Detecting soil salinity with arid fraction integrated index and salinity index in feature space using Landsat TM imagery

Modeling soil salinity in an arid salt-affected ecosystem is a difficult task when using remote sensing data because of the complicated soil context （vegetation cover, moisture, surface roughness, and organic matter） and the weak spectral features of salinized soil. Therefore, an index such as the salinity index （SI） that only uses soil spectra may not detect soil salinity effectively and quantitatively. The use of vegetation reflectance as an indirect indicator can avoid limitations associated with the direct use of soil reflectance. The normalized difference vegetation index （NDVI）, as the most common vegetation index, was found to be responsive to salinity but may not be available for retrieving sparse vegetation due to its sensitivity to background soil in arid areas. Therefore, the arid fraction integrated index （AFⅡ） was created as supported by the spectral mixture analysis （SMA）, which is more appropriate for analyzing variations in vegetation cover （particularly halophytes） than NDVI in the study area. Using soil and vegetation separately for detecting salinity perhaps is not feasible. Then, we developed a new and operational model, the soil salinity detecting model （SDM） that combines AFⅡ and SI to quantitatively estimate the salt content in the surface soil. SDMs, including SDM1 and SDM2, were constructed through analyzing the spatial characteristics of soils with different salinization degree by integrating AFⅡ and SI using a scatterplot. The SDMs were then compared to the combined spectral response index （COSRI） from field measurements with respect to the soil salt content. The results indicate that the SDM values are highly correlated with soil salinity, in contrast to the performance of COSRI. Strong exponential relationships were observed between soil salinity and SDMs （R2〉0.86, RMSE〈6.86） compared to COSRI （R2=0.71, RMSE=16.21）. These results suggest that the feature space related to biophysical properties combined with AFII and SI can effectively provide information on soil salinity.

A spatial-explicit dynamic vegetation model that couples carbon,water,and nitrogen processes for arid and semiarid ecosystems

Arid and semiarid ecosystems, or dryland, are important to global biogeochemical cycles. Dryland＇s community structure and vegetation dynamics as well as biogeochemical cycles are sensitive to changes in climate and atmospheric composition. Vegetation dynamic models has been applied in global change studies, but the com- plex interactions among the carbon （C）, water, and nitrogen （N） cycles have not been adequately addressed in the current models. In this study, a process-based vegetation dynamic model was developed to study the responses of dryland ecosystems to environmental changes, emphasizing on the interactions among the C, water, and N proc- esses. To address the interactions between the C and water processes, it not only considers the effects of annual precipitation on vegetation distribution and soil moisture on organic matter （SOM） decomposition, but also explicitly models root competition for water and the water compensation processes. To address the interactions between C and N processes, it models the soil inorganic mater processes, such as N mineralization/immobilization, denitrifica- tion/nitrification, and N leaching, as well as the root competition for soil N. The model was parameterized for major plant functional types and evaluated against field observations.

Modeling grassland net primary productivity and water-use efficiency along an elevational gradient of the Northern Tianshan Mountains

Mountainous ecosystems are considered highly sensitive and vulnerable to natural disasters and cli- rnatic changes. Therefore, quantifying the effects of elevation on grassland productivity to understand ecosys- tem-climate interactions is vital for mountainous ecosystems. Water-use efficiency （WUE） provides a useful index for understanding the metabolism of terrestrial ecosystems as well as for evaluating the degradation of grasslands. This paper explored net primary productivity （NPP） and WUE in grasslands along an elevational gradient ranging from 400 to 3,400 m asl in the northern Tianshan Mountains-southern Junggar Basin （TMJB）, Xinjiang of China, using the Biome-BGC model. The results showed that： 1 ） the NPP increased by 0.05 g C/（m2-a） with every increase of 1-m elevation, reached the maximum at the mid-high elevation （1,600 m asl）, and then decreased by 0.06 g C/（m2.a） per 1-m increase in elevation; 2） the grassland NPP was positively correlated with temperature in alpine meadow （AM, 2,700-3,500 m asl）, mid-mountain forest meadow （MMFM, 1,650-2,700 m asl） and low-mountain dry grassland （LMDG, 650-1,650 m asl）, while positive correlations were found between NPP and annual precipitation in plain desert grassland （PDG, lower than 650 m asl）; 3） an increase （from 0.08 to 1.09 g C/（m2.a）） in mean NPP for the grassland in TMJB under a real climate change scenario was observed from 1959 to 2009; and 4） remarkable differences in WUE were found among different elevations, in general, WUE increased with decreasing elevation, because water availability is lower at lower elevations; however, at elevations lower than 540 m asl, we did observe a decreasing trend of WUE with decreasing elevation, which may be due to the sharp changes in canopy cover over this gradient. Our research suggests that the NPP simulated by Biome-BGC is consistent with field data, and the modeling provides an opportunity to further evaluate interactions between environmental factors and ecosystem productivity.

Can soil respiration estimate neglect the contribution of abiotic exchange?

This study examines the hypothesis that soil respiration can always be interpreted purely in terms of biotic processes, neglecting the contribution of abiotic exchange to COg fluxes in alkaline soils of arid areas that characterize 5% of the Earth＇s total land surface. Analyses on flux data collected from previous studies suggested reconciling soil respiration as organic （root/microbial respiration） and inorganic （abiotic CO2 exchange） respiration, whose contributions in the total CO2 flux were determined by soil alkaline content. On the basis of utilizing mete- orological and soil data collected from the Xinjiang and Central Asia Scientific Data Sharing Platform, an incorpo- rated model indicated that inorganic respiration represents almost half of the total CO2 flux. Neglecting the abiotic module may result in overestimates of soil respiration in arid alkaline lands, which partly explains the long-sought ＂missing carbon sink＂.

The relationship between soil,climate and forest development in the mid-mountain zone of the Sangong River watershed in the northern Tianshan Mountains,China

The mountainous forests in arid regions, being sensitive to climate change, are one of the key research topics related to the mechanism of interaction between climate and the terrestrial ecosystem. In this study, the spatial distribution of a mid-mountain forest and its environmental factors were investigated by using a combination of remote sensing technology, field survey, climate indices and soil nutrient analysis in the Sangong River watershed of the northern Tianshan Mountains. The forest （Picea schrenkiana） was distributed between 1,510 and 2,720 m asl. Tree height and diameter at breast height （DBH） exhibited a bi-modal pattern with increasing elevation, and rested at 2,450 and 2,250 m asl, respectively. The two maxima of DBH appeared at 2,000 and 2,550 m asl, and the taller trees were observed at 2,100 and 2,600 m asl. For the annual mean temperature, the difference was approximately 5.8℃ between the lowest and the highest limits of the forest, and the average decreasing rates per hundred meters were 0.4g℃ and 0.55℃ with increasing altitude between 1,500 and 2,000 m asl and above 2,000 m asl, respec- tively. The annual precipitation in the forest zone first increased and then decreased with the increase of altitude, and the maximum value was at 2,000 m asl. For per hundred meters, the annual precipitation increased with the rate of 31 mm between 1,500 and 2,000 m asl and decreased by 7.8 mm above 2,000 m asl. The SOM, TN and TP were high between 2,000 and 2,700 m asl and low at the lower and upper forest limits. The minimum CaCO3 con- centration, pH value and EC coincided with the maximum precipitation belt at 2,000 m asl. The SOM, TN and TP were high in the topsoil （0-10 cm） and differed significantly from the values observed in the deep soil layers （〉10 cm）. The soil nutrients exhibited spatial heterogeneity and higher aggregation in the topsoil. In conclusion, soil and climate are closely related to each other, working synergistically to determine the development and spatial distribution of the mid-mountain forest in the study area. The order of the importance of environmental factors to forest development in this study is as follows： soil nutrients〉precipitation〉elevation〉temperature.

Modeling the contribution of abiotic exchange to CO_2 flux in alkaline soils of arid areas

Recent studies on alkaline soils of arid areas suggest a possible contribution of abiotic exchange to soil CO2 flux(Fc).However,both the overall contribution of abiotic CO2 exchange and its drivers remain unknown.Here we analyzed the environmental variables suggested as possible drivers by previous studies and constructed a function of these variables to model the contribution of abiotic exchange to Fc in alkaline soils of arid areas.An automated flux system was employed to measure Fc in the Manas River Basin of Xinjiang Uygur autonomous region,China.Soil pH,soil temperature at 0–5 cm(Ts),soil volumetric water content at 0–5 cm(θs)and air temperature at10 cm above the soil surface(Tas)were simultaneously analyzed.Results highlight reduced sensitivity of Fc to Ts and good prediction of Fc by the model Fc=R10Q10(Tas–10)/10+r7q7(pH–7)+λTas+μθs+e which represents Fc as a sum of biotic and abiotic components.This presents an approximate method to quantify the contribution of soil abiotic CO2 exchange to Fc in alkaline soils of arid areas.

Persistence of four dominant psammophyte species in central Inner Mongolia of China under continual drought

Clarifying the persistence time of seedlings of dominant species under continual drought will help us understand responses of ecosystems to global climate change and improve revegetation efforts. Drought tolerance of four dominant psammophytic shrub species occurring in different environments was studied in the semi-arid areas of Inner Mongolian grasslands. Seedlings of Hedysarum laeve, Caragana korshinskii, Artemisia sphaerocephala and Artemisia ordosica were grown under four air temperature regimes （night/day： 12.5/22.5℃, 15/25℃, 17.5/27.5℃ and 20/30℃） within climate （air temperature and humidity） controlled, naturally lit glasshouses with a night/day relative humidity of 70%/50%. Pots were watered to field capacity for each temperature treatment. Soil water condition was monitored by weighting each pot every day using an electronic balance. Date of seedling death for each treatment was recorded and the dead plants were harvested. Plant dry weights were determined after oven drying at 80℃ for 3 days. Two Artemisia species had higher growth rates than H. laeve and C. korshinskii, and the growth of all four species increased with increasing temperatures. The two Artemisia species had the highest leaf biomass increment, followed by C. korshinskii, and then H. laeve. Shoot biomass increment was higher for A. ordosica and C. korshinskii, intermediate for A. sphaerocephala and lowest for H. laeve. C. korshinskii had the highest root biomass increment. The final soil water content at death for all four species varied from 1% to 2%. C. korshinskii, A. sphaerocephala, H. laeve and A. ordosica survived for 25-43, 24-41, 26-41 and 24-37 days without watering, respectively. C. korshinskii, A. sphaerocephala, H. Laeve, and A. ordosica seedlings survived longer at the lowest temperatures （12.5/22.5℃） than at the highest temperatures （20/30℃） by 18, 17, 15 and 13 days, respectively. Increased climatic temperatures induce the death of seedlings in years with long intervals between rainfall events. The adaptation of seedlings to droughts should be emphasized in revegetation efforts in the Ordos Plateau, Inner Mongolia.

水管理对干旱区盐渍化与土地退化中和的影响

通过优化灌溉和水资源管理以减少耕地土壤盐渍化对实现土地退化中和至关重要.各种灌溉和水资源管理措施对流域尺度盐渍化的缓解作用的有效性和可持续性尚不明确.本研究利用遥感技术估算了1984-2021年干旱区耕地的表层土壤盐度.然后,利用贝叶斯网络分析比较了十个大型干旱区流域(尼罗河、底格里斯-幼发拉底河、印度河、塔里木河、阿姆河、伊犁河、锡尔河、准格尔盆地、科罗拉多河和圣华金河流域)的土壤表层盐度对水资源管理(如各种灌溉和排水方式)的时空响应.在开发水平较高的流域,管理者采用滴灌和地下水灌溉,通过降低地下水水位有效地控制了土壤盐度.对于仍采用传统漫灌的流域,经济发展和政策支持对于建立“改善灌溉系统——降低盐度——增加农业收入”的良性循环至关重要.这也是实现土地退化中和目标的关键.