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Due to climate change and global warming, the frequency of sandstorms in northern China is increasing. Stipa breviflora, a dominant species in Eurasian grasslands, can help prevent desertification from becoming more serious. Studies on S. breviflora cover a wide range of fields. To the best of our knowledge, the present study is the first to sequence, assemble, and annotate the S. breviflora genome. In total, 2,781,544 contigs were assembled, and 2,600,873 scaffolds were obtained, resulting in a total length of 649,849,683 bp. The number of scaffolds greater than 1 kb was 70,770. We annotated the assembled genome (>121 kb), conducted a selective sweep analysis, and ultimately succeeded in assembling the Matk gene of S. breviflora. More importantly, our research identified 26 scaffolds that may be responsible for the drought tolerance of S. breviflora Griseb. In summary, the data obtained regarding S. breviflora will be of great significance for future research. [ABSTRACT FROM AUTHOR]

Leymus chinensis is a widely distributed species of Eurasian grasslands that is well adapted to a range of environmental conditions. In this study, we measured soil and plant chemical elements to examine the basis of the ecological adaptations of L. chinensis to temperate steppe. We sampled leaves of L. chinensis and soil layers at different latitudes in temperate steppe for three consecutive years from 2012 to 2014. One-way analysis of variance and linear regression were used to analyze the variation in foliar nitrogen (N) and phosphorus (P) contents and the N:P ratio in L. chinensis. The correlations between the foliar N:P ratio and the variation in soil total nitrogen (TN) and total P contents with latitudinal gradient were measured to explore the homeostasis stoichiometry of foliar N and P in L. chinensis. With increasing latitude, both the foliar N and P contents of L. chinensis showed parabolic trends with significant negative correlations. The population of L. chinensis was limited by N, and the soil TN content showed a significant increasing trend with the increase in the foliar N:P ratio. The variation in the foliar N:P ratio of L. chinensis was determined through the variation in the soil N content. In different latitude intervals, the foliar N, P, and N:P ratio of L. chinensis showed absolute stability and strong internal stability, and the values of HN:P were high and similar in different latitudes. In conclusion, the population of L. chinensis in the temperate steppe is highly adaptable; and, thus, can maintain a dominant position in the variable environment and has a wide distribution range. [ABSTRACT FROM AUTHOR]

Drought has a great impact on global terrestrial ecosystems. A large number of studies have shown that the impact of drought on vegetation growth has a lagged and cumulative effect, but it is unclear how much it contributes to different vegetation types. Therefore, based on the standardized precipitation evapotranspiration index (SPEI) base version 2.5 and the Global Inventory Monitoring and Modeling System (GIMMS3g) normalized difference vegetation index (NDVI) datasets, this study aimed to analyze the response process of different vegetation types to the cumulative and lagged effects of drought in the Mongolian Plateau during 1982–2015 using Pearson correlation and the Mann–Kendall mutation method and deeply explore the magnitude of the contribution of drought cumulative and lagged effects on vegetation using the multiple regression method. Our results show that, from 1982 to 2015 as a whole, NDVI showed an insignificant increasing trend, and SPEI had a significant mutation in 1998 and showed an insignificant increasing trend before and after 1998. Before 1998, the cumulative months were shorter (1–3 months) in the central steppe and agricultural vegetation zones, and the lagged months were longer (10–12 months) in the southeastern steppe and northeastern forest zones; after 1998, the cumulative months of NDVI increased (7–12 months) and the lag months decreased (3–8 months) in most vegetation zones. A comparison of the contribution of drought accumulation and lag to NDVI revealed that the main driver of NDVI has shifted from lagged to cumulative effect. [ABSTRACT FROM AUTHOR]

Soil represents the largest terrestrial organic carbon pool. To address global climate change, it is essential to explore the soil organic carbon storage patterns and their controlling factors. We investigated the soil organic carbon density (SOCD) in 48 grassland sites along the Eurasian steppe eastern transect (ESET) region, which covers the Inner Mongolia grassland subregion and Mongolia grasslands subregion. Specifically, we analyzed the SOCD in the top 30 cm soil layer and its relationships with climatic variables, soil texture, grazing intensity and community biomass productivity. The results showed that the average SOCD of the ESET was 4.74 kg/m2, and the SOCD of the Inner Mongolia grassland subregion (4.11 kg/m2) was significantly lower than that of the Mongolia grassland subregion (5.79 kg/m2). Significant negative relationships were found between the SOCD and the mean annual temperature (MAT), mean annual precipitation (MAP) and grazing intensity in the ESET region. The MAT and grazing intensity were identified as the major factors influencing the SOCD in the ESET region; the MAP and MAT were the major factors influencing the SOCD in the Inner Mongolia grassland subregion; and the MAT and soil pH were the major factors influencing the SOCD in the Mongolia grassland subregion. [ABSTRACT FROM AUTHOR]

Agricultural flood disaster risk assessment plays a vital role in agricultural flood disaster risk management. Extreme precipitation events are the main causes of flood disasters in the Midwest Jilin province (MJP). Therefore, it is important to analyse the characteristics of extreme precipitation events and assess the flood risk. In this study, the Multifractal Detrended Fluctuation Analysis (MF-DFA) method was used to determine the threshold of extreme precipitation events. The total duration of extreme precipitation and the total extreme precipitation were selected as flood indicators. The copula functions were then used to determine the joint distribution to calculate the bivariate joint return period, which is the flood hazard. Historical data and flood indicators were used to build an agricultural flood disaster vulnerability surface model. Finally, the risk curve for agricultural flood disasters was established to assess the flood risk in the MJP. The results show that the proposed approaches precisely describe the joint distribution of the flood indicators. The results of the vulnerability surface model are in accordance with the spatiotemporal distribution pattern of the agricultural flood disaster loss in this area. The agricultural flood risk of the MJP gradually decreases from east to west. The results provide a firm scientific basis for flood control and drainage plans in the area. [ABSTRACT FROM AUTHOR]