Advertisement

Environmental Science and Pollution Research

, Volume 26, Issue 19, pp 19365–19378 | Cite as

Linking the reclaimed soils and rehabilitated vegetation in an opencast coal mining area: a complex network approach

  • Zhaotong Zhang
  • Jinman WangEmail author
  • Yu Feng
Research Article
  • 120 Downloads

Abstract

As two main factors, soil and vegetation play key roles in land rehabilitation and ecological remediation of mining areas. There is a complex interaction between soil and vegetation, and understanding the mechanisms of interaction between soil and vegetation is of great significance for land rehabilitation and ecological remediation in mining areas. This study introduced complex network method to analyze the complex interaction systematically. A survey of vegetation and soil properties in 70 reclaimed plots was carried out in the Anjialing and Antaibao opencast coal-mines in Shanxi, China. The indices of soil and vegetation acted as nodes, and the interaction between these indices as sides to establish a soil-vegetation network. Calculating the network indices to analyze the structure of a complex network and explore the mechanism of interaction between soil and vegetation. SOM (soil organic matter) was at the core of the soil-vegetation interaction network. The average path length of the soil-vegetation network was 1.8, with a faster rate of information transfer. The soil-vegetation network consisted of three clusters (soil physical property cluster, soil chemical property cluster, and vegetation cluster), in which the soil chemical property cluster owned the highest clustering coefficient and the largest number of triangles, and it was most stable and the interaction within the cluster was strongest. The soil-vegetation network was stable and the connectivity of the network had robustness to node failures. The scale of the network became larger and the network became tighter and more stable with the increase of reclamation time. Some measures should be conducted to promote vegetation restoration by improving important soil nodes, e.g., surface soil covering, applying organic fertilizer, and planting nitrogen-fixing plants.

Keywords

Land reclamation Soil Vegetation Interaction Complex network Opencast coal-mine 

Abbreviations

AQ

Arbor quantity

ADBH

Average diameter at breast height

AH

Average height

CD

Canopy density

HC

Herb coverage

BD

Soil bulk density

RC

Rock content

TN

Total nitrogen

SOM

Soil organic matter

AP

Available phosphorus

AK

Available potassium

SPSS

Statistical product and service solutions

CO2

Carbon dioxide

LUCC

Land use/cover change

CV

Coefficient of variation

I

West dump of the Anjialing mine

II

Internal dump of the Antaibao mine

III

West dump of the Antaibao mine

IV

South dump of the Antaibao mine

Notes

Funding information

This research was financially supported by the National Natural Science Foundation of China (41877532, 41701607), the Beijing Higher Education Young Elite Teacher Project (YETP0638), and the Fundamental Research Funds for the Central Universities of China (2652015179, 2652015336).

References

  1. Albert R, Barabási A (2002) Statistical mechanics of complex networks. Springer Berlin Heidelberg 74(1)Google Scholar
  2. Alday JG, Marrs RH, Martinez-Ruiz C (2011) Vegetation convergence during early succession on coal wastes: a 6-year permanent plot study. J Veg Sci 22:1072–1083.  https://doi.org/10.1111/j.1654-1103.2011.01308.x
  3. Alday JG, Marrs RH, Martínez-Ruiz C (2012) Soil and vegetation development during early succession on restored coal wastes: a six-year permanent plot study. Plant Soil 353(1–2):305–320Google Scholar
  4. An MY, Han YG, Xu L, Wang XR, Ao C, Pang DB (2019) KINEROS2-based simulation of total nitrogen loss on slopes under rainfall events. Catena 177:13–21Google Scholar
  5. Beygelzimer A, Grinstein GE, Linsker R, Rish I (2005) Improving network robustness by edge modification. Physica A: Statistical Mechanics and its Applications 357(3):593–612Google Scholar
  6. Boldt-Burisch K, Naeth MA, Schneider BU, Hüttl RF (2015) Linkage between root systems of three pioneer plant species and soil nitrogen during early reclamation of a mine site in Lusatia, Germany. Restor Ecol 23:357–365Google Scholar
  7. Brandes U (2001) A faster algorithm for betweenness centrality. J Math Sociol 25:163–177Google Scholar
  8. Buibas M, Khanna HS, Silva GA (2009) Complex network mapping. EP 2087654 A2Google Scholar
  9. Burylo M, Hudek C, Rey F (2010) Soil reinforcement by the roots of six dominant species on eroded mountainous marly slopes (southern Alps, France). Catena 84(1–2):70–78Google Scholar
  10. Cao XB, Hong C, Du WB, Zhang J (2013) Improving the network robustness against cascading failures by adding links. Chaos Solitons Fractals 57:35–40Google Scholar
  11. Cárdenas JP, Santiago A, Tarquis AM, Losada JC, Borondo F, Benito RM (2010) Soil porous system as heterogeneous complex network. Geoderma 160(1):13–21Google Scholar
  12. Chen BP (2012) Application of grey correlative analysis in the analysis of primary factor influencing products cost. Electronic Sci Technol 25(5):145–147Google Scholar
  13. Ciarkowska K (2017) Organic matter transformation and porosity development in non-reclaimed mining soils of different ages and vegetation covers: a field study of soils of the zinc and lead ore area in SE Poland. J Soils Sediments 17(8):2066-2079Google Scholar
  14. Ding QP (2006) Study on soil nutrients and organic carbon in the soil reclaimed for different years. Journal of Anhui Agricultural Sciences 34(17):4360-4363Google Scholar
  15. Dorogovtsev SN, Mendes JFF, Samukhin AN (2002) Principles of statistical mechanics of uncorrelated random networks. Nucl Phys 666(3):396–416Google Scholar
  16. Feng TY, Wang YM, Duan XM (2005) A study on the relationship between capital structure of enterprise and its determinant— comparison and application of multivariate linear regression model and neural network model. Syst Eng 23(1):42–48Google Scholar
  17. Fernandez C (2003) Estimating water erosion and sediment yield with GIS, RUSLE, and SEDD. J Soil Water Conserv 58:128–136Google Scholar
  18. Frouz J, Prach K, Pižl V, Háněl L, Starý J, Tajovský K, Materna J, Balík V, Kalčík J, Řehounková K (2008) Interactions between soil development, vegetation and soil fauna during spontaneous succession in post mining sites. Eur J Soil Biol 44(1):109–121Google Scholar
  19. Han Y, Yu X, Wang X (2013) Net anthropogenic phosphorus inputs (NAPI) index application in mainland China. Chemosphere 90(2):329–337Google Scholar
  20. Han Y, Fan Y, Yang P (2014) Net anthropogenic nitrogen inputs (NANI) index application in mainland China. Geofis Int 213(1):87–94Google Scholar
  21. Heras MDL, Merino-Martín L, Nicolau JM (2009) Effect of vegetation cover on the hydrology of reclaimed mining soils under Mediterranean-continental climate. Catena 77:39–47Google Scholar
  22. Hetrick BA, Wilson GW, Figge DA (1994) The influence of mycorrhizal symbiosis and fertilizer amendments on establishment of vegetation in heavy metal mine spoil. Environ Pollut 86(2):171–179Google Scholar
  23. Huang L, Zhang P, Hu Y, Yang Z (2015) Vegetation succession and soil infiltration characteristics under different aged refuse dumps at the Heidaigou opencast coal mine. Glob Ecol Conserv 4:255–263Google Scholar
  24. Jeloudar ZJ, Arzani H, Jafari M, Kavian A, Zahedi G, Azarnivand H (2010) Vegetation community in relation to the soil characteristics of Rineh rangeland, Iran. Caspian journal of environmental sciences 8(2):141-150Google Scholar
  25. Li X (2009) Research and application of grey canonical correlation analysis. Comput Eng Sci 31(6):121–121Google Scholar
  26. Li GZ (2012) Conducting and interpreting canonical correlation analysis in foreign language education research. J Chongqing Univ Technol (Social Science) 26(3):113–119Google Scholar
  27. Li S, Di X, Wu D, Zhang J (2013) Effects of sewage sludge and nitrogen fertilizer on herbage growth and soil fertility improvement in restoration of the abandoned opencast mining areas in Shanxi, China. Environ Earth Sci 70(7):3323–3333Google Scholar
  28. Liang HQ, Zhang X, Peng Z, Zhou J (2009) Canonical correlation analysis of soil nutrients, microorganisms and enzyme activities in vegetation restoration areas of degraded and eroded soils in northwestern Hunan Province, China. Front For China 4(4):443–449Google Scholar
  29. Liu X, Zhang W, Yang F, Zhou X, Liu Z, Qu F, Lian S, Wang C, Tang X (2012) Changes in vegetation–environment relationships over long-term natural restoration process in middle Taihang Mountain of North China. Ecol Eng 49:193–200Google Scholar
  30. Malik A, Scullion J (1998) Soil development on restored opencast coal sites with particular reference to organic matter and aggregate stability. Soil Use Manag 14:234–239Google Scholar
  31. Mariano MDLH, Merinomartín L, Espigares T, Nicolau JM (2014) Soil erosion-vegetation interactions in Mediterranean-dry reclaimed mining slopes, EGU General Assembly Conference. EGU General Assembly Conference AbstractsGoogle Scholar
  32. Martin MA, Reyes M (2008) A fractal interaction model for winding paths through complex distributions: application to soil drainage networks. Pure Appl Geophys 165(6):1153–1165Google Scholar
  33. Mcnab WH, Browning SA, Simon SA, Fouts PE (1999) An unconventional approach to ecosystem unit classification in western North Carolina, USA. For Ecol Manag 114(2–3):405–420Google Scholar
  34. Merdun H (2011) Self-organizing map artificial neural network application in multidimensional soil data analysis. Neural Comput & Applic 20(8):1295–1303Google Scholar
  35. Min B, Yi S, Lee KM, Goh KI (2014) Network robustness of multiplex networks with interlayer degree correlations. Phys Rev E Stat Nonlinear Soft Matter Phys 89(4):042811Google Scholar
  36. Morohosi H (2010) Measuring the network robustness by Monte Carlo estimation of shortest path length distribution. Math Comput Simul 81(3):551–559Google Scholar
  37. Newman MEJ (2003) The structure and function of complex networks. SIAM Rev 45(2):167–256Google Scholar
  38. Newman MEJ (2005) A measure of betweenness centrality based on random walks. Soc Networks 27:39–54Google Scholar
  39. Ni C, Sugimoto CR, Jiang J (2011) Degree, closeness, and betweenness: application of group centrality measurements to explore macro-disciplinary evolution diachronically. In Proceedings of ISSI 2011, Durban, South AfricaGoogle Scholar
  40. Pan L, Fanzhen XU, Sha L (2015) Effect of biochar on soil properties and rubber (hevea brasilensis) seedling biomass. Mountain Research 4:449-456Google Scholar
  41. Peng W, Song T, Zeng F, Wang K, Du H, Lu S (2012) Relationships between woody plants and environmental factors in karst mixed evergreen-deciduous broadleaf forest. Southwest China J Food Agric Environ 10:890–896Google Scholar
  42. Poisot T, Gravel D (2014) When is an ecological network complex? Connectance drives degree distribution and emerging network properties. Peerj 2(2):e251Google Scholar
  43. Prach K, Pyšek P, Jarošík V (2007) Climate and pH as determinants of vegetation succession in central European man-made habitats. J Veg Sci 18(5):701–710Google Scholar
  44. Pu M, Mitchell RJ, Jones RH (1997) Root distribution of two tree species under a heterogeneous nutrient environment. J Appl Ecol 34(3):645–656Google Scholar
  45. Purbosari K (2015) Exploring the roles of social networks centrality in indonesian public employees: degree, betweenness and closeness. Proceedings of the third international conference on Asian studies 20Google Scholar
  46. Qiu Y, Zhang JT (2000) The ordination axes clustering based on detrended canonical correspondence analysis ordination and its application to the analysis of the ecological gradients of plant communities. Acta Ecol Sin 1(2):199–206Google Scholar
  47. Rodiek J (1978) Mined land rehabilitation in the semiarid regions of the United States. Landsc Res 3(3):17–19Google Scholar
  48. Samec M, Santiago A, Cárdenas JP, Benito RM, Tarquis AM, Mooney SJ, Ak DK (2013) Quantifying soil complexity using network models of soil porous structure. Nonlinear Process Geophys 20:41–45Google Scholar
  49. Saramãki J, Kivelã M, Onnela JP, Kaski K, Kertãsz J (2007) Generalizations of the clustering coefficient to weighted complex networks. Phys Rev E Stat Nonlinear Soft Matter Phys 75(2):027105Google Scholar
  50. Shi Z, Wang Y, Yu P, Xu L, Xiong W, Guo H (2008) Effect of rock fragments on the percolation and evaporation of forest soil in Liupan Mountains, China. Acta Ecol Sin 28(12):6090–6098Google Scholar
  51. Sun C, Xu Y, Yang X (2007) A tag-based network evolution mechanism for online communities. International conference on natural computation 5:487-491Google Scholar
  52. Tian C, Yang XB, Jun LI, Cao YS, Zhang W, Liu Y, Ke-Jiao BI (2011) Hydrological effects of forest litters and soil in the slope of north mountain of Hebei province. J Soil Water Conserv 25(2):97–103Google Scholar
  53. Wang J, Bo FU, Qiu Y, Chen L, Li YU (2003) Spatial distribution patterns of soil nutrients in a small catchment of the Loess plateau-Kriging method. Geogr Res 5(2):71–73Google Scholar
  54. Wang J, Zhang M, Bai Z, Yang R, Guo L (2014) Multi-fractal characteristics of reconstructed soil particle in opencast coal mine dump in loess area. Trans Chin Soc Agric Eng 30:230–238Google Scholar
  55. Wang J, Yang R, Bai Z (2015) Spatial variability and sampling optimization of soil organic carbon and total nitrogen for minesoils of the Loess plateau using geostatistics. Ecol Eng 82:159–164Google Scholar
  56. Wardani AK, Purqon A (2016) Thermal conductivity prediction of soil in complex plant soil system using artificial neural networks. J Phys Conf Ser 739:012007Google Scholar
  57. Wen ZM, Jiao F, Jing LI (2009) Identification of the natural communities in vegetation succession using grey relational analysis in loess hilly region, China. Research of Soil & Water Conservation 16(5):40-44Google Scholar
  58. Wu P, Gong H, Zhou D (2012) Identification of key changed land use type in LUCC: a case study of Guishui river basin. International Conference on Geoinformatics. IEEE, Hongkong, China.Google Scholar
  59. Zhang L, Wang J, Bai Z, Lv C (2015) Effects of vegetation on runoff and soil erosion on reclaimed land in an opencast coal-mine dump in a loess area. Catena 128:44–53Google Scholar
  60. Zhang B, Le Y, Zhang S (2016) Assessment on characteristics of LUCC process based on complex network in modern Yellow River Delta, Shandong Province of China. Earth Sci Inf 9(1):83–93Google Scholar
  61. Zhao X, Chunlan HE (2012) The effect of Eucalyptus uraphylla spp.introduction on soil physical properties in a mountainous region of Yunnan. Ecol Environ Sci 21(11):1810–1816Google Scholar
  62. Zheng SA, Chang QR, Yan-Bing QI (2006) Soil texture grade and mineral element of plantations with different ages on Loess plateau. Agric Res Arid Areas 24(6):94–97Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.College of Land Science and TechnologyChina University of GeosciencesBeijingPeople’s Republic of China
  2. 2.Key Laboratory of Land Consolidation and Rehabilitation, Ministry of Natural ResourcesBeijingPeople’s Republic of China

Personalised recommendations