|Restoration of cropland (termed 'Farm') after abandonment including shrubs (termed 'Shrub'), trees (termed 'Tree') and natural grassland (termed 'Grass') has become a routine process aimed to improve land productivity and control desertification. During this restoration process, soil macro-faunal diversity, and trophic structure were investigated at four types of sites (Farm, Shrub, Tree, and Grass) during growing season in the semi-arid agro-pasture zone of northern China. Results indicated that the Staphylinidae family was found to dominate at the Grass, Shrub, and Tree sites, whiles larval Pyralidae individuals were found at the Grass site only. The density of the omnivores (i.e., Formicidae family) was significantly (P<0.05) greater at the Grass site than at the Tree and Farm sites. The total density and richness of predator and phytophages were found to be markedly (P<0.05) greater at the Grass site than at the Farm site. Meanwhile, we found the taxon richness of predators was significantly (P<0.05) higher at the Shrub site than at the Farm and Tree sites. Compared with the Farm and afforested Shrub/Tree sites, the Grass site had greater density, taxon richness, and Shannon index (P<0.05). In conclusion, natural restoration of abandoned croplands toward grassland was an effective strategy relative to artificial afforestation for improvement of soil biological diversity. Moreover, planting shrub is a preferable measure in abandoned croplands for land development in the semi-arid agro-pasture zone of northern China.|
|Soil water content (SWC) is a key factor limiting ecosystem sustainability in arid and semi-arid areas of the Hexi Corridor of China, which is characterized by an ecological environment that is vulnerable to climate change. However, there is a knowledge gap regarding the large-scale spatial distribution of SWC in this region. The specific objectives of this study were to determine the spatial distribution patterns of SWC across the Hexi Corridor and identify the factors responsible for spatial variation of SWC at a regional scale. This study collected and analyzed SWC in the 0–100 cm soil profile from 109 field sampling sites (farmland, grassland and forestland) across the Hexi Corridor in 2017. We selected 17 factors, including land use, topography (latitude, longitude, elevation, slope gradient, and slope aspect), soil properties (soil clay content, soil silt content, soil bulk density, saturated hydraulic conductivity, field capacity, and soil organic carbon content), climate factors (mean annual precipitation, potential evaporation, and aridity index), plant characteristic (vegetation coverage) and planting pattern (irrigation or rain-fed), as possible environmental variables to analyze their effects on SWC. The results showed that SWC was 0.083 (±0.067) g/g in the 0–100 cm soil profile and decreased in the order of farmland, grassland and forestland. The SWC in the upper soil layers (0–20, 20–40 and 40–60 cm) had obvious difference when the mean annual precipitation differed by 200 mm. The SWC decreased from southeast to northwest following the same pattern as precipitation, and had a moderate to strong spatial dependence in a large effective range (75–378 km). The SWC showed a similar distribution and had no significant difference between soil layers in the 0–100 cm soil profile. The principal component analysis showed that the mean annual precipitation, geographical position (longitude and latitude) and soil properties (soil bulk density and soil clay content) were the main factors dominating the variance of environmental variables. A stepwise linear regression equation showed that plant characteristic (vegetation coverage) and soil properties (soil organic carbon content, field capacity and soil clay content) were the optimal factors to predict the variation of SWC. Soil clay content could be better to explain the SWC variation in the deeper soil layers compared with the other factors.|
|Soil salinization is a serious ecological and environmental problem because it adversely affects sustainable development worldwide, especially in arid and semi-arid regions. It is crucial and urgent that advanced technologies are used to efficiently and accurately assess the status of salinization processes. Case studies to determine the relations between particular types of salinization and their spectral reflectances are essential because of the distinctive characteristics of the reflectance spectra of particular salts. During April 2015 we collected surface soil samples (0–10 cm depth) at 64 field sites in the downstream area of Minqin Oasis in Northwest China, an area that is undergoing serious salinization. We developed a linear model for determination of salt content in soil from hyperspectral data as follows. First, we undertook chemical analysis of the soil samples to determine their soluble salt contents. We then measured the reflectance spectra of the soil samples, which we post-processed using a continuum-removed reflectance algorithm to enhance the absorption features and better discriminate subtle differences in spectral features. We applied a normalized difference salinity index to the continuum-removed hyperspectral data to obtain all possible waveband pairs. Correlation of the indices obtained for all of the waveband pairs with the wavebands corresponding to measured soil salinities showed that two wavebands centred at wavelengths of 1358 and 2382 nm had the highest sensitivity to salinity. We then applied the linear regression modelling to the data from half of the soil samples to develop a soil salinity index for the relationships between wavebands and laboratory measured soluble salt content. We used the hyperspectral data from the remaining samples to validate the model. The salt content in soil from Minqin Oasis were well produced by the model. Our results indicate that wavelengths at 1358 and 2382 nm are the optimal wavebands for monitoring the concentrations of chlorine and sulphate compounds, the predominant salts at Minqin Oasis. Our modelling provides a reference for future case studies on the use of hyperspectral data for predictive quantitative estimation of salt content in soils in arid regions. Further research is warranted on the application of this method to remotely sensed hyperspectral data to investigate its potential use for large-scale mapping of the extent and severity of soil salinity.|
|With the aim to investigate if the halophyte Halothamnus iraqensis Botsch. can be suitable for re-vegetation and remediation of salt-affected lands, this study evaluated (1) the effects of photoperiod, thermoperiod, storage period and wings' presence on its seed germination, and (2) the ability of its seeds to have successful germination recovery after salt stress. Germination tests in different photoperiods (12 h light/12 h darkness and total darkness) and thermoperiods (15°C/20°C and 20°C/25°C) were conducted for seeds collected in 2012, 2013, 2014, 2015 and 2016. The seeds collected in 2016 were sown under different salinity levels (0, 100, 200, 400 and 600 mM NaCl) to assess the salinity tolerance during the germination. Wings' presence highly inhibited seed germination of this species in both photoperiods and thermoperiods under all salinity level treatments. In addition, the germination recovery occurred well when seeds were deprived of their wings. The photoperiod of 12 h light/12 h darkness and the thermoperiod of 15°C/20°C were the best conditions for seed germination. Germination percentages of H. iraqensis seeds decreased with the increasing storage duration, especially after three years of the collection. In addition, H. iraqensis seeds were able to germinate under different salinity levels, and their germination percentages decreased with increasing salinity levels. H. iraqensis seeds have the ability to recover their germination after alleviating the salt stress, irrespective of photoperiod, highlighting the halophilous character of this species.|
|Intraspecific trait variation and heritability in different environmental conditions not only suggest a potential for an evolutionary response but also have important ecological consequences at the population, community, and ecosystem levels. However, the contribution of quantitative trait variation within a grassland species to evolutionary responses or ecological consequences is seldom documented. Leymus chinensis is an important dominant species in semi-arid grasslands of China, which has seriously suffered from drought and high temperature stresses in recent decades. In the present study, we measured variation and heritability of 10 quantitative traits, namely the number of tillers, maximum shoot height, number of rhizomes, maximum rhizome length, rhizome mass, aboveground mass, root mass, maximum net photosynthetic rate (Pmax), specific leaf area (SLA), and leaf length to leaf width ratio (LL/LW), for 10 genotypes of L. chinensis under one non-stress (Ck) condition and three environmental stress conditions (i.e., drought (Dr), high temperature (Ht), and both drought and high temperature (DrHt)). Result indicated that (1) the interaction of genotype and environmental condition (G×E) was significant for 6 traits but not significant for the other 4 traits as shown by two-way analysis of variance (ANOVA), suggesting that different selection forces were placed for different traits on the factors dominating phenotypic responses to different environmental conditions. Moreover, these significant G×E effects on traits indicated significantly different phenotypic adaptive responses among L. chinensis genotypes to different environmental conditions. Additionally, individuals could be grouped according to environmental condition rather than genotype as shown by canonical discriminant analysis, indicating that environmental condition played a more important role in affecting phenotypic variation than genotype; (2) by one-way ANOVA, significant differences among L. chinensis genotypes were found in all 10 traits under Ck and Dr conditions, in 8 traits under DrHt condition and only in 4 traits under Ht condition; and (3) all 10 traits showed relatively low or non-measurable broad-sense heritability (H2) under stress conditions. However, the lowest H2 value for most traits did not occur under DrHt condition, which supported the hypothesis of 'unfavorable conditions have unpredictable effects' rather than 'unfavorable conditions decrease heritability'. Results from our experiment might aid to improve predictions on the potential impacts of climate changes on L. chinensis and eventually species conservation and ecosystem restoration.|
Soil organic carbon (SOC) and soil total nitrogen (STN) in arid regions are important components of global C and the N cycles, and their response to climate change will have important implications for both ecosystem processes and global climate feedbacks. Grassland ecosystems of Funyun County in the southern foot of the Altay Mountains are characterized by complex topography, suggesting large variability in the spatial distribution of SOC and STN. However, there has been little investigation of SOC and STN on grasslands in arid regions with a mountain-basin structure. Therefore, we investigated the characteristics of SOC and STN in different grassland types in a mountain-basin system at the southern foot of the Altai Mountains, north of the Junggar Basin in China, and explored their potential influencing factors and relationships with meteorological factors and soil properties. We found that the concentrations and storages of SOC and STN varied significantly with grassland type, and showed a decreasing trend along a decreasing elevation gradient in alpine meadow, mountain meadow, temperate typical steppe, temperate steppe desert, and temperate steppe desert. In addition, the SOC and STN concentrations decreased with depth, except in the temperate desert steppe. According to Pearson's correlation values and redundancy analysis, the mean annual precipitation, soil moisture content and soil available N concentration were significantly positively correlated with the SOC and STN concentrations. In contrast, the mean annual temperature, pH, and soil bulk density were significantly and negatively correlated with the SOC and STN concentrations. The mean annual precipitation and mean annual temperature were the primary factors related to the SOC and STN concentrations. The distributions of the SOC and STN concentrations were highly regulated by the elevation-induced differences in meteorological factors. Mean annual precipitation and mean annual temperature together explained 97.85% and 98.38% of the overall variations in the SOC and STN concentrations, respectively, at soil depth of 0–40 cm, with precipitation making the greatest contribution. Our results provide a basis for estimating and predicting SOC and STN concentrations in grasslands in arid regions with a mountain-basin structure.