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Journal of Arid Land  2024, Vol. 16 Issue (5): 725-737    DOI: 10.1007/s40333-024-0076-1
Research article     
Effects of desert plant communities on soil enzyme activities and soil organic carbon in the proluvial fan in the eastern foothills of the Helan Mountain in Ningxia, China
SHEN Aihong1, SHI Yun2,*(), MI Wenbao1,2, YUE Shaoli3, SHE Jie2, ZHANG Fenghong4, GUO Rui4, HE Hongyuan4, WU Tao5, LI Hongxia2, ZHAO Na2
1College of Forestry and Prataculture of Ningxia University, Yinchuan 750021, China
2School of Geography and Planning of Ningxia University, Yinchuan 750021, China
3Ningxia Hui Autonomous Region Agricultural Comprehensive Development Center, Yinchuan 750002, China
4Ningxia Helan Mountain National Nature Reserve Administration, Yinchuan 750021, China
5Yinchuan Yinxi Ecological Protection Forest Management Center, Yinchuan 750002, China
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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%-42.73% 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.

Key wordsproluvial fan      desert plant community      soil enzyme activity      particulate organic carbon      mineral-associated organic carbon      Helan Mountain     
Received: 21 January 2024      Published: 31 May 2024
Corresponding Authors: *SHI Yun (E-mail:
Cite this article:

SHEN Aihong, SHI Yun, MI Wenbao, YUE Shaoli, SHE Jie, ZHANG Fenghong, GUO Rui, HE Hongyuan, WU Tao, LI Hongxia, ZHAO Na. Effects of desert plant communities on soil enzyme activities and soil organic carbon in the proluvial fan in the eastern foothills of the Helan Mountain in Ningxia, China. Journal of Arid Land, 2024, 16(5): 725-737.

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Fig. 1 Plant coverage (a), aboveground biomass (b), and Shannon-Wiener index (c) of different plant communities. Epr, Ephedra rhytidosperma; Cot, Convolvulus tragacanthoides; Stb, Stipa breviflora; Stt, Stipa tianschanica var. gobica; Sal, Salsola laricifolia. Lowercase letters indicate that the differences are significant in different plant communities (P<0.05). Bars are standard errors (n=4).
Table 1 Soil physicochemical properties of the topsoil and subsoil in different plant communities
Fig. 2 Soil enzyme activities of ALP (a), βG (b), CBH (c), βX (d), LAP (e), NAG (f), and βD (g) in the topsoil (soil depth of 0-10 cm) and subsoil (soil depth of 10-20 cm) of different plant communities. ALP, alkaline phosphatase; βG, β-1,4-glucosidase; CBH, Cellobiohvdrolase; βX, β-1.4-xylosidase; LAP, leucine aminopeptidase; NAG, β-1.4-N-acetylglucosaminidase; βD, cellulase. Lowercase letters indicate that the differences are significant (P<0.05) in the topsoil; uppercase letters indicate that the differences are significant (P<0.05) in the subsoil. * indicates that the differences are significant (P<0.05) among different soil layers. Bars are standard errors (n=4).
Fig. 3 Contents of POC (a), MAOC (b), and SOC (c) in the topsoil and subsoil of different plant communities. POC, particulate organic carbon; MAOC, mineral-associated organic carbon; SOC, soil organic carbon. Lowercase letters indicate that soil POC, MAOC, and SOC contents differ significantly (P<0.05) in the topsoil; uppercase letters indicate that soil POC, MAOC, and SOC contents differ significantly (P<0.05) in the subsoil. * indicates that the differences are significant (P<0.05) among different soil layers. Bars are standard errors (n=4).
Fig. 4 Partial least squares path model (PLS-PM) results of the effects of plant species diversity, plant coverage, soil pH, soil water content (SWC), and soil C-cycle enzyme activities related to SOC cycling on POC and MAOC under different plant communities. The numbers on the arrows indicate the path coefficients. *, P<0.05; **, P<0.01. Red arrows represent positive correlations, blue arrows represent negative correlations, and the wider arrows represent significant differences (P<0.05). R2 refers to the proportion of variance explained in the assessment of model fit, and the closer it is to 1.00, the more the model explains the variability of the dependent variable, which indicates that the model fit is better. df, degree of freedom.
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