Meadow Steppe Research Articles

Response mechanisms of 3 typical plants nitrogen and phosphorus nutrient cycling to nitrogen deposition in temperate meadow grasslands.

The increase of nitrogen (N) deposition and the diversity of its components lead to significant changes in the structure and function of temperate meadow steppe, which could affect plant nutrient uptake, nutrient resorption and litter decomposition, thus affecting the biogeochemical cycle process. The distribution and metabolism of nitrogen and phosphorus in plants determine the growth process and productivity of plants. Plant nutrient uptake, nutrient resorption and litter decomposition play an important role in the nutrient cycling process of ecosystem. This study closely combined these three processes to carry out experiments with different nitrogen dosages and types, and systematically explored the response of nitrogen and phosphorus nutrient cycling to nitrogen deposition. The results showed that nitrogen deposition can greatly affect ecosystem nutrient cycle of nitrogen and phosphorus. Firstly, Nitrogen deposition has significant effect on plant nutrient uptake. Nitrogen uptake of stems and leaves increased with the increase of nitrogen addition dosage, while phosphorus uptake of stems and leaves showed a downward trend or no significant effect. Besides, nitrogen addition type had a significant effect on nitrogen and phosphorus content of stems. Secondly, Nitrogen addition dosage had a significant effect on plant nutrient resorption, while nitrogen addition type had no significant effect on it. Thirdly, nitrogen deposition has significant effect on litter decomposition. With the increase of nitrogen addition dosage, the initial nitrogen content of litters increased and the decomposition rate of litters accelerated. Nitrogen application type had significant effect on stem litter decomposition. These results indicated that nitrogen deposition significantly affects plant nutrient cycling, and thus affects the structure and function of grassland ecosystem.

Effect of isolated lactic acid bacteria on the quality and bacterial diversity of native grass silage.

The objective of this study was to isolate lactic acid bacteria (LAB) from native grasses and naturally fermented silages, determine their identity, and assess their effects on silage quality and bacterial communities of the native grasses of three steppe types fermented for 60 days. Among the 58 isolated LAB strains, Limosilactobacillus fermentum (BL1) and Latilactobacillus graminis (BL5) were identified using 16S rRNA sequences. Both strains showed normal growth at 15- 45°C temperature, 3-6.5% NaCl concentration, and pH 4-9. Two isolated LAB strains (labeled L1 and L5) and two commercial additives (Lactiplantibacillus plantarum and Lentilactobacillus buchneri; designated as LP and LB, respectively) were added individually to native grasses of three steppe types (meadow steppe, MS; typical steppe, TS; desert steppe, DS), and measured after 60 d of fermentation. The fresh material (FM) of different steppe types was treated with LAB (1 × 105 colony forming units/g fresh weight) or distilled water (control treatment [CK]). Compared with CK, the LAB treatment showed favorable effects on all three steppe types, i.e., reduced pH and increased water-soluble carbohydrate content, by modulating the microbiota. The lowest pH was found in the L5 treatment of three steppe types, at the same time, the markedly (p < 0.05) elevated acetic acid (AA) concentration was detected in the L1 and LB treatment. The composition of bacterial community in native grass silage shifted from Pantoea agglomerans and Rosenbergiella nectarea to Lentilactobacillus buchneri at the species level. The abundance of Lentilactobacillus buchneri and Lactiplantibacillus plantarum increased significantly in L1, L5, LP, and LB treatments, respectively, compared with CK (p < 0.05). In summary, the addition of LAB led to the shifted of microbiota and modified the quality of silage, and L. fermentum and L. graminis improved the performance of native grass silage.

Effects of nitrogen inputs and mowing on the abundance and species richness of herbivorous insects in a meadow steppe.

To reveal the effects of nitrogen (N) inputs and mowing on the abundance and richness of insect community in meadow steppe, we investigated the abundance and diversity of herbivorous insects under four treatments in Inner Mongolia meadow steppe in August 2022, including control, N addition, mowing, and combined N addition and mowing. At a long-term control experimental platform, we collected insects using the vacuum sampling method. The results showed that N addition significantly increased the abundance of herbivorous insects, and mowing significantly decreased the abundance of herbivorous insects. Nitrogen addition significantly increased insect abundance in unmown condition but not in the mown condition. The responses of insect abundance at the community level to N addition were mainly driven by the dominant groups, Cicadellidae and Lygaeidae, which was affected by the abundance of Gramineae species. In contrast, their responses to mowing were the opposite. Both N addition and mowing did not affect the diversity of herbivorous insects. Our results indicated that the responses of herbivorous insect abundance to N inputs and mowing were directly regulated by food resources. With increasing food resource availability, the abundance but not the diversity of herbivorous insects increased, with stronger responses of dominant groups than subordinate ones.

State of &lt;i&gt;Limonium&lt;/i&gt; &lt;i&gt;gmelinii&lt;/i&gt; (Plumbaginaceae) Coenopopulations in the Republic of Khakassia

Abstract—The study is focused on the characteristic halophyte of Khakassia – Limonium gmelinii (Willd.) Kuntze (Plumbaginaceae). There is no information on the structure and assessment of the state of the coenopopulations of L. gmelinii in Khakassia. The materials were collected in 2022 from steppe and meadow plant communities with varying degrees of salinity. It was found that L. gmelinii coenopopulations are stable. The studied coenopopulations are normal, complete and incomplete. The left-sided type of the ontogenetic spectrum is formed in the alkaline steppe with low total projective cover and sufficient moisture; centered – on slightly saline or almost non-saline substrate of grass-covered steppe and meadow communities under different moisture regimes. The change in the ontogenetic structure and an increase in the undergrowth are associated with seed renewal and ecological and phytocenotic conditions of habitats. The density of individuals depends on the ecological and phytocenotic environment. The maximum total score of organismal and populational characters in Limonium gmelinii individuals was observed on slightly saline and practically non-saline soils in the cold sagebrush-grass and sagebrush real steppes of Khakassia. On the steppe meadows with low salinity, extensive grass cover and lack of moisture, the species does not reach the optimum. On highly saline soils, under low competition from related species and sufficient moisture, the total score of organismal and population characters reaches an average value.

Phytochemical Characteristics and Antimicrobial Effects of &lt;i&gt;Nonea rossica&lt;/i&gt; (Boraginaceae) Extracts

Abstract—A phytochemical and microbiological analysis of a widespread Russian species, Nonea rossica Steven (Boraginaceae) was carried out. As an object of study, we used the aerial part (herb) of N. rossica, harvested during flowering stage from a steppe meadow in the Novosibirsk region. The qualitative composition of biologically active compounds (BAC) was determined by thin layer chromatography, using two solvent systems: ethyl acetate–ethanol–dimexide and ethyl acetate–anhydrous formic acid–glacial acetic acid–water. The quantification of their amount was carried out by spectrophotometry (flavonoids expressed as rutin, hydroxycinnamic acids – as caffeic acid, and coumarin-like compounds – as coumarin). The raw material ethanolic extracts of different concentrations (20, 40, 70 and 95%) were used in pharmacological research. Antimicrobial activity was determined by the serial dilution method. Strains of gram-positive bacteria (Staphylococcus aureus ATCC 6538 FDA 209P and Bacillus cereus ATCC 10702) and fungi – Candida albicans NCTC 885-653 were used as test cultures. The presence of bioactive phenolic compounds (hydroxycinnamic acids, flavonoids, coumarins) was established and their quantitative content was determined. It was observed that the highest yield of bioactive phenolic compounds resulted from using 40–70% ethanol as extractant. The microbiological activity of hydroalcoholic extracts from Nonea rossica herb was studied. It was determined that antimicrobial activity against Staphylococcus aureus and Bacillus cereus, and antifungal activity against Candida albicans were exhibited by 40–70% ethanolic extracts of Nonea rossica, where equal content of caffeic acid and coumarin was measured. The synergistic interaction of these compounds determines the established bactericidal and fungistatic properties of such extracts.

Biome regulates the effects of long‐term grazing on soil microbial diversity

AbstractIntroductionLivestock overgrazing represents one of the most destructive uses of land in terrestrial ecosystems and threatens biodiversity. However, understanding the effects of livestock overgrazing on below‐ground soil microbial diversity is limited, despite soil microbes representing the majority of biodiversity and determining ecosystem functioning.Materials and MethodsTo investigate the effects of overgrazing on soil microbial richness, a long‐term grazing exclusion experiment was conducted at six sites including three meadow steppes and three typical steppes in northern China.ResultsOur results revealed that overgrazing decreased bacterial and fungal richness across temperate steppes in northern China, and the biome could regulate the overgrazing effects, especially for fungal richness. Specifically, the negative effects of overgrazing on microbial richness were highly significant in typical steppes while not significant in meadow steppes that contained higher plant diversity and precipitation. Partial least‐squares path model showed that overgrazing affected soil microbial richness in highly complex ways, and the affected pathways were different in meadow steppes and typical steppes. The direct negative effects of grazing and their indirect negative effects via soil properties resulted in a significant decrease in microbial richness in typical steppes. In meadow steppes, the indirect beneficial effects via plant attributes offset the direct negative effects of grazing. Consequently, the soil microbial community in meadow steppe resisted overgrazing disturbance.ConclusionOur study illuminates the complex and highly biome‐dependent grazing effects and pathways on soil microbiota and indicates that meadow steppe may be more resistant or resilient to human disturbance than typical steppe. These findings suggest that different grasslands might be managed differently considering their intrinsic characteristics to help biodiversity conservation. Moreover, future research should focus on the underlying mechanisms of grazing effects on soil microbial richness. Besides grazing‐induced plant and soil traits changes, other potential pathways could strongly influence soil microbial diversity.

Identification of spatial distribution and drivers for grasshopper populations based on geographic detectors

Grasshoppers are important elements for supporting ecosystem services which make it important to understand their spatial distribution characteristics to reduce outbreaks, implement effective control while minimizing non-target impacts. The spatial software package Geographical Detector (GD) was used to rank the interaction and effects of 19 environmental factors on the distribution of grasshopper species were quantified in four types of steppes in Northwestern, China. Results showed that the distribution of the insect was mainly influenced by elevation (q = 0.44). Among the factor interactions, elevation ∩ average annual precipitation (q = 0.795) was the strongest, followed by elevation ∩ soil available nitrogen (q = 0.722). Temperate meadow steppe and temperate steppe were identified as the areas at greatest risk for grasshopper’s occurrence. This research shows that the Geographical Detector could be provided a useful tool to identify the driving forces for grasshopper distribution. Our research also offers a new method to more broadly understand the interactions between different drivers to explain the distribution of other insects.

Impacts of Grazing Disturbance on Soil Nitrogen Component Contents and Storages in a Leymus chinensis Meadow Steppe

Long-term grazing leads to soil degradation in Inner Mongolia grassland. Based on the Hulunbeier meadow steppe, the variation characteristics of soil nitrogen content and storage in soil layers between 0–40 cm, under six different grazing intensities, and the response of vegetation and other physical and chemical properties of soil to grazing were studied. The main results were as follows: (1) Moderate grazing increased soil total nitrogen (TN), soluble total nitrogen (STN) and microbial biomass nitrogen (MBN) contents, while heavy grazing decreased MBN content. In the year with more rain, heavy grazing increased nitrate nitrogen (NO3−-N) content and storage, while less rain increased ammonium nitrogen (NH4+-N) content. (2) The proportion of 0–40 cm nitrogen components showed an upward trend in the year with more rain, and the opposite in the years with less rainfall with the increase of grazing intensity. Soil soluble organic nitrogen (SON) and NO3−-N storages decreased and MBN storage increased in rainy years. (3) Soil nitrogen component contents and storages were correlated with plant growth status, soil moisture (SM) and soil bulk density (SBD), and were significantly negatively correlated with soil temperature (ST) and pH (p &lt; 0.05). The content and storage of soil nitrogen were affected by grazing, soil, vegetation, meteorological and other environmental factors. Moderate grazing was more conducive to the improvement of soil nitrogen storage capacity and the healthy development of grassland.

Different nitrogen saturation thresholds for above-, below-, and total net primary productivity in a temperate steppe.

Identifying the thresholds for the positive responses of total net primary productivity (NPP) to nitrogen (N) enrichment is an essential prerequisite for predicting the benefits of N deposition on ecosystem carbon sequestration. However, the responses of below-ground NPP (BNPP) to N enrichment are unknown in many ecosystems, which limits our ability to understand the carbon cycling under the scenario of increasing N availability. We examined the changes in above-ground NPP (ANPP), BNPP, and NPP of a temperate meadow steppe across a wide-ranging N addition gradient (0, 2, 5, 10, 20, and 50 g N m-2 year-1 ) during 5 years. Both ANPP and NPP increased nonlinearly with N addition rates. The N saturation threshold for ANPP (TA ) and NPP (TN ) was at the rate of 13.11 and 6.70 g N m-2 year-1 , respectively. BNPP decreased with increasing N addition when N addition rates ˃5 g N m-2 year-1 , resulting in much lower TN than TA . Soil N enrichment played a key role in driving the negative impacts of high N addition rates on BNPP, and consequently on the earlier occurrence of N saturation threshold for NPP. Our results highlight the negative effects of soil N enrichment on NPP in natural grasslands super-saturated with N. Furthermore, by considering ANPP and BNPP simultaneously, our results indicate that previous findings from above-ground might have over-estimated the positive effects of N deposition on primary productivity.

Assessment of Changes in the Biological Activity of Mountain Meadow-Steppe Soils of Pastures of Different Stages of Digression in the Central Caucasus

The indicators of biological activity (humus content and reserves, microbial biomass carbon content and reserves, activity of hydrolase and oxidoreductase class enzymes) in the upper horizons (0–10 cm) of mountain meadow-steppe soils of the Central Caucasus (Kabardino-Balkaria) were determined at different stages of pasture digression (D1, D2, D3). It was found that the values of controlled soil parameters in conditions of weakly (D1) and moderately disturbed (D2) meadow phytocenoses did not significantly differ (t 1.97; P 0.05). Statistically significant decreases (t 2.95; P 0.05) in biological parameters were revealed in soils of severely disturbed meadow steppes (D3) compared with less damaged meadows (D1 and D2). Based on the totality of the studied indicators of biological activity, an integral indicator of the ecological and biological state of soils (IIEBSS) is calculated, reflecting the overall level of biological activity of the studied soils at different stages of digression of meadow-steppe communities. There was a decrease in the IIEBSS of moderately grazed (D2) and overgrazed (D3) meadows relative to the values of the conditional standard (D1) by 11and 45%, respectively. The obtained results of the biological state of mountain meadow-steppe soils are used for monitoring studies aimed at assessing the degree of change in the soil and vegetation cover of mountain pasture ecosystems.

Impacts of human pressure and climate on biodiversity-multifunctionality relationships on the Qinghai-Tibetan Plateau.

Many studies have investigated the effects of environmental context on biodiversity or multifunctionality in alpine regions, but it is uncertain how human pressure and climate may affect their relationships. Here, we combined the comparative map profile method with multivariate datasets to assess the spatial pattern of ecosystem multifunctionality and further identify the effects of human pressure and climate on the spatial distribution of biodiversity-multifunctionality relationships in alpine ecosystems of the Qinghai-Tibetan Plateau (QTP). Our results indicate that at least 93% of the areas in the study region show a positive correlation between biodiversity and ecosystem multifunctionality across the QTP. Biodiversity-multifunctionality relationships with increasing human pressure show a decreasing trend in the forest, alpine meadow, and alpine steppe ecosystems, while an opposite pattern was found in the alpine desert steppe ecosystem. More importantly, aridity significantly strengthened the synergistic relationship between biodiversity and ecosystem multifunctionality in forest and alpine meadow ecosystems. Taken together, our results provide insights into the importance of protecting and maintaining biodiversity and ecosystem multifunctionality in response to climate change and human pressure in the alpine region.

Deepened snow cover increases grassland soil carbon stocks by incorporating carbon inputs into deep soil layers.

Climate-induced changes in snow cover can greatly impact winter soil microclimate and spring water supply. These effects, in turn, can influence plant and microbial activity and the strength of leaching processes, potentially altering the distribution and storage of soil organic carbon (SOC) across different soil depths. However, few studies have examined how changes in snow cover will affect SOC stocks, and even less is known about the impact of snow cover on SOC dynamics along soil profiles. By selecting 11 snow fences along a 570 km climate gradient in Inner Mongolia, covering arid, temperate, and meadow steppes, we measured plant and microbial biomass, community composition, SOC content, and other soil parameters from topsoil to a depth of 60 cm. We found that deepened snow increased aboveground and belowground plant biomass, as well as microbial biomass. Plant and microbial carbon input were positively correlated with grassland SOC stocks. More importantly, we found that deepened snow altered SOC distribution along vertical soil profiles. The increase in SOC caused by deepened snow was much greater in the subsoil (+74.7%; 40-60 cm) than that in the topsoil (+19.0%; 0-5 cm). Additionally, the controls on SOC content under deepened snow differed between the topsoil and subsoil layers. The increase in microbial and root biomass jointly enhanced topsoil C accumulation, while the increase in leaching processes became critical in promoting subsoil C accumulation. We conclude that under deepened snow, the subsoil had a high capacity to sink C by incorporating C leached from the topsoil, suggesting that the subsoil, originally thought to be climate insensitive, could have a higher response to precipitation changes due to vertical C transport. Our study highlights the importance of considering soil depth when assessing the impacts of snow cover changes on SOC dynamics.

Spatial–Temporal Correlation Considering Environmental Factor Fusion for Estimating Gross Primary Productivity in Tibetan Grasslands

Gross primary productivity (GPP) is an important indicator in research on carbon cycling in terrestrial ecosystems. High-accuracy GPP prediction is crucial for ecosystem health and climate change assessments. We developed a site-level GPP prediction method based on the GeoMAN model, which was able to extract spatiotemporal features and fuse external environmental factors to predict GPP on the Tibetan Plateau. We evaluated four models’ behavior—Random Forest (RF), Support Vector Machine (SVM), Deep Belief Network (DBN), and GeoMAN—in predicting GPP at nine flux observation sites on the Tibetan Plateau. The GeoMAN model achieved the best results (R2 = 0.870, RMSE = 0.788 g Cm−2 d−1, MAE = 0.440 g Cm−2 d−1). Distance and vegetation type of the flux sites influenced GPP prediction, with the latter being more significant. The different grassland vegetation types exhibited different sensitivity to environmental factors (Ta, PAR, EVI, NDVI, and LSWI) for GPP prediction. Among them, the site located in the alpine swamp meadow was insensitive to changes in environmental factors; the GPP prediction accuracy of the site located in the alpine meadow steppe decreased significantly with the changes in environmental factors; and the GPP prediction accuracy of the site located in the alpine Kobresia meadow also varied with environmental factor changes, but to a lesser extent than the former. This study provides a good reference that deep learning model is able to achieve good accuracy in GPP simulation when considers spatial, temporal, and environmental factors, and the judgement made by deep learning model conforms to basic knowledge in the relevant field.

Carbon in Chinese grasslands: meta-analysis and theory of grazing effects

Globally, livestock grazing is an important management factor influencing soil degradation, soil health and carbon (C) stocks of grassland ecosystems. However, the effects of grassland types, grazing intensity and grazing duration on C stocks are unclear across large geographic scales. To provide a more comprehensive assessment of how grazing drives ecosystem C stocks in grasslands, we compiled and analyzed data from 306 studies featuring four grassland types across China: desert steppes, typical steppes, meadow steppes and alpine steppes. Light grazing was the best management practice for desert steppes (< 2 sheep ha−1) and typical steppes (3 to 4 sheep ha−1), whereas medium grazing pressure was optimal for meadow steppes (5 to 6 sheep ha−1) and alpine steppes (7 to 8 sheep ha−1) leading to the highest ecosystem C stocks under grazing. Plant biomass (desert steppes) and soil C stocks (meadow steppes) increased under light or medium grazing, confirming the ‘intermediate disturbance hypothesis’. Heavy grazing decreased all C stocks regardless of grassland ecosystem types, approximately 1.4 Mg ha−1 per year for the whole ecosystem. The regrowth and regeneration of grasslands in response to grazing intensity (i.e., grazing optimization) depended on grassland types and grazing duration. In conclusion, grassland grazing is a double-edged sword. On the one hand, proper management (light or medium grazing) can maintain and even increase C stocks above- and belowground, and increase the harvested livestock products from grasslands. On the other hand, human-induced overgrazing can lead to rapid degradation of vegetation and soils, resulting in significant carbon loss and requiring long-term recovery. Grazing regimes (i.e., intensity and duration applied) must consider specific grassland characteristics to ensure stable productivity rates and optimal impacts on ecosystem C stocks.Graphical

Random forest method for analysis of remote sensing inversion of aboveground biomass and grazing intensity of grasslands in Inner Mongolia, China

ABSTRACT The quantification of grassland above-ground biomass (AGB) and grazing intensity (GI) and their distribution in space is of great significance to grassland management and eco-conservation. Remote-sensing technology is widely applied, but it is difficult to measure accurately when monitoring GI. In this study, the neural network, random forest and statistical function models of the relationship between Landsat NDVI and AGB were constructed by field survey and literature data collection in Inner Mongolia grassland, China. By comparing the accuracy among the three models, we constructed a remote-sensing retrieving model of grass AGB. We also estimated the grassland AGB during the peak growing season (August) for Inner Mongolia. Frequency histograms were then made to identify AGB thresholds under four GI levels (light or ungrazed, moderate grazing, overgrazing and extreme grazing) for each of three grassland types (meadow steppe, typical steppe and desert steppe). This study shows that the random forest model simulates grass AGB more accurately than other models. The spatial distribution of AGB in Inner Mongolia grasslands showed a tendency of decreasing from southeast to northwest, with an increasing trend in the last 10 years. The four GI levels in 2021 accounted for 18%, 25%, 36% and 21% of the grasslands in Inner Mongolia, respectively, and over the last 10 years the GI first improved and then deteriorated. This study provides a guideline to remote monitoring for grassland AGB and GI, and supplies scientific support for sustainable management and grassland restoration of large-scale grasslands.

Shrub encroachment increases soil carbon and nitrogen stocks in alpine grassland ecosystems of the central Tibetan Plateau

Shrub encroachment can significantly affect the ecosystem structure and functioning of alpine grasslands. However, little is known about how this phenomenon alters soil organic carbon stocks (SOCS) and soil nitrogen stocks (STNS) in different alpine grassland ecosystems within the same region. Here we addressed this research gap by investigating the SOCS and STNS of encroached and non-encroached plots in alpine meadow and alpine steppe ecosystems on the central Tibetan Plateau. We found that, in both ecosystems, shrub encroachment significantly increased herbaceous plant richness, diversity, and aboveground biomass, but more notably in alpine meadow. Conversely, shrub encroachment increased belowground plant biomass in alpine steppe but had the opposite effect in alpine meadow, where belowground biomass was four times lower at encroached than at non-encroached plots. Importantly, encroaching shrubs resulted in significantly higher SOCS and STNS in both ecosystems, with alpine steppe showing the greatest carbon and nitrogen gains. The shrub encroached plots had 34.24 % and 97.25 % higher carbon stocks and 70.87 % and 67.34 % higher nitrogen stocks than non-encroached plots at the alpine meadow and alpine steppe, respectively. Increases in carbon and nitrogen stocks occurred mostly at the 10–30 cm soil layer and were highly correlated with shrub-induced changes in the herbaceous community composition. Overall, our results indicated that (1) shrub encroachment promoted carbon and nitrogen accumulation in the soils of both alpine meadow and alpine steppe and (2) the degree of accumulation and the mechanisms behind these changes varied between the two alpine grasslands. Our findings advance the general understanding of the soil carbon and nitrogen dynamics in shrub‐encroached alpine grasslands and highlight the importance of investigating how this phenomenon affects different ecosystems within the same region.

Quantifying the Contribution of Driving Factors on Distribution and Change of Net Primary Productivity of Vegetation in the Mongolian Plateau

In recent years, multiple disturbances have significantly altered terrestrial ecosystems in arid and semi-arid regions, particularly on the Mongolian Plateau (MP). Net primary productivity (NPP) of vegetation is an essential component of the surface carbon cycle. As such, it characterizes the state of variation in terrestrial ecosystems and reflects the productive capacity of natural vegetation. This study revealed the complex relationship between the natural environment and NPP in the ecologically fragile and sensitive MP. The modified Carnegie–Ames–Stanford Approach (CASA) model was used to simulate vegetation NPP. Further, the contributions of topography, vegetation, soils, and climate to NPP’s distribution and spatiotemporal variation were explored using the geographic detector model (GDM) and structural equation model (SEM). The study’s findings indicate the following: (1) NPPs for different vegetation types in the MP were in the order of broad-leaved forest &gt; meadow steppe &gt; coniferous forest &gt; cropland &gt; shrub &gt; typical steppe &gt; sandy land &gt; alpine steppe &gt; desert steppe. (2) NPP showed an increasing trend during the growing seasons from 2000 to 2019, with forests providing larger vegetation carbon stocks. It also maintained a more stable level of productivity. (3) Vegetation cover, precipitation, soil moisture, and solar radiation were the key factors affecting NPP’s spatial distribution. NPP’s spatial distribution was primarily explained by the normalized difference vegetation index, solar radiation, precipitation, vegetation type, soil moisture, and soil type (-statistics = 0.86, 0.71, 0.67, 0.67, 0.57, and 0.57, respectively); the contribution of temperature was small (-statistics = 0.26), and topographic factors had the least influence on NPP’s distribution, as their contribution amounted to less than 0.20. (4) A SEM constructed based on the normalized difference vegetation index (NDVI), solar radiation, precipitation, temperature, and soil moisture explained 17% to 65% of the MP’s NPP variations. The total effects of the MP’s NPP variations in absolute values were in the order of NDVI (0.47) &gt; precipitation (0.33) &gt; soil moisture (0.16) &gt; temperature (0.14) &gt; solar radiation (0.02), and the mechanisms responsible for NPP variations differed slightly among the relevant vegetation types. Overall, this study can help understand the mechanisms responsible for the MP’s NPP variations and offer a new perspective for regional vegetation ecosystem management.

Alternations of ensiling performance and bacterial community in response to different native grassland in Mongolian Plateau

The aim of this study was to investigate the dynamics of bacterial communities and natural fermentation quality in three steppe types [meadow steppe (MS); typical steppe (TS); and desert steppe (DS)] on the Mongolian Plateau. PacBio single molecule with real-time sequencing technology was applied to provide insights into the dynamics of the physicochemical characteristics and the complex microbiome of native grass after 1, 7, 15, and 30 days of fermentation process. The dry matter, crude protein, and water soluble carbohydrate (WSC) contents of the three groups slowly decreased after 1 day of fermentation process, and the lowest WSC concentration after 30 days of ensiling was detected in the DS group compared to that in the MS and TS groups. There was no significant effect of steppe types on lactic acid and butyric acid content (P>0.05). The pH was higher in the early stages of fermentation. After 30 days of fermentation, the pH of MS and DS dropped to ∼5.60, while TS was as high as 5.94. At different ensiling days, the pH of TS was significantly higher than that of MS (P<0.05). The ammonia nitrogen content of MS was significantly higher than TS and DS (P<0.05). During the whole fermentation process, Leuconostoc mesenteroides and Pseudocitrobacter faecalis were the main species of DS, while Enterobacter roggenkampii and Faecalibacterium prausnitzii dominated the fermentation process in MS and TS, respectively. The fermentation quality of native grass silage of different steppe types was less satisfactory, with the silage quality ranging from DS, MS, and TS in descending order. The epiphytic bacteria dominating the fermentation process differed between steppe types of silage. Leuconostoc mesenteroides as the main strain of DS had a modulating effect on pH and LA content, while the main strains of MS and TS (Enterobacter roggenkampii and Faecalibacterium prausnitzii) dominated the silage without significant effect on improving fermentation characteristics and nutritional quality.

Relationships between modern pollen and vegetation and climate on the eastern Tibetan Plateau

The Tibetan Plateau ecosystem is fragile and sensitive to climate change. Understanding the relationships between modern pollen and the vegetation and climate of the region is critical for the evaluation of ecological processes. Here, we explore modern pollen assemblages of typical land-cover types at a large spatial scale by analyzing 36 surface samples from the southeastern Tibetan Plateau, supplemented by typical desert, desert-steppe, and steppe meadow transition data selected from the Chinese Surface Pollen Database, giving a total of 75 samples. We used redundancy analysis (RDA) to explore the responses of vegetation in the assemblages to regional climate. Our results show that pollen assemblages generally reflect the vegetation composition: assemblages from alpine meadow samples are dominated by Cyperaceae, Asteraceae, Rosaceae, and Polygonaceae; alpine shrublands mainly comprise Fabaceae, Rosaceae, Ericaceae, and Quercus (Q. spinosa); and coniferous forest surface samples mainly comprise Picea, Abies, Pinus, and Betulaceae. Our RDA shows that mean annual precipitation (MAP) is the main meteorological factor affecting the pollen assemblage and vegetation type; MAP positively correlates with percentages of Cyperaceae, Poaceae, Rosaceae, and Asteraceae, and negatively correlates with percentages of Chenopodiaceae, Ephedraceae, Nitraria, and Tamaricaceae. The ratio of Artemisia to Chenopodiaceae is a useful indicator to distinguish temperate desert from other land-cover types on the Tibetan Plateau, while the ratio of Cyperaceae + Asteraceae to Artemisia + Chenopodiaceae can be used to distinguish arid desert from other land-cover types, and may provide a useful altitude index for the eastern Tibetan Plateau.

A dataset of land cover classifications with a spatial resolution of 30m in Mongolia in 2005 and 2015

The Mongolian Plateau is in the interior of Northeast Asia, and is extremely vulnerable to climate change and the deleterious effects of human activities. Mongolia is an important component unit of the Mongolian Plateau, and its resources, environment and ecological problems are closely related to the ecological barrier and resource security in northern China and the sustainable development of the China-Mongolia-Russia Corridor. However, there is still a lack of high-precision land cover data products suitable for the regional characteristics of Mongolia. In this study, according to the landscape pattern of Mongolia, we constructed a land cover classification system suitable for Mongolia; and based on the object-oriented remote sensing interpretation method, we adopted the split-scene interpretation to select a variety of indexes. According to certain rules and classification thresholds, we obtained a dataset of land cover classifications with a spatial resolution of 30m in Mongolia in 2005 and 2015. The land cover classifications of Mongolia includes 11 categories: forest, meadow steppe, real steppe, desert steppe, bare land, sand, desert, ice and snow, water, cropland and built areas. Based on multi-source validation point information and high-resolution Google Earth images, we completed an overall quality assessment and a single classification quality assessment of land cover classification results in Mongolia. In 2005, the overall classification accuracy is 78.85% and the Kappa coefficient is 0.77. In 2015, the overall classification accuracy is 80.49% and the Kappa coefficient is 0.78. The average annual classification accuracy is 79.67%, which meets the accuracy requirements. The dataset can directly reflect the changes of land cover pattern and trend in Mongolia and provide basic scientific data to support the sustainable development of Mongolia.