Changes of soil particle size fraction along a chronosequence in sandy desertified land: a fundamental process for ecosystem succession and ecological restoration

Zhang, Jiyi; Gu, P. F.; Li, L. Y.; Liang-gang, Zong; Zhao, Weijun

doi:10.1007/s11368-016-1454-x

Cited by 16 publications

(6 citation statements)

References 8 publications

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“…Nevertheless, the change of NPP would also influence the sand and clay content of soil (Zhang, Gu, Li, Zong, & Zhao, 2016; Zhu, Yang, Cao, Liu, & Yang, 2007), thereby affecting the water holding capacity of soil; hence, the quantified relationship between NPP and soil sand and clay were modelled using a regression model (Equations and ) derived from a previous study (Xu et al, 2016):

{sand}_{t} (() %) = ({, \begin{array}{l} 0 {sand}_{t} (() %) < 0 \\ - 0.0287 \times {NPP}_{t - 1} + 52.31 0 \leq {sand}_{t} (() %) \leq 100 \\ 100 {sand}_{t} (() %) > 100 \end{array})

{clay}_{t} (() %) = ({, \begin{array}{l} 0 {clay}_{t} (() %) < 0 \\ 0.0176 \times {NPP}_{t - 1} + 13.105 0 \leq {clay}_{t} (() %) \leq 100 \\ 100 {clay}_{t} (() %) > 100 \end{array})

where sand t is the soil sand content in year t (%); clay t is the soil clay content in year t (%); and NPP t − 1 is the NPP in year t − 1 (gC km −2 yr −1 ).…”

Section: Methodsmentioning

confidence: 99%

“…Nevertheless, the change of NPP would also influence the sand and clay content of soil (Zhang, Gu, Li, Zong, & Zhao, 2016;Zhu, Yang, Cao, Liu, & Yang, 2007), thereby affecting the water holding capacity of soil; hence, the quantified relationship between NPP and soil sand and clay were modelled using a regression model (Equations 6 and 7)…”

Section: Desertification Simulationmentioning

confidence: 99%

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Multi‐scenario simulation of desertification in North China for 2030

Zhang

2020

Land Degrad Dev

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Since desertification threatens the global environment and the security of societies, predicting its patterns and trends across space and time would inform policy‐making strategies for desertification control and sustainable development. China is among the countries most severely affected by desertification, representing 17.93% of its total land area. To better understand the future dynamics of desertification in China, a spatial system dynamics model that coupled natural and human factors was developed to simulate the desertification process in North China in 2030 under nine scenarios. The results showed the model had good applicability and satisfactory accuracy for desertification simulation at the national scale, for which temperature and rainfall were the most sensitive factors driving the process. Current ecological projects and policies were found to be effective for desertification control, which would lead to reversal of desertification in 2030 when coupled with average predicted climate conditions; further, this reversal trend would be accelerated under a humid climate scenario. Although positive ecological policies would promote the reversal of desertification, only a 5% increase of rehabilitated area was obtained when it was coupled with an arid climatic conditions. The latter (aridity) and a passive ecological protection policy would together accelerate desertification expansion, especially in the Yili Basin, in the Houshan region of Inner Mongolia and the Yinchuan Plain. Thus, the ecological projects and policies should be carried on in the long‐term to achieve sustainable control and help prevent desertification.

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{sand}_{t} (() %) = ({, \begin{array}{l} 0 {sand}_{t} (() %) < 0 \\ - 0.0287 \times {NPP}_{t - 1} + 52.31 0 \leq {sand}_{t} (() %) \leq 100 \\ 100 {sand}_{t} (() %) > 100 \end{array})

{clay}_{t} (() %) = ({, \begin{array}{l} 0 {clay}_{t} (() %) < 0 \\ 0.0176 \times {NPP}_{t - 1} + 13.105 0 \leq {clay}_{t} (() %) \leq 100 \\ 100 {clay}_{t} (() %) > 100 \end{array})

where sand t is the soil sand content in year t (%); clay t is the soil clay content in year t (%); and NPP t − 1 is the NPP in year t − 1 (gC km −2 yr −1 ).…”

Section: Methodsmentioning

confidence: 99%

“…Nevertheless, the change of NPP would also influence the sand and clay content of soil (Zhang, Gu, Li, Zong, & Zhao, 2016;Zhu, Yang, Cao, Liu, & Yang, 2007), thereby affecting the water holding capacity of soil; hence, the quantified relationship between NPP and soil sand and clay were modelled using a regression model (Equations 6 and 7)…”

Section: Desertification Simulationmentioning

confidence: 99%

Multi‐scenario simulation of desertification in North China for 2030

Zhang

2020

Land Degrad Dev

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“…grassland plot (NM); Plot B, post-non-grazing restoration plot (NGR); Plots C and D, post-light-grazing restoration plot (LGR) and post-heavy-grazing restoration plot (HGR). NM, NGR, LGR and HGR were long-term observation fields, and many studies have been carried out (Su et al, 2006;Zhao et al, 2009;Zhang et al, 2016). The NM Plot has been monitored since 2005 and has an area of 0.60 ha (200 × 30 m).…”

Section: Introductionmentioning

confidence: 99%

Long-term effects of restoration on the links between above-and belowground biodiversity in degraded Horqin sandy grassland, Northern China

Huang

Wang

et al. 2023

Front. Environ. Sci.

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Long-term ecological restoration plays an important role in the sustainable development of degraded grassland ecosystem. In this study, the levels of species diversity, genetic diversity and soil microbial diversity in restored grassland were measured by vegetation survey, DNA barcoding and soil microbial high-throughput sequencing technology, so as to explore the relationship between above- and belowground biodiversity and its driving factors in Horqin sandy grassland. In this study, the results found that herb are dominated in restoration grassland types. Plant species richness (SR) from post-non-grazing restoration plot (NGR) communities was significantly higher than other restoration communities (10 ± 1.1, p = 0.004). Genetic diversity indices of dominant plant species in chloroplast DNA (cpDNA), were remarkable greater than nuclear DNA (nrDNA) in each recovering sandy grassland plots (amplitude of difference was 44.8%–70.5% in allelic richness (AR), 81.9%–128.1% in expected heterozygosity (HE)). The soil bacterial and fungal richness from natural mobile dune grassland (NM) communities was notably lower than that from recovering grassland types (1641.9 ± 100.4, p < 0.001; 533 ± 16.6, p < 0.001). In this study, heterogeneous levels of genetic variability among different recovering sandy grassland types were detected. Correlation analyses revealed that there were positive correlations between species diversity and genetic diversity (SR & AR: r = 0.56, R2 = 0.31, p < 0.001; SR & HE: r = 0.33, R2 = 0.11, p = 0.045) and a negative correlation between soil microbial diversity and genetic diversity (r = -0.44, R2 = 0.19, p = 0.005). The final structural equation model explained 38% of the variance in SR, 57% in AR, 52% in soil microbial diversity (SD), 49% in aboveground biomass (AGB), 87% in soil organic carbon (SOC), 47% in soil alkali-hydrolyzable nitrogen (SAN) and 69% in soil available phosphorus (SOP). Long-term ecological restoration had significant direct positive effects on AGB, SOC, SAN, SOP, AR, SR and SD. There was a negative correlation between above- and belowground biodiversity and biological and abiotic factors. The results of this study have clarified the above- and underground biodiversity levels of sandy grassland and the relationship with driving factors under long-term ecological restoration measures, and will provide effective support for the management and sustainable development of sandy grassland.

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“…Desertification results in serious soil erosion, low vegetation coverage and sparse ground surface soil, and a continuous reduction in soil nutrients and moisture, resulting in barren sandy land and frequent sandstorms [ 46 , 91 ]. These changes have strongly affected the ecological processes and functions of the sandy land ecosystem [ 77 , 105 , 111 ]. Thus, desertification control has captured great attention from all over the world.…”

Section: Introductionmentioning

confidence: 99%

High-Throughput Absolute Quantification Sequencing Reveals that a Combination of Leguminous Shrubs Is Effective in Driving Soil Bacterial Diversity During the Process of Desertification Reversal

et al. 2022

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Desertification leads to the extreme fragility of ecosystems and seriously threatens ecosystem functioning in desert areas. The planting of xerophytes, especially leguminous shrubs, is an effective and common means to reverse desertification. Soil microorganisms play a crucial role in nutrient cycling and energy flow in ecosystems. However, the effects of introducing leguminous shrubs on soil microbial diversity and the relevant mechanisms are not clear. Here, we employed the high-throughput absolute quantification 16S rRNA sequencing method to analyze the diversity of soil bacteria in sand-fixing areas of mixed shrublands with three combinations of shrubs, i.e., C. korshinskii × Corethrodendron scoparium (CaKCoS), C. korshinskii × Calligonum mongolicum (CaKCaM), and C. scoparium × C. mongolicum (CoSCaM), in the south of the Mu Us Sandy Land, China. This area suffered from moving dunes 20 years ago, but after introducing these shrubs to fix the dunes, the ecosystem was restored. Additionally, the effects of soil physicochemical properties on soil bacterial composition and diversity were analyzed with redundancy analysis (RDA) and structural equation modeling (SEM). It was found that the Shannon index of soil bacteria in CaKCoS was significantly higher than that in CaKCaM and CoSCaM, and the abundance of the dominant phyla, including Actinobacteria, Proteobacteria, Acidobacteria, Chloroflexi, Planctomycetes, Thaumarchaeota, Armatimonadetes, candidate_division_WPS-1, and Nitrospirae, increased significantly in CaKCoS and CaKCaM compared to that in CoSCaM. RDA showed that the majority of soil properties, such as total nitrogen (TN), available potassium (AK), N:P ratio, soil moisture (SM), and available phosphorus (AP), were important soil environmental factors affecting the abundance of the dominant phyla, and RDA1 and RDA2 accounted for 56.66% and 2.35% of the total variation, respectively. SEM showed that the soil bacterial α-diversity was positively affected by the soil organic carbon (SOC), N:P ratio, and total phosphorus (TP). Moreover, CaKCoS had higher SM, total carbon (TC), total potassium (TK), and AP than CaKCaM and CoSCaM. Collectively, these results highlight a conceptual framework in which the combination of leguminous shrubs can effectively drive soil bacterial diversity by improving soil physicochemical properties and maintaining ecosystem functioning during desertification reversal. Graphical Abstract

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Changes of soil particle size fraction along a chronosequence in sandy desertified land: a fundamental process for ecosystem succession and ecological restoration

Cited by 16 publications

References 8 publications

Multi‐scenario simulation of desertification in North China for 2030

Multi‐scenario simulation of desertification in North China for 2030

Long-term effects of restoration on the links between above-and belowground biodiversity in degraded Horqin sandy grassland, Northern China

High-Throughput Absolute Quantification Sequencing Reveals that a Combination of Leguminous Shrubs Is Effective in Driving Soil Bacterial Diversity During the Process of Desertification Reversal

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