Research in Cold and Arid Regions最新文献

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.

Water resources are one of the key factors restricting the development of arid areas, and cloud water resources is an important part of water resources. The arid region of central Asia is the core region of the current national green silk road construction, and is the largest arid region in the world. Based on cloud cover data of ECMWF, the current study analyzed temporal and spatial characteristics of cloud properties in arid regions of Central Asia between 1980 and 2019. Our findings show that: (1) From the point of view of spatial distribution, total cloudiness in arid regions of Central Asia was low in the south and high in the north. The distribution of high cloud frequency and medium cloud frequency was higher in the south and lower in the north, while low cloud frequency distribution was low in the south and high in the north. (2) In terms of time, the variation of cloud cover and cloud type frequency had obvious seasonal characteristics. From winter to spring, cloud cover increased, and the change of cloud type frequency increased. From spring to summer, cloud cover continued to increase and the change of cloud type frequency increased further. Cloud cover began to decrease from summer to autumn, and the change of cloud type frequency also decreased. (3) Generally, average total cloud cover decreased in most of central Asia, and high and medium cloud cover increased while low cloud cover decreased. This study provides a reference for the rational development of cloud resources in the region.

The Three-River Headwaters Region (TRHR) of Qinghai Province, in the Tibetan Plateau of China, is the main source of the Yangtze, Yellow, and Lancang rivers, and is very significant to the security of freshwater resources for China and southeastern Asia. It is a critical ecological region of China for its ecological functions, and has been changed or even degraded in recent decades owing to climate change and human pressure. To effectively protect and restore the degraded ecosystems, the Chinese government initiated a series of ecological conservation projects in TRHR. It is essential to quantitatively assess ecosystem changes and their relationship to driving factors for in-depth understanding of long-term changes of ecosystems and effects of ecological restoration policies and offer practical insights for ecological restoration. Here, land cover data has been interpreted with the series data of Landsat during 1990–2015. The patterns of different ecosystems and their developing process have been derived from land cover change. The results show that ecosystem types in TRHR include forest, grassland, cropland, wetland, artificial surface and barren land, accounting for 4.51%, 70.80%, 0.15%, 9.47%, 0.16% and 14.90%, respectively. Barren land converted to wetland was the significant ecosystem change from 1990 to 2015. Increases in temperature and precipitation and implementation of ecological rehabilitation helped maintain relatively stable ecosystem patterns. It is necessary to continue ecological projects to improve and/or maintain the ecosystems in TRHR because there is still a risk of land degradation under increasing climate change and human activity.

Unhealthy eating habits with sugar-rich and high-fat foods can bring nutritional imbalance and other chronic diseases. At present, there is an increasing demand in regulating human sub-health through functional foods. Agriophyllum squarrosum (L.) Moq., a pioneer plant native to sand dunes with ecological restoration function, is a traditional food plant of sand regions and Mongolian folk medicine. Numerous studies have confirmed that A. squarrosum seed, also called sand rice, has high nutritional value. However, the long-term health effects of eating sand rice remain unclear. To better explore and evaluate its long-term effects, hereby, ICR mice were fed with sand rice flour at different ratios (control, 60% and 95%) for 100 days. Results show that the growth and blood glucose level curve of these experimental mice were lower and more stable than that of the control. In addition, mice fed pure sand rice ingredient (95%) gained more stable body weight and blood glucose after 28 days, which revealed that sand rice is a food with comprehensive nutritional value and rarely negatively impacts the body growth performance. Our data also demonstrates that, the content of triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) provided the lowest level in the blood of mice with a diet of pure sand rice ingredient, 0.48, 4.14, 0.91, 3.03 mmol/L, respectively. Also, T-SOD and GSH-PX activity provided a high level in mice with pure sand rice gradient, which significantly increased by 36% (T-SOD) and 19% (GSH-PX) compared to the control. These results suggest that long term intake of the pure sand rice ingredients is more helpful for stabilizing blood lipid and improve antioxidant capacity and beneficial to people suffering from chronic disease. This study supplies the first animal evidence to support the claim that sand rice is a promising functional food with comprehensive nutrition in the future. We are confident that, with increasing demands of daily sand rice usage, planting A. squarrosum in the vast desert regions will further increase the local economy and ecological restoration when coping with global warming.

Silty clay is widely used as subgrade filler in cold regions, which suffer from frost heave in winter and mud pumping in spring. In this study, polyvinyl alcohol (PVA) and polypropylene (PP) fiber were used to improve the mechanical and frost heave behavior of silty clay in cold regions, and the direct shear test and one-dimensional frost heave test were employed in studying improvement effects. Moreover, improvement mechanisms of PVA and PP fiber were analyzed based on test results. The main findings are as follows. (1) Both PP and PVA can heighten the strength of silty clay and suppress frost heave, but the PVA solution has a more decisive influence on improving mechanical properties than PP fiber. (2) The improvement mechanism of the PVA solution is cementing. The improvement effect of 2% PVA solution is the best, which can increase the shear strength by approximately 40%–60% at different stress levels and decrease the frost heave ratio from 0.89% to 0.16% at optimal water content. (3) For 2% PVA improved samples, 0.25% PP fiber can further increase soil cohesion by approximately 20–30 kPa at different stress levels and further decrease the frost heave ratio from 0.16% to 0.07% at optimal water content. The improvement effect is neglectable when the PP fiber content exceeds 0.25%. Overall, 2% PVA with 0.25% PP fiber is the optimum combination to improve silty clay in cold regions.

A challenge for the development of Land Surface Models (LSMs) is improving transpiration of water exchange and photosynthesis of carbon exchange between terrestrial plants and the atmosphere, both of which are governed by stoma in leaves. In the photosynthesis module of these LSMs, variations of parameters arising from diversity in plant functional types (PFTs) and climate remain unclear. Identifying sensitive parameters among all photosynthetic parameters before parameter estimation can not only reduce operation cost, but also improve the usability of photosynthesis models worldwide. Here, we analyzed 13 parameters of a biochemically-based photosynthesis model (FvCB), implemented in many LSMs, using two sensitivity analysis (SA) methods (i.e., the Sobol’ method and the Morris method) for setting up the parameter ensemble. Three different model performance metrics, i.e., Root Mean Squared Error (RMSE), Nash Sutcliffe efficiency (NSE), and Standard Deviation (STDEV) were introduced for model assessment and sensitive parameters identification. The results showed that among all photosynthetic parameters only a small portion of parameters were sensitive, and the sensitive parameters were different across plant functional types: maximum rate of Rubisco activity (V_cmax25), maximum electron transport rate (J_max25), triose phosphate use rate (TPU) and dark respiration in light (R_d) were sensitive in broad leaf-evergreen trees (BET), broad leaf-deciduous trees (BDT) and needle leaf-evergreen trees (NET), while only V_cmax25 and TPU are sensitive in short vegetation (SV), dwarf trees and shrubs (DTS), and agriculture and grassland (AG). The two sensitivity analysis methods suggested a strong SA coherence; in contrast, different model performance metrics led to different SA results. This misfit suggests that more accurate values of sensitive parameters, specifically, species specific and seasonal variable parameters, are required to improve the performance of the FvCB model.

Vegetation fires become the concern worldwide due to their substantial impacts on climate and environment, and in particular in the circum-Arctic. Assessing vegetation fires and associated emissions and causes can improve understanding of fire regime and provide helpful information for vegetation fires solution. In this study, satellite-based vegetation fires and emissions during 2001–2020 were investigated and contributions of different types of fires were analyzed. Furthermore, climate anomalies related to extreme vegetation fires were explored. The main results showed that the region south of the Arctic circle (50°N−67°N) experienced a greater number of vegetation fires compared to the Arctic (north of 67°N). During 2001–2020, interannual variability of vegetation fires between 50°N and 67°N appeared to be decreasing while emissions (including carbon, dry matter, PM_2.5, and BC) appeared to be increasing overall, which were contributed by the increasing summer boreal forest fires in this region largely. In the Arctic, vegetation fires and emissions increased in recent years distinctly, and those were dominated by the summer forest fires. Spatially, large increases of vegetation fires were located in the eastern Siberia and northern North America while large decreases were located in the northwestern Eurasia mainly. Additionally, in the Arctic, the unprecedented vegetation fires were observed in the eastern Siberia and Alaska in 2019 and in the eastern Siberia in 2020, which could be attributed to high pressure, high near-surface temperature, and low air moisture anomalies. Meanwhile, obvious anticyclonic anomalies in Alaska in 2019 and in the eastern Siberia in 2020 and cyclonic anomalies in the western Siberia in 2019, also played an important role on fire occurrences making drier conditions.

Buildings are always affected by frost heave and thaw settlement in cold regions, even where saline soil is present. This paper describes the triaxial testing results of frozen silty clay with high salt content and examines the influence of confining pressure and temperature on its mechanical characteristics. Conventional triaxial compression tests were conducted under different confining pressures (0.5–7.0 MPa) and temperatures (−6 °C, −8 °C, −10 °C, and −12 °C). The test results show that when the confining pressure is less than 1 MPa, the frozen saline silty clay is dominated by brittle behavior with the X-shaped dilatancy failure mode. As the confining pressure increases, the sample gradually transitions from brittle to plastic behavior. The strength of frozen saline silty clay rises first and then decreases with increasing confining pressure. The improved Duncan-Chang hyperbolic model can describe the stress-strain relationship of frozen saline silty clay. And the parabolic strength criterion can be used to describe the strength evolution of frozen saline silty clay. The function relation of strength parameters with temperature is obtained by fitting, and the results of the parabolic strength criterion are in good agreement with the experimental results, especially when confining pressure is less than 5 MPa. Therefore, the study has important guiding significance for design and construction when considering high salinity soil as an engineering material in cold regions.

Spatial patterns of plant species and patchy community are important properties in grasslands. However, research regarding spatial patterns of formed patches with various species has not fully advanced until now. Our purpose is to clarify differences in spatial pattern formed by species and community constructed under shady and terrace habitats. The three common Kobresia-Carex patches (Size 1, 0.6–0.9 m²; Size 2, 3.0–3.8 m² and Size 3, 6.5–8.8 m²) were selected in shady and terrace on the Qinghai-Tibetan Plateau, and corresponding quadrats of 1m×1m, 2m×2m and 3m×3m were placed for S1, S2 and S3 patches, respectively. The surveyed quadrats were divided into 20cm×20cm large cells (L-cells), and further divided into four 10cm×10cm small cells (S-cells). We used the binary occurrence system (presence/absence data) to record occurrences of all species in S-cells. The analysis shows that the power law model was well able to determine the spatial distribution pattern of species or patchy community in shady and terrace. All species and patches show aggregated distribution in shady and terrace habitats. In the shady habitat, the relative spatial heterogeneity (ε) of individual plant species was lowest at presence frequency (P) of 0.1–0.3, whereas in the terrace habitat ε was lowest at P <0.1, and ε increased monotonically with increasing P. For most dominant species, P and ε values were higher in terrace than those in shady. We concluded that the dominant species largely determine spatial heterogeneity of the Kobresia-Carex patches, while companion and rare species have weak influence on the community-level heterogeneity in shady and terrace habitats.