ارزیابی اثر جایگاه شیب و تخریب جنگل بر روی شاخص کیفیت خاک

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد، گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه کردستان

2 استادیار گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه کردستان

چکیده

اثر جایگاه شیب و تخریب جنگل بر روی کیفیت خاک شناخته شده و مهم است. پایش تغییرات شاخص­های کیفیت خاک، روشی ساده و معمول جهت ارزیابی کیفیت خاک است. در این پژوهش، اثر تخریب جنگل و جایگاه شیب بر روی شاخص کیفیت خاک وزنی تجمعی و نمرو در جنگل­های مریوان در استان کردستان بررسی شد. تعداد 8 نیمرخ خاک در جایگاه­های مختلف دو شیب تپه، تحت کاربری­های جنگل و جنگل تخریب شده حفر و تشریح شدند. افزون بر این، در هر کاربری در هر موقعیت شیب، 3 نمونه خاک از عمق 20-0 سانتی­متری برداشت شد. 15 ویژگی خاک اندازه­گیری و به‌عنوان مجموعه کل داده ها استفاده شدند؛ سپس با استفاده از روش تجزیه مولفه اصلی هفت ویژگی خاک (کربن آلی، ظرفیت تبادل کاتیونی، رطوبت قابل دسترس، فسفر قابل دسترس، ازت کل، جرم مخصوص ظاهری و فرسایش پذیری خاک) به‌عنوان مجموعه حداقل داده­ها انتخاب شدند. وزن و نمره هر ویژگی به‌ترتیب با استفاده از واریانس مشترک و توابع نمره­دهی مشخص شدند و در نهایت شاخص کیفیت وزنی تجمعی خاک محاسبه شد. میانگین مقادیر شاخص­های کیفیت خاک در جنگل تخریب شده به‌طور معنی­داری، کمتر از کاربری جنگل بود؛ همچنین میانگین شاخص­های کیفیت خاک در موقعیت شانه شیب به‌طور معنی­داری کمتر از سایر موقعیت­های شیب بود. ضریب همبستگی معنی­دار قوی (98/0) بین شاخص­های کیفیت وزنی تجمعی خاک محاسبه شده با استفاده از مجموعه کل داده­ها و مجموعه حداقل داده­ها به‌دست آمد.

کلیدواژه‌ها


عنوان مقاله [English]

Assessing the effect of forest degradation and slope position on soil quality index

نویسندگان [English]

  • Serve Moradi 1
  • Kamal Nabiollahi 2
  • Syed Mohammad taher hossaini 1
1 MSc student, Soil Science and Engineering Department, Agriculture Faculty, University of Kurdistan, Iran
2 Assistant Professor, Soil Science and Engineering Department, Agriculture Faculty, University of Kurdistan, Iran
چکیده [English]

Introduction Soil quality is the capacity of soil function to sustain plant and animal productivities, to maintain or enhance water and air quality and to support human health. Slope position and deforestation are known to influence soil quality and assessing the soil quality degradation is important to soil management. Soil-quality indices are a common and easy way to quantify soil quality; they can improve understanding of soil ecosystems and allow more efficient soil management Two soil indicator selection approaches, total data sets and minimum data sets have been widely used to evaluate soil quality. The region of Marivan in Kurdistan province is one of the forested areas of Zagros which has been threatened due to population growth and increasing demand for food and, some parts are now under agriculture land use. Based on the present reports, deforestation and cultivation on the sloping areas have started almost 30 years ago. The aim of this research was to assess the effect of forest degradation and slope position on soil quality index.
Materials and Methods The study area is located in Kurdistan Province, about 10 km northeast of Marivan city, west Iran (46°24΄ 46°40΄E, 35°42΄ 35°50΄N). Two adjacent sites were selected, consisting of a natural forest and deforested cultivated land on a hill slope. Average annual precipitation and temperature are 813 mm and 13.8 °C, respectively. Soil moisture and temperature regimes are Xeric and Mesic, respectively. Forests of the study area are relative intensive and their main forest vegetation is oak. In this study, 24 soil samples (0–20 cm depth) were taken from four slope positions (shoulder, back slope, foot slope and toe slope) of forest and adjacent deforested cultivated soils. Eight profiles (on each slope positions of both land uses) were also described. Fifteen soil properties: pH, electrical conductivity, sodium adsorption ratio, organic carbon, cation exchange capacity, carbonat calcium equivalent, soil erodibility, soil porosity, mean weight diameter of aggregates, available water, soil microbial respiration, available phosphorous, available potassium, total nitrogen, bulk density, were measured for 24 soil samples (0–20 cm depth). These Fifteen soil properties were applied as the total data set. Then, seven soil properties were selected as minimum data set using principle component analysis. Weight and score of each property were found using communality and scoring function (including more is better, low is better and optimum) and finally weighted additive and nemoro soil quality indices was computed.
Results and Discussion: Seven soil properties (including soil organic carbon, cation exchange capacity, bulk density, soil erodibility, plant available water content, available potassium and total nitrogen) were selected as total data set using principle component analysis. The soils formed in low slope positions had higher depth and evolution compared to high slope positions. The results also showed land use change of forest land to cropland has led to degradation of Mollisols. The results showed that the mean values for weighted additive and nemoro soil quality indices in the deforested were significantly lower compared to forest. The mean values for weighted additive and nemoro soil quality indices in the shoulder were significantly lower compared to other slope position. significantly Strong Pearson correlation coefficients (0.98) were obtained between computed weighted additive soil quality index using total data set and a minimum data set.
Conclusion: The results showed that forest degradation in the Marivan region led to a decrease in weighted additive and nemoro soil quality indices through a significant reduction of organic carbon, microbial respiration, total nitrogen, CEC, soil porosity and available moisture and significant increasing of bulk density, pH, SAR and soil erodibility. Forest degradation and land use change also due to cultivation led to decrease in the organic carbon content and soil structure degradation of Mollic horizon. Therefore, Mollic horizon has converted to Ochric horizon and Entisols and Inceptisols have formed in cropland land use. Moreover, the results showed different slope positions affect weighted additive soil quality index and mark significant difference. The results also showed that using the weighted additive soil quality index and minimum data set method can adequately represent total data set (R2=0.98) and thus reduce the time and cost involved in evaluating soil quality. Slope positions and where forest was converted to agriculture were characterized by low values of weighted additive soil quality index, suggesting a recovery of soil quality through changing to sustainable practices.

کلیدواژه‌ها [English]

  • Soil quality
  • minimum dataset
  • principle component analysis
  • hill slope
  1. Anderson, E. and John, P. 1982. Soil respiration. Methods of Soil Analysis Part2. Amer. Soc. of Agron, Madison USA. pp: 831-870
  2. Andrews, S. S., Karlen, D. L., Cambardella, C. A. 2004. The soil management assessment framework: a quantitative soil quality evaluation method. Soil Science Society of America Journal, 68: 1945–1962.
  3. Andrews, S. S., Flora, C. B., Mitchell, J. P. Karlen, D. L. 2003. Grower’s perceptions andacceptance of soil quality indices. Geoderma, 114: 187–213.
  4. Andrews, S. S., Mitchell, J. P., Mancinelli, R., Karlen, K. L., Hartz, T. K., Horwath, W. R., Pettygrove, G. S., Scow, K. M. Munk, D. S. 2002. On-farm assessment of soil quality in California's central valley. Agronomy Journal, 94: 12–23.
  5. Aparicio, V. and Costa, J. L. 2007. Soil quality indicators under continuouscropping systems in the Argentinean pampas. Soil and Tillage Research, 96: 155-165.
  6. Askari, M. S., O Rourke, S. M. Holden, M. M. 2015. Evaluation of soil quality for agricultural production using visible–near-infrared spectroscopy. Geoderma, 243–244, 80-91.
  7. Assefa, D., Rewald, B., Sanden, H., Rosinger, C., Abiyu, A., Yitaferu, B. L. Godbold, D. 2017. Deforestation and land use strongly effect soil organic carbon and nitrogen stock in Northwest Ethiopia. Catena, 153: 89–99.
  8. Biswas, S., Hazra, G. C., Purakayastha, T. J., Saha, N., Mitran, T., Roy, S. S., Basak, N. Mandal B. 2017. Establishment of critical limits of indicators and indices of soil quality in rice-rice cropping systems under different soil orders. Geoderma, 292: 34-48.
  9. Blake, G. R. and Hartage, K. H. 1986. Bulk density, P 363-382. In: Klute, A. (Ed.), Methods of Soil Analysis. Part1: physical and Mineralogical Methods, 2nd ed. Agronomy Monograph. 9: ASA, Madison, WI.
  10. Bower, C. A., Reitemeier, R. F. Fireman, M. 1952. Exchangeable cation analysis of saline and alkali soils. Soil Science, 73: 251-262.
  11. Cambardella, C. A., Moorman, T. B., Andrews, S. S. Karlen, D. L.  2004. Watershed-scale assessment of soil quality in the loess hills of southwest Iowa. Soil and Tillage Research, 78:237–247.
  12. Chen, L. F., Hu, Z., B., Zhu, X., Du, J., Yang, J. J., Li, J. He, J. 2017. Impacts of afforestation on plant diversity, soil properties, and soil organic carbon storage in a semi-arid grassland of northwestern China. Catena, 147: 300–307.
  13. Das B, Chakraborty D, Singh VK, Ahmed M, Singh AK, Barman A. 2016. Evaluating Fertilization Effects on Soil Physical Properties Using a Soil Quality Index in an Intensive Rice-Wheat Cropping System. Pedosphere, 26 (6): 887–894.
  14. Deumlich, D., Ellerbrock, R. H. Frielinghaus, M. O. 2016. Estimating carbon stocks in young moraine soils affected by erosion. Catena, 162: 51–60.
  15. Eckert, S. and Engesser, M. 2013. Assessing vegetation cover and biomass in restored erosion areas in Iceland using SPOT satellite data. Applied Geography, 40: 179–190.
  16. Fazlollahi Mohammadi, M., Jalali, S. G., Kooch, Y. Said-Pullicino, D. 2017. The effect of landform on soil microbial activity and biomass in a Hyrcanian oriental beech stand. Catena, 149: 309-317.
  17. Gee, G. W. and Bauder, J.W. 1986. Particle size analysis, P 383-411. In: A. Klute. (ed). Methods of Soil Analysis. Part 1: Physical and mineralogical methods, second edition. American Society of Agronomy,Inc., Soil Science Society of America, Inc., Madison, WI.
  18. Gorji, M., Kakeh, j., and AliMohammadi, A. 2018. Quanitative soil quality assessment in different land uses at some parts of south eastern of Qazvin. Iranian Soil and Water Research. 48: 941-950. (In Persian)
  19. Guo, L., Sun, Z. H., Ouyang, Z. H., Han, D. Li, F. 2017. A comparison of soil quality evaluation methods for Fluvisol along the lower Yellow River. Catena, 152: 135–143.
  20. Hall, G. F.1983. In: L.P. Wilding, N.E. Smeck, and G.F. Hall (Eds.). Pedogenesis and Soil Taxonomy. I. Concepts and Interactions. Elsevier, Amesterdam. pp: 117–140.
  21. Henok, K., Dondeyne, S., Poesen, J., Frankl, A. Nyssen, J. 2017. Transition from Forestbased to Cereal-based Agricultural Systems: A Review of the Drivers of Land use Change and Degradation in Southwest Ethiopia. Land Degradation and Development, 28: 431-449.
  22. Hole, F. D., and Campbell, J. B. 1985. Soil landscape analysis. Rowman and Allenheld, Totowa, NJ.
  23. Hunckler, R. V. and Schaetzl, R. J. 1997. Spodosol development as affected by geomorphic aspect, Baraga County, Michigan. Soil Science Society of America Journal, 61: 1105–1115.
  24. Hussain, I., Olson, K. R., Wanter, M. W. Karlen, D. L. 1999. Adaptation of soil quality indices and application to three tillage systems in southern Ilinois. Soil and Tillage Research, 50: 237-249.
  25. Jayachandran, K., Gamare, J.S., Nair, P.R., Xavier, M. Aggarwal, S.K. 2012. A novel biamperometric methodology for thorium determination by EDTA complexometric titration. Radiochimica Acta, 100: 311–314.
  26. Johnson RA, Wichern DW. 1992. Applied Multivariate Statistical Analysis. Prentice-Hall, Englewood Cliffs, NJ.
  27. Jones, B. J. 2001. Laboratory guide for conducting soil tests and plant analysis. Boca Raton, London, New York and Washington, D.C. CRC Press.
  28. Karlen, D.L., Gardner, J.C., and Rosek, M.J. 1998. A soil quality framework for evaluating the impact of  CRP. Journal of Production Agriculture, 11: 56-60.
  29. Karlen, D. L. and Scott, D. E. 1994. A framework for evaluating physical and chemical indicators of soil quality. In: Doran JW, Coleman DC, Bezdicek DF, Stewart BA. (Eds.), Defining Soil Quality for a Sustainable Environment. ASA and SSSA, Madison, WI, USA. pp: 53–72.
  30. Kassa, H., Dondeyne, S., Poesen, J., Frankl, A. Nyssen, J. 2017. Impact of deforestation on soil fertility, soil carbon and nitrogen stocks: the case of the Gacheb catchment in the White Nile Basin, Ethiopia. Agriculture Ecosystems and Environment, 247: 273-282.
  31. Kemper, W.D., and Rosenau, R. C. 1986. Aggregate stability and size distribution. In: Klute, A. (Ed.), Methods of Soil Analysis. Part I: Physical Analysis. SSSA,Madison, WI. pp: 425–442.
  32. Khaledian, Y., Kiani, F., Ebrahimi, S., and Movahedi Naeini, A. 2011. Impact of forest degradation, changing land use and building villas on some indicators of soil quality in the watershed, Golestan province. Journal of Soil and Water Conservation, 18: 167-184. (In Persian)
  33. Khormali, F., Ajami, M., Ayoubi, S., Srinivasarao, Ch. Wani, S.P. 2009. Role of deforestation and hill slope position on soil quality attributes of loess-derived soils in Golestan province, Iran. Journal of Agriculture Ecosystems and Environment, 134: 178–189.
  34. Lal, R., 1994. Methods and Guidelines for Assessing Sustainable Use of Soil and Water Resources in the Tropics. The Ohio State University.
  35. Li, Zh., Liu, Ch., Dong, Y., Chang, X., Nie, X., Liu, L., Xiao, H., Lu, Y. Zenga, G. 2017. Response of soil organic carbon and nitrogen stocks to soil erosion and land use types in the Loess hilly–gully region of China. Soil and Tillage Research, 166:1-9.
  36. Lin, Y., Deng, H., Du, K., Li, j., Lin, H., Chen, C., Fisher, L. Wu, C. 2017. Soil quality assessment in different climate zones of China’s Wenchuan earthquake affected region. Soil and Tillage Research,165: 315-324.
  37. Liu, J., Wu, L., Chen, D., Yu, Zh. Wei, Ch. 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.
  38. McLean, E.O. 1982. Soil pH and lime requirement, P 199–224 .9. In: Page, A.L., Miller, R.H., and Keeney, D.R. (Eds.), Methods of Soil Analysis, Part 2 Chemical and Microbiological Properties, 2nd ed. ASA-SSSA, Madison, WI.
  39. Moorman, T. B., Cambardella, C. A., James, D. E., Karlen, D. L. Kramer, L. A. 2004. Quantification of tillage and landscape effects on soil carbon in small Iowa watersheds. Soil and Tillage Research,78: 225–236.
  40. Nakajima, T., Lal, R. Jiang, S. 2015. Soil quality index of a crosby silt loam in central Ohio. Soil and Tillage Research,146: 323-328.
  41. Nelson, D.W., and Sommers, L.E. 1982. Total carbon, organic carbon, and organic matter. P 539-594 In: Page, A.L., R.H., D.R., Keeney (Eds.), Methods of Soil Analysis, Part 2-Chemical and Microbiological Properties. ASA-SSSA, Madison, WI.
  42. Nosrati, K. 2017. Ascribing soil erosion of hillslope components to river sediment yield. Journal of Environmental Management, 194: 63-72.
  43. Olsen, S. R. and Sommers, L. 1982. phosohorus, P 403-430. In: AL. Page: Methods of soil analysis, Agron. No. 9, Part2: Chemical and microbiological properties, (ed.), Am. Soc.Agron., Madison, WI, USA.
  44. Ozgoz, E., Gunal, H., Acir, N., Gokmen, F., Birol, M., Budak, M. 2013. Soil quality and spatial varability assessment of land use effects in a Typic Haplustoll. Land Degradation and Development, 24: 277–286.
  45. Raiesi, F, and Kabiri, V. 2016. Identification of soil quality indicators for assessing the effect of different tillage practices through a soil quality index in a semi-arid environment. Ecological Indicators, 71:198–207.
  46. Rahmanipour, F., Marzaioli, R., Hossein Ali, B., Fereidouni, Z. Sima, R. B. 2014. Assessment of soil quality indices in agricultural lands of Qazvin Province, Iran. Ecological Indicators, 40:19–26.
  47. Rhoades, J. D. 1982. Soluble salts. In: Page, A.L. (Ed.), Methods of Soil Analysis, Part II, 2nd ed., ASA, Monograph No. 9, Madison, WI. pp: 167–179.
  48. Richards, L. A. 1954. Diagnosis and improvement of saline and alkali soils. Washington: United States Salinity Laboratory, 160 p.
  49. Ruhe, R. V. 1960. Elements of the soil landscape. Transactions of the Seventh International Congress of Soil Science, Madison 4, pp: 165–170.
  50. Sanchez-Navarro, A., Gil-Vazquez, J. M., Delgado-Iniesta, M. J, Marin-Sanleandro, P., Blanco-Bernardeau, A. Ortiz-Silla, R. 2015. Establishing an index and identification of limiting parameters for characterizing soil quality in Mediterranean ecosystems. Catena, 131: 35-45.
  51. Sewerniak, P., Jankowski, M., and Dąbrowski, M. 2017. Effect of topography and deforestation on regular variation of soils on inland dunes in the Torun Basin (N Poland). Catena, 149: 318–330.
  52. Shirazi, M.A. Boersma, L. 1984. A unifying quantitative analysis of soil texture. Soil Science Society of America Journal, 48: 142-147. (In Persian)
  53. Soil Survey Staff, 2014. Keys to Soil Taxonomy, 12th edn. United States Department of Agriculture, Washington.
  54. Sohng J, Singhakumara BMP, Ashton MS. 2017. Effects on soil chemistry of tropical deforestation for agriculture and subsequent reforestation with special reference to changes in carbon and nitrogen. Forest Ecology and Management, 389: 331–340.
  55. Sparks, D. L., Page, A. L., Helmke, P. A., Leoppert, R. H., Soltanpour, P. N., Tabatabai, M. A., Johnston, G. T. Summer, M. E. 1996. Methods of Soil Analysis. Soil Science Society of American Journal. Book Series No. 5. ASA and SSSA, Madison, Wisconsin, WI, USA.
  56. Tesfaye, M. A., Bravo, F., Ruiz-Peinado, R., Pando, V. Bravo-Oviedo, A. 2016. Impact of changes in land use, species and elevation on soil organic carbon and total nitrogen in Ethiopian central highlands. Geoderma, 261: 70-79.
  57. Vasu, D., Singh, S. K., Ray, S. K., Duraisami, V. P., Tiwary, P., Chandran, P., Nimkar, A. M. Anantwar, S. G. 2016. Soil quality index (SQI) as a tool to evaluate crop productivity in semi-arid Deccan plateau, India. Geoderma, 282: 70-79.
  58. Wang, Zh., Wang, R., Sun, Q., Du, L., Zhao, M. Hu, Y. 2017. Soil CO2 emissions from different slope gradients and positions in thesemiarid Loess Plateau of China. Ecological Indicators, 105: 231-239.
  59. Weeb, A. A. Dowling, A. J. 2005. Characterization of basaltic clay soils (Vertisols) from the Oxford land system in central Queensland. Australian Journal of Soil Research, 28: 841-856.
  60.  Wei, S., Zhang, X., Mclaughlin, N. B., Liang, A., Jia, S. Chen, X. 2014. Effectof soil temperature and soil moisture on CO2 flux from eroded landscapepositions on black soil in Northeast China. Soil and Tillage Research, 144: 119-125.
  61. Wischmeier, W. H. Smith, D.D. 1978. Predicting rainfall erosion losses: a guide to conservation planning. In Agriculture Handbook 537, USA. Department of Agriculture, Washington, DC 58p.
  62. Yu, P., Liu, Sh., Zhang, L., Li, Q. Zhou, D. 2018. Selecting the minimum data set and quantitative soil quality indexing of alkaline soils under different land uses in northeastern China. Science Total Environment, 616-617: 564-571.
  63. Zhu, H., Wu, J., Guo, Sh., Huang, D., Zhu, Q., Ge, T. Lei, T. 2014. Land use and topographic position control soil organic C and N accumulation in eroded hilly watershed of the Loess Plateau. Catena, 120: 64-72.