Dew is an essential water resource for the survival and reproduction of organisms in arid and semi-arid regions. Yet estimating the dew amount and quantifying its long-term variation are challenging. In this study, we elucidate the dew amount and its long-term variation in the Kunes River Valley, Northwest China, based on the measured daily dew amount and reconstructed values (using meteorological data from 1980 to 2021), respectively. Four key results were found: (1) the daily mean dew amount was 0.05 mm during the observation period (4 July–12 August and 13 September–7 October of 2021). In 35 d of the observation period (i.e., 73% of the observation period), the daily dew amount exceeded the threshold (>0.03 mm/d) for microorganisms; (2) air temperature, relative humidity, and wind speed had significant impacts on the daily dew amount based on the relationships between the measured dew amount and meteorological variables; (3) for estimating the daily dew amount, random forest (RF) model outperformed multiple linear regression (MLR) model given its larger R2 and lower MAE and RMSE; and (4) the dew amount during June–October and in each month did not vary significantly from 1980 to the beginning of the 21st century. It then significantly decreased for about a decade, after it increased slightly from 2013 to 2021. For the whole meteorological period of 1980–2021, the dew amount decreased significantly during June–October and in July and September, and there was no significant variation in June, August, and October. Variation in the dew amount in the Kunes River Valley was mainly driven by relative humidity. This study illustrates that RF model can be used to reconstruct long-term variation in the dew amount, which provides valuable information for us to better understand the dew amount and its relationship with climate change.
Abstract: Litter decomposition is an important component of the nutrient recycling process and is highly sensitive to climate change. However, the impacts of warming and increased precipitation on litter decomposition have not been well studied, especially in the alpine grassland of Tianshan Mountains. We conducted a manipulative warming and increased precipitation experiment combined with different grassland types to examine the impact of litter quality and climate change on the litter decomposition rate based on three dominant species (Astragalus mongholicus, Potentilla anserina, and Festuca ovina) in Tianshan Mountains from 2019 to 2021. The results of this study indicated there were significant differences in litter quality, specific leaf area, and leaf dry matter content. In addition, litter quality exerted significant effects on litter decomposition, and the litter decomposition rate varied in different grassland types. Increased precipitation significantly accelerated the litter decomposition of P. anserina; however, it had no significant effect on the litter decomposition of A. mongholicus and F. ovina. However, warming consistently decreased the litter decomposition rate, with the strongest impact on the litter decomposition of F. ovina. There was a significant interaction between increased precipitation and litter type, but there was no significant interaction between warming and litter type. These results indicated that warming and increased precipitation significantly influenced litter decomposition; however, the strength was dependent on litter quality. In addition, soil water content played a crucial role in regulating litter decomposition in different grassland types. Moreover, we found that the litter decomposition rate exhibited a hump-shaped or linear response to the increase of soil water content. Our study emphasizes that ongoing climate change significantly altered litter decomposition in the alpine grassland, which is of great significance for understanding the nutrient supply and turnover of litter.
Abstract: Hydrothermal condition is mismatched in arid and semi-arid regions, particularly in Central Asia (including Kazakhstan, Kyrgyzstan, Tajikistan, Uzbekistan, and Turkmenistan), resulting many environmental limitations. In this study, we projected hydrothermal condition in Central Asia based on bias-corrected multi-model ensembles (MMEs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under four Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP) scenarios (SSP126 (SSP1-RCP2.6), SSP245 (SSP2-RCP4.5), SSP460 (SSP4-RCP6.0), and SSP585 (SSP5-RCP8.5)) during 2015–2100. The bias correction and spatial disaggregation, water-thermal product index, and sensitivity analysis were used in this study. The results showed that the hydrothermal condition is mismatched in the central and southern deserts, whereas the region of Pamir Mountains and Tianshan Mountains as well as the northern plains of Kazakhstan showed a matched hydrothermal condition. Compared with the historical period, the matched degree of hydrothermal condition improves during 2046–2075, but degenerates during 2015–2044 and 2076–2100. The change of hydrothermal condition is sensitive to precipitation in the northern regions and the maximum temperatures in the southern regions. The result suggests that the optimal scenario in Central Asia is SSP126 scenario, while SSP585 scenario brings further hydrothermal contradictions. This study provides scientific information for the development and sustainable utilization of hydrothermal resources in arid and semi-arid regions under climate change.
Abstract: Glaciers are highly sensitive to climate change and are undergoing significant changes in mid-latitudes. In this study, we analyzed the spatiotemporal changes of typical glaciers and their responses to climate change in the period of 1990–2015 in 4 different mountainous sub-regions in Xinjiang Uygur Autonomous Region of Northwest China: the Bogda Peak and Karlik Mountain sub-regions in the Tianshan Mountains; the Yinsugaiti Glacier sub-region in the Karakorum Mountains; and the Youyi Peak sub-region in the Altay Mountains. The standardized snow cover index (NDSI) and correlation analysis were used to reveal the glacier area changes in the 4 sub-regions from 1990 to 2015. Glacial areas in the Bogda Peak, Karlik Mountain, Yinsugaiti Glacier, and Youyi Peak sub-regions in the period of 1990–2015 decreased by 57.7, 369.1, 369.1, and 170.4 km², respectively. Analysis of glacier area center of gravity showed that quadrant changes of glacier areas in the 4 sub-regions moved towards the origin. Glacier area on the south aspect of the Karlik Mountain sub-region was larger than that on the north aspect, while glacier areas on the north aspect of the other 3 sub-regions were larger than those on the south aspect. Increased precipitation in the Karlik Mountain sub-region inhibited the retreat of glaciers to a certain extent. However, glacier area changes in the Bogda Peak and Youyi Peak sub-regions were not sensitive to the increased precipitation. On a seasonal time scale, glacier area changes in the Bogda Peak, Karlik Mountain, Yinsugaiti Glacier, and Youyi Peak sub-regions were mainly caused by accumulated temperature in the wet season; on an annual time scale, the correlation coefficient between glacier area and annual average temperature was –0.72 and passed the significance test at P<0.05 level in the Karlik Mountain sub-region. The findings of this study can provide a scientific basis for water resources management in the arid and semi-arid regions of Northwest China in the context of global warming.
Abstract: Identifying water vapor sources in the natural vegetation of the Tianshan Mountains is of significant importance for obtaining greater knowledge about the water cycle, forecasting water resource changes, and dealing with the adverse effects of climate change. In this study, we identified water vapor sources of precipitation and evaluated their effects on precipitation stable isotopes in the north slope of the Tianshan Mountains, China. By utilizing the temporal and spatial distributions of precipitation stable isotopes in the forest and grassland regions, Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, and isotope mass balance model, we obtained the following results. (1) The Eurasia, Black Sea, and Caspian Sea are the major sources of water vapor. (2) The contribution of surface evaporation to precipitation in forests is lower than that in the grasslands (except in spring), while the contribution of plant transpiration to precipitation in forests (5.35%) is higher than that in grasslands (3.79%) in summer. (3) The underlying surface and temperature are the main factors that affect the contribution of recycled water vapor to precipitation; meanwhile, the effects of water vapor sources of precipitation on precipitation stable isotopes are counteracted by other environmental factors. Overall, this work will prove beneficial in quantifying the effect of climate change on local water cycles.
Water shortage is one bottleneck that limits economic and social developments in arid and semi-arid areas. As the impacts of climate change and human disturbance intensify across time, uncertainties in both water resource supplies and demands increase in arid and semi-arid areas. Taking a typical arid region in China, Xinjiang Uygur Autonomous Region, as an example, water yield depth (WYD) and water utilization depth (WUD) from 2002 to 2018 were simulated using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and socioeconomic data. The supply-demand relationships of water resources were analyzed using the ecosystem service indices including water supply-demand difference (WSDD) and water supply rate (WSR). The internal factors in changes of WYD and WUD were explored using the controlled variable method. The results show that the supply- demand relationships of water resources in Xinjiang were in a slight deficit, but the deficit was alleviated due to increased precipitation and decreased WUD of irrigation. WYD generally experienced an increasing trend, and significant increase mainly occurred in the oasis areas surrounding both the Junggar Basin and Tarim Basin. WUD had a downward trend with a decline of 20.70%, especially in oasis areas. Water resources in most areas of Xinjiang were fully utilized and the utilization efficiency of water resources increased. The water yield module in the InVEST model was calibrated and validated using gauging station data in Xinjiang, and the result shows that the use of satellite-based water storage data helped to decrease the bias error of the InVEST model by 0.69×108 m3. This study analyzed water resource supplies and demands from a perspective of ecosystem services, which expanded the scope of the application of ecosystem services and increased the research perspective of water resource evaluation. The results could provide guidance for water resource management such as spatial allocation and structural optimization of water resources in arid and semi-arid areas.
摘要：With the increase of exploration depth, it is more and more difficult to find Au deposits. Due to the limitation of time and cost, traditional geological exploration methods are becoming increasingly difficult to be effectively applied. Thus, new methods and ideas are urgently needed. This study assessed the feasibility and effectiveness of using hyperspectral technology to prospect for hidden Au deposits. For this purpose, 48 plant (Seriphidium terrae-albae) and soil (aeolian gravel desert soil) samples were first collected along a sampling line that traverses an Au mineralization alteration zone (Aketasi mining region in an arid region of China) and were used to obtain soil Au contents by a chemical analysis method and the reflectance spectra of plants obtained with an Analytical Spectral Device (ASD) FieldSpec3 spectrometer. Then, the corresponding relationship between the soil Au content anomaly and concealed Au deposits was investigated. Additionally, the characteristic bands were selected from plant spectra using four different methods, namely, genetic algorithm (GA), stepwise regression analysis (STE), competitive adaptive reweighted sampling (CARS), and correlation coefficient method (CC), and were then input into the partial least squares (PLS) method to construct a model for estimating the soil Au content. Finally, the quantitative relationship between the soil Au content and the 15 different plant transformation spectra was established using the PLS method. The results were compared with those of a model based on the full spectrum. The results obtained in this study indicate that the location of concealed Au deposits can be predicted based on soil geochemical anomaly information, and it is feasible and effective to use the full plant spectrum and PLS method to estimate the Au content in the soil. The cross-validated coefficient of determination (R2) and the ratio of the performance to deviation (RPD) between the predicted value and the measured value reached the maximum of 0.8218 and 2.37, respectively, with a minimum value of 6.56 μg/kg for the root-mean-squared error (RMSE) in the full spectrum model. However, in the process of modeling, it is crucial to select the appropriate transformation spectrum as the input parameter for the PLS method. Compared with the GA, STE, and CC methods, CARS was the superior characteristic band screening method based on the accuracy and complexity of the model. When modeling with characteristic bands, the highest accuracy, R2 of 0.8016, RMSE of 7.07 μg/kg, and RPD of 2.20 were obtained when 56 characteristic bands were selected from the transformed spectra (1/lnR)' (where it represents the first derivative of the reciprocal of the logarithmic spectrum) of sampled plants using the CARS method and were input into the PLS method to construct an inversion model of the Au content in the soil. Thus, characteristic bands can replace the full spectrum when constructing a model for estimating the soil Au content. Finally, this study proposes a method of using plant spectra to find concealed Au deposits, which may have promising application prospects because of its simplicity and rapidity.
摘要：The purpose of the current study was to investigate the eco-physiological responses, in terms of growth and C:N:P stoichiometry of plants cultured from dimorphic seeds of a single-cell C4 annual Suaeda aralocaspica (Bunge) Freitag and Schütze under elevated CO2. A climatic chamber experiment was conducted to examine the effects of ambient (720 μg/L) and CO2-enriched (1440 μg/L) treatments on these responses in S. aralocaspica at vegetative and reproductive stages in 2012. Result showed that elevated CO2 significantly increased shoot dry weight, but decreased N:P ratio at both growth stages. Plants grown from dimorphic seeds did not exhibit significant differences in growth and C:N:P stoichiometric characteristics. The transition from vegetation to reproductive stage significantly increased shoot:root ratio, N and P contents, but decreased C:N, C:P and N:P ratios, and did not affect shoot dry weight. Moreover, our results indicate that the changes in N:P and C:N ratios between ambient and elevated CO2 are mainly caused by the decrease of N content under elevated CO2. These results provide an insight into nutritional metabolism of single-cell C4 plants under climate change.
摘要：Net primary productivity (NPP) of the vegetation in an oasis can reflect the productivity capacity of a plant community under natural environmental conditions. Owing to the extreme arid climate conditions and scarce precipitation in the arid oasis regions, groundwater plays a key role in restricting the development of the vegetation. The Qira Oasis is located on the southern margin of the Taklimakan Desert (Tarim Basin, China) that is one of the most vulnerable regions regarding vegetation growth and water scarcity in the world. Based on remote sensing images of the Qira Oasis and daily meteorological data measured by the ground stations during the period 2006–2019, this study analyzed the temporal and spatial patterns of NPP in the oasis as well as its relation with the variation of groundwater depth using a modified Carnegie Ames Stanford Approach (CASA) model. At the spatial scale, NPP of the vegetation decreased from the interior of the Qira Oasis to the margin; at the temporal scale, NPP of the vegetation in the oasis fluctuated significantly (ranging from 29.80 to 50.07 g C/(m2•month)) but generally showed an increasing trend, with the average increase rate of 0.07 g C/(m2•month). The regions with decreasing NPP occupied 64% of the total area of the oasis. During the study period, NPP of both farmland and grassland showed an increasing trend, while that of forest showed a decreasing trend. The depth of groundwater was deep in the south of the oasis and shallow in the north, showing a gradual increasing trend from south to north. Groundwater, as one of the key factors in the surface change and evolution of the arid oasis, determines the succession direction of the vegetation in the Qira Oasis. With the increase of groundwater depth, grassland coverage and vegetation NPP decreased. During the period 2008–2015, with the recovery of groundwater level, NPP values of all types of vegetation with different coverages increased. This study will provide a scientific basis for the rational utilization and sustainable management of groundwater resources in the oasis.