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High-resolution temperature reconstructions in the previous millennium are limited in Northeast Asia, but they are important for assessing regional climate dynamics. Here, we present, for the first time, a 202-year reliable reconstruction of April temperature changes before the millennium volcanic eruption in 946 CE using tree rings of carbonized logs buried in the tephra in Changbai Mountain, Northeast Asia. The reconstructed temperature changes were consistent with previous reconstructions in China and the Northern Hemisphere. The influences of large-scale oscillations (e.g. El Niño–Southern Oscillation, ENSO) on temperature variability were not significantly different between the periods of 745–946 CE preceding the eruption and 1883–2012. However, compared to the palaeotemperature of the previous millennium, the temperature changes were more complex with stronger temperature fluctuations, more frequent temperature abruption, and a weaker periodicity of temperature variance during the last 130 years. These recent changes correspond to long-term anthropogenic influences on regional climate. [ABSTRACT FROM AUTHOR]

Constructing disturbance regimes is key to understanding current forest conditions and anticipating future changes. Many disturbance regimes, however, can only be constructed over large areas and long time-spans to capture the stochasticity of individual disturbance events. Typically, field-based approaches can go sufficiently back in time but are limited to small areas (e.g., several hectares), while remote-sensing-based approaches can cover large areas but are limited to relatively short-time spans (e.g., several decades). In this study, we developed a framework that combines contemporary and pre-remote-sensing disturbances to construct a disturbance regime for a large region. Specifically, we extracted the contemporary disturbances (1984–2021) from remote-sensing data, from which we trained machine-learning models (XGBoost algorithm) to predict key disturbance attributes, including the elapsed time since disturbance and spatial contraction distance, which were used to derive the occurrence time and original extent of individual disturbance events. We then extracted pre-remote-sensing disturbances from the earliest remote-sensing images (1980s) and used the machine-learning models to extrapolate the pre-remote-sensing disturbance attributes and thus expanded the timespan to 1900. Our approach incorporates ecological factors key to characterizing spatiotemporal dynamics in post-disturbance forest recovery, including vegetation index to represent recovery stage, disturbance pattern (shape and size of disturbed patches), distance to the edge of disturbed patches to reflect the effects of seed dispersal, and topography and forest type to capture the effects of spatial heterogeneity in environment and vegetation. We tested the framework in a wind-prone region of Changbai Mountain, northeast China. We showed that our approach can derive spatially-explicitly severe wind disturbance events for a large region over a long time-span while capturing the spatiotemporal stochasticity of the wind disturbance regime. The framework represents a process in constructing disturbance regimes over large areas, and it is transferable to other forest regions and other types of disturbances such as fire. The derived disturbance regime could fill the information gap of forest restoration and management. • Develop framework to construct disturbance regime over large region and long timespan. • Use contemporary remote sensing and pre-remote-sensing disturbances events. • Incorporate ecological factors key to characterizing post-disturbance dynamics. • The framework is transferable to other regions and other types of disturbances. [ABSTRACT FROM AUTHOR]

ABSTRACT On the basis of the daily minimum temperature, records of 109 meteorological stations over Northeastern China ( NEC) from 1961 to 2013 and the output data of eight models from CMIP5, this study investigates the recent and future spatiotemporal changes of the frost-free season. The results show that the date of last spring frost ( LSFD) has a significant decreasing trend. Stations exhibiting significant negative trends are mostly distributed in the eastern Jilin Province and the Midwest of Heilongjiang Province. The date of first fall frost ( FFFD) and length of frost-free season ( LFFS) both show significant increasing trends. The spatial patterns of stations showing significant positive trends in the FFFD and LFFS are similar, which are mainly located in the middle part of Eastern Inner Mongolia and the south and middle parts of Changbai Mountains. The LFFSs have significant increasing trends with the magnitudes of 0.49 days/decade for RCP2.6, 1.62 days/decade for RCP4.5, and 3.85 days/decade for RCP8.5 during 2006-2100. The southern Liaoning Province and the northwestern NEC will experience the longer LFFS under each scenario between 2071 and 2100. The frost-free season indices have significant correlations with the Northern Hemisphere Polar Vortex Area index. The atmospheric circulation patterns of an anticyclonic circulation anomaly prevailed over the Lake Baikal region and a cyclonic circulation anomaly located in the northwest Pacific Ocean in springs and an anticyclonic circulation anomaly prevailed over the south part of the Russian Far East in falls block more cold air flowing into NEC, which result in the earlier LSFD and later FFFD. The adverse patterns in springs and in falls could bring out the later LSFD and earlier LSFD, respectively. Our results could benefit the prevention and reduction of frost disaster and provide a reference for the policy-making of future crop production. [ABSTRACT FROM AUTHOR]

ABSTRACT Climate involves different combinations of temperature and precipitation, and each year's combination of factors can be assigned a climatic year type ( CYT; e.g. Warm-Humid). Describing the changes in the CYT provides more information than describing the temperature or precipitation data alone. In this study, we defined nine CYTs using the probability density function of annual temperature and precipitation. Recent and future spatiotemporal changes in CYT were analysed using 507-station observational data and projected data obtained from the CMIP5 multi-model ensemble under RCP2.6, RCP4.5, and RCP8.5 scenarios. China was divided into six subregions to analyse the spatiotemporal changes. Obvious differences in spatial patterns among the various CYTs reflect the climate regime throughout China. The warmth-associated CYTs (Warm-Humid, Warm-Dry, and Warm-Normal) mainly occur in West China (e.g. Southwest China). The cold-associated CYTs (Cold-Humid, Cold-Dry, and Cold-Normal) dominate at high latitudes and high altitudes (e.g. Northeast China and the Tibetan Plateau). The climate in China changed from cold to warm in the last half-century, accompanying the transformation of Cold-Humid, Cold-Dry, and Cold-Normal before the early 1990s to Warm-Humid, Warm-Dry, and Warm-Normal from the early 1990s onward. In the 21st century, the projected CYTs are mainly Warm-Humid, Warm-Dry, and Warm-Normal in China. Warm-Humid dominates in West China, North China, and Northeast China. Warm-Dry is mainly projected in the Yellow River Valley and South China. High-frequency Warm-Normal is projected in the Yellow River Valley. Warm-Humid is projected to increase whereas Warm-Dry and Warm-Normal are projected to decrease from 2015 to 2099. All three CYTs are projected to exhibit larger changes in trends under stronger versus weaker RCPs ( RCP8.5 > RCP4.5 > RCP2.6). Compared with temperature or precipitation data alone, CYTs provide more complete information on climate change and more accurately characterize regional differences in climate throughout China. [ABSTRACT FROM AUTHOR]

More than half of the world's population is living in towns and cities according to the United Nations Population Fund (). The rapid urbanization, especially in China, has significantly influenced the climate at least at a local scale. The increasing extreme temperature (ET) occurrence in urban areas prompts us to examine the historical and current situation of ET occurrence in cities by comparing them with that in mountains which provide a relatively natural record of the earth's climate because they are far away from cities and it is not influenced by urbanization effects. The ET occurrence was determined by multifractal detrended fluctuation analysis (MF-DFA), a well-accepted method aiming at finding the ET thresholds according to the characteristics of the data themselves. Warming trends in the city and mountain sites and the frequencies, intensities, and severities of ET occurrence were compared using climatic data between 1959 and 2011. The results show that the warming amplitude of the cities is not higher than that of the mountain regions, even with urbanization effect. The extremely low temperatures (ELT) in the cities occurred significantly lower in frequency and severity compared with that in the mountain sites. However, the intensity of ELT is generally higher than that in the mountains. Only the cities at low latitudes in China have experienced more frequent and severe extremely high temperature (EHT) occurrence than the mountain sites in recent decades. But the intensity was not as high as that in the mountain sites. We conclude that the current situation of ET occurrence in the cities is not very serious if we consider the ET occurrence of the mountains as the 'new norm.' However, it is highly possible that the frequency of ET, especially the EHT, in the cities would increase and will be even more than that of the mountains. Moreover, the changes of ET occurrences before and after 1980 are distinguishable, which could be attributed to urbanization. [ABSTRACT FROM AUTHOR]

In this study, the multifractal detrended fluctuation analysis method is employed to determine the thresholds of extreme events. Subsequently, the characteristics of extreme temperatures have been analyzed over Northeast China during 1961-2009. Approximately 58 % of stations have negative interdecadal trends of −2.2 days/10 years to 0 days/10 years in extreme low minimum temperature (ELMT) frequency. Notable positive trend of 0-2.5 days/10 years in extreme high maximum temperature (EHMT) frequency of about 94 % stations are found. Approximately 58 % of stations have decreasing trend in ELMT intensity, whereas 69 % of stations have increasing trend of EHMT intensity. The trends are the range of −0.72 °C/10 years to 0 °C/10 years and 0-0.7 °C/10 years, respectively. We propose the extreme temperatures indices, ELMT index (ELMTI) and EHMT index (EHMTI), which combined the frequency and intensity of extreme temperatures to represent the order of severity of extreme temperatures. According to this approach, serious ELMT mainly occur in the Songliao Plain and the Sanjiang Plain, especially in the Songliao Plain. Serious EHMT distinctly occur in the Sanjing Plain, and the southwestern and northwestern regions of Northeast China in recent five decades. [ABSTRACT FROM AUTHOR]

Daily global solar radiation is an important input required in most crop models. In the present study, a sunshine-based model, the Ångström-Prescott model, is employed to estimate daily global solar radiation on a horizontal surface during the growing season in Northeast China. Data from six control groups are used. The controls include the entire sequence, precipitation days, and non-precipitation days both during the growing season and year-round. Estimations are validated by comparing the calculated values with the corresponding measured values. The results indicate that estimating daily global solar radiation during the growing season using data only from the growing season is better than using year-round data. Classifying days with respect to precipitation and non-precipitation is also unnecessary. The performance on estimating daily global solar radiation during the growing season using the entire data in growing season performs best. A sunshine-based equation is obtained using our method to estimate growing season daily radiation for all meteorological stations in Northeast China. The approved approach is expected to be beneficial to crop models and other agricultural purposes. [ABSTRACT FROM AUTHOR]

Environmental factors that drive carbon storage are often used as an explanation for alpine treeline formation. However, different tree species respond differently to environmental changes, which challenges our understanding of treeline formation and shifts. Therefore, we selected Picea jezoensis and Betula ermanii, the two treeline species naturally occurring in Changbai Mountain in China, and measured the concentration of non-structural carbohydrates (NSC), soluble sugars and starch in one-year-old leaves, shoots, stems and fine roots at different elevations. We found that compared with P. jezoensis, the NSC and soluble sugars concentrations of leaves and shoots of B. ermanii were higher than those of P. jezoensis, while the starch concentration of all the tissues were lower. Moreover, the concentration of NSC, soluble sugars and starch in the leaves of B. ermanii decreased with elevation. In addition, the starch concentration of B. ermanii shoots, stems and fine roots remained at a high level regardless of whether the soluble sugars concentration decreased. Whereas the concentrations of soluble sugars and starch in one-year-old leaves, shoots and stems of P. jezoensis responded similarly changes with elevation. These findings demonstrate that compared with P. jezoensis, B. ermanii has a higher soluble sugars/starch ratio, and its shoots, stems and fine roots actively store NSC to adapt to the harsh environment, which is one of the reasons that B. ermanii can be distributed at higher altitudes. [ABSTRACT FROM AUTHOR]

• Examine effects of daily to seasonal climate data on simulated tree biomass. • Examine effects of the climate data on mono and multiculture forest systems. • Quantify relative importance of climate data and inter-species competition. Terrestrial ecosystem models are driven by climate data, which often have daily, monthly, and seasonal resolutions, but few have examined the effects of different temporal resolutions of climate data on modeled vegetation change. In this study, we investigated the effects of daily, monthly, and seasonal climate data on simulated tree-species biomass in a temperate forest region of northeast China. We conducted the study by using the LINKAGES terrestrial ecosystem model to quantify the relative importance of climate data resolutions (daily, monthly and seasonal) and interspecific competition on predicted tree-species biomass from short-term (<40 years) to long-term (70–100 years) simulations. Results showed that simulated tree-species biomass was sensitive to daily, monthly, and seasonal climate data. The difference in the simulated biomass based on daily vs. monthly climate data was not significant for tree species monocultures, suggesting that monthly climate data can be used as a surrogate for daily climate data in such simulations. However, interspecific competition amplifies the differences in biomass simulations under daily and monthly climate data, thus increasing prediction uncertainties in mixed-species systems. Results based on climate data at the seasonal resolution showed the greatest departure from the daily and monthly climate data, because averaging climate data over a season may result in unrealistic climate estimates for modeling tree biomass growth. Simulated biomass of shade-intolerant tree species was highest when using climate data at the daily resolution, followed by monthly and seasonal climate data. The opposite pattern was true for shade-tolerant tree species. At the early stages of simulated tree growth, inter-tree competition was a more important factor affecting the biomass of late-successional, shade-tolerant tree species while different temporal resolutions of climate data were more important for early- and mid-successional species. This trend reverses at the late stages of stand development. These results can help guide choosing climate input of terrestrial ecosystem models and aiding results interpretation. [ABSTRACT FROM AUTHOR]

Global environmental changes continuously result in plant migration from lower elevations or latitudes into alpine or arctic tundra ecosystems. In response to global environmental changes, the alpine shrubby tundra on the Changbai Mountain in northeastern China has been invaded by a low-elevation herb species Deyeuxia angustifolia over the past several decades. In this experiment, we studied the effects of D. angustifolia migration, Nitrogen (N) deposition (ambient N vs. N-addition of 10 g/m2/yr), and elevation (a higher elevation of 2200 m vs. a lower elevation of 2050 m a.s.l.) on soil properties and soil microbial communities to better understand the consequences of this migration for soil microbes and obtain feedback on the likelihood of further migration. We found that the migration of D. angustifolia decreased the soil available phosphorus (AP) and microbial biomass (particularly the biomass of Gram-positive bacteria (Gp) and Actinobacteria) at 2200 m a.s.l. N addition enhanced the availability of soil N, the nitrogen: phosphorous (N: P) ratio, and reduced the fungal: bacterial (F: B) ratio at 2200 m a.s.l. There was a higher Gram-positive: Gram-negative bacterial (Gp: Gn) ratio at 2200 m a.s.l. than those at 2050 m a.s.l. Our results suggest that the upward migration of D. angustifolia into the shrubby tundra combined with N deposition will substantially change the soil microbial community composition on the one hand, and result in a shortage of soil P on the other hand, especially at higher elevations. These changes may increase the competitive ability of D. angustifolia , and further benefit its migration, and suppress the shrubby species that currently exist in that habitat. This study helps to understand the mechanisms for the upward migration of D. angustifolia and facilitates the management of the Changbai alpine tundra in a changing world. • Increasing elevation increased soil Gram-positive:Gram-negative ratio. • D. angustifolia migration (D) decreased soil microbial biomass and Gram-positive:Gram-negative ratio. • N addition (N) decreased soil fungal biomass and fungi:bacteria ratio. • Soil P limitation and the proportion of Gn increased with D and N. • The microbial responses to D and N were more pronounced at higher elevations. [ABSTRACT FROM AUTHOR]

• Birch recruitment is highly sensitively to temperature above the alpine treeline. • The sensitivity of stem radial growth to temperature is not altered by warming. • Warmer climate can increase tree recruitment and growth above the alpine treeline. Trees at temperature-limited alpine treeline are highly sensitive to temperature fluctuations. However, few studies have directly linked the recruitment and growth of juvenile trees to climate warming to investigate the processes underlying climate-induced alpine treeline shift. On the cold-humid Changbai Mountain of northeastern China, almost no tree recruitment occurred above the current treeline on the west side before 1985, whereas considerable recruitment has occurred since 1985. To investigate whether this recent recruitment was caused by warming temperatures, we established a 450 m × 50 m permanent plot above the current alpine treeline. We used dendrochronology to reconstruct the time series of recruitment of Betula ermanii juveniles. In addition, we used open top chambers (OTCs) to increase the growing season day-time temperature by c. 2.8°C and thereby to study the growth responses of juvenile trees to future warmer conditions beyond the current treeline. We found that tree recruitment increased substantially during a period of warmer summer temperatures since 1985, showing a high sensitivity of tree recruitment to temperature above the alpine treeline. The daily stem radial increment recorded by dendrometers was significantly (p ≤ 0.05) positively correlated with temperature but negatively correlated with soil water content, indicating no water limitation. Correspondingly, the increase in radial growth in OTCs was primarily a consequence of higher temperatures, especially in July. The regression slope between stem radial growth and temperature in the OTCs did not differ from that in ambient controls, indicating that the sensitivity of stem radial growth to temperature was not altered by warming. These suggest that future climate warming will induce increases in tree recruitment and growth above the alpine treeline. Our results revealed a direct link between temperature and recruitment and growth of juvenile trees, and that climate warming will likely cause forests to advance beyond the alpine treeline. [ABSTRACT FROM AUTHOR]

Aeolian desertification is one of the most serious environmental issues negatively impacting society. Assessing the spatiotemporal changes in desertification and determining its driving factors are crucial to preventing and controlling desertification. In this study, Landsat remote sensing images from 1980 to 2015 are used to extract the information of aeolian desertified land (ADL) in the Hulunbuir Grassland. We analyse the spatiotemporal dynamic changes in desertification using an intensity analysis, the gravity centre change model, and GIS spatial analysis and discuss the driving factors of these changes. The results show that the ADL area in the Hulunbuir Grassland increased during both 1980–2000 and 2000–2015. The ADL is mainly distributed in the central and western Hulunbuir Grassland. The gravity centres were distributed from west to east in the order of light, moderate, extremely severe, and severe ADL. ADL area and intensity changes were the highest during 1990–2000. The gain intensity of all ADL levels was active during 1980–2015. Excluding the severe ADL from 1980 to 1990 and the extremely severe ADL from 1990 to 2000, the loss intensity of other ADL levels was active. All ADL levels transformed to one level lower after 2000. The increasing annual average temperature, population, farmland area, and number of livestock promoted aeolian desertification during 1980–2000. Environmental protection policies and climate change contributed to the reversal of ADL during 2000–2015. In summary, Hulunbuir Grassland desertification has been controlled to a certain degree and has improved. The development and reversal of ADL were affected by the combined effects of climate change and human activities in the Hulunbuir Grassland. The results can provide meaningful information for the prevention and control of aeolian desertification in the Hulunbuir Grassland. • Desertification from 1980 to 2015 in study area was monitored using Landsat images. • The spatial-temporal distribution of ADL in different stages was identified. • The changes in the ADL area and intensity were the highest during 1990–2000. • Desertification has been controlled to a certain degree and has improved. • Ecological protection policies and climate change contributed to the reversal of ADL. [ABSTRACT FROM AUTHOR]

Droughts are widespread in China and have brought considerable losses to the economy and society. Droughts are intricate, stochastic processes with multi-attributes (e.g., duration, severity, intensity, and return period). However, most drought assessments tend to focus on univariate drought characteristics, which are inadequate to describe the intrinsic characteristics of droughts due to the existence of correlations between drought attributes. In this study, we employed the standardized precipitation index to identify drought events using China's monthly gridded precipitation dataset from 1961 to 2020. Univariate and copula-based bivariate methods were then used to examine drought duration and severity on 3-, 6-, and 12-month time scales. Finally, we used the hierarchical cluster method to identify drought-prone regions in mainland China at various return periods. Results revealed that time scale played an essential role in the spatial heterogeneity of drought behaviors, such as average characteristics, joint probability, and risk regionalization. The main findings were as follows: (1) 3- and 6-month time scales yielded comparable regional drought features, but not 12-month time scales; (2) higher drought severity was associated with longer drought duration; (3) drought risk was higher in the northern Xinjiang, western Qinghai, southern Tibet, southwest China, and the middle and lower reaches of the Yangtze River, and lower in the southeastern coastal areas of China, the Changbai Mountains, and the Greater Khingan Mountains; (4) mainland China was divided into six subregions according to joint probabilities of drought duration and severity. Our study is expected to contribute to better drought risk assessment in mainland China.

Soil microbial biomass and microbial stoichiometric ratios are important for understanding carbon and nutrient cycling in terrestrial ecosystems. Here, we compiled data from 12245 observations of soil microbial biomass from 1626 published studies to map global patterns of microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), microbial biomass phosphorus (MBP), and their stoichiometry using a random forest model. Concentrations of MBC, MBN, and MBP were most closely linked to soil organic carbon, while climatic factors were most important for stoichiometry in microbial biomass ratios. Modeled seasonal MBC concentrations peaked in summer in tundra and in boreal forests, but in autumn in subtropical and in tropical biomes. The global mean MBC/MBN, MBC/MBP, and MBN/MBP ratios were estimated to be 10, 48, and 6.7, respectively, at 0-30 cm soil depth. The highest concentrations, stocks, and microbial C/N/P ratios were found at high latitudes in tundra and boreal forests, probably due to the higher soil organic matter content, greater fungal abundance, and lower nutrient availability in colder than in warmer biomes. At 30-100 cm soil depth, concentrations of MBC, MBN, and MBP were highest in temperate forests. The MBC/MBP ratio showed greater flexibility at the global scale than did the MBC/MBN ratio, possibly reflecting physiological adaptations and microbial community shifts with latitude. The results of this study are important for understanding C, N, and P cycling at the global scale, as well as for developing soil C-cycling models including soil microbial C, N, and P as important parameters., (© 2022 John Wiley & Sons Ltd.)

Tree line ecotone in the Changbai Mountains has undergone large changes in the past decades. Tree locations show variations on the four sides of the mountains, especially on the northern and western sides, which has not been fully explained. Previous studies attributed such variations to the variations in temperature. However, in this study, we hypothesized that topographic controls were responsible for causing the variations in the tree locations in tree line ecotone of the Changbai Mountains. To test the hypothesis, we used IKONOS images and WorldView-1 image to identify the tree locations and developed a logistic regression model using topographical variables to identify the dominant controls of the tree locations. The results showed that aspect, wetness, and slope were dominant controls for tree locations on western side of the mountains, whereas altitude, SPI, and aspect were the dominant factors on northern side. The upmost altitude a tree can currently reach was 2140 m asl on the northern side and 2060 m asl on western side. The model predicted results showed that habitats above the current tree line on the both sides were available for trees. Tree recruitments under the current tree line may take advantage of the available habitats at higher elevations based on the current tree location. Our research confirmed the controlling effects of topography on the tree locations in the tree line ecotone of Changbai Mountains and suggested that it was essential to assess the tree response to topography in the research of tree line ecotone.