دوماه نامه

نوع مقاله : مقالات پژوهشی

نویسندگان

1 دانشگاه شیراز

2 استادیار بخش تحقیقات خاک و آب، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی فارس، سازمان تحق

3 دانشگاه تهران

4 موسسه تحقیقات خاک و آب، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران

چکیده

کیفیت خاک ابزاری کارآمد برای ارزیابی عملکردخاک و تغییرات ناشی از مدیریت بر خاک می‌باشد. برای ارزیابی کیفیت خاک و تغییرات آنها از شاخص‌هایی بیولوژیک استفاده می‌شود. این پروژه به‌منظورارزیابی برخی از ویژگی‌های بیولوژیک خاک در دشت پاسارگاد به‌وسعت حدود 1200 هکتار اجرا شد. بدین منظور پس از بررسی نقشه اولیه دشت پاسارگاد، نقاط نمونه‌برداری به‌صورت شبکه‌بندی منظم و با فاصله 500 متر تعیین گردید و تعداد 60 نمونه از عمق سطحی خاک (30-0 سانتی‌متر) جمع‌آوری شد.در بیشتر موارد ویژگی‌های مورد مطالعه دامنۀ تغییرات زیادی داشتند. بر پایۀ ضریب تغییرات، pH کمترین و تنفس ویژه بیشترین تغییرات را داشت. همبستگی خطی معنی‌داری بین ویژگی‌های خاک وجود داشت. همچنین، کریجینگ، بهترین میان‌یاب برای واکنش خاک، هدایت الکتریکی، کربن آلی، کربن توده زنده میکروبی، آنزیم اوره‌آز، تنفس ویژه و نسبت کربن توده میکروبی به کربن آلی بود. روش وزن‌دهی عکس فاصله برای آنزیم فسفاتاز قلیایی و کوکرجینگ برای تنفس پایه خاک به‌عنوان بهترین روش انتخاب گردید. مقدار واکنش خاک از شمال به جنوب افزوده شد اما مقدار هدایت الکتریکی و کربن آلی عکس مقدار واکنش خاک بود. بیشترین مقادیر تنفس میکروبی و آنزیم اوره‌آز به ترتیب در جنوب و شرق مشاهده گردیدند. مقدار آنزیم فسفاتاز قلیایی در دشت به‌صورت پراکنده بود و مساحت گسترده‌ای از دشت مقادیری بین µgPNP/g.hr 275-215 را داشت. بیشترین مقدار کربن توده زنده میکروبی و نسبت کربن توده زنده میکروبی به کربن آلی و کمترین مقدار تنفس ویژه در غرب مشاهده گردید. نتایج این تحقیق در بهبود برنامه‌ریزی‌های منطقه‌ای جهت مدیریت پایدار خاک کاربرد دارد.

کلیدواژه‌ها

عنوان مقاله [English]

Evaluation of Spatial Variability of Biological Indicators of Soil Quality in Wheat Farms of Pasargad Plain

نویسندگان [English]

  • vahid alah jahandideh mahjan abadi 1
  • alidad karami 2
  • sayed roholla mousavi 3
  • H. Asadi Rahmani 4

1

2

3

4 Tarbiyat modarres

چکیده [English]

Introduction:Soil quality as an important part from soil resource sustainability, consistently isinfluenced by human activities.Today, the presence of accurate information about variability of soil quality properties is considered more than ever to apply this information in economic modeling, environmental predictions, accurate farming and natural resources management. Soil quality is defined as: “capacity of the soil to function, within the ecosystem and land-use boundaries, to sustain biological productivity, maintain environmental quality, and promote plant and animal health”; therefore, it is one of the most important factors in developing sustainable land management and sustaining the global biosphere. The definition of soil quality encompasses physical, chemical and biological characteristics, and it is related to fertility and soil health. Many indicators can be used to describe soil quality, but it is important to take into account sensitivity, required time, and related properties, than can be explained. Properties related to organic matter content, such as microbial respiration, microbial biomass carbon (MBC) and enzymatic activity (urease and phosphatases) can be used as soil quality indicators. They provide early information about mineralization processes, nutrient availability and fertility, as well as effects resulting from changes in land use or agricultural practices (e.g. tillage or application of different types of organic matter). In this context, biological properties have been used as soil quality indicators, because of their relationship with organic matter content, terrestrial arthropofauna, lichen, microbial community (biomass or functional groups), metabolic products as ergosterol or glomalin and soil activities as microbial respiration and enzyme production. This study was carried out for evaluation the spatial variability of biological soil quality indicators in wheat farms of Pasargad plain.
Materials and Methods: After reviewing the initial map of Pasargad, a total of 60 samples were provided using a systematic grid square sampling pattern with 500×500 m over the 1200 ha area of Pasargad at surface soil depth (0-30 cm). The characteristics of soil including organic carbon, pH, EC, microbial respiration, microbial biomass carbon , soil alkaline phosphatase and urease enzymes activity, ratio of microbial biomass carbon to organic carbon (MBC/OC) andmicrobial metabolic quotient(qCO2) were measured and calculated. Results were analysed with SPSS, Excel, GS+, and ArcGIS sotwares. Summary statistics were calculated for the 60 samples including mean, maximum and minimum, coefficient of variation (CV), kurtosis and skewness. In addition, Pearson correlation coefficients were calculated for untransformed data. For evaluation of different interpolation methods of soil characteristics in Pasargad plain root mean square error (RMSE), mean bias error (MBE) and mean absolute error (MAE) were used. We also constructed maps of the spatial distributions for each individual variable using best interpolators including kriging, inverse distance weighting (IDW) and cokriging methods.
Results and Discussion; The results showed that in the most cases the studied properties had too much variation. Based on the coefficient of variation, pHand qCO2had the lowest and highest variations, respectively. There was significant linear correlation between most of soil properties. From lognormal transformation was used for normalization of EC and qCO2. Best model for single semivariogram of organic carbon, microbial respiration, urease enzyme activity, microbial biomass carbon, qCO2 and MBC/OC in the soil was spherical model, for pH in the soilwas exponential model and for EC and phosphatase enzyme activity was gaussian model. Also, the best interpolator for pH, EC, organic carbon, microbial biomass carbon, urease activity, qCO2and MBC/OC was kriging, for alkaline phosphatase activity was inverse distance weight, and for microbial respiration was cokriging method. Amount of pH increased from north to south of Pasargad plain, but amounts of EC and organic carbon were inverse of pH.The higher amounts of microbial respiration and urease activity were observed at the south and east, respectively. The amount of phosphatase activity in the soil of Pasargad plain was scattered, and wide area in the plain had the activity between 215-275 µg PNP/g.hr. The higher amount of MBC and MBC/OCand lower amount of qCO2were observed at the west.
Conclusions: The biological soil properties were sensitive and rapid indicators of effects of soil management. Generally, according to the spatial variabilitymap, the areas in the region are critical situations in terms of biological indicators of soil. So the management techniques that are applied by farmers in these areas have to be changed. The results of this study used in the improvement of regional planning for sustainable management of soil.

کلیدواژه‌ها [English]

  • Biological properties variability
  • Geostatistic
  • Soil quality
1. Acosta-Martinez, V., Klose, S., and Zobeck, T.M. 2003. Enzyme activities in semiarid soils under conservation reserve program, native rangeland, and cropland. Journal of Plant Nutrition and Soil Science, 166: 699-707.
2. Anderson, J.P.E. 1982. Soil respiration. p. 831-872. In: A.L. Page, R.H. Miller, and D.R. Keeney (eds.) Methods of Soil Analysis. Part 2. Soil Science Society of America, Madison, Wisconsin.
3. Anderson, T.H. 2003. Microbial eco-physiological indicators to assess soil quality. Agriculture, Ecosystem & Environmental, 98: 285-293.
4. Anderson, T.H., and Domsch, K.H. 1989. Ratios of microbial biomass carbon to total organic carbon in arable soils. Soil Biology and Biochemistry, 21:471-479.
5. Brejda, J.J., Moorman, T.B., Karlen, D.L., and Dao, T.H. 2000. Identification of regional soil quality foctors and indicators: I. Central and southern highy plains. Soil Science of Society American Journal, 64: 2115-2124.
6. Camberdella, C.A., Moorman, T.B., Novak, J.M., Parkin, T.B., Karlen, D.L., Turco, R.F., and Konopka, A.E. 1994. Field-scale variability of soil properties in central Iowa soils. Soil Science of Society American Journal, 58: 1501-1511.
7. Chander, K., Goya, S., and Kapoor, K. 2006. Microbial biomass dynamics during the decomposition of leaf litter of Poplar and eucalyptus in a sandy loam. Applied Soil Ecology, 35: 10-23.
8. Dixon, W.J., and Massey, F.J. 1983. Introduction to statistical analysis. McGraw Hill Pub., USA.
9. Duffera, M., White, J.G., and Weisz, R. 2007. Spatial variability of Southeastern U.S. Coastal Plain soil physical properties: Implication for site-specific management. Geoderma, 137: 327-339.
10. Garcia-Gil, J.C., Plazac Senesi, N., Brunetti, G., and polo, A. 2004. Effects of sewage sludge amendment on humic acids and microbiological properties of semiarid Mediterranean soil. Biology and Fertility of Soils, 39: 320-328.
11. Ghorbani Dashtaki, S., Homaee, M., Mahdian, M.H., and Kouchakzadeh, M. 2009. Site-dependence performance of infiltration models. Water Resources Management, 23: 1573-1650.
12. Islam, K.R., and Weil, R.R. 2000. Soil quality indicator properties in mid-Atlantic soils as influenced by conservation management. Journal of Soil and Water Conservation, 54: 69-78.
13. Jeffrey, L.S., and Jonathan, J.H. 2011. Field scale studies on the spatial variability of soil quality indicators inwashington state, USA. Applied and Environmental Soil Science, doi:10.1155/2011/198737.
14. Karami, A., and Basirat, S. 2015. Geostatistical assessment of spatial variability of some surface soil properties in arsenjan plain. Soil Research (Soil and Water Sciences). 29: 59-69. (in Persian with English abstract)
15. Khodaverdiloo, H., Homaee, M., van Genuchten, M.T., and Ghorbani Dashtaki, S. 2011. Deriving and validating pedotransfer functions for some calcareous soils. Journal of Hydrology, 399: 93–99.
16. Li, X., and Chen, Z. 2004. Soil microbial biomass C and N along a climatic transect in the Mongolian steppe. Biology and Fertility of Soils, 39:344-351.
17. McBratney, A.B., and Webster, R. 1983. Optimal interpolation and is arithmic mapping of soil properties: V. Coregionalization and multiple sampling strategies. Journal of Soil Science, 34: 137-162.
18. Mishra, U., Lal, R., Liu, D., and Van Meirvenne, M. 2010. Predicting the spatial variation of the soil organic carbon pool at a regional scale. SSSAJ, 74: 906-914.
19. Mohammadi, G. 2006. Pedometer 2 (spatial statistics). Pelk Press, Tehran, 453 p. (in Persian)
20. Monreal, C.M., and Bergstrom, D.W. 2000. Soil enzymatic factors expressing the influence of land use, tillage system and texture on soil biochemical quality. Canadian Journal of Soil Science, 80: 419-428.
21. Neal, M., Khademi, H., and Hajabbasi, A. 2004. Response of soil quality indicators and their spatial Variability to land degradation in central Iran. Applied soil ecology, 27: 221-232.
22. Oyonarte, N.A., and Mateos, L. 2002. Accounting for soil variability in the evaluation of furro irrigation. Transactions of the ASAE, 45: 85-94.
23. Renella, G., Merch, M., Land, L., and Nannaipieri, P. 2005.Microbial activity and hydrolase synthesis in long- termed-contaminated soils. Soil Biology and Biochemistry, 37: 133-139.
24. Richards, L.A. 1954. Diagnosis and improvement of saline and alkali soils. USDA Salinity Laboratory Staff, 160 p.
25. Richter, D., Hofmockel, M., Callaham, M.A., Powlson, D.S., and Smith, P. 2007. Long-term soil experiments: Keys to managing earth’s rapidly changing ecosystems. Soil Science of Society American Journal, 71: 266–279.
26. Robinson, T.P., and Metternicht, G. 2006. Testing the performance of spatial. interpolation techniques for mapping soil properties. Computers and Electronics in Agriculture, 50: 97-108.
27. Saggar, S., Hedley, C.B., and Salt, G.J. 2001. Soil microbial biomass, metabolic quotient, and carbon and nitrogen mineralisation in 25-year-old Pinus radiata agroforestry regimes. Australian Journal of Soil Research, 39: 491-504.
28. Shi, W., Dell, E., Bowman, D., and Iyyemperumal, K. 2006. Soil enzyme activities and organic matter composition in a turfgrass chromosequence. Plant and Soil, 288: 288-296.
29. Sparling, G.P. 1992. Ratio of microbial biomass carbon to soil organic carbon as a sensitive indicator of changes in soil organic matter. Australian Journal of Soil Research, 30: 195-207.
30. Tabatabai, M.A. 1982. Soil enzymes. In: A.L. Page, R.H. Miller, and D.R. Keeney (eds.) Methods of Soil Analysis. Part 2. 2nd ed. Agron. Monogr. No. 9. ASA and SSSA, Madison WI.
31. Thomas, G.W. 1996. Soil PH and soil acidity. p. 475-490. In: D.L. sparks (ed.) Methods of Soil Analysis. Part 3. No. 5. ASA and SSSA, Madison, WI.
32. Van Leeuwen, J.P., Lehtinen, T., Lair, G.J., Bloem, J., Hemerik, L., Ragnarsdottir, K.V., Gisladottir, G., Newton, J.S., and de Ruiter, P.C. 2015a. An ecosystem approach to assess soil quality in organically and conventionally managed farms in Iceland and Austria. Soil Science, 1: 83-101.
33. Van Leeuwen, J.P., Moraetis, D., Lair, G.J., Bloem, J., Nikolaidis, N.P., Hemerik, L., and de Ruiter, P.C. 2015b. Ecological soil quality affected by land use and management on semi-arid Crete. Soil Discussion, 2: 187–215.
34. Vance, E.D., Brookes, P.C., and Jenkinson, D.S. 1987. An extraction method for measuring soil microbial biomass carbon. Soil Biology and Biochemistry, 19: 703-704.
35. Veum, K.S., Goyne, K.W., Kremer, R.J., and Miles, R.J. 2013. Biological indicators of soil quality and soil organic matter characteristics in an agricultural management continuum. Biogeochemistry, doi:10.1007/s10533-013-9868-7.
36. Wakernagel, H. 2002. Multivariate Geostatistics. Springer Press, 387 p.
37. Walkley, A., and Black, I.A. 1934. An examination of degtjareff method for determining soil organic matter and a proposed modification of the chromic acid titration method. Soil Science, 37: 29-38.
38. Webster, R., and Oliver, M.A. 2001. Geostatistics for Environmental Scientists. John Wiley and Sons, Chichester, England, 271 p.
39. Wei, J.B., Xiao, D.N., Zhang, X.Y., and Li, X.Z. 2006. Spatial variability of soil organic carbon in relation to environmental factors of a typical small watershed in the black soil region, northeast China. Environmental Monitoring and Assessment, 121: 597-613.
40. Wilding, L.P. 1985. Spatial variability: Its documentation, accommodation, and implication to soil survey. p. 166-194. In: D.R. Nielsen, and J. Bouma (eds.) Soil Spatial Variability Wageningen, Netherlands.
41. Wilding, L.P., and Lin, H. 2006. Advancing the frontiers of soil science towards geoscience. Geoderma, 131: 257–274.
42. Yang, F., Zhang, G., Yin, X., and Liu, Z. 2011. Field-scale spatial variation of saline-sodic soil and its relation with environmental factors in western Songnen plain of China. International Journal of Environmental Research, 8: 374-387.
43. Yasrebi, J., Sharifi, M., Fathi, H., Karimian, N., Emadi, M., and Baghernejad, M. 2008. Spatial variability of soil fertility properties for precision agriculture in southern Iran. Journal of Applied Sciences, 8: 1612-1650.
44. Zare-Mehrjardi, M., Taghizadeh-Mehrjardi, R., and Akbarzadeh, A. 2010. Evaluation of geostatistical techniques for mapping spatial distribution of soil pH, salinity and plant cover affected by environmental factors in Southern Iran. Notulae Scientia Biologicae, 2: 92–103.
45. Zeng, D.H., Hu, Y.L., Chang, S.X., and Fan, Z.P. 2009. Land cover change effects on soil chemical and biological properties after planting Mongolian pine (Pinus sylvestris var. mongolica) in sandy lands in Keerqin, northeastern China. Plant and Soil, 317: 121-133.
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