نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانش آموخته کارشناسی ارشد گروه علوم خاک دانشکده علوم کشاورزی، دانشگاه گیلان

2 دانشیار گروه علوم خاک دانشکده علوم کشاورزی، دانشگاه گیلان

چکیده

در این مطالعه شاخص‌های کیفیت خاک با استفاده از تحلیل‌های‌چند متغیره در سه کاربری مختلف در منطقه توتکابن استان گیلان مورد ارزیابی قرار گرفت. 60 نمونه خاک مرکب از دو عمق صفر تا 15 و 15 تا 30 سانتی‌متری از سه کاربری جنگل، زراعی و مرتع برداشت شد. با استفاده از روش تجزیه به مؤلفه‌های اصلی(PCA) ، از میان 12 ویژگی موثر بر کیفیت خاک، چهار ویژگی شامل درصد رس، میانگین وزنی قطر خاکدانه، کربن آلی و فسفر قابل دسترس به‌عنوان حداقل ویژگی‌های مؤثر بر کیفیت خاک انتخاب شدند. سپس کیفیت خاک با استفاده از دو مدل شاخص کیفیت تجمعی (IQI) و شاخص کیفیت نمورو (NQI) به روش‌های نمره‌دهی خطی و غیرخطی (LS و NLS) و هرکدام در دو مجموعه کل داده‌ها (TDS) و داده‌های حداقل (MDS) ارزیابی شد. برای اولویتدهی و ارزیابی شاخص‌های کیفیت خاک از مجموع دو معیار شاخص حساسیت و درصد راندمان استفاده شد. نتایج نشان داد که شاخص‌های کیفیت خاک به روش نمره‌دهی خطی نسبت به غیرخطی تفاوت کیفیت خاک بین کاربری‌های مختلف را بهتر نشان می‌دهد؛ به‌طوری‌که کاربری جنگل و زراعی در مقایسه با مرتع از میانگین شاخص کیفیت خاک بالاتری برخوردار بود.. مقادیر درصد راندمان نشان داد که شاخص‌های IQI-LS و IQI-NLS برای مجموعه MDS در مقایسه با TDS با دارا بودن میزان راندمان 75 درصد از کارآیی بالاتری برخوردار هستند. براساس اولویت‌دهی شاخص‌های کیفیت خاک، شاخص IQI-LS-MDS اولین رتبه را به خود اختصاص داد، بر این اساس از بین شاخص‌های کیفیت خاک، IQI-LS-MDSبرای بررسی وضعیت کلی خاک در منطقه مطالعاتی قابلیت بیشتری دارد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Assessment of soil quality indices using multivariate analysis in different land uses (case study: Tootkabon, Guilan province)

نویسندگان [English]

  • Mozhdeh Taghipour 1
  • Nafiseh Yaghmaeian Mahabadi 2
  • Mahmoud Shabanpour 2

1 Former MSc. Student,, Department of Soil Science, Faculty of Agricultural Sciences, University of Guilan, Iran

2 Associate Professor, Department of Soil Science, Faculty of Agricultural Sciences, University of Guilan, Iran

چکیده [English]

Introduction: Soil quality index is used as a quantitative tool for assessing the impact of land use and management practices on soil condition. Soil quality is a sensitive indicator for revealing the dynamics of soil conditions, and it may vary with different land use and ecological restoration measures. The land use affects the physical and chemical properties, biological processes, and land productivity, which lead to the change in soil quality. Land use change and agricultural development can lead to degradation, erosion and reduction of surface and subsurface soil quality. In most of the conducted studies, the surface soil quality has been evaluated; but these studies provide incomplete information because subsurface soil have the greatest impact on soil function and crop. In spite of various soil quality assessment methods developed in former researches, there are fewer attempts for selecting suitable and sensitive soil quality index, especially in different land uses. In this study, soil quality indicators were evaluated using multivariate analysis in three different land uses to select the most suitable and appropriate soil quality index in Tootkabon area of Guilan province.

Materials and Methods: The study area is located in Tootkabon in Guilan province (latitude 36º 53' 21" N, longitude 49º 33' 44" E). Parent material is limestone and geomorphologic units that are comprised of hill land and plateau. In order to achieve the objectives of the research, 20 composite soil samples were taken from two depths of 0 to 15 and 15 to 30 cm from each of the land use, including forest, cropland and rangeland (60 soil samples in total) with the same parent material. The three land uses were located next to each other and at a close distance. In this research, using the principal component analysis (PCA) method, among 12 physical, chemical and biological soil indicators as total data set (TDS), clay percent, mean weight diameter, organic matter and available phosphorus were determined as the minimum data set. Then, the soil quality was evaluated by integrated quality index (IQI) and Nemoro quality index (NQI) using two linear and non-linear scoring methods (LS and NLS) and two soil indicator selection approaches, a total data set (TDS) and a minimum data set (MDS). Finally, to prioritize the soil quality indices based on sensitivity index (SI) and efficiency ratio (ER), the ranks of both criteria were summed and then made appropriate decision. All soil parameters were tested using one-way analysis of variance and the differences among means were analyzed using Duncan's significant difference test at the probability level of 0.05.

Results and Discussion: The results of the present study showed that some soil properties including clay percentage, mean weight diameter, organic matter and available phosphorus had the greatest effect on soil quality in the study area. Most of the soil properties in rangeland and forest had a higher stratification ratio compared to cropland. The soil quality indices calculated using linear function for MDS indicated soil quality of forest and cropland were higher than rangeland. Maximum SI belonged to IQI-LS-TDS and IQI-LS-MDS with values of 1.56 and 1.40, respectively. Efficiency ratios (ER) were calculated to specify the power of each soil quality index being as representative index for whole soil parameters set. IQI-LS-MDS and IQI-NLS-MDS have the highest value of ER (75.0 %), it is obviously deducted that these developed soil quality indices correlate with much indicators than other indices. It has more efficiency ratio and therefore represents the soil overall condition highly. Finally prioritizing according to ranks of SI and ER showed that IQI-LS-MDS is the most suitable approach in soil quality assessment of study area.

Conclusion: Minimum data set selection using principal component analysis as a multivariate statistical method could adequately represent total data set method. Therefore, it seems to be an appropriate approach for choosing more effective indicators with respect to saving time and money in the developing countries The linear soil quality indices showed higher capability than non-linear indices to differentiate soil quality among different land uses. Overall results of the prioritization soil quality indices imply that the IQI-LS-MDS has the most efficiency and sensitivity for variation in land uses, so it is suggested to use this quality index for further and comprehensive soil quality assessments plans.

کلیدواژه‌ها [English]

  • Land use change
  • Sensitivity index
  • Efficiency ratio
  • Scoring methods
  1. Andrews, S. S., Karlen, D. L., and Mitchell, J. P. 2002. A comparison of soil quality indexing methods for vegetable production systems in Northern California. Agriculture, ecosystems and environment, 90(1): 25-45.
  2. Armenise, E., Redmile-Gordon, M. A., Stellacci, A. M., Ciccarese, A., and Rubino, P. 2013. Developing a soil quality index to compare soil fitness for agricultural use under different managements in the Mediterranean environment. Soil and Tillage Research, 130: 91-98.
  3. Askari, M. S., and Holden, N. M. 2014. Indices for quantitative evaluation of soil quality under grassland management. Geoderma, 230: 131-142.
  4. Askari, M. S., and Holden, N. M. 2015. Quantitative soil quality indexing of temperate arable management systems. Soil and Tillage Research, 150: 57-67.
  5. Babu, S., Mohapatra, K. P., Yadav, G. S., Lal, R., Singh, R., Avasthe, R. K., Das, A., Chandra, P., Gudade, B. A., and Kumar, A. 2020. Soil carbon dynamics in diverse organic land use systems in North Eastern Himalayan ecosystem of India. Catena, 194: 104785.
  6. Bakhshandeh, E., Hossieni, M., Zeraatpisheh, M., and Francaviglia, R. 2019. Land use change effects on soil quality and biological fertility: a case study in northern Iran. European Journal of Soil Biology, 95: 103119.
  7. Banaei, H. M. 1998. Soil moisture and temperature regimes map of Iran (1: 2500000). Soil and Water Research Institute. (in Persian)
  8. Bi, C. J., Chen, Z. L., Wang, J. and Zhou, D. 2013. Quantitative assessment of soil health under different planting patterns and soil types. Pedosphere, 23(2): 194-204
  9. Blake, G. R., and Hartge, K. H. 1986. Bulk density. Methods of soil analysis: Part 1 Physical and mineralogical methods, 5: 363-375.
  10. Cao, Z. H., and Zhou, J. M. 2008. Soil quality of China.Science Press, Beijing.
  11. Corral-Fernández, R., Parras-Alcántara, L., and Lozano-García, B. 2013. Stratification ratio of soil organic C, N and C: N in Mediterranean evergreen oak woodland with conventional and organic tillage. Agriculture, ecosystems and environment, 164: 252-259.
  12. Davari, M., Gholami, L., Nabiollahi, K., Homaee, M., and Jafari, H. J. 2020. Deforestation and cultivation of sparse forest impacts on soil quality (case study: West Iran, Baneh). Soil and Tillage Research, 198: 104504.
  13. Donovan, M., and 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.
  14. Fang, X., Xue, Z., Li, B., and An, S. 2012. Soil organic carbon distribution in relation to land use and its storage in a small watershed of the Loess Plateau, China. Catena, 88: 6-13.
  15. Franzluebbers, A. J. 2002. Soil organic matter stratification ratio as an indicator of soil quality. Soil and Tillage Research, 66(2): 95-106.
  16. Gee, G. W., Bauder, J. W., and Klute, A. 1986. Methods of soil analysis, part 1, physical and mineralogical methods. Soil Science Society of America Book Series. American Society of Agronomy, Inc. and Soil Science Society of America, Inc. Madison, Wisconsin, 404-410.
  17. Govaerts, B., Sayre, K. D., and Deckers, J. 2006. A minimum data set for soil quality assessment of wheat and maize cropping in the highlands of Mexico. Soil and tillage research, 87(2): 163-174.
  18. Guo, L., Sun, Z., Ouyang, Z., Han, D., and Li, F. 2017. A comparison of soil quality evaluation methods for Fluvisol along the lower Yellow River. Catena, 152: 135-143.
  19. Hamidi Nehrani, S., Askari, M. S., Saadat, S., Delavar, M. A., and Taheri, M. 2020. Using multivariate analysis to evaluate soil quality in agricultural lands of Zanjan province. Applied Soil Research, 8(2): 158-173. (in Persian with English abstract)
  20. Hesse, P. R. 1971. A text book of soil chemical analysis. John Murray. London. 556 p.
  21. Kamali, K., Zehtabian, G., Mesbahzadeh, T., Arabkhedri, M., Shohab Arkhazloo, H., and Moghadamnia, A. 2021. Determining the most effective properties to evaluate soil quality of agriculture lands in Mohammadshahr plain of Karaj. Water and Soil, 35(2), 251-266. (in Persian with English abstract)
  22. Kavian, A., Azmoodeh, A., and Solaimani, K. 2014. Deforestation effects on soil properties, runoff and erosion in northern Iran. Arabian Journal of Geosciences, 7(5): 1941-1950.
  23. Kemper, W. D., and Rosenau, R. C. 1986. Aggregate stability and size distribution.
  24. Knudsen, D., Peterson, G. A. and Pratt, P. F. 1982. Lithium, sodium and potassium. In: A.L. Page (Ed.). Methods of Soil Analysis. Part 2. America Society of Agronomy. Madison, WI. 225-246.
  25. Li, D., Gao, G., Lü, Y., and Fu, B. 2016. Multi-scale variability of soil carbon and nitrogen in the middle reaches of the Heihe River basin, northwestern China. Catena, 137: 328-339.
  26. Liu, J., Wu, L.C., Chen, D., Yu, Z.G., Wei, C.J., 2018. Development of a soil quality index for Camellia oleifera forestland yield under three different parent materials in southern China. Soil and Tillage Research. 176, 45–50.
  27. Liu, Z., Zhou, W., Shen, J., Li, S., He, P., and Liang, G. 2014. Soil quality assessment of Albic soils with different productivities for eastern China. Soil and Tillage Research, 140, 74-81.
  28. Macias, M.D.G., Carbajal, N., Vargas, J.T., 2020. Soil deterioration in the southern Chihuahuan Desert caused by agricultural practices and meteorological events. J. Arid Enviro. 176: 104-097.
  29. Madejón, E., Murillo, J.M., Moreno, F., López, M.V., Arrue, J.L., Alvaro-Fuentes, J.,Cantero, C., 2009. Effect of long-term conservation tillage on soil biochemicalproperties in Mediterranean Spanish areas. Soil and Tillage Research. 105: 55–62.
  30. Mamehpour, N., S. Rezapour, and N. Ghaemian. 2021. Quantitative assessment of soil quality indices for urban croplands in a calcareous semi-arid ecosystem. Geoderma 382: 114781.
  31. Molaei Arpnahi, M., Salehi, M., Karimian Egbal, M., and Mosleh, Z. 2020. Effect of land-use change on some physical and chemical indices of soil quality in the Bazoft region, (Chaharmahal-va-Bakhtiari province). Water and Soil, 34(3): 707-720. (in Persian with English abstract) 
  32. Nabiollahi, K., Golmohamadi, F., Taghizadeh-Mehrjardi, R., Kerry, R., and Davari, M. 2018. Assessing the effects of slope gradient and land use change on soil quality degradation through digital mapping of soil quality indices and soil loss rate. Geoderma, 318: 16-28.
  33. Olsen, S. R., Cole, C. V., Watanabe, F. S. and Dean, L. A. 1954. Estimation of Available Phosphorous in Soils by Extraction with Sodium Bicarbonate. U.S. Department of Agriculture: Washington, D.C., USDA Circ. 939.
  34. Rahmanipour, F., Marzaioli, R., Bahrami, H. A., Fereidouni, Z., and Bandarabadi, S. R. 2014. Assessment of soil quality indices in agricultural lands of Qazvin Province, Iran. Ecological indicators, 40: 19-26.
  35. Raiesi, F. 2017. A minimum data set and soil quality index to quantify the effect of land use conversion on soil quality and degradation in native rangelands of upland arid and semiarid regions. Ecological Indicators, 75: 307-320.
  36. Sa, J. C. D. M., and Lal, R. 2009. Stratification ratio of soil organic matter pools as an indicator of carbon sequestration in a tillage chronosequence on a Brazilian Oxisol. Soil and Tillage Research, 103(1): 46-56.
  37. Salek-Gilani, S., Raiesi, F., Tahmasebi, P., Ghorbani, N., 2013. Soil organic matter inrestored rangelands following cessation of rainfed cropping in a mountainoussemi-arid landscape. Nutr. Cycl. Agroecosyst. 96: 215–232.
  38. Samie, F., Yaghmaeian Mahabadi, N., Abrishamkesh, S., Maslahatjou, A. 2022. Impact of land use change on erodibility and soil quality indicators (case study: Sidasht, Guilan Province), Journal of Agricultural Engineering Soil Science and Agricultural Mechanization, (Scientific Journal of Agriculture), 45(1): 58-78. (in Persian with English abstract) 
  39. Santos-Francés, F., Martínez-Graña, A., Ávila-Zarza, C., Criado, M. and Sánchez-Sánchez, Y., 2021. Soil quality and evaluation of spatial variability in a semi-arid ecosystem in a region of the Southeastern Iberian Peninsula (Spain). Land, 11(1), p.5.
  40. Shah Piri, A., Kooch, Y., and Dianati Tilaki, G. A. 2021. Evaluation of soil quality indicators in degraded and converted forest habitats to rangeland in western Mazandaran. Iranian Journal of Soil and Water Research, 52(3): 857-867. (in Persian with English abstract)
  41. Sheidai Karkaj, E., A. Sepehry, H. Barani, J. Motamedi, and F. Shahbazi. 2019. Establishing a suitable soil quality index for semi-arid rangeland ecosystems in northwest of Iran. Journal of Soil Science and Plant Nutrition 19(3): 648-658.
  42. Sparks, D. L., Page, A. L., Helmke, P. A., Leoppert, R. H., Soltanpour, P. N., Tabatabai, M. A., Johnston, G. T. and Summer, M. E. 1996. Methods of Soil Analysis, Soil Science Society of American Journal. Book Series No. 5.
  43. Walkley, A., and Black, I. A. 1934. An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil science, 37(1): 29-38.
  44. Yaghmaeian Mahabadi, N., Fayyaz, H., Sabouri, A., and Shirinfekr, A. 2021. Comparison of Soil Quality Evaluation Methods and Their Relationships with Tea Yield in West Guilan Province. Iranian Journal of Soil Research34(4): 435-450. (in Persian with English abstract)
  45. Yu, P., Han, D., Liu, S., Wen, X., Huang, Y., and Jia, H. 2018. Soil quality assessment under different land uses in an alpine grassland. Catena, 171: 280-287.
  46. Zeraatpisheh, M., Bakhshandeh, E., Hosseini, M. and Alavi, S.M., 2020. Assessing the effects of deforestation and intensive agriculture on the soil quality through digital soil mapping. Geoderma, 363, p.114139.
  47. Zhang, Y., Xu, X., Li, Z., Xu, C. and Luo, W. 2021. Improvements in soil quality with vegetation succession in subtropical China karst. Science of the Total Environment, 775: 145876.
  48. Zhou, M., Y. Xiao, Y. Li, X. Zhang, G. Wang, J. Jin, G. Ding, and X. Liu. 2022. Soil quality index evaluation model in responses to six-year fertilization practices in Mollisols. Archives of Agronomy and Soil Science 68(2): 180-194.
  49. Zhou, Y., Ma, H.B., Xiea, Y.B., J., Su, T., Lia, j., and Shena, Y.B., 2020. Assessment of soil quality indexes for different land use types in typical steppe in the loess hilly area, China Ecological Indicators. 118: 106-743.