and enhanced intensity (0.09 °C/decade). The spatial pattern of the variations was complex with anomalous regions. Multimodel ensembles (MMEs) from CMIP6 agreed well with observations regarding the average trends of temperature extremes over China, although detailed changes in spatial pattern were not captured adequately. The hazards of temperature extremes deserve close attention in the future due to the complex changes likely to occur across China for various characteristics of these temperature extremes under conditions of climate change.

The Global Climate Observing System and Global Terrestrial Observing Network have identified permafrost as an 'Essential Climate Variable,' for which ground temperature and active layer dynamics are key variables. This work presents long-term climate, and permafrost monitoring data at seven sites representative of diverse climatic and environmental conditions in the western Russian Arctic. The region of interest is experiencing some of the highest rates of permafrost degradation globally. Since 1970, mean annual air temperatures and precipitation have increased at rates from 0.05 to 0.07 °C yr⁻¹ and 1 to 3 mm yr⁻¹ respectively. In response to changing climate, all seven sites examined show evidence of rapid permafrost degradation. Mean annual ground temperatures increases from 0.03 to 0.06 °C yr⁻¹ at 10–12 m depth were observed in continuous permafrost zone. The permafrost table at all sites has lowered, up to 8 m in the discontinuous permafrost zone. Three stages of permafrost degradation are characterized for the western Russian Arctic based on the observations reported.

Using data collected from a specially designed experiment at the Dunhuang Station (40°10'N, 94°31'E, 1150 m) from September 2017 to September 2018, we have characterized the influences of soil moisture and solar altitude on surface spectral albedo in an arid area. The specific settings of our experiment allowed us to minimize the influences of underlying surface, cloud cover, aerosol and weather conditions, and thus highlight the influence of soil moisture and solar altitude. During the timespan of the experiment, we observed the annual mean surface albedo of global radiation (GR), ultraviolet radiation (UV), visible radiation (VIS) and near-infrared radiation (NIR) to be 0.24, 0.11, 0.24 and 0.25. A significantly negative linear correlation between surface albedo and soil moisture was identified, with the correlation coefficients between GR, UV, VIS, NIR and soil moisture being −0.68, −0.75, −0.70 and −0.61. In addition, we identified an exponential relationship between surface albedo and solar altitude. The exponential regression coefficients are −0.21, −0.077, −0.53 and −0.21, respectively. From these analyses, we derived a new two-factor parametric formula for depicting the influence of soil moisture and solar altitude on surface spectral albedo. Using observation data, we demonstrate that the formula recapitulates the real-world relationship between soil moisture, solar altitude and surface spectral albedo with little deviation. These findings may help us gain a deeper understanding of improving land surface parameterizations and have potential implications for solar energy research and applications.

This paper presents an original approach to characterizing historical fire regimes for regions with limited fire data. Fire variables were derived from satellite datasets and regional fire occurrence statistics. They defined the integral elements of a fire regime such as historical trends, spatiotemporal evolution, fire seasonality and causes. Temporal evolution was investigated based on a regime shift detection method developed by Rodionov while changes in the fire regime were analyzed for statistical significance using the Mann–Kendall trend test and Sen's slope estimator. A descriptive analysis was performed to assess fire seasonality, causes, and together formed the basis for this methodology. We validated the proposed approach by assessing historical fire activity in the Sakha Republic (Yakutia), which is one of the most fire-prone regions of Russia. The assessment was conducted with data from the period of 1996–2018. We detected increases in historical fire activity as well as thresholds of change in the fire regime. Changes during the analysis period included lengthening of fire season, increased burned area extent, and extension of peak fire period. Overall, significant changes in the fire regime were detected in the regions strongly affected by warming and increasing anthropogenic alteration.

Urbanization causes tremendous pressure on biodiversity and ecosystems at the global scale. China is among the countries undergoing the fastest urban expansion. For a long time, ecological environment protection has not been a priority in China's urban planning process. Current urban growth optimization research has some limitations regarding the selection of more scientific ecological constraint indicators and the interaction between urban expansion and ecological factors. This paper at first aimed to establish a reasonable comprehensive biodiversity constraint indicator based on the indicators of net primary productivity, habitat connectivity and habitat quality, and then conducted a case study in Beijing and compared biodiversity loss and urban growth patterns under different developing situations. The integrated valuation of ecosystem services and trade-offs model and GIS-related methods were used to obtain biodiversity and ecological spatial distribution layers. Then an ecological priority-oriented urban growth simulation method was proposed to search for minimum biodiversity loss. The results showed that the important biodiversity security areas were mostly distributed in the western part of the study area and that the ecological degradation in 2000 had a radial pattern and was well in line with the urban construction and ring road distribution patterns. Meanwhile, biodiversity loss with the biodiversity constraint was much less than actual urban growth in 2000–2010. Under the guidance of ecological optimization, urban growth in the research results reflects decentralized and multi-center spatial development characteristics. This type of urban growth not only provides a new model for breaking the inertia of urban sprawl but also proposes 'biodiversity security' as an applicable regulatory tool for urban planning and space governance reforming.

This study aims to perform the results of the investigation of the Kara Sea carbonate system (CS) changes and the factors that determine it. The important feature of the Kara Sea water structure is strong stratification caused mainly by the Ob' and Yenisey rivers discharge which is estimated as 81% of the total continental runoff to sea. Occurring climate changes, as an increase in the total volume of the Arctic Ocean water (due to melting of glaciers, sea ice decline and river runoff increase), air temperature and CO₂ concentration growth should affect greatly the Kara Sea CS. However, riverine water influence seems to be the main driver of future acidification of the Kara Sea water due to permafrost thawing as it stores a great amount of buried carbon. An increase of carbon (mainly inorganic) flow to the sea will lead to carbonate equilibrium shift, oxidation of organic matter and release of CO₂ that ultimately leads to a decrease in pH and therefore acidification. The area of the riverine plume depends on the amount of freshwater flowing into the sea and the conditions of the wind forcing. According to the data from Shirshov Institute cruises within the plume area aragonite saturation is below 1 that shows its state as acidified. Prevalence of pCO₂ values in the freshened surface layer over the atmospheric shows that atmospheric carbon dioxide, apparently, cannot serve as the main driver for the acidification of the surface waters of the Kara Sea. At the shallow shelf to the north of the Ob' Inlet mouth we observe acidification of the whole water column from surface to the bottom layer due to elevated riverine discharge and increase of flowing terrestrial carbon.

Satellite studies using the normalized difference vegetation index (NDVI) have revealed changes in northern Eurasian vegetation productivity in recent decades, including greening in tundra and browning in the boreal forests. However, apparent NDVI changes and relationships to climate depend on the temporal and spatial sampling and the biome and forest-land cover type studied. Here we perform a consistent analysis of NDVI and climate across four bioclimatic zones (tundra, forest-tundra, northern and middle taiga) in northern West Siberia (NWS), further stratified into eight forest-land cover types. We utilize NDVI data from the Moderate Resolution Imaging Spectroradiometer and climate reanalysis data from 2000 to 2016, a period including the record warm anomaly in 2016 (+2 °C–5 °C June–July surface air temperature (SAT) across NWS). Statistically significant (α = 0.05) correlations were found for two bivariate relationships at the biome level: between NDVImax and June–July surface air temperature (SAT)(r ∼ +0.79), and between middle taiga NDVImax and July precipitation (r ∼ +0.48). No significant statistical relationships were found for the northern taiga and forest-tundra biomes. However, within these biomes we found that deciduous needle-leaf (larch) NDVImax is significantly correlated with July temperature (r ∼ +0.48). Qualitatively, spatial composites of NDVI and climate variables were effective for revealing insights and patterns of these relationships at the sub-regional scale. The spatial heterogeneity of NDVI patterns indicates divergent reactions of specific types of vegetation, as well as local effects that are clearly important on the background of a regional climate response.

The distribution of trace elements of anthropogenic origin, especially toxic metals, is an environmental problem. We present the first results of research into the geochemistry of lake waters and metallic pollution in European Russia (ER) and Western Siberia (WS), based on a survey of 367 lakes from the tundra to the steppe zones. The content of more than 80 elements in the lake water was studied; the influence of airborne contamination and the geochemistry of water were estimated. We found that the concentrations of alkaline and alkaline-earth elements, as well as As, V, Co, U, Nb, Sb, increase with a change in the climatic gradient. This fact is explained not only by airborne contamination, but also by the geochemistry of lakes and the climatic factor (increased evaporation concentration). Anthropogenic eutrophication leads to an increase in the content of Fe, Sr, Mo, and acidification—Zn, Cd, Ni, Cu, and especially Pb. There are industry-specific influences: the waters of the northern regions of ER are enriched by Ni, Cd, As, Sb and especially Se because of the emissions from copper-nickel smelters. The oil and gas industry (WS) leads to increased concentrations of V, Pb and Mo in water. We assess the metallic pollution status of surface water in the Eurasian region of Russia using an enrichment factor (EF). In surface waters of ER and WS, metal concentrations do not exceed the maximum permissible concentration, but we have established higher concentrations of many elements in the background, including toxic ones. Prolonged low doses of toxic elements can be a potential hazard to ecosystems and humans. The results showed that from the northern to the southern regions the EF increases for most of the analyzed elements. It can be assumed that with climate warming the concentration of metals in these bodies of water will increase and this is dangerous for the environment.

Due to catastrophic desiccation, today's Aral Sea consists of a few separate residual basins, characterized by different ecological conditions (the Large Aral, Lake Tshchebas, the Small Aral). This study is the first report on dissolved methane concentrations in these basins. Overall, 48 water samples were obtained and analyzed for methane content. High values of dissolved methane in the anaerobic layer of the Large Aral Sea, including the Chernyshev Bay, are apparently caused by damping of vertical mixing and decomposition of abundant organic matter in anoxic conditions. The estimated methane flux from the surface of the Large Aral Sea is actually higher than that from many other lakes in the world. For the anoxic layer of the Large Aral, certain relations between distributions of methane and other hydrochemical parameters, including dissolved oxygen and hydrogen sulfide, were found. In the brackish Small Aral Sea, methane content was moderate. Lake Tshchebas exhibits intermediate conditions between the Large and the Small Aral seas in terms of salinity and methane concentration. The observed differences of methane content and distributions in separate residual basins are linked with the differences of their mixing and oxygenation regimes.

In the past, human migrations have been associated with climate change. As our civilizations developed, humans depended less on the environment, in particular on climate, because technological and economic development in the span of human history allowed us to adapt to and overcome environmental discomfort. Asian Russia (east of the Urals to the Pacific) is known to be sparsely populated. The population is concentrated along the forest-steppe in the south, with its comfortable climate and thriving agriculture on fertile soils. We use current and predicted climate scenarios to evaluate the climate comfort of various landscapes to determine the potential for human settlers throughout the 21st century. Climate change scenarios are taken from 20 CMIP5 general circulation models. Two CO₂ Representative Concentration Pathway scenarios, RCP 2.6 representing mild climate change and RCP 8.5 representing more extreme changes, are applied to the large subcontinental territory of Asian Russia. The ensemble January and July temperature anomaly means and annual precipitation are calculated with respect to the baseline 1961–1990 climate. Three climate indices, which are important for human livelihood and well-being, are calculated based on January and July temperatures and annual precipitation: Ecological Landscape Potential, winter severity, and permafrost coverage. Climates predicted by the 2080s over Asian Russia would be much warmer and milder. Ensemble means do not show extreme aridity. The permafrost zone is predicted to significantly shift to the northeast. Ecological Landscape Potential would increase 1–2 categories from 'low' to 'relatively high' which would result in a higher capacity for population density across Asian Russia. Socio-economic processes and policy choices will compel the development that will lead to attracting people to migrate throughout the century. Therefore, understanding ecological landscape potential is crucial information for developing viable strategies for long-term economic and social development in preparation for climate migration and strategic adaptation planning.

Ecosystem service (ES) flows across geophysical and administrative boundaries are ubiquitous and are receiving more attention in an increasingly metacoupled world. Omitting trans-boundary ES flows from ES assessments will lead to unilateral conclusions and underestimation of ES contributions over distances. Inner Mongolia is an important ecological security barrier of China and Eurasia, but the trans-boundary effect of this barrier is difficult to be quantitatively evaluated and is rarely assessed. This study assessed the ecological security barrier function of Inner Mongolia from the perspective of trans-boundary ES flows, including wind prevention and sand fixation (WPSF), water provision (WP), carbon sequestration (CS) and livestock product provision (LPP) service flows. The trans-boundary value flows for the WPSF, WP, CS and LPP services in 2010 were 6.20 × 10¹⁰ CNY (Chinese currency, yuan), 0.21 × 10¹⁰ CNY, 1.29 × 10¹⁰ CNY and 1.27 × 10¹⁰ CNY, respectively, and 5.89 × 10¹⁰ CNY, 0.16 × 10¹⁰ CNY, 0.37 × 10¹⁰ CNY and 1.33 × 10¹⁰ CNY, respectively, in 2015; correspondingly, the percentages of these trans-boundary value flows in terms of the total value flow were 69.12%, 2.34%, 14.38% and 14.16%, respectively, in 2010 and 76.00%, 2.06%, 4.77% and 17.16%, respectively, in 2015. Therefore, WPSF service plays a more important role in the trans-boundary ecological security barrier function of Inner Mongolia. This study can enhance the understanding of trans-boundary telecoupling in an integral socio-ecological system and identify the critical ESs to form a foundation for ecological conservation measures considering sustainable development.

Wildfire is one of the main disturbances affecting forest dynamics, succession, and the carbon cycle in Siberian forests. The Zabaikal region in southern Siberia is characterized by one of the highest levels of fire activity in Russia. Time series of Landsat data and field measurements of the reforestation state were analyzed in order to estimate post-fire vegetation recovery. The results showed that the normalized burn ratio time series can be used to estimate forest recovery in the pine- and larch-dominated forests of the Zabaikal region. Multiple factors determine a forest's recovery rate after a wildfire, including fire severity, tree species characteristics, topography, hydrology, soil properties, and climate. Assessing these factors is important if we are to understand the effects of fire on forest succession and to implement sustainable forest management strategies. In this work we used the field data and Landsat data to estimate post-fire vegetation dynamics as a function of several environmental factors. These factors include fire severity, pre-fire forest state, topography, and positive surface temperature anomalies. A regression model showed that fire frequency, fire severity, and surface temperature anomalies are the primary factors, explaining about 58% of the variance in post-fire recovery. High frequency of fire and positive surface temperature anomalies hamper the post-fire reforestation process, while more severe burns are followed by higher recovery rates. Further studies are necessary to consider other important factors such as soil properties, moisture, and precipitation, for better explanation of post-fire vegetation recovery.

Long-term changes in convective and stratiform precipitation in Northern Eurasia (NE) over the last five decades are estimated. Different types of precipitation are separated according to their genesis using routine meteorological observations of precipitation, weather conditions, and morphological cloud types for the period 1966–2016. From an initial 538 stations, the main analysis is performed for 326 stations that have no gaps and meet criteria regarding the artificial discontinuity absence in the data. A moderate increase in total precipitation over the analyzed period is accompanied by a relatively strong growth of convective precipitation and a concurrent decrease in stratiform precipitation. Convective and stratiform precipitation totals, precipitation intensity and heavy precipitation sums depict major changes in summer, while the relative contribution of the two precipitation types to the total precipitation (including the contribution of heavy rain events) show the strongest trends in transition seasons. The contribution of heavy convective showers to the total precipitation increases with the statistically significant trend of 1%–2% per decade in vast NE regions, reaching 5% per decade at a number of stations. The largest increase is found over the southern Far East region, mostly because of positive changes in convective precipitation intensity with a linear trend of more than 1 mm/day/decade, implying a 13.8% increase per 1 °C warming. In general, stratiform precipitation decreases over the majority of NE regions in all seasons except for winter. This decrease happens at slower rates in comparison to the convective precipitation changes. The overall changes in the character of precipitation over the majority of NE regions are characterized by a redistribution of precipitation types toward more heavy showers.

Improvement in the efficiency of farmland utilization and multiple cropping systems are of prime importance for achieving food security in China. Therefore, spatially-explicit analysis detecting trends of cropping intensity are important preconditions for sustainable agricultural development. However, knowledge about the spatiotemporal dynamics of cropping intensity in China remains limited. In this study, we generated annual cropping intensity maps in China during 2000–2015 using a rule-based algorithm and MOD09A1 time series imagery. We then analyzed the spatio-temporal changes of cropping intensity. The results showed single-cropping and double-cropping areas were about 1.28 ± 0.027 × 10⁶ km² and 0.52 ± 0.027 × 10⁶ km² in China in 2015 and their areas were relatively stable from 2000–2015. However, cropping intensity had substantial spatial changes during 2000–2015. About 0.164 ± 0.026 × 10⁶ km² of single-cropping area was converted to double-cropping area, which mainly occurred in the Huang-Huai-Hai Region. About 0.193 ± 0.028 × 10⁶ km² of double-cropping area was converted to single-cropping area, which mainly occurred in the southern part of China. About 85% of croplands with decreases in cropping intensity were located in the southern part of China, and about 80% of croplands with increases in cropping intensity was distributed in the Huang-Huai-Hai Region and the northern part of the Middle and Lower Reaches of the Yangtze River region (p < 0.05). The landscapes of different cropping systems tended to be homogenized in major agricultural production regions.

Russian regions containing permafrost play an important role in the Russian economy, containing vast reserves of natural resources and hosting large-scale infrastructure to facilitate these resources' exploitation. Rapidly changing climatic conditions are a major concern for the future economic development of these regions. This study examines the extent to which infrastructure and housing are affected by permafrost in Russia and estimates the associated value of these assets. An ensemble of climate projections is used as a forcing to a permafrost-geotechnical model, in order to estimate the cost of buildings and infrastructure affected by permafrost degradation by mid-21st century under RCP 8.5 scenario. The total value of fixed assets on permafrost was estimated at 248.6 bln USD. Projected climatic changes will affect 20% of structures and 19% of infrastructure assets, costing 16.7 bln USD and 67.7 bln USD respectively to mitigate. The total cost of residential real estate on permafrost was estimated at 52.6 bln USD, with 54% buildings affected by significant permafrost degradation by the mid-21st century. The paper discusses the variability in climate-change projections and the ability of Russia's administrative regions containing permafrost to cope with projected climate-change impacts. The study can be used in land use planning and to promote the development of adaptation and mitigation strategies for addressing the climate-change impacts of permafrost degradation on infrastructure and housing.

This study focuses on changing trends in precipitation across mainland China during the period 1957–2014. We explore the influence of the El Niño–Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), and related large-scale atmospheric circulation variables on the changes in precipitation. The number of wet days showed statistically significant downward trends in North China, Jianghuai, South China, and Southwest of China, but upward trends on the Tibetan Plateau and in Northwest China. However, the number of very wet days increased in Jianghuai, South China and regions in Southwest China, and there was an increase in the spatial variability of a number of rainfall extremes over China. Because the changes in the frequency of wet days and very wet days were non-uniform, an increasing percentage of the total annual precipitation was derived from extreme events over large regions of mainland China. The ENSO and the PDO had a zonal influence on precipitation variability through the modulation of large-scale atmospheric circulation. Both the number of wet days and the frequency of extreme precipitation increased in southern Jianghuai and South China in El Niño years compared with La Niña years. A decrease (increase) in the number of wet days was observed in northern China (southeastern China) during positive PDO-phase years, which was likely a response to the large decrease in Southerly winds.

Russia and Ukraine are countries with relatively large untapped agricultural potentials, both in terms of abandoned agricultural land and substantial yield gaps. Here we present a comprehensive assessment of Russian and Ukrainian crop production potentials and we analyze possible impacts of their future utilization, on a regional as well as global scale. To this end, the total amount of available abandoned land and potential yields in Russia and Ukraine are estimated and explicitly implemented in an economic agricultural sector model. We find that cereal (barley, corn, and wheat) production in Russia and Ukraine could increase by up to 64% in 2030 to 267 million tons, compared to a baseline scenario. Oilseeds (rapeseed, soybean, and sunflower) production could increase by 84% to 50 million tons, respectively. In comparison to the baseline, common net exports of Ukraine and Russia could increase by up to 86.3 million tons of cereals and 18.9 million tons of oilseeds in 2030, representing 4% and 3.6% of the global production of these crops, respectively. Furthermore, we find that production potentials due to intensification are ten times larger than potentials due to recultivation of abandoned land. Consequently, we also find stronger impacts from intensification at the global scale. A utilization of crop production potentials in Russia and Ukraine could globally save up to 21 million hectares of cropland and reduce average global crop prices by more than 3%.

The Warm Arctic–cold Siberia surface temperature pattern during recent boreal winter is suggested to be triggered by the ongoing decrease of Arctic autumn sea ice concentration and has been observed together with an increase in mid-latitude extreme events and a meridionalization of tropospheric circulation. However, the exact mechanism behind this dipole temperature pattern is still under debate, since model experiments with reduced sea ice show conflicting results. We use the early twentieth-century Arctic warming (ETCAW) as a case study to investigate the link between September sea ice in the Barents–Kara Sea (BKS) and the Siberian temperature evolution. Analyzing a variety of long-term climate reanalyses, we find that the overall winter temperature and heat flux trend occurs with the reduction of September BKS sea ice. Tropospheric conditions show a strengthened atmospheric blocking over the BKS, strengthening the advection of cold air from the Arctic to central Siberia on its eastern flank, together with a reduction of warm air advection by the westerlies. This setup is valid for both the ETCAW and the current Arctic warming period.

Projected changes of the thermal growing season (TGS) over Northern Eurasia at 1.5 °C and 2 °C global warming levels are investigated using 22 CMIP5 models under both RCP4.5 and RCP8.5 scenarios. The multi-model mean projections indicate Northern Eurasia will experience extended and intensified TGSs in a warmer world. The prolongation of TGSs under 1.5 °C and 2 °C warming is attributed to both earlier onset and later termination, with the latter factor playing a dominating role. Interestingly, earlier onset is of greater importance under RCP4.5 than under RCP8.5 in prolonging TGS as the world warms by an additional 0.5 °C. Under both RCPs, growing degree day sum (GDD) above 5 °C is anticipated to increase by 0 °C–450 °C days and 0 °C–650 °C days over Northern Eurasia at 1.5 °C and 2 °C warming, respectively. However, effective GDD (EGDD) which accumulates optimum temperature for the growth of wheat, exhibits a decline in the south of Central Asia under warmer climates. Therefore, for wheat production over Northern Eurasia, adverse effects incurred by scorching temperatures and resultant inadequacy in water availability may counteract benefits from lengthening and warming TGS. In response to a future 1.5 °C and 2 °C warmer world, proper management and scientifically-tailored adaptation are imperative to optimize local-regional agricultural production.

The mid-depth temperature maximum (TeM) was measured in an estuarine Bol'shoi Vilyui Lake (Kamchatka peninsula, Russia) in summer 2015. We applied 1D k–ε model LAKE to the case, and found it successfully simulating the phenomenon. We argue that the main prerequisite for mid-depth TeM development is a salinity increase below the freshwater mixed layer, sharp enough in order to increase the temperature with depth not to cause convective mixing and double diffusion there. Given that this condition is satisfied, the TeM magnitude is controlled by physical factors which we identified as: radiation absorption below the mixed layer, mixed-layer temperature dynamics, vertical heat conduction and water-sediments heat exchange. In addition to these, we formulate the mechanism of temperature maximum 'pumping', resulting from the phase shift between diurnal cycles of mixed-layer depth and temperature maximum magnitude. Based on the LAKE model results we quantify the contribution of the above listed mechanisms and find their individual significance highly sensitive to water turbidity. Relying on physical mechanisms identified we define environmental conditions favouring the summertime TeM development in salinity-stratified lakes as: small-mixed layer depth (roughly, ~< 2 m), transparent water, daytime maximum of wind and cloudless weather. We exemplify the effect of mixed-layer depth on TeM by a set of selected lakes.

Despite the potential importance of small (< 1000 m²) thaw ponds and thermokarst lakes in greenhouse gas (GHG) emissions from inland waters of high latitude and boreal regions, these features have not been fully inventoried and the volume of GHG and carbon in thermokarst lakes remains poorly constrained. This is especially true for the vast Western Siberia Lowland (WSL) which is subject to strong thermokarst activity. We assessed the number of thermokarst lakes and their size distribution for the permafrost-affected WSL territory based on a combination of medium-resolution Landsat-8 images and high-resolution Kanopus-V scenes on 78 test sites across the WSL in a wide range of lake sizes (from 20 to 2 × 10⁸ m²). The results were in fair agreement with other published data for world lakes including those in circum-polar regions. Based on available measurements of CH₄, CO₂, and dissolved organic carbon (DOC) in thermokarst lakes and thaw ponds of the permafrost-affected part of the WSL, we found an inverse relationship between lake size and concentration, with concentrations of GHGs and DOC being highest in small thaw ponds. However, since these small ponds represent only a tiny fraction of the landscape (i.e. ~1.5% of the total lake area), their contribution to the total pool of GHG and DOC in inland lentic water of the permafrost-affected part of the WSL is less than 2%. As such, despite high concentrations of DOC and GHG in small ponds, their role in overall C storage can be negated. Ongoing lake drainage due to climate warming and permafrost thaw in the WSL may lead to a decrease in GHG emission potential from inland waters and DOC release from lakes to rivers.

Wildfires are the dominant disturbance agent in the Siberian larch forests. Extensive low- to mediate-intensity non-stand-replacing fires are a notable property of fire regime in these forests. Recent large scale studies of these fires have focused mostly on their impacts on carbon budget; however, their potential impacts on energy budget through post-fire albedo changes have not been considered. This study quantifies the post-fire surface forcing for Siberian larch forests that experienced non-stand-replacing fires between 2001 and 2012 using the full record of MODIS MCD43A3 albedo product and a burned area product developed specifically for the Russian forests. Despite a large variability, the mean effect of non-stand-replacing fires imposed through albedo is a negative forcing which lasts for at least 14 years. However, the magnitude of the forcing is much smaller than that imposed by stand-replacing fires, highlighting the importance of differentiating between the two fire types in the studies involving the fire impacts in the region. The results of this study also show that MODIS-based summer differenced normalized burn ratio (dNBR) provides a reliable metric for differentiating non-stand-replacing from stand-replacing fires with an overall accuracy of 88%, which is of considerable importance for future work on modeling post-fire energy budget and carbon budget in the region.

The deposition of short-lived aerosols and pollutants on snow above the Arctic Circle transported from northern mid-latitudes have amplified the short term warming in the Arctic region. Specifically, black carbon has received a great deal of attention due to its absorptive efficiency and its fairly complex influence on the climate. Cropland burning in Russia is a large contributor to the black carbon emissions deposited directly onto the snow in the Arctic region during the spring when the impact on the snow/ice albedo is at its highest. In this study, our focus is on identifying a possible atmospheric pattern that may enhance the transport of black carbon emissions from cropland burning in Russia to the snow-covered Arctic. Specifically, atmospheric blocking events are large-scale patterns in the atmospheric pressure field that are nearly stationary and act to block migratory cyclones. The persistent low-level wind patterns associated with these mid-latitude weather patterns are likely to accelerate potential transport and increase the success of transport of black carbon emissions to the snow-covered Arctic during the spring. Our results revealed that overall, in March, the transport time of hypothetical black carbon emissions from Russian cropland burning to the Arctic snow is shorter (in some areas over 50 hours less at higher injection heights) and the success rate is also much higher (in some areas up to 100% more successful) during atmospheric blocking conditions as compared to conditions without an atmospheric blocking event. The enhanced transport of black carbon has important implications for the efficacy of deposited black carbon. Therefore, understanding these relationships could lead to possible mitigation strategies for reducing the impact of deposition of black carbon from crop residue burning in the Arctic.

Throughout the Euro-Arctic region of Russia (Murmansk region), there is a substantial increase of metal concentrations in water, which are related to local discharges from the metallurgical and mining industry, transboundary pollution, as well as indirect leaching of elements by acid precipitation. This study collates data to investigate the relationship between surface water contamination by metals, and fish and human health. Fish are used as a biological indicator to show the impact of water pollution by metals on the ecosystem's health. The etiology of fish and human diseases are related to the water pollution and accumulation of metals in organisms. High concentrations of Ni and Cd in water drives an accumulation of these elements in organs and tissues of fish, especially in kidneys. The relation between the accumulation of Ni in kidneys and the development of fish nephrocalcinosis and fibroelastosis was established. Statistical analysis demonstrated that human populations in cities close in proximity to smelters show the highest incidence of disease. The results of histological, clinical, and post-mortem examination of patients shows the highest content of toxic metals, especially Cd, in livers and kidneys. Our complex investigation of a set of disorders observed in fish and human populations indicates that there is a high probability that the negative impact on human health is caused by prolonged water contamination by heavy metals. As a novel finding, this paper shows that based on the similarity of pathological processes and bioaccumulation of metals in fish and humans, examining the content of heavy metals in fish can be used to confirm etiology and evaluate the potential risk to human health by pollution of surface waters.

Few studies have examined changing snow seasonality in Central Asia. Here, we analyzed changes in the seasonality of snow cover across Kyrgyzstan (KGZ) over 14 years from 2002/03–2015/16 using the most recent version (v006) of MODIS Terra and Aqua 8 day snow cover composites (MOD10A2/MYD10A2). We focused on three metrics of snow seasonality—first date of snow, last date of snow, and duration of snow season—and used nonparametric trends tests to assess the significance and direction of trends. We evaluated trends at three administration scales and across elevation. We used two techniques to assure that our identification of significant trends was not resulting from random spatial variation. First, we report only significant trends (positive or negative) that are at least twice as prevalent as the converse trends. Second, we use a two-stage analysis at the national scale to identify asymmetric directional changes in snow seasonality. Results show that more territory has been experiencing earlier onset of snow than earlier snowmelt, and roughly equivalent areas have been experiencing longer and shorter duration of snow seasons in the past 14 years. The changes are not uniform across KGZ, with significant shifts toward earlier snow arrival in western and central KGZ and significant shifts toward earlier snowmelt in eastern KGZ. The duration of the snow season has significantly shortened in western and eastern KGZ and significantly lengthened in northern and southwestern KGZ. Duration is significantly longer where the snow onset was significantly earlier or the snowmelt significantly later. There is a general trend of significantly earlier snowmelt below 3400 m and the area of earlier snowmelt is 15 times greater in eastern than western districts. Significant trends in the Aqua product were less prevalent than in the Terra product, but the general trend toward earlier snowmelt was also evident in Aqua data.

While the global carbon budget (GCB) is relatively well constrained over the last decades of the 20th century [1], observations and reconstructions of atmospheric CO₂ growth rate present large discrepancies during the earlier periods [2]. The large uncertainty in GCB has been attributed to the land biosphere, although it is not clear whether the gaps between observations and reconstructions are mainly because land-surface models (LSMs) underestimate inter-annual to decadal variability in natural ecosystems, or due to inaccuracies in land-use change reconstructions.

As Eurasia encompasses about 15% of the terrestrial surface, 20% of the global soil organic carbon pool and constitutes a large CO₂ sink, we evaluate the potential contribution of natural and human-driven processes to induce large anomalies in the biospheric CO₂ fluxes in the early 20th century. We use an LSM specifically developed for high-latitudes, that correctly simulates Eurasian C-stocks and fluxes from observational records [3], in order to evaluate the sensitivity of the Eurasian sink to the strong high-latitude warming occurring between 1930 and 1950. We show that the LSM with improved high-latitude phenology, hydrology and soil processes, contrary to the group of LSMs in [2], is able to represent enhanced vegetation growth linked to boreal spring warming, consistent with tree-ring time-series [4]. By compiling a dataset of annual agricultural area in the Former Soviet Union that better reflects changes in cropland area linked with socio-economic fluctuations during the early 20th century, we show that land-abadonment during periods of crisis and war may result in reduced CO₂ emissions from land-use change (44%–78% lower) detectable at decadal time-scales.

Our study points to key processes that may need to be improved in LSMs and LUC datasets in order to better represent decadal variability in the land CO₂ sink, and to better constrain the GCB during the pre-observational record.

Central Asia has been rapidly changing in multiple ways over the past few decades. Increases in temperature and likely decreases in precipitation in Central Asia as the result of global climate change are making one of the most arid regions in the world even more susceptible to large-scale droughts. Global climate oscillations, such as the El Niño–Southern Oscillation, have previously been linked to observed weather patterns in Central Asia. However, until now it has been unclear how the different climate oscillations act simultaneously to affect the weather and subsequently the vegetated land surface in Central Asia. We fit well-established land surface phenology models to two versions of MODIS data to identify the land surface phenology of Central Asia between 2001 and 2016. We then combine five climate oscillation indices into one regression model and identify the relative importance of each of these indices on precipitation, temperature, and land surface phenology, to learn where each climate index has the strongest influence. Our analyses illustrate that the North Atlantic Oscillation, the East Atlantic/West Russia pattern, and the Atlantic Multi-Decadal Oscillation predominantly influence temperature in the northern part of Central Asia. We also show that the Scandinavia index and the Multivariate ENSO index both reveal significant impacts on the precipitation in this region. Thus, we conclude that the land surface phenology across Central Asia is affected by several climate modes, both those that are strongly linked to far northern weather patterns and those that are forced by southern weather patterns, making this region a 'climate change hotspot' with strong spatial variations in weather patterns. We also show that regional climate patterns play a significant role in Central Asia, indicating that global climate patterns alone might not be sufficient to project weather patterns and subsequent land surface changes in this region.

Temperate grasslands, including those of northern Eurasia, are among the most imperiled ecosystems on Earth. Eighty percent of Mongolia's land area is rangeland, where interacting climate, land-use and changes in governance threaten the sustainability of Mongolia's rangelands and pastoral culture. Particularly concerning are the potential ecological impacts of changing pastoral grazing practices—namely declining use of grazing reserves and pastoral mobility. However, like other grazing practices globally, there have been no empirical studies to evaluate the effects of specific Mongolian grazing practices on ecological function at a management scale. We collected data on the grazing practices of 130 pastoral households across four ecological zones and sampled ecological conditions in their winter pastures. We used a novel social-ecological analysis process to (1) develop integrated, holistic indicators of ecological function using exploratory and confirmatory factor analysis, and (2) assess the effects of individual grazing practices on these indicators using statistical matching to control for confounding management and contextual factors. We identified two latent factors related to ecological and pastoral resilience: Factor 1 represents resource retention and soil stability and Factor 2 represents species richness and functional diversity. Using these two factors as response variables, we found that the values of both resilience factors were higher in pastures where households made fall or winter otor migrations or set aside grazing reserves. This study provides the first management-scale empirical test of the ecological response to specific grazing practices in Mongolia, using an approach that can be applied in other rangeland systems. Our findings highlight the importance to ecological and pastoral resilience of supporting traditional pastoral practices of mobility and grazing reserves, while also controlling stocking densities, increasing rangeland monitoring, and ensuring equitable access to state-designated emergency grazing reserves at local, regional, and national levels.

Dense meteorological networks are needed to advance understanding of urban climatology in the northern polar region where global warming is rapid and amplified. High quality and density urban temperature datasets are required to monitor thawing processes in urban soils, properly assess and project climatic trends in human comfort, air quality and weather extremes. This study presents an Urban Heat Island Arctic Research Campaign (UHIARC) observational network, which has been deployed in several mid-sized cities (Salekhard, Vorkuta, Nadym, Novy Urengoy) of the Eurasian Arctic region in the winter of 2016–2017. The network comprises an array of air temperature loggers and one automatic weather station in each of these four cities. The UHIARC observations revealed strong warm temperature anomalies in all four cities. Such persistent temperature anomalies are frequently referred to as urban heat islands (UHIs). The mean wintertime magnitude of these temperature anomalies (the UHI intensity) was found to be between 0.8 K and 1.4 K. Extreme UHI intensities up to 7 K were observed during cold anticyclonic weather conditions. Such a strong mediation of cold temperature spells by UHI might induce considerable socio-economic and environmental impacts in the cities. The UHIARC dataset is available for further analysis from http://urbanreanalysis.ru/uhiarc.html.

The impact of grazing activity on terrestrial carbon (C) sequestration has been noticed and studied worldwide. Recent efforts have been made to incorporate the disturbance into process-based land models. However, the performance of grazing models has not been well investigated at large scales. In this study, we performed a spatially explicit model uncertainty assessment in the world's largest pasture ecosystem, the temperate Eurasian Steppe. Five grazing models were explicitly incorporated into a single terrestrial biogeochemical model to simulate regional C consumption from grazing activity (C_graze). First, we summarized the underlying mechanisms and explicitly compared the general functions used to describe the processes in different models. Then, the models (five models with 12 simulations) were run in parallel using the same forcing data and livestock distribution map in 2006. Results indicated that the modeled regional C_graze varied from 0.1–16.1 gC m⁻² for the year. The corresponding ratios of C_graze to aboveground net primary productivity ANPP and net primary productivity (NPP) ranged from 0.08%–24.6% and 0.028%–11.2%, respectively. Parameter sensitivity was further analyzed. Model outputs are highly sensitive to the intake rate (i.e. feeding rate of livestock per day), half maximum intake rate, and initial livestock weight. Our results indicate that great uncertainty exists in simulating C_graze. We ascribed the major uncertainty to the different process description and poor parameterization. This study calls for more efforts to the comprehensive synthesis of usable dataset, the foundation of a standard observation system and the observe-based inter-comparison to evaluate models, which would facilitate more accurate assessment of C sequestration by pasture ecosystems and lead to better representation in earth system models.

This study focuses on the assessment of forest cover and disturbance changes in the heavily polluted Ore Mountains (Czechia, Central Europe) during the second half of the 20th century and onward. It analyzes the driving forces of forest changes with reference to environmental, societal and political development in the region. Anthropogenic air pollution, prevalently SO₂ from adjacent coal-burning industry, caused extensive forest decline, especially between the 1970s and 1980s. The most affected tree species was the main economical timber species, Norway spruce, which proved to be remarkably pollution-sensitive. We used Landsat time series, and a combination of an integrated forest Z-score and Disturbance Index (DI), to analyze the forest cover change and disturbance development during 1985–2016. In 1994, the forest cover reached its minimum there. The breakdown of communism in the 1990s implied fulfilling EU pollution standards via air protection regulations, investment in power plant desulphurization, and forest management measures, which were the main drivers of the forest recovery. The forest recovery continued till about 2005; however, fluctuations in forest cover and DI have continued during the last decade. Apparently, forests weakened by old loads are prone to new stress factors. Landsat time series represent a powerful data source to monitor the impact of these drivers on forests on a regional scale. Originally, the severely damaged eastern part with heavier acidic load and large forest decline recovered faster after remarkable lowering of air pollution loads compared to the western part, with lower loads and less damaged forests. However, the interactions of persisting driving forces (soil acidification, adverse meteorological events, climate change factors, air pollution, tree species composition and physiological state, pest outbreaks) still threaten the forests there, which remain moderately damaged in both parts of the Ore Mountains. This may lead to unpredictable forest development independently of societal and political driving forces.

Spanning a vast territory of approximately 13 million km², Asian Russia was home to 38 million people in 2016. In an effort to synthesize data and knowledge regarding urbanization and sustainable development in Asian Russia in the context of socioeconomic transformation following the breakup of the Soviet Union in 1990, we quantified the spatiotemporal changes of urban dynamics using satellite imagery and explored the interrelationships between urbanization and sustainability. We then developed a sustainability index, complemented with structural equation modeling, for a comprehensive analysis of their dynamics. We chose six case cities, i.e., Yekaterinburg, Novosibirsk, Krasnoyarsk, Omsk, Irkutsk, and Khabarovsk, as representatives of large cities to investigate whether large cities are in sync with the region in terms of population dynamics, urbanization, and sustainability. Our major findings include the following. First, Asian Russia experienced enhanced economic growth despite the declining population. Furthermore, our case cities showed a general positive trend for population dynamics and urbanization as all except Irkutsk experienced population increases and all expanded their urban built-up areas, ranging from 13% to 16% from 1990 to 2014. Second, Asian Russia and its three federal districts have improved their sustainability and levels of economic development, environmental conditions, and social development. Although both regional sustainability and economic development experienced a serious dip in the 1990s, environmental conditions and social development continuously improved from 1990 to 2014, with social development particularly improving after 1995. Third, in terms of the relationships between urbanization and sustainability, economic development appeared as an important driver of urbanization, social development, and environmental degradation in Asian Russia, with economic development having a stronger influence on urbanization than on social development or environmental degradation.

Ecological restoration has increased in prominence since the last century as an active way to reverse ecosystem deterioration derived from human interventions. The goal of this study was to assess the impact of restoration approaches on ecological and economic conditions of typical regions in the Qinghai-Tibetan Plateau. Data were collected using structured questionnaires delivered to 195 herders living in areas with average elevation above 3773 m. Land use maps, MODIS images, and government statistics were also used for the study. It was found that local herders have adopted five major approaches, i.e. enclosure, grazing prohibition, enclosure + deratization, enclosure + deratization + grass seeding, and enclosure + deratization + crop-forage cultivation + warm sheds, to ensure success of the restoration programs initiated by the government. The results show that vegetation coverage, especially for high and very high coverage grasslands, increased across the study sites and across approaches used, with a high grassland recovery rate observed in the areas where either grazing is prohibited or grassland management was dominated by integration approaches. Furthermore, households who employed integrated approaches tended to have more animals to rear, higher capability of resisting risks, and higher income than those who did not. These findings imply that balanced ecological and economic development is possible when appropriate management approaches are adopted. However, evaluation and monitoring of grassland conditions are needed to readjust restoration policy and associated approaches in a timely manner.

Acidic deposition has caused severe surface water acidification in Europe and North America, but surface water acidification has not been systematically studied in Russia. Here we present the first detailed study on regional surface water acidification in European Russia (ER) and Western Siberia (WS) based on a survey of 367 lakes in a transect from the tundra to the steppe, which were investigated to explore the status and mechanism of surface water acidification. The variability of water chemistry is documented and discussed. High pH and acid-neutralizing capacity (ANC) were observed for lakes in the southern region, indicating that surface water acidification does not occur here. Anthropogenic acidification occurs in the humid areas of both regions, being observed in 4.4% of ER and 8.2% of WS lakes. These tundra and taiga lakes are characterized by high transparency, low pH, and ANC with a high concentration of strong acid anions. The main factor leading to acidification in the ER lakes is sulfur emission from metal smelters whilst that in WS is acidification, likely associated with gas burning by oil production facilities. In the ER acid lakes, SO₄²⁻ is dominant; this is in contrast to WS, where NO₃⁻ and Cl⁻ are dominate. The influence of strong technogenic acids on the structure of organic components and their possibility to form a proton is discussed. The phenomenon of the increase in water acidification by organic acids and strong acids is explained. These results clearly show the effect of a number of factors that strengthen the acidity of water. Differences in the chemical composition of lakes of both regions, as well as differentiation by their acid properties, were statistically proved. Results of our research indicate the need to reduce emissions of acidic gases into the atmosphere.

The dryland belt (DLB) in Northern Eurasia is the largest contiguous dryland on Earth. During the last century, changes here have included land use change (e.g. expansion of croplands and cities), resource extraction (e.g. coal, ores, oil, and gas), rapid institutional shifts (e.g. collapse of the Soviet Union), climatic changes, and natural disturbances (e.g. wildfires, floods, and dust storms). These factors intertwine, overlap, and sometimes mitigate, but can sometimes feedback upon each other to exacerbate their synergistic and cumulative effects. Thus, it is important to properly document each of these external and internal factors and to characterize the structural relationships among them in order to develop better approaches to alleviating negative consequences of these regional environmental changes. This paper addresses the climatic changes observed over the DLB in recent decades and outlines possible links of these changes (both impacts and feedback) with other external and internal factors of contemporary regional environmental changes and human activities within the DLB.

Systematic errors in forecast near-surface air temperature (SAT) still constitute a considerable problem for numerical weather prediction (NWP) at high latitudes. Numerous studies in the past have attempted to reduce this problem through recalibration of physical parameterization schemes and better approximation of the surface energy budget. The errors, however, remain despite notable improvements in the overall weather forecast performance. This study looks at the problem from a different perspective. It analyzes asymmetries in the SAT forecast errors. The study reveals a statistical pattern of warm SAT biases under cold weather conditions and cold SAT biases under warm weather conditions. The largest errors were found in shallow atmospheric boundary layers (ABLs). The study attributes the problem to the modeled excessive ABL thickness in northern Eurasia (the NEFI region). The ABL thickness is considered as a scaling factor controlling the efficacy of the applied surface heating. Too thick an ABL damps the magnitude and agility of the SAT response. The study utilized the operational model SL-AV of the Russian Hydrometeorological Centre. Two turbulence schemes were evaluated in the northern European and western Siberian regions of Russia against observations from 73 meteorological stations. The pTKE (old) scheme is based on the local balance of the turbulence characteristics. The TOUCANS (new) scheme incorporated the total turbulence energy equations in an energy-flux balance approach. Neither scheme uses the ABL thickness as a prognostic parameter. The study reveals that the SAT errors are consistent with the damped response of temperature and reduced agility of temperature fluctuations in too thick ABLs. The TOUCANS scheme did not improve those features, probably because it links the turbulent fluxes and the ABL thickness. The SAT errors in shallow ABLs persist in the new scheme. This study emphasizes the need for a closer look at the ABL thickness in the NWP models.

Forest inventory and biomass mapping are important tasks that require inputs from multiple data sources. In this paper we implement two methods for the Ukrainian region of Polissya: random forest (RF) for tree species prediction and k-nearest neighbors (k-NN) for growing stock volume and biomass mapping. We examined the suitability of the five-band RapidEye satellite image to predict the distribution of six tree species. The accuracy of RF is quite high: ~99% for forest/non-forest mask and 89% for tree species prediction. Our results demonstrate that inclusion of elevation as a predictor variable in the RF model improved the performance of tree species classification. We evaluated different distance metrics for the k-NN method, including Euclidean or Mahalanobis distance, most similar neighbor (MSN), gradient nearest neighbor, and independent component analysis. The MSN with the four nearest neighbors (k = 4) is the most precise (according to the root-mean-square deviation) for predicting forest attributes across the study area. The k-NN method allowed us to estimate growing stock volume with an accuracy of 3 m³ ha⁻¹ and for live biomass of about 2 t ha⁻¹ over the study area.

In many terrestrial regions, higher than usual surface temperatures are associated with (or are even induced by) surface moisture deficits. When in the warm season temperatures become anomalously high, their extreme values affect human beings causing heat stress. Besides increased temperature, rising humidity may also have substantial implications for bodily thermal comfort. However, the effects of surface moisture on heat stress, when considering both temperature and humidity, are less known. In this study, the relationship between the number of hot days in July as indicated by the wet-bulb globe temperature and the preceding three months of precipitation was assessed over eastern China. It is found that the probability of occurrence of above the average number of hot days exceeds 0.7 after a preceding precipitation deficit in northeastern China, but is less than 0.3 in southeastern China. Generally, over eastern China, the precipitation in the preceding months is negatively correlated with temperature and positively correlated with specific humidity in July. The combined effects generate a spatially distinct pattern: precipitation deficits in preceding months enhance heat stress in northeastern China while in southern China these deficits are associated with reduction of heat stress. In the south, abundant preceding precipitation tends to increase atmospheric humidity that is instrumental for the increase of heat stress. These results contribute predictive information about the probability of mid-summer heat stress in eastern China a few weeks ahead of its occurrence.

In this paper, we analyze observational and reanalysis data to demonstrate that the Atlantic Multidecadal Oscillation (AMO) significantly modulates winter Eurasian surface air temperature through its impact on the shape, frequency and persistence of Ural blocking (UB) events that last for 10–20 d. This impact results from changes in mid-high latitude westerly winds over Eurasia associated with the warming in the Barents–Kara Seas (BKS) through the AMO-driven high sea surface temperature and sea-ice decline and resultant weakening in meridional temperature gradients. The BKS warming has a strongest positive correlation with the AMO at a time lag of about 14 years. During the recent positive AMO phase, more persistent northwest–southeast (NW–SE) oriented UB events are favored by weakened westerly winds in Eurasian mid-high latitudes. Through cold atmospheric advection and radiative cooling, such UB events produce a strong, persistent and widespread cooling over Eurasia and enhance BKS warming during 1999–2015. However, the positive AMO phase cannot directly produce the Eurasian cooling if the UB is absent. Thus, we conclude that the recent AMO phase change is a major cause of the recent winter cooling over Eurasia through its impact on BKS temperature and sea ice, which in turn affect the meridional temperature gradient, the westerly winds and the UB events.

Carbon dioxide (CO₂) fluxes by different methods vary largely at global, regional and local scales. The net CO₂ fluxes by three bottom-up methods (tower observation (TWR), biogeochemical models (GTM), and a data-driven model (SVR)), and an ensemble of atmospheric inversions (top-down method, INV) are compared in Yakutsk, Siberia for 2004–2013. The region is characterized by highly homogeneous larch forest on a flat terrain. The ecosystem around Yakutsk shows a net sink of CO₂ by all the methods (means during 2004–2007 were 10.9 g C m⁻² month⁻¹ by TWR, 4.28 g C m⁻² month⁻¹ by GTM, 5.62 g C m⁻² month⁻¹ and 0.863 g C m⁻² month⁻¹ by SVR at two different scales, and 4.89 g C m⁻² month⁻¹ by INV). Absorption in summer (June–August) was smaller by three bottom-up methods (ranged from 88.1 to 191.8 g C m⁻² month⁻¹) than the top-down method (223.6 g C m⁻² month⁻¹). Thus the peak-to-trough amplitude of the seasonal cycle is greater for the inverse models than bottom-up methods. The monthly-mean seasonal cycles agree among the four methods within the range of inter-model variations. The interannual variability estimated by an ensemble of inverse models and a site-scale data-driven model (the max-min range was 35.8 g C m⁻² month⁻¹and 34.2 g C m⁻² month⁻¹) is more similar to that of the tower observation (42.4 g C m⁻² month⁻¹) than those by the biogeochemical models and the large-scale data-driven model (9.5 g C m⁻² month⁻¹ and 1.45 g C m⁻² month⁻¹). The inverse models and tower observations captured a reduction in CO₂ uptake after 2008 due to unusual waterlogging.