Please wait a minute...
Journal of Arid Land  2021, Vol. 13 Issue (12): 1201-1214    DOI: 10.1007/s40333-021-0027-z     CSTR: 32276.14.s40333-021-0027-z
Original article     
Effects of restoration modes on the spatial distribution of soil physical properties after land consolidation: a multifractal analysis
KE Zengming1, LIU Xiaoli2, MA Lihui1,3,*(), TU Wen2, FENG Zhe2, JIAO Feng1,3, WANG Zhanli1,3
1State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A&F University, Yangling 712100, China
2College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China
3Institute of Water Saving Agriculture in Arid Areas of China, Northwest A&F University, Yangling 712100, China
Download: HTML     PDF(1834KB)
Export: BibTeX | EndNote (RIS)      

Abstract  

Soil physical properties (SPP) are considered to be important indices that reflect soil structure, hydrological conditions and soil quality. It is of substantial interest to study the spatial distribution of SPP owing to the high spatial variability caused by land consolidation under various land restoration modes in excavated farmland in the loess hilly area of China. In our study, three land restoration modes were selected including natural restoration land (NR), alfalfa land (AL) and maize land (ML). Soil texture composition, including the contents of clay, silt and sand, field capacity (FC), saturated conductivity (Ks) and bulk density (BD) were determined using a multifractal analysis. SPP were found to possess variable characteristics, although land consolidation destroyed the soil structure and decreased the spatial autocorrelation. Furthermore, SPP varied with land restoration and could be illustrated by the multifractal parameters of D1, ∆D, ∆α and ∆f in different modes of land restoration. Owing to multiple compaction from large machinery in the surface soil, soil particles were fine-grained and increased the spatial variability in soil texture composition under all the land restoration modes. Plough numbers and vegetative root characteristics had the most significant impacts on the improvement in SPP, which resulted in the best spatial distribution characteristics of SPP found in ML compared with those in AL and NR. In addition, compared with ML, ∆α values of NR and AL were 4.9- and 3.0-fold that of FC, respectively, and ∆α values of NR and AL were 2.3- and 1.5-fold higher than those of Ks, respectively. These results indicate that SPP can be rapidly improved by increasing plough numbers and planting vegetation types after land consolidation. Thus, we conclude that ML is an optimal land restoration mode that results in favorable conditions to rapidly improve SPP.



Key wordsland consolidation      land restoration      multifractal analysis      spatial distribution      soil physical properties     
Received: 10 October 2021      Published: 10 December 2021
Corresponding Authors: *MA Lihui (E-mail: gjzmlh@126.com)
Cite this article:

KE Zengming, LIU Xiaoli, MA Lihui, TU Wen, FENG Zhe, JIAO Feng, WANG Zhanli. Effects of restoration modes on the spatial distribution of soil physical properties after land consolidation: a multifractal analysis. Journal of Arid Land, 2021, 13(12): 1201-1214.

URL:

http://jal.xjegi.com/10.1007/s40333-021-0027-z     OR     http://jal.xjegi.com/Y2021/V13/I12/1201

Fig. 1 (a), location of Ansai District in the hilly loess region of China; (b), schematic illustration of the "Gullies Reclamation for Farmland" project; (c), excavated farmland.
Fig. 2 Overview of study area. (a), natural restoration land; (b), alfalfa land; (c), maize land.
Soil property Soil depth (cm) ML CV AL CV NR CV
Clay content
(%)
0-20 9.85±0.34Aa 0.03 9.62±0.36Aab 0.04 9.49±0.36Ab 0.04
20-40 9.99±0.32Aa 0.03 9.72±0.31Ab 0.03 9.61±0.36Ab 0.04
Silt content
(%)
0-20 39.20±1.72Aa 0.04 39.33±1.74Aa 0.04 38.61±1.82Aa 0.05
20-40 40.04±1.71Aa 0.04 39.36±1.7Aa 0.04 38.97±1.70Aa 0.04
Sand content
(%)
0-20 50.95±1.61Aa 0.03 51.06±1.57Aa 0.03 51.89±1.69Aa 0.03
20-40 49.97±1.69Ab 0.03 50.92±1.68Ab 0.03 51.42±1.68Aa 0.03
BD (g/cm3) 0-20 1.06±0.08Bc 0.07 1.31±0.07Bb 0.05 1.52±0.07Aa 0.05
20-40 1.25±0.09Ac 0.07 1.49±0.11Ab 0.07 1.55±0.12Aa 0.08
FC (%) 0-20 24.26±0.81Aa 0.03 21.44±1.29Ab 0.06 19.48±1.58Ac 0.08
20-40 23.21±0.72Ba 0.03 20.08±1.10Bb 0.05 18.91±1.49Ac 0.08
Ks (cm/min) 0-20 0.62±0.13Aa 0.20 0.47±0.24Aab 0.50 0.35±0.25Ab 0.71
20-40 0.39±0.17Ba 0.44 0.20±0.12Bb 0.58 0.16±0.16Bb 0.99
Table 1 Soil bulk density (BD), field capacity (FC), saturated hydraulic conductivity (Ks) and soil texture (clay, silt and sand contents) in three plots
Soil
property
Soil depth
(cm)
ML AL NR
D1 D α f D1 D α f D1 D α f
Clay content 0-20 1.9992 0.0169 0.0335 0.0081 1.9990 0.0195 0.0388 0.0091 1.9990 0.0198 0.0395 0.0229
20-40 1.9994 0.0125 0.0253 0.0225 1.9994 0.0124 0.0249 0.0222 1.9992 0.0168 0.0335 0.0229
Mean 1.9993 0.0147 0.0294 0.0153 1.9992 0.016 0.0319 0.0157 1.9991 0.0183 0.0365 0.0229
Silt content 0-20 1.9988 0.0238 0.0469 -0.0296 1.9988 0.0238 0.0470 -0.0272 1.9986 0.0279 0.0551 -0.0355
20-40 1.9993 0.0146 0.0288 -0.0245 1.9992 0.0158 0.0312 -0.0259 1.9992 0.0163 0.0320 -0.0269
Mean 1.9991 0.0192 0.0379 -0.0271 1.9990 0.0198 0.0391 -0.0266 1.9989 0.0221 0.0436 -0.0312
Sand content 0-20 1.9994 0.0122 0.0245 0.0111 1.9994 0.0117 0.0235 0.0103 1.9993 0.0133 0.0267 0.0129
20-40 1.9995 0.0101 0.0204 0.0187 1.9995 0.0101 0.0203 0.0163 1.9995 0.0095 0.0190 0.0154
Mean 1.9995 0.0112 0.0225 0.0149 1.9995 0.0109 0.0219 0.0133 1.9994 0.0114 0.0229 0.0142
BD 0-20 1.9965 0.0688 0.1356 0.1243 1.9987 0.0246 0.0476 -0.0440 1.9990 0.0199 0.0390 -0.0096
20-40 1.9969 0.0596 0.1150 0.1126 1.9972 0.0546 0.1066 -0.0138 1.9974 0.0518 0.1036 0.1345
Mean 1.9967 0.0642 0.1253 0.1185 1.9980 0.0396 0.0771 -0.0289 1.9982 0.0359 0.0713 0.0625
FC 0-20 1.9994 0.0126 0.0249 -0.0041 1.9976 0.0462 0.0890 0.0256 1.9967 0.0614 0.1134 -0.0257
20-40 1.9995 0.0103 0.0204 0.0018 1.9987 0.0253 0.0488 -0.0119 1.9974 0.0539 0.1096 0.0338
Mean 1.9995 0.0115 0.0227 -0.0012 1.9982 0.0358 0.0689 0.0069 1.9971 0.0577 0.1115 0.0041
Ks 0-20 1.9745 0.3820 0.6086 -0.2603 1.8837 1.0203 1.2591 0.7595 1.7287 1.6684 1.9590 1.3434
20-40 1.9047 1.0157 1.3356 0.5495 1.7815 1.5097 1.7385 -0.7527 1.6603 2.1597 2.4938 -0.7405
Mean 1.9396 0.6989 0.9721 0.1446 1.8326 1.2650 1.4988 0.0034 1.6945 1.9141 2.2264 0.3015
Table 2 Multifractal parameters for soil bulk density (BD), field capacity (FC), saturated hydraulic conductivity (Ks) and soil texture (clay, silt and sand contents) in three plots
Fig. 3 Generalized fractal dimension (Dq) of soil texture (clay (a and b), silt (c and d) and sand contents (e and f)) in different soil layers in three plots. q, probability density weight index; ML, maize land; AL, alfalfa land; NR, natural recovery land.
Fig. 4 Generalized fractal dimension (Dq) of soil bulk density (BD; a and b), field capacity (FC; c and d) and saturated hydraulic conductivity (Ks; e and f) in different soil layers in three plots. q, probability density weight index; ML, maize land; AL, alfalfa land; NR, natural recovery land.
Fig. 5 Multifractal spectrum functions for soil texture (clay (a and b), silt (c and d) and sand contents (e and f)) in different soil layers in three plots. f(α), singularity spectrum; α(q), singularity exponent; ML, maize land; AL, alfalfa land; NR, natural recovery land.
Fig. 6 Multifractal spectrum functions for soil bulk density (BD; a and b), field capacity (FC; c and d) and saturated hydraulic conductivity (Ks; e and f) in different soil layers in three plots. f(α), singularity spectrum; α(q), singularity exponent; ML, maize land; AL, alfalfa land; NR, natural recovery land.
[1]   Abed G A A, Kouzani A, Gyasi-Agyei Y, et al. 2020. Effects of solarisation on soil thermal-physical properties under different soil treatments: A review. Geoderma, 363: 114137, doi: 10.1016/j.geoderma.2019.114137.
doi: 10.1016/j.geoderma.2019.114137
[2]   Altes W K, Sang B I. 2011. Promoting rural development through the use of land consolidation: The case of Korea. International Planning Studies, 16(2): 151-167.
doi: 10.1080/13563475.2011.561060
[3]   Boix-Fayos C, Calvo-Cases A, Imeson A C, et al. 2001. Influence of soil properties on the aggregation of some Mediterranean soils and the use of aggregate size and stability as land degradation indicators. CATENA, 44(1): 47-67.
doi: 10.1016/S0341-8162(00)00176-4
[4]   Caniego F J, Espejo R, Martı́n M A, et al. 2005. Multifractal scaling of soil spatial variability. Ecological Modelling, 182(3-4): 291-303.
doi: 10.1016/j.ecolmodel.2004.04.014
[5]   Chen Y P, Luo S M, Li F M, et al. 2015. Proposals on the sustainable development of agriculture in Yan'an gully regions. Journal of Earth Environment, 6(5): 265-269.
[6]   Chen Y P, Wu J H, Wang H, et al. 2019. Evaluating the soil quality of newly created farmland in the hilly and gully region on the Loess Plateau, China. Journal of Geographical Sciences, 29: 791-802. (in Chinese)
doi: 10.1007/s11442-019-1628-8
[7]   Dong W H, Zhang S, Rao X, et al. 2016. Newly-reclaimed alfalfa forage land improved soil properties comparison to farmland in wheat-maize cropping systems at the margins of oases. Ecological Engineering, 94: 57-64.
doi: 10.1016/j.ecoleng.2016.05.056
[8]   Donovan M, Monaghan R. 2021. Impacts of grazing on ground cover, soil physical properties and soil loss via surface erosion: A novel geospatial modelling approach. Journal of Environmental Management, 287: 112206, doi: 10.1016/j.jenvman.2021.112206.
doi: 10.1016/j.jenvman.2021.112206
[9]   Doran J W, Jones J A, Arshad M A. 1996. Physical tests for monitoring soil quality. Soil Science Society of America Journal, 49: 123-141.
[10]   Dou Y X, Yang Y, An S S, et al. 2020. Effects of different vegetation restoration measures on soil aggregate stability and erodibility on the Loess Plateau, China. CATENA, 185: 104294, doi: 10.1016/j.catena.2019.104294.
doi: 10.1016/j.catena.2019.104294
[11]   Drewry J J. 2006. Natural recovery of soil physical properties from treading damage of pastoral soils in New Zealand and Australia: A review. Agriculture, Ecosystems & Environment, 114(2-4): 159-169.
doi: 10.1016/j.agee.2005.11.028
[12]   Evertsz C J G, Mandelbrot B B. 1992. Multifractal Measures. Berlin: Springer-Verlag, 984.
[13]   Federer C A. 1983. Nitrogen mineralization and nitrification: Depth variation in four New England forest soils. Soil Science Society of America Journal, 47(4): 1008-1014.
doi: 10.2136/sssaj1983.03615995004700050034x
[14]   Fu D G, Wu X N, Duan C J, et al. 2020. Traits of dominant species and soil properties co-regulate soil microbial communities across land restoration types in a subtropical plateau region of Southwest China. Ecological Engineering, 153: 105897, doi: 10.1016/j.ecoleng.2020.105897.
doi: 10.1016/j.ecoleng.2020.105897
[15]   Gao Z Y, Niu F J, Lin Z J, et al. 2021. Fractal and multifractal analysis of soil particle-size distribution and correlation with soil hydrological properties in active layer of Qinghai-Tibet Plateau, China. CATENA, 203: 105373, doi: 10.1016/j.catena.2021.105373.
doi: 10.1016/j.catena.2021.105373
[16]   Guo M M, Wang W L, Kang H L, et al. 2018. Effect of natural vegetation restoration age on slope soil anti-scourability in gully region of Loess Plateau. Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 34: 138-146. (in Chinese)
[17]   He J N, Shi Y, Yu Z W. 2019. Subsoiling improves soil physical and microbial properties, and increases yield of winter wheat in the Huang-Huai-Hai Plain of China. Soil and Tillage Research, 187: 182-193.
doi: 10.1016/j.still.2018.12.011
[18]   Huang Z, Sun L, Liu Y, et al. 2019. Alfalfa planting significantly improved alpine soil water infiltrability in the Qinghai-Tibetan Plateau. Agriculture, Ecosystems & Environment, 285: 106606, doi: 10.1016/j.agee.2019.106606.
doi: 10.1016/j.agee.2019.106606
[19]   Jing Z R, Wang J M, Wang R G, et al. 2019. Using multi-fractal analysis to characterize the variability of soil physical properties in subsided land in coal-mined area. Geoderma, 364, 114054, doi: 10.1016/j.geoderma.2019.114054.
doi: 10.1016/j.geoderma.2019.114054
[20]   Li Q X, Jia Z Q, Liu T, et al. 2017. Effects of different plantation types on soil properties after vegetation restoration in an alpine sandy land on the Tibetan Plateau, China. Journal of Arid Land, 9: 200-209.
doi: 10.1007/s40333-017-0006-6
[21]   Li X D, Shao M A, Zhao C L, et al. 2019. Spatial variability of soil water content and related factors across the Hexi Corridor of China. Journal of Arid Land, 11: 123-134.
doi: 10.1007/s40333-018-0123-x
[22]   Li Y, Li M, Horton R. 2011. Single and joint multifractal analysis of soil particle size distributions. Pedosphere, 21(1): 75-83.
doi: 10.1016/S1002-0160(10)60081-1
[23]   Li Y, Song Y G, Fitzsimmons K E, et al. 2018. New evidence for the provenance and formation of loess deposits in the Ili River Basin, Arid Central Asia. Aeolian Research, 35: 1-8.
doi: 10.1016/j.aeolia.2018.08.002
[24]   Li Y Y, Shao M A. 2006. Change of soil physical properties under long-term natural vegetation restoration in the Loess Plateau of China. Journal of Arid Environments, 64(1): 77-96.
doi: 10.1016/j.jaridenv.2005.04.005
[25]   Liang W J, Wei X. 2020. Relationships between ecosystems above and below ground including forest structure, herb diversity and soil properties in the mountainous area of Northern China. Global Ecology and Conservation, 24: e01228, doi: 10.1016/j.gecco.2020.e01228.
doi: 10.1016/j.gecco.2020.e01228
[26]   Liao K H, Lai X M, Zhou Z W, et al. 2017. Applying fractal analysis to detect spatio-temporal variability of soil moisture content on two contrasting land use hillslopes. CATENA, 157: 163-172.
doi: 10.1016/j.catena.2017.05.022
[27]   Liu X, Zhang G C, Heathman G C, et al. 2009. Fractal features of soil particle-size distribution as affected by plant communities in the forested region of Mountain Yimeng, China. Geoderma, 154(1-2): 123-130.
doi: 10.1016/j.geoderma.2009.10.005
[28]   Lozano-Baez SE, Cooper M, Meli P, et al. 2019. Land restoration by tree planting in the tropics and subtropics improves soil infiltration, but some critical gaps still hinder conclusive results. Forest Ecology and Management, 444: 89-95.
doi: 10.1016/j.foreco.2019.04.046
[29]   Ma J F, Chen Y P, Wang H J, et al. 2020. Newly created farmland should be artificially ameliorated to sustain agricultural production on the Loess Plateau. Land Degradation & Development, 31(17): 2565-2576.
doi: 10.1002/ldr.v31.17
[30]   Marschalko M, Yilmaz I, Bednárik M, et al. 2012. Influence of underground mining activities on the slope deformation genesis: Doubrava Vrchovec, Doubrava Ujala and Staric case studies from Czech Republic. Engineering Geology: 147-148: 37-51.
doi: 10.1016/j.enggeo.2012.07.014
[31]   Mehdi H, Fatemeh A, Marzban F, et al. 2019. Interaction between climate and management on beta diversity components of vegetation in relation to soil properties in arid and semi-arid oak forests, Iran. Journal of Arid Land, 11: 43-57.
doi: 10.1007/s40333-018-0024-z
[32]   Min X Y, Li X J, Li Q C. 2017. Influence of mechanical compaction on reclaimed soil particle size distribution multifractal characteristics. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 33: 274-283. (in Chinese)
[33]   Morató M C, Castellanos M T, Bird N R, et al. 2017. Multifractal analysis in soil properties: Spatial signal versus mass distribution. Geoderma, 287: 54-65.
doi: 10.1016/j.geoderma.2016.08.004
[34]   Pachepsky Y A, Kravchenko A N. 2004. Soil Variability Assessment with Fractal Techniques. Florida: CRC Press, 617-638.
[35]   Paterson S, Minasny B, McBratney A. 2018. Spatial variability of Australian soil texture: A multiscale analysis. Geoderma, 309: 60-74.
doi: 10.1016/j.geoderma.2017.09.005
[36]   Perring M P, Standish R J, Hulvey K B, et al. 2012. The Ridgefield Multiple Ecosystem Services Experiment: Can restoration of former agricultural land achieve multiple outcomes? Agriculture, Ecosystems & Environment, 163: 14-27.
doi: 10.1016/j.agee.2012.02.016
[37]   Premo L S. 2004. Local spatial autocorrelation statistics quantify multi-scale patterns in distributional data: an example from the Maya Lowlands. Journal of Archaeological Science, 31(7): 855-866.
doi: 10.1016/j.jas.2003.12.002
[38]   Prévost M. 2004. Predicting soil properties from organic matter content following mechanical site preparation of forest soils. Soil Science Society of America Journal, 68(3): 943-949.
doi: 10.2136/sssaj2004.9430
[39]   Qi F, Zhang R H, Liu X, et al. 2018. Soil particle size distribution characteristics of different land-use types in the Funiu mountainous region. Soil and Tillage Research, 184: 45-51.
doi: 10.1016/j.still.2018.06.011
[40]   Ren Z P, Zhu L J, Wang B, et al. 2016. Soil hydraulic conductivity as affected by vegetation restoration age on the Loess Plateau, China. Journal of Arid Land, 8: 546-555.
doi: 10.1007/s40333-016-0010-2
[41]   Šípek V, Hnilica J, Vlček L, et al. 2020. Influence of vegetation type and soil properties on soil water dynamics in the Šumava Mountains (Southern Bohemia). Journal of Hydrology, 582: 124285, doi: 10.1016/j.jhydrol.2019.124285.
doi: 10.1016/j.jhydrol.2019.124285
[42]   Stanić F, Tchiguirinskaia I, Versini P A, et al. 2021. A new multifractal-based grain size distribution model. Geoderma, 404: 115294, doi: 10.1016/j.geoderma.2021.115294.
doi: 10.1016/j.geoderma.2021.115294
[43]   Teng M J, Zeng L X, Xiao W F, et al. 2017. Spatial variability of soil organic carbon in Three Gorges Reservoir area, China. Science of the Total Environment, 599-600: 1308-1316.
doi: 10.1016/j.scitotenv.2017.05.085
[44]   Tripathi N, Singh R S, Singh J S. 2009. Impact of post-mining subsidence on nitrogen transformation in southern tropical dry deciduous forest, India. Environmental Research, 109: 258-266.
doi: 10.1016/j.envres.2008.10.009 pmid: 19147131
[45]   Wang J M, Wang P, Qin Q, et al. 2017. The effects of land subsidence and rehabilitation on soil hydraulic properties in a mining area in the Loess Plateau of China. CATENA, 159: 51-59.
doi: 10.1016/j.catena.2017.08.001
[46]   Wang J M, Lu X, Feng Y, et al. 2018a. Integrating multi-fractal theory and geo-statistics method to characterize the spatial variability of particle size distribution of mine soils. Geoderma, 317: 39-46.
doi: 10.1016/j.geoderma.2017.12.027
[47]   Wang J M, Qin Q, Guo L L, et al. 2018b. Multi-fractal characteristics of three-dimensional distribution of reconstructed soil pores at opencast coal-mine dump based on high-precision CT scanning. Soil and Tillage Research, 182: 144-152.
doi: 10.1016/j.still.2018.05.013
[48]   Wang M R, Liu H J, Lennartz B. 2021. Small-scale spatial variability of hydro-physical properties of natural and degraded peat soils. Geoderma, 399: 115123, doi: 10.1016/j.geoderma.2021.115123.
doi: 10.1016/j.geoderma.2021.115123
[49]   Wang Y Q, Zhang X C, Han F P. 2008. Profile variability of soil properties in check dam on the Loess Plateau and its functions. Environmental Science, 29(4): 1020-1026. (in Chinese)
[50]   Wu Z L, Deng Y S, Cai C F, et al. 2021. Multifractal analysis on spatial variability of soil particles and nutrients of Benggang in granite hilly region, China. CATENA, 207: 105594, doi: 10.1016/j.catena.2021.105594.
doi: 10.1016/j.catena.2021.105594
[51]   Xia J B, Ren R R, Chen Y P, et al. 2020. Multifractal characteristics of soil particle distribution under different vegetation types in the Yellow River Delta chenier of China. Geoderma, 368: 114311, doi: 10.1016/j.geoderma.2020.114311.
doi: 10.1016/j.geoderma.2020.114311
[52]   Ying L X, Dong Z J, Wang J, et al. 2020. Rural economic benefits of land consolidation in mountainous and hilly areas of southeast China: Implications for rural development. Journal of Rural Studies, 74: 142-159.
doi: 10.1016/j.jrurstud.2020.01.007
[53]   Zhang X, Zhao W W, Wang L X, et al. 2019. Relationship between soil water content and soil particle size on typical slopes of the Loess Plateau during a drought year. Science of the Total Environment, 15(648): 943-954.
[54]   Zhou H, Li B G, Lv Y Z, et al. 2010. Multifractal characteristics of soil porestructure under different tillage systems. Acta Pedologica Sinica, 47(6): 1094-1100. (in Chinese)
[55]   Zhu X M. 1995. More on land management measures of loess plateau. Journal of Soil and Water Conservation, (1): 4-11. (in Chinese)
[1] LIU Yufang, YANG Qingwen, PEI Xiangjun, LI Jingji, WANG Shuangcheng, HUANG Zhenfu, HAN Wei, ZHENG Tianliang. Spatial distribution of soil salinization under the influence of human activities in arid areas, China[J]. Journal of Arid Land, 2024, 16(10): 1344-1364.
[2] WANG Jing, WEI Yulu, PENG Biao, LIU Siqi, LI Jianfeng. Spatiotemporal variations in ecosystem services and their trade-offs and synergies against the background of the gully control and land consolidation project on the Loess Plateau, China[J]. Journal of Arid Land, 2024, 16(1): 131-145.
[3] Benjamin DAVIDSON, Elli GRONER. An arthropod community beyond the dry limit of plant life[J]. Journal of Arid Land, 2021, 13(6): 629-638.
[4] Rentao LIU, STEINBERGER Yosef, Jingwei HOU, Juan ZHAO, Jianan LIU, Haitao CHANG, Jing ZHANG, Yaxi LUO. Conversion of cropland into agroforestry land versus naturally-restored grassland alters soil macro-faunal diversity and trophic structure in the semi-arid agro-pasture zone of northern China[J]. Journal of Arid Land, 2019, 11(2): 306-317.
[5] Beibei SHEN, Jinglu WU, Zhonghua ZHAO. Organochlorine pesticides and polycyclic aromatic hydrocarbons in water and sediment ofthe Bosten Lake, Northwest China[J]. Journal of Arid Land, 2017, 9(2): 287-298.
[6] ZHU Yangchun, ZHAO Xueyong, LIAN Jie, CHEN Min. Variation of Zn content in soils under different land-use types in the Hetao oasis, Inner Mongolia of China[J]. Journal of Arid Land, 2016, 8(6): 861-870.
[7] LIU Rentao, ZHU Fan, Yosef STEINBERGER. Ground-active arthropod responses to rainfall-induced dune microhabitats in a desertified steppe ecosystem, China[J]. Journal of Arid Land, 2016, 8(4): 632-646.
[8] Michael J JACOBS, Catherine A SCHLOEDER, Philip D TANIMOTO. Dryland agriculture and rangeland restoration priorities in Afghanistan[J]. Journal of Arid Land, 2015, 7(3): 391-402.
[9] YuBi YAO, RunYuan WANG, JinHu YANG, Ping YUE, DengRong LU, GuoJu XIAO, Yang WANG, LinChun LIU. Changes in terrestrial surface dry and wet conditions on the Loess Plateau (China) during the last half century[J]. Journal of Arid Land, 2013, 5(1): 15-24.
[10] Jilili ABUDUWAILI, Yang TANG, Mireban ABULIMITI, DongWei LIU, Long MA. Spatial distribution of soil moisture, salinity and organic matter in Manas River watershed, Xinjiang, China[J]. Journal of Arid Land, 2012, 4(4): 441-449.
[11] Yan LIU, DaoYuan ZHANG, HongLan YANG, MeiYing LIU, Xiang SHI. Fine-scale genetic structure of Eremosparton songoricum and implication for conservation[J]. Journal of Arid Land, 2010, 2(1): 26-32.