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Journal of Arid Land  2024, Vol. 16 Issue (11): 1541-1561    DOI: 10.1007/s40333-024-0063-6    
Research article     
Benefits and ecological restoration implications of hanging grass fences in Mongolian desert steppe
MIAO Jiamin1,2,3, LI Shengyu1,2,3,*(), XU Xinwen1,2,3, LIU Guojun1,2,3, WANG Haifeng1,2,3, FAN Jinglong1,2,3, Khaulanbek AKHMADI4
1Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
2National Engineering Technology Research Center for Desert-Oasis Ecological Construction, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
3University of Chinese Academy of Sciences, Beijing 100049, China
4Institute of Geography and Geoecology, Mongolian Academy of Sciences, Ulaanbaatar 15170, Mongolia
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Abstract  

Tumbleweeds participate in a common seasonal biological process in temperate grasslands, creating hanging grass fences during the grass-withering season that result in distinct ecological phenomena. In this study, we addressed the urgent need to understand and restore the degraded desert steppe in Central Mongolia, particularly considering the observed vegetation edge effects around hanging grass fences. Using field surveys conducted in 2019 and 2021 in the severely degraded desert steppe of Central Mongolia, we assessed vegetation parameters and soil physical and chemical properties influenced by hanging grass fences and identified the key environmental factors affecting vegetation changes. The results indicate that the edge effects of hanging grass fences led to changes in species distributions, resulting in significant differences in species composition between the desert steppe's interior and edge areas. Vegetation parameters and soil physical and chemical properties exhibited nonlinear responses to the edge effects of hanging grass fences, with changes in vegetation coverage, aboveground biomass, and soil sand content peaking at 26.5, 16.5, and 6.5 m on the leeward side of hanging grass fences, respectively. In the absence of sand dune formation, the accumulation of soil organic carbon and available potassium were identified as crucial factors driving species composition and increasing vegetation coverage. Changes in species composition and plant density were primarily influenced by soil sand content, electrical conductivity, and sand accumulation thickness. These findings suggest that hanging grass fences have the potential to alter vegetation habitats, promote vegetation growth, and control soil erosion in the degraded desert steppe of Central Mongolia. Therefore, in the degraded desert steppe, the restoration potential of hanging grass fences during the enclosure process should be fully considered.



Key wordshanging grass fences      edge effects      vegetation recovery      enclosure treatment      degraded desert steppe      Central Mongolia     
Received: 19 May 2024      Published: 30 November 2024
Corresponding Authors: *LI Shengyu (E-mail: oasis@ms.xjb.ac.cn)
Cite this article:

MIAO Jiamin, LI Shengyu, XU Xinwen, LIU Guojun, WANG Haifeng, FAN Jinglong, Khaulanbek AKHMADI. Benefits and ecological restoration implications of hanging grass fences in Mongolian desert steppe. Journal of Arid Land, 2024, 16(11): 1541-1561.

URL:

http://jal.xjegi.com/10.1007/s40333-024-0063-6     OR     http://jal.xjegi.com/Y2024/V16/I11/1541

Fig. 1 Overview of the study area, climate characteristics, and hanging grass fences. (a), location of the study area (the study area is located in the ecotone of steppe and desert steppe in Central Mongolia); (b), image showing the experimental design; (c), monthly variations in temperature, precipitation, and wind speed during the sampling period (2019-2021); (d), frequency of sand-driving winds at 10 m in height with wind rose directions; (e), photo showing the hanging grass fence during the grass-withering season (April) in 2019; (f), photo showing the tumbleweeds hanging and accumulating on the fence in April 2019. Note that Figure 1a is based on the standard map (GS(2016)1666) of the Map Service System (http://bzdt.ch.mnr.gov.cn/), and the boundary of the base map has not been modified. The enclosure in Figure 1b is shown in a true-colour image downloaded from Google Earth, including enclosure with hanging grass fences (abbreviated as GF) and enclosure with non-hanging grass fences (abbreviated as NF). N, north; NE, northeast; E, east; SE, southeast; S, south; SW, southwest; W, west; NW, northwest. The abbreviations are the same in the following figures.
Fig. 2 Experimental design and sampling locations for vegetation and soil survey. (a), drone images showing example locations of transects and sample plots; (b), photo showing vegetation recovery during the early formation of the hanging grass fences in April 2019; (c), photo showing the regreening of the grassland in August 2019 for the first year of enclosure with hanging grass fences (GF1); (d), photo showing the regreening of the grassland in August 2021 for the third year of enclosure with hanging grass fences (GF3); (e), photo showing the third year of enclosure with non-hanging grass fences (NF3). Positive distances indicate sample plots within the enclosure area on the leeward side of the fences, and negative distances indicate sample plots within the grazing area on the windward side of the fences. The abbreviations are the same in the following figures.
Fig. 3 Responses of species composition to different enclosure treatments (GF1, GF3, and NF3). (a), differences in the importance values of plant species on the windward and leeward sides of fences (the complete data are shown in Tables S1-3); (b), nonmetric multidimensional scaling (NMDS) of species composition, with dispersion ellipses at 95% confidence intervals added. PERMANOVA, permutational multivariate analysis of variance. Ellipse labels represent the 3 enclosure treatments, and the top 20 plant species points in terms of abundance are reflected in the figure. Distance indicates the distance from the sample plots to the fences.
Fig. 4 Comparison of vegetation coverage (a), plant height (b), plant density (c), species richness (d), and aboveground biomass (e) at the interface between the windward and leeward sides of different enclosure treatments. Different lowercase letters indicate significant differences in means (P>0.05). Bars mean standard errors. Positive distances indicate sample plots within the enclosure area on the leeward side of the fences, and negative distances indicate sample plots within the grazing area on the windward side of the fences. Marginal r² refers to the fixed effects only. 'Pdis', 'Pdis2', and 'Ppdis3' represent significance tests for the distance, squared distance, and cubic distance from the fences, respectively. The abbreviations are the same in the following figures.
Fig. 5 Comparison of soil physical and chemical properties at the interface between the windward and leeward sides of fences under different enclosure treatments. (a), pH; (b), electrical conductivity (EC); (c), soil water content (SWC); (d), soil organic carbon (SOC) content; (e), available potassium (AK) content; (f), available phosphorus (AP) content; (g), sand content; (h), silt content; (i), clay content. Positive distances indicate sample plots within the enclosure area on the leeward side of the fence, and negative distances indicate sample plots within the grazing area on the windward side of the fence. Different lowercase letters indicate significant differences in means (P>0.05). Bars mean standard errors. Only model r2 values with P<0.05 are labeled in the figure; full model results are provided in Table S4. 'Psoil depth' indicates the significance of soil depth on soil physical and chemical properties. The abbreviations are the same in the following figures.
Fig. 6 Impacts of different environmental factors on species composition. (a), canonical correspondence analysis (CCA) of species composition at varying distances from the fence under different enclosure treatments; (b), contributions of different groups of environmental factors to species composition calculated by variation partitioning. Arrows represent the nine significant environmental factors selected for forward selection. "Treatment" represents the three different enclosure treatments: GF1, GF3, and NF3. "Thickness" denotes sand accumulation thickness. "Distance-Thickness" represents the interaction between distance from the fence and sand accumulation thickness. Note that factors with contributions to the total variance less than 0.0 are not shown.
Fig. 7 Impacts of different environmental factors on vegetation coverage (a) and plant density (b) based on structural equation modelling (SEM). Boxes represent the environmental factors included in the model. Arrows indicate the paths, with the numbers on the paths representing standardized regression weights (the thicker the lines, the greater the weights). Solid arrows represent significant paths, with red solid arrows indicating positive effects, blue solid arrows indicating negative effects, and grey dashed arrows indicating non-significant paths. The significances along the paths at P<0.05, P<0.01, and P<0.001 levels are indicated by *, **, and ***, respectively. The standardized estimates and significance are displayed within each soil physical and chemical property box. The total explained variance of the environmental factors (R²) is marked near the box. χ2, chi-square; df, degree of freedom; n, sample size; AIC, Akaike information criterion; BIC, Bayesian information criterion; CFI, comparative fit index; RMSEA, root mean square error of approximation; SRMR, standardized root mean square residual.
Species Relative importance value (%)
-16.5 m 1.5 m 6.5 m 11.5 m 16.5 m 21.5 m
Bassia dasyphylla 0.00 0.00 0.00 0.74 0.00 0.00
Eragrostis minor 0.90 3.48 0.00 0.00 0.00 0.00
Chenopodium acuminatum 0.00 0.00 0.00 0.00 0.00 0.00
Salsola collina 0.00 3.14 1.13 0.00 0.00 0.00
Corispermum mongolicum 0.00 1.43 0.97 0.00 0.00 0.00
Artemisia frigida 34.47 29.70 25.27 34.94 38.19 32.57
Convolvulus ammanii 5.00 0.78 0.00 0.00 1.69 0.00
Carex duriuscula 0.00 0.00 0.00 0.00 0.00 1.27
Chenopodium aristatum 0.00 0.00 0.00 0.00 0.00 0.00
Allium mongolicum 3.76 0.00 3.71 3.75 0.00 5.70
Haplophyllum dahuricum 2.95 7.86 6.57 4.05 7.87 7.10
Setaria viridis 0.00 0.00 0.00 0.00 0.00 0.00
Astragalus sp. 0.00 0.00 0.00 0.00 0.00 0.00
Chenopodium album 0.00 2.61 8.06 3.96 0.00 0.00
Stipa krylovii 22.32 19.99 14.85 14.79 19.10 19.74
Alyssum canescens 5.94 15.62 4.49 13.50 13.16 11.33
Cleistogenes squarrosa 0.00 0.00 0.00 0.00 0.00 0.00
Leymus chinensis 0.00 1.86 0.00 0.00 0.00 0.00
Sibbaldianthe adpressa 0.00 0.00 0.00 0.00 0.00 0.00
Tribulus terrestris 0.00 0.00 0.00 0.00 0.00 0.00
Caragana stenophylla 4.55 2.11 0.00 3.39 0.00 2.80
Allium polyrhizum 1.63 0.00 0.00 0.00 0.00 0.00
Artemisia scoparia 0.00 0.00 2.36 0.00 5.70 0.00
Heteropappus hispidus 7.62 2.97 6.72 7.86 8.63 5.69
Caragana microphylla 0.00 0.00 0.00 0.00 0.00 0.00
Asparagus dahurica 0.00 2.00 3.21 0.00 0.00 0.00
Artemisia macrocephala 2.30 0.00 9.81 3.51 0.00 3.15
Oxytropis sp. 0.00 0.00 0.00 0.00 0.00 0.00
Cymbaria dahurica 9.75 0.00 0.00 0.00 0.00 3.50
Potentilla bifurca 0.00 0.00 2.41 7.00 2.72 7.14
Agropyron cristatum 0.00 7.58 7.35 0.00 0.00 0.00
Scorzonera sp. 0.00 0.00 0.00 0.00 0.00 0.00
Carex sp. 0.00 0.00 0.00 0.00 0.00 0.00
Artemisia palustris 0.00 0.00 1.60 0.00 0.00 0.00
Artemisia adamsii 0.00 0.00 1.49 2.51 0.00 0.00
Table S1 Relative importance values of species at different distances from fences in the first year of enclosure with hanging grass fences (GF1)
Species Relative importance value (%)
-16.5 m -11.5 m -6.5 m -1.5 m -0.5 m 0.5 m 1.5 m 6.5 m 11.5 m 16.5 m 21.5 m 26.5 m
Bassia dasyphylla 57.22 47.38 0.00 0.61 0.00 12.87 13.30 0.00 3.95 5.21 3.97 5.78
Eragrostis minor 10.30 8.87 0.36 0.00 0.00 42.85 15.23 10.71 6.93 5.97 0.00 0.00
Chenopodium acuminatum 0.00 0.00 3.80 2.48 0.00 7.33 5.91 1.88 4.45 4.99 1.94 3.56
Salsola collina 0.00 6.75 2.27 0.00 1.77 6.81 5.01 0.00 2.51 2.08 2.90 1.55
Corispermum mongolicum 4.75 6.90 0.00 0.00 0.00 24.81 47.39 11.56 21.05 18.70 1.52 2.39
Artemisia frigida 1.15 0.00 29.14 31.28 25.59 0.00 0.00 19.44 21.60 26.51 31.80 36.13
Convolvulus ammanii 0.00 0.00 5.81 9.78 18.16 0.00 0.00 4.17 3.48 4.85 7.87 5.00
Carex duriuscula 0.00 0.00 7.41 6.51 2.78 0.00 0.00 5.47 3.44 4.60 11.30 8.85
Chenopodium aristatum 0.00 0.00 0.00 0.00 0.00 7.74 7.11 2.42 4.83 0.59 1.58 0.00
Allium mongolicum 0.00 0.00 7.72 4.01 1.49 0.00 0.00 2.17 1.35 1.02 2.40 3.65
Haplophyllum dahuricum 0.00 0.00 6.81 4.16 10.12 0.00 0.00 4.60 2.13 3.69 0.83 0.00
Setaria viridis 0.00 0.00 0.00 0.00 0.00 0.00 2.41 0.00 0.00 3.73 0.00 0.00
Astragalus sp. 0.00 0.00 0.00 3.19 4.83 0.00 0.00 0.77 0.00 0.00 0.00 3.38
Chenopodium album 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.69 0.87 0.00 0.00
Stipa krylovii 0.00 0.00 10.24 3.06 10.89 0.00 0.00 3.24 4.05 6.22 10.74 9.89
Alyssum canescens 0.00 0.00 0.69 2.47 0.00 0.00 0.00 1.17 1.01 0.00 1.66 0.00
Cleistogenes squarrosa 2.15 0.00 2.36 3.78 2.83 0.00 0.00 0.00 0.00 0.48 1.93 0.38
Leymus chinensis 0.00 0.00 3.40 9.43 7.18 0.00 0.00 13.07 15.18 2.74 6.53 8.58
Sibbaldianthe adpressa 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.54 1.39 2.23
Tribulus terrestris 0.00 6.26 0.00 0.00 0.00 1.47 3.64 0.62 0.89 0.00 0.00 0.74
Caragana stenophylla 0.00 0.00 2.10 1.69 2.97 0.00 0.00 1.82 0.00 7.55 0.00 2.02
Allium polyrhizum 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.44 0.99 1.55
Artemisia scoparia 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.81 0.00
Heteropappus hispidus 0.00 0.00 1.24 7.51 5.04 0.00 0.00 8.29 0.00 0.00 1.00 3.55
Caragana microphylla 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.70 0.00
Asparagus dahurica 0.00 0.00 1.46 0.00 0.00 0.00 0.00 0.00 0.00 1.46 0.00 1.39
Artemisia macrocephala 22.81 23.84 7.97 7.60 4.30 0.00 0.00 3.91 0.00 0.00 0.00 0.00
Oxytropis sp. 0.00 0.00 1.05 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Cymbaria dahurica 0.00 0.00 1.29 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Potentilla bifurca 0.00 0.00 5.77 1.41 0.00 0.00 0.00 2.94 2.30 1.03 4.15 0.75
Agropyron cristatum 0.00 0.00 0.00 0.00 1.34 0.00 0.00 0.00 0.00 0.00 4.70 0.00
Scorzonera sp. 0.00 0.00 2.06 1.02 0.00 0.00 0.00 0.89 0.00 0.00 0.00 0.92
Carex sp. 0.00 0.00 0.00 0.00 0.72 0.00 0.00 0.85 0.00 0.00 0.00 0.00
Artemisia palustris 0.00 0.00 3.17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Artemisia adamsii 1.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Table S2 Relative importance values of species at different distances from fences in the third year of enclosure with hanging grass fences (GF3)
Species Relative importance value (%)
-16.5 m -11.5 m -6.5 m -1.5 m -0.5 m 0.5 m 1.5 m 6.5 m 11.5 m 16.5 m 21.5 m 26.5 m
Bassia dasyphylla 3.47 0.00 0.00 0.00 0.00 40.88 17.53 6.66 0.00 8.25 0.00 0.00
Eragrostis minor 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Chenopodium acuminatum 2.76 0.00 0.00 0.00 0.00 0.00 1.96 0.00 0.00 2.21 0.00 0.00
Salsola collina 2.99 0.00 0.00 1.69 1.70 2.96 5.80 9.26 0.00 1.09 1.40 0.00
Corispermum mongolicum 2.02 0.00 0.00 0.00 0.00 10.97 3.99 0.00 0.00 0.00 0.00 0.00
Artemisia frigida 18.03 30.11 25.68 25.11 36.72 4.37 22.05 20.85 23.27 40.23 36.99 22.71
Convolvulus ammanii 0.00 0.00 7.63 5.24 0.00 0.00 0.00 0.00 0.00 0.00 10.79 14.09
Carex duriuscula 0.00 0.00 5.22 6.09 0.00 0.00 0.00 1.24 1.53 1.94 0.00 2.20
Chenopodium aristatum 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Allium mongolicum 1.78 3.53 4.54 0.00 2.42 0.00 0.00 0.00 1.92 11.66 3.99 2.11
Haplophyllum dahuricum 9.69 6.98 11.60 13.18 7.53 10.46 10.01 1.73 10.28 3.18 0.00 9.49
Setaria viridis 0.00 0.00 0.00 0.00 0.00 1.74 0.00 0.00 0.00 0.00 0.00 0.00
Astragalus sp. 0.00 0.00 0.00 0.00 0.00 0.00 2.22 2.38 0.91 0.00 0.00 2.34
Chenopodium album 0.00 0.00 0.00 0.00 0.00 1.37 1.69 0.00 0.00 0.00 0.00 0.00
Stipa krylovii 7.40 19.59 12.17 6.26 9.81 7.10 8.96 12.42 11.10 2.01 12.75 11.69
Alyssum canescens 1.52 6.05 2.46 3.04 5.97 0.84 0.00 0.00 1.33 0.00 0.00 0.00
Cleistogenes squarrosa 7.07 8.21 16.19 11.00 5.68 0.00 0.00 9.10 16.70 4.02 8.61 15.09
Leymus chinensis 0.00 0.00 0.00 0.00 5.81 0.00 0.00 0.00 0.00 0.00 1.78 0.00
Sibbaldianthe adpressa 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Tribulus terrestris 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Caragana stenophylla 3.07 4.28 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Allium polyrhizum 0.00 0.00 0.00 2.52 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.27
Artemisia scoparia 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Heteropappus hispidus 7.06 4.55 3.75 11.05 11.66 2.14 3.69 0.00 9.65 8.89 5.51 7.39
Caragana microphylla 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Asparagus dahurica 0.00 2.86 3.69 0.00 5.17 0.00 0.00 0.00 0.00 5.21 0.00 0.00
Artemisia macrocephala 2.92 0.00 0.00 0.00 0.00 2.38 0.00 0.00 0.00 0.00 0.00 0.00
Oxytropis sp. 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Cymbaria dahurica 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.50
Potentilla bifurca 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 8.62 11.91 0.00
Agropyron cristatum 5.45 1.68 2.33 6.58 1.91 4.43 14.73 2.51 6.79 2.69 3.00 0.00
Scorzonera sp. 1.87 3.24 4.72 8.24 5.64 0.00 0.00 0.00 8.71 0.00 3.27 4.11
Carex sp. 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Artemisia palustris 6.02 0.00 0.00 0.00 0.00 0.00 10.29 22.63 0.00 0.00 0.00 0.00
Artemisia adamsii 16.89 8.95 0.00 0.00 0.00 10.37 1.55 11.21 7.82 0.00 0.00 0.00
Table S3 Relative importance values of species at different distances from fences in the third year of enclosure with non-hanging grass fences (NF3)
Variable Goodness-of-fit Intercept Distance from the fence (m) DiffGF1-GF3 SAT Distance-Year 2021 Soil depth
(0-10 cm)
Marginal r² Conditional r²
GF1 vs. GF3
Vegetation coverage 0.525 0.585 31.397*** (3.563) 0.241 (0.186) 8.150* (3.684) 0.096 (0.155) 0.798** (0.241) -
Plant height 0.460 0.546 10.867*** (1.342) 0.037 (0.007) 2.324 (1.322) 0.067 (0.056) 0.295** (0.086) -
Aboveground biomass 0.629 0.670 55.865* (23.022) -0.049 (1.248) 109.238*** (24.609) 2.075 (1.041) 6.862*** (1.615) -
Species richness 0.557 0.560 6.495*** (1.052) 1.004 (1.003) 1.408*** (1.007) 0.980*** (1.003) 0.996 (1.004) -
Plant density 0.904 0.904 46.390*** (1.058) 1.001 (1.006) 0.898 (1.094) 0.975*** (1.002) 0.999 (1.008) -
pH 0.414 0.586 6.617*** (0.126) -0.001 (0.005) 0.490*** (0.101) 0.007 (0.004) 0.011 (0.007) -
SOC 0.256 0.320 10.220*** (0.580) 0.007 (0.030) -0.413 (0.650) -0.048 (0.030) -0.101* (0.043) -
EC 0.459 0.529 0.038** (0.008) 0.000 (0.000) 0.021* (0.009) 0.002*** (0.000) 0.001 (0.001) -
AP 0.656 0.913 32.226*** (2.647) -0.054 (0.166) -13.076*** (2.482) 0.178** (0.060) 0.421 (0.216) -
AK 0.955 0.972 434.036*** (17.475) -3.688* (1.613) -295.078*** (23.429) 0.583 (0.576) 3.920 (2.101) -
Sand content 0.344 0.356 77.912*** (1.492) 0.032 (0.099) -4.051* (1.904) 0.363*** (0.082) 0.163 (0.128) -
Silt content 0.336 0.350 11.714*** (1.234) -0.042 (0.081) 3.581* (1.568) -0.290*** (0.068) -0.114 (0.105) -
Clay content 0.363 0.669 10.096*** (0.588) 0.012 (0.050) -0.252 (0.737) -0.052** (0.018) -0.053 (0.066) -
Vegetation coverage 0.369 0.389 32.035*** (3.293) 0.247 (0.220) 4.982 (3.968) -0.125 (0.093) 0.654* (0.271) -
Plant height 0.315 0.325 11.714*** (1.171) 0.023 (0.083) 0.133 (1.472) 0.093* (0.035) 0.285** (0.103) -
Aboveground biomass 0.383 0.471 102.824** (26.800) 0.472 (1.377) 42.495 (26.267) 0.411 (0.587) 5.777** (1.698) -
Species richness 0.638 0.672 8.933*** (1.081) 0.995 (1.004) 1.015 (1.086) 0.980*** (1.002) 1.006 (1.005) -
Plant density 0.666 0.674 46.109*** (1.100) 1.000 (1.007) 0.905 (1.124) 0.971*** (1.003) 1.002 (1.008) -
pH 0.114 0.288 7.386*** (0.127) -0.015** (0.005) -0.211* (0.091) 0.003 (0.002) 0.022*** (0.006) -0.148* (0.067)
SOC 0.215 0.219 10.038*** (0.492) -0.028 (0.032) 0.636 (0.557) -0.080*** (0.013) 0.033 (0.039) -0.408 (0.457)
EC 0.259 0.299 0.078*** (0.012) -0.002** (0.001) -0.025* (0.012) 0.002*** (0.000) 0.002* (0.009) 0.006 (0.001)
AP 0.308 0.512 16.987*** (3.454) 0.166 (0.370) -2.288 (3.931) 0.273*** (0.065) 0.276 (0.454) 4.070* (1.909)
AK 0.366 0.382 69.350*** (9.090) 0.573 (0.521) 44.403*** (9.564) 0.903*** (0.221) 0.232 (0.643) 26.387*** (7.516)
Sand content 0.489 0.493 73.785*** (1.238) -0.179 (0.232) 5.364** (2.002) 0.145*** (0.037) 0.260 (0.361) -2.150 (1.195)
Silt content 0.425 0.435 13.740*** (0.990) 0.164 (0.180) -3.015 (1.587) -0.105*** (0.029) −0.208 (0.221) 1.741 (0.927)
Clay content 0.486 0.486 12.520*** (0.408) 0.015 (0.079) -2.444*** (0.664) -0.039** (0.012) -0.052 (0.097) 0.409 (0.407)
SWC 0.004 0.059 4.007 (0.125) 0.002 (0.006) 0.039 (0.121) 0.001 (0.003) -0.001 (0.008) 0.002 (0.093)
Table S4 Effects of the duration of enclosure with hanging grass fences (GF) and the presence of hanging grasses on vegetation parameters and soil physical and chemical properties based on the linear mixed model (LMM)
[1]   Allan E, Manning P, Alt F, et al. 2015. Land use intensification alters ecosystem multifunctionality via loss of biodiversity and changes to functional composition. Ecology Letters, 18(8): 834-843.
doi: 10.1111/ele.12469 pmid: 26096863
[2]   Bai Y F, Cotrufo M F. 2022. Grassland soil carbon sequestration: Current understanding, challenges, and solutions. Science, 377(6606): 603-608.
doi: 10.1126/science.abo2380 pmid: 35926033
[3]   Baker D V, Beck K G. 2008. The weed tunnel: Building an experimental wind tunnel. Weed Technology, 22(3): 549-552.
[4]   Bao S. 2000. Soil and Agricultural Chemistry Analysis. Beijing: China Agriculture Press, 14-209. (in Chinese)
[5]   Bates D, Mächler M, Bolker B, et al. 2015. Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1): 1-48.
[6]   Becker D A. 1978. Stem abscission in tumbleweeds of the Chenopodiaceae: Kochia. American Journal of Botany, 65(4): 375-383.
[7]   Bell L W, Kirkegaard J A, Swan A, et al. 2011. Impacts of soil damage by grazing livestock on crop productivity. Soil & Tillage Research, 113(1): 19-29.
[8]   Boutin C, Baril A, Martin P A. 2008. Plant diversity in crop fields and woody hedgerows of organic and conventional farms in contrasting landscapes. Agriculture, Ecosystems & Environment, 123(1-3): 185-193.
[9]   Bruegger R A, Jigjsuren O, Fernández-Giménez M E. 2014. Herder observations of rangeland change in Mongolia: indicators, causes, and application to community-based management. Rangeland Ecology & Management, 67(2): 119-131.
[10]   Burst M, Chauchard S, Dambrine E, et al. 2020. Distribution of soil properties along forest-grassland interfaces: Influence of permanent environmental factors or land-use after-effects? Agriculture, Ecosystems & Environment, 289: 106739, doi: 10.1016/j.agee.2019.106739.
[11]   Cardelús C L, Mekonnen A B, Jensen K H, et al. 2020. Edge effects and human disturbance influence soil physical and chemical properties in Sacred Church Forests in Ethiopia. Plant and Soil, 453: 329-342.
[12]   Cleugh H A, Hughes D E. 2002. Impact of shelter on crop microclimates: A synthesis of results from wind tunnel and field experiments. Australian Journal of Experimental Agriculture, 42(6): 679-701.
[13]   Díaz S, Lavorel S, McIntyre S, et al. 2007. Plant trait responses to grazing-a global synthesis. Global Change Biology, 13(2): 313-341.
[14]   Du C J, Jing J, Shen Y, et al. 2020. Short-term grazing exclusion improved topsoil conditions and plant characteristics in degraded alpine grasslands. Ecological Indicators, 108: 105680, doi: 10.1016/j.ecolind.2019.105680.
[15]   Eldridge D J, Delgado-Baquerizo M. 2017. Continental-scale impacts of livestock grazing on ecosystem supporting and regulating services. Land Degradation & Development, 28(4): 1473-1481.
[16]   Ewers R M, Didham R K. 2006. Continuous response functions for quantifying the strength of edge effects. Journal of Applied Ecology, 43(3): 527-536.
[17]   Fernandez-Gimenez M E. 2000. The role of Mongolian nomadic pastoralists' ecological knowledge in rangeland management. Ecological Applications, 10(5): 1318-1326.
[18]   Feyisa K, Beyene S, Angassa A, et al. 2017. Effects of enclosure management on carbon sequestration, soil properties and vegetation attributes in East African rangelands. Catena, 159: 9-19.
[19]   Fox J, Weisberg S. 2019. An R Companion to Applied Regression (3rd ed.). Thousand Oaks, CA: Sage. [2024-01-03]. https://socialsciences.mcmaster.ca/jfox/Books/Companion/.
[20]   Gasperini C, Carrari E, Govaert S, et al. 2021. Edge effects on the realised soil seed bank along microclimatic gradients in temperate European forests. Science of the Total Environment, 798: 149373, doi: 10.1016/j.scitotenv.2021.149373.
[21]   Haddaway N R, Brown C, Eales J, et al. 2018. The multifunctional roles of vegetated strips around and within agricultural fields. Environmental Evidence, 7: 14, doi: 10.1186/s13750-018-0126-2.
[22]   Hamm M, Drossel B. 2017. Habitat heterogeneity hypothesis and edge effects in model metacommunities. Journal of Theoretical Biology, 426: 40-48
doi: S0022-5193(17)30230-8 pmid: 28529154
[23]   Hao G, Dong K, Yang N, et al. 2021. Both fencing duration and shrub cover facilitate the restoration of shrub-encroached grasslands. Catena, 207: 105578, doi: 10.1016/j.catena.2021.105587.
[24]   Hu Z Y, Ma Y Y, Jin Q J, et al. 2023. Attribution of the March 2021 exceptional dust storm in North China. Bulletin of the American Meteorological Society, 104(4): E749-E755.
[25]   Ju W L, Fang L C, Shen G T, et al. 2023. New perspectives on microbiome and nutrient sequestration in soil aggregates during long-term grazing exclusion. Global Change Biology, 30(1): e17027, doi: 10.1111/gcb.17027.
[26]   Khaulanbek A, Tsogtbaatar J, Khudulmur S. 2013. National Atlas on Desertification. Ulaanbaatar: Bembi-San, 2-5.
[27]   Kinar N J. 2017. Modeling blowing snow accumulation downwind of an obstruction: The Ohara Eulerian particle distribution equation. Water Resources Research, 53(5): 3557-3564.
[28]   Lenth R V. 2016. Least-squares means: The R package lsmeans. Journal of Statistical Software, 69(1): 1-33.
[29]   Li G, Qin J M, Yu H X, et al. 2022. Wind-tunnel experimental studies of the spatial snow distribution over grass and bush surfaces. Journal of Hydrodynamics, 34: 85-93.
[30]   Li S G, Tsujimura M, Sugimoto A, et al. 2006. Natural recovery of steppe vegetation on vehicle tracks in Central Mongolia. Journal of Biosciences, 31: 85-93.
[31]   Liang Y M, Gao Y, Wang R D, et al. 2021. Fungal community characteristics and driving factors during the decaying process of Salix psammophila sand barriers in the desert. PLoS ONE, 16(10): e0258159, doi: 10.1371/journal.pone.0258159
[32]   Liira J, Paal T. 2013. Do forest-dwelling plant species disperse along landscape corridors? Plant Ecology, 214: 455-470.
[33]   Liu C, Li H, Liu K S, et al. 2023. Vegetation characteristics of the main grassland types in China respond differently to the duration of enclosure: a meta-analysis. Agronomy-Basel, 13(3): 854, doi: 10.3390/agronomy13030854.
[34]   Luo J F, Deng D Z, Zhang L, et al. 2019. Soil and vegetation conditions changes following the different sand dune restoration measures on the Zoige Plateau. PLoS ONE, 14(9): e0216975, doi: 10.1371/journal.pone.0216975.
[35]   Ma W Y, Luo Y, Li F Q, et al. 2022. The influence of wind deflectors on the snow distribution in road cuttings during snowdrift. Cold Regions Science and Technology, 196: 103505, doi: 10.1016/j.coldregions.2022.103505.
[36]   Matlack G R. 1993. Microenvironment variation within and among forest edge sites in the Eastern United States. Biological Conservation, 66(3): 185-194.
[37]   Matthews J W, Molano-Flores B, Ellis J, et al. 2017. Impacts of management and antecedent site condition on restoration outcomes in a sand prairie. Restoration Ecology, 25(6): 972-981.
[38]   McDonald S E, Lawrence R, Kendal L, et al. 2019. Ecological, biophysical and production effects of incorporating rest into grazing regimes: A global meta-analysis. Journal of Applied Ecology, 56(12): 2723-2731.
doi: 10.1111/1365-2664.13496
[39]   Meng X Y, Gao X, Li S Y, et al. 2020. Spatial and temporal characteristics of vegetation NDVI changes and the driving forces in Mongolia during 1982-2015. Remote Sensing, 12(4): 603, doi: 10.3390/rs12040603.
[40]   Meng X Y, Gao X, Li S, et al. 2021. Monitoring desertification in Mongolia based on Landsat images and Google Earth Engine from 1990 to 2020. Ecological Indicators, 129: 107908, doi: 10.1016/j.ecolind.2021.107908.
[41]   Michels K K, Hotchkiss S C, Jonaitis E, et al. 2017. A new application of change point analysis reveals extensive edge effects on a temperate mixed forest. Applied Vegetation Science, 20(4): 651-661.
[42]   Munoz-Cerro E, Garcia-Duro J, Matinez-Ruiz C, et al. 2023. Soil amelioration induced by nurse shrubs in coal mines reclaimed to pastures and their synergistic effects with grazing. Agriculture, Ecosystems & Environment, 350: 108483, doi: 10.1016/j.agee.2023.108483.
[43]   Novaes L R, Calixto E S, Alves-de-Lima L, et al. 2022. Testing direct and indirect road edge effects on reproductive components of anemochoric plants. Landscape and Urban Planning, 218: 104291, doi: 10.1016/j.landurbplan.2021.104291.
[44]   Oksanen J, Blanchet F G, Friendly M, et al. 2020. Vegan: Community Ecology Package. R package version 2.5-7. [2023-09-01]. https://CRAN.R-project.org/package=vegan.
[45]   Pohlman C L, Turton S M, Goosem M. 2009. Temporal variation in microclimatic edge effects near powerlines, highways and streams in Australian tropical rainforest. Agricultural and Forest Meteorology, 149(4): 84-95.
[46]   Porensky L M. 2011. When edges meet: interacting edge effects in an African savanna. Journal of Ecology, 99(4): 923-934.
[47]   Pulido M, Schnabel S, Contador J F L, et al. 2018. The impact of heavy grazing on soil quality and pasture production in rangelands of SW Spain. Land Degradation & Development, 29(2): 219-230.
[48]   Ries L, Sisk T D. 2004. A predictive model of edge effects. Ecology, 85(11): 2917-2926.
[49]   Rosseel Y. 2012. Lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2): 1-36.
[50]   Rotundo J L, Aguiar M R, Benech-Arnold R. 2015. Understanding erratic seedling emergence in perennial grasses using physiological models and field experimentation. Plant Ecology, 216: 143-156.
[51]   Sainnemekh S, Barrio I C, Densambuu B, et al. 2022. Rangeland degradation in Mongolia: A systematic review of the evidence. Journal of Arid Environments, 196: 104654, doi: 10.1016/j.jaridenv.2021.104654.
[52]   Sanaei A, Li M S, Ali A. 2019. Topography, grazing, and soil textures control over rangelands' vegetation quantity and quality. Science of the Total Environment, 697: 134153, doi: 10.1016/j.scitotenv.2019.134153.
[53]   Schopke B, Wesche K, Wulf M. 2023. Dry grasslands adjacent to organic fields have higher plant diversity-Even far into their interior. Agriculture, Ecosystems & Environment, 357: 108672, doi: 10.1016/j.agee.2023.108672.
[54]   Seddon A W R, Macias-Fauria M, Long P R, et al. 2016. Sensitivity of global terrestrial ecosystems to climate variability. Nature, 531: 229-232.
[55]   Shinoda M, Gillies J A, Mikami M, et al. 2011. Temperate grasslands as a dust source: Knowledge, uncertainties, and challenges. Aeolian Research, 3(3): 271-293.
[56]   Sitzia T, Trentanovi G, Marini L, et al. 2013. Assessment of hedge stand types as determinants of woody species richness in rural field margins. iForest-Biogeosciences and Forestry, 6(4): 201-208.
[57]   Sizer N C, Tanner E V J, Ferraz I D K. 2000. Edge effects on litterfall mass and nutrient concentrations in forest fragments in central Amazonia. Journal of Tropical Ecology, 16(6): 853-863.
[58]   Soons M B, Heil G W, Nathan R, et al. 2004. Determinants of long-distance seed dispersal by wind in grasslands. Ecology, 85(11): 3056-3068.
[59]   Teng J D, Yasufuku N, Liu Q, et al. 2014. Experimental evaluation and parameterization of evaporation from soil surface. Natural Hazards, 73: 1405-1418.
[60]   Vacek Z, Rehácek D, Cukor J, et al. 2018. Windbreak efficiency in agricultural landscape of the Central Europe: multiple approaches to wind erosion control. Environmental Management, 62: 942-954.
doi: 10.1007/s00267-018-1090-x pmid: 30143821
[61]   Veste M, Littmann T, Kunneke A, et al. 2020. Windbreaks as part of climate-smart landscapes reduce evapotranspiration in vineyards, Western Cape Province, South Africa. Plant Soil and Environment, 66(3): 119-127.
doi: 10.17221/616/2019-PSE
[62]   Wang B Z, Zhu Y J, Erdenebileg E, et al. 2023. Effect of soil physicochemical properties on the steppe grazing potential in Eastern Eurasian steppe. Journal of Soils and Sediments, 23: 731-744.
[63]   Wang Z P, Han S J, Zheng Y H, et al. 2021. Fencing facility affects plant species and soil organic carbon in temperate steppes. Catena, 196: 104928, doi: 10.1016/j.catena.2020.104928.
[64]   Wilkerson M L. 2014. Using hedgerows as model linkages to examine non-native plant patterns. Agriculture, Ecosystems & Environment, 192: 38-46.
[65]   Xi C, Zuo H J, Wei X H, et al. 2023. Sand-fixing effect and compound change of nylon checkerboard sand barrier. Environmental Science and Pollution Research, 30: 35727-35744.
[66]   Xiong D P, Shi P L, Zhang X Z, et al. 2016. Effects of grazing exclusion on carbon sequestration and plant diversity in grasslands of China-A meta-analysis. Ecological Engineering, 94: 647-655.
[67]   Xu H W, You C M, Tan B, et al. 2023. Effects of livestock grazing on the relationships between soil microbial community and soil carbon in grassland ecosystems. Science of the Total Environment, 881: 163461, doi: 10.1016/j.scitotenv.2023.163416.
[68]   Yan N A, Zhu W W, Wu B F, et al. 2023. Assessment of the grassland carrying capacity for winter-spring period in Mongolia. Ecological Indicators, 146: 109868, doi: 10.1016/j.ecolind.2023.109868.
[69]   Yates C J, Norton D A, Hobbs R J. 2000. Grazing effects on plant cover, soil and microclimate in fragmented woodlands in south-western Australia: implications for restoration. Austral Ecology, 25(1): 36-47.
[70]   Zhang B, Thomas B W, Beck R, et al. 2018. Slope position regulates response of carbon and nitrogen stocks to cattle grazing on rough fescue grassland. Journal of Soils and Sediments, 18: 3228-3234.
[71]   Zhang C L, Li Q, Zhou N, et al. 2016. Field observations of wind profiles and sand fluxes above the windward slope of a sand dune before and after the establishment of semi-buried straw checkerboard barriers. Aeolian Research, 20: 59-70.
[72]   Zhang N N, Sun G, Zhong B, et al. 2019. Impacts of wise grazing on physicochemical and biological features of soil in a sandy grassland on the Tibetan Plateau. Land Degradation & Development, 30(7): 719-729.
[73]   Zhang Y Z, Wang Q, Wang Z Q, et al. 2020. Impact of human activities and climate change on the grassland dynamics under different regime policies in the Mongolian Plateau. Science of the Total Environment, 698: 134304, doi: 10.1016/j.scitotenv.2019.134304.
[74]   Zheng J H, Zhang B, Zhang F, et al. 2023. Effects of fencing on near-term ecosystem multifunctionality in a typical steppe in Inner Mongolia. Agriculture, Ecosystems & Environment, 342: 108238, doi: 10.1016/j.agee.2022.108238.
[75]   Zheng X, Zhu J J, Xing Z F. 2016. Assessment of the effects of shelterbelts on crop yields at the regional scale in Northeast China. Agricultural Systems, 143: 49-60.
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