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    26 March 2020, Volume 37 Issue 2 Previous Issue    Next Issue
    The rate of warming is slowing and temperature is showing sharp changes in middle and high latitude regions
    2020, 37 (2):  275-281.  doi: 10.13866/j.azr.2020.02.01
    Abstract ( 2053 )   PDF (1101KB) ( 394 )  
    This work used daily temperature data spanning 30 years from 13 national benchmark climate stations in the midlatitude regions of China to assess the freezing/thawing index and trends in the number of freezing/thawing days.The results show that the thawing index shows a significantly increasing trend and the freezing index shows a slightly increasing trend.An upward trend in thawing days and downward trend in freezing days were insignificant.The daily average thawing index significantly increased,whereas the daily average freezing index slightly increased.The characteristics of cold and warm polarizations were obvious.The more than 10 ℃ accumulated temperature and days in study area showed a significantly increasing trend,the less than -10 ℃ accumulated temperature showed a downtrend,and the less than -10 ℃ accumulated temperature days on the rise trend,the transition between two periods significantly decreased.The fluctuation in the thawing index was clearly less than that of the freezing index.Moreover,the thawing index was negatively correlated with latitude and altitude,whereas the freezing index was positively correlated with latitude and altitude.The influence of altitude on the thawing index was greater than that of the freezing index.As the latitude and altitude increased,the change in freezing index and freezing days were observed to be more stable,and the corresponding melting index showed larger fluctuations.On the whole,the rate of warming has slowed in China’s mid and high latitudes since the 1990s,and the polarization of average daily temperature and the sharp change in temperature are obvious in both the cold and warm seasons.
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    Spatial and temporal distribution characteristics of drought in Central Asia based on SPEI index
    ZHANG Leyuan, WANG Yi, CHEN Yaning
    2020, 37 (2):  282-290.  doi: 10.13866/j.azr.2020.02.07
    Abstract ( 1195 )   PDF (2546KB) ( 754 )  
    As a core region of the Silk Road,the importance of Central Asia to China is selfevident.With climate change,high dependence on irrigated agriculture,and increasing human disturbance,drought and water resource availability have become a key issue restricting the development and regional stability in Central Asia.This paper focused on five Central Asian countries (Kazakhstan,Kyrgyzstan,Tajikistan,Uzbekistan,and Turkmenistan) to assess the spatial and temporal distribution characteristics using the drought standardized precipitation evapotranspiration index (SPEI),which was calculated based on monthly Climatic Research Unit (CRU) data from 1961 to 2017.Specifically,the CRU grid point data (including monthly precipitation,temperature,and potential evapotranspiration) were used calculating SPEI to better reflect the climate change in Central Asia in terms of data quality and sequence.SPI and PDSI are widely used as drought indices; however,this study proposed the use of SPEI to analyze the drought condition in Central Asia as it can better reflect the effects of climate change on meteorological drought in arid and semiarid regions.The Thornthwaite formula has generally been used in the initial calculation process of SPEI; however,this only considers temperature in the calculation of potential evapotranspiration,and the calculated values may have large errors in arid and semiarid regions.Therefore,the PenmanMonteith formula was used in this paper to calculate potential evapotranspiration in the five Central Asian countries.In contrast to previous studies that mainly focused on a particular region of Central Asia,this paper calculated the SPEI value of each grid point of the five countries as a whole territory,thereby analyzing the spatial and temporal variation drought trends in Central Asia in detail.The results showed the following:(1) With the increase in temperature over the past half a century,precipitation in most parts of Central Asia showed a slow upward trend and potential evapotranspiration increased.The increase was centered in the Aral Sea basin and declined in a circular direction.(2) From 1961 to 2017,the average SPEI index in Central Asia has continuously declined; however,it greatly fluctuated.Annual changes showed a slow downward trend in SPEI value in spring and winter,and a significant downward trend in summer and autumn,indicating that the drought condition increased in summer and autumn in Central Asia.(3) Spatially,drought in most parts of Central Asia mainly increased in summers and autumns,and generally decreased in springs; in winters,drought at the border of Kazakhstan and Uzbekistan increased,and drought decreased in the eastern region.The results calculated using the SPEI drought index in this study were compared with the actual drought events and satisfactory results were obtained,indicating that our analysis and calculation of SPEI can reflect realtime drought situations in Central Asia,both temporally and spatially.Therefore,SPEI can be used as an important reference index of drought in Central Asia and can provide a valuable reference for drought risk assessment and water resources planning in Central Asia.
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    Experimental analysis for estimating the canopy snow water equivalent intercepted by the snow cover area of the Tianshan spruce
    WANG Yifan, XIE Ling, CHANG Shunli, LIU Suhong, Mariam Mamuti, Mirzati Yimin, Abdowli Abdukrmu
    2020, 37 (2):  341-348.  doi: 10.13866/j.azr.2020.02.08
    Abstract ( 756 )   PDF (2699KB) ( 208 )  
    The snow water equivalent is an important indicator that can directly reflect the amount of snow waterresources.An accurate and comprehensive acquisition of snow water equivalent data intercepted by the Tianshan spruce canopy is of considerable significance to improve the calculation accuracy of the Tianshan water resources.In this study,experiments were conducted to investigate the snow interception of spruce using simulated snow and the Tianshan spruce saplings.The snow cover area of the spruce was obtained using a camera,and the mass of the spruce canopy interception water was measured using a highprecision balance.Further,the relation between the snow cover area and the snow water equivalent was established.The experimental results show that the fitting curves between the snow water equivalent of the spruce canopy interception water and the spruce snow cover area obtained via vertical downward digital photography tend to be consistent for multiple spruce saplings over several simulated snowfall events; the fitted regression equation is y=21.235x2-1.457x(R2=0.992 5).Using repeated simulations of the spruce snowfall experiment,the snow cover and snow water equivalent of the spruce canopy interception models were obtained. Accordingly, a scientific method has been proposed to estimate the snow water equivalent of the spruce canopy interception based on the snow cover to provide a highprecision estimation model with respect to the intercepted snowfall and snow water equivalent of the Tianshan spruce canopy.
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    Relationship between the grassland and soil conditions in the Eastern Qilian Mountains
    Relationship between the grassland and soil conditions in the Eastern Qilian Mountains
    2020, 37 (2):  374-381.  doi: 10.13866/j.azr.2020.02.12
    Abstract ( 943 )   PDF (932KB) ( 262 )  
    This study explored the relationship between the characteristics of the grassland and soil conditions in the Eastern Qilian Mountains.We selected grass and soil from five areas of the mountain valley:the upper shady slope,lower shady slope,upper sunny slope,lower sunny slope and level terraces.Results showed that each site harbored different dominating species;the sunny slope was dominated by Kobresia sedges and the shady slope was dominated by the Polygonaceae flowering plants.Total vegetation coverage was greatest on the sunny slope weakest on the shady slope;grassland height was tallest on the lower shady slope and shortest on the horizontal terrace;the number of genera and species on the lower shady slopes were higher than those on the upper sunny slopes.The biomass above the ground,from greatest to least,was as follows:bottom shady slope>upper sunny slope>upper shady slope>bottom sunny slope>horizontal terraces.Through an examination of 60 cm deep soil,the underground biomass was found to be:bottom shady slope>bottom sunny slope>upper shady slope>horizontal terraces>upper sunny slope.Both the biomass and soil conditions at each site significantly differed (P<0.05).There were significant correlations and interactions between characteristics of the soil (i.e.,moisture content,bulk density,porosity,and total nitrogen content) and the grassland (i.e.,total vegetation coverage,biomass above the ground,grassland heights,and number of genera and species present).Therefore,these results indicated that aboveground soil characteristics were key factors that affected the quality of the grassland.
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    Effects of nitrogen addition on soil enzyme activities and ecoenzymatic stoichiometry in alpine grassland of the Tianshan Mountains
    LE Jiajia, SU Yuan, PENG Qingwen, GENG Fengzhan, HAN Wenxuan, LI Wenli, LI Kaihui, LIU Xuejun
    2020, 37 (2):  382-389. 
    Abstract ( 681 )   PDF (1064KB) ( 284 )  
    The effects of nitrogen (N) addition on activities of soil carbon (C),N,and phosphorus (P) circulationrelated enzymes were investigated in an alpine grassland ecosystem in 2018.A longterm simulated N addition experiment was initiated at the Bayinbuluk Grassland Ecological Research Station of the Chinese Academy of Sciences in 2009;four N fertilizer treatments were applied at different sites:control (N0,0 kg·hm-2·a-1),low nitrogen (N1,10 kg·hm-2·a-1),moderate nitrogen (N3,30 kg·hm-2·a-1),and high nitrogen (N9,90 kg·hm-2·a-1).In the present study,stoichiometric ratios of soil ecological enzymes and the relationships between soil enzyme activities and environmental factors were analyzed.Our results revealed the following.Compared with N0,N3 treatment significantly increased β-1,4-glucosidase (BG),cellobiohydrolase (CBH) and β-1,4-xylosidase activities (βx) (P<0.05).N1 and N3 treatments obviously increased phenol oxidase (PPO) activity ( P < 0.05).N3 treatment obviously increased β-1,4-Nacetylglucosaminidase (NAG) activity ( P <0.05).No N treatment affected Lleucine aminopeptidase activity (LAP).Correlation analysis showed that activities of all soil enzymes were positively correlated to soil organic C (SOC) content (except NAG) and total phosphorus (TP) content but were not to total nitrogen content.Soil ecoenzymatic C∶N∶P stoichiometry in the study area was 1∶1∶1.2,which is inconsistent with the global 1∶1∶1 pattern.This result suggests that soil microbial growth in the studied grasslands is limited by P content.Canonical redundancy analysis indicated that SOC and TP were the dominant factors affecting soil enzyme activity.
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    Effects of irrigation and fertilization on the stem and leaf growth and ecostoichiometric characteristics of Lycium ruthenicum Murr.
    LI Fakui, LI Jinxia, SUN Xiaomei, CHEN Nianlai
    2020, 37 (2):  452-461.  doi: 10.13866/j.azr.2020.02.21
    Abstract ( 531 )   PDF (1554KB) ( 275 )  
    Lycium ruthenicum Murr.was grown under field conditions in the middle reaches of Shiyang River in China in the presence and absence of irrigation and fertilization,and stem and leaf growth at different stages and ecostoichiometric characteristics of the species were measured.Associations between organ growth rates and ecostoichiometric characteristics were analyzed,and the growth rate hypothesis of the ecostoichiometric theory was tested.Irrigation and fertilization significantly increased stem length,basal diameter,leaf length,leaf width,and leaf dry weight of L.ruthenicum (P<0.05);however,there were no significant differences in stem length,basal diameter,leaf area,and leaf dry weight between treated plants and controls.During the growth period,new L.ruthenicum shoots showed increased C content and C∶N and C∶P ratios and decreased N and P contents and N∶P ratio.Furthermore,stems of treated plants showed lower C content and C∶N,C∶P,and N∶P ratios but higher N and P contents than those of controls.During the growth period,leaves showed decreased C,N,and P contents and increased C∶N,C∶P,and N∶P ratios.Leaves of treated plants showed lower C content and C∶N,C∶P,and N∶P ratios but higher N and P contents than those of controls.Stems showed significantly higher C content and C∶N and C∶P ratios (P <0.05) but significantly lower N and P contents and N∶P ratio (P <0.05) than leaves.The growth rate hypothesis states that the individual growth rate is negatively correlated to N∶P and C∶P ratios and positively correlated to N and P contents in vivo.In the present study,there were no significant correlations of stem and leaf growth rates of L.ruthenicum with N and P contents and C∶P and N∶P ratios,indicating that stem and leaf growth rates and ecostoichiometric characteristics of L.ruthenicum did not support the growth rate hypothesis under irrigation and fertilization.
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    Biomass prediction model for Reaumuria soongorica in the Urat desert steppe in Inner Mongolia
    LI Xiangyun, YUE Ping, CHENG Huan, GUO Xinxin, ZHAO Shenglong, ZHANG Senxi, WANG Shaokun, ZUO Xiaoan
    2020, 37 (2):  462-469.  doi: 10.13866/j.azr.2020.02.19
    Abstract ( 559 )   PDF (925KB) ( 285 )  
    Reaumuria soongorica is a perennial semishrub that is widely distributed in the semidesert regions of China.It is one of the most typical plant species in arid deserts and shows excellent characteristics of soil fixation wind erosion prevention.Estimation of Reaumuria soongorica biomass is important for evaluating its ecological function in the desert steppe and managing desert grasslands.In this context,a predictive model is one of the important methods to estimate R.soongorica biomass.Therefore,the full digging method was used to obtain the biomass of aboveground parts and belowground roots of R.soongorica in Urat desert steppe.Regression analysis with the relevant growth model(power function W=aXb) was applied to construct the predictive models for biomass of the aboveground parts(W1),underground parts(W2),and whole plant(W) based on plant height(H),crown width(C),and base diameter(D).Optimal biomass estimation models were then screened by comparing size of the discriminant coefficient R2.The results showed that (1) the estimation model W1= 0.555×C1.867(R2=0.866) better reflected cumulative characteristics of the aboveground biomass of a single R.soongorica plant;(2) the estimation model W2=2.259×(D2H)0.762(R2=0.769) better reflected cumulative characteristics of the underground biomass of R.soongorica;and (3) the estimation model W=7.057×(D2H)0.813(R2=0.859) better reflected cumulative characteristics of the total biomass of R.soongorica.These biomass models showed high precision and were easy to implement.Our data provide a scientific basis for evaluating the ecological function of R.soongorica in Urat desert steppe and for accurately measuring the biomass of this species.
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    Spatiotemporal evolution and driving factors of landscape ecological vulnerability in Shaanxi Province
    2020, 37 (2):  496-505.  doi: 10.13866/j.azr.2020.02.26
    Abstract ( 448 )   PDF (2098KB) ( 373 )  
    sing the landscape pattern and landscape function to construct a landscape ecological vulnerability model for Shaanxi Province,this work analyzes two dimensions (provincial and internal natural units) of the spatiotemporal evolution of landscape ecological vulnerability.It also explores the multiscale driving mechanism of landscape ecological vulnerability by applying a geographical probe model.The results showed the following:(1) The landscape pattern vulnerability index of Shaanxi Province in 2000 and 2015 was 0.477 3 and 0.409 7,respectively,suggesting a decrease of 6.76%.The spatial difference in landscape pattern vulnerability shows that high values are distributed in the north,whereas low values are distributed on both sides of the central area.The landscape function vulnerability index in 2000 and 2015 was 0.492 6 and 0.417 4,respectively,suggesting a decrease of 7.52%.The spatial difference in landscape functional vulnerability is concentrated in the scattered spatial layout of lowvalue areas in the north and the central region.(2) In 2000 and 2015,the landscape ecological vulnerability index of Shaanxi Province was 0.427 5 and 0.369 7,respectively,suggesting a decrease of 5.78%.The spatial difference in vulnerability is significant,and the overall distribution pattern from south to north shows a high-low zonal staggered distribution pattern,with an obvious transition between internal partitions.The vulnerabilities of the Loess Plateau,Guanzhong Basin,and the Qinba Mountains were reduced by 8.55%,3.81%,and 1.20%,respectively.(3) The influencing factors of the whole province and internal divisions vary with the geographical scale.Natural environmental factors play a vital role in the change in vulnerability,while the role of socioeconomic factors are continuously increasing.The landscape ecological vulnerability assessment method proposed in this paper can provide a reference for the ecological vulnerability assessment.The research conclusion can provide a decisionmaking basis for regional sustainable development.
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    Study on the determinants of agricultural watersaving technologies: A case in Zhangbei County,Hebei Province,China
    2020, 37 (2):  523-531.  doi: 10.13866/j.azr.2020.02.29
    Abstract ( 605 )   PDF (1283KB) ( 281 )  
    In relation to drought and water shortage in North China,watersaving irrigation is considered an effective measure for reducing the use of agricultural water.Over the recent years,the Chinese government has increased its investment in agricultural watersaving technologies in this region.However,owing to a lack of understanding of the determinants relating to their adoption,the use of watersaving technologies has been significantly constrained.Based on survey data from Zhangbei County,Hebei Province,this paper studies these determinants,including the characteristics of lands and peasants,and social factors,of different irrigation modes using multiplelogit and decisiontree models.In terms of the influencing factors relating to farmers’ choices of irrigation method in arid areas,the results estimated using the multiplelogit and decisiontree models are highly consistent.Both models indicate that government support is a key factor in terms of farmers choosing modern communitybased watersaving technologies;this is followed by block area and scale of household irrigation.In addition,farmers’ age and education level,soil type,and the choice of irrigation methods also have important influences,whereas the water supply and demand conditions perceived by farmers are insignificant.In terms of the factors influencing the degree by which farmers adopt modern communitybased watersaving technologies in arid areas,the following observation were noted:(1) when the soil type is loam,the proportion of modern communitybased irrigation technologies is significantly lower than that when the soil is sandy;(2) for farmers,the older they are and the lower their level of education is,the more they adopt modern communitybased irrigation technologies;(3) the higher the total household income of farmers are,the more are modern communitybased irrigation technologies utilized by them.The scale of irrigated land for farming households,whether they have been supported by the government,and the water supply and demand conditions perceived by farmers do not significantly affect the level of this type of technology adoption.To address the existing problems in the use of agricultural irrigation water and improve the efficiency of irrigation water use,the following suggestions have been provided:(1) increase funding for watersaving irrigation technology,(2) advocate for largescale agricultural production,and (3) increase farmer awareness regarding the importance of water saving.
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