Accurate assessment of wetland ecosystem carbon sinks is an estimation of future atmospheric CO2 concentrations, prediction of climate change and its impact on wetland ecosystems. In this study, ...using remote sensing data and 351 wetland sample sites in 2015, a remote sensing multiple linear regression model (RS-MLRM) was constructed to clarify the carbon storage capacity and its changing process from 2000 to 2015 and their controlling factors in arid regions wetlands. The results are as follows: (1) The studied wetlands acted as atmospheric carbon sinks from 2000 to 2015, increasing by 3.88 × 104 tC/a. Moreover, the soil carbon sink (0–40 cm) was approximately twice that of the vegetation carbon sink. (2) Carbon sinks had a clear spatial distribution, with high concentrations in Helan and Pingluo Counties in the central Ningxia Plain. From 2005 to 2015, constructed wetlands significantly increased the carbon sink (P < 0.05) and were the main contributors to carbon sequestration, indicating that positive human intervention enhances the carbon sink effect of wetlands. (3) Human activities, policy factors, soil physical and chemical properties and nutrients were the main factors affecting carbon sink in Ningxia Plain Wetland in arid regions. (4) The results provides a scientific basis for the protection and management of wetland ecosystems in arid areas.
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•We estimate carbon sinks in Ningxia Plain Wetland in arid areas.•We develop an accurate and applicable RS-MLRM for estimating carbon sinks.•Wetland carbon density increased significantly in Ningxia Plain from 2000 to 2015.•Human activity, policy were the main factors affecting carbon sink in arid areas.•These findings related to carbon cycling and environmental controls in arid areas.
Desert steppe soil security issues have been the focus of attention. Therefore, to understand the impact of industrial activities on the soil quality of desert grasslands, this experiment ...investigated the Gaoshawo Industrial Concentration Zone in Yanchi County. Based on the distance and direction from the industrial park, sample plots were established at intervals of 1-2 km. A total of 82 surface soil samples (0-20 cm) representing different pollution sources were collected. The samples were analysed for pH, total nitrogen, total phosphorus, available phosphorus, available potassium, organic matter, copper (Cu), cadmium (Cd), chromium (Cr), lead (Pb), and zinc (Zn). The desert steppe soil quality was analysed based on the integrated fertility index (IFI) and the Nemerow pollution index (PN), followed by the calculation of the comprehensive soil quality index (SQI), which considers the most suitable soil quality indicators through a geostatistical model. The results showed that the IFI was 0.393, indicating that the soil fertility was relatively poor. Excluding the available potassium, the nugget coefficients of the fertility indicators were less than 25% and showed strong spatial autocorrelation. The average values of Cu, Cd, Cr, Pb and Zn were 21.64 ± 3.26, 0.18 ± 0.02, 44.99 ± 21.23, 87.18 ± 25.84, and 86.63 ± 24.98 mg·kg
, respectively; the nugget coefficients of Cr, Pb and Zn were 30.79-47.35%. Pb was the main element causing heavy metal pollution in the study area. Higher PN values were concentrated north of the highway in the study area, resulting in lower soil quality in the northern region and a trend of decreasing soil quality from south to north. The results of this research showed that the average SQI was 0.351 and the soil quality was extremely low. Thus, industrial activities and transportation activities in the Gaoshawo Industrial Zone significantly impact the desert steppe soil quality index.
Spatial models are effective in obtaining local details on grassland biomass, and their accuracy has important practical significance for the stable management of grasses and livestock. To this end, ...the present study utilized measured quadrat data of grass yield across different regions in the main growing season of temperate grasslands in Ningxia of China (August 2020), combined with hydrometeorology, elevation, net primary productivity (NPP), and other auxiliary data over the same period. Accordingly, non-stationary characteristics of the spatial scale, and the effects of influencing factors on grass yield were analyzed using a mixed geographically weighted regression (MGWR) model. The results showed that the model was suitable for correlation analysis. The spatial scale of ratio resident-area index (PRI) was the largest, followed by the digital elevation model, NPP, distance from gully, distance from river, average July rainfall, and daily temperature range; whereas the spatial scales of night light, distance from roads, and relative humidity (RH) were the most limited. All influencing factors maintained positive and negative effects on grass yield, save for the strictly negative effect of RH. The regression results revealed a multiscale differential spatial response regularity of different influencing factors on grass yield. Regression parameters revealed that the results of Ordinary least squares (OLS) (
Adjusted R
2
= 0.642) and geographically weighted regression (GWR) (
Adjusted R
2
= 0.797) models were worse than those of MGWR (
Adjusted R
2
= 0.889) models. Based on the results of the RMSE and radius index, the simulation effect also was MGWR > GWR > OLS models. Ultimately, the MGWR model held the strongest prediction performance (
R
2
= 0.8306). Spatially, the grass yield was high in the south and west, and low in the north and east of the study area. The results of this study provide a new technical support for rapid and accurate estimation of grassland yield to dynamically adjust grazing decision in the semi-arid loess hilly region.
Nitrogen is the most important driving factor in primary production and decomposition in arid and semi-arid ecosystems. The effects of shrub encroachment on nitrogen cycling have been investigated at ...the site scale but seldomly conducted at the landscape scale. Here, we selected 43 shrubland sites distributing across 3000 km
2
area in temperate desert grassland in eastern Yanchi County of Ningxia Hui Autonomous. We investigated the spatial heterogeneity and driving factors of soil total nitrogen (STN) at the landscape scale by using geostatistical analysis and the geographical detector method. Our results showed that the average soil total nitrogen decreased in the order of 0–5 cm (0.21 g kg
−1
) > 5–15 cm (0.19 g kg
−1
) > 15–40 cm (0.18 g kg
−1
). Geostatistical analysis showed that soil total nitrogen exhibited the strong spatial autocorrelation in the 0–5 and 5–15 cm soil layers and the moderate spatial autocorrelation in the 15–40 cm soil layer. Furthermore, the geographic detector method indicated that soil physicochemical properties exhibited the stronger effects than these of topographic and vegetation biomass in determining the spatial distribution of soil total nitrogen. Specifically, soil water content in the 0–20 cm soil layer explained 35% of variation in soil total nitrogen spatial pattern in the 0–5 cm soil layer, while soil organic carbon content in the 15–40 cm soil layer explained 64% and 45% of variation in soil total nitrogen spatial patterns in the 5–15 cm and 15–40 cm soil layers, respectively. It was concluded that soil water content and organic carbon content primarily drove the formation of soil total nitrogen spatial heterogeneity in shrubland at the landscape scale, indicating that anthropogenic shrub encroachment evidently affected soil water content and redistribution in dryland.
It is of great significance to study the effects of desert plants on soil enzyme activities and soil organic carbon (SOC) for maintaining the stability of the desert ecosystem. In this study, we ...studied the responses of soil enzyme activities and SOC fractions (particulate organic carbon (POC) and mineral-associated organic carbon (MAOC)) to five typical desert plant communities (
Convolvulus tragacanthoides, Ephedra rhytidosperma, Stipa breviflora, Stipa tianschanica
var.
gobica
, and
Salsola laricifolia
communities) in the proluvial fan in the eastern foothills of the Helan Mountain in Ningxia Hui Autonomous Region, China. We recorded the plant community information mainly including the plant coverage and herb and shrub species, and obtained the aboveground biomass and plant species diversity through sample surveys in late July 2023. Soil samples were also collected at depths of 0–10 cm (topsoil) and 10–20 cm (subsoil) to determine the soil physicochemical properties and enzyme activities. The results showed that the plant coverage and aboveground biomass of
S. laricifolia
community were significantly higher than those of
C. tragacanthoides, S. breviflora
, and
S. tianschanica
var.
gobica
communities (
P
<0.05). Soil enzyme activities varied among different plant communities. In the topsoil, the enzyme activities of alkaline phosphatase (ALP) and β-1,4-glucosidas (βG) were significantly higher in
E. rhytidosperma
and
S. tianschanica
var.
gobica
communities than in other plant communities (
P
<0.05). The topsoil had higher POC and MAOC contents than the subsoil. Specifically, the content of POC in the topsoil was 18.17%–12.73% higher than that in the subsoil. The structural equation model (SEM) indicated that plant species diversity, soil pH, and soil water content (SWC) were the main factors influencing POC and MAOC. The soil pH inhibited the formation of POC and promoted the formation of MAOC. Conversely, SWC stimulated POC production and hindered MAOC formation. Our study aimed to gain insight into the effects of desert plant communities on soil enzyme activities and SOC fractions, as well as the drivers of SOC fractions in the proluvial fan in the eastern foothills of the Helan Mountain and other desert ecosystems.
China’s desert steppe is the transition zone between the grasslands in central China and the arid desert. Ecological security in this region has long been a subject of debate, both in the local and ...academic communities. Heavy metals and other pollutants are readily released during industrial production, combustion, and transportation, aggravating the vulnerability of the desert steppes. To understand the impact of industrial activiteis on the heavy metal content of dust fall in the desert steppe, a total of 37 dust fall samples were collected over 90 days. An inductively-coupled plasma mass spectrometer (NexION 350X) was used to measure the concentration of heavy metals Cu, Cd, Cr, Pb, Mn, Co, and Zn in the dust. Using comprehensive pollution index and multivariate statistical analysis methods, we explored the characteristics and sources of heavy metal pollution. We also quantitatively assessed the carcinogenic risks of heavy metals resulting from dust reduction with the help of health risk assessment models. The heavy metals’ comprehensive pollution index values in the study area’s dust fall were ranked as follows: Zn > Cd > Pb > Mn > Cu > Co > Cr. Among these, Zn, Cd, and Pb were significant pollution factors in the study area, and were affected by industrial production and transportation. The high pollution index was concentrated in the north of the research industrial park and on both sides of a highway. The seven heavy metals’ total non-carcinogenic risk index (HI) values were ranked as follows: Mn > Co > Pb > Zn > Cr > Cu > Cd (only the HI of Mn was greater than one). Excluding Mn, the non-carcinogenic and carcinogenic risk index values of the other six heavy metals were within acceptable ranges. Previous studies have also shown that industrial transportation and production have had a significant impact on the heavy metal content of dust fall in the desert steppe.
The temperate steppe experienced degradation and desertification as a result of long-term heavy grazing and excessive reclamation. Some major ecological projects, such as the Grain for Green Program ...(GGP) and Grazing Exclosure (GE), have been implemented to promote ecological restoration in grassland ecosystems. With the goal of carbon neutrality, the effects of the GGP and GE on grassland carbon sequestration need to be further explored. Based on soil data from the second soil survey in the 1980s, a field survey in 2021, and the land-use/land-cover datasets of 2000–2018, we characterized the changes in soil C stock following grazing exclosure, analyzed the effect of GGP on land-use changes and soil C accumulation, and then estimated the overall grassland carbon sequestration in Ningxia on the Loess Plateau of China. From 2000 to 2018, GE increased the grassland SOCD from 49.60 Mg ha
−1
to 90.71 Mg ha
−1
, and the C stock increased by 65.55 T g. Under the influence of the GGP, 347.62 km
2
of cultivated land was converted into grasslands, increasing the grassland soil carbon sequestration by 1.31 T g. Subsequently, the grassland organic carbon storage increased by 66.86 T g, which accounted for approximately 4.26% of the grassland organic carbon storage in the Loess Plateau of China. In the southern Loess hilly area, which experienced high precipitation and low temperatures, grasslands increased by 95.55 km
2
; the average organic carbon density increased 46.95 Mg ha
−1
due to a rate of increase of 2.61 Mg ha
−1
yr
−1
; and the corresponding values for those in the middle arid zone were 36.25 Mg ha
−1
and 2.01 Mg ha
−1
yr
−1
, with grasslands decreasing by 147.41 km
2
. The follow-up policies of the GGP and GE should be implemented and improved according to local conditions to improve the carbon sink and ecological services in grassland ecosystems.
Grassland-shrubland state transition causes profound effects on soil nutrients and microorganisms, yet little is known about how these soil characteristics are influenced by rainfall and litter ...changes during transition. Here, we examined water (high or low moisture pulse) and litter (grass or shrub) effects on these soil characteristics in grassland-shrubland mosaics consisting of desert grassland (DG), grassland edge (GE), shrubland edge (SE), and shrubland (SL) sites. The results showed that the transition of DG-GE-SE-SL significantly reduced soil moisture, total carbon (C), total nitrogen (N), total phosphorus (P), microbial biomass carbon, and microbial biomass nitrogen, revealing evident soil degradation during this transition. After applying water and litter, soil microbial respiration (SMR) and the activities of all enzymes were promoted to varying degrees among the sites. Specifically, SMR was promoted under a low moisture pulse but suppressed under a high moisture pulse along the transition from DG to SL. Two C-acquisition enzymes, cellobiohydrolase and β-1,4-glucosidase, became increasingly active from DG to SL. Another C-acquisition enzyme of β-1,4-xylosidase and an N-acquisition enzyme of leucine aminopeptidase showed the strongest preferences for low moisture pulses in SL. These results indicated that shrub encroachment retained certain microbes with an advanced ability to acquire to C and N from dry and infertile soil in SL. Although a P-acquisition enzyme of alkaline phosphatase showed a decreasing trend along the transition from DG to SL, similar like those C- and N- acquisition enzymes, it was not sensitive to varying moisture levels, suggesting that alkaline phosphatase was affected by other soil physicochemical properties rather than soil moisture. The joint analysis of soil extracellular enzymes and nutrients indicated that microbial biomass carbon played a more important role than other soil characteristics in determining soil extracellular enzyme activities along the transition from DG to SL. Future research on dissecting soil microbial communities is warranted to better understand the microbiological mechanisms behind these phenomena in the shrub encroachment process.
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•Soil moisture, nutrients, and microbial biomass declined with state transition.•Soil C- enzymes were more active in shrubland and the low moisture pulse.•Encroachment of shrubs into grassland deceased activities of P-, not N- enzymes.•Litter changes affected activities of C-, N-, and P- enzymes in varying degrees.
Through selecting key factors such as gradient, exposure, erosive channel, soil erosion and vegetation coverage, the paper establishes the factor index system for the evaluation of the ecological ...system of Pengyang County, determines the weight of evaluation factors, makes analysis on key ecological factors, sets up the comprehensive sensitivity evaluation model of the ecological system, and obtains the ecological sensitivity grade, area, and spatial distribution of the study area through GIS spatial analysis function, factor superposition method, and analytic hierarchy process. The findings are as follows: the zone extremely sensitive to the ecology covers 82956.47 hm, accounting for 32.98%. Landforms in the area usually include steep slopes with rich vegetation, and high ecological value, erosive channels, and zones affected by erosive channels, all of which are under the key protection; the zone moderately sensitive to the ecology cover 104613.69 hm, accounting for 41.59%. Landforms in the area usually include forestlands of gentle relief and diversified plants. A good many factors should be taken into consideration in the development of the areas; the zone slightly sensitive to the ecology covers 63965.53 hm, accounting for 25.43%. Landforms in the area are usually of low elevation and flat, mainly ordinary greenbelt with singular vegetation, sections with poor vegetation, and farmlands. The area is resistant to human disturbance and able to go through development and construction of the specific intensity. The lands can be developed for a variety of purposes, but attention should be paid to the development intensity.
A study area was selected from the industrial region of Gaoshawo Town, Yanchi County, Ningxia, to explore the level of heavy metal pollution in desert grasslands due to industrial activities. A total ...of 82 surface soils were collected, and the concentration of heavy metals, namely, Cu, Cd, Cr, Pb, Zn, Mn, and Co, was determined by ICP-AES (atomic emission spectrometer) (HK-8100); the average values were 21.64 ± 3.26, 0.18 ± 0.02, 44.99 ± 21.23, 87.18 ± 25.84, 86.63 ± 24.98, 570.49 ± 171.57, and 17.96 ± 9.96 mg kg
−1
. The single-factor, Nemerow pollution, and potential ecological risk index methods were used to evaluate the status of soil heavy metal pollution and the contribution from the major sources identified by the receptor model. The results showed that 9.09% of the samples were slightly polluted, 32.47% of the samples were moderately polluted, and 58.41% of the samples were heavily polluted. The comprehensive potential ecological risk index indicated that 90.79% of the samples had moderate ecological risk. It was verified from the models and spatial distribution maps that Cr, Co, Zn, and Mn are mainly contributed by the industrial sources that account for 55.04%, 92.13%, 50.05%, and 48.77% of these heavy metals, respectively. The heavily contaminated areas are distributed around the industrial park. A total of 70.63% and 77.83% of Cu and Pb are contributed by transportation sources, respectively, with the concentrations decreasing from southwest to northeast. The contribution from agricultural activities to Cd is 77.02%, with concentrations largely distributed in the north of the highway. This study showed that the existence of the Gaoshawo Industrial Zone and the corresponding industrial and transportation activities have a significant impact on the grassland soil environment.
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