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(a) Location of the Mongolian Plateau that mainly consists of Mongolia and the Inner Mongolia Autonomous Region (IMAR) of China. (b) Spatial distribution extents of meadow steppe, typical steppe and desert steppe on the plateau. (c) Mean annual temperature (MAT) and (d) mean annual precipitation (MAP) from 1983 to 2015 across the plateau.
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Steppes on the Mongolian Plateau, mainly within the Republic of Mongolia and the Inner Mongolia Autonomous Region (IMAR) of China, have been subjected to widespread degradation as a result of climate change and human utilization. Field experiments and long-term observations suggest that the productivity of degraded grassland ecosystems might show g...
Citations
... In recent decades, the interaction between climate change and anthropogenic disturbances has led to more complex spatial and temporal changes in the response of the MP to climate change Bao et al., 2019;Cho et al., 2021;Miao et al., 2015a;Rihan et al., 2021;Su et al., 2020). Recent study has reported a significant destabilization of vegetation activity over a large proportion of the entire steppe area over the past three decades, especially in Mongolia (Zhao et al., 2021b). Zhao et al. (2014) found precipitation was the primary climatic constraint on plant growth in the growing season. ...
In-depth understanding of the changes and characteristics of vegetation activity on the Mongolian Plateau (MP) is essential to address climate change in temperate regions and even globally, but the seasonal dynamics and spatial patterns of vegetation activity have not been fully investigated. To this end, we used different types of satellite vegetation datasets from 2001 to 2020, namely, gross primary production (GPP), solar-induced chlorophyll fluorescence (SIF), and normalized difference vegetation index (NDVI), in conjunction with environmental factor datasets, then we investigated the interaction between vegetation activity of the MP and environmental factors. The spatial pattern of vegetation activity in JJA exhibited obvious spatial heterogeneity, which mainly manifested that strong vegetation activity occurred mostly in the northeast and north MP, while weak vegetation activity occurred in the southeast MP, and this pattern was closely related to hydrothermal conditions. Vegetation activity mainly exhibited an increasing or stable trend on the MP in JJA. By exploring the changes in JJA vegetation activity and its trends over the last 20 years, we found that vegetation activity in the study area is predominantly positively correlated with temperature (Tem) and negatively correlated with vapor pressure deficit (VPD) and deep soil moisture (SM). Additionally, the trends of wind speed, solar radiation, and deep SM made significant contributions to the trend in vegetation activity, suggesting that water availability has an important influence on vegetation change. Clarifying the effects of environmental factors on vegetation activity is fundamental to understanding the impact of climate change on vegetation.
... The response of surface vegetation to ecological projects has a certain lag [64] and is also negatively affected by the development of urbanization. With the full implementation of the national ecological projects, large areas of sloping cultivated land and barren hills and wasteland were converted to forests and grasslands, and the effect of vegetation restoration gradually became obvious [65,66]; therefore, the human activities in the later part of the study period had a predominantly positive effect on the changes in NDVI, and the degree of the effect showed a significantly higher trend, which is basically in line with the results of Zhou et al. [67] and Zhao et al. [68]. ...
Climate and human activities are the basic driving forces that control and influence the spatial distribution and change of vegetation. Using trend analysis, the Hurst index, correlation analysis, the Moran index, path analysis, residual analysis, and other methods, the effects of human activities and climate factors on vegetation change were analyzed. The results show that: (1) The research area’s normalized difference vegetation index (NDVI) exhibited a substantial upward trend from 2001 to 2020, increasing at a rate of 0.003/a, and the vegetation cover was generally healthy. The generally constant NDVI region made up 78.45% of the entire area, and the grassland, cultivated land, and forest land showed the most visible NDVI aggregation features. (2) The Vegetation is mainly promoted by water and heat, particularly precipitation, have a major impact on plants, with the direct influence of precipitation on vegetation growth being much greater than the indirect effect through the temperature. (3) The trend of NDVI residuals showed obvious spatial variability, presenting a distribution characteristic of high in the south and low in the north. The results of this study can provide a basis for the scientific layout of ecological protection and restoration projects in the Yinshanbeilu area.
... Intensive climate change and anthropogenic disturbances have led to the degradation of large areas of grasslands (Bardgett et al., 2021). Thus, assessing the underlying mechanisms of grassland stability is a vital topic for social development and ecological protection (García-Palacios et al., 2018;Zhao et al., 2021). Nitrogen, as the basic component of chlorophyll (Chapin, 1980), is the limiting nutrient in most grassland ecosystems (Du et al., 2020). ...
Nitrogen (N) enrichment threatens the ability of grasslands to support sustainable functions. However, we do not know whether grassland degradation can alter the effect of N enrichment on the multidimensional stability of plant community productivity.
Using data from N enrichment experiments at temperate grassland sites (no, moderate and severe degradation) that experienced a flooding event, we tested the impact of N enrichment on multidimensional stability (resistance, resilience, recovery and temporal stability) of plant community productivity.
In non‐degraded and moderately degraded grasslands, N enrichment negatively influenced resistance and temporal stability but positively altered resilience and did not change recovery. Species asynchrony altered all stability dimensions, except for recovery. In severely degraded grasslands, the effects of N enrichment on multidimensional stability shifted. Resilience and recovery were negatively affected by N enrichment, while resistance and temporal stability were not influenced. A decrease in dominant species stability reduced community resilience and recovery in severely degraded grasslands.
Synthesis and application. Grassland degradation regulates the effect of N enrichment on the multidimensional stability of plant community productivity. Thus, our findings highlight the need to consider grassland degradation in future studies for a comprehensive understanding of grassland dynamics.
... The Inner Mongolia Autonomous Region accounts for 68% of the total length of the China-Mongolia border, with a length of 3193 km [35]. The long-term changes in biomass in the Mongolian Plateau indicate great geographic differences, with non-significant changes in vegetation, which accounted for 35% in Inner Mongolia and 44% in Mongolia [49,50]. The Mongolian Plateau is located from the Gobi Desert in Central Asia to the Siberian taiga forest [51,52]. ...
The frequency and intensity of fires are increasing because of warmer temperatures and increased droughts, as well as climate-change induced fuel distribution changes. Vegetation in environments, such as those in the mid-to-high latitudes and high elevations, moves to higher latitudes or elevations in response to global warming. Over the past 40 years, the Mongolian Plateau has been arid and semi-arid, with a decrease in growing season vegetation in the southwest and an increase in growing season vegetation in the northeast. The northward movement of vegetation has brought fires, especially in the Dornod, Sukhbaatar, and Kent provinces near the Kent Mountains, and has become more obvious in the past 20 years. The occurrence of a dead fuel index (DFI) with high probability is distributed in northern Mongolia, the border area between China and Mongolia, and the forest-side meadow-steppe region of the Greater Khingan Mountains. These findings suggest that vegetation is moving northward because of climate change and this presents a challenge of future warming spreading fire northward, adding material to the study of the relationship between the northward movement of global vegetation and fires.
... Climate change and overgrazing have resulted in vegetation degradation over the past few decades [25,26]. Consequently, the stability of grassland productivity has decreased significantly and potentially threatens the sustainability of local livestock production systems [27]. In this context, the development of a low-cost and real-time monitoring system for forage biomass and quality is crucial for the conservation and management of regional grassland resources. ...
... The study was conducted in temperate grasslands in the Xilingol region of IMAR, northern China ( Figure 1). This region is characterized by a continental semi-arid climate, with a mean annual precipitation of 267 mm and mean annual temperature of 1.0 °C [27]. Precipitation occurs predominately in summer (June-August) in synchrony with high temperatures. ...
Grasslands provide essential forage sources for global livestock production. Remote sensing approaches have been widely used to estimate the biomass production of grasslands from regional to global scales, but simultaneously mapping the forage biomass and quality metrics (e.g., crude fiber and crude protein) is still relatively lacking despite an increasing need for better livestock management. We conducted novel gradient grass-cutting experiments and measured hyperspectral reflectance, forage biomass, crude fiber per area (CFarea), and crude protein per area (CParea) across 19 temperate grassland sites in the Xilingol region, Inner Mongolia, China. Based on these measurements, we identified sensitive spectral bands, calculated nine potential spectral indices (Normalized Difference Vegetation Index, Enhanced Vegetation Index, Red Edge Normalized Difference Vegetation Index, Red-Edge Inflection Point, Inverted Red-Edge Chlorophyll Index algorithm, Normalized Difference Red Edge Index, Nitrogen Reflectance Index, Normalized Greenness Index, Land Surface Water Index) and established Random Forest (RF) models that well predicted forage biomass (R2 = 0.67, NRMSE = 12%), CFarea (R2 = 0.59, NRMSE = 14%), and CParea (R2 = 0.77, NRMSE = 10%). Among these nine indices, Land Surface Water Index (LSWI, calculated by R785-900 and R2100-2280) was identified to be the most important predictor and was then used to establish empirical power law models, showing comparable prediction accuracies (forage biomass, R2 = 0.53; NRMSE = 14%; CFarea, R2 = 0.40, NRMSE = 17%; CParea, R2 = 0.72, NRMSE = 11%) in comparison to Random Forest models. Combining the empirical power law models with the LSWI calculated from Sentinel-2 observations, we further mapped the forage biomass and quality and estimated the livestock carrying capacity. The predicted forage biomass, CFarea, and CParea all showed a significant increase with higher mean annual precipitation, but showed no significant correlations with mean annual temperature. Compared with the estimates based on crude protein, the conventional approach solely based on forage biomass consistently overestimated livestock carrying capacity, especially in wetter areas. Our work provides an approach to simultaneously map the forage biomass and quality metrics and recommends a LSWI-based power law model for rapid and low-cost assessment of regional forage status to guide better livestock management.
... The Mongolian Plateau (MP) is the largest temperate steppe in the world. Most of the MP is located in the arid and semi-arid regions, with fragile ecological environments, and is vulnerable to climate change and human activities (Miao et al., 2020;Na et al., 2021;Zhao et al., 2021). In less than 20 years, it has experienced one of the wettest and driest periods in its history of about 2000 years (Lu et al., 2019). ...
As a major component of temperate steppes in the Eurasian continent, the Mongolian Plateau (MP) plays a pivotal role in the East Asian and global carbon cycles. This paper describes the use of five remote sensing indices derived from satellite data to characterize vegetation cover on MP, namely: gross primary production (GPP), net primary production (NPP), normalized difference vegetation index (NDVI), leaf area index (LAI) and fractional vegetation cover (FVC). It is found that GPP, NPP, and NDVI exhibit increasing trends, whereas LAI and FVC present decreasing trends on the MP since 1982. The different indices highlight discrepancies in the spatial pattern of vegetation growth, with the greatest increase in the southeast of MP. Only 3.4% of the total land area of MP exhibited consistent trends in the indices (0.1% degradation and 3.3% growth, P < 0.01), with the synchronous change of both LAI and NPP exhibiting higher consistency than that of raw NDVI and NPP. Understanding of the characteristics and status of vegetation change on the MP has far-reaching implications for its ecological protection management, and climate change mitigation.
Climate change is manifesting rapidly in the form of fires, droughts, floods, resource scarcity, and species loss, and remains a global risk. Owing to the disaster risk management, there is a need to determine the Dead Fuel Index (DFI) threshold of the fire occurrence area and analyze the spatio-temporal variation of DFI to apply prevention measures efficiently and facilitate sustainable fire risk management. This study used the MODIS Burned Area Monthly L3 (MCD64A1), Landsat Global Burned Area (BA) products, and MODIS Surface Reflectance 8-Day L3 (MOD09A1) data from 2001 to 2020 to calculate the values of the DFI in the study area before the occurrence of fire. The results showed that: (1) The inversion of the meadow steppe DFI values in the fire area was distributed in the range of 14-26, and the fire rate was the highest in the range of 20-22. The inversion of the typical steppe DFI values in the fire area was distributed in the range of 12-26, and the fire rate was the highest in the range of 16-22. (2) Areas with high fire DFI values included Khalkhgol, Matad, Erdenetsagaan, Bayandun, Gurvanzagal, Dashbalbar in Mongolia, and scattered areas of the Greater Khin-gan Mountains (forest edge meadow steppe area), East and West Ujumqin Banner, and Xin Barag Right Banner. The highest fire probability of fire occurred during October and April. (3) The DFI values were sensitive to changes in altitude. The results of this study may provide useful information on surface energy balance, grassland carbon storage, soil moisture, grassland health, land desertification, and grazing in the study area, especially for fire risk management.
Temporal stability of plant community productivity (‘plant community stability’ hereafter) in the face of environmental disturbance is essential for maintenance of ecosystem functioning. However, most existing studies that examined the biotic drivers of plant community stability concentrated on plant attributes, neglecting the potential stabilizing effects of soil microbes. Here, we conducted a 5-year field experiment to quantify plant community stability (i.e., the ratio of the temporal mean of community biomass to its standard deviation over this period) at four grassland sites with no, moderate, severe, and extreme degradation statuses in northern China. Soil bacterial communities were determined with 16S ribosomal RNA gene sequences. Our results demonstrated that high bacterial network complexity and relative abundance of oligotrophs were beneficial to improve plant community stability of moderately and severely degraded grasslands. The strong impacts of bacterial community composition on plant community stability indicated that particular taxa, especially oligotrophs and copiotrophs, determined stability. The positive relationship between bacterial network complexity and plant community stability supported the central ecological belief that complexity begets stability. Together, these findings provide a new insight into the importance of soil bacterial community composition and network complexity for buffering negative effects of grassland degradation on plant community stability.
Nitrogen (N) enrichment poses a severe threat to ecosystem multifunctionality. Given increasing variability of ecosystem functioning and uncertainty under global change, a pressing question is how N enrichment affects temporal stability of multiple functions (i.e., ‘multifunctional stability’). Whether the responses of multifunctional stability to N enrichment change with external disturbance, such as grasslands with different degradation statuses, remains unclear. We conducted multi-level N enrichment experiments at four grassland sites with no, moderate, severe, and extreme degradation statuses in Inner Mongolia, China. We measured temporal stability of five functions, comprising aboveground net primary productivity, soil total carbon (C) and N storage, and soil microbial biomass C and N storage, to explore how multifunctional stability responded to N enrichment. The temporal stability of most individual functions and multifunctional stability decreased sharply when N input exceeded 20 g N m⁻² y⁻¹ in the non-, moderately, and severely degraded grasslands, whereas the threshold declined to 10 g N m⁻² y⁻¹ in the extremely degraded grassland. The relative importance of plant and soil microbes in regulating multifunctional stability varied along the degradation gradient. In particular, plant species asynchrony and species richness showed strong positive relationships with multifunctional stability in the non- and moderately degraded grasslands, whereas soil microbial diversity, especially bacterial diversity, was positively associated with multifunctional stability in the severely and extremely degraded grasslands. Overall, our findings identified a critical threshold for N-induced multifunctional stability and called for context-specific biodiversity conservation strategies to buffer the negative effect of N enrichment on grassland ecosystem stability.
Global change in recent decades has caused severe degradation of grassland ecosystems in arid and semi-arid regions in the world. In the context of global change, the maximum gross primary production (GPPmax) and its response to drought on the Mongolian Plateau (MP) remain unclear. Here, we used long time-series datasets (temperature, precipitation, GPP) and calculated GPPmax, timing of GPPmax (TGM), and Standardized Precipitation Evapotranspiration Index (SPEI) to explore the changes in peak growth of vegetation and its response to drought on the MP from 1982 to 2018. Our results show that GPPmax and TGM presented high spatial heterogeneity. The mean GPPmax was 336 g C·m⁻² over the past three decades, with a decreasing trend at a rate of 0.32 g C·m⁻²·year⁻¹; the mean TGM was on DOY (day of year) 197, with little year-to-year change, TGM received the time-lag effect (mostly 1, 2, 10 months in time scale) of drought was found in 35.3% of the MP, while the cumulative effect of drought on TGM occurred only 16.3% of the MP. These results reveal changes in vegetation growth peaks on the MP and their response to drought over three decades and can contribute to our understanding of the response and feedbacks of MP vegetation to global change.
