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Journal of Arid Land
Journal of Arid Land  2022, Vol. 14 Issue (8): 877-893    DOI: 10.1007/s40333-022-0070-4     CSTR: 32276.14.s40333-022-0070-4
Research article     
Wind-proof and sand-fixing effects of Artemisia ordosica with different coverages in the Mu Us Sandy Land, northern China
PANG Yingjun1,2,3,4,*(), WU Bo1,2,3,*(), JIA Xiaohong1,2,3, XIE Shengbo5
1Institute of Desertification Studies, Chinese Academy of Forestry, Beijing 100091, China
2Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry, Beijing 100091, China
3Key Laboratory of Desert Ecosystem and Global Change, National Forestry and Grassland Administration, Beijing 100091, China
4Kumtag Desert Ecosystem Research Station, National Forestry and Grassland Administration, Dunhuang 736200, China
5Key Laboratory of Desert and Desertification, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
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Abstract  

Wind erosion is a key global environmental problem and has many adverse effects. The Mu Us Sandy Land of northern China is characterized by an arid climate, where vegetation patches and bare sand patches are usually distributed mosaically, and aeolian activities occur frequently. Vegetation plays a significant role in controlling wind erosion. Artemisia ordosica is the most dominant native plant species in the Mu Us Sandy Land. It is urgent to study the wind-proof and sand-fixing effects of Artemisia ordosica in the Mu Us Sandy Land. This study analyzed the wind-proof and sand-fixing effects of Artemisia ordosica based on the field data of wind regimes, aeolian sediment transport, and surface change of Artemisia ordosica plots with four coverages (denoted as site A, site B, site C, and site D) in the Mu Us Sandy Land during the period from 1 June 2018 to 29 June 2019. The coverages of Artemisia ordosica at site A, site B, site C, and site D were 2%, 16%, 29%, and 69%, respectively. The annual average wind speeds at 2.0 m height above the ground for site A, site B, site C, and site D were 3.47, 2.77, 2.21, and 1.97 m/s, respectively. The annual drift potentials were 193.80, 69.72, 15.05, and 6.73 VU at site A, site B, site C, and site D, respectively. The total horizontal aeolian sediment fluxes during the period from 2-3 June 2018 to 6 June 2019 at site A, site B, site C, and site D were 4633.61, 896.80, 10.54, and 6.14 kg/m, respectively. Site A had the largest surface changes, and the surface changes at site B were significantly weaker than those at site A, whereas the surface changes at site C and site D were minimal. The results indicated that Artemisia ordosica significantly reduced the wind speed, drift potential, aeolian sediment transport, and surface changes. The higher the coverage of Artemisia ordosica is, the more obvious the effects of wind-proof and sand-fixing. Wind erosion would be effectively controlled in the Mu Us Sandy Land if the coverage of Artemisia ordosica is greater than 29%. These results provide a scientific basis for evaluating the ecosystem service function of Artemisia ordosica and the vegetation protection and construction projects in the Mu Us Sandy Land.

Key words： Artemisia ordosica      wind-proof      sand-fixing      wind erosion      aeolian sediment flux      Mu Us Sandy Land     
Received: 14 February 2022      Published: 30 August 2022
Corresponding Authors: * PANG Yingjun (E-mail: pangyingjun@caf.ac.cn);WU Bo (E-mail: wubo@caf.ac.cn)
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PANG Yingjun, WU Bo, JIA Xiaohong, XIE Shengbo. Wind-proof and sand-fixing effects of Artemisia ordosica with different coverages in the Mu Us Sandy Land, northern China. Journal of Arid Land, 2022, 14(8): 877-893.

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http://jal.xjegi.com/10.1007/s40333-022-0070-4     OR     http://jal.xjegi.com/Y2022/V14/I8/877

Fig. 1 Overview of the study area and distribution area of monitoring sites. Note that this map is based on the Google Earth images.
Fig. 2 Photographs of the monitoring sites with different coverages of Artemisia ordosica. (a), site A; (b), site B; (c), site C; (d), site D.
Location Artemisia ordosica
coverage (%)		 Observation height of
wind (m)		 Observation height of
sediment collection (m)
Site A 2 0.2, 0.5, 1.0, and 2.0 0.2, 0.5, 1.0, 1.5, and 2.0
Site B 16 2.0 0.2, 0.5, 1.0, and 2.0
Site C 29 0.2, 0.5, 1.0, and 2.0 0.2, 0.5, 1.0, 1.5, and 2.0
Site D 69 0.2, 0.5, 1.0, and 2.0 0.2, 0.5, 1.0, 1.5, and 2.0
Table 1 Description of the monitoring sites selected in this study
Direction Abbreviation Azimuth degree (°) Direction Abbreviation Azimuth degree (°)
North N 348.75-11.25 South S 168.75-191.25
North-northeast NNE 11.25-33.75 South-southwest SSW 191.25-213.75
Northeast NE 33.75-56.25 Southwest SW 213.75-236.25
East-northeast ENE 56.25-78.75 West-southwest WSW 236.25-258.75
East E 78.75-101.25 West W 258.75-281.25
East-southeast ESE 101.25-123.75 West-northwest WNW 281.25-303.75
Southeast SE 123.75-146.25 Northwest NW 303.75-326.25
South-southeast SSE 146.25-168.75 North-northwest NNW 326.25-348.75
Table 2 Description of the direction and azimuth degree
Fig. 3 Wind roses of the four monitoring sites at 2.0 m height above the ground during the period from 1 June 2018 to 31 May 2019. (a), site A; (b), site B; (c), site C; (d), site D. N, north; NNE, north-northeast; NE, northeast; ENE, east-northeast; E, east; ESE, east-southeast; SE, southeast; SSE, south-southeast; S, south; SSW, south-southwest; SW, southwest; WSW, west-southwest; W, west; WNW, west-northwest; NW, northwest; NNW, north-northwest.
Fig. 4 Monthly average wind speeds at a height of 2.0 m above the ground at the four monitoring sites during the period from 1 June 2018 to 31 May 2019
Fig. 5 Drift potential (DP) roses at the four monitoring sites during the period from 1 June 2018 to 31 May 2019. (a), site A; (b), site B; (c), site C; (d), site D. The arrow line segment represents the resultant drift potential (RDP), and the direction of the arrow represents the resultant drift direction (RDD). VU, vector units.
Fig. 6 Horizontal aeolian sediment fluxes at the four monitoring sites during the period from 2-3 June 2018 to 6 June 2019. (a), site A; (b), site B; (c), site C; (d), site D.
Location Sample Height above
the
ground
(m)		 Percentage of grain size (%) Mean
grain
size
(μm)
Clay Silt Very fine sand Fine
sand		 Medium
sand		 Coarse
sand		 Very coarse
sand		 Gravel
(0-
2 μm)		 (2-
63 μm)		 (63-
125 μm)		 (125-
250 μm)		 (250-
500 μm)		 (500-
1000 μm)		 (1000-
2000 μm)		 (>2000 μm)
Site A SSS 0.0 0.00 0.81 2.00 44.24 50.88 2.06 0.01 0.00 272.94
HASS 0.2 0.00 0.00 3.24 54.03 41.45 1.28 0.00 0.00 234.24
HASS 0.5 0.00 4.53 14.04 50.71 30.44 0.28 0.00 0.00 192.67
HASS 1.0 0.00 3.83 21.68 55.09 19.40 0.00 0.00 0.00 168.06
HASS 1.5 0.00 11.90 24.51 47.78 15.80 0.01 0.00 0.00 143.11
HASS 2.0 0.00 11.27 23.57 49.77 15.38 0.00 0.00 0.00 145.43
Site B SSS 0.0 0.05 2.38 1.82 36.27 52.71 6.77 0.00 0.00 293.79
HASS 0.2 0.00 0.00 2.39 43.25 49.29 5.06 0.00 0.00 261.83
HASS 0.5 0.00 1.23 6.24 52.53 38.58 1.43 0.00 0.00 224.38
HASS 1.0 0.00 6.20 9.89 50.24 33.11 0.57 0.00 0.00 201.48
HASS 2.0 0.01 45.99 25.45 20.82 7.59 0.15 0.00 0.00 73.06
Site C SSS 0.0 0.00 2.28 3.80 42.98 46.98 3.96 0.00 0.00 267.66
HASS 0.2 0.00 2.21 1.51 36.01 54.70 5.56 0.00 0.00 275.73
HASS 0.5 0.00 16.46 19.87 39.33 23.79 0.54 0.00 0.00 143.39
HASS 1.0 0.00 22.94 26.33 33.51 16.77 0.45 0.00 0.00 118.50
HASS 1.5 0.00 22.64 19.43 22.25 25.71 9.89 0.09 0.00 151.78
HASS 2.0 0.00 43.24 30.97 17.73 7.72 0.34 0.00 0.00 77.72
Site D SSS 0.0 0.15 21.07 10.68 34.85 31.25 2.00 0.00 0.00 150.81
HASS 0.2 0.00 19.63 19.97 34.27 23.46 2.66 0.02 0.00 138.16
HASS 0.5 0.00 47.30 25.65 17.51 8.55 0.99 0.00 0.00 71.02
HASS 1.0 0.01 64.01 23.85 9.32 2.80 0.01 0.00 0.00 45.94
HASS 1.5 0.01 62.36 24.36 9.36 3.45 0.46 0.00 0.00 49.00
HASS 2.0 0.00 50.74 28.81 12.90 6.05 1.49 0.00 0.00 66.47
Table 2 Grain size distributions of the surface sediment samples and horizontal aeolian sediment samples at different heights above the ground
Fig. 7 Grain size distributions of the surface sediment samples at the four monitoring sites
Fig. 8 Grain size distributions of the horizontal aeolian sediment samples at different heights at the four monitoring sites. (a), site A; (b), site B; (c), site C; (d), site D.
Fig. 9 Surface changes at the four monitoring sites during the period from 2 June 2018 to 29 June 2019. (a), site A; (b), site B; (c), site C; (d), site D. Positive values on y-axis represent surface deposition, while negative values represent surface erosion.
Fig. 10 Relationship between the DP and horizontal aeolian sediment flux at the four monitoring sites
Fig. 11 Relationship between Artemisia ordosica coverage and the total horizontal aeolian sediment flux during the period from 2-3 June 2018 to 6 June 2019
[1]   Asensio C, Lozano F J, Gallardo P, et al. 2016. Soil wind erosion in ecological olive trees in the Tabernas desert (southeastern Spain): a wind tunnel experiment. Solid Earth, 7(4): 1233-1242.
doi: 10.5194/se-7-1233-2016
[2]   Ash J E, Wasson R J. 1983. Vegetation and mobility in the Australian desert dunefield. Zeitschrift für Geomorphologie, 45: 7-25.
[3]   Breckle S W, Yair A, Veste M, et al. 2008. Arid Dune Ecosystems. Heidelberg: Springer Berlin, 217-220.
[4]   Buckley R. 1987. The effect of sparse vegetation on the transport of dune sand by wind. Nature, 325(6103): 426-428.
doi: 10.1038/325426a0
[5]   Buckley R. 1996. Effects of vegetation on the transport of dune sand. Annals of Arid Zone, 35(3): 215-223.
[6]   Burri K, Gromke C, Lehning M, et al. 2011. Aeolian sediment transport over vegetation canopies: A wind tunnel study with live plants. Aeolian Research, 3(2): 205-213.
doi: 10.1016/j.aeolia.2011.01.003
[7]   Chen C, Park T, Wang X H, et al. 2019. China and India lead in greening of the world through land-use management. Nature Sustainability, 2(2): 122-129.
doi: 10.1038/s41893-019-0220-7 pmid: 30778399
[8]   Ci L J, Yang X H. 2010. Desertification and Its Control in China. Beijing: Higher Education Press, 299-426.
[9]   Dupont S, Bergametti G, Simoëns S. 2014. Modeling aeolian erosion in presence of vegetation. Journal of Geophysical Research-Earth Surface, 119(2): 168-187.
doi: 10.1002/2013JF002875
[10]   Feng K, Wang T, Liu S L, et al. 2021. Path analysis model to identify and analyse the causes of aeolian desertification in Mu Us Sandy Land, China. Ecological Indicators, 124: 107386, doi: 10.1016/j.ecolind.2021.107386.
doi: 10.1016/j.ecolind.2021.107386
[11]   Folk R L, Ward W C. 1957. Brazos River bar: a study in the significance of grain size parameters. Journal of Sedimentary Research, 27(1): 3-26.
doi: 10.1306/74D70646-2B21-11D7-8648000102C1865D
[12]   Fryberger S G, Dean G. 1979. Dune forms and wind regime. In: McKeeE D. Washington: United States Geological Survey, 137-169.
[13]   Gillies J A, Nickling W G, King J. 2002. Drag coefficient and plant form response to wind speed in three plant species: Burning Bush (Euonymus alatus), Colorado Blue Spruce (Picea pungens glauca), and Fountain Grass (Pennisetum setaceum). Journal of Geophysical Research: Atmospheres, 107(D24): 4760, doi: 10.1029/2001JD001259.
doi: 10.1029/2001JD001259
[14]   IPCC. 2019. Climate Change and Land: an IPCC special report on climate change, desertifcation, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems. [2021-12-20]. https://www.ipcc.ch/srccl/.
[15]   Keiko U, Satoshi T. 2007. Experimental study of blown sand in a vegetated area. Journal of Coastal Research, 23(5): 1175-1182.
doi: 10.2112/05-0499.1
[16]   King J, Nickling W G, Gillies J A. 2005. Representation of vegetation and other nonerodible elements in aeolian shear stress partitioning models for predicting transport threshold. Journal of Geophysical Research: Earth Surface, 110(F4): F04015, doi: 10.1029/2004JF000281.
doi: 10.1029/2004JF000281
[17]   Kuriyama Y, Mochizuki N, Nakashima T. 2005. Influence of vegetation on aeolian sand transport rate from a backshore to a foredune at Hasaki, Japan. Sedimentology, 52(5): 1123-1132.
doi: 10.1111/j.1365-3091.2005.00734.x
[18]   Lancaster N, Baas A. 1998. Influence of vegetation cover on sand transport by wind: Field studies at Owens Lake, California. Earth Surface Processes and Landforms, 23(1): 69-82.
doi: 10.1002/(SICI)1096-9837(199801)23:1<69::AID-ESP823>3.0.CO;2-G
[19]   Leenders J K, van Boxel J H, Sterk G. 2007. The effect of single vegetation elements on wind speed and sediment transport in the Sahelian zone of Burkina Faso. Earth Surface Processes and Landforms, 32(10): 1454-1474.
doi: 10.1002/esp.1452
[20]   Leenders J K, Sterk G, Van Boxel J H. 2011. Modelling wind-blown sediment transport around single vegetation elements. Earth Surface Processes and Landforms, 36(9): 1218-1229.
doi: 10.1002/esp.2147
[21]   Leenders J K, Sterk G, van Boxel J H. 2016. Wind erosion reduction by scattered woody vegetation in farmers' fields in Northern Burkina Faso. Land Degradation & Development, 27(8): 1863-1872.
doi: 10.1002/ldr.2322
[22]   Lei J Q, Li S Y, Jin Z Z, et al. 2008. Comprehensive eco-environmental effects of the shelter-forest ecological engineering along the Tarim Desert Highway. Chinese Science Bulletin, 53: 190-202.
[23]   Li J R, Okin G S, Alvarez L, et al. 2007. Quantitative effects of vegetation cover on wind erosion and soil nutrient loss in a desert grassland of southern New Mexico, USA. Biogeochemistry, 85: 317-332.
doi: 10.1007/s10533-007-9142-y
[24]   Li X R, Xiao H L, Zhang J G, et al. 2004. Long-term ecosystem effects of sand-binding vegetation in the Tengger Desert, northern China. Restoration Ecology, 12(3): 376-390.
doi: 10.1111/j.1061-2971.2004.00313.x
[25]   Liu J Q, Kimura R, Miyawaki M, et al. 2021. Effects of plants with different shapes and coverage on the blown-sand flux and roughness length examined by wind tunnel experiments. CATENA, 197: 104976, doi: 10.1016/j.catena.2020.104976.
doi: 10.1016/j.catena.2020.104976
[26]   Meng Z J, Dang X H, Gao Y, et al. 2018. Interactive effects of wind speed, vegetation coverage and soil moisture in controlling wind erosion in a temperate desert steppe, Inner Mongolia of China. Journal of Arid Land, 10(4): 534-547.
doi: 10.1007/s40333-018-0059-1
[27]   National Forestry and Grassland Administration of China. 2017. 2017 China Forestry and Grassland Development Report. Beijing: China Forestry Press. (in Chinese)
[28]   Ohte N, Miki N H, Matsuo N, et al. 2021. Life history of Juniperus sabina L. adapted to the sand shifting environment in the Mu Us Sandy Land, China: A review. Landscape and Ecological Engineering, 17(3): 281-294.
doi: 10.1007/s11355-021-00453-y
[29]   Okin G S. 2008. A new model of wind erosion in the presence of vegetation. Journal of Geophysical Research: Earth Surface, 113(F2): F02S10, doi: 10.1029/2007JF000758.
doi: 10.1029/2007JF000758
[30]   Pang Y J, Wu B, Li Y H, et al. 2020. Morphological characteristics and dynamic changes of seif dunes in the eastern margin of the Kumtagh Desert, China. Journal of Arid Land, 12(5): 887-902.
doi: 10.1007/s40333-020-0099-1
[31]   Pi H W, Sharratt B, Lei J Q. 2017. Windblown sediment transport and loss in a desert-oasis ecotone in the Tarim Basin. Scientific Reports, 7: 7723, doi: 10.1038/s41598-017-04971-4.
doi: 10.1038/s41598-017-04971-4
[32]   Stockton P H, Gillette D A. 1990. Field measurement of the sheltering effect of vegetation on erodible land surfaces. Land Degradation & Development, 2(2): 77-85.
doi: 10.1002/ldr.3400020202
[33]   Sun Z H, Mao Z G, Yang L Y, et al. 2021. Impacts of climate change and afforestation on vegetation dynamic in the Mu Us Desert, China. Ecological Indicators, 129: 108020, doi: 10.1016/j.ecolind.2021.108020.
doi: 10.1016/j.ecolind.2021.108020
[34]   Sweeney M R, Lu H Y, Cui M C, et al. 2016. Sand dunes as potential sources of dust in northern China. Science China Earth Sciences, 59: 760-769.
doi: 10.1007/s11430-015-5246-8
[35]   Udden J A. 1914. Mechanical composition of clastic sediments. Bulletin of the Geological Society of America, 25(1): 655-744.
doi: 10.1130/GSAB-25-655
[36]   UNEP (United Nations Environment Programme), WMO (World Meteorological Organization), UNCCD (United Nations Convention to Combat Desertification). 2016. Global Assessment of Sand and Dust Storms. Nairobi, Kenya: UNEP. [2021-12-28]. https://library.wmo.int/doc_num.php?explnum_id=3083.
[37]   Wang T. 2003. Desert and Desertification in China. Shijiazhuang: Hebei Science & Technology Press. (in Chinese)
[38]   Webb N P, McCord S E, Edwards B L, et al. 2021. Vegetation canopy gap size and height: Critical indicators for wind erosion monitoring and management. Rangeland Ecology & Management, 76(1): 78-83.
doi: 10.1016/j.rama.2021.02.003
[39]   Wentworth C K. 1922. A scale of grade and class terms for clastic sediments. The Journal of Geology, 30(5): 377-392.
doi: 10.1086/622910
[40]   Wiggs G F S, Thomas D S G, Bullard J E, et al. 1995. Dune mobility and vegetation cover in the Southwest Kalahari Desert. Earth Surface Processes and Landforms, 20(6): 515-529.
doi: 10.1002/esp.3290200604
[41]   Wolfe S A, Nickling W G. 1993. The protective role of sparse vegetation in wind erosion. Progress in Physical Geography, 17(1): 50-68.
[42]   Xiu L N, Yan C Z, Li X S, et al. 2018. Monitoring the response of vegetation dynamics to ecological engineering in the Mu Us Sandy Land of China from 1982 to 2014. Environmental Monitoring and Assessment, 190: 543, doi: 10.1007/s10661-018-6931-9.
doi: 10.1007/s10661-018-6931-9
[43]   Xu Z W, Hu R, Wang K X, et al. 2018. Recent greening (1981-2013) in the Mu Us dune field, north-central China, and its potential causes. Land Degradation & Development, 29(5): 1509-1520.
doi: 10.1002/ldr.2910
[44]   Yan Y C, Xin X P, Xu X L, et al. 2013. Quantitative effects of wind erosion on the soil texture and soil nutrients under different vegetation coverage in a semiarid steppe of northern China. Plant and Soil, 369: 585-598.
doi: 10.1007/s11104-013-1606-3
[45]   Youssef F, Visser S M, Karssenberg D, et al. 2012. The effect of vegetation patterns on wind-blown mass transport at the regional scale: A wind tunnel experiment. Geomorphology, 159: 178-188.
[46]   Zhang M M, Wu X Q. 2020. The rebound effects of recent vegetation restoration projects in Mu Us Sandy land of China. Ecological Indicators, 113: 106228, doi: 10.1016/j.ecolind.2020.106228.
doi: 10.1016/j.ecolind.2020.106228
[47]   Zhang Z C, Dong Z N, Zhao A G, et al. 2011. Relationship between sand transport and sand drift potential. Journal of Desert Research, 31(4): 824-827. (in Chinese)
[48]   Zhao M, Geruo G, Zhang J, et al. 2021. Ecological restoration impact on total terrestrial water storage. Nature Sustainability, 4: 56-62.
doi: 10.1038/s41893-020-00600-7
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