بررسی توزیع مکانی برخی از خصوصیات فیزیکی و شیمیایی خاک و آب جنگل‌های مانگرو جزیره قشم با استفاده از زمین‌آمار

نوع مقاله: علمی- پژوهشی

نویسندگان

1 دانشجوی دکتری جنگلداری، دانشگاه تربیت مدرس

2 هیات علمی دانشگاه تربیت مدرس

چکیده

این پژوهش با هدف بررسی تغییرات مکانی برخی از خصوصیات خاک و آب جنگل‌های مانگرو جزیره قشم ازجمله درصد اشباع، هدایت الکتریکی، اسیدیته گل اشباع، مواد آلی، سدیم، منیزیم، کلسیم، پتاسیم، بافت خاک (درصد شن، سیلت، رس)، سدیم تبادلی، نسبت سدیم قابل جذب، هدایت الکتریکی و اسیدیته آب با استفاده از روش زمین‌آمار انجام شده است. واریوگرام‌های تجربی همسانگرد برای متغیرهای خصوصیات خاک و آب محاسبه شد. نتایج واریوگرافی نشان داد که از 15 متغیر موردبررسی، پتاسیم، نسبت جذب سدیم، سیلت و درصد رطوبت اشباع از ساختار مکانی مناسبی برخوردار نیست، اما سایر پارامترها ساختار مکانی متوسط تا قوی از خود نشان دادند. ارزیابی نتایج با محاسبه مجذور میانگین مربعات خطا (RMSE) و (MAE) و R نشان دهنده دقت قابل قبول تخمین‌گر کریجینگ در بررسی خصوصیات خاک و آب است. نتایج ارزیابی صحت نشان داد که می‌توان توزیع مکانی متغیرهای هدایت الکتریکی، اسیدیته گل اشباع، سدیم، درصد رس، ماسه، سدیم تبادلی، هدایت الکتریکی و اسیدیته آب را با دقت مناسبی تولید کرد. بنابراین براساس نتیجه پژوهش پیش‌رو می‌توان استفاده از روش زمین‌آمار را در مدیریت جنگل‌های مانگرو برای حفظ و توسعه این جنگل‌ها پیشنهاد داد.

کلیدواژه‌ها


عنوان مقاله [English]

Investigation of spatial distribution of soil and water properties by use of geostatistical in Mangrove forest of Qeshm Island

نویسندگان [English]

  • Shahram Jafarnia 1
  • Moslem Akbarinia 2
1 Ph.D. student, Department of Forestry, Faculty of Natural Resources & Marine Sciences, ‎University of Tarbiat Modares, Nor, I.R. Iran
2 Associate Professor, Department of Forestry, Faculty of Natural Resources & Marine Sciences, University of ‎Tarbiat Modares, Nor, I.R. Iran.‎
چکیده [English]

In this study, the main objective was to assess the spatial variation of chemical and physical soil and water properties. Using this information, the studies also aimed at establishing a pasture rehabilitation experiment in the mangroves of Qeshm Island. To this aim, soil  and water samples were analyzed for a set of factors including pH, EC, Oc, Na, Ca, Mg, K, SP, ESP, SAR, Clay, Sand, Silt, water pH and water EC. The kriging method was applied to derive the spatial variation of chemical and physical soil and water properties. Experimental variograms were calculated for soil and water properties. The variograms of EC, pH, Clay, sand, Na, Oc, SAR, water EC and water pH indicated a high amount of spatial autocorrelation fitted by spherical models. However, SP and K showed large nugget effects. In addition, diagnostic measures of RMSE, MAE and R suggested kriging to feature appropriate accuracy to estimate the spatial variability. Results of cross-validation for EC, pH, Clay, sand, Na, Oc, SAR, water EC and water pH also showed high accuracy of the estimates. Therefore, geostatistics is concluded to enable capturing the spatial variability and estimating the majority of soil and water attributes across such Mangroves.

کلیدواژه‌ها [English]

  • Spatial variation
  • Geostatistics
  • Kriging
  • Qeshm mangroves
  • soil and water properties
Akhavan, R. and Kleinn, C. 2009.  On the potential of kriging for estimation and mapping of forest plantation stock (Case study: Beneshki plantation). Iranian Journal of Forest and Poplar Research, 17(2): 303-318 (In Persian).

Anonymous, 1954. Diagnosis and improvement of saline and alkali soils. L. A. Richards, U.S. Dept. of Agriculture Handbook, 60p.

Baalousha, H. 2010. Assesssment of a groundwater quality monitorin network using vulnerability mapping and geostatistics: A case study from Heretaunga Plains, New Zealand. Agricultural Water Management, 97(2): 240-246.

Badola, R., Barthwal, S. and Hussain, S.A. 2012. Attitudes of local communities towards conservation of mangrove forests: A case study from the east coast of India. Estuarine, Coastal and Shelf Science, 96(1): 188-196.

Berger, U., Rivera-Monroy, V.H., Doyle, T.W., Dahdouh-Guebas, F., Duke, N.C., Fontalvo-Herazo, M.L., Hildenbrandt, H., Koedam, N., Mehlig, U. and Piou, C. 2008. Advances and limitations of individual-based models to analyze and predict dynamics of mangrove forests: A review. Aquatic Botany, 89(2): 260-274.

Cheng, X., An, S., Chen, J. and Li, B. 2006. Spatial relationships among species above-ground biomass, N, P in degraded grassland in ordos Plateau. Journal of Arid Environment, 3(1): 75-88.

Duffera, M., White, J.G. and Weisz, R. 2006. Spatial variability of southwestern U.S. coastal plain soil physical properties. Geoderama, 128(1): 121-133.

Ferreira, T., Vidal-Torrado, P., Otero, X. and Macías, F. 2006. Are mangrove forest substrates sediments or soils? A case study in southeastern Brazil. Catena, 70(1): 79-91.

Freeman, E.A. and Moisen, G.G. 2007. Evaluating kriging as a tool to improve moderate resolution maps of forest biomass. Environmental Monitoring and Assessment, 128: 395-410.

Habashi, H., Hosseini, S.M., Mohammadi, J. and Rahmani, R. 2007. Geostatistic applied in forest soil studying processes. Journal of Agriculture Science Natural Resourses, 14(1): 1-10 (In Persian).

Hassani pak, A. 1998. Geostatistic. Tehran University Press, 314p.

Hosseini, V., Akhavan, R. and Tahmasebi, M. 2012. Effect of Pistachio (Pistacia atlantica) canopy on the spatial distribution of soil chemical characteristics (Case study: Sarvabad, Kurdistan). Iranian Journal of Forest, 4(1):13-24 (In Persian). 

Klute, A. 1986. Methods of soil analysis part 1. Physical and mineralogical methods. 2nd Ed. Soil Science Society American journal, 1188 p. 

McLean, E. 1982. Soil pH and lime requirement Methods of soil analysis. Part. A. L. Page. Madison, is. American Society of Agronomy, Soil Science Society of America, (1): 199-224.

Mesdaghi, M. 2004. Regression methods for agriculture and natural resources researches. Imam Reza University press, Mashhad, Iran, 290p.

Miller, M.P., Singer, M.J. and Nielson, D.R. 2003. Spatial variability of wheat yield and soil properties on complex hills. Soil Science Society of American Journal, 52(1):1133-1141.

Page, A., Miller R. and Keeney M. 1992. Methods of soil analysis. Part 2: Chemical and mineralogical properties 2nd Ed. Soil Science Society of American Journal, 1159 p.

Phung, T., Dijk, H. and Visser, L. 2014. Impacts of changes in Mangrove forest management practices on forest accessibility and livelihood: A case study in mangrove-shrimp farming system in Ca Mau Province, Mekong Delta, Vietnam. Land Use Policy, 36(1): 89- 101.

Quine, T.A. and Zhang, Y. 2002. An investigation of spatial variation in soil erosion, soil properties and crop production within an agricultural field in Devon, U.K., Journal of Soil and Water Conservation, 57(2): 50-60.

Rhoades, J. 1982. Soluble salts. Methods of soil analysis. A. L. Page. Madison, Wis, American Society of Agronomy. Soil Science Society of America, 2(1): 167-179.

Safyari, Sh. 2002. Mangrove Forest in Iran. Research Institute of Forests and Rangelands Press, Tehran, Iran, 501p (In Persian).

Shahvoie, S. 2006. The nature and properties of soils, Kordestan University Press. 300 p (In Persian).

Smoak, J.M., Breithaupt, J.L., Smith,T.J. and Sanderes, C.J. 2013. Sediment accretion and organic carbon burial relative to sea-level rise and storm events in two mangrove forests in Everglades National Park. Journal of Catena, 104(1): 58-66.

Stark, C.E., Condron, L.M., Stewart, A.H., Di, J. and Callaghan, M. 2004. Small scale spatial variability of selected soil biological properties. Soil Biology and Biochemistry, 36(1):601-608.

Webster, R. 1985. Quantitative spatial of soil in the field, Advance in soil Science, New York. Springer, 3(1):1-70.

Webster, R. and Oliver, M.A. 2000. Geostatistics for environmental scientists. Wiley press, 271p.